U.S. patent application number 15/410091 was filed with the patent office on 2018-01-04 for genetic markers predictive of response to glatiramer acetate.
This patent application is currently assigned to Teva Pharmaceutical Industries, Ltd.. The applicant listed for this patent is Iris GROSSMAN, Liat HAYARDENY, Michael HAYDEN, David LADKANI, Colin James Douglas ROSS, Amir TCHELET. Invention is credited to Iris GROSSMAN, Liat HAYARDENY, Michael HAYDEN, David LADKANI, Colin James Douglas ROSS, Amir TCHELET.
Application Number | 20180002753 15/410091 |
Document ID | / |
Family ID | 52826364 |
Filed Date | 2018-01-04 |
United States Patent
Application |
20180002753 |
Kind Code |
A1 |
TCHELET; Amir ; et
al. |
January 4, 2018 |
GENETIC MARKERS PREDICTIVE OF RESPONSE TO GLATIRAMER ACETATE
Abstract
The present invention provides a method for treating a human
subject afflicted with multiple sclerosis or a single clinical
attack consistent with multiple sclerosis with a pharmaceutical
composition comprising glatiramer acetate and a pharmaceutically
acceptable carrier, comprising the steps of: (i) determining a
genotype of the subject at a location corresponding to the location
of one or more single nucleotide polymorphisms (SNPs) selected from
the group consisting of: Group 1, (ii) identifying the subject as a
predicted responder to glatiramer acetate if the genotype of the
subject contains one or more A alleles at the location of Group 2,
one or more C alleles at the location of Group 3, one or more G
alleles at the location of Group 4, or one or more T alleles at the
location of kgp18432055, kgp279772, kgp3991733 or kgp7242489; and
(iii) administering the pharmaceutical composition comprising
glatiramer acetate and a pharmaceutically acceptable carrier to the
subject only if the subject is identified as a predicted responder
to glatiramer acetate.
Inventors: |
TCHELET; Amir;
(Hod-Hasharon, IL) ; HAYDEN; Michael;
(Petach-Tikva, IL) ; HAYARDENY; Liat; (Tel Aviv,
IL) ; ROSS; Colin James Douglas; (Burnaby, CA)
; GROSSMAN; Iris; (Yakir, IL) ; LADKANI;
David; (Jerusalem, IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
TCHELET; Amir
HAYDEN; Michael
HAYARDENY; Liat
ROSS; Colin James Douglas
GROSSMAN; Iris
LADKANI; David |
Hod-Hasharon
Petach-Tikva
Tel Aviv
Burnaby
Yakir
Jerusalem |
|
IL
IL
IL
CA
IL
IL |
|
|
Assignee: |
Teva Pharmaceutical Industries,
Ltd.
Petach-Tikva
IL
|
Family ID: |
52826364 |
Appl. No.: |
15/410091 |
Filed: |
January 19, 2017 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
14520280 |
Oct 21, 2014 |
9702007 |
|
|
15410091 |
|
|
|
|
62048641 |
Sep 10, 2014 |
|
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|
62048127 |
Sep 9, 2014 |
|
|
|
61893807 |
Oct 21, 2013 |
|
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
A61K 38/02 20130101;
C12Q 1/6883 20130101; C12Q 2600/106 20130101; A61P 25/00 20180101;
A61K 38/16 20130101; C12Q 2600/156 20130101 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; A61K 38/16 20060101 A61K038/16 |
Claims
1-96. (canceled)
97. A method for treating a human subject afflicted with multiple
sclerosis or a single clinical attack consistent with multiple
sclerosis with a pharmaceutical composition comprising glatiramer
acetate and a pharmaceutically acceptable carrier, comprising the
steps of: (i) determining the genotype of the subject at a single
nucleotide polymorphism (SNP) kgp7747883; (ii) identifying the
subject as a predicted responder to glatiramer acetate if the
genotype of the subject contains one or more G alleles at the
location of kgp7747883; and (iii) administering the pharmaceutical
composition comprising glatiramer acetate and a pharmaceutically
acceptable carrier to the subject only if the subject is identified
as a predicted responder to glatiramer acetate.
98. The method of claim 97, wherein administering the
pharmaceutical composition comprising glatiramer acetate and a
pharmaceutically acceptable carrier comprises administering to the
human subject three subcutaneous injections of the pharmaceutical
composition over a period of seven days with at least one day
between every subcutaneous injection.
99. The method of claim 97, wherein the pharmaceutical composition
is a unit dose of a 1 ml aqueous solution comprising 40 mg of
glatiramer acetate; or a unit dose of a 1 ml aqueous solution
comprising 20 mg of glatiramer acetate.
100. The method of claim 97, wherein the human subject is a naive
patient, has been previously administered glatiramer acetate, or
has been previously administered a multiple sclerosis drug other
than glatiramer acetate.
101. The method of claim 97, which comprises determining the
genotype of the subject at 4 SNPs selected from the group
consisting of kgp24415534, kgp6214351, kgp6599438, kgp7747883,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408,
rs3135391, and rs759458.
102. The method of claim 97, further comprising determining the
genotype of the subject at SNP kgp6214351, and identifying the
subject as a predicted responder to glatiramer acetate if the
genotype of the subject contains one or more A alleles at the
location of kgp6214351.
103. The method of claim 102, further comprising determining the
genotype of the subject at SNP kgp24415534, and identifying the
subject as a predicted responder to glatiramer acetate if the
genotype of the subject contains one or more G alleles at the
location of kgp24415534.
104. The method of claim 103, further comprising determining the
genotype of the subject at SNP kgp8817856, and identifying the
subject as a predicted responder to glatiramer acetate if the
genotype of the subject contains one or more G alleles at the
location of kgp8817856.
105. The method of claim 97, which comprises determining the
genotype of the subject at SNPs kgp6214351, kgp8817856, kgp7747883
and kgp24415534.
106. The method of claim 105, wherein the patient is identified as
a responder if the genotype of the subject contains one or more G
alleles at the locations of kgp7747883, kgp24415534, and kgp8817856
and one or more A alleles at the location of kgp6214351.
107. A method of identifying a human subject afflicted with
multiple sclerosis or a single clinical attack consistent with
multiple sclerosis as a predicted responder or as a predicted
non-responder to glatiramer acetate, the method comprising the
steps of: (i) determining using a probe or primer the genotype of
the subject at single nucleotide polymorphism (SNP) kgp7747883 and
(ii) identifying the subject as a predicted responder to glatiramer
acetate if the genotype of the subject contains one or more G
alleles at the location of kgp7747883; or identifying the human
subject as a predicted non-responder to glatiramer acetate if the
genotype of the subject contains no G alleles at the location of
kgp7747883, thereby identifying a human subject afflicted with
multiple sclerosis or a single clinical attack consistent with
multiple sclerosis as a predicted responder or as a predicted
non-responder to glatiramer acetate.
108. The method of claim 107, which comprises determining the
genotype of the subject at 4 SNPs selected from the group
consisting of kgp24415534, kgp6214351, kgp6599438, kgp7747883,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408,
rs3135391, and rs759458.
109. The method of claim 108, further comprising determining using
a probe or primer the genotype of the subject at SNP kgp6214351,
and identifying the subject as a predicted responder to glatiramer
acetate if the genotype of the subject contains one or more A
alleles at the location of kgp6214351 or identifying the subject as
a predicted non-responder to glatiramer acetate if the genotype of
the subject contains no A alleles at the location of
kgp6214351.
110. The method of claim 109, further comprising determining using
a probe or primer the genotype of the subject at SNP kgp24415534,
and identifying the subject as a predicted responder to glatiramer
acetate if the genotype of the subject contains one or more G
alleles at the location of kgp24415534 or identifying the subject
as a predicted non-responder to glatiramer acetate if the genotype
of the subject contains no G alleles at the location of
kgp24415534.
111. The method of claim 110, further comprising determining using
a probe or primer the genotype of the subject at SNP kgp8817856,
and identifying the subject as a predicted responder to glatiramer
acetate if the genotype of the subject contains one or more G
alleles at the location of kgp8817856 or identifying the subject as
a predicted non-responder to glatiramer acetate if the genotype of
the subject contains no G alleles at the location of
kgp8817856.
112. The method of claim 107, which comprises determining using a
probe or primer the genotype of the subject at SNPs kgp6214351,
kgp8817856, kgp7747883 and kgp24415534.
113. The method of claim 112, wherein the patient is identified as
a responder if the genotype of the subject contains one or more G
alleles at the locations of kgp7747883, kgp24415534, and kgp8817856
and one or more A alleles at the location of kgp6214351, or wherein
the subject is identified as a non-responder if the genotype of the
subject contains no G alleles at the location of kgp7747883, no G
alleles at the location of kgp24415534, no G alleles at the
location of kgp8817856, or no A alleles at the location of
kgp6214351.
114. The method of claim 97, (a) wherein the genotype is determined
from a nucleic acid-containing sample that has been obtained from
the subject; (b) wherein determining the genotype comprises using a
method selected from the group consisting of restriction fragment
length polymorphism (RFLP) analysis, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), denaturing high performance liquid chromatography
(DHPLC), Polymerase Chain Reaction (PCR) and an array, or a
combination thereof; (c) wherein the genotype is determined using
at least one pair of PCR primers and at least one probe; (d)
wherein determining the genotype comprises using an array, wherein
the array is selected from the group consisting of a gene chip, and
a TaqMan Open Array, wherein if the array is a gene chip, then the
gene chip is selected from the group consisting of a DNA array, a
DNA microarray, a DNA chip, and a whole genome genotyping array;
(e) wherein the genotype of the subject at the location
corresponding to the location of said SNP is determined indirectly
by determining the genotype of the subject at a location
corresponding to the location of at least one SNP that is in
linkage disequilibrium with said SNP; (f) wherein the genotype of
the subject at the location corresponding to the location of said
SNP is determined by indirect genotyping, and the indirect
genotyping allows identification of the genotype of the subject at
the location corresponding to the location of said SNP with a
probability of at least 85%, at least 90%, or at least 99%; (g)
further comprising determining the log number of relapses in the
last two years for the human subject; (h) further comprising
determining the baseline Expanded Disability Status Scale (EDSS)
score for the human subject; or (i) wherein determining the
genotype of the subject at the location corresponding to the
location of said SNP comprises: obtaining DNA from a sample that
has been obtained from the subject; optionally amplifying the DNA;
and subjecting the DNA or the amplified DNA to a method selected
from the group consisting of restriction fragment length
polymorphism (RFLP) analysis, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), denaturing high performance liquid chromatography
(DHPLC), Polymerase Chain Reaction (PCR) and an array, or a
combination thereof, for determining the identity the one or more
SNPs, wherein i) the array comprises a plurality of probes suitable
for determining the identity of the one or more SNPs; or ii) the
array is a gene chip, and the gene chip is a whole genome
genotyping array.
115. The method of claim 97, wherein (a) step (i) further comprises
determining a genotype of the subject at one or more single
nucleotide polymorphism (SNP): kgp6214351, kgp24415534,
kgp10090631, kgp1009249, kgp10152733, kgp10224254, kgp10305127,
kgp10351364, kgp10372946, kgp10404633, kgp10412303, kgp10523170,
kgp1054273, kgp10558725, kgp10564659, kgp10591989, kgp10594414,
kgp10619195, kgp10620244, kgp10632945, kgp10633631, kgp10679353,
kgp10788130, kgp10826273, kgp10910719, kgp10922969, kgp10948564,
kgp10967046, kgp10974833, kgp1098237, kgp11002881, kgp11010680,
kgp11077373, kgp11141512, kgp11206453, kgp11210903, kgp1124492,
kgp11281589, kgp11285862, kgp11328629, kgp11356379, kgp11407560,
kgp11453406, kgp11467007, kgp11514107, kgp11543962, kgp11580695,
kgp11627530, kgp11633966, kgp11686146, kgp11702474, kgp11711524,
kgp11768533, kgp11804835, kgp11843177, kgp12008955, kgp12083934,
kgp12182745, kgp12230354, kgp1224440, kgp12371757, kgp124162,
kgp12426624, kgp12557319, kgp1285441, kgp13161760, kgp1355977,
kgp1371881, kgp15390522, kgp1683448, kgp1688752, kgp1699628,
kgp1753445, kgp1779254, kgp1786079, kgp18379774, kgp18432055,
kgp18525257, kgp1912531, kgp19568724, kgp20163979, kgp2023214,
kgp2045074, kgp20478926, kgp2092817, kgp21171930, kgp2245775,
kgp2262166, kgp22778566, kgp22793211, kgp22811918, kgp22823022,
kgp2282938, kgp2299675, kgp23298674, kgp2356388, kgp23672937,
kgp23737989, kgp2388352, kgp2391411, kgp24131116, kgp2446153,
kgp2451249, kgp2465184, kgp24729706, kgp24753470, kgp25191871,
kgp25216186, kgp25543811, kgp25921291, kgp25952891, kgp26026546,
kgp26271158, kgp2638591, kgp26528455, kgp26533576, kgp2688306,
kgp26995430, kgp270001, kgp2709692, kgp2715873, kgp27500525,
kgp27571222, kgp27640141, kgp2788291, kgp279772, kgp28532436,
kgp28586329, kgp28687699, kgp28817122, kgp2923815, kgp29367521,
kgp293787, kgp2958113, kgp2959751, kgp297178, kgp29794723,
kgp30282494, kgp3048169, kgp304921, kgp3182607, kgp3202939,
kgp3205849, kgp3218351, kgp3267884, kgp3276689, kgp337461,
kgp3418770, kgp3450875, kgp345301, kgp3477351, kgp3496814,
kgp355027, kgp355723, kgp3593828, kgp3598409, kgp3651767,
kgp3669685, kgp3730395, kgp3812034, kgp3854180, kgp3933330,
kgp3951463, kgp3984567, kgp3991733, kgp4011779, kgp4056892,
kgp4096263, kgp4127859, kgp4155998, kgp4162414, kgp4223880,
kgp4346717, kgp4370912, kgp4418535, kgp4420791, kgp4479467,
kgp4524468, kgp4543470, kgp4559907, kgp4573213, kgp4634875,
kgp4705854, kgp4734301, kgp4755147, kgp4812831, kgp4842590,
kgp485316, kgp487328, kgp4898179, kgp5002011, kgp5014707,
kgp5017029, kgp5053636, kgp5068397, kgp512180, kgp5144181,
kgp5159037, kgp5216209, kgp5292386, kgp5334779, kgp5388938,
kgp5409955, kgp5440506, kgp5441587, kgp5483926, kgp55646,
kgp5564995, kgp5579170, kgp5680955, kgp5869992, kgp5908616,
kgp6023196, kgp6032617, kgp6038357, kgp6076976, kgp6091119,
kgp6127371, kgp61811, kgp6190988, kgp6228750, kgp6236949,
kgp6469620, kgp6505544, kgp6507761, kgp652534, kgp6539666,
kgp6567154, kgp6599438, kgp6603796, kgp6666134, kgp6700691,
kgp6737096, kgp6768546, kgp6772915, kgp6835138, kgp6959492,
kgp6996560, kgp7059449, kgp7063887, kgp7077322, kgp7092772,
kgp7117398, kgp7121374, kgp7178233, kgp7181058, kgp7186699,
kgp7189498, kgp7242489, kgp7331172, kgp7416024, kgp7481870,
kgp7506434, kgp7521990, kgp759150, kgp767200, kgp7714238,
kgp7730397, kgp7792268, kgp7802182, kgp7804623, kgp7924485,
kgp8030775, kgp8036704, kgp8046214, kgp8106690, kgp8107491,
kgp8110667, kgp8169636, kgp8174785, kgp8178358, kgp8183049,
kgp8192546, kgp8200264, kgp8303520, kgp8335515, kgp8372910,
kgp841428, kgp8437961, kgp8440036, kgp85534, kgp8599417,
kgp8602316, kgp8615910, kgp8767692, kgp8777935, kgp8793915,
kgp8796185, kgp8869954, kgp8990121, kgp9018750, kgp9071686,
kgp9078300, kgp9320791, kgp9354462, kgp9354820, kgp9368119,
kgp9410843, kgp9421884, kgp9450430, kgp9530088, kgp9551947,
kgp9601362, kgp9627338, kgp9627406, kgp9669946, kgp9699754,
kgp971582, kgp97310, kgp974569, kgp9795732, kgp9806386, kgp9854133,
kgp9884626, rs10049206, rs10124492, rs10125298, rs10162089,
rs10201643, rs10203396, rs10251797, rs10278591, rs10489312,
rs10492882, rs10498793, rs10501082, rs10510774, rs10512340,
rs1079303, rs10815160, rs10816302, rs10841322, rs10841337,
rs10954782, rs11002051, rs11022778, rs11029892, rs11029907,
rs11029928, rs11083404, rs11085044, rs11136970, rs11147439,
rs11192461, rs11192469, rs11559024, rs1157449, rs11648129,
rs11691553, rs12013377, rs12494712, rs12943140, rs13002663,
rs13394010, rs13415334, rs13419758, rs1380706, rs1387768,
rs1410779, rs1478682, rs1508102, rs1532365, rs1544352, rs1545223,
rs1579771, rs1604169, rs1621509, rs1644418, rs16886004, rs16895510,
rs16901784, rs16927077, rs16930057, rs17029538, rs17224858,
rs17238927, rs17329014, rs17400875, rs17449018, rs17577980,
rs17638791, rs1858973, rs1886214, rs1894406, rs1894407, rs1894408,
rs196295, rs196341, rs196343, rs197523, rs1979992, rs1979993,
rs2043136, rs2058742, rs2071469, rs2071470, rs2071472, rs2074037,
rs2136408, rs2139612, rs2175121, rs2241883, rs2309760, rs2325911,
rs241435, rs241440, rs241442, rs241443, rs241444, rs241445,
rs241446, rs241447, rs241449, rs241451, rs241452, rs241453,
rs241454, rs241456, rs2453478, rs2598360, rs2621321, rs2621323,
rs2660214, rs2816838, rs2824070, rs2839117, rs2845371, rs2857101,
rs2857103, rs2857104, rs2926455, rs2934491, rs3135388, rs3218328,
rs343087, rs343092, rs3767955, rs3792135, rs3799383, rs3803277,
rs3815822, rs3818675, rs3829539, rs3885907, rs3899755, rs4075692,
rs4143493, rs419132, rs423239, rs4254166, rs4356336, rs4360791,
rs4449139, rs4584668, rs4669694, rs4709792, rs4738738, rs4769060,
rs4780822, rs4782279, rs4822644, rs484482, rs4894701, rs5024722,
rs502530, rs543122, rs6032205, rs6032209, rs6110157, rs623011,
rs6497396, rs6535882, rs6687976, rs6718758, rs6835202, rs6840089,
rs6845927, rs6895094, rs6899068, rs7020402, rs7024953, rs7028906,
rs7029123, rs7062312, rs714342, rs7187976, rs7191155, rs720176,
rs7217872, rs7228827, rs7348267, rs7496451, rs7524868, rs7563131,
rs7579987, rs759458, rs7666442, rs7670525, rs7672014, rs7677801,
rs7725112, rs7844274, rs7850, rs7860748, rs7862565, rs7864679,
rs7928078, rs7948420, rs8035826, rs8050872, rs8053136, rs8055485,
rs823829, rs858341, rs9315047, rs931570, rs9346979, rs9376361,
rs9393727, rs9501224, rs9508832, rs950928, rs9579566, rs9597498,
rs9670531, rs9671124, rs9671182, rs9817308, rs9834010, rs9876830,
rs9913349, rs9931167 or rs9931211, and wherein step (ii) further
comprises identifying the subject as a predicted responder to
glatiramer acetate if the genotype of the subject contains one or
more A alleles at the location of kgp6214351, kgp10152733,
kgp10224254, kgp10305127, kgp10351364, kgp10372946, kgp10404633,
kgp10564659, kgp10591989, kgp10594414, kgp10619195, kgp10620244,
kgp10633631, kgp10974833, kgp11002881, kgp11285862, kgp11328629,
kgp11407560, kgp11514107, kgp11627530, kgp11702474, kgp11711524,
kgp11768533, kgp11804835, kgp12083934, kgp12182745, kgp12230354,
kgp1224440, kgp124162, kgp12557319, kgp1371881, kgp1699628,
kgp1753445, kgp1779254, kgp1786079, kgp18379774, kgp18525257,
kgp20163979, kgp2023214, kgp20478926, kgp21171930, kgp2262166,
kgp22778566, kgp2465184, kgp24753470, kgp25191871, kgp25216186,
kgp25952891, kgp26026546, kgp26533576, kgp27500525, kgp27571222,
kgp28532436, kgp28586329, kgp28817122, kgp2958113, kgp29794723,
kgp30282494, kgp304921, kgp3205849, kgp3218351, kgp3276689,
kgp337461, kgp345301, kgp355027, kgp355723, kgp3593828, kgp3812034,
kgp3951463, kgp4162414, kgp4223880, kgp4418535, kgp4543470,
kgp4573213, kgp4634875, kgp4755147, kgp4842590, kgp485316,
kgp5068397, kgp5334779, kgp5483926, kgp5564995, kgp5869992,
kgp5908616, kgp6032617, kgp6038357, kgp6076976, kgp6091119,
kgp6127371, kgp61811, kgp6228750, kgp6236949, kgp6469620,
kgp6505544, kgp6507761, kgp6666134, kgp6700691, kgp6772915,
kgp6959492, kgp7077322, kgp7117398, kgp7178233, kgp7186699,
kgp7506434, kgp759150, kgp7730397, kgp7802182, kgp7804623,
kgp7924485, kgp8030775, kgp8036704, kgp8046214, kgp8106690,
kgp8110667, kgp8178358, kgp8200264, kgp8372910, kgp841428,
kgp8602316, kgp8615910, kgp8793915, kgp8796185, kgp8990121,
kgp9018750, kgp9354462, kgp9368119, kgp9410843, kgp9450430,
kgp9530088, kgp9627338, kgp9669946, kgp97310, kgp974569,
kgp9806386, kgp9884626, rs10049206, rs10124492, rs10125298,
rs10162089, rs10203396, rs10251797, rs10278591, rs10489312,
rs10492882, rs10498793, rs10501082, rs10510774, rs10512340,
rs10815160, rs10816302, rs10841337, rs11029892, rs11029928,
rs11192469, rs11559024, rs11648129, rs12013377, rs13394010,
rs13415334, rs1478682, rs1544352, rs1545223, rs1604169, rs1621509,
rs1644418, rs17029538, rs17400875, rs17449018, rs17577980,
rs1858973, rs1894406, rs1894407, rs197523, rs2058742, rs2071469,
rs2071472, rs2139612, rs2241883, rs2309760, rs241440, rs241442,
rs241444, rs241445, rs241446, rs241449, rs241453, rs241456,
rs2453478, rs2660214, rs2824070, rs2845371, rs2857103, rs2926455,
rs343087, rs343092, rs3767955, rs3792135, rs3829539, rs3899755,
rs4075692, rs4143493, rs423239, rs4254166, rs4356336, rs4584668,
rs4780822, rs4782279, rs5024722, rs6032209, rs6110157, rs623011,
rs6497396, rs6845927, rs6895094, rs6899068, rs7024953, rs7028906,
rs7029123, rs7062312, rs7187976, rs7191155, rs720176, rs7228827,
rs7496451, rs7563131, rs759458, rs7666442, rs7670525, rs7677801,
rs7725112, rs7850, rs7862565, rs7948420, rs8035826, rs8053136,
rs8055485, rs823829, rs9315047, rs9501224, rs9508832, rs950928,
rs9597498, rs9670531, rs9671124, rs9817308, rs9834010, rs9876830 or
rs9931211, one or more C alleles at the location of kgp10910719,
kgp11077373, kgp11453406, kgp12426624, kgp2045074, kgp22811918,
kgp23298674, kgp2709692, kgp28687699, kgp3496814, kgp3669685,
kgp3730395, kgp4056892, kgp4370912, kgp5053636, kgp5216209,
kgp5292386, kgp6023196, kgp652534, kgp7059449, kgp7189498,
kgp7521990, kgp7792268, kgp8303520, kgp9320791, kgp9795732,
rs10201643, rs11022778, rs11136970, rs11147439, rs11691553,
rs1579771, rs16901784, rs2136408, rs2325911, rs241443, rs2857104,
rs3803277, rs3885907, rs4738738, rs4894701, rs502530, rs6032205,
rs6687976, rs6718758, rs6835202, rs714342, rs7524868, rs7844274,
rs9393727 or rs9671182, one or more G alleles at the location of
kgp24415534, kgp10090631, kgp1009249, kgp10412303, kgp10523170,
kgp1054273, kgp10558725, kgp10632945, kgp10679353, kgp10788130,
kgp10826273, kgp10922969, kgp10948564, kgp10967046, kgp1098237,
kgp11010680, kgp11141512, kgp11206453, kgp11210903, kgp1124492,
kgp11281589, kgp11356379, kgp11467007, kgp11543962, kgp11580695,
kgp11633966, kgp11686146, kgp11843177, kgp12008955, kgp12371757,
kgp1285441, kgp13161760, kgp1355977, kgp15390522, kgp1683448,
kgp1688752, kgp1912531, kgp19568724, kgp2092817, kgp2245775,
kgp22793211, kgp22823022, kgp2282938, kgp2299675, kgp2356388,
kgp23672937, kgp23737989, kgp2388352, kgp2391411, kgp24131116,
kgp2446153, kgp2451249, kgp24729706, kgp25543811, kgp25921291,
kgp26271158, kgp2638591, kgp26528455, kgp2688306, kgp26995430,
kgp270001, kgp2715873, kgp27640141, kgp2788291, kgp2923815,
kgp29367521, kgp293787, kgp2959751, kgp297178, kgp3048169,
kgp3182607, kgp3202939, kgp3267884, kgp3418770, kgp3450875,
kgp3477351, kgp3598409, kgp3651767, kgp3854180, kgp3933330,
kgp3984567, kgp4011779, kgp4096263, kgp4127859, kgp4155998,
kgp4346717, kgp4420791, kgp4479467, kgp4524468, kgp4559907,
kgp4705854, kgp4734301, kgp4812831, kgp487328, kgp4898179,
kgp5002011, kgp5014707, kgp5017029, kgp512180, kgp5144181,
kgp5159037, kgp5388938, kgp5409955, kgp5440506, kgp5441587,
kgp55646, kgp5579170, kgp5680955, kgp6190988, kgp6539666,
kgp6567154, kgp6599438, kgp6603796, kgp6737096, kgp6768546,
kgp6835138, kgp6996560, kgp7063887, kgp7092772, kgp7121374,
kgp7181058, kgp7331172, kgp7416024, kgp7481870, kgp767200,
kgp7714238, kgp8107491, kgp8169636, kgp8174785, kgp8183049,
kgp8192546, kgp8335515, kgp8437961, kgp8440036, kgp85534,
kgp8599417, kgp8767692, kgp8777935, kgp8869954, kgp9071686,
kgp9078300, kgp9354820, kgp9421884, kgp9551947, kgp9601362,
kgp9627406, kgp9699754, kgp971582, kgp9854133, rs1079303,
rs10841322, rs10954782, rs11002051, rs11029907, rs11083404,
rs11085044, rs11192461, rs1157449, rs12494712, rs12943140,
rs13002663, rs13419758, rs1380706, rs1387768, rs1410779, rs1508102,
rs1532365, rs16886004, rs16895510, rs16927077, rs16930057,
rs17224858, rs17238927, rs17329014, rs17638791, rs1886214,
rs1894408, rs196295, rs196341, rs196343, rs1979992, rs1979993,
rs2043136, rs2071470, rs2074037, rs2175121, rs241435, rs241447,
rs241451, rs241452, rs241454, rs2598360, rs2621321, rs2621323,
rs2816838, rs2839117, rs2857101, rs2934491, rs3135388, rs3218328,
rs3799383, rs3815822, rs3818675, rs419132, rs4360791, rs4449139,
rs4669694, rs4709792, rs4769060, rs4822644, rs484482, rs543122,
rs6535882, rs6840089, rs7020402, rs7217872, rs7348267, rs7579987,
rs7672014, rs7860748, rs7864679, rs7928078, rs8050872, rs858341,
rs931570, rs9346979, rs9376361, rs9579566, rs9913349 or rs9931167,
or one or more T alleles at the location of kgp18432055, kgp279772,
kgp3991733 or kgp7242489, thereby identifying a human subject
afflicted with multiple sclerosis or a single clinical attack
consistent with multiple sclerosis as a predicted responder or as a
predicted non-responder to glatiramer acetate; (b) step (i) further
comprises determining a genotype of the subject at one or more
single nucleotide polymorphism (SNP): rs10988087, rs1573706,
rs17575455, rs2487896, rs3135391, rs6097801 or rs947603, and
wherein step (ii) further comprises identifying the subject as a
predicted responder to glatiramer acetate if the genotype of the
subject contains one or more A alleles at the location of
rs10988087, one or more C alleles at the location of rs17575455, or
one or more G alleles at the location of rs1573706, rs2487896,
rs3135391, rs6097801 or rs947603, thereby identifying a human
subject afflicted with multiple sclerosis or a single clinical
attack consistent with multiple sclerosis as a predicted responder
or as a predicted non-responder to glatiramer acetate; or (c) step
(i) further comprises determining a genotype of the subject at one
or more single nucleotide polymorphism (SNP): kgp10148554,
kgp10215554, kgp10762962, kgp10836214, kgp10989246, kgp11285883,
kgp11604017, kgp11755256, kgp1211163, kgp12253568, kgp12562255,
kgp1432800, kgp1682126, kgp1758575, kgp2176915, kgp22839559,
kgp24521552, kgp2877482, kgp2920925, kgp2993366, kgp3188,
kgp3287349, kgp3420309, kgp3488270, kgp3598966, kgp3624014,
kgp3697615, kgp394638, kgp4037661, kgp4137144, kgp433351,
kgp4456934, kgp4575797, kgp4591145, kgp4892427, kgp4970670,
kgp4985243, kgp5252824, kgp5326762, kgp541892, kgp5691690,
kgp5747456, kgp5894351, kgp5924341, kgp5949515, kgp6042557,
kgp6081880, kgp6194428, kgp6213972, kgp625941, kgp6301155,
kgp6429231, kgp6828277, kgp6889327, kgp6990559, kgp7006201,
kgp7151153, kgp7161038, kgp7653470, kgp7778345, kgp7932108,
kgp8145845, kgp8644305, kgp8847137, kgp9143704, kgp9409440,
kgp956070, kgp9909702, kgp9927782, rs10038844, rs1026894,
rs10495115, rs11562998, rs11563025, rs11750747, rs11947777,
rs12043743, rs12233980, rs12341716, rs12472695, rs12881439,
rs13168893, rs13386874, rs1357718, rs1393037, rs1393040, rs1397481,
rs1474226, rs1508515, rs1534647, rs16846161, rs1715441, rs17187123,
rs17245674, rs17419416, rs1793174, rs1883448, rs1905248, rs209568,
rs2354380, rs2618065, rs263247, rs2662, rs28993969, rs34647183,
rs35615951, rs3768769, rs3847233, rs3858034, rs3858035, rs3858036,
rs3858038, rs3894712, rs4740708, rs4797764, rs4978567, rs528065,
rs6459418, rs6577395, rs6811337, rs7119480, rs7123506, rs7231366,
rs7680970, rs7684006, rs7696391, rs7698655, rs7819949, rs7846783,
rs7949751, rs7961005, rs8000689, rs8018807, rs961090, rs967616,
rs9948620 or rs9953274, and wherein step (ii) further comprises
identifying the subject as a predicted responder to glatiramer
acetate if the genotype of the subject contains one or more A
alleles at the location of kgp10762962, kgp11285883, kgp11604017,
kgp1211163, kgp12253568, kgp12562255, kgp2176915, kgp24521552,
kgp2877482, kgp2993366, kgp3188, kgp3624014, kgp394638, kgp4037661,
kgp433351, kgp4456934, kgp4575797, kgp4591145, kgp4892427,
kgp4970670, kgp4985243, kgp5252824, kgp5326762, kgp541892,
kgp5747456, kgp5894351, kgp6042557, kgp6081880, kgp6194428,
kgp6429231, kgp7006201, kgp7151153, kgp7161038, kgp7653470,
kgp8145845, kgp8644305, kgp9143704, kgp9409440, kgp9909702,
kgp9927782, rs10038844, rs10495115, rs11750747, rs12341716,
rs12881439, rs13168893, rs1393040, rs1474226, rs1534647, rs1715441,
rs17187123, rs17245674, rs17419416, rs1793174, rs1883448,
rs1905248, rs263247, rs34647183, rs35615951, rs3847233, rs3858038,
rs4740708, rs528065, rs6459418, rs6577395, rs6811337, rs7680970,
rs7684006, rs7698655, rs7961005, rs8018807, rs9948620 or rs9953274,
one or more C alleles at the location of kgp10836214, kgp1432800,
kgp22839559, kgp6301155, kgp6828277, rs2354380, rs2662, rs3858035,
rs3894712, rs4797764 or rs7696391, one or more G alleles at the
location of kgp10148554, kgp10215554, kgp10989246, kgp11755256,
kgp1682126, kgp1758575, kgp2920925, kgp3287349, kgp3420309,
kgp3488270, kgp3598966, kgp3697615, kgp4137144, kgp5691690,
kgp5924341, kgp5949515, kgp6213972, kgp625941, kgp6889327,
kgp6990559, kgp7778345, kgp7932108, kgp8847137, kgp956070,
rs1026894, rs11562998, rs11563025, rs11947777,
rs12233980, rs12472695, rs13386874, rs1357718, rs1393037,
rs1397481, rs1508515, rs16846161, rs209568, rs2618065, rs28993969,
rs3768769, rs3858034, rs3858036, rs4978567, rs7119480, rs7123506,
rs7231366, rs7819949, rs7846783, rs7949751, rs8000689, rs961090 or
rs967616, or one or more T alleles at the location of rs12043743,
thereby identifying a human subject afflicted with multiple
sclerosis or a single clinical attack consistent with multiple
sclerosis as a predicted responder to glatiramer acetate.
116. The method of claim 107, wherein (a) step (i) further
comprises determining a genotype of the subject at one or more
single nucleotide polymorphism (SNP): kgp10090631, kgp1009249,
kgp10152733, kgp10224254, kgp10305127, kgp10351364, kgp10372946,
kgp10404633, kgp10412303, kgp10523170, kgp1054273, kgp10558725,
kgp10564659, kgp10591989, kgp10594414, kgp10619195, kgp10620244,
kgp10632945, kgp10633631, kgp10679353, kgp10788130, kgp10826273,
kgp10910719, kgp10922969, kgp10948564, kgp10967046, kgp10974833,
kgp1098237, kgp11002881, kgp11010680, kgp11077373, kgp11141512,
kgp11206453, kgp11210903, kgp1124492, kgp11281589, kgp11285862,
kgp11328629, kgp11356379, kgp11407560, kgp11453406, kgp11467007,
kgp11514107, kgp11543962, kgp11580695, kgp11627530, kgp11633966,
kgp11686146, kgp11702474, kgp11711524, kgp11768533, kgp11804835,
kgp11843177, kgp12008955, kgp12083934, kgp12182745, kgp12230354,
kgp1224440, kgp12371757, kgp124162, kgp12426624, kgp12557319,
kgp1285441, kgp13161760, kgp1355977, kgp1371881, kgp15390522,
kgp1683448, kgp1688752, kgp1699628, kgp1753445, kgp1779254,
kgp1786079, kgp18379774, kgp18432055, kgp18525257, kgp1912531,
kgp19568724, kgp20163979, kgp2023214, kgp2045074, kgp20478926,
kgp2092817, kgp21171930, kgp2245775, kgp2262166, kgp22778566,
kgp22793211, kgp22811918, kgp22823022, kgp2282938, kgp2299675,
kgp23298674, kgp2356388, kgp23672937, kgp23737989, kgp2388352,
kgp2391411, kgp24131116, kgp24415534, kgp2446153, kgp2451249,
kgp2465184, kgp24729706, kgp24753470, kgp25191871, kgp25216186,
kgp25543811, kgp25921291, kgp25952891, kgp26026546, kgp26271158,
kgp2638591, kgp26528455, kgp26533576, kgp2688306, kgp26995430,
kgp270001, kgp2709692, kgp2715873, kgp27500525, kgp27571222,
kgp27640141, kgp2788291, kgp279772, kgp28532436, kgp28586329,
kgp28687699, kgp28817122, kgp2923815, kgp29367521, kgp293787,
kgp2958113, kgp2959751, kgp297178, kgp29794723, kgp30282494,
kgp3048169, kgp304921, kgp3182607, kgp3202939, kgp3205849,
kgp3218351, kgp3267884, kgp3276689, kgp337461, kgp3418770,
kgp3450875, kgp345301, kgp3477351, kgp3496814, kgp355027,
kgp355723, kgp3593828, kgp3598409, kgp3651767, kgp3669685,
kgp3730395, kgp3812034, kgp3854180, kgp3933330, kgp3951463,
kgp3984567, kgp3991733, kgp4011779, kgp4056892, kgp4096263,
kgp4127859, kgp4155998, kgp4162414, kgp4223880, kgp4346717,
kgp4370912, kgp4418535, kgp4420791, kgp4479467, kgp4524468,
kgp4543470, kgp4559907, kgp4573213, kgp4634875, kgp4705854,
kgp4734301, kgp4755147, kgp4812831, kgp4842590, kgp485316,
kgp487328, kgp4898179, kgp5002011, kgp5014707, kgp5017029,
kgp5053636, kgp5068397, kgp512180, kgp5144181, kgp5159037,
kgp5216209, kgp5292386, kgp5334779, kgp5388938, kgp5409955,
kgp5440506, kgp5441587, kgp5483926, kgp55646, kgp5564995,
kgp5579170, kgp5680955, kgp5869992, kgp5908616, kgp6023196,
kgp6032617, kgp6038357, kgp6076976, kgp6091119, kgp6127371,
kgp61811, kgp6190988, kgp6214351, kgp6228750, kgp6236949,
kgp6469620, kgp6505544, kgp6507761, kgp652534, kgp6539666,
kgp6567154, kgp6599438, kgp6603796, kgp6666134, kgp6700691,
kgp6737096, kgp6768546, kgp6772915, kgp6835138, kgp6959492,
kgp6996560, kgp7059449, kgp7063887, kgp7077322, kgp7092772,
kgp7117398, kgp7121374, kgp7178233, kgp7181058, kgp7186699,
kgp7189498, kgp7242489, kgp7331172, kgp7416024, kgp7481870,
kgp7506434, kgp7521990, kgp759150, kgp767200, kgp7714238,
kgp7730397, kgp7792268, kgp7802182, kgp7804623, kgp7924485,
kgp8030775, kgp8036704, kgp8046214, kgp8106690, kgp8107491,
kgp8110667, kgp8169636, kgp8174785, kgp8178358, kgp8183049,
kgp8192546, kgp8200264, kgp8303520, kgp8335515, kgp8372910,
kgp841428, kgp8437961, kgp8440036, kgp85534, kgp8599417,
kgp8602316, kgp8615910, kgp8767692, kgp8777935, kgp8793915,
kgp8796185, kgp8869954, kgp8990121, kgp9018750, kgp9071686,
kgp9078300, kgp9320791, kgp9354462, kgp9354820, kgp9368119,
kgp9410843, kgp9421884, kgp9450430, kgp9530088, kgp9551947,
kgp9601362, kgp9627338, kgp9627406, kgp9669946, kgp9699754,
kgp971582, kgp97310, kgp974569, kgp9795732, kgp9806386, kgp9854133,
kgp9884626, rs10049206, rs10124492, rs10125298, rs10162089,
rs10201643, rs10203396, rs10251797, rs10278591, rs10489312,
rs10492882, rs10498793, rs10501082, rs10510774, rs10512340,
rs1079303, rs10815160, rs10816302, rs10841322, rs10841337,
rs10954782, rs11002051, rs11022778, rs11029892, rs11029907,
rs11029928, rs11083404, rs11085044, rs11136970, rs11147439,
rs11192461, rs11192469, rs11559024, rs1157449, rs11648129,
rs11691553, rs12013377, rs12494712, rs12943140, rs13002663,
rs13394010, rs13415334, rs13419758, rs1380706, rs1387768,
rs1410779, rs1478682, rs1508102, rs1532365, rs1544352, rs1545223,
rs1579771, rs1604169, rs1621509, rs1644418, rs16886004, rs16895510,
rs16901784, rs16927077, rs16930057, rs17029538, rs17224858,
rs17238927, rs17329014, rs17400875, rs17449018, rs17577980,
rs17638791, rs1858973, rs1886214, rs1894406, rs1894407, rs1894408,
rs196295, rs196341, rs196343, rs197523, rs1979992, rs1979993,
rs2043136, rs2058742, rs2071469, rs2071470, rs2071472, rs2074037,
rs2136408, rs2139612, rs2175121, rs2241883, rs2309760, rs2325911,
rs241435, rs241440, rs241442, rs241443, rs241444, rs241445,
rs241446, rs241447, rs241449, rs241451, rs241452, rs241453,
rs241454, rs241456, rs2453478, rs2598360, rs2621321, rs2621323,
rs2660214, rs2816838, rs2824070, rs2839117, rs2845371, rs2857101,
rs2857103, rs2857104, rs2926455, rs2934491, rs3135388, rs3218328,
rs343087, rs343092, rs3767955, rs3792135, rs3799383, rs3803277,
rs3815822, rs3818675, rs3829539, rs3885907, rs3899755, rs4075692,
rs4143493, rs419132, rs423239, rs4254166, rs4356336, rs4360791,
rs4449139, rs4584668, rs4669694, rs4709792, rs4738738, rs4769060,
rs4780822, rs4782279, rs4822644, rs484482, rs4894701, rs5024722,
rs502530, rs543122, rs6032205, rs6032209, rs6110157, rs623011,
rs6497396, rs6535882, rs6687976, rs6718758, rs6835202, rs6840089,
rs6845927, rs6895094, rs6899068, rs7020402, rs7024953, rs7028906,
rs7029123, rs7062312, rs714342, rs7187976, rs7191155, rs720176,
rs7217872, rs7228827, rs7348267, rs7496451, rs7524868, rs7563131,
rs7579987, rs759458, rs7666442, rs7670525, rs7672014, rs7677801,
rs7725112, rs7844274, rs7850, rs7860748, rs7862565, rs7864679,
rs7928078, rs7948420, rs8035826, rs8050872, rs8053136, rs8055485,
rs823829, rs858341, rs9315047, rs931570, rs9346979, rs9376361,
rs9393727, rs9501224, rs9508832, rs950928, rs9579566, rs9597498,
rs9670531, rs9671124, rs9671182, rs9817308, rs9834010, rs9876830,
rs9913349, rs9931167 and rs9931211, and ii) identifying the human
subject as a predicted responder to glatiramer acetate if the
genotype of the subject contains one or more A alleles at the
location of kgp10152733, kgp10224254, kgp10305127, kgp10351364,
kgp10372946, kgp10404633, kgp10564659, kgp10591989, kgp10594414,
kgp10619195, kgp10620244, kgp10633631, kgp10974833, kgp11002881,
kgp11285862, kgp11328629, kgp11407560, kgp11514107, kgp11627530,
kgp11702474, kgp11711524, kgp11768533, kgp11804835, kgp12083934,
kgp12182745, kgp12230354, kgp1224440, kgp124162, kgp12557319,
kgp1371881, kgp1699628, kgp1753445, kgp1779254, kgp1786079,
kgp18379774, kgp18525257, kgp20163979, kgp2023214, kgp20478926,
kgp21171930, kgp2262166, kgp22778566, kgp2465184, kgp24753470,
kgp25191871, kgp25216186, kgp25952891, kgp26026546, kgp26533576,
kgp27500525, kgp27571222, kgp28532436, kgp28586329, kgp28817122,
kgp2958113, kgp29794723, kgp30282494, kgp304921, kgp3205849,
kgp3218351, kgp3276689, kgp337461, kgp345301, kgp355027, kgp355723,
kgp3593828, kgp3812034, kgp3951463, kgp4162414, kgp4223880,
kgp4418535, kgp4543470, kgp4573213, kgp4634875, kgp4755147,
kgp4842590, kgp485316, kgp5068397, kgp5334779, kgp5483926,
kgp5564995, kgp5869992, kgp5908616, kgp6032617, kgp6038357,
kgp6076976, kgp6091119, kgp6127371, kgp61811, kgp6214351,
kgp6228750, kgp6236949, kgp6469620, kgp6505544, kgp6507761,
kgp6666134, kgp6700691, kgp6772915, kgp6959492, kgp7077322,
kgp7117398, kgp7178233, kgp7186699, kgp7506434, kgp759150,
kgp7730397, kgp7802182, kgp7804623, kgp7924485, kgp8030775,
kgp8036704, kgp8046214, kgp8106690, kgp8110667, kgp8178358,
kgp8200264, kgp8372910, kgp841428, kgp8602316, kgp8615910,
kgp8793915, kgp8796185, kgp8990121, kgp9018750, kgp9354462,
kgp9368119, kgp9410843, kgp9450430, kgp9530088, kgp9627338,
kgp9669946, kgp97310, kgp974569, kgp9806386, kgp9884626,
rs10049206, rs10124492, rs10125298, rs10162089, rs10203396,
rs10251797, rs10278591, rs10489312, rs10492882, rs10498793,
rs10501082, rs10510774, rs10512340, rs10815160, rs10816302,
rs10841337, rs11029892, rs11029928, rs11192469, rs11559024,
rs11648129, rs12013377, rs13394010, rs13415334, rs1478682,
rs1544352, rs1545223, rs1604169, rs1621509, rs1644418, rs17029538,
rs17400875, rs17449018, rs17577980, rs1858973, rs1894406,
rs1894407, rs197523, rs2058742, rs2071469, rs2071472, rs2139612,
rs2241883, rs2309760, rs241440, rs241442, rs241444, rs241445,
rs241446, rs241449, rs241453, rs241456, rs2453478, rs2660214,
rs2824070, rs2845371, rs2857103, rs2926455, rs343087, rs343092,
rs3767955, rs3792135, rs3829539, rs3899755, rs4075692, rs4143493,
rs423239, rs4254166, rs4356336, rs4584668, rs4780822, rs4782279,
rs5024722, rs6032209, rs6110157, rs623011, rs6497396, rs6845927,
rs6895094, rs6899068, rs7024953, rs7028906, rs7029123, rs7062312,
rs7187976, rs7191155, rs720176, rs7228827, rs7496451, rs7563131,
rs759458, rs7666442, rs7670525, rs7677801, rs7725112, rs7850,
rs7862565, rs7948420, rs8035826, rs8053136, rs8055485, rs823829,
rs9315047, rs9501224, rs9508832, rs950928, rs9597498, rs9670531,
rs9671124, rs9817308, rs9834010, rs9876830 or rs9931211, one or
more C alleles at the location of kgp10910719, kgp11077373,
kgp11453406, kgp12426624, kgp2045074, kgp22811918, kgp23298674,
kgp2709692, kgp28687699, kgp3496814, kgp3669685, kgp3730395,
kgp4056892, kgp4370912, kgp5053636, kgp5216209, kgp5292386,
kgp6023196, kgp652534, kgp7059449, kgp7189498, kgp7521990,
kgp7792268, kgp8303520, kgp9320791, kgp9795732, rs10201643,
rs11022778, rs11136970, rs11147439, rs11691553, rs1579771,
rs16901784, rs2136408, rs2325911, rs241443, rs2857104, rs3803277,
rs3885907, rs4738738, rs4894701, rs502530, rs6032205, rs6687976,
rs6718758, rs6835202, rs714342, rs7524868, rs7844274, rs9393727 or
rs9671182, one or more G alleles at the location of kgp10090631,
kgp1009249, kgp10412303, kgp10523170, kgp1054273, kgp10558725,
kgp10632945, kgp10679353, kgp10788130, kgp10826273, kgp10922969,
kgp10948564, kgp10967046, kgp1098237, kgp11010680, kgp11141512,
kgp11206453, kgp11210903, kgp1124492, kgp11281589, kgp11356379,
kgp11467007, kgp11543962, kgp11580695, kgp11633966, kgp11686146,
kgp11843177, kgp12008955, kgp12371757, kgp1285441, kgp13161760,
kgp1355977, kgp15390522, kgp1683448, kgp1688752, kgp1912531,
kgp19568724, kgp2092817, kgp2245775, kgp22793211, kgp22823022,
kgp2282938, kgp2299675, kgp2356388, kgp23672937, kgp23737989,
kgp2388352, kgp2391411, kgp24131116, kgp24415534, kgp2446153,
kgp2451249, kgp24729706, kgp25543811, kgp25921291, kgp26271158,
kgp2638591, kgp26528455, kgp2688306, kgp26995430, kgp270001,
kgp2715873, kgp27640141, kgp2788291, kgp2923815, kgp29367521,
kgp293787, kgp2959751, kgp297178, kgp3048169, kgp3182607,
kgp3202939, kgp3267884, kgp3418770, kgp3450875, kgp3477351,
kgp3598409, kgp3651767, kgp3854180, kgp3933330, kgp3984567,
kgp4011779, kgp4096263, kgp4127859, kgp4155998, kgp4346717,
kgp4420791, kgp4479467, kgp4524468, kgp4559907, kgp4705854,
kgp4734301, kgp4812831, kgp487328, kgp4898179, kgp5002011,
kgp5014707, kgp5017029, kgp512180, kgp5144181, kgp5159037,
kgp5388938, kgp5409955, kgp5440506, kgp5441587, kgp55646,
kgp5579170, kgp5680955, kgp6190988, kgp6539666, kgp6567154,
kgp6599438, kgp6603796, kgp6737096, kgp6768546, kgp6835138,
kgp6996560, kgp7063887, kgp7092772, kgp7121374, kgp7181058,
kgp7331172, kgp7416024, kgp7481870, kgp767200, kgp7714238,
kgp8107491, kgp8169636, kgp8174785, kgp8183049, kgp8192546,
kgp8335515, kgp8437961, kgp8440036, kgp85534, kgp8599417,
kgp8767692, kgp8777935, kgp8869954, kgp9071686, kgp9078300,
kgp9354820, kgp9421884, kgp9551947, kgp9601362, kgp9627406,
kgp9699754, kgp971582, kgp9854133, rs1079303, rs10841322,
rs10954782, rs11002051, rs11029907, rs11083404, rs11085044,
rs11192461, rs1157449, rs12494712, rs12943140, rs13002663,
rs13419758, rs1380706, rs1387768, rs1410779, rs1508102, rs1532365,
rs16886004, rs16895510, rs16927077, rs16930057, rs17224858,
rs17238927, rs17329014, rs17638791, rs1886214, rs1894408, rs196295,
rs196341, rs196343, rs1979992, rs1979993, rs2043136, rs2071470,
rs2074037, rs2175121, rs241435, rs241447, rs241451, rs241452,
rs241454, rs2598360, rs2621321, rs2621323, rs2816838, rs2839117,
rs2857101, rs2934491, rs3135388, rs3218328, rs3799383, rs3815822,
rs3818675, rs419132, rs4360791, rs4449139, rs4669694, rs4709792,
rs4769060, rs4822644, rs484482, rs543122, rs6535882, rs6840089,
rs7020402, rs7217872, rs7348267, rs7579987, rs7672014, rs7860748,
rs7864679, rs7928078, rs8050872, rs858341, rs931570, rs9346979,
rs9376361, rs9579566, rs9913349 or rs9931167, or one or more T
alleles at the location of kgp18432055, kgp279772, kgp3991733 or
kgp7242489, or identifying the human subject as a predicted
non-responder to glatiramer acetate if the genotype of the subject
contains no A alleles at the location of kgp10152733, kgp10224254,
kgp10305127, kgp10351364, kgp10372946, kgp10404633, kgp10564659,
kgp10591989, kgp10594414, kgp10619195, kgp10620244, kgp10633631,
kgp10974833, kgp11002881, kgp11285862, kgp11328629, kgp11407560,
kgp11514107, kgp11627530, kgp11702474, kgp11711524, kgp11768533,
kgp11804835, kgp12083934, kgp12182745, kgp12230354, kgp1224440,
kgp124162, kgp12557319, kgp1371881, kgp1699628, kgp1753445,
kgp1779254, kgp1786079, kgp18379774, kgp18525257, kgp20163979,
kgp2023214, kgp20478926, kgp21171930, kgp2262166, kgp22778566,
kgp2465184, kgp24753470, kgp25191871, kgp25216186, kgp25952891,
kgp26026546, kgp26533576, kgp27500525, kgp27571222, kgp28532436,
kgp28586329, kgp28817122, kgp2958113, kgp29794723, kgp30282494,
kgp304921, kgp3205849, kgp3218351, kgp3276689, kgp337461,
kgp345301, kgp355027, kgp355723, kgp3593828, kgp3812034,
kgp3951463, kgp4162414, kgp4223880, kgp4418535, kgp4543470,
kgp4573213, kgp4634875, kgp4755147, kgp4842590, kgp485316,
kgp5068397, kgp5334779, kgp5483926, kgp5564995, kgp5869992,
kgp5908616, kgp6032617, kgp6038357, kgp6076976, kgp6091119,
kgp6127371, kgp61811, kgp6214351, kgp6228750, kgp6236949,
kgp6469620, kgp6505544, kgp6507761, kgp6666134, kgp6700691,
kgp6772915, kgp6959492, kgp7077322, kgp7117398, kgp7178233,
kgp7186699, kgp7506434, kgp759150, kgp7730397, kgp7802182,
kgp7804623, kgp7924485, kgp8030775, kgp8036704, kgp8046214,
kgp8106690, kgp8110667, kgp8178358, kgp8200264, kgp8372910,
kgp841428, kgp8602316, kgp8615910, kgp8793915, kgp8796185,
kgp8990121, kgp9018750, kgp9354462, kgp9368119, kgp9410843,
kgp9450430, kgp9530088, kgp9627338, kgp9669946, kgp97310,
kgp974569, kgp9806386, kgp9884626, rs10049206, rs10124492,
rs10125298, rs10162089, rs10203396, rs10251797, rs10278591,
rs10489312, rs10492882, rs10498793, rs10501082, rs10510774,
rs10512340, rs10815160, rs10816302, rs10841337, rs11029892,
rs11029928, rs11192469, rs11559024, rs11648129, rs12013377,
rs13394010, rs13415334, rs1478682, rs1544352, rs1545223, rs1604169,
rs1621509, rs1644418, rs17029538, rs17400875, rs17449018,
rs17577980, rs1858973, rs1894406, rs1894407, rs197523, rs2058742,
rs2071469, rs2071472, rs2139612, rs2241883, rs2309760, rs241440,
rs241442, rs241444, rs241445, rs241446, rs241449, rs241453,
rs241456, rs2453478, rs2660214, rs2824070, rs2845371, rs2857103,
rs2926455, rs343087, rs343092, rs3767955, rs3792135, rs3829539,
rs3899755, rs4075692, rs4143493, rs423239, rs4254166, rs4356336,
rs4584668, rs4780822, rs4782279, rs5024722, rs6032209, rs6110157,
rs623011, rs6497396, rs6845927, rs6895094, rs6899068, rs7024953,
rs7028906, rs7029123, rs7062312, rs7187976, rs7191155, rs720176,
rs7228827, rs7496451, rs7563131, rs759458, rs7666442, rs7670525,
rs7677801, rs7725112, rs7850, rs7862565, rs7948420, rs8035826,
rs8053136, rs8055485, rs823829, rs9315047, rs9501224, rs9508832,
rs950928, rs9597498, rs9670531, rs9671124, rs9817308, rs9834010,
rs9876830 or rs9931211, no C alleles at the location of
kgp10910719, kgp11077373, kgp11453406, kgp12426624, kgp2045074,
kgp22811918, kgp23298674, kgp2709692, kgp28687699, kgp3496814,
kgp3669685, kgp3730395, kgp4056892, kgp4370912, kgp5053636,
kgp5216209, kgp5292386, kgp6023196, kgp652534, kgp7059449,
kgp7189498, kgp7521990, kgp7792268, kgp8303520, kgp9320791,
kgp9795732, rs10201643, rs11022778, rs11136970, rs11147439,
rs11691553, rs1579771, rs16901784, rs2136408, rs2325911, rs241443,
rs2857104, rs3803277, rs3885907, rs4738738, rs4894701, rs502530,
rs6032205, rs6687976, rs6718758, rs6835202, rs714342, rs7524868,
rs7844274, rs9393727 or rs9671182, no G alleles at the location of
kgp10090631, kgp1009249, kgp10412303, kgp10523170, kgp1054273,
kgp10558725, kgp10632945, kgp10679353, kgp10788130, kgp10826273,
kgp10922969, kgp10948564, kgp10967046, kgp1098237, kgp11010680,
kgp11141512, kgp11206453, kgp11210903, kgp1124492, kgp11281589,
kgp11356379, kgp11467007, kgp11543962, kgp11580695, kgp11633966,
kgp11686146, kgp11843177, kgp12008955, kgp12371757, kgp1285441,
kgp13161760, kgp1355977, kgp15390522, kgp1683448, kgp1688752,
kgp1912531,
kgp19568724, kgp2092817, kgp2245775, kgp22793211, kgp22823022,
kgp2282938, kgp2299675, kgp2356388, kgp23672937, kgp23737989,
kgp2388352, kgp2391411, kgp24131116, kgp24415534, kgp2446153,
kgp2451249, kgp24729706, kgp25543811, kgp25921291, kgp26271158,
kgp2638591, kgp26528455, kgp2688306, kgp26995430, kgp270001,
kgp2715873, kgp27640141, kgp2788291, kgp2923815, kgp29367521,
kgp293787, kgp2959751, kgp297178, kgp3048169, kgp3182607,
kgp3202939, kgp3267884, kgp3418770, kgp3450875, kgp3477351,
kgp3598409, kgp3651767, kgp3854180, kgp3933330, kgp3984567,
kgp4011779, kgp4096263, kgp4127859, kgp4155998, kgp4346717,
kgp4420791, kgp4479467, kgp4524468, kgp4559907, kgp4705854,
kgp4734301, kgp4812831, kgp487328, kgp4898179, kgp5002011,
kgp5014707, kgp5017029, kgp512180, kgp5144181, kgp5159037,
kgp5388938, kgp5409955, kgp5440506, kgp5441587, kgp55646,
kgp5579170, kgp5680955, kgp6190988, kgp6539666, kgp6567154,
kgp6599438, kgp6603796, kgp6737096, kgp6768546, kgp6835138,
kgp6996560, kgp7063887, kgp7092772, kgp7121374, kgp7181058,
kgp7331172, kgp7416024, kgp7481870, kgp767200, kgp7714238,
kgp8107491, kgp8169636, kgp8174785, kgp8183049, kgp8192546,
kgp8335515, kgp8437961, kgp8440036, kgp85534, kgp8599417,
kgp8767692, kgp8777935, kgp8869954, kgp9071686, kgp9078300,
kgp9354820, kgp9421884, kgp9551947, kgp9601362, kgp9627406,
kgp9699754, kgp971582, kgp9854133, rs1079303, rs10841322,
rs10954782, rs11002051, rs11029907, rs11083404, rs11085044,
rs11192461, rs1157449, rs12494712, rs12943140, rs13002663,
rs13419758, rs1380706, rs1387768, rs1410779, rs1508102, rs1532365,
rs16886004, rs16895510, rs16927077, rs16930057, rs17224858,
rs17238927, rs17329014, rs17638791, rs1886214, rs1894408, rs196295,
rs196341, rs196343, rs1979992, rs1979993, rs2043136, rs2071470,
rs2074037, rs2175121, rs241435, rs241447, rs241451, rs241452,
rs241454, rs2598360, rs2621321, rs2621323, rs2816838, rs2839117,
rs2857101, rs2934491, rs3135388, rs3218328, rs3799383, rs3815822,
rs3818675, rs419132, rs4360791, rs4449139, rs4669694, rs4709792,
rs4769060, rs4822644, rs484482, rs543122, rs6535882, rs6840089,
rs7020402, rs7217872, rs7348267, rs7579987, rs7672014, rs7860748,
rs7864679, rs7928078, rs8050872, rs858341, rs931570, rs9346979,
rs9376361, rs9579566, rs9913349 or rs9931167, or no T alleles at
the location of kgp18432055, kgp279772, kgp3991733 or kgp7242489,
thereby identifying a human subject afflicted with multiple
sclerosis or a single clinical attack consistent with multiple
sclerosis as a predicted responder or as a predicted non-responder
to glatiramer acetate; (b) step (i) further comprises determining a
genotype of the subject at one or more single nucleotide
polymorphism (SNP): rs10988087, rs1573706, rs17575455, rs2487896,
rs3135391, rs6097801 or rs947603, and wherein step (ii) further
comprises identifying the subject as a predicted responder to
glatiramer acetate if the genotype of the subject contains one or
more A alleles at the location of rs10988087, one or more C alleles
at the location of rs17575455, or one or more G alleles at the
location of rs1573706, rs2487896, rs3135391, rs6097801 or rs947603
or identifying the human subject as a predicted non-responder to
glatiramer acetate if the genotype of the subject contains no A
alleles at the location of rs10988087, no C alleles at the location
of rs17575455, or no G alleles at the location of rs1573706,
rs2487896, rs3135391, rs6097801 or rs947603, thereby identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate; or
(c) step (i) further comprises determining a genotype of the
subject at one or more single nucleotide polymorphism (SNP)
kgp10148554, kgp10215554, kgp10762962, kgp10836214, kgp10989246,
kgp11285883, kgp11604017, kgp11755256, kgp1211163, kgp12253568,
kgp12562255, kgp1432800, kgp1682126, kgp1758575, kgp2176915,
kgp22839559, kgp24521552, kgp2877482, kgp2920925, kgp2993366,
kgp3188, kgp3287349, kgp3420309, kgp3488270, kgp3598966,
kgp3624014, kgp3697615, kgp394638, kgp4037661, kgp4137144,
kgp433351, kgp4456934, kgp4575797, kgp4591145, kgp4892427,
kgp4970670, kgp4985243, kgp5252824, kgp5326762, kgp541892,
kgp5691690, kgp5747456, kgp5894351, kgp5924341, kgp5949515,
kgp6042557, kgp6081880, kgp6194428, kgp6213972, kgp625941,
kgp6301155, kgp6429231, kgp6828277, kgp6889327, kgp6990559,
kgp7006201, kgp7151153, kgp7161038, kgp7653470, kgp7778345,
kgp7932108, kgp8145845, kgp8644305, kgp8847137, kgp9143704,
kgp9409440, kgp956070, kgp9909702, kgp9927782, rs10038844,
rs1026894, rs10495115, rs11562998, rs11563025, rs11750747,
rs11947777, rs12043743, rs12233980, rs12341716, rs12472695,
rs12881439, rs13168893, rs13386874, rs1357718, rs1393037,
rs1393040, rs1397481, rs1474226, rs1508515, rs1534647, rs16846161,
rs1715441, rs17187123, rs17245674, rs17419416, rs1793174,
rs1883448, rs1905248, rs209568, rs2354380, rs2618065, rs263247,
rs2662, rs28993969, rs34647183, rs35615951, rs3768769, rs3847233,
rs3858034, rs3858035, rs3858036, rs3858038, rs3894712, rs4740708,
rs4797764, rs4978567, rs528065, rs6459418, rs6577395, rs6811337,
rs7119480, rs7123506, rs7231366, rs7680970, rs7684006, rs7696391,
rs7698655, rs7819949, rs7846783, rs7949751, rs7961005, rs8000689,
rs8018807, rs961090, rs967616, rs9948620 or rs9953274, and wherein
step (ii) further comprises identifying the subject as a predicted
responder to glatiramer acetate if the genotype of the subject
contains one or more A alleles at the location of kgp10762962,
kgp11285883, kgp11604017, kgp1211163, kgp12253568, kgp12562255,
kgp2176915, kgp24521552, kgp2877482, kgp2993366, kgp3188,
kgp3624014, kgp394638, kgp4037661, kgp433351, kgp4456934,
kgp4575797, kgp4591145, kgp4892427, kgp4970670, kgp4985243,
kgp5252824, kgp5326762, kgp541892, kgp5747456, kgp5894351,
kgp6042557, kgp6081880, kgp6194428, kgp6429231, kgp7006201,
kgp7151153, kgp7161038, kgp7653470, kgp8145845, kgp8644305,
kgp9143704, kgp9409440, kgp9909702, kgp9927782, rs10038844,
rs10495115, rs11750747, rs12341716, rs12881439, rs13168893,
rs1393040, rs1474226, rs1534647, rs1715441, rs17187123, rs17245674,
rs17419416, rs1793174, rs1883448, rs1905248, rs263247, rs34647183,
rs35615951, rs3847233, rs3858038, rs4740708, rs528065, rs6459418,
rs6577395, rs6811337, rs7680970, rs7684006, rs7698655, rs7961005,
rs8018807, rs9948620 or rs9953274, one or more C alleles at the
location of kgp10836214, kgp1432800, kgp22839559, kgp6301155,
kgp6828277, rs2354380, rs2662, rs3858035, rs3894712, rs4797764 or
rs7696391, one or more G alleles at the location of kgp10148554,
kgp10215554, kgp10989246, kgp11755256, kgp1682126, kgp1758575,
kgp2920925, kgp3287349, kgp3420309, kgp3488270, kgp3598966,
kgp3697615, kgp4137144, kgp5691690, kgp5924341, kgp5949515,
kgp6213972, kgp625941, kgp6889327, kgp6990559, kgp7778345,
kgp7932108, kgp8847137, kgp956070, rs1026894, rs11562998,
rs11563025, rs11947777, rs12233980, rs12472695, rs13386874,
rs1357718, rs1393037, rs1397481, rs1508515, rs16846161, rs209568,
rs2618065, rs28993969, rs3768769, rs3858034, rs3858036, rs4978567,
rs7119480, rs7123506, rs7231366, rs7819949, rs7846783, rs7949751,
rs8000689, rs961090 or rs967616, or one or more T alleles at the
location of rs12043743, thereby identifying a human subject
afflicted with multiple sclerosis or a single clinical attack
consistent with multiple sclerosis as a predicted responder to
glatiramer acetate.
Description
[0001] This application claims the benefit of U.S. Provisional
Application No. 61/893,807, filed Oct. 21, 2013, U.S. Provisional
Application No. 62/048,127, filed Sep. 9, 2014, and U.S.
Provisional Application No. 62/048,641, filed Sep. 10, 2014, the
contents of which are hereby incorporated by reference.
[0002] Throughout this application various publications are
referenced. The disclosures of these publications in their
entireties are hereby incorporated by reference into this
application in order to more fully describe the state of the art to
which this invention pertains.
BACKGROUND OF THE INVENTION
Multiple Sclerosis
[0003] Multiple sclerosis (MS) is a chronic, debilitating
autoimmune disease of the central nervous system (CNS) with either
relapsing-remitting (RR) or progressive course leading to
neurologic deterioration and disability. At time of initial
diagnosis, RRMS is the most common form of the disease (1) which is
characterized by unpredictable acute episodes of neurological
dysfunction (relapses), followed by variable recovery and periods
of clinical stability. The vast majority of RRMS patients
eventually develop secondary progressive (SP) disease with or
without superimposed relapses. Around 15% of patients develop a
sustained deterioration of their neurological function from the
beginning; this form is called primary progressive (PP) MS.
Patients who have experienced a single clinical event (Clinically
Isolated Syndrome or "CIS") and who show lesion dissemination on
subsequent magnetic resonance imaging (MRI) scans according to
McDonald's criteria, are also considered as having relapsing
MS.(2)
[0004] With a prevalence that varies considerably around the world,
MS is the most common cause of chronic neurological disability in
young adults.(3,4) Anderson et al. estimated that there were about
350,000 physician-diagnosed patients with MS in the United States
in 1990 (approx. 140 per 100,000 population).(5) It is estimated
that about 2.5 million individuals are affected worldwide.(6) In
general, there has been a trend toward an increasing prevalence and
incidence of MS worldwide, but the reasons for this trend are not
fully understood.(5)
[0005] Current therapeutic approaches consist of i) symptomatic
treatment ii) treatment of acute relapses with corticosteroids and
iii) treatment aimed to modify the course of the disease. Currently
approved therapies target the inflammatory processes of the
disease. Most of them are considered to act as immunomodulators but
their mechanisms of action have not been completely elucidated.
Immunosuppressants or cytotoxic agents are also used in some
patients after failure of conventional therapies. Several
medications have been approved and clinically ascertained as
efficacious for the treatment of RR-MS; including BETASERON.RTM.,
AVONEX.RTM. and REBIF.RTM., which are derivatives of the cytokine
interferon beta (IFNB), whose mechanism of action in MS is
generally attributed to its immunomodulatory effects, antagonizing
pro-inflammatory reactions and inducing suppressor cells.(7) Other
approved drugs for the treatment of MS include Mitoxantrone and
Natalizumab.
Glatiramer Acetate
[0006] Glatiramer acetate (GA) is the active substance in
Copaxone.RTM., a marketed product indicated for reduction of the
frequency of relapses in patients with RRMS. Its effectiveness in
reducing relapse rate and disability accumulation in RR-MS is
comparable to that of other available immunomodulating
treatments.(8,9,10) Glatiramer acetate consists of the acetate
salts of synthetic polypeptides containing four naturally occurring
amino acids: L-glutamic acid, L-alanine, L-tyrosine and L-lysine.
The average molecular weight of glatiramer acetate is between 5,000
and 9,000 Daltons. At a daily standard dose of 20 mg, GA is
generally well tolerated, however response to the drug is variable.
In various clinical trials, GA reduced relapse rates and
progression of disability in patients with RR-MS. The therapeutic
effect of GA is supported by the results of magnetic resonance
imaging (MRI) findings from various clinical centers (11), however
there are no validated predictive biomarkers of response to GA
treatment.
[0007] A possible initial mode of action of GA is associated with
binding to MHC molecules and consequent competition with various
myelin antigens for their presentation to T cells.(12) A further
aspect of its mode of action is the potent induction of T helper 2
(Th2) type cells that presumably can migrate to the brain and lead
to in situ bystander suppression.(13) It has been shown that GA
treatment in MS results in the induction of GA-specific T cells
with predominant Th2 phenotype both in response to GA and
cross-reactive myelin antigens.(13,14) Furthermore, the ability of
GA-specific infiltrating cells to express anti-inflammatory
cytokines such as IL-10 and transforming growth factor-beta
(TGF-.beta.) together with brain-derived neurotrophic factor (BDNF)
seem to correlate with the therapeutic activity of GA in
EAE.(15,16,17)
[0008] Clinical experience with GA consists of information obtained
from completed and ongoing clinical trials and from post-marketing
experience. The clinical program includes three double-blind,
placebo-controlled studies in RRMS subjects treated with GA 20
mg/day.(18,19,20) A significant reduction in the number of
relapses, compared with placebo, was seen. In the largest
controlled study, the relapse rate was reduced by 32% from 1.98
under placebo to 1.34 under GA 20 mg. GA 20 mg has also
demonstrated beneficial effects over placebo on MRI parameters
relevant to RRMS. A significant effect in median cumulative number
of Gd-enhancing lesions over 9 months of treatment (11 lesions in
the 20 mg group compared to 17 lesions under placebo) was
demonstrated.
[0009] The clinical program with GA also includes one double-blind
study in chronic-progressive MS subjects,(21) one double-blind
placebo-controlled study in primary progressive patients,(22) one
double-blind placebo-controlled study in CIS patients(23) and
numerous open-label and compassionate use studies, mostly in RRMS.
The clinical use of GA has been extensively reviewed and published
in the current literature (24,25,26,27).
[0010] U.S. Pat. No. 7,855,176 discloses administering glatiramer
acetate to patients afflicted with relapsing-remitting multiple
sclerosis (RRMS) by subcutaneous injection of 0.5 ml of an aqueous
pharmaceutical solution which contains in solution 20 mg glatiramer
acetate and 20 mg mannitol (34).
[0011] U.S. Patent Application Publication No. US 2011-0046065 A1
discloses administering glatiramer acetate to patients suffering
from relapsing-remitting multiple sclerosis by three subcutaneous
injections of a therapeutically effective dose of glatiramer
acetate over a period of seven days with at least one day between
every subcutaneous injection (35).
Pharmacogenomics
[0012] Pharmacogenomics is the methodology which associates genetic
variability with physiological responses to drug. Pharmacogenetics
is a subset of pharmacogenomics and is defined as "the study of
variations in DNA sequence as related to drug response" (ICH E15;
fda.gov/downloads/RegulatoryInformation/Guidances/ucm129296.pdf.
Pharmacogenetics focuses on genetic polymorphism in genes related
to drug metabolism, drug mechanism of action, disease type, and
side effects. Pharmacogenetics is the cornerstone of Personalized
Medicine which allows the development of more individualized drug
therapies to obtain more effective and safe treatment.
[0013] Pharmacogenetics has become a core component of many drug
development programs, being used to explain variability in drug
response among subjects in clinical trials, to address unexpected
emerging clinical issues, such as adverse events, to determine
eligibility for a clinical trial (pre-screening) to optimize trial
yield, to develop drug-linked diagnostic tests to identify patients
who are more likely or less likely to benefit from treatment or who
may be at risk of adverse events, to provide information in drug
labels to guide physician treatment decisions, to better understand
the mechanism of action or metabolism of new and existing drugs,
and to provide better understanding of disease mechanisms.
[0014] Generally, Pharmacogenetics analyses are performed in either
of two methodology approaches: Candidate genes research technique,
and Genome Wide Association Study (GWAS). Candidate genes research
technique is based on the detection of polymorphism in candidate
genes pre-selected using the knowledge on the disease, the drug
mode of action, toxicology or metabolism of drug. The Genome Wide
Association Study (GWAS) enables the detection of more than 1 M
(one million) polymorphisms across the genome. This approach is
used when related genes are unknown. DNA arrays used for GWAS can
be also analyzed per gene as in candidate gene approach.
Pharmacogenetic Studies
[0015] Various pharmacogenetic studies were done in MS patients.
For example, a Genome-Wide Association study by Byun et al. (36)
focused on extreme clinical phenotypes in order to maximize the
ability to detect genetic differences between responders and
non-responders to interferon-beta. A multi-analytical approach
detected significant associations between several SNPs and
treatment response. Responders and Non-Responders had significantly
different genotype frequencies for SNPs located in many genes,
including glypican 5, collagen type XXV al, hyaluronan proteoglycan
link protein, calpastatin, and neuronal PAS domain protein 3. Other
studies used pharmacogenetic analyses in order to characterize the
genomic profile and gene expression profile of IFN responders and
non-responders.
[0016] Other pharmacogenetic studies analyzed the genetic
background associated with response to Glatiramer Acetate. For
examples, Fusco C et al (37) assessed a possible relationship
between HLA alleles and response to GA (N=83 RRMS). DRB1*1501
allele frequency was increased in MS patients compared to healthy
controls (10.8% vs 2.7%; p=0.001). In DRB1*1501 carriers the
response rate was 81.8% compared to 39.4% in non-carriers of
DRB1*1501 and to 50% in the whole study population. Grossman et al
(38) genotyped HLA-DRB1*1501 and 61 SNPs within a total of 27 other
candidate genes, on DNA from two clinical trial cohorts. The study
revealed no association between HLA-DRB1*1501 and response to GA.
The results of the study are disclosed in the international
application published as WO2006/116602 (39).
[0017] Pharmacogenetics is the cornerstone of personalized medicine
which allows the development of more individualized drug therapies
to obtain more effective and safe treatment. Multiple Sclerosis is
a complex disease with clinical heterogeneity. In patients
afflicted with multiple sclerosis or a single clinical attack
consistent with multiple sclerosis, the ability to determine the
likelihood of treatment success would be an important tool
improving the therapeutic management of the patients. As the
therapeutic options for MS and CIS increase, the importance of
being able to determine who will respond favorably to therapy and
specifically to GA, has become of increasing significance.
SUMMARY OF THE INVENTION
Independent Embodiments
[0018] The present invention provides a method for treating a human
subject afflicted with multiple sclerosis or a single clinical
attack consistent with multiple sclerosis with a pharmaceutical
composition comprising glatiramer acetate and a pharmaceutically
acceptable carrier, comprising the steps of: [0019] (i) determining
a genotype of the subject at a location corresponding to the
location of one or more single nucleotide polymorphisms (SNPs)
selected from the group consisting of: kgp10090631, kgp1009249,
kgp10152733, kgp10224254, kgp10305127, kgp10351364, kgp10372946,
kgp10404633, kgp10412303, kgp10523170, kgp1054273, kgp10558725,
kgp10564659, kgp10591989, kgp10594414, kgp10619195, kgp10620244,
kgp10632945, kgp10633631, kgp10679353, kgp10788130, kgp10826273,
kgp10910719, kgp10922969, kgp10948564, kgp10967046, kgp10974833,
kgp1098237, kgp11002881, kgp11010680, kgp11077373, kgp11141512,
kgp11206453, kgp11210903, kgp1124492, kgp11281589, kgp11285862,
kgp11328629, kgp11356379, kgp11407560, kgp11453406, kgp11467007,
kgp11514107, kgp11543962, kgp11580695, kgp11627530, kgp11633966,
kgp11686146, kgp11702474, kgp11711524, kgp11768533, kgp11804835,
kgp11843177, kgp12008955, kgp12083934, kgp12182745, kgp12230354,
kgp1224440, kgp12371757, kgp124162, kgp12426624, kgp12557319,
kgp1285441, kgp13161760, kgp1355977, kgp1371881, kgp15390522,
kgp1683448, kgp1688752, kgp1699628, kgp1753445, kgp1779254,
kgp1786079, kgp18379774, kgp18432055, kgp18525257, kgp1912531,
kgp19568724, kgp20163979, kgp2023214, kgp2045074, kgp20478926,
kgp2092817, kgp21171930, kgp2245775, kgp2262166, kgp22778566,
kgp22793211, kgp22811918, kgp22823022, kgp2282938, kgp2299675,
kgp23298674, kgp2356388, kgp23672937, kgp23737989, kgp2388352,
kgp2391411, kgp24131116, kgp24415534, kgp2446153, kgp2451249,
kgp2465184, kgp24729706, kgp24753470, kgp25191871, kgp25216186,
kgp25543811, kgp25921291, kgp25952891, kgp26026546, kgp26271158,
kgp2638591, kgp26528455, kgp26533576, kgp2688306, kgp26995430,
kgp270001, kgp2709692, kgp2715873, kgp27500525, kgp27571222,
kgp27640141, kgp2788291, kgp279772, kgp28532436, kgp28586329,
kgp28687699, kgp28817122, kgp2923815, kgp29367521, kgp293787,
kgp2958113, kgp2959751, kgp297178, kgp29794723, kgp30282494,
kgp3048169, kgp304921, kgp3182607, kgp3202939, kgp3205849,
kgp3218351, kgp3267884, kgp3276689, kgp337461, kgp3418770,
kgp3450875, kgp345301, kgp3477351, kgp3496814, kgp355027,
kgp355723, kgp3593828, kgp3598409, kgp3651767, kgp3669685,
kgp3730395, kgp3812034, kgp3854180, kgp3933330, kgp3951463,
kgp3984567, kgp3991733, kgp4011779, kgp4056892, kgp4096263,
kgp4127859, kgp4155998, kgp4162414, kgp4223880, kgp4346717,
kgp4370912, kgp4418535, kgp4420791, kgp4479467, kgp4524468,
kgp4543470, kgp4559907, kgp4573213, kgp4634875, kgp4705854,
kgp4734301, kgp4755147, kgp4812831, kgp4842590, kgp485316,
kgp487328, kgp4898179, kgp5002011, kgp5014707, kgp5017029,
kgp5053636, kgp5068397, kgp512180, kgp5144181, kgp5159037,
kgp5216209, kgp5292386, kgp5334779, kgp5388938, kgp5409955,
kgp5440506, kgp5441587, kgp5483926, kgp55646, kgp5564995,
kgp5579170, kgp5680955, kgp5869992, kgp5908616, kgp6023196,
kgp6032617, kgp6038357, kgp6076976, kgp6091119, kgp6127371,
kgp61811, kgp6190988, kgp6214351, kgp6228750, kgp6236949,
kgp6469620, kgp6505544, kgp6507761, kgp652534, kgp6539666,
kgp6567154, kgp6599438, kgp6603796, kgp6666134, kgp6700691,
kgp6737096, kgp6768546, kgp6772915, kgp6835138, kgp6959492,
kgp6996560, kgp7059449, kgp7063887, kgp7077322, kgp7092772,
kgp7117398, kgp7121374, kgp7178233, kgp7181058, kgp7186699,
kgp7189498, kgp7242489, kgp7331172, kgp7416024, kgp7481870,
kgp7506434, kgp7521990, kgp759150, kgp767200, kgp7714238,
kgp7730397, kgp7747883, kgp7792268, kgp7802182, kgp7804623,
kgp7924485, kgp8030775, kgp8036704, kgp8046214, kgp8106690,
kgp8107491, kgp8110667, kgp8169636, kgp8174785, kgp8178358,
kgp8183049, kgp8192546, kgp8200264, kgp8303520, kgp8335515,
kgp8372910, kgp841428, kgp8437961, kgp8440036, kgp85534,
kgp8599417, kgp8602316, kgp8615910, kgp8767692, kgp8777935,
kgp8793915, kgp8796185, kgp8817856, kgp8869954, kgp8990121,
kgp9018750, kgp9071686, kgp9078300, kgp9320791, kgp9354462,
kgp9354820, kgp9368119, kgp9410843, kgp9421884, kgp9450430,
kgp9530088, kgp9551947, kgp9601362, kgp9627338, kgp9627406,
kgp9669946, kgp9699754, kgp971582, kgp97310, kgp974569, kgp9795732,
kgp9806386, kgp9854133, kgp9884626, rs10049206, rs10124492,
rs10125298, rs10162089, rs10201643, rs10203396, rs10251797,
rs10278591, rs10489312, rs10492882, rs10498793, rs10501082,
rs10510774, rs10512340, rs1079303, rs10815160, rs10816302,
rs10841322, rs10841337, rs10954782, rs11002051, rs11022778,
rs11029892, rs11029907, rs11029928, rs11083404, rs11085044,
rs11136970, rs11147439, rs11192461, rs11192469, rs11559024,
rs1157449, rs11648129, rs11691553, rs12013377, rs12494712,
rs12943140, rs13002663, rs13394010, rs13415334, rs13419758,
rs1380706, rs1387768, rs1410779, rs1478682, rs1508102, rs1532365,
rs1544352, rs1545223, rs1579771, rs1604169, rs1621509, rs1644418,
rs16886004, rs16895510, rs16901784, rs16927077, rs16930057,
rs17029538, rs17224858, rs17238927, rs17329014, rs17400875,
rs17449018, rs17577980, rs17638791, rs1858973, rs1886214,
rs1894406, rs1894407, rs1894408, rs196295, rs196341, rs196343,
rs197523, rs1979992, rs1979993, rs2043136, rs2058742, rs2071469,
rs2071470, rs2071472, rs2074037, rs2136408, rs2139612, rs2175121,
rs2241883, rs2309760, rs2325911, rs241435, rs241440, rs241442,
rs241443, rs241444, rs241445, rs241446, rs241447, rs241449,
rs241451, rs241452, rs241453, rs241454, rs241456, rs2453478,
rs2598360, rs2621321, rs2621323, rs2660214, rs2816838, rs2824070,
rs2839117, rs2845371, rs2857101, rs2857103, rs2857104, rs2926455,
rs2934491, rs3135388, rs3218328, rs343087, rs343092, rs3767955,
rs3792135, rs3799383, rs3803277, rs3815822, rs3818675, rs3829539,
rs3885907, rs3899755, rs4075692, rs4143493, rs419132, rs423239,
rs4254166, rs4356336, rs4360791, rs4449139, rs4584668, rs4669694,
rs4709792, rs4738738, rs4769060, rs4780822, rs4782279, rs4822644,
rs484482, rs4894701, rs5024722, rs502530, rs543122, rs6032205,
rs6032209, rs6110157, rs623011, rs6497396, rs6535882, rs6687976,
rs6718758, rs6835202, rs6840089, rs6845927, rs6895094, rs6899068,
rs7020402, rs7024953, rs7028906, rs7029123, rs7062312, rs714342,
rs7187976, rs7191155, rs720176, rs7217872, rs7228827, rs7348267,
rs7496451, rs7524868, rs7563131, rs7579987, rs759458, rs7666442,
rs7670525, rs7672014, rs7677801, rs7725112, rs7844274, rs7850,
rs7860748, rs7862565, rs7864679, rs7928078, rs7948420, rs8035826,
rs8050872, rs8053136, rs8055485, rs823829, rs858341, rs9315047,
rs931570, rs9346979, rs9376361, rs9393727, rs9501224, rs9508832,
rs950928, rs9579566, rs9597498, rs9670531, rs9671124, rs9671182,
rs9817308, rs9834010, rs9876830, rs9913349, rs9931167 and rs9931211
(hereinafter Group 1), [0020] (ii) identifying the subject as a
predicted responder to glatiramer acetate if the genotype of the
subject contains [0021] one or more A alleles at the location of
kgp10152733, kgp10224254, kgp10305127, kgp10351364, kgp10372946,
kgp10404633, kgp10564659, kgp10591989, kgp10594414, kgp10619195,
kgp10620244, kgp10633631, kgp10974833, kgp11002881, kgp11285862,
kgp11328629, kgp11407560, kgp11514107, kgp11627530, kgp11702474,
kgp11711524, kgp11768533, kgp11804835, kgp12083934, kgp12182745,
kgp12230354, kgp1224440, kgp124162, kgp12557319, kgp1371881,
kgp1699628, kgp1753445, kgp1779254, kgp1786079, kgp18379774,
kgp18525257, kgp20163979, kgp2023214, kgp20478926, kgp21171930,
kgp2262166, kgp22778566, kgp2465184, kgp24753470, kgp25191871,
kgp25216186, kgp25952891, kgp26026546, kgp26533576, kgp27500525,
kgp27571222, kgp28532436, kgp28586329, kgp28817122, kgp2958113,
kgp29794723, kgp30282494, kgp304921, kgp3205849, kgp3218351,
kgp3276689, kgp337461, kgp345301, kgp355027, kgp355723, kgp3593828,
kgp3812034, kgp3951463, kgp4162414, kgp4223880, kgp4418535,
kgp4543470, kgp4573213, kgp4634875, kgp4755147, kgp4842590,
kgp485316, kgp5068397, kgp5334779, kgp5483926, kgp5564995,
kgp5869992, kgp5908616, kgp6032617, kgp6038357, kgp6076976,
kgp6091119, kgp6127371, kgp61811, kgp6214351, kgp6228750,
kgp6236949, kgp6469620, kgp6505544, kgp6507761, kgp6666134,
kgp6700691, kgp6772915, kgp6959492, kgp7077322, kgp7117398,
kgp7178233, kgp7186699, kgp7506434, kgp759150, kgp7730397,
kgp7802182, kgp7804623, kgp7924485, kgp8030775, kgp8036704,
kgp8046214, kgp8106690, kgp8110667, kgp8178358, kgp8200264,
kgp8372910, kgp841428, kgp8602316, kgp8615910, kgp8793915,
kgp8796185, kgp8990121, kgp9018750, kgp9354462, kgp9368119,
kgp9410843, kgp9450430, kgp9530088, kgp9627338, kgp9669946,
kgp97310, kgp974569, kgp9806386, kgp9884626, rs10049206,
rs10124492, rs10125298, rs10162089, rs10203396, rs10251797,
rs10278591, rs10489312, rs10492882, rs10498793, rs10501082,
rs10510774, rs10512340, rs10815160, rs10816302, rs10841337,
rs11029892, rs11029928, rs11192469, rs11559024, rs11648129,
rs12013377, rs13394010, rs13415334, rs1478682, rs1544352,
rs1545223, rs1604169, rs1621509, rs1644418, rs17029538, rs17400875,
rs17449018, rs17577980, rs1858973, rs1894406, rs1894407, rs197523,
rs2058742, rs2071469, rs2071472, rs2139612, rs2241883, rs2309760,
rs241440, rs241442, rs241444, rs241445, rs241446, rs241449,
rs241453, rs241456, rs2453478, rs2660214, rs2824070, rs2845371,
rs2857103, rs2926455, rs343087, rs343092, rs3767955, rs3792135,
rs3829539, rs3899755, rs4075692, rs4143493, rs423239, rs4254166,
rs4356336, rs4584668, rs4780822, rs4782279, rs5024722, rs6032209,
rs6110157, rs623011, rs6497396, rs6845927, rs6895094, rs6899068,
rs7024953, rs7028906, rs7029123, rs7062312, rs7187976, rs7191155,
rs720176, rs7228827, rs7496451, rs7563131, rs759458, rs7666442,
rs7670525, rs7677801, rs7725112, rs7850, rs7862565, rs7948420,
rs8035826, rs8053136, rs8055485, rs823829, rs9315047, rs9501224,
rs9508832, rs950928, rs9597498, rs9670531, rs9671124, rs9817308,
rs9834010, rs9876830 or rs9931211 (hereinafter Group 2), [0022] one
or more C alleles at the location of kgp10910719, kgp11077373,
kgp11453406, kgp12426624, kgp2045074, kgp22811918, kgp23298674,
kgp2709692, kgp28687699, kgp3496814, kgp3669685, kgp3730395,
kgp4056892, kgp4370912, kgp5053636, kgp5216209, kgp5292386,
kgp6023196, kgp652534, kgp7059449, kgp7189498, kgp7521990,
kgp7792268, kgp8303520, kgp9320791, kgp9795732, rs10201643,
rs11022778, rs11136970, rs11147439, rs11691553, rs1579771,
rs16901784, rs2136408, rs2325911, rs241443, rs2857104, rs3803277,
rs3885907, rs4738738, rs4894701, rs502530, rs6032205, rs6687976,
rs6718758, rs6835202, rs714342, rs7524868, rs7844274, rs9393727 or
rs9671182 (hereinafter Group 3), [0023] one or more G alleles at
the location of kgp10090631, kgp1009249, kgp10412303, kgp10523170,
kgp1054273, kgp10558725, kgp10632945, kgp10679353, kgp10788130,
kgp10826273, kgp10922969, kgp10948564, kgp10967046, kgp1098237,
kgp11010680, kgp11141512, kgp11206453, kgp11210903, kgp1124492,
kgp11281589, kgp11356379, kgp11467007, kgp11543962, kgp11580695,
kgp11633966, kgp11686146, kgp11843177, kgp12008955, kgp12371757,
kgp1285441, kgp13161760, kgp1355977, kgp15390522, kgp1683448,
kgp1688752, kgp1912531, kgp19568724, kgp2092817, kgp2245775,
kgp22793211, kgp22823022, kgp2282938, kgp2299675, kgp2356388,
kgp23672937, kgp23737989, kgp2388352, kgp2391411, kgp24131116,
kgp24415534, kgp2446153, kgp2451249, kgp24729706, kgp25543811,
kgp25921291, kgp26271158, kgp2638591, kgp26528455, kgp2688306,
kgp26995430, kgp270001, kgp2715873, kgp27640141, kgp2788291,
kgp2923815, kgp29367521, kgp293787, kgp2959751, kgp297178,
kgp3048169, kgp3182607, kgp3202939, kgp3267884, kgp3418770,
kgp3450875, kgp3477351, kgp3598409, kgp3651767, kgp3854180,
kgp3933330, kgp3984567, kgp4011779, kgp4096263, kgp4127859,
kgp4155998, kgp4346717, kgp4420791, kgp4479467, kgp4524468,
kgp4559907, kgp4705854, kgp4734301, kgp4812831, kgp487328,
kgp4898179, kgp5002011, kgp5014707, kgp5017029, kgp512180,
kgp5144181, kgp5159037, kgp5388938, kgp5409955, kgp5440506,
kgp5441587, kgp55646, kgp5579170, kgp5680955, kgp6190988,
kgp6539666, kgp6567154, kgp6599438, kgp6603796, kgp6737096,
kgp6768546, kgp6835138, kgp6996560, kgp7063887, kgp7092772,
kgp7121374, kgp7181058, kgp7331172, kgp7416024, kgp7481870,
kgp767200, kgp7714238, kgp7747883, kgp8107491, kgp8169636,
kgp8174785, kgp8183049, kgp8192546, kgp8335515, kgp8437961,
kgp8440036, kgp85534, kgp8599417, kgp8767692, kgp8777935,
kgp8817856, kgp8869954, kgp9071686, kgp9078300, kgp9354820,
kgp9421884, kgp9551947, kgp9601362, kgp9627406, kgp9699754,
kgp971582, kgp9854133, rs1079303, rs10841322, rs10954782,
rs11002051, rs11029907, rs11083404, rs11085044, rs11192461,
rs1157449, rs12494712, rs12943140, rs13002663, rs13419758,
rs1380706, rs1387768, rs1410779, rs1508102, rs1532365, rs16886004,
rs16895510, rs16927077, rs16930057, rs17224858, rs17238927,
rs17329014, rs17638791, rs1886214, rs1894408, rs196295, rs196341,
rs196343, rs1979992, rs1979993, rs2043136, rs2071470, rs2074037,
rs2175121, rs241435, rs241447, rs241451, rs241452, rs241454,
rs2598360, rs2621321, rs2621323, rs2816838, rs2839117, rs2857101,
rs2934491, rs3135388, rs3218328, rs3799383, rs3815822, rs3818675,
rs419132, rs4360791, rs4449139, rs4669694, rs4709792, rs4769060,
rs4822644, rs484482, rs543122, rs6535882, rs6840089, rs7020402,
rs7217872, rs7348267, rs7579987, rs7672014, rs7860748, rs7864679,
rs7928078, rs8050872, rs858341, rs931570, rs9346979, rs9376361,
rs9579566, rs9913349 or rs9931167 (hereinafter Group 4), or [0024]
one or more T alleles at the location of kgp18432055, kgp279772,
kgp3991733 or kgp7242489; and [0025] (iii) administering the
pharmaceutical composition comprising glatiramer acetate and a
pharmaceutically acceptable carrier to the subject only if the
subject is identified as a predicted responder to glatiramer
acetate.
[0026] The present invention also provides a method of identifying
a human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the method comprising determining the genotype of the subject at a
location corresponding to the location of one or more single
nucleotide polymorphisms (SNPs) selected from the group consisting
of Group 1, and identifying the human subject as a predicted
responder to glatiramer acetate if the genotype of the subject
contains [0027] one or more A alleles at the location of Group 2,
[0028] one or more C alleles at the location of Group 3, [0029] one
or more G alleles at the location of Group 4, or [0030] one or more
T alleles at the location of kgp18432055, kgp279772, kgp3991733 or
kgp7242489, [0031] or identifying the human subject as a predicted
non-responder to glatiramer acetate if the genotype of the subject
contains [0032] no A alleles at the location of Group 2, [0033] no
C alleles at the location of Group 3, [0034] no G alleles at the
location of Group 4, or [0035] no T alleles at the location of
kgp18432055, kgp279772, kgp3991733 or kgp7242489.
[0036] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising at least one probe specific for the location of
a SNP selected from the group consisting of Group 1.
[0037] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising at least one pair of PCR primers designed to
amplify a DNA segment which includes the location of a SNP selected
from the group consisting of Group 1.
[0038] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising a reagent for performing a method selected from
the group consisting of restriction fragment length polymorphism
(RFLP) analysis, sequencing, single strand conformation
polymorphism analysis (SSCP), chemical cleavage of mismatch (CCM),
gene chip and denaturing high performance liquid chromatography
(DHPLC) for determining the genotype of the subject at a location
corresponding to the location of at least one SNP selected from the
group consisting of Group 1.
[0039] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising reagents for TaqMan Open Array assay designed
for determining the genotype of the subject at a location
corresponding to the location of at least one SNP selected from the
group consisting of Group 1.
[0040] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising [0041] a) at least one probe specific for a
location corresponding to the location of at least one SNP; [0042]
b) at least one pair of PCR primers designed to amplify a DNA
segment which includes a location corresponding to the location of
at least one SNP; [0043] c) at least one pair of PCR primers
designed to amplify a DNA segment which includes a location
corresponding to the location of at least one SNP and at least one
probe specific for a location corresponding to the location of at
least one SNP; [0044] d) a reagent for performing a method selected
from the group consisting of restriction fragment length
polymorphism (RFLP) analysis, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), gene chip and denaturing high performance liquid
chromatography (DHPLC) for determining the identity of at least one
SNP; or [0045] e) reagents for TaqMan Open Array assay designed for
determining the genotype at a location corresponding to the
location of at least one SNP, [0046] wherein the at least one SNP
is selected from the group consisting of Group 1.
[0047] The present invention also provides a probe for identifying
the genotype of a location corresponding to the location of a SNP
selected from the group consisting of kgp10090631, kgp1009249,
kgp10148554, kgp10152733, kgp10215554, kgp10224254, kgp10305127,
kgp10351364, kgp10372946, kgp10404633, kgp10412303, kgp10523170,
kgp1054273, kgp10558725, kgp10564659, kgp10591989, kgp10594414,
kgp10619195, kgp10620244, kgp10632945, kgp10633631, kgp10679353,
kgp10762962, kgp10788130, kgp10826273, kgp10836214, kgp10910719,
kgp10922969, kgp10948564, kgp10967046, kgp10974833, kgp1098237,
kgp10989246, kgp11002881, kgp11010680, kgp11077373, kgp11141512,
kgp11206453, kgp11210903, kgp1124492, kgp11281589, kgp11285862,
kgp11285883, kgp11328629, kgp11356379, kgp11407560, kgp11453406,
kgp11467007, kgp11514107, kgp11543962, kgp11580695, kgp11604017,
kgp11627530, kgp11633966, kgp11686146, kgp11702474, kgp11711524,
kgp11755256, kgp11768533, kgp11804835, kgp11843177, kgp12008955,
kgp12083934, kgp1211163, kgp12182745, kgp12230354, kgp1224440,
kgp12253568, kgp12371757, kgp124162, kgp12426624, kgp12557319,
kgp12562255, kgp1285441, kgp13161760, kgp1355977, kgp1371881,
kgp1432800, kgp15390522, kgp1682126, kgp1683448, kgp1688752,
kgp1699628, kgp1753445, kgp1758575, kgp1779254, kgp1786079,
kgp18379774, kgp18432055, kgp18525257, kgp1912531, kgp19568724,
kgp20163979, kgp2023214, kgp2045074, kgp20478926, kgp2092817,
kgp21171930, kgp2176915, kgp2245775, kgp2262166, kgp22778566,
kgp22793211, kgp22811918, kgp22823022, kgp2282938, kgp22839559,
kgp2299675, kgp23298674, kgp2356388, kgp23672937, kgp23737989,
kgp2388352, kgp2391411, kgp24131116, kgp24415534, kgp2446153,
kgp2451249, kgp24521552, kgp2465184, kgp24729706, kgp24753470,
kgp25191871, kgp25216186, kgp25543811, kgp25921291, kgp25952891,
kgp26026546, kgp26271158, kgp2638591, kgp26528455, kgp26533576,
kgp2688306, kgp26995430, kgp270001, kgp2709692, kgp2715873,
kgp27500525, kgp27571222, kgp27640141, kgp2788291, kgp279772,
kgp28532436, kgp28586329, kgp28687699, kgp2877482, kgp28817122,
kgp2920925, kgp2923815, kgp29367521, kgp293787, kgp2958113,
kgp2959751, kgp297178, kgp29794723, kgp2993366, kgp30282494,
kgp3048169, kgp304921, kgp3182607, kgp3188, kgp3202939, kgp3205849,
kgp3218351, kgp3267884, kgp3276689, kgp3287349, kgp337461,
kgp3418770, kgp3420309, kgp3450875, kgp345301, kgp3477351,
kgp3488270, kgp3496814, kgp355027, kgp355723, kgp3593828,
kgp3598409, kgp3598966, kgp3624014, kgp3651767, kgp3669685,
kgp3697615, kgp3730395, kgp3812034, kgp3854180, kgp3933330,
kgp394638, kgp3951463, kgp3984567, kgp3991733, kgp4011779,
kgp4037661, kgp4056892, kgp4096263, kgp4127859, kgp4137144,
kgp4155998, kgp4162414, kgp4223880, kgp433351, kgp4346717,
kgp4370912, kgp4418535, kgp4420791, kgp4456934, kgp4479467,
kgp4524468, kgp4543470, kgp4559907, kgp4573213, kgp4575797,
kgp4591145, kgp4634875, kgp4705854, kgp4734301, kgp4755147,
kgp4812831, kgp4842590, kgp485316, kgp487328, kgp4892427,
kgp4898179, kgp4970670, kgp4985243, kgp5002011, kgp5014707,
kgp5017029, kgp5053636, kgp5068397, kgp512180, kgp5144181,
kgp5159037, kgp5216209, kgp5252824, kgp5292386, kgp5326762,
kgp5334779, kgp5388938, kgp5409955, kgp541892, kgp5440506,
kgp5441587, kgp5483926, kgp55646, kgp5564995, kgp5579170,
kgp5680955, kgp5691690, kgp5747456, kgp5869992, kgp5894351,
kgp5908616, kgp5924341, kgp5949515, kgp6023196, kgp6032617,
kgp6038357, kgp6042557, kgp6076976, kgp6081880, kgp6091119,
kgp6127371, kgp61811, kgp6190988, kgp6194428, kgp6213972,
kgp6214351, kgp6228750, kgp6236949, kgp625941, kgp6301155,
kgp6429231, kgp6469620, kgp6505544, kgp6507761, kgp652534,
kgp6539666, kgp6567154, kgp6599438, kgp6603796, kgp6666134,
kgp6700691, kgp6737096, kgp6768546, kgp6772915, kgp6828277,
kgp6835138, kgp6889327, kgp6959492, kgp6990559, kgp6996560,
kgp7006201, kgp7059449, kgp7063887, kgp7077322, kgp7092772,
kgp7117398, kgp7121374, kgp7151153, kgp7161038, kgp7178233,
kgp7181058, kgp7186699, kgp7189498, kgp7242489, kgp7331172,
kgp7416024, kgp7481870, kgp7506434, kgp7521990, kgp759150,
kgp7653470, kgp767200, kgp7714238, kgp7730397, kgp7747883,
kgp7778345, kgp7792268, kgp7802182, kgp7804623, kgp7924485,
kgp7932108, kgp8030775, kgp8036704, kgp8046214, kgp8106690,
kgp8107491, kgp8110667, kgp8145845, kgp8169636, kgp8174785,
kgp8178358, kgp8183049, kgp8192546, kgp8200264, kgp8303520,
kgp8335515, kgp8372910, kgp841428, kgp8437961, kgp8440036,
kgp85534, kgp8599417, kgp8602316, kgp8615910, kgp8644305,
kgp8767692, kgp8777935, kgp8793915, kgp8796185, kgp8817856,
kgp8847137, kgp8869954, kgp8990121, kgp9018750, kgp9071686,
kgp9078300, kgp9143704, kgp9320791, kgp9354462, kgp9354820,
kgp9368119, kgp9409440, kgp9410843, kgp9421884, kgp9450430,
kgp9530088, kgp9551947, kgp956070, kgp9601362, kgp9627338,
kgp9627406, kgp9669946, kgp9699754, kgp971582, kgp97310, kgp974569,
kgp9795732, kgp9806386, kgp9854133, kgp9884626, kgp9909702,
kgp9927782, P1_M_061510_11_106_M, P1_M_061510_18_342_P,
P1_M_061510_6_159_P, rs10038844, rs10049206, rs10124492,
rs10125298, rs10162089, rs10201643, rs10203396, rs10251797,
rs1026894, rs10278591, rs10489312, rs10492882, rs10495115,
rs10498793, rs10501082, rs10510774, rs10512340, rs1079303,
rs10815160, rs10816302, rs10841322, rs10841337, rs10954782,
rs11002051, rs11022778, rs11029892, rs11029907, rs11029928,
rs11083404, rs11085044, rs11136970, rs11147439, rs11192461,
rs11192469, rs11559024, rs11562998, rs11563025, rs1157449,
rs11648129, rs11691553, rs11750747, rs11947777, rs12013377,
rs12043743, rs12233980, rs12341716, rs12472695, rs12494712,
rs12881439, rs12943140, rs13002663, rs13168893, rs13386874,
rs13394010, rs13415334, rs13419758, rs1357718, rs1380706,
rs1387768, rs1393037, rs1393040, rs1397481, rs1410779, rs1474226,
rs1478682, rs1508102, rs1508515, rs1532365, rs1534647, rs1544352,
rs1545223, rs1579771, rs1604169, rs1621509, rs1644418, rs16846161,
rs16886004, rs16895510, rs16901784, rs16927077, rs16930057,
rs17029538, rs1715441, rs17187123, rs17224858, rs17238927,
rs17245674, rs17329014, rs17400875, rs17419416, rs17449018,
rs17577980, rs17638791, rs1793174, rs1858973, rs1883448, rs1886214,
rs1894406, rs1894407, rs1894408, rs1905248, rs196295, rs196341,
rs196343, rs197523, rs1979992, rs1979993, rs2043136, rs2058742,
rs2071469, rs2071470, rs2071472, rs2074037, rs209568, rs2136408,
rs2139612, rs2175121, rs2241883, rs2309760, rs2325911, rs2354380,
rs241435, rs241440, rs241442, rs241443, rs241444, rs241445,
rs241446, rs241447, rs241449, rs241451, rs241452, rs241453,
rs241454, rs241456, rs2453478, rs2598360, rs2618065, rs2621321,
rs2621323, rs263247, rs2660214, rs2662, rs2816838, rs2824070,
rs2839117, rs2845371, rs2857101, rs2857103, rs2857104, rs28993969,
rs2926455, rs2934491, rs3135388, rs3218328, rs343087, rs343092,
rs34647183, rs35615951, rs3767955, rs3768769, rs3792135, rs3799383,
rs3803277, rs3815822, rs3818675, rs3829539, rs3847233, rs3858034,
rs3858035, rs3858036, rs3858038, rs3885907, rs3894712, rs3899755,
rs4075692, rs4143493, rs419132, rs423239, rs4254166, rs4356336,
rs4360791, rs4449139, rs4584668, rs4669694, rs4709792, rs4738738,
rs4740708, rs4769060, rs4780822, rs4782279, rs4797764, rs4822644,
rs484482, rs4894701, rs4978567, rs5024722, rs502530, rs528065,
rs543122, rs6032205, rs6032209, rs6110157, rs623011, rs6459418,
rs6497396, rs6535882, rs6577395, rs6687976, rs6718758, rs6811337,
rs6835202, rs6840089, rs6845927, rs6895094, rs6899068, rs7020402,
rs7024953, rs7028906, rs7029123, rs7062312, rs7119480, rs7123506,
rs714342, rs7187976, rs7191155, rs720176, rs7217872, rs7228827,
rs7231366, rs7348267, rs7496451, rs7524868, rs7563131, rs7579987,
rs759458, rs7666442, rs7670525, rs7672014, rs7677801, rs7680970,
rs7684006, rs7696391, rs7698655, rs7725112, rs7819949, rs7844274,
rs7846783, rs7850, rs7860748, rs7862565, rs7864679, rs7928078,
rs7948420, rs7949751, rs7961005, rs8000689, rs8018807, rs8035826,
rs8050872, rs8053136, rs8055485, rs823829, rs858341, rs9315047,
rs931570, rs9346979, rs9376361, rs9393727, rs9501224, rs9508832,
rs950928, rs9579566, rs9597498, rs961090, rs9670531, rs9671124,
rs9671182, rs967616, rs9817308, rs9834010, rs9876830, rs9913349,
rs9931167, rs9931211, rs9948620 and rs9953274 (hereinafter Group
5).
[0048] The present invention also provides glatiramer acetate or a
pharmaceutical composition comprising glatiramer acetate for use in
treating a human subject afflicted with multiple sclerosis or a
single clinical attack consistent with multiple sclerosis which
human subject is identified as a predicted responder to glatiramer
acetate by: [0049] a) determining a genotype of the subject at a
location corresponding to the location of one or more single
nucleotide polymorphisms (SNPs) selected from the group consisting
of: Group 1, and [0050] b) identifying the subject as a predicted
responder to glatiramer acetate if the genotype of the subject
contains [0051] one or more A alleles at the location of Group 2,
[0052] one or more C alleles at the location of Group 3, [0053] one
or more G alleles at the location of Group 4, or [0054] one or more
T alleles at the location of kgp18432055, kgp279772, kgp3991733 or
kgp7242489.
[0055] The present invention also provides a method of determining
the genotype of a human subject comprising identifying whether the
genotype of a human subject contains [0056] one or more A alleles
at the location of Group 2, [0057] one or more C alleles at the
location of Group 3, [0058] one or more G alleles at the location
of Group 4, or [0059] one or more T alleles at the location of
kgp18432055, kgp279772, kgp3991733 or kgp7242489.
[0060] The present invention also provides a method of identifying
a human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis who is predicted
to have a slower course of disease progression, comprising the
steps of: [0061] (i) determining a genotype of the subject at a
location corresponding to the location of one or more single
nucleotide polymorphisms (SNPs) selected from the group consisting
of: kgp10148554, kgp10215554, kgp10762962, kgp10836214,
kgp10989246, kgp11285883, kgp11604017, kgp11755256, kgp1211163,
kgp12253568, kgp12562255, kgp1432800, kgp1682126, kgp1758575,
kgp2176915, kgp22839559, kgp24521552, kgp2877482, kgp2920925,
kgp2993366, kgp3188, kgp3287349, kgp3420309, kgp3488270,
kgp3598966, kgp3624014, kgp3697615, kgp394638, kgp4037661,
kgp4137144, kgp433351, kgp4456934, kgp4575797, kgp4591145,
kgp4892427, kgp4970670, kgp4985243, kgp5252824, kgp5326762,
kgp541892, kgp5691690, kgp5747456, kgp5894351, kgp5924341,
kgp5949515, kgp6042557, kgp6081880, kgp6194428, kgp6213972,
kgp625941, kgp6301155, kgp6429231, kgp6828277, kgp6889327,
kgp6990559, kgp7006201, kgp7151153, kgp7161038, kgp7653470,
kgp7778345, kgp7932108, kgp8145845, kgp8644305, kgp8847137,
kgp9143704, kgp9409440, kgp956070, kgp9909702, kgp9927782,
rs10038844, rs1026894, rs10495115, rs11562998, rs11563025,
rs11750747, rs11947777, rs12043743, rs12233980, rs12341716,
rs12472695, rs12881439, rs13168893, rs13386874, rs1357718,
rs1393037, rs1393040, rs1397481, rs1474226, rs1508515, rs1534647,
rs16846161, rs1715441, rs17187123, rs17245674, rs17419416,
rs1793174, rs1883448, rs1905248, rs209568, rs2354380, rs2618065,
rs263247, rs2662, rs28993969, rs34647183, rs35615951, rs3768769,
rs3847233, rs3858034, rs3858035, rs3858036, rs3858038, rs3894712,
rs4740708, rs4797764, rs4978567, rs528065, rs6459418, rs6577395,
rs6811337, rs7119480, rs7123506, rs7231366, rs7680970, rs7684006,
rs7696391, rs7698655, rs7819949, rs7846783, rs7949751, rs7961005,
rs8000689, rs8018807, rs961090, rs967616, rs9948620 and rs9953274
(hereinafter Group 6), and [0062] (ii) identifying the subject as
predicted to have a slower course of disease progression if the
genotype of the subject contains [0063] one or more A alleles at
the location of kgp10762962, kgp11285883, kgp11604017, kgp1211163,
kgp12253568, kgp12562255, kgp2176915, kgp24521552, kgp2877482,
kgp2993366, kgp3188, kgp3624014, kgp394638, kgp4037661, kgp433351,
kgp4456934, kgp4575797, kgp4591145, kgp4892427, kgp4970670,
kgp4985243, kgp5252824, kgp5326762, kgp541892, kgp5747456,
kgp5894351, kgp6042557, kgp6081880, kgp6194428, kgp6429231,
kgp7006201, kgp7151153, kgp7161038, kgp7653470, kgp8145845,
kgp8644305, kgp9143704, kgp9409440, kgp9909702, kgp9927782,
rs10038844, rs10495115, rs11750747, rs12341716, rs12881439,
rs13168893, rs1393040, rs1474226, rs1534647, rs1715441, rs17187123,
rs17245674, rs17419416, rs1793174, rs1883448, rs1905248, rs263247,
rs34647183, rs35615951, rs3847233, rs3858038, rs4740708, rs528065,
rs6459418, rs6577395, rs6811337, rs7680970, rs7684006, rs7698655,
rs7961005, rs8018807, rs9948620 or rs9953274 (hereinafter Group 7),
[0064] one or more C alleles at the location of kgp10836214,
kgp1432800, kgp22839559, kgp6301155, kgp6828277, rs2354380, rs2662,
rs3858035, rs3894712, rs4797764 or rs7696391 (hereinafter Group 8),
[0065] one or more G alleles at the location of kgp10148554,
kgp10215554, kgp10989246, kgp11755256, kgp1682126, kgp1758575,
kgp2920925, kgp3287349, kgp3420309, kgp3488270, kgp3598966,
kgp3697615, kgp4137144, kgp5691690, kgp5924341, kgp5949515,
kgp6213972, kgp625941, kgp6889327, kgp6990559, kgp7778345,
kgp7932108, kgp8847137, kgp956070, rs1026894, rs11562998,
rs11563025, rs11947777, rs12233980, rs12472695, rs13386874,
rs1357718, rs1393037, rs1397481, rs1508515, rs16846161, rs209568,
rs2618065, rs28993969, rs3768769, rs3858034, rs3858036, rs4978567,
rs7119480, rs7123506, rs7231366, rs7819949, rs7846783, rs7949751,
rs8000689, rs961090 or rs967616 (hereinafter Group 9), or [0066]
one or more T alleles at the location of rs12043743.
[0067] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis who is predicted
to have a slower course of disease progression, the kit comprising
[0068] a) at least one probe specific for a location corresponding
to the location of at least one SNP; [0069] b) at least one pair of
PCR primers designed to amplify a DNA segment which includes a
location corresponding to the location of at least one SNP; [0070]
c) at least one pair of PCR primers designed to amplify a DNA
segment which includes a location corresponding to the location of
at least one SNP and at least one probe specific for a location
corresponding to the location of at least one SNP; [0071] d) a
reagent for performing a method selected from the group consisting
of restriction fragment length polymorphism (RFLP) analysis,
sequencing, single strand conformation polymorphism analysis
(SSCP), chemical cleavage of mismatch (CCM), gene chip and
denaturing high performance liquid chromatography (DHPLC) for
determining the identity of at least one SNP; or [0072] e) reagents
for TaqMan Open Array assay designed for determining the genotype
at a location corresponding to the location of at least one SNP,
[0073] wherein the at least one SNP is selected from the group
consisting of Group 6.
BRIEF DESCRIPTION OF THE DRAWINGS
[0074] FIG. 1 shows Receiver Operating Characteristics for
optimization of test threshold.
[0075] FIG. 2 shows Response Rate of Predicted Responders (green
line) and Response Rate of Predicted Non-Responders (red line) by
predictive test threshold.
[0076] FIG. 3 shows overall percent of Predicted Responders by
predictive test threshold.
[0077] FIG. 4 shows chi square P-values (-Log P-value) of different
test thresholds in the ability of the test to differentiate between
cases and controls. A threshold of 0.71 demonstrated the most
significant p-value.
[0078] FIG. 5 shows overall Response to glatiramer acetate as
Predicted by Model (model 3, threshold 0.71) for Predicted
Responders (left panel) and Predicted Non-Responders (right
panel).
[0079] FIG. 6 shows GALA and FORTE patients were stratified by
clearly defined response. High Response: improved ARR (ARR change
<(-1), during study versus prior 2 years). Low Response: no
change or worsening of ARR (ARR change .gtoreq.0, during study
versus previous 2 years).
[0080] FIG. 7 shows predictive model building for GALA and FORTE
cohorts.
[0081] FIG. 8 shows the algorithm and calculation of values for all
genotyped patients of the Gala and FORTE cohorts, based on the
predictive model (11 SNPs and 2 clinical variables).
[0082] FIG. 9 shows the algorithm and calculation of values for all
genotyped patients of the Gala and FORTE cohorts, based on the 11
SNPs in the predictive model, without including the clinical
variables, and using a threshold at .about.30% of the population
classified as "predicted responders".
DETAILED DESCRIPTION OF THE INVENTION
Embodiments of the Invention
[0083] The present invention provides a method for treating a human
subject afflicted with multiple sclerosis or a single clinical
attack consistent with multiple sclerosis with a pharmaceutical
composition comprising glatiramer acetate and a pharmaceutically
acceptable carrier, comprising the steps of: [0084] (i) determining
a genotype of the subject at a location corresponding to the
location of one or more single nucleotide polymorphisms (SNPs)
selected from the group consisting of: Group 1, [0085] (ii)
identifying the subject as a predicted responder to glatiramer
acetate if the genotype of the subject contains [0086] one or more
A alleles at the location of Group 2, [0087] one or more C alleles
at the location of Group 3, [0088] one or more G alleles at the
location of Group 4, or [0089] one or more T alleles at the
location of kgp18432055, kgp279772, kgp3991733 or kgp7242489; and
[0090] (iii) administering the pharmaceutical composition
comprising glatiramer acetate and a pharmaceutically acceptable
carrier to the subject only if the subject is identified as a
predicted responder to glatiramer acetate.
[0091] In some embodiments step (i) further comprises determining a
genotype of the subject at a location corresponding to the location
of one or more single nucleotide polymorphisms (SNPs) selected from
the group consisting of: rs10988087, rs1573706, rs17575455,
rs2487896, rs3135391, rs6097801 and rs947603, and wherein step (ii)
further comprises identifying the subject as a predicted responder
to glatiramer acetate if the genotype of the subject contains one
or more A alleles at the location of rs10988087, one or more C
alleles at the location of rs17575455, or one or more G alleles at
the location of rs1573706, rs2487896, rs3135391, rs6097801 or
rs947603.
[0092] In some embodiments administering the pharmaceutical
composition comprising glatiramer acetate and a pharmaceutically
acceptable carrier comprises administering to the human subject
three subcutaneous injections of the pharmaceutical composition
over a period of seven days with at least one day between every
subcutaneous injection.
[0093] In some embodiments the pharmaceutical composition is a unit
dose of a 1 ml aqueous solution comprising 40 mg of glatiramer
acetate.
[0094] In some embodiments the pharmaceutical composition is a unit
dose of a 1 ml aqueous solution comprising 20 mg of glatiramer
acetate.
[0095] In some embodiments the pharmaceutical composition is a unit
dose of a 0.5 ml aqueous solution comprising 20 mg of glatiramer
acetate.
[0096] In some embodiments the pharmaceutical composition
comprising glatiramer acetate and a pharmaceutically acceptable
carrier is administered as a monotherapy.
[0097] In some embodiments the pharmaceutical composition
comprising glatiramer acetate and a pharmaceutically acceptable
carrier is administered in combination with at least one other
multiple sclerosis drug.
[0098] The present invention also provides a method of identifying
a human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the method comprising determining the genotype of the subject at a
location corresponding to the location of one or more single
nucleotide polymorphisms (SNPs) selected from the group consisting
of Group 1, and
identifying the human subject as a predicted responder to
glatiramer acetate if the genotype of the subject contains [0099]
one or more A alleles at the location of Group 2, [0100] one or
more C alleles at the location of Group 3, [0101] one or more G
alleles at the location of Group 4, or [0102] one or more T alleles
at the location of kgp18432055, kgp279772, kgp3991733 or
kgp7242489, [0103] or identifying the human subject as a predicted
non-responder to glatiramer acetate if the genotype of the subject
contains [0104] no A alleles at the location of Group 2, [0105] no
C alleles at the location of Group 3, [0106] no G alleles at the
location of Group 4, or [0107] no T alleles at the location of
kgp18432055, kgp279772, kgp3991733 or kgp7242489.
[0108] In some embodiments the methods further comprise determining
a genotype of the subject at a location corresponding to the
location of one or more SNPs selected from the group consisting of:
rs10988087, rs1573706, rs17575455, rs2487896, rs3135391, rs6097801
and rs947603, and identifying the human subject as a predicted
responder to glatiramer acetate if the genotype of the subject
contains one or more A alleles at the location of rs10988087, one
or more C alleles at the location of rs17575455, or one or more G
alleles at the location of rs1573706, rs2487896, rs3135391,
rs6097801 or rs947603, or identifying the human subject as a
predicted non-responder to glatiramer acetate if the genotype of
the subject contains no A alleles at the location of rs10988087, no
C alleles at the location of rs17575455, or no G alleles at the
location of rs1573706, rs2487896, rs3135391, rs6097801 or rs947603.
In some embodiments the genotype is determined from a nucleic
acid-containing sample that has been obtained from the subject.
[0109] In some embodiments determining the genotype comprises using
a method selected from the group consisting of restriction fragment
length polymorphism (RFLP) analysis, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), denaturing high performance liquid chromatography
(DHPLC), Polymerase Chain Reaction (PCR) and an array, or a
combination thereof.
[0110] In some embodiment, applying the algorithm depicted in FIG.
8 or in FIG. 9 to identify the subject as a predicted responder or
as a predicted non-responder to glatiramer acetate.
[0111] In some embodiments the genotype is determined using at
least one pair of PCR primers and at least one probe.
[0112] In some embodiments the array is selected from the group
consisting of a gene chip, and a TaqMan Open Array.
[0113] In some embodiments the gene chip is selected from the group
consisting of a DNA array, a DNA microarray, a DNA chip, and a
whole genome genotyping array.
[0114] In some embodiments the array is a TaqMan Open Array.
[0115] In some embodiments the gene chip is a whole genome
genotyping array.
[0116] In some embodiments determining the genotype of the subject
at the location corresponding to the location of the said one or
more SNPs comprises: [0117] (i) obtaining DNA from a sample that
has been obtained from the subject; [0118] (ii) optionally
amplifying the DNA; and [0119] (iii) subjecting the DNA or the
amplified DNA to a method selected from the group consisting of
restriction fragment length polymorphism (RFLP) analysis,
sequencing, single strand conformation polymorphism analysis
(SSCP), chemical cleavage of mismatch (CCM), denaturing high
performance liquid chromatography (DHPLC), Polymerase Chain
Reaction (PCR) and an array, or a combination thereof, for
determining the identity the one or more SNPs.
[0120] In some embodiments the array comprises a plurality of
probes suitable for determining the identity of the one or more
SNPs.
[0121] In some embodiments the array is a gene chip.
[0122] In some embodiments the gene chip is a whole genome
genotyping array.
[0123] In some embodiments the human subject is a naive
patient.
[0124] In some embodiments the human subject has been previously
administered glatiramer acetate.
[0125] In some embodiments the human subject has been previously
administered a multiple sclerosis drug other than glatiramer
acetate.
[0126] In some embodiments the genotype is determined at locations
corresponding to the locations of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16 or more single nucleotide polymorphisms
(SNPs).
[0127] In some embodiments the one or more SNPs is selected from
the group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp7747883, kgp8110667, kgp8817856, rs10162089, rs16886004,
rs1894408 and rs759458 (hereinafter Group 10).
[0128] In some embodiments the one or more SNPs is selected from
the group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp7747883, kgp8110667, kgp8817856, rs10162089, rs16886004,
rs1894408, rs3135391, and rs759458.
[0129] In some embodiments the one or more SNPs is selected from
the group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408,
rs3135391, and rs759458.
[0130] In some embodiments, if rs3135391 is the at least one SNP
selected, then selecting at least one SNP other than rs3135391.
[0131] In some embodiments the one or more SNPs comprise 2, 3, 4,
5, 6, 7, 8, 9 or 10 of the SNPs selected from the group consisting
of Group 10.
[0132] In some embodiments the one or more SNPs further comprise
rs3135391.
[0133] In some embodiments the one or more SNPs comprise 2, 3, 4,
5, 6, 7, 8, 9, 10, or 11 of the SNPs selected from the group
consisting of kgp24415534, kgp6214351, kgp6599438, kgp7747883,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408,
rs3135391 and rs759458.
[0134] In some embodiments the one or more single nucleotide
polymorphisms (SNPs) further comprise 2, 3, 4, 5, 6, 7, 8, 9 or 10
of the SNPs selected from the group consisting of kgp24415534,
kgp6214351, kgp6599438, kgp8110667, kgp8817856, rs10162089,
rs16886004, rs1894408, rs3135391 and rs759458.
[0135] In some embodiments the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined indirectly by determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs.
[0136] In some embodiments the genotype of the subject at the
location corresponding to the location of the one or more SNPs is
determined by indirect genotyping.
[0137] In some embodiments the indirect genotyping allows
identification of the genotype of the subject at the location
corresponding to the location of the one or more SNPs with a
probability of at least 85%.
[0138] In some embodiments the indirect genotyping allows
identification of the genotype of the subject at the location
corresponding to the location of the one or more SNPs with a
probability of at least 90%.
[0139] In some embodiments the indirect genotyping allows
identification of the genotype of the subject at the location
corresponding to the location of the one or more SNPs with a
probability of at least 99%.
[0140] In some embodiments the methods further comprise the step of
determining the log number of relapses in the last two years for
the human subject.
[0141] In some embodiments the methods further comprise the step of
determining the baseline Expanded Disability Status Scale (EDSS)
score for the human subject.
[0142] In some embodiments the methods further comprise determining
the genotype of the subject at a location corresponding to the
location of one or more single nucleotide polymorphisms (SNPs)
selected from the group consisting of: Group 6, and
identifying the human subject as a predicted responder to
glatiramer acetate if the genotype of the subject contains [0143]
one or more A alleles at the location of Group 7, [0144] one or
more C alleles at the location of Group 8, [0145] one or more G
alleles at the location of Group 9, or [0146] one or more T alleles
at the location of rs12043743.
[0147] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising at least one probe specific for the location of
a SNP selected from the group consisting of Group 1.
[0148] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising at least one pair of PCR primers designed to
amplify a DNA segment which includes the location of a SNP selected
from the group consisting of Group 1.
[0149] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising a reagent for performing a method selected from
the group consisting of restriction fragment length polymorphism
(RFLP) analysis, sequencing, single strand conformation
polymorphism analysis (SSCP), chemical cleavage of mismatch (CCM),
gene chip and denaturing high performance liquid chromatography
(DHPLC) for determining the genotype of the subject at a location
corresponding to the location of at least one SNP selected from the
group consisting of Group 1.
[0150] In some embodiments the gene chip is a whole genome
genotyping array.
[0151] In some embodiments the kit comprises [0152] (i) at least
one pair of PCR primers designed to amplify a DNA segment which
includes the location a SNP selected from the group consisting of
Group 1, and [0153] (ii) at least one probe specific for the
location of a SNP selected from the group consisting of Group
1.
[0154] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising reagents for TaqMan Open Array assay designed
for determining the genotype of the subject at a location
corresponding to the location of at least one SNP selected from the
group consisting of Group 1.
[0155] In some embodiments the kit further comprises instructions
for use of the kit for identifying a human subject afflicted with
multiple sclerosis or a single clinical attack consistent with
multiple sclerosis as a predicted responder or as a predicted
non-responder to glatiramer acetate.
[0156] In some embodiments the one or more single nucleotide
polymorphisms (SNPs) are selected from the group consisting of
Group 10.
[0157] In some embodiments the one or more single nucleotide
polymorphisms (SNPs) comprise 2, 3, 4, 5, 6, 7, 8, 9 or 10 of the
SNPs selected from the group consisting of Group 10.
[0158] In some embodiments the one or more SNPs further comprise
rs3135391.
[0159] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis as a predicted
responder or as a predicted non-responder to glatiramer acetate,
the kit comprising [0160] a) at least one probe specific for a
location corresponding to the location of at least one SNP; [0161]
b) at least one pair of PCR primers designed to amplify a DNA
segment which includes a location corresponding to the location of
at least one SNP; [0162] c) at least one pair of PCR primers
designed to amplify a DNA segment which includes a location
corresponding to the location of at least one SNP and at least one
probe specific for a location corresponding to the location of at
least one SNP; [0163] d) a reagent for performing a method selected
from the group consisting of restriction fragment length
polymorphism (RFLP) analysis, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), gene chip and denaturing high performance liquid
chromatography (DHPLC) for determining the identity of at least one
SNP; or [0164] e) reagents for TaqMan Open Array assay designed for
determining the genotype at a location corresponding to the
location of at least one SNP, [0165] wherein the at least one SNP
is selected from the group consisting of Group 1.
[0166] In some embodiments the at least one single nucleotide
polymorphisms (SNPs) are selected from the group consisting of
Group 10,
preferably wherein the kit further comprises instructions for use
of the kit for identifying a human subject afflicted with multiple
sclerosis or a single clinical attack consistent with multiple
sclerosis as a predicted responder or as a predicted non-responder
to glatiramer acetate.
[0167] In some embodiments the at least one single nucleotide
polymorphisms (SNPs) comprise 2, 3, 4, 5, 6, 7, 8, 9 or 10 of the
SNPs selected from the group consisting of Group 10.
[0168] In some embodiments the at least one single nucleotide
polymorphisms (SNPs) further comprise rs3135391.
[0169] In some embodiments the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined by indirect genotyping,
[0170] In some embodiments the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined indirectly by determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs.
[0171] In some embodiments the kit comprises [0172] a) at least one
probe specific for a location corresponding to the location of at
least one SNP; [0173] b) at least one pair of PCR primers designed
to amplify a DNA segment which includes a location corresponding to
the location of at least one SNP; [0174] c) at least one pair of
PCR primers designed to amplify a DNA segment which includes a
location corresponding to the location of at least one SNP and at
least one probe specific for a location corresponding to the
location of at least one SNP; [0175] d) a reagent for performing a
method selected from the group consisting of restriction fragment
length polymorphism (RFLP) analysis, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), gene chip and denaturing high performance liquid
chromatography (DHPLC) for determining the identity of at least one
SNP; or [0176] e) reagents for TaqMan Open Array assay designed for
determining the genotype at a location corresponding to the
location of at least one SNP, [0177] wherein the at least one SNP
is in linkage disequilibrium with the one or more SNPs.
[0178] In some embodiments determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs allows
identification of the genotype of the subject at the location
corresponding to the location of the one or more SNPs with a
probability of at least 85%.
[0179] In some embodiments determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs allows
identification of the genotype of the subject at the location
corresponding to the location of the one or more SNPs with a
probability of at least 90%.
[0180] In some embodiments determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs allows
identification of the genotype of the subject at the location
corresponding to the location of the one or more SNPs with a
probability of at least 99%.
[0181] The present invention also provides a probe for identifying
the genotype of a location corresponding to the location of a SNP
selected from the group consisting of Group 5.
[0182] The present invention also provides a probe for identifying
the genotype of a location corresponding to the location of a SNP
selected from the group consisting of kgp24415534, kgp6214351,
kgp6599438, kgp7747883, kgp8110667, kgp8817856, rs10162089,
rs16886004, rs1894408, rs3135391, and rs759458.
[0183] In some embodiments the SNP is in linkage disequilibrium
with the one or more SNPs.
[0184] The present invention also provides glatiramer acetate or a
pharmaceutical composition comprising glatiramer acetate for use in
treating a human subject afflicted with multiple sclerosis or a
single clinical attack consistent with multiple sclerosis which
human subject is identified as a predicted responder to glatiramer
acetate by: [0185] a) determining a genotype of the subject at a
location corresponding to the location of one or more single
nucleotide polymorphisms (SNPs) selected from the group consisting
of: Group 1, and [0186] b) identifying the subject as a predicted
responder to glatiramer acetate if the genotype of the subject
contains [0187] one or more A alleles at the location of Group 2,
[0188] one or more C alleles at the location of Group 3, [0189] one
or more G alleles at the location of Group 4, or [0190] one or more
T alleles at the location of kgp18432055, kgp279772, kgp3991733 or
kgp7242489.
[0191] In some embodiments the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined indirectly by determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs.
[0192] The present invention also provides a method of determining
the genotype of a human subject comprising identifying whether the
genotype of a human subject contains [0193] one or more A alleles
at the location of Group 2, [0194] one or more C alleles at the
location of Group 3, [0195] one or more G alleles at the location
of Group 4, or [0196] one or more T alleles at the location of
kgp18432055, kgp279772, kgp3991733 or kgp7242489.
[0197] In some embodiments identifying whether the genotype of a
human subject contains [0198] one or more A alleles at the location
of Group 2, [0199] one or more C alleles at the location of Group
3, [0200] one or more G alleles at the location of Group 4, or
[0201] one or more T alleles at the location of kgp18432055,
kgp279772, kgp3991733 or kgp7242489 is determined indirectly by
determining the genotype of the subject at a location corresponding
to the location of at least one SNP that is in linkage
disequilibrium with the one or more SNPs.
[0202] The present invention also provides a method of determining
the genotype of a human subject comprising identifying the genotype
of a human subject at the location of kgp6214351, kgp6599438,
kgp7747883, kgp8110667, kgp8817856, rs10162089, rs16886004,
rs1894408, rs3135391, or rs759458.
[0203] The present invention also provides a method of identifying
a human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis who is predicted
to have a slower course of disease progression, comprising the
steps of: [0204] (i) determining a genotype of the subject at a
location corresponding to the location of one or more single
nucleotide polymorphisms (SNPs) selected from the group consisting
of: Group 6, and [0205] (ii) identifying the subject as predicted
to have a slower course of disease progression if the genotype of
the subject contains [0206] one or more A alleles at the location
of Group 7, [0207] one or more C alleles at the location of Group
8, [0208] one or more G alleles at the location of Group 9, or
[0209] one or more T alleles at the location of rs12043743.
[0210] In some embodiments the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined indirectly by determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs.
[0211] The present invention also provides a kit for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis who is predicted
to have a slower course of disease progression, the kit comprising
[0212] a) at least one probe specific for a location corresponding
to the location of at least one SNP; [0213] b) at least one pair of
PCR primers designed to amplify a DNA segment which includes a
location corresponding to the location of at least one SNP; [0214]
c) at least one pair of PCR primers designed to amplify a DNA
segment which includes a location corresponding to the location of
at least one SNP and at least one probe specific for a location
corresponding to the location of at least one SNP; [0215] d) a
reagent for performing a method selected from the group consisting
of restriction fragment length polymorphism (RFLP) analysis,
sequencing, single strand conformation polymorphism analysis
(SSCP), chemical cleavage of mismatch (CCM), gene chip and
denaturing high performance liquid chromatography (DHPLC) for
determining the identity of at least one SNP; or [0216] e) reagents
for TaqMan Open Array assay designed for determining the genotype
at a location corresponding to the location of at least one SNP,
[0217] wherein the at least one SNP is selected from the group
consisting of Group 6.
[0218] For the foregoing embodiments, each embodiment disclosed
herein is contemplated as being applicable to each of the other
disclosed embodiments. Thus, all combinations of the various
elements described herein are within the scope of the
invention.
Definitions
[0219] As used herein, a genetic marker refers to a DNA sequence
that has a known location on a chromosome. Several non-limiting
examples of classes of genetic markers include SNP (single
nucleotide polymorphism), STR (short tandem repeat), and SFP
(single feature polymorphism). VNTR (variable number tandem
repeat), microsatellite polymorphism, insertions and deletions. The
genetic markers associated with the invention are SNPs. As used
herein a SNP or "single nucleotide polymorphism" refers to a
specific site in the genome where there is a difference in DNA base
between individuals. In some embodiments the SNP is located in a
coding region of a gene. In other embodiments the SNP is located in
a noncoding region of a gene. In still other embodiments the SNP is
located in an intergenic region.
[0220] Several non-limiting examples of databases from which
information on SNPs or genes that are associated with human disease
can be retrieved include: NCBI resources, The SNP Consortium LTD,
NCBI dbSNP database, International HapMap Project, 1000 Genomes
Project, Glovar Variation Browser, SNPStats, PharmGKB, GEN-SniP,
and SNPedia.
[0221] SNPs are identified herein using the rs identifier numbers
in accordance with the NCBI dbSNP database, which is publically
available at: ncbi.nlm.nih.gov/projects/SNP/ or using the kgp
identifier numbers, which were created by Illumina. Genotype at the
kgp SNPs can be obtained by using the Illumina genotyping arrays.
In addition, SNPs can be identified by the specific location on the
chromosome indicated for the specific SNP.
[0222] Additional information about identifying SNPs can be
obtained from the NCBI database SNP FAQ archive located at
ncbi.nlm.nih.gov/books/NBK3848/ or from literature available on the
Illumina website located at
illumina.com/applications/genotyping/literature.ilmn.
[0223] In some embodiments, SNPs in linkage disequilibrium with the
SNPs associated with the invention are useful for obtaining similar
results. As used herein, linkage disequilibrium refers to the
non-random association of SNPs at one loci. Techniques for the
measurement of linkage disequilibrium are known in the art. As two
SNPs are in linkage disequilibrium if they are inherited together,
the information they provide is correlated to a certain extent.
SNPs in linkage disequilibrium with the SNPs included in the models
can be obtained from databases such as HapMap or other related
databases, from experimental setups run in laboratories or from
computer-aided in-silico experiments. Determining the genotype of a
subject at a position of SNP as specified herein, e.g. as specified
by NCBI dbSNP rs identifier, may comprise "direct genotyping", e.g.
by determining the identity of the nucleotide of each allele at the
locus of SNP, and/or "indirect genotyping", defined herein as
evaluating/determining the identity of an allele at one or more
loci that are in linkage disequilibrium with the SNP in question,
allowing one to infer the identity of the allele at the locus of
SNP in question with a substantial degree of confidence. In some
cases, indirect genotyping may comprise determining the identity of
each allele at one or more loci that are in sufficiently high
linkage disequilibrium with the SNP in question so as to allow one
to infer the identity of each allele at the locus of SNP in
question with a probability of at least 85%, at least 90% or at
least 99% certainty.
[0224] A genotype at a position of SNP (genotype "at a" SNP) may be
represented by a single letter which corresponds to the identity of
the nucleotide at the SNP, where A represents adenine, T represents
thymine, C represents cytosine, and G represents guanine. The
identity of two alleles at a single SNP may be represented by a two
letter combination of A, T, C, and G, where the first letter of the
two letter combination represents one allele and the second letter
represents the second allele, and where A represents adenine, T
represents thymine, C represents cytosine, and G represents
guanine. Thus, a two allele genotype at a SNP can be represented
as, for example, AA, AT, AG, AC, TT, TG, TC, GG, GC, or CC. It is
understood that AT, AG, AC, TG, TC, and GC are equivalent to TA,
GA, CA, GT, CT, and CG, respectively.
[0225] The SNPs of the invention can be used as predictive
indicators of the response to GA in subjects afflicted with
multiple sclerosis or a single clinical attack consistent with
multiple sclerosis. Aspects of the invention relate to determining
the presence of SNPs through obtaining a patient DNA sample and
evaluating the patient sample for the presence of one or more SNPs,
or for a certain set of SNPs. It should be appreciated that a
patient DNA sample can be extracted, and a SNP can be detected in
the sample, through any means known to one of ordinary skill in
art. Some non-limiting examples of known techniques include
detection via restriction fragment length polymorphism (RFLP)
analysis, arrays including but not limited to planar microarrays or
bead arrays, sequencing, single strand conformation polymorphism
analysis (SSCP), chemical cleavage of mismatch (CCM), Polymerase
chain reaction (PCR) and denaturing high performance liquid
chromatography (DHPLC).
[0226] In some embodiments, the genotyping array is a whole genome
genotyping array. In some embodiments, the Whole-genome genotyping
arrays as defined here are arrays that contain hundreds of
thousands to millions of genetic sequences (which may also be named
"probes"). In some embodiments, Whole-genome genotyping arrays
contain 500,000 probes or more. In some embodiments, Whole-genome
genotyping arrays contain 1 million probes or more. In some
embodiments, Whole-genome genotyping arrays contain 5 million
probes or more.
[0227] In some embodiments, a SNP is detected through PCR
amplification and sequencing of the DNA region comprising the SNP.
In some embodiments SNPs are detected using arrays, exemplified by
gene chip, including but not limited to DNA arrays or microarrays,
DNA chips, and whole genome genotyping arrays, all of which may be
for example planar arrays or bead arrays, or a TaqMan open Array.
Arrays/Microarrays for detection of genetic polymorphisms, changes
or mutations (in general, genetic variations) such as a SNP in a
DNA sequence, may comprise a solid surface, typically glass, on
which a high number of genetic sequences are deposited (the
probes), complementary to the genetic variations to be studied.
Using standard robotic printers to apply probes to the array a high
density of individual probe features can be obtained, for example
probe densities of 600 features per cm.sup.2 or more can be
typically achieved. The positioning of probes on an array is
precisely controlled by the printing device (robot, inkjet printer,
photolithographic mask etc) and probes are aligned in a grid. The
organization of probes on the array facilitates the subsequent
identification of specific probe-target interactions. Additionally
it is common, but not necessary, to divide the array features into
smaller sectors, also grid-shaped, that are subsequently referred
to as sub-arrays. Sub-arrays typically comprise 32 individual probe
features although lower (e.g. 16) or higher (e.g. 64 or more)
features can comprise each sub-array. In some arrays the probes are
connected to beads instead of the solid support. Such arrays are
called "bead arrays" or "bead CHIPs".
[0228] In some embodiments, detection of genetic variation such as
the presence of a SNP involves hybridization to sequences which
specifically recognize the normal and the mutant allele in a
fragment of DNA derived from a test sample. Typically, the fragment
has been amplified, e.g. by using the polymerase chain reaction
(PCR), and labeled e.g. with a fluorescent molecule. A laser can be
used to detect bound labeled fragments on the chip and thus an
individual who is homozygous for the normal allele can be
specifically distinguished from heterozygous individuals (in the
case of autosomal dominant conditions then these individuals are
referred to as carriers) or those who are homozygous for the mutant
allele. In some embodiments, the amplification reaction and/or
extension reaction is carried out on the microarray or bead itself.
For differential hybridization based methods there are a number of
methods for analyzing hybridization data for genotyping: Increase
in hybridization level: The hybridization levels of probes
complementary to the normal and mutant alleles are compared.
Decrease in hybridization level: Differences in the sequence
between a control sample and a test sample can be identified by a
decrease in the hybridization level of the totally complementary
oligonucleotides with a reference sequence. A loss approximating
100% is produced in mutant homozygous individuals while there is
only an approximately 50% loss in heterozygotes. In Microarrays for
examining all the bases of a sequence of "n" nucleotides
("oligonucleotide") of length in both strands, a minimum of "2n"
oligonucleotides that overlap with the previous oligonucleotide in
all the sequence except in the nucleotide are necessary. Typically
the size of the oligonucleotides is about 25 nucleotides. However
it should be appreciated that the oligonucleotide can be any length
that is appropriate as would be understood by one of ordinary skill
in the art. The increased number of oligonucleotides used to
reconstruct the sequence reduces errors derived from fluctuation of
the hybridization level.
[0229] However, the exact change in sequence cannot be identified
with this method; in some embodiments this method is combined with
sequencing to identify the mutation. Where amplification or
extension is carried out on the microarray or bead itself, three
methods are presented by way of example: In the Minisequencing
strategy, a mutation specific primer is fixed on the slide and
after an extension reaction with fluorescent dideoxynucleotides,
the image of the Microarray is captured with a scanner. In the
Primer extension strategy, two oligonucleotides are designed for
detection of the wild type and mutant sequences respectively. The
extension reaction is subsequently carried out with one
fluorescently labeled nucleotide and the remaining nucleotides
unlabelled. In either case the starting material can be either an
RNA sample or a DNA product amplified by PCR. In the Tag arrays
strategy, an extension reaction is carried out in solution with
specific primers, which carry a determined 5.sup.1 sequence or
"tag". The use of Microarrays with oligonucleotides complementary
to these sequences or "tags" allows the capture of the resultant
products of the extension. Examples of this include the high
density Microarray "Flex-flex" (Affymetrix). In the Illumina 1M Dou
BeadChip array
(illumina.com/products/human1m_duo_dna_analysis_beadchip_kits.ilmn),
SNP genotypes are generated from fluorescent intensities using the
manufacturer's default cluster settings.
[0230] In some aspects of the invention measurement of clinical
variables comprises part of the prediction model predicting
response to GA along with the genetic variables. Some non-limiting
examples are age of the patient (in years), gender of patient,
clinical manifestations, MRI parameter, country, ancestry, and
years of exposure to treatment) "Clinical manifestations" include
but are not limited to EDSS score such as baseline EDSS score, log
of number of relapses in last 2 Years and relapse rate. "MRI
parameters" include but are not limited to the volume and/or number
of T1 enhancing lesions and/or T2 enhancing lesions; exemplified by
baseline volume of T2 lesion, number of Gd-T1 lesions at baseline.
In certain aspect of the invention, the clinical variables taken
into account are as measured at the time of the decision about the
treatment suitable for the patient, or measured at a time point
determined by the physician, researcher or other professional
involved in the decision.
[0231] The identification of a patient as a responder or as a
non-responder to GA based on the presence of at least one SNP from
tables 2-32 and 34-44, a set of SNPs from tables 2-32 and 34-44, or
the combination of a SNP or a set of SNPs from tables 2-32 and
34-44 with one or more clinical variables described above, may be
used for predicting response to GA.
[0232] Also within the scope of the invention are kits and
instructions for their use. In some embodiments kits associated
with the invention are kits for identifying one or more SNPs within
a patient sample. In some embodiments a kit may contain primers for
amplifying a specific genetic locus. In some embodiments, a kit may
contain a probe for hybridizing to a specific SNP. The kit of the
invention can include reagents for conducting each of the following
assays including but not limited to restriction fragment length
polymorphism (RFLP) analysis, arrays including but not limited to
planar microarrays or bead arrays, sequencing, single strand
conformation polymorphism analysis (SSCP), chemical cleavage of
mismatch (CCM), and denaturing high performance liquid
chromatography (DHPLC), PCR amplification and sequencing of the DNA
region comprising the SNP. A kit of the invention can include a
description of use of the contents of the kit for participation in
any biological or chemical mechanism disclosed herein. A kit can
include instructions for use of the kit components alone or in
combination with other methods or compositions for assisting in
screening or diagnosing a sample and/or determining whether a
subject is a responder or a non-responder to GA.
Forms of Multiple Sclerosis:
[0233] There are five distinct disease stages and/or types of MS:
[0234] 1) benign multiple sclerosis; [0235] 2) relapsing-remitting
multiple sclerosis (RRMS); [0236] 3) secondary progressive multiple
sclerosis (SPMS); [0237] 4) progressive relapsing multiple
sclerosis (PRMS); and [0238] 5) primary progressive multiple
sclerosis (PPMS).
[0239] Benign multiple sclerosis is a retrospective diagnosis which
is characterized by 1-2 exacerbations with complete recovery, no
lasting disability and no disease progression for 10-15 years after
the initial onset. Benign multiple sclerosis may, however, progress
into other forms of multiple sclerosis.
[0240] Patients suffering from RRMS experience sporadic
exacerbations or relapses, as well as periods of remission. Lesions
and evidence of axonal loss may or may not be visible on MRI for
patients with RRMS. SPMS may evolve from RRMS. Patients afflicted
with SPMS have relapses, a diminishing degree of recovery during
remissions, less frequent remissions and more pronounced
neurological deficits than RRMS patients. Enlarged ventricles,
which are markers for atrophy of the corpus callosum, midline
center and spinal cord, are visible on MRI of patients with
SPMS.
[0241] PPMS is characterized by a steady progression of increasing
neurological deficits without distinct attacks or remissions.
Cerebral lesions, diffuse spinal cord damage and evidence of axonal
loss are evident on the MRI of patients with PPMS. PPMS has periods
of acute exacerbations while proceeding along a course of
increasing neurological deficits without remissions. Lesions are
evident on MRI of patients suffering from PRMS.(28)
[0242] A clinically isolated syndrome (CIS) is a single
monosymptomatic attack compatible with MS, such as optic neuritis,
brain stem symptoms, and partial myelitis. Patients with CIS that
experience a second clinical attack are generally considered to
have clinically definite multiple sclerosis (CDMS). Over 80 percent
of patients with a CIS and MRI lesions go on to develop MS, while
approximately 20 percent have a self-limited process.(29,30)
Patients who experience a single clinical attack consistent with MS
may have at least one lesion consistent with multiple sclerosis
prior to the development of clinically definite multiple
sclerosis.
[0243] Multiple sclerosis may present with optic neuritis, blurring
of vision, diplopia, involuntary rapid eye movement, blindness,
loss of balance, tremors, ataxia, vertigo, clumsiness of a limb,
lack of co-ordination, weakness of one or more extremity, altered
muscle tone, muscle stiffness, spasms, tingling, paraesthesia,
burning sensations, muscle pains, facial pain, trigeminal
neuralgia, stabbing sharp pains, burning tingling pain, slowing of
speech, slurring of words, changes in rhythm of speech, dysphagia,
fatigue, bladder problems (including urgency, frequency, incomplete
emptying and incontinence), bowel problems (including constipation
and loss of bowel control), impotence, diminished sexual arousal,
loss of sensation, sensitivity to heat, loss of short term memory,
loss of concentration, or loss of judgment or reasoning.
Relapsing Form of Multiple Sclerosis:
[0244] The term relapsing MS includes: [0245] 1) patients with
RRMS; [0246] 2) patients with SPMS and superimposed relapses; and
[0247] 3) patients with CIS who show lesion dissemination on
subsequent MRI scans according to McDonald's criteria.
[0248] As used herein, relapsing forms of multiple sclerosis
include:
Relapsing-remitting multiple sclerosis (RRMS), characterized by
unpredictable acute episodes of neurological dysfunction
(relapses), followed by variable recovery and periods of clinical
stability; Secondary Progressive MS (SPMS), wherein patients having
RRMS develop sustained deterioration with or without relapses
superimposed; and Primary progressive-relapsing multiple sclerosis
(PPRMS) or progressive-relapsing multiple sclerosis (PRMS), an
uncommon form wherein patients developing a progressive
deterioration from the beginning can also develop relapses later
on.
Kurtzke Expanded Disability Status Scale (EDSS):
[0249] The Kurtzke Expanded Disability Status Scale (EDSS) is a
method of quantifying disability in multiple sclerosis. The EDSS
replaced the previous Disability Status Scales which used to bunch
people with MS in the lower brackets. The EDSS quantifies
disability in eight Functional Systems (FS) and allows neurologists
to assign a Functional System Score (FSS) in each of these. The
Functional Systems are: pyramidal, cerebellar, brainstem, sensory,
bowel and bladder, visual & cerebral (according to
mult-sclerosis.org/expandeddisabilitystatusscale).
Clinical Relapse:
[0250] A clinical relapse, which may also be used herein as
"relapse," "confirmed relapse," or "clinically defined relapse," is
defined as the appearance of one or more new neurological
abnormalities or the reappearance of one or more previously
observed neurological abnormalities.
[0251] This change in clinical state must last at least 48 hours
and be immediately preceded by a relatively stable or improving
neurological state of at least 30 days. This criterion is different
from the clinical definition of exacerbation "at least 24 hours
duration of symptoms," (31) as detailed in the section "relapse
evaluation."
[0252] An event is counted as a relapse only when the subject's
symptoms are accompanied by observed objective neurological
changes, consistent with:
a) an increase of at least 0.5 in the EDSS score or one grade in
the score of two or more of the seven FS (32); or, b) two grades in
the score of one of FS as compared to the previous evaluation.
[0253] The subject must not be undergoing any acute metabolic
changes such as fever or other medical abnormality. A change in
bowel/bladder function or in cognitive function must not be
entirely responsible for the changes in EDSS or FS scores.
[0254] As used herein, a "multiple sclerosis drug" is a drug or an
agent intended to treat clinically defined MS, CIS, any form of
neurodegenerative or demyelinating diseases, or symptoms of any of
the above mentioned diseases. "Multiple sclerosis drugs" may
include but are not limited to antibodies, immunosuppressants,
anti-inflammatory agents, immunomodulators, cytokines, cytotoxic
agents and steroids and may include approved drugs, drugs in
clinical trial, or alternative treatments, intended to treat
clinically defined MS, CIS or any form of neurodegenerative or
demyelinating diseases. "Multiple sclerosis drugs" include but are
not limited to Interferon and its derivatives (including
BETASERON.RTM., AVONEX.RTM. and REBIF.RTM.), Mitoxantrone and
Natalizumab. Agents approved or in-trial for the treatment of other
autoimmune diseases, but used in a MS or CIS patient to treat MS or
CIS are also defined as multiple sclerosis drugs.
[0255] As used herein, a "naive patient" is a subject that has not
been treated with any multiple sclerosis drugs as defined in the
former paragraph.
[0256] The administration of glatiramer acetate may be oral, nasal,
pulmonary, parenteral, intravenous, intra-articular, transdermal,
intradermal, subcutaneous, topical, intramuscular, rectal,
intrathecal, intraocular, buccal or by gavage.
[0257] As used herein, "GALA" is a phase 3 clinical trial entitled
"A Study in Subjects With Relapsing-Remitting Multiple Sclerosis
(RRMS) to Assess the Efficacy, Safety and Tolerability of
Glatiramer Acetate (GA) Injection 40 mg Administered Three Times a
Week Compared to Placebo (GALA)." The GALA trial has the
ClinicalTrials.gov Identifier NCT01067521, and additional
information about the trial can be found at
clinicaltrials.gov/ct2/show/NCT01067521.
[0258] As used herein, "FORTE" is a phase 3 clinical trial entitled
"Clinical Trial Comparing Treatment of Relapsing-Remitting Multiple
Sclerosis (RR-MS) With Two Doses of Glatiramer Acetate (GA)." The
FORTE trial has the ClinicalTrials.gov Identifier NCT00337779 and
additional information, including study results can be found at
clinicaltrials.gov/ct2/show/NCT00337779.
[0259] As used herein, "about" with regard to a stated number
encompasses a range of +10 percent to -10 percent of the stated
value. By way of example, about 100 mg/kg therefore includes the
range 90-100 mg/kg and therefore also includes 90, 91, 92, 93, 94,
95, 96, 97, 98, 99, 100, 101, 102, 103, 104, 105, 106, 107, 108,
109 and 110 mg/kg. Accordingly, about 100 mg/kg includes, in an
embodiment, 100 mg/kg.
[0260] It is understood that where a parameter range is provided,
all integers within that range, tenths thereof, and hundredths
thereof, are also provided by the invention. For example, "0.2-5
mg/kg" is a disclosure of 0.2 mg/kg, 0.21 mg/kg, 0.22 mg/kg, 0.23
mg/kg etc. up to 0.3 mg/kg, 0.31 mg/kg, 0.32 mg/kg, 0.33 mg/kg etc.
up to 0.4 mg/kg, 0.5 mg/kg, 0.6 mg/kg etc. up to 5.0 mg/kg.
[0261] All combinations of the various elements described herein
are within the scope of the invention.
[0262] This invention will be better understood by reference to the
Experimental Details which follow, but those skilled in the art
will readily appreciate that the specific experiments detailed are
only illustrative of the invention as described more fully in the
claims which follow thereafter.
Experimental Details
Description of the Study
[0263] Copaxone.RTM. (Glatiramer acetate) is a leading drug for the
treatment of MS that is marketed by TEVA. Glatiramer acetate
significantly improves patient outcomes, but glatiramer acetate
treatment is not equally effective in all patients. Individual
differences between patients, including inherited genetic factors,
can account for significant differences in individual responses to
medications. A consequence of this diversity is that no single
medication is effective in all patients. Clinical and genetic
factors are predictive of patient response to glatiramer
acetate.
[0264] In the following Examples, predictive genetic factors of
glatiramer acetate treatment response are identified and a
diagnostic model is demonstrated to help guide MS drug therapy to
significantly improve patient outcomes.
EXAMPLES
Example 1 Patient Populations
[0265] Response definitions were received from patients from two
large glatiramer acetate clinical trial cohorts (GALA, FORTE) and
patients were categorized as responder, non-responder,
extreme-responder, or extreme non-responder according to the
criteria set forth in Table 1.
Example 2 Patient Genotyping
[0266] DNA samples from categorized patients were subject to
quality control analysis followed by genotyping with the Illumina
OMNI-5M genome wide array. This array tests 4,301,331 variants with
a median marker spacing of 360 bp. The array includes 84,004
non-synonymous SNPs including 43,904 variants in the MHC region.
Over 800 patients were genotyped.
Genotyping Quality Control
[0267] An Illumina-derived algorithm of SNP cluster definitions
(i.e., the specific parameters used to determine specific genotypes
of each SNP) was used to determine the 4,301,331 genotypes for each
of the genotyped samples. For genotyping QC, SNPs were evaluated as
either pass, fail, or the SNP cluster calling definitions were
revised and the SNP was re-evaluated as pass or fail.
[0268] Evaluation of SNPs with poor cluster separation values
(i.e., the location of SNP calling clusters were very close
together) identified 126 SNPs for which SNP clustering was manually
corrected. Evaluation of SNPs that were not in Hardy-Weinburg
equilibrium identified 1,000 SNPs for which SNP clustering was
manually corrected. Evaluation of SNPs with low GC scores (GC
score: an Illumina-developed score of overall SNP performance)
identified 10,000 SNPs for which SNP clustering was manually
corrected. Evaluation of SNPs with low GC scores also identified
160,000 SNPs for which SNP clustering was revised using Illumina
GenomeStudio software to re-define SNP cluster calling definitions.
A total of 524 SNPs were scored as "failed" and removed from
further analyses due to poor SNP clustering that could not be
manually corrected.
[0269] In addition, SNPs with low call rates (i.e., a low number of
genotype calls were generated from a particular SNP test) were
scored as "fail" and removed from further analyses. Applying a
"call rate" threshold of >85% to the 4,301,331 SNPs tested
(i.e., for each SNP, the % of samples for which a genotype was
called) resulted in "fails" for 4,384 SNPs, yielding a total of
4,296,423 SNPs available for subsequent analyses (99.89% of
variants tested).
[0270] Finally, samples with call rates less than 94% (i.e.,
samples for which less than 94% of the genotyped SNPs produced
genotype calls) were removed. This resulted in the removal of 31
samples with call rates of 49-93%, and resulted in a final cohort
of 776 samples for subsequent analyses. Notably, of these 31
excluded samples, 18 (58%) had very low (<1 ng/ul) DNA
concentrations and 12 of the other 13 excluded samples had low DNA
quality (OD 260/280 ratio <1.8 or >2.0), or low DNA
volumes.
[0271] For the final 776 samples, the overall median sample
genotype call rate was 99.88% (min. 94.26%, max. 99.96%) indicative
of high quality genotype data for these samples.
Example 3 Overview of Genetic Analysis
[0272] Genotype data was merged with selected clinical data
(Responder/Non-Responder status, country, age, gender, ancestry,
log of number of relapses in last 2 Years, baseline EDSS score,
baseline volume of T2 lesion, number of Gd-T1 lesions at baseline,
and years of exposure to treatment). Association and regression
analyses were conducted using SVS7 software.
[0273] Analyses were conducted using standard association analyses
and regression analyses. To maximize the statistical power for high
priority variants, the analyses began with focused list of
candidate variants (35), then expanded to a larger number of
variants in 30 genes, then expanded to variants in 180 candidate
genes, and finally expanded to the entire genome-wide analysis.
[0274] For each stage of association analyses, results were
calculated to identify genetic associations using three genetic
models:
1. Allelic Model (chi-square, chi-square -10 Log P, fisher exact,
fisher exact -10 Log P, values for fisher and chi-square with
Bonferoni correction, Odds Ratios and Confidence Bounds, Regression
P-value, Regression -log 10 P, Call Rate (Cases), Call Rate
(Controls), Minor Allele Frequency, Allele Freq. (Cases), Allele
Freq. (Controls), Major Allele Frequency, Allele Freq. (Cases),
Allele Freq. (Controls), Genotype Counts for cases and controls,
Missing Genotype Counts, Allele Counts for cases and controls). 2.
Additive Model (Cochrane-Armitage Trend Test P-value, Exact for of
Cochrane Armitage Trend Test, -log 10 P-values, Correlation/Trend
test P-value, Correlation/Trend -log 10 P, Call Rate, Call Rate
(Cases), Call Rate (Controls), Minor Allele Frequency, Allele Freq.
(Cases), Allele Freq. (Controls). 3. Genotypic Model (chi-square,
chi-square -10 Log P, fisher exact, fisher exact -10 Log P, values
for fisher and chi-square with Bonferoni correction, Odds Ratios
and Confidence Bounds, Regression P-value, Regression -log 10 P,
Call Rate (Cases), Call Rate (Controls), Minor Allele Frequency,
Allele Freq. (Cases), Allele Freq. (Controls), Major Allele
Frequency, Allele Freq. (Cases), Allele Freq. (Controls), Genotype
Counts for cases and controls, Missing Genotype Counts, Allele
Counts for Cases and controls).
[0275] For each stage of regression analyses, results were
calculated to identify genetic associations using an additive
genetic model.
Example 4 Stages of Analysis
[0276] Stage 1.
[0277] Discovery Cohort (n=318: 198 R vs. 120 NR)--In the first
stage of analysis, the discovery cohort (GALA) was analyzed to
identify variants associated with good response vs. poor
response.
[0278] Stage 2.
[0279] Replication Cohort (n=262: 201 R vs. 61 NR)--In the second
stage of each analysis, variants selected in the discovery cohort
were analyzed to identify replicating associations in the FORTE
replication cohort associated with good response vs. poor
response.
[0280] Stage 3.
[0281] Combined Cohorts (n=580: 399 R vs. 111 NR)--In the third
stage of the analysis, the combined GALA and FORTE cohorts were
analyzed.
[0282] Stage 4.
[0283] Placebo Cohort (n=196: 95 R vs. 101 NR) In the fourth stage
of the analysis, the placebo cohort (GALA placebo) was analyzed to
identify variants associated with placebo response/non-response.
These results will be used to confirm whether significantly
associated variants are specific to glatiramer acetate drug
response versus disease severity.
[0284] An overview of these analyses is presented in Table A. For
each stage a step-wise analysis was performed in order to maximize
study power.
TABLE-US-00001 TABLE A Overview of the analyses used to identify
genetic markers predictive of response to glatiramer acetate.
Combined Cohorts for Discovery Cohort Replication Cohort
Comparative Parameters Step 1 Candidate SNPs (35) Candidate SNPs
(35) Candidate SNPs (35) -Additive, Allelic, Genotypic, Regression
-Additive, Allelic, Genotypic, Regression -Additive, Allelic,
Genotypic, Regression Candidate SNPs, Extreme Candidate SNPs,
Extreme Candidate SNPs, Extreme -Additive, Allelic, Genotypic,
Regression -Additive, Allelic, Genotypic, Regression -Additive,
Allelic, Genotypic, Regression Step 2 Candidate Genes (30)
Candidate Genes (30) Candidate Genes (30) -Additive, Allelic,
Genotypic, Regression -Additive, Allelic, Genotypic, Regression
-Additive, Allelic, Genotypic, Regression Candidate Genes, Extreme
Candidate Genes, Extreme Candidate Genes, Extreme -Additive,
Allelic, Genotypic, Regression -Additive, Allelic, Genotypic,
Regression -Additive, Allelic, Genotypic, Regression Step 3
Candidate Genes (180) Candidate Genes (180) Candidate Genes (180)
-Additive, Allelic, Genotypic, Regression -Additive, Allelic,
Genotypic, Regression -Additive, Allelic, Genotypic, Regression
Candidate Genes, Extreme Candidate Genes, Extreme Candidate Genes,
Extreme -Additive, Allelic, Genotypic, Regression -Additive,
Allelic, Genotypic, Regression -Additive, Allelic, Genotypic,
Regression Step 4 Genome-wide Genome-wide Genome-wide -Additive,
Allelic, Genotypic, Regression -Additive, Allelic, Genotypic,
Regression -Additive, Allelic, Genotypic, Regression +Corrected for
ancestry +Corrected for ancestry +Corrected for ancestry +Corrected
for clinical covariates +Corrected for clinical covariates
+Corrected for clinical covariates +Corrected for top SNP
+Corrected for top SNP +Corrected for top SNP Genome-wide, Extreme
Genome-wide, Extreme Genome-wide, Extreme -Additive, Allelic,
Genotypic, Regression -Additive, Allelic, Genotypic, Regression
-Additive, Allelic, Genotypic, Regression +Corrected for clinical
covariates +Corrected for clinical covariates +Corrected for
clinical covariates +Corrected for top SNP +Corrected for top SNP
+Corrected for top SNP
Example 5 Analysis Part 1--Analysis of Candidate Variants
[0285] The initial analysis was limited to 35 genetic variants
identified in high priority genes. Power (80%) with Bonferroni
statistical correction for multiple testing to identify significant
genetic associations with an odds ratio >3, for variants with an
allele frequency greater than 10%. (Or rare alleles (2.5%) with an
odds ratio >7).
[0286] Results for Standard Response Definition, Candidate Variants
Selected a priori for Additive, Allelic and Genotypic models are
presented in tables 2-4, respectively.
[0287] In some embodiments genetic markers presented in Tables 2, 3
and 4 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.12,
less than about 0.08, less than about 0.05, less than about 0.01 or
less than about 0.005.
[0288] In some embodiments genetic markers presented in Tables 2, 3
and 4 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.12, less than about 0.08, less than about 0.05, less than about
0.01, less than about 0.005 or less than about 0.001.
[0289] In some embodiments genetic markers presented in Tables 2, 3
and 4 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.12, less than about 0.08, less than about 0.05, less than about
0.01, less than about 0.005 or less than about 0.001.
Example 6 Analysis Part 2--Analysis of Candidate Genes (30)
[0290] The second analysis was limited to a selected set of genetic
variants in 30 priority candidate genes (4,012 variants). Power
(80%) to identify significant genetic associations with an odds
ratio >4, for variants with an allele frequency greater than
10%. (Or rare alleles (5%) with an odds ratio >6).
[0291] Results for Standard Response Definition, Top 30 Candidate
Genes Selected a priori for Additive, Allelic and Genotypic models
are presented in tables 5-7, respectively.
[0292] In some embodiments genetic markers presented in Tables 5, 6
and 7 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.05,
less than about 0.01 or less than about 0.005.
[0293] In some embodiments genetic markers presented in Tables 5, 6
and 7 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.10, less than about 0.05, less than about 0.01, less than about
0.005 or less than about 0.001.
[0294] In some embodiments genetic markers presented in Tables 5, 6
and 7 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.05, less than about 0.01, less than about 0.005, less than about
0.001, less than about 0.0005 or less than about 10.sup.-4.
Example 7 Analysis Part 3--Analysis of Candidate Genes (180)
[0295] The third analysis was limited to a selected set of genetic
variants in 180 priority candidate genes (25,461 variants).
[0296] Results for Standard Response Definition, 180 Candidate
Genes Selected a priori for Additive, Allelic and Genotypic models
are presented in tables 8-10, respectively.
[0297] In some embodiments genetic markers presented in Tables 8, 9
and 10 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.05,
less than about 0.01, less than about 0.005, less than about 0.001,
less than about 0.0005 or less than about 10.sup.-4.
[0298] In some embodiments genetic markers presented in Tables 8, 9
and 10 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.05, less than about 0.01 or less than about 0.005.
[0299] In some embodiments genetic markers presented in Tables 8, 9
and 10 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.05, less than about 0.01, less than about 0.005, less than about
0.001, less than about 0.0005 or less than about 10.sup.-4.
Example 8 Analysis Part 4--Genome Wide Analysis
[0300] A full genome-wide analysis was then conducted (4 M
variants). Power (80%) with Bonferroni statistical correction to
identify significant genetic associations with an odds ratio >7,
for variants with an allele frequency greater than 10%. (Or rare
alleles (5%) with an odds ratio >11). Approximately 4,200
variants were selected for analysis in stage 2 (replication)
(P<0.001).
[0301] Replication Cohort (n=262: 201 R vs. 61 NR)--In the second
stage of analysis, variants selected in the discovery cohort were
analyzed to identify replicating associations in the FORTE
replication cohort associated with good response vs. poor response.
Based upon an analysis of an estimated 4,200 variants, there is
statistical power (80%) with Bonferroni correction to identify
significant genetic associations with an odds ratio >6.5, for
variants with an allele frequency greater than 5%.
[0302] Combined Cohorts (n=580: 399 R vs. 111 NR)--In the third
stage of the analysis, the combined GALA and FORTE cohorts were
analyzed identify variants associated with response/non-response
using a full genome-wide analysis (4 M variants).
[0303] Results for Standard Response Definition, Genome Wide
Analysis for Additive, Allelic and Genotypic models are presented
in tables 11-13, respectively.
[0304] In some embodiments genetic markers presented in Tables 11,
12 and 13 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about
0.001, less than about 0.0005, less than about 10.sup.-4 or less
than about 5*10.sup.-5.
[0305] In some embodiments genetic markers presented in Tables 11,
12 and 13 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.05, less than about 0.01, less than about 0.005, less than about
0.001 or less than about 0.0005.
[0306] In some embodiments genetic markers presented in Tables 11,
12 and 13 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.05, less than about 0.01, less than about 0.005, less than about
0.001, or less than about 0.0005, less than about 10.sup.-4, less
than about 5*10.sup.-5, less than about 10.sup.-5, less than about
5*10.sup.-6, less than about 10.sup.-6 or less than about
5*10.sup.-7.
[0307] In the fourth stage of the analysis, the placebo cohort
(n=196: 95 R vs. 101 NR) (GALA placebo) was analyzed to identify
variants associated with placebo response/non-response. These
results will be used to confirm whether significantly associated
variants are specific to glatiramer acetate drug response versus
disease severity.
Overlap with Placebo Cohort Results:
[0308] An analysis to investigate whether any of the highly
associated variants (P<0.0001) from the combined cohorts in the
additive association analysis showed a similar significant
association in the placebo cohort was conducted. This analysis
identified two overlapping associations with the placebo
associations, which include the 132.sup.nd top associated variant
in the combined cohorts (variant kpg5144181) and the 242.sup.nd top
associated variant in the combined cohort (kpg7063887).
[0309] Results for Standard Response Definition, Placebo Cohort
Results for Additive, Allelic and Genotypic models are presented in
tables 14-16, respectively.
TABLE-US-00002 TABLE 14 Additive Model, Genome Wide Placebo Cohort
Analysis GALA PLACEBO cohort Allele Allele Gene Armitage Regression
Freq. Freq. DD DD Dd Dd dd dd Name Chr Position Gene(s) Mutation
Locations(s) P Odds Ratio (Cases) (Controls) (Cases) (Controls)
(Cases) (Controls) (Cases) (Controls) rs12472695 2 65804266 ? ? ?
2.31E-05 0.38 31% 51% 10 21 39 62 46 18 kgp3188 2 65804244 ? ? ?
2.99E-05 0.39 36% 56% 13 25 41 63 40 13 kgp5747456 2 23932556 ? ? ?
3.24E-05 Infinity 8% 0% 0 0 15 0 80 101 rs11562998 2 51814215 ? ? ?
3.41E-05 6.52 14% 2% 2 0 23 5 70 96 rs11563025 2 51864372 ? ? ?
3.41E-05 6.52 14% 2% 2 0 23 5 70 96 rs16846161 2 2.12E+08 ERBB4, ER
Silent, Sile INTRON 3.72E-05 12.04 12% 1% 2 0 18 2 74 97
kgp22839559 ? ? ? 3.97E-05 2.82 34% 16% 10 2 44 28 40 70
kgp12562255 1 2.01E+08 ? ? ? 4.21E-05 21.79 9% 0% 0 0 17 1 78 100
kgp6990559 1 7014101 CAMTA1 Silent INTRON, E 4.49E-05 0.44 35% 58%
15 35 36 42 43 20 rs6577395 1 6991925 CAMTA1 Silent INTRON, E
5.34E-05 0.45 37% 59% 16 38 37 43 41 20 kgp4456934 2 2.18E+08 DIRC3
Silent INTRON 5.68E-05 3.79 21% 7% 4 0 31 13 60 87 rs10495115 1
2.19E+08 ? ? ? 6.04E-05 2.90 30% 13% 7 2 43 23 45 76 kgp4137144 1
2.19E+08 ? ? ? 6.13E-05 6.19 14% 3% 2 0 22 5 70 95 rs3768769 2
1.14E+08 IL36A Silent INTRON 7.21E-05 4.30 17% 5% 2 0 29 10 64 91
kgp3488270 1 20335423 ? ? ? 7.30E-05 0.27 6% 21% 1 4 10 33 84 63
rs2354380 2 51826155 ? ? ? 7.48E-05 5.49 14% 3% 2 0 23 6 69 95
kgp7151153 3 79590648 ROBO1 Silent INTRON 7.86E-05 3.98 18% 5% 4 1
27 8 64 92 rs28993969 2 1.14E+08 ? ? ? 8.51E-05 3.67 20% 6% 4 0 30
13 61 88 rs12043743 1 1.97E+08 KCNT2 Silent INTRON 8.61E-05 0.16 3%
13% 0 0 5 26 90 75 kgp24521552 2 1.44E+08 ARHGAP1 Silent INTRON
8.86E-05 4.22 17% 5% 4 0 25 9 66 91 kgp11755256 2 42245135 ? ? ?
8.99E-05 0.38 14% 32% 1 14 25 37 68 50 rs528065 2 23859449 KLHL29
Silent INTRON 9.24E-05 2.45 44% 26% 19 3 46 46 30 52 rs13386874 2
51820543 ? ? ? 9.25E-05 2.64 32% 15% 12 1 37 28 46 72 kgp956070 2
2.06E+08 PARD3B, P Silent, Sile INTRON 9.39E-05 0.37 14% 32% 2 11
23 41 70 48 rs35615951 2 1.34E+08 NCKAP5, Silent, Sile INTRON
9.41E-05 2.32 48% 28% 22 8 46 41 26 52 kgp12253568 3 79428265 ROBO1
Silent INTRON 9.55E-05 4.29 17% 4% 4 1 24 6 67 94 rs1397481 2
2.06E+08 PARD3B, P Silent, Sile INTRON 9.56E-05 0.37 14% 31% 2 10
23 43 70 48 kgp7161038 2 53521025 ? ? ? 9.70E-05 0.09 1% 10% 0 0 2
20 92 81 rs1534647 2 62038088 ? ? ? 9.72E-05 3.34 22% 8% 5 0 32 16
58 85 kgp7799142 3 13902000 WNT7A Silent INTRON 1.04E-O4 0.12 2%
11% 0 0 3 22 91 79 kgp6029 2 1.69E+08 ? ? ? 1.07E-04 0.37 13% 30% 2
11 21 39 72 51 kgp8142606 2 1.74E+08 ? ? ? 1.10E-04 0.22 4% 17% 0 3
8 27 87 70 rs6737616 2 51807660 ? ? ? 1.18E-04 5.98 13% 2% 1 0 22 5
72 96 kgp7713264 2 2.42E+08 GPR35, GP Silent, Sile INTRON 1.18E-04
0.45 30% 51% 10 27 37 47 47 26 kgp8055964 3 1.73E+08 SPATA16 Silent
INTRON 1.19E-04 Infinity 7% 0% 0 0 13 0 82 101 rs12712821 2
42238864 ? ? ? 1.19E-04 0.39 15% 32% 1 14 26 37 68 50 rs13424176 2
42239532 ? ? ? 1.19E-04 0.39 15% 32% 1 14 26 37 68 50 kgp9777128 2
42242872 ? ? ? 1.19E-04 0.39 15% 32% 1 14 26 37 68 50 rs10195970 2
42249643 ? ? ? 1.19E-04 0.39 15% 32% 1 14 26 37 68 50 rs10177811 2
42263580 ? ? ? 1.19E-04 0.39 15% 32% 1 14 26 37 68 50 indicates
data missing or illegible when filed
TABLE-US-00003 TABLE 15 Allelic Model, Genome Wide Placebo Cohort
Analysis GALA PLACEBO cohort Odds Ratio Allele Allele Gene Fisher's
(Minor Freq. Freq. DD DD Dd Dd dd dd Name Chr Position Gene(s)
Mutation Locations(s) Exact P Allele) (Cases) (Controls) (Cases)
(Controls) (Cases) (Controls) (Cases) (Controls) kgp5471255 11
57870219 OR9Q1 Silent INTRON, E 1.16E-06 0.25 9% 29% 5 25 7 7 81 63
kgp11285883 9 2953403 ? ? ? 2.68E-06 2.79 46% 23% 26 5 35 37 34 59
kgp433351 8 41496314 ? ? ? 2.70E-06 0.35 23% 46% 6 19 32 55 57 27
kgp10148554 4 89767803 FAM13A Silent INTRON 3.69E-06 7.19 15% 2% 3
0 23 5 68 96 rs3858038 9 2988280 ? ? ? 5.49E-06 2.63 53% 30% 33 7
34 46 28 48 kgp2877482 6 1644677 GMDS, GM Silent, Sile INTRON
6.08E-06 8.20 14% 2% 0 0 27 4 68 97 kgp6042557 3 1.94E+08 LOC10050
Silent INTRON 6.53E-06 0.08 1% 12% 0 1 2 22 93 77 kgp22755512 X
27326117 ? ? ? 6.61E-06 ? 8% 0% 3 0 10 0 82 101 kgp10989246 4
89761443 FAM13A Silent INTRON 6.68E-06 7.11 15% 3% 3 0 23 5 68 95
rs7698655 4 89756076 FAM13A Silent INTRON 6.76E-06 7.10 15% 2% 3 0
23 5 69 96 kgp9409440 4 89759159 FAM13A Silent INTRON 6.76E-06 7.10
15% 2% 3 0 23 5 69 96 kgp6889327 4 89766553 FAM13A Silent INTRON
6.76E-06 7.10 15% 2% 3 0 23 5 69 96 rs7696391 4 89789287 FAM13A
Silent INTRON 6.76E-06 7.10 15% 2% 3 0 23 5 69 96 rs11947777 4
89768744 FAM13A Silent INTRON 6.92E-06 7.02 15% 3% 3 0 23 5 69 95
kgp6301155 4 89766647 FAM13A Silent INTRON 7.20E-06 6.95 15% 3% 3 0
23 5 69 94 rs16846161 2 2.12E+08 ERBB4, ER Silent, Sile INTRON
7.44E-06 12.99 12% 1% 2 0 18 2 74 97 kgp7778345 9 2965090 ? ? ?
9.91E-06 2.59 49% 27% 27 6 38 42 29 52 kgp6990559 1 7014101 CAMTA1
Silent INTRON, E 1.01E-05 0.40 35% 58% 15 35 36 42 43 20 rs1393040
9 2985743 ? ? ? 1.04E-05 2.57 48% 27% 28 6 35 42 31 53 rs6577395 1
6991925 CAMTA1 Silent INTRON, E 1.27E-05 0.40 37% 59% 16 38 37 43
41 20 rs7846783 9 2958182 ? ? ? 1.28E-05 2.58 45% 24% 25 6 36 37 34
58 kgp5747456 2 23932556 ? ? ? 1.42E-05 ? 8% 0% 0 0 15 0 80 101
kgp6429231 15 62931802 MGC1588 Silent INTRON 1.42E-05 ? 8% 0% 0 0
15 0 80 101 kgp30689515 X 56022365 ? ? ? 1.42E-05 ? 8% 0% 4 0 7 0
84 101 kgp1682126 5 2047397 ? ? ? 1.56E-05 0.05 1% 10% 0 1 1 18 94
82 kgp2920925 17 39694480 ? ? ? 1.56E-05 0.30 10% 27% 0 6 19 43 76
52 rs3894712 5 73973651 ? ? ? 1.70E-05 0.29 9% 25% 3 5 11 41 81 55
rs7119480 11 84247636 DLG2, DLG Silent, Sile INTRON, E 1.71E-05
0.34 14% 33% 1 9 25 48 69 44 rs3858035 9 2968044 ? ? ? 1.72E-05
2.51 48% 27% 27 7 37 41 30 53 rs3847233 9 2987835 ? ? ? 1.95E-05
2.49 52% 30% 31 7 34 46 28 47 kgp12253568 3 79428265 ROBO1 Silent
INTRON 2.10E-05 4.91 17% 4% 4 1 24 6 67 94 kgp1977942 9 2938757 ? ?
? 2.17E-05 2.52 46% 26% 28 7 32 37 35 56 kgp22744690 X 83601713
HDX, HDX, Silent, Sile INTRON 2.21E-05 7.50 13% 2% 7 0 11 4 77 97
rs8000689 13 41043438 TTL, TTL, T Silent, Sile INTRON 2.22E-05 0.42
38% 60% 14 40 45 41 36 20 kgp4892427 9 2995617 ? ? ? 2.27E-05 2.46
52% 30% 31 7 36 47 28 47 rs11562998 2 51814215 ? ? ? 2.36E-05 6.53
14% 2% 2 0 23 5 70 96 rs11563025 2 51864372 ? ? ? 2.36E-05 6.53 14%
2% 2 0 23 5 70 96 rs7680970 4 89772301 FAM13A Missense EXON
2.37E-05 5.88 15% 3% 3 0 23 6 69 95 kgp22836129 X 1.45E+08 ? ? ?
2.38E-05 5.84 15% 3% 5 0 19 6 70 93 kgp11604017 11 1.18E+08 AMICA1,
A Silent, Sile INTRON 2.39E-05 2.69 38% 18% 11 3 48 31 34 67
rs961090 15 40617414 ? ? ? 2.40E-05 2.97 31% 13% 9 2 40 22 46 77
kgp22760557 X 3520721 ? ? ? 2.40E-05 2.97 31% 13% 16 5 26 16 53 80
rs1393037 9 2968451 ? ? ? 2.41E-05 2.50 48% 27% 27 7 37 40 30 52
rs4978567 9 1.17E+08 ? ? ? 2.47E-05 0.41 32% 54% 10 27 41 52 44 20
indicates data missing or illegible when filed
TABLE-US-00004 TABLE 16 Genotypic Model, Genome Wide Placebo Cohort
Analysis GALA PLACEBO cohort Allele Allele Gene Fisher's Freq.
Freq. DD DD Dd Dd dd dd Name Chromosome Position Gene(s) Mutation
Locations(s) Exact P (Cases) (Controls) (Cases) (Controls) (Cases)
(Controls) (Cases) (Controls) kgp54189 5 73992881 HEXB Missense
EXON 8.76E-07 9% 25% 3 3 11 44 81 54 kgp34948 14 91731724 ? ? ?
1.53E-06 6% 17% 3 1 5 32 87 67 kgp21160 14 91744233 CCDC88C Silent
INTRON 1.55E-06 6% 17% 3 1 5 32 86 67 kgp28774 6 1644677 GMDS, G
Silent, Sil INTRON 2.43E-06 14% 2% 0 0 27 4 68 97 rs1175074 5
73973220 ? ? ? 2.71E-06 9% 25% 3 4 11 42 81 55 rs1223398 5 73975094
? ? ? 2.71E-06 9% 25% 3 4 11 42 81 55 rs1203094 1 67701765 IL23R
Silent INTRON 3.44E-06 36% 37% 20 5 29 64 46 32 rs3894712 5
73973651 ? ? ? 3.50E-06 9% 25% 3 5 11 41 81 55 rs3858038 9 2988280
? ? ? 4.13E-06 53% 30% 33 7 34 46 28 48 kgp62594 5 73973306 ? ? ?
5.26E-06 9% 24% 3 4 11 41 81 56 rs7159692 14 91729406 ? ? ?
6.22E-06 7% 18% 3 1 7 34 85 66 kgp43335 8 41496314 ? ? ? 7.73E-06
23% 46% 6 19 32 55 57 27 kgp60425 3 1.94E+08 LOC10050 Silent INTRON
8.38E-06 1% 12% 0 1 2 22 93 77 kgp89109 8 4818950 CSMD1 Silent
INTRON 8.91E-06 45% 33% 27 5 32 57 36 39 kgp48182 14 86277089 ? ? ?
8.95E-06 45% 36% 10 18 66 36 19 47 kgp66017 19 28886975 ? ? ?
9.85E-06 19% 31% 7 3 21 55 65 42 kgp57474 2 23932556 ? ? ? 1.03E-05
8% 0% 0 0 15 0 80 101 kgp64292 15 62931802 MGC1588 Silent INTRON
1.03E-05 8% 0% 0 0 15 0 80 101 kgp82762 14 91725476 ? ? ? 1.22E-05
7% 17% 3 1 7 33 85 67 kgp68282 9 8373943 PTPRD, PT Silent, Sil
INTRON 1.23E-05 26% 10% 3 2 43 17 48 82 rs3847233 9 2987835 ? ? ?
1.32E-05 52% 30% 31 7 34 46 28 47 kgp3188 2 65804244 ? ? ? 1.34E-05
36% 56% 13 25 41 63 40 13 rs1890118 6 82857479 ? ? ? 1.48E-05 26%
32% 13 4 23 56 59 41 rs2282624 11 57001911 APLNR, AP Silent, Sil
INTRON, E 1.54E-05 30% 35% 15 5 27 61 53 35 kgp48924 9 2995617 ? ?
? 1.54E-05 52% 30% 31 7 36 47 28 47 kgp11285 9 2953403 ? ? ?
1.66E-05 46% 23% 26 5 35 37 34 59 rs4740708 9 2993975 ? ? ?
1.67E-05 51% 30% 31 7 34 47 29 47 rs695915 1 82664165 ? ? ?
1.90E-05 34% 28% 6 17 51 23 37 61 rs2327006 6 1.31E+08 EPB41L2,
Silent, Sil INTRON 1.93E-05 22% 9% 1 2 39 13 55 84 kgp93349 6
1.31E+08 EPB41L2, Silent, Sil INTRON 2.05E-05 22% 8% 2 2 38 13 55
86 rs193933 19 8331375 ? ? ? 2.07E-05 27% 46% 11 17 30 59 54 25
kgp12475 4 1.86E+08 ACSL1 Silent INTRON 2.11E-05 13% 3% 0 1 24 4 71
96 rs1247269 2 65804266 ? ? ? 2.11E-05 31% 51% 10 21 39 62 46 18
rs1393040 9 2985743 ? ? ? 2.31E-05 48% 27% 28 6 35 42 31 53
kgp29209 17 39694480 ? ? ? 2.33E-05 10% 27% 0 6 19 43 76 52
rs209568 8 17612639 MTUS1, M Synonym EXON 2.34E-05 27% 11% 4 0 44
22 47 79 kgp12562 1 2.01E+08 ? ? ? 2.42E-05 9% 0% 0 0 17 1 78 100
kgp26263 13 67483846 PCDH9, P Silent, Sil INTRON, E 2.43E-05 34%
49% 4 28 56 43 34 30 kgp16821 5 2047397 ? ? ? 2.51E-05 1% 10% 0 1 1
18 94 82 kgp10148 4 89767803 FAM13A Silent INTRON 2.55E-05 15% 2% 3
0 23 5 68 96 kgp57600 6 1.31E+08 EPB41L2, Silent, Sil INTRON
2.61E-05 20% 7% 1 2 35 11 58 88 kgp78398 1 95321361 SLC44A3,
Silent, Sil INTRON 2.67E-05 20% 20% 0 11 38 19 57 71 rs1049917 6
1.31E+08 EPB41L2, Silent, Sil INTRON 2.77E-05 19% 7% 1 2 35 11 59
88 kgp37781 19 28893126 ? ? ? 2.80E-05 19% 32% 7 4 23 56 65 41
kgp76534 17 39694186 ? ? ? 2.81E-05 10% 27% 0 5 19 44 76 52
rs1684616 2 2.12E+08 ERBB4, ER Silent, Sil INTRON 2.96E-05 12% 1% 2
0 18 2 74 97 indicates data missing or illegible when filed
Example 9 Analysis for Extreme Responders vs. Extreme
Non-Responders Part 1--Analysis of Candidate Variants
[0310] The initial analysis was analyzed to 35 genetic variants in
high priority genes. Power (80%) with Bonferroni statistical
correction for multiple testing to identify significant genetic
associations with an odds ratio >4, for variants with an allele
frequency greater than 10%.
[0311] Results for Extreme Response Definition, Candidate Variants
Selected a priori for Additive, Allelic and Genotypic models are
presented in tables 17-19, respectively.
[0312] In some embodiments genetic markers presented in Tables
17-19 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.15,
less than about 0.13, less than about 0.07 or less than about
0.06.
[0313] In some embodiments genetic markers presented in Tables
17-19 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.10, less than about 0.05, less than about 0.01, less than about
0.005 or less than about 0.001.
[0314] In some embodiments genetic markers presented in Tables
17-19 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.10, less than about 0.05, less than about 0.01, less than about
0.005 or less than about 0.001.
Example 10 Analysis for Extreme Responders vs. Extreme
Non-Responders Part 2--Analysis of Candidate Genes (30)
[0315] The second analysis was analyzed to a selected set of
genetic variants in 30 priority candidate genes (4,012 variants).
Power (80%) to identify significant genetic associations with an
odds ratio >7, for variants with an allele frequency greater
than 10%.
[0316] Results for Extreme Response Definition, Analysis of
Candidate Genes (30) Selected a priori for Additive, Allelic and
Genotypic models are presented in tables 20-22, respectively. No
variants replicated in both cohorts (P<0.05). Less stringent
(P<0.10+P<0.05) values were used.
[0317] In some embodiments genetic markers presented in Tables
20-22 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.10,
less than about 0.09, less than about 0.08, less than about 0.07 or
less than about 0.02.
[0318] In some embodiments genetic markers presented in Tables
20-22 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.05, less than about 0.02, less than about 0.01 or less than about
0.005.
[0319] In some embodiments genetic markers presented in Tables
20-22 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.05, less than about 0.01 or less than about 0.005.
Example 11 Analysis for Extreme Responders vs. Extreme
Non-Responders Part 3--Analysis of Candidate Genes (180)
[0320] The third analysis was analyzed to a selected set of genetic
variants in 180 priority candidate genes (25,461 variants). Power
(80%) to identify significant genetic associations with an odds
ratio >7, for variants with an allele frequency greater than
10%.
[0321] Results for Extreme Response Definition, Analysis of
Candidate Genes (180) Selected a priori for Additive, Allelic and
Genotypic models are presented in tables 23-25, respectively.
[0322] In some embodiments genetic markers presented in Tables
23-25 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.05,
less than about 0.01, less than about 0.005, less than about 0.001,
less than about 0.0005 or less than about 10.sup.-4.
[0323] In some embodiments genetic markers presented in Tables
23-25 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.05, less than about 0.01, less than about 0.005 or less than
about 0.001.
[0324] In some embodiments genetic markers presented in Tables
23-25 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
0.05, less than about 0.01, less than about 0.005, less than about
0.001, less than about 0.0005 or less than about 10.sup.-4.
Example 12 Analysis for Extreme Responders vs. Extreme
Non-Responders Part 4--Genome Wide Analysis
[0325] A full genome-wide analysis (4 M variants) was then
conducted. Power (80%) with Bonferroni statistical correction to
identify significant genetic associations with an odds ratio
>11, for variants with an allele frequency greater than 10%.
Approximately 4200 variants were selected for analysis in stage 2
(replication) (P<0.001).
[0326] Results for Extreme Response Definition, Genome Wide
Analysis for Additive, Allelic and Genotypic models are presented
in tables 23-25, respectively.
[0327] In some embodiments genetic markers presented in Tables
26-28 are identified as predictive of response to glatiramer
acetate if the p-value for the GALA cohort is less than about 0.05,
less than about 0.01, less than about 0.001, less than about
0.0005, less than about 10.sup.-4 or less than about
5*10.sup.-5.
[0328] In some embodiments genetic markers presented in Tables
26-28 are identified as predictive of response to glatiramer
acetate if the p-value for the FORTE cohort is less than about
0.05, less than about 0.01, less than about 0.001, less than about
0.0005, less than about 10.sup.-4 or less than about
5*10.sup.-5.
[0329] In some embodiments genetic markers presented in Tables
26-28 are identified as predictive of response to glatiramer
acetate if the p-value for the Combined cohort is less than about
10.sup.-4, less than about 5*10.sup.-5, less than about 10.sup.-5,
less than about 5*10.sup.-6, less than about 10.sup.-6 or less than
about 5*10.sup.-7.
[0330] Stage 4.
[0331] Placebo Cohort (n=102: 23 R vs. 79 NR)--The placebo cohort
(GALA placebo) was analyzed to identify variants associated with
placebo response/non-response.
[0332] Results for Standard Response Definition, Placebo Cohort
Results for Additive, Allelic and Genotypic models are presented in
tables 29-31, respectively.
TABLE-US-00005 TABLE 29 Additive Model, Extreme Response
Definition, Genome Wide Placebo Cohort Analysis Placebo Regres- DD
Dd dd Gene Armitage sion Odds DD (Con- Dd (Con- dd (Con- Name Chr
Position Gene(s) Mutation Locations(s) P Ratio (Cases) trols)
(Cases) trols) (Cases) trols) rs1978721 19 30966217 ZNF536 Silent
INTRON 9.89E-09 35.3 0 0 11 2 12 77 kgp7344529 19 30967564 ZNF536
Silent INTRON 9.89E-09 35.3 0 0 11 2 12 77 rs7252241 19 30967836
ZNF536 Silent INTRON 9.89E-09 35.3 0 0 11 2 12 77 rs1978720 19
30968371 ZNF536 Silent INIRON 9.89E-09 35.3 0 0 11 2 12 77
kgp146166 19 30965980 ZNF536 Silent INTRON 1.92E-07 13.8 0 0 14 8 9
71 rs8112863 19 30965063 ZNF536 Silent INTRON 2.37E-07 13.6 0 0 14
8 9 70 kgp2877482 6 1644677 GMDS, GMDS Silent, Silent INTRON
3.47E-07 17.2 0 0 11 4 12 75 kgp7851536 15 27960322 ? ? ? 3.76E-07
? 0 0 7 0 16 79 kgp9348779 15 101900592 PCSK6, PCSK6, PCSK6,
Silent, Silent, Silent, Silent, INTRON 3.76E-07 ? 0 0 7 0 16 79
PCSK6, PCSK6, PCSK6 Silent, Silent rs2289333 15 40617209 ? ? ?
5.68E-07 17.9 1 0 9 3 13 76 kgp2471573 15 40633138 C15orf52
Synonymous_ASA EXON 5.68E-07 17.9 1 0 9 3 13 76 kgp8598661 6
1627678 GMDS, GMDS Silent, Siltent INTRON 6.01E-07 12.5 1 0 11 6 11
73 rs16846841 2 197063250 ? ? ? 6.12E-07 41.6 0 0 8 1 15 78
rs7565256 2 79227275 ? ? ? 6.17E-07 9.1 4 0 14 22 5 56 kgp12396787
22 27267611 ? ? ? 7.21E-07 41.1 0 0 8 1 15 77 kgp6535349 15
40614200 ? ? ? 7.54E-07 24.4 0 0 9 2 14 76 kgp9775757 1 23063465
EPHB2, EPHB2 Silent, Silent INTRON 1.13E-06 9.2 3 0 15 22 5 57
kgp2151888 2 79295288 ? ? ? 1.87E-06 8.2 3 0 13 19 6 60 kgp4985243
7 136556162 CHRM2, CHRM2, CHRM2, Silent, Silent, Silent, Silent,
INTRON 2.25E-06 9.3 1 0 13 11 9 68 CHRM2, CHRM2, CHRM2, Silent,
Silent, Silent, Silent CHRM2, CHRM2 kgp6870400 2 79278036 ? ? ?
2.38E-06 7.4 4 0 13 22 6 57 rs1077476 15 40619743 ? ? ? 2.53E-06
13.1 1 0 9 4 13 74 kgp2136475 15 40623593 ? ? ? 2.53E-06 13.1 1 0 9
4 13 74 rs4935590 10 57059483 ? ? ? 2.59E-06 8.2 2 0 12 12 9 67
rs16907220 10 57059690 ? ? ? 2.59E-06 8.2 2 0 12 12 9 67 rs1073665
10 57061057 ? ? ? 2.59E-06 8.2 2 0 12 12 9 67 rs4477500 10
128645821 ? ? ? 2.62E-06 7.3 9 2 10 37 3 39 kgp9016053 17 69386788
? ? ? 2.87E-06 10.5 1 0 10 7 10 71 kgp2617488 3 11849777 TAMM41
Silent INTRON 2.88E-06 ? 0 0 6 0 17 79 kgp3537954 5 103927513 ? ? ?
2.88E-06 74935934087673200.0 0 0 6 0 17 79 kgp9400093 5 104031832 ?
? ? 2.88E-06 74935934087673200.0 0 0 6 0 17 79 kgp3681524 7
145920329 CNTNAP2 Silent INTRON 2.88E-06 45450941538370800.0 0 0 6
0 17 79 kgp788303 10 23646459 ? ? ? 2.88E-06 74935934087672700.0 0
0 6 0 17 79 kgp7824246 12 11333716 ? ? ? 2.88E-06
74935934087672700.0 0 0 6 0 17 79 kgp27533766 12 65501698 WIF1
Silent INTRON 2.88E-06 74935934087672700.0 0 0 6 0 17 79 kgp4089310
18 7309451 ? ? ? 2.88E-06 ? 0 0 6 0 17 79 rs17225585 17 69370430 ?
? ? 3.05E-06 10.2 1 0 11 7 11 69 rs13104183 4 113323634 ALPK1,
ALPK1, ALPK1 Silent, Silent, Silent INTRON, EXON 3.43E-06 6.7 4 0
10 16 8 63 kgp11962282 10 88223587 WAPAL Silent INTRON 3.61E-06
10.5 1 1 10 6 12 73 rs3934982 2 242926558 ? ? ? 3.66E-06 11.5 1 0 9
5 12 74 kgp896539 3 135473872 ? ? ? 3.77E-06 10.6 0 0 12 8 10 71
rs6743255 2 205363596 ? ? ? 4.33E-06 7.7 2 0 13 15 8 64 kgp5046752
2 179650234 TTN, TTN, TTN, TTN, TTN Silent, Silent, Silent, Silent,
INTRON 4.67E-06 34.1 0 0 7 1 16 78 Silent kgp3420885 13 112188913 ?
? ? 4.67E-06 34.1 0 0 7 1 16 78 kgp3423367 19 54113722 ? ? ?
4.67E-06 34.1 0 0 7 1 16 78 kgp9522435 19 30951753 ZNF536 Silent
INTRON 4.71E-06 20.5 0 0 8 2 15 77 kgp5544649 19 30958606 ZNF536
Silent INTRON 4.71E-06 20.5 0 0 8 2 15 77 kgp3185857 22 27269249 ?
? ? 4.71E-06 20.5 0 0 8 2 15 77 kgp5863276 22 27274898 ? ? ?
4.71E-06 20.5 0 0 8 2 15 77 rs17825388 17 69380584 ? ? ? 4.74E-06
9.2 1 0 11 8 11 71 rs1942396 18 69347308 ? ? ? 4.74E-08 9.2 1 0 11
8 11 71 kgp2575625 2 218219226 DIRC3 Silent INTRON 5.23E-06 8.6 1 0
12 10 10 69 kgp11688655 2 218219697 DIRC3 Silent INTRON 5.23E-06
8.6 1 0 12 10 10 69 kgp3778675 2 218226516 DIRC3 Silent INTRON
5.23E-06 8.6 1 0 12 10 10 69 rs10488907 4 113312105 ALPK1, ALPK1,
ALPK1 Silent, Silent, Silent INTRON, EXON 5.36E-06 7.5 2 0 12 13 9
66 kgp2832863 3 8820301 ? ? ? 5.38E-06 33.7 0 0 7 1 16 77
kgp6643157 3 13145604 ? ? ? 5.46E-06 20.3 0 0 8 2 15 76 kgp4292871
22 27274445 ? ? ? 5.46E-06 20.3 0 0 8 2 15 76 rs6643055 X 111782861
? ? ? 5.65E-06 18.3 1 0 7 2 15 77 rs12005792 9 87236739 ? ? ?
6.46E-06 6.8 3 1 15 22 5 56 rs882829 15 40607689 ? ? ? 6.98E-06
10.6 1 0 9 5 13 74 kgp1305638 6 122195448 ? ? ? 7.74E-06 29.6 1 0 6
1 16 78 rs6673115 1 23069649 EPHB2, EPHB2 Silent, Silent INTRON
8.25E-06 6.7 5 1 14 30 4 48 kgp7380442 22 28746343 TTC28 Silent
INTRON 8.80E-06 ? 1 0 5 0 17 79 kgp4898364 22 29092726 CHEK2,
CHEK2, CHEK2 Silent, Silent, Silent INTRON 8.80E-06 ? 1 0 5 0 17 79
kgp9420863 1 105167334 ? ? ? 9.42E-06 9.0 0 0 13 10 10 69 kgp100271
1 105186472 ? ? ? 9.42E-06 9.0 0 0 13 10 10 69 kgp4009576 1
105189899 ? ? ? 9.42E-06 9.0 0 0 13 10 10 69 kgp11130156 12
20871256 SLCO1C1, SLCO1C1, Silent, Silent, Silent, Silent INTRON
9.52E-06 6.4 2 1 13 13 8 65 SLCO1C1, SLCO1C1 rs10746192 12 81942162
PPFIA2, PPFIA2, PPFIA2, Silent, Silent, Silent, Silent, INTRON
9.87E-06 8.0 8 5 15 45 0 29 PPFIA2, PPFIA2, PPFIA2, Silent, Silent,
Silent PPF1A2 kgp8919080 7 84958459 ? ? ? 9.94E-06 8.9 1 0 10 7 12
72
TABLE-US-00006 TABLE 30 Allelic Model, Extreme Response Definition,
Genome Wide Placebo Cohort Analysis Placebo Odds Ratio Allele
Allele Gene Fisher's (Minor Freq. Freq. DD DD Dd Dd dd dd Name Chr
Position Gene(s) Mutation Location(s) Exact P Allele) (Cases)
(Controls) (Cases) (Controls) (Cases) (Controls) (Cases) (Controls)
kgp10638 3 196573166 ? ? ? 1.00E-06 0.1 7% 44% 0 17 3 35 20 27
rs1978721 19 30966217 ZNF536 Silent INTRON 1.49E-06 24.5 24% 1% 0 0
11 2 12 77 kgp734452 19 30967564 ZNF536 Silent INTRON 1.49E-06 24.5
24% 1% 0 0 11 2 12 77 rs7252241 19 30967836 ZNF536 Silent INTRON
1.49E-06 24.5 24% 1% 0 0 11 2 12 77 rs1978720 19 30968371 ZNF536
Silent INTRON 1.49E-06 24.5 24% 1% 0 0 11 2 12 77 kgp183404 3
196579489 ? ? ? 2.26E-06 0.1 7% 42% 0 14 3 38 20 27 kgp860737 17
20459947 ? ? ? 4.36E-06 0.0 2% 35% 0 10 1 35 20 34 rs2289333 15
40617209 ? ? ? 5.79E-06 16.2 24% 2% 1 0 9 3 13 76 kgp247157 15
40633138 C15orf52 Synonymo EXON 5.79E-06 16.2 24% 2% 1 0 9 3 13 76
rs7565256 2 79227275 ? ? ? 7.04E-06 5.6 48% 14% 4 0 14 22 5 56
kgp85986 6 1627678 GMDS, GM Silent, Silen INTRON 8.30E-06 10.0 28%
4% 1 0 11 6 11 73 rs1310418 4 113323634 ALPK1, ALP Silent, Silen
INTRON, E 9.26E-06 6.1 41% 10% 4 0 10 16 8 63 rs4477500 12
128645821 ? ? ? 9.70E-06 4.9 64% 26% 9 2 10 37 3 39 kgp35989 4
7649861 SORCS2 Silent INTRON 9.97E-06 0.0 2% 31% 0 7 1 35 22 37
kgp11164 17 20459328 ? ? ? 1.07E-05 0.1 4% 35% 0 9 2 36 21 32
kgp14616 19 30965980 ZNF536 Silent INTRON 1.22E-05 8.2 30% 5% 0 0
14 8 9 71 rs8112863 19 30965063 ZNF536 Silent INTRON 1.38E-05 8.1
30% 5% 0 0 14 8 9 70 rs2555629 4 175430288 HPGD, HPG Silent, Silen
INTRON, E 1.40E-05 4.6 61% 25% 11 4 6 32 6 43 kgp25188 2 79295288 ?
? ? 1.44E-05 5.6 43% 12% 3 0 13 19 6 60 kgp553777 20 35531097
SAMHD1 Silent INTRON 1.68E-05 5.5 41% 11% 4 1 11 16 8 62 kgp40047
20 35539858 SAMHD1 Silent INTRON 1.68E-05 5.5 41% 11% 4 1 11 16 8
62 kgp97757 1 23068465 EPBB2, EP Silent, Silen INTRON 1.68E-05 5.2
46% 14% 3 0 15 22 5 57 kgp68704 2 79278036 ? ? ? 1.68E-05 5.2 46%
14% 4 0 13 22 6 57 rs763318 4 12963574 ? ? ? 1.70E-05 5.4 83% 47%
15 20 8 33 0 25 rs4935590 10 57059483 ? ? ? 1.73E-05 6.5 35% 8% 2 0
12 12 9 67 rs1690722 10 57059690 ? ? ? 1.73E-05 6.5 35% 8% 2 0 12
12 9 67 rs1073665 10 57061057 ? ? ? 1.73E-05 6.5 35% 8% 2 0 12 12 9
67 kgp59692 4 12976777 ? ? ? 1.73E-05 4.5 70% 34% 11 10 10 33 2 36
kgp28774 6 1644677 GMDS, GM Silent, Silen INTRON 1.81E-05 12.1 24%
3% 0 0 11 4 12 75 rs4916561 3 196576109 ? ? ? 1.84E-05 0.1 7% 38% 0
12 3 36 20 30 kgp22823 X 31244702 DMD, DMD Silent, Silen INTRON
1.91E-05 0.1 2% 30% 0 17 1 14 22 48 rs1077476 15 40619743 ? ? ?
2.00E-05 11.9 24% 3% 1 0 9 4 13 74 kgp21364 15 40623593 ? ? ?
2.00E-05 11.9 24% 3% 1 0 9 4 13 74 kgp785153 15 27960322 ? ? ?
2.04E-05 ? 15% 0% 0 0 7 0 16 79 kgp934877 15 101900592 PCSK6, PCS
Silent, Silen INTRON 2.04E-05 ? 15% 0% 0 0 7 0 16 79 indicates data
missing or illegible when filed
TABLE-US-00007 TABLE 31 Genotype Model, Extreme Response
Definition, Genome Wide Placebo Cohort Analysis Placebo Allele
Allele Gene Fisher's Freq. Freq. DD DD Dd Dd dd dd Name Chr
Position Gene(s) Mutation Locations(s) Exact P (Cases) (Controls)
(Cases) (Controls) (Cases) (Controls) (Cases) (Controls) rs1978721
19 30966217 ZNF536 Silent INTRON 4.57E-07 24% 1% 0 0 11 2 12 77
kgp7344529 19 30967564 ZNF536 Silent INTRON 4.57E-07 24% 1% 0 0 11
2 12 77 rs7252241 19 30967836 ZNF536 Silent INTRON 4.57E-07 24% 1%
0 0 11 2 12 77 rs1978720 19 30968371 ZNF536 Silent INTRON 4.57E-07
24% 1% 0 0 11 2 12 77 kgp146166 19 30965980 ZNF536 Silent INTRON
1.91E-06 30% 5% 0 0 14 8 9 71 rs8112863 19 30965063 ZNF536 Silent
INTRON 2.19E-06 30% 5% 0 0 14 8 9 70 rs7565256 2 79227275 ? ? ?
2.25E-06 48% 14% 4 0 14 22 5 56 kgp6295377 19 30953846 ZNF536
Silent INTRON 3.08E-06 20% 2% 0 1 9 1 14 77 rs4477500 12 128645821
? ? ? 3.54E-06 64% 26% 9 2 10 37 3 39 rs11705401 22 37678096 ? ? ?
3.97E-06 13% 37% 2 4 2 50 19 25 kgp2536097 6 25181978 ? ? ?
5.58E-06 74% 41% 14 8 6 48 3 23 rs2109066 19 28835327 ? ? ?
5.93E-06 9% 31% 2 5 0 39 21 35 kgp2877482 6 1644677 GMDS, GM
Silent, Silen INTRON 6.14E-06 24% 3% 0 0 11 4 12 75 kgp9775757 1
23068465 EPHB2, EP Silent, Silen INTRON 6.34E-06 46% 14% 3 0 15 22
5 57 kgp6601755 19 28886975 ? ? ? 6.76E-06 11% 33% 2 3 1 45 19 30
kgp8598661 6 1627678 GMDS, GM Silent, Silen INTRON 8.89E-06 28% 4%
1 0 11 6 11 73 rs2159327 19 28835571 ? ? ? 9.75E-06 9% 31% 2 5 0 39
20 35 kgp2151888 2 79295288 ? ? ? 9.91E-06 43% 12% 3 0 13 19 6 60
rs2289333 15 40617209 ? ? ? 1.01E-05 24% 2% 1 0 9 3 13 76
kgp2471573 15 40633138 C15orf52 Synonymo EXON 1.01E-05 24% 2% 1 0 9
3 13 76 kgp6870400 2 79278036 ? ? ? 1.27E-05 46% 14% 4 0 13 22 6 57
kgp6850713 19 28885593 ? ? ? 1.28E-05 7% 32% 1 3 1 44 20 32
kgp7851536 15 27960322 ? ? ? 1.33E-05 15% 0% 0 0 7 0 16 79
kgp9348779 15 101900592 PCSK6, PCS Silent, Silen INTRON 1.33E-05
15% 0% 0 0 7 0 16 79 rs995834 19 28866596 ? ? ? 1.39E-05 11% 32% 2
4 1 43 20 32 rs1773631 10 25665449 GPR158 Silent INTRON 1.43E-05
27% 7% 0 2 12 7 10 70 kgp8034516 8 97282138 PTDSS1 Silent INTRON
1.46E-05 20% 3% 0 1 9 2 14 76 rs13280716 8 97282560 PTDSS1 Silent
INTRON 1.46E-05 20% 3% 0 1 9 2 14 76 kgp303315 8 97283313 PTDSS1
Silent INTRON 1.46E-05 20% 3% 0 1 9 2 14 76 kgp5433489 8 97302091
PTDSS1 Silent INTRON 1.46E-05 20% 3% 0 1 9 2 14 76 rs17707686 8
97312442 PTDSS1 Silent INTRON 1.46E-05 20% 3% 0 1 9 2 14 76
rs727047 22 37677719 ? ? ? 1.48E-OS 13% 35% 2 4 2 48 19 27
kgp7521451 8 97297894 PTDSS1 Silent INTRON 1.49E-05 20% 4% 0 2 9 2
13 74 rs2056136 12 20867893 SLCO1C1, Silent, Silen INTRON 1.50E-05
35% 9% 1 1 14 12 8 66 rs10746192 12 81942162 PPFIA2, PP Silent,
Silen INTRON 1.54E-05 67% 35% 8 5 15 45 0 29 rs2555629 4 175430288
HPGD, HPG Silent, Silen INTRO, E 1.57E-05 61% 25% 11 4 6 32 6 43
kgp12537012 8 97285429 PTDSS1 Silent INTRON 1.60E-05 20% 3% 0 1 9 2
14 75 rs9969509 8 97293953 PTDSS1 Silent INTRON 1.60E-05 20% 3% 0 1
9 2 14 75 kgp6535349 15 40614200 ? ? ? 1.60E-05 20% 1% 0 0 9 2 14
76 rs16846841 2 197063250 ? ? ? 1.73E-05 17% 1% 0 0 8 1 15 78
kgp12396787 22 27267611 ? ? ? 1.87E-05 17% 1% 0 0 8 1 15 77
kgp4985243 7 136556162 CHRM2, C Silent, Silen INTRON 1.91E-05 33%
7% 1 0 13 11 9 68 rs4935590 10 57059483 ? ? ? 1.98E-05 35% 8% 2 0
12 12 9 67 rs16907220 10 57059690 ? ? ? 1.98E-05 35% 8% 2 0 12 12 9
67 rs1073665 10 57061057 ? ? ? 1.98E-05 35% 8% 2 0 12 12 9 67
rs2292275 1 163292217 NUF2, NU Silent, Silen INTRON, E 2.11E-05 57%
27% 4 6 18 30 1 42 rs7962380 12 128643018 ? ? ? 2.27E-05 67% 34% 11
5 9 44 3 30 kgp10638512 3 196573166 ? ? ? 2.34E-05 7% 44% 0 17 3 35
20 27 indicates data missing or illegible when filed
Example 13 Association Analyses Corrected for Ancestry
[0333] A Principal Components Analysis (PCA) was performed in order
to investigate potential population stratification among cases and
controls. Sample-specific Eigen values were calculated to produce
an output of 1st and 2nd Principal Components which can be used to
infer patient ancestry.
[0334] An association analysis was performed using an Additive
Genetic Model with Principal Components Analysis correction for
population stratification; results are presented in Table 32.
Example 14 Regression Analysis
[0335] Regression analysis was conducted using an additive genetic
model to identify additional clinical and genetic variants that are
highly associated with response after correction for the most
significantly associated variables.
[0336] For clinical factors, regression analyses revealed two
highly associated clinical covariates: "Log number of relapses in
the last two years" significantly associated with response to
glatiramer acetate (combined cohorts p-value 3.6.times.10.sup.-32,
odds ratio 14.5 (95% CI 8.6-24.4)) and "Baseline Expanded
Disability Status Scale (EDSS) Score" (combined cohorts p-value
5.9.times.10.sup.-10, odds ratio 0.62 (95% CI 8.6-24.4)) with
higher baseline EDSS scores (increased MS disability) associated
with increased likelihood of non-response to glatiramer acetate.
Importantly, these clinical factors were significantly associated
with glatiramer acetate response in both the GALA and FORTE patient
cohorts.
[0337] Results of regression analyses for the Additive Models are
presented in Tables 34-37.
[0338] In some embodiments, all of the genetic markers presented in
Tables 34-37 are identified as predictive of response to glatiramer
acetate.
Example 15 Selection of Genetic Markers Predictive of Response to
Glatiramer Acetate
[0339] Based on the analyses above, genetic markers were selected
as Predictive of Response to Glatiramer Acetate based on the
following p-value thresholds: Priority candidate variants:
P<0.05 (combined cohorts); Priority Genes: Replicated P<0.05
in both cohorts; GWAS: P<10-4 (combined cohorts); and Placebo
P<10-4 (placebo cohort).
[0340] The selected genetic markers are presented in Tables 38-41.
Alleles associated with response are highlighted.
Example 16 Selection of Genetic Markers for Predictive Models
[0341] A total of 11 genetic variants were selected for inclusion
in a preliminary multi-marker risk prediction model. Importantly,
many of the identified genes have been previously implicated in MS
and/or glatiramer acetate response (i.e., MAGI2, HLA-DOB/TAP2
region, MBP, ALOX5AP, and the HLA-DRB1-15:01 polymorphism).
[0342] Variants were identified and selected using a multi-step
approach, beginning with the selection of replicated variants from
a priority list of 35 candidate variants. This led to one variant
selected for inclusion into the model: rs3135391, a marker of
HLA-DRB1*1501, P<0.05 in Gala, P<0.05 in Forte, P=0.014
combined, odds ratio 1.6).
[0343] This was followed by selection of three replicated variants
from a list of 4,012 variants in 30 priority genes (kgp8817856 in
HLA-DQB2/DOB, p<0.001 in Gala, p<0.001 in Forte, p-value
5.33E-06, odds ratio 0.53; rs1894408 in HLA-DOB/TAP2, p<0.01 in
Gala, p<0.01 in Forte, p-value 0.000098, odds ratio 1.7; and
kgp7747883 in MBP, p<0.05 in Gala, p<0.01 in Forte, p-value
0.00086, odds ratio 0.64).
[0344] This was followed by a selection of two variants from a list
of 25,000 candidate variants in 180 second priority genes
(kgp6599438 in PTPRT, p<0.01 in Gala, p<0.05 in Forte,
p-value 0.00025, odds ratio 0.26; and rs10162089 in ALOX5AP,
p<0.01 in Gala, p<0.05 in Forte, p-value 0.0014, odds ratio
1.5).
[0345] Finally, three variants were selected from the entire
genome-wide panel (rs16886004 in MAGI2, p<0.005 in Gala,
p<0.00005 in Forte, p-value 0.00000098 combined, odds ratio 2.8;
kgp24415534 in the ZAK/CDCA7 gene region, p<0.00005 in Gala,
p<0.05 in Forte, p-value 0.000000398, odds ratio 0.08; and
kgp8110667 in the RFPL3/SLC5A4 region, p<0.01 in Gala, p<0.05
in Forte, p-value 0.00014, odds ratio: infinity).
[0346] In addition, two variants were selected from the entire
genome-wide panel using an extreme phenotype definition (kgp6214351
in the UVRAG gene, combined p-value 0.0000055, odds ratio 0.35; and
rs759458 in SLC1A4, combined p-value 0.002; odds ratio 1.6). The
statistics of the selected 11 SNPs are shown for the additive,
allelic, and genotypic genetic models. The statistics of the
selected 11 SNPs are shown for the additive, allelic, and genotypic
genetic models (Tables 42, 43 and 44a and 44b, respectively).
TABLE-US-00008 TABLE 44b Genotypic Model Characteristics of
Individual SNPs in Model SNP - rs SNP - kgp rs759458 rs139890339
kgp24415534 rs3135391 rs28724893 kgp8817856 rs1894408 rs16886004
rs80191572 kgp6214351 rs10162089 rs1789054 kgp7747883 rs117602254
kgp6599438 rs73166319 kgp8110667
Example 17 Preliminary Predictive Model: Clinical and Genetic
Factors Combined
[0347] A predictive model was generated based on the 11 SNPs shown
in tables 42, 43, 44a and 44b and the two Clinical co-variants
shown in table 33.
[0348] Receiver Operating Characteristic (ROC) analysis was
performed using the actual value (case or control) and predicted
value for each sample from the multi-marker regression model (FIG.
1). For these preliminary analyses, two risk groups were defined
using the predicted values from the multi-marker regression model.
The predictive threshold value was set at 0.71 (termed "model 3")
based on a variety of factors after consultation with the Teva team
and Teva MS clinical experts.
[0349] Ultimately, a threshold that best differentiated between
responders and non-responders (minimum positive predictive value of
90% or higher) (FIG. 2), while maximizing the number of predicted
responders (predicted responders >60%) (FIG. 3) was selected.
This threshold also coincided with the lowest p-value of all the
thresholds examined (Chi square p-value 6.1.times.10.sup.-46, odds
ratio 19.9) (FIG. 4). The positive predictive value (% of all
predicted responders to be true responders) was 91.1%, sensitivity
(% of all true responders detected) was 80.2%; specificity (% of
all true non-responders classified as non-responders) was 83.1%;
and the negative predictive value (% of all true non-responders
classified as non-responders) was 65.9%.
Example 18 Patient Responses Predicted by the Preliminary
Predictive Model
[0350] For the genotyped patients of the Gala and Forte cohorts,
based on the predictive model, 60% of patients were classified as
"predicted responders" with a response rate of 91.1% (as defined by
the a priori definition of responders and non-responders). While
40% of patients were classified as "predicted non-responders" with
an overall response rate of 34% (FIG. 5).
[0351] Compared to the "predicted non-responders", the "predicted
responders" exhibited a 2.7-fold improved response rate (91% vs.
34%) (P<10.sup.-40); and the "predicted responders" had a 34%
improvement in response rate compared to the overall cohort (68%
vs. 91%).
[0352] The annualized relapse rate (ARR) of the "predicted
responders" (0.21.+-.0.03 standard error of the mean) was reduced
(improved) by 60% compared to the overall patient cohort
(0.53.+-.0.04), and reduced (improved) by 80% compared to the
"predicted non-responders" (1.04.+-.0.08) (p-value
2.2.times.10.sup.-25).
[0353] The number of confirmed relapses (nrelapse) of the
"predicted responders" (0.19.+-.0.03 standard error of the mean)
was reduced (improved) by 58% compared to the overall patient
cohort (0.46.+-.0.03), and reduced (improved) by 78% compared to
the "predicted non-responders" (0.88.+-.0.06) (p-value
7.70.times.10.sup.-32).
[0354] The number of T1 enhancing lesions at month 12 was
significantly reduced (improved) by 47% in the "predicted
responders" compared to the "predicted non-responders"
(0.91.+-.0.18 versus 1.70.+-.0.38; p-value 0.043). Similarly, EDSS
progression was significantly delayed (improved) by 72% in the
"predicted responders" versus the "predicted non-responders"
(0.03.+-.0.01 vs. 0.10.+-.0.02; p-value 0.00095), and showed a
strong trend with a 49% reduced progression compared to the overall
cohort (value 0.057, p-value 0.08).
Predictive Modeling
[0355] A predictive model based on the identified markers was
developed and tested in the full cohorts, including intermediate
responders. Additional independent cohorts are used to evaluate and
confirm the predictive model.
[0356] DNA was collected from consenting RRMS patients in one year
GALA study (40 mg Copaxone TIW, or placebo) and one year FORTE
study (20 mg Copaxone or 40 mg Copaxone daily) ("PGx population")
(Table 45) The PGx (i.e. the population studied for genetic
analyses) and ITT (intent to treat) populations did not differ on
baseline characteristics.
[0357] To identify genetic markers associated with high response to
Copaxone.RTM. comprising the following characteristics: (1) high
response as measured by ARR reductions, (2) predictive, not
prognostic, markers: associated with response only in
Copaxone.RTM.-treated patients, and not in the placebo group, (3)
markers that are confirmed in an independent cohort, and (4) a
subset of GALA and FORTE studies' patients with clarly defined
response phenotypes (high responders versus low responders) (FIG.
6) Patient DNA samples were genotyped for 4.3 million genetic
variants (Illumina HumanOmni5 array).
[0358] Association analysis, using a tiered candidate-marker and
genome-wide approach, was conducted in the GALA cohort to identify
GA-specific response-associated SNPs. SNPs that were not associated
with placebo response and that replicated in the FORTE cohort, were
selected for modeling.
[0359] Regression analysis was applied, with the threshold for
distinguishing responders from non-responders was selected by
analysis of receiver-operator curves. Intermediate responders were
genotyped by either Illumina 5M array or focused taqman-based SNP
genotyping and Sanger sequencing.
[0360] The SNP-signature was evaluated in the full GALA/FORTE
population including intermediate patients (FIG. 7). In the high
response/low response subgroups of both GALA and FORTE, the SNP
signature exhibited highly predictive characteristics (OR 6 to 8,
p-value<10.sup.-11) (Table 46). Validation of the identified
model can be applied to additional independent cohorts.
[0361] The signature was associated with Copaxone.RTM.-, and not
placebo-response since 129 placebo-treated patients were predicted
to be high Copaxone.RTM.-responders based on the signature. These
patients of not show ARR reduction when treated with placebo (3%
ARR reduction versus remaining placebo patients who provided DNA
samples (n=252)) The SNP signature was significantly associated
with high response to Copaxone in both GALA and FORTE (OR of 1.9 to
3.8, p<0.002 including sensitivity analysis) and not in placebo
(OR of 0.9 to 1.2, NS).
[0362] Genetic association with response to Copaxone.RTM., and not
placebo, was identified. In Copaxone.RTM. naive RRMS patients, the
11 SNP signature identifies high Copaxone.RTM. responders who
exhibit significantly greater reductions in ARR compared to the
average response observed in Copaxone.RTM. clinical trials.
TABLE-US-00009 TABLE 45 Baseline characteristics of PGx and ITT
populations Study GALA FORTE Population ITT PGx ITT PGx N 1404 1158
(82%) 1155 604 (52%) Age (Ave .+-. SD) 37.6 .+-. 9.35 37.71 .+-.
9.38 36.27 .+-. 8.99 35.97 .+-. 8.82 Gender (% Female) 67.90%
67.90% 71.70% 72.20% Caucasian 97.60% 97.90% 95.20% 100% Disease
duration (years) 3.76 .+-. 4.9 3.74 .+-. 4.94 3.16 .+-. 4.41 2.86
.+-. 4.05 No. of Relapses in the Last 2 Years 1.91 .+-. 0.91 1.89
.+-. 0.92 2.01 .+-. 1.00 1.97 .+-. 0.89 Baseline EDSS 2.79 .+-.
1.23 2.77 .+-. 1.21 2.12 .+-. 1.12 2.13 .+-. 1.12
TABLE-US-00010 TABLE 46 Genes of the 11 SNP Signature GALA FORTE
GA-treated GA-treated Genes of 11-SNP Signature * OR OR
HLA-DRB1*15:01 0.7 0.6 HLA gene region 1.7 1.8 Myelin basic protein
gene 0.7 0.6 Receptor-tyrosine protein phosphatase gene 0.2 0.3
Arachidonate 5-lipoxygenase-activating 1.6 1.6 protein
Membrane-associated guanylate kinase gene 2.2 5.6 Solute carrier
family 5 (low affinity glucose Inf. Inf. co-transporter) gene HLA
gene region 0.5 0.5 Mitogen-activated protein kinase gene region
0.05 0.1 Radiation resistance-associated gene protein 0.2 0.1
Glutamate/neutral amino acid transporter 3.3 1.9 * All SNPs met
statistical significance
Example 19
[0363] Additional genotyping of the 11 SNPs of the predictive model
(rs3135391, rs1894408, kgp7747883, kpg6599438, rs10162089,
rs16886004, kgp8110667, kgp8817856, kgp24415534, kgp6214351,
rs759458) was conducted on the remaining portion of the patients
from the GALA and FORTE cohorts, for which DNA was available (FIG.
8).
[0364] When analysis was conducted for all genotyped patients of
the Gala and FORTE cohorts, based on the predictive model (11 SNPs
and 2 clinical variables), 34% of GALA, and 42% of FORTE--patients
were classified as "predicted responders".
[0365] In the GALA Copaxone treated patients, the annualized
relapse rate (ARR) of the "predicted responders" (0.185.+-.0.032
standard error of the mean) was reduced (improved) by 51% compared
to the "predicted non-responders" (0.374.+-.0.038) (p-value=0.0028)
and by 64% compared to the placebo (0.510.+-.0.062)
(p-value<0.0001).
[0366] In the FORTE Copaxone treated patients, the annualized
relapse rate (ARR) of the "predicted responders" (0.102.+-.0.020
standard error of the mean) was reduced (improved) by 72% compared
to the "predicted non-responders" (0.368.+-.0.039)
(p-value<0.0001).
[0367] In some embodiments, the at least one single nucleotide
polymorphisms (SNPs) are selected from the group consisting of
kgp24415534, kgp6214351, kgp6599438, kgp7747883, kgp8110667,
kgp8817856, rs10162089, rs16886004, rs1894408, rs3135391, and
rs759458.
[0368] In some embodiments, the at least one single nucleotide
polymorphisms (SNPs) comprise 2, 3, 4, 5, 6, 7, 8, 9 or 10 of the
SNPs selected from the group consisting of kgp24415534, kgp6214351,
kgp6599438, kgp7747883, kgp8110667, kgp8817856, rs10162089,
rs16886004, rs1894408, rs3135391 and rs759458.
[0369] In some embodiments, the at least one single nucleotide
polymorphisms (SNPs) are selected from the group consisting of
kgp24415534, kgp6214351, kgp6599438, kgp7747883, kgp8110667,
kgp8817856, rs10162089, rs16886004, rs1894408, and rs759458.
[0370] In some embodiments, the at least one single nucleotide
polymorphisms (SNPs) comprise 2, 3, 4, 5, 6, 7, 8, 9 or 10 of the
SNPs selected from the group consisting of kgp24415534, kgp6214351,
kgp6599438, kgp7747883, kgp8110667, kgp8817856, rs10162089,
rs16886004, rs1894408 and rs759458.
[0371] In some embodiments, the at least one SNPs is selected from
the group further comprising rs3135391.
[0372] In some embodiments, if rs3135391 is the at least one SNP
selected, then selecting at least one SNP other than rs3135391.
[0373] In some embodiments, the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined by indirect genotyping.
[0374] In some embodiments, the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined indirectly by determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs.
[0375] In some embodiments, the genotype is determined at locations
corresponding to the locations of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, or more SNPs.
[0376] In some embodiments, one or more SNPs is selected from the
group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp7747883, kgp8110667, kgp8817856, rs10162089, rs16886004,
rs1894408, rs3135391, and rs759458.
[0377] In some embodiments, one or more SNPs comprise 2, 3, 4, 5,
6, 7, 8, 9 or 10 of the SNPs selected from the group consisting of
kgp24415534, kgp6214351, kgp6599438, kgp7747883, kgp8110667,
kgp8817856, rs10162089, rs16886004, rs1894408, rs3135391, and
rs759458.
[0378] In some embodiments, one or more SNPs is selected from the
group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp7747883, kgp8110667, kgp8817856, rs10162089, rs16886004,
rs1894408, and rs759458.
[0379] In some embodiments, one or more SNPs comprise 2, 3, 4, 5,
6, 7, 8, 9 or 10 of the SNPs selected from the group consisting of
kgp24415534, kgp6214351, kgp6599438, kgp7747883, kgp8110667,
kgp8817856, rs10162089, rs16886004, rs1894408, and rs759458.
[0380] In some embodiments, the one or more SNPs is selected from
the group further comprising rs3135391.
[0381] In some embodiments, if rs3135391 is the one SNP selected,
then selecting at least one SNP other than rs3135391.
[0382] In some embodiments, the method further comprising applying
the algorithm depicted in FIG. 8 or FIG. 9 to identify the subject
as a predicted responder or as a predicted non-responder to
glatiramer acetate.
[0383] In some embodiments the kit for identifying a human subject
afflicted with multiple sclerosis or a single clinical attack
consistent with multiple sclerosis as a predicted responder or as a
predicted non-responder to glatiramer acetate, or for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis who is predicted
to have a slower course of disease progression, the kit comprising
[0384] a) at least one probe specific for a location corresponding
to the location of at least one SNP; [0385] b) at least one pair of
PCR primers designed to amplify a DNA segment which includes a
location corresponding to the location of at least one SNP; [0386]
c) at least one pair of PCR primers designed to amplify a DNA
segment which includes a location corresponding to the location of
at least one SNP and at least one probe specific for a location
corresponding to the location of at least one SNP; [0387] d) a
reagent for performing a method selected from the group consisting
of restriction fragment length polymorphism (RFLP) analysis,
sequencing, single strand conformation polymorphism analysis
(SSCP), chemical cleavage of mismatch (CCM), gene chip and
denaturing high performance liquid chromatography (DHPLC) for
determining the identity of at least one SNP; or [0388] e) reagents
for TaqMan Open Array assay designed for determining the genotype
at a location corresponding to the location of at least one SNP,
[0389] wherein the at least one SNP is selected from the group
consisting of kgp24415534, kgp6214351, kgp6599438, kgp7747883,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408,
rs3135391, and rs759458; or [0390] wherein the at least one SNP is
selected from the group consisting of kgp24415534, kgp6214351,
kgp6599438, kgp7747883, kgp8110667, kgp8817856, rs10162089,
rs16886004, rs1894408, and rs759458.
[0391] In some embodiments, the kit further comprising applying the
algorithm depicted in FIG. 8 or FIG. 9 to identify the subject as a
predicted responder or as a predicted non-responder to glatiramer
acetate.
Example 20
[0392] Analysis was conducted for all genotyped patients of the
Gala and FORTE cohorts, based on the 11 SNPs in the predictive
model, but without including the clinical variables, and using a
threshold at .about.30% of the population classified as "predicted
responders" (FIG. 9).
[0393] In the GALA Copaxone treated patients, the annualized
relapse rate (ARR) of the "predicted responders" (0.131.+-.0.026
standard error of the mean) was reduced (improved) by 62% compared
to the "predicted non-responders" (0.382.+-.0.037)
(p-value<0.0001) and by 71% compared to the placebo
(0.488.+-.0.058) (p-value<0.0001).
[0394] In the FORTE Copaxone treated patients, the annualized
relapse rate (ARR) of the "predicted responders" (0.145.+-.0.029
standard error of the mean) was reduced (improved) by 50% compared
to the "predicted non-responders" (0.290.+-.0.03)
(p-value=0.0113).
[0395] In some embodiments, the method further comprising applying
the algorithm depicted in FIG. 9 to identify the subject as a
predicted responder or as a predicted non-responder to glatiramer
acetate.
[0396] In some embodiments, the method further comprising applying
the algorithm depicted in FIG. 8 or FIG. 9 to identify the subject
as a predicted responder or as a predicted non-responder to
glatiramer acetate.
[0397] In some embodiments, the kit further comprising applying the
algorithm depicted in FIG. 8 or FIG. 9 to identify the subject as a
predicted responder or as a predicted non-responder to glatiramer
acetate.
Example 21
[0398] Additional genotyping of 10 SNPs of the predictive model
(rs3135391, rs1894408, kpg6599438, rs10162089, rs16886004,
kgp8110667, kgp8817856, kgp24415534, kgp6214351, rs759458) was
conducted on the remaining portion of the patients from the GALA
and FORTE cohorts, for which DNA was available.
[0399] When analysis was conducted for all genotyped patients of
the Gala and FORTE cohorts, based on the 10 SNPs and 2 clinical
variables, 34% of GALA, and 42% of FORTE--patients were classified
as "predicted responders".
[0400] In the GALA Copaxone treated patients, the annualized
relapse rate (ARR) of the "predicted responders" (0.185.+-.0.032
standard error of the mean) was reduced (improved) by 51% compared
to the "predicted non-responders" (0.374.+-.0.038) (p-value=0.0028)
and by 64% compared to the placebo (0.510.+-.0.062)
(p-value<0.0001).
[0401] In the FORTE Copaxone treated patients, the annualized
relapse rate (ARR) of the "predicted responders" (0.102.+-.0.020
standard error of the mean) was reduced (improved) by 72% compared
to the "predicted non-responders" (0.368.+-.0.039)
(p-value<0.0001).
[0402] In some embodiments, the genotype is determined at locations
corresponding to the locations of 2, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, or more SNPs.
[0403] In some embodiments, one or more SNPs is selected from the
group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408,
rs3135391, and rs759458.
[0404] In some embodiments, one or more SNPs is selected from the
group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408, and
rs759458.
[0405] In some embodiments, one or more SNPs is selected from the
group further comprising rs3135391.
[0406] In some embodiments, one or more SNPs comprise 2, 3, 4, 5,
6, 7, 8, 9 or 10 of the SNPs selected from the group consisting of
kgp24415534, kgp6214351, kgp6599438, kgp8110667, kgp8817856,
rs10162089, rs16886004, rs1894408, rs3135391, and rs759458.
[0407] In some embodiments, if rs3135391 is the one SNP selected,
then selecting at least one SNP other than rs3135391.
[0408] In some embodiments, the at least one single nucleotide
polymorphisms (SNPs) comprise 2, 3, 4, 5, 6, 7, 8, 9 or 10 of the
SNPs selected from the group consisting of kgp24415534, kgp6214351,
kgp6599438, kgp8110667, kgp8817856, rs10162089, rs16886004,
rs1894408, rs3135391 and rs759458.
[0409] In some embodiments, if rs3135391 is the at least one SNP
selected, then selecting at least one SNP other than rs3135391.
[0410] In some embodiments, the at least one SNP is selected from
the group further comprising rs3135391.
[0411] In some embodiments, the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined by indirect genotyping.
[0412] In some embodiments, the genotype of the subject at the
location corresponding to the location of one or more of the SNPs
is determined indirectly by determining the genotype of the subject
at a location corresponding to the location of at least one SNP
that is in linkage disequilibrium with the one or more SNPs.
[0413] In some embodiments the kit for identifying a human subject
afflicted with multiple sclerosis or a single clinical attack
consistent with multiple sclerosis as a predicted responder or as a
predicted non-responder to glatiramer acetate, or for identifying a
human subject afflicted with multiple sclerosis or a single
clinical attack consistent with multiple sclerosis who is predicted
to have a slower course of disease progression, the kit comprising
[0414] a) at least one probe specific for a location corresponding
to the location of at least one SNP; [0415] b) at least one pair of
PCR primers designed to amplify a DNA segment which includes a
location corresponding to the location of at least one SNP; [0416]
c) at least one pair of PCR primers designed to amplify a DNA
segment which includes a location corresponding to the location of
at least one SNP and at least one probe specific for a location
corresponding to the location of at least one SNP; [0417] d) a
reagent for performing a method selected from the group consisting
of restriction fragment length polymorphism (RFLP) analysis,
sequencing, single strand conformation polymorphism analysis
(SSCP), chemical cleavage of mismatch (CCM), gene chip and
denaturing high performance liquid chromatography (DHPLC) for
determining the identity of at least one SNP; or [0418] e) reagents
for TaqMan Open Array assay designed for determining the genotype
at a location corresponding to the location of at least one SNP,
[0419] wherein the at least one SNP is selected from the group
consisting of kgp24415534, kgp6214351, kgp6599438, kgp8110667,
kgp8817856, rs10162089, rs16886004, rs1894408, rs3135391, and
rs759458; or [0420] wherein the at least one SNP is selected from
the group consisting of kgp24415534, kgp6214351, kgp6599438,
kgp8110667, kgp8817856, rs10162089, rs16886004, rs1894408, and
rs759458.
[0421] In some embodiments, the method further comprising applying
the algorithm depicted in FIG. 8 or FIG. 9 to identify the subject
as a predicted responder or as a predicted non-responder to
glatiramer acetate.
[0422] In some embodiments, the kit further comprising applying the
algorithm depicted in FIG. 8 or FIG. 9 to identify the subject as a
predicted responder or as a predicted non-responder to glatiramer
acetate.
Biology of High Response to Copaxone.RTM.
[0423] Identified genes are associated with Copaxone.RTM.
(glatiramer acetate, or GA) mechanism of action. These genes
include: (1) Myelin Basic Protein (MBP), which is associated with
Copaxone.RTM. response (38), and Copaxone.RTM. designed to mimic
MBP; (2) MHC region (3 SNPs), including HLA-DRB1*15:01 (37)
involved in antigen processing and presentation and is associated
with Copaxone.RTM. response and MS susceptibility or severity; and
(3) arachidonate 5-lipoxygenase-activating protein, involved in
synthesis of leukotrienes (inflammation) and associated with
Copaxone.RTM. response (40).
[0424] Identified genes are also associated with MS severity and/or
the brain. These genes include: (1) Membrane-associated guanylate
kinase, a synaptic junction scaffold molecule exclusively expressed
in brain and shown to modulate MS severity; (2) Glutamate/neutral
amino acid transporter, which transports glutamate and alanine (2
of the 4 amino acid components of Copaxone.RTM.), as well as
serine, cysteine, and threonine and has highest expression in
brain; (3) Radiation resistance-associated gene protein, which is
highly expressed in brain and has a role in axis formation and
autophagy; and (4) Receptor-tyrosine protein phosphatase,
associated with Copaxone.RTM. response, and tyrosine
phosphorylation involved in myelin formation, differentiation of
oligodendrocytes and Schwann cells, and recovery from demyelinating
lesions.
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