U.S. patent application number 14/069749 was filed with the patent office on 2016-07-21 for computer-assisted means for assessing lifestyle risk factors.
This patent application is currently assigned to BODYSYNC, INC.. The applicant listed for this patent is BODYSYNC, INC.. Invention is credited to Rosalynn D. Gill, Christopher J. Martin, Manuel V. Sanchez-Felix.
Application Number | 20160210880 14/069749 |
Document ID | / |
Family ID | 25093375 |
Filed Date | 2016-07-21 |
United States Patent
Application |
20160210880 |
Kind Code |
A1 |
Gill; Rosalynn D. ; et
al. |
July 21, 2016 |
COMPUTER-ASSISTED MEANS FOR ASSESSING LIFESTYLE RISK FACTORS
Abstract
The present invention relates to methods of assessing disease
susceptibility associated with dietary and lifestyle risk factors.
The invention provides for analysis of alleles at loci of genes
associated with lifestyle risk factors, and the disease
susceptibility profile of an individual is determined by reference
to datasets which further match the risk factor with lifestyle
recommendations in order to produce a personalized lifestyle advice
plan.
Inventors: |
Gill; Rosalynn D.; (Boulder,
CO) ; Martin; Christopher J.; (Isle of Wight, GB)
; Sanchez-Felix; Manuel V.; (Isle of Wight, GB) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
BODYSYNC, INC. |
REDONDO BEACH |
CA |
US |
|
|
Assignee: |
BODYSYNC, INC.
REDONDO BEACH
CA
|
Family ID: |
25093375 |
Appl. No.: |
14/069749 |
Filed: |
November 1, 2013 |
Related U.S. Patent Documents
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Application
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Filing Date |
Patent Number |
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13590919 |
Aug 21, 2012 |
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14069749 |
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13073601 |
Mar 28, 2011 |
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13590919 |
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12627554 |
Nov 30, 2009 |
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13073601 |
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11277525 |
Mar 27, 2006 |
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12627554 |
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09771933 |
Jan 30, 2001 |
7054758 |
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11277525 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G16H 10/40 20180101;
G06Q 50/22 20130101; G16H 10/60 20180101; G06Q 50/24 20130101; G16B
25/00 20190201; G09B 5/02 20130101; G16B 40/00 20190201; G06F
19/3481 20130101; G16H 20/70 20180101; G16H 50/30 20180101; G09B
19/0092 20130101 |
International
Class: |
G09B 19/00 20060101
G09B019/00; G09B 5/02 20060101 G09B005/02; G06F 19/00 20060101
G06F019/00 |
Claims
1. A computer assisted method of providing a personalized lifestyle
advice plan for a human subject comprising: (i) providing a first
dataset on a data processing means, said first dataset comprising
information correlating the presence of individual alleles at
genetic loci with a lifestyle risk factor, wherein at least one
allele of each genetic locus is known to be associated with
increased or decreased disease susceptibility; (ii) providing a
second dataset on a data processing means, said second dataset
comprising information matching each said risk factor with at least
one lifestyle recommendation; (iii) inputting a third dataset
identifying alleles at one or more of the genetic loci of said
first dataset of said human subject; (iv) determining the risk
factors associated with said alleles of said human subject using
said first dataset; (v) determining at least one appropriate
lifestyle recommendation based on each identified risk factor from
step (iv) using said second dataset; and (vi) generating a
personalized lifestyle advice plan based on said lifestyle
recommendations.
2. The method according to the method of claim 1 wherein the
personalized lifestyle advice plan includes recommended minimum
and/or maximum amounts of food subtypes.
3. The method according to claim 1 wherein the method comprises the
step of delivering the report to the client.
4. The method according to claim 3 wherein the plan is delivered
via the Inter net and accessible via a unique identifier code.
5. The method according to claim 4 wherein the plan comprises
hyperlinks to one or more Web pages.
6. The method according to claim 1 wherein said first dataset
comprises information relating to two or more alleles of one or
more genetic loci of genes selected from the group comprising: (a)
genes that encode enzymes responsible for detoxification of
xenobiotics in Phase I metabolism; (b) genes that encode enzymes
responsible for conjugation reactions in Phase II metabolism; (c)
genes that encode an enzyme that helps cells to combat oxidative
stress; (d) genes associated with micronutrient deficiency; and (e)
genes that encode an enzyme responsible for metabolism of alcohol.
(f) genes that encode enzymes involved in lipid and/or cholesterol
metabolism; (g) genes that encode enzymes involved in clotting; (h)
genes that encode trypsin inhibitors; (i) genes that encode enzymes
related to susceptibility to metal toxicity; (j) genes which encode
proteins required for normal cellular metabolism and growth; (k)
genes which encode HLA Class 2 molecules.
7. The method according to claim 6 wherein said first dataset
comprises information relating to two or more alleles of one or
more genetic loci of genes selected from each member of the group
comprising: (a) genes that encode enzymes responsible for
detoxification of xenobiotics in Phase I metabolism; (b) genes that
encode enzymes responsible for conjugation reactions in Phase II
metabolism; (c) genes that encode enzymes that helps cells to
combat oxidative stress; (d) genes associated with micronutrient
deficiency; and (e) genes that encode enzymes responsible for
metabolism of alcohol. (f) genes that encode enzymes involved in
lipid and/or cholesterol metabolism; (g) genes that encode enzymes
involved in clotting; (h) genes that encode trypsin inhibitors; (i)
genes that encode enzymes related to susceptibility to metal
toxicity; (j) genes which encode proteins required for normal
cellular metabolism and growth; (k) genes which encode HLA Class 2
molecules.
8. The method according to claim 6 wherein said first dataset
comprises information relating to two or more alleles of one or
more genetic loci of genes encoding an enzyme selected from the
group comprising: cytochrome P450 monooxygenase,
N-acetyltransferase 1, N-acetyltransferase 2,
glutathione-S-transferase, manganese superoxide dismutase,
5,10-methylenetetrahydrofolatereductase and alcohol dehydrogenase
2.
9. The method according to claim 8 wherein said first dataset
comprises information relating to two or more alleles of one or
more genetic loci of each of the genes encoding cytochrome P450
monooxygenase, N-acetyltransferase 1, N-acetyltransferase 2,
glutathione-S-transferase, manganese superoxide dismutase,
5,10-methylene-tetrahydrofolatereductase and alcohol dehydrogenase
2.
10. The method according to claim 1 including the step determining
the presence of individual alleles at one or more genetic loci of
the DNA in a DNA sample of said human subject, and constructing the
dataset used in step (iii) using results of said determination.
11. The method according to claim 10 wherein said presence of said
individual alleles is determined by hybridisation with
allele-specific oligonucleotides.
12. The method according to claim 11 wherein said allele specific
oligonucleotides are selected from oligonucleotides each specific
for one of the genes selected from the group comprising the CYP1A1
gene, the GST.mu. gene, the GST.pi. gene, the GST.theta. gene, the
NAT1 gene, the NAT2 gene, the MnSOD gene, the MTHFR gene and the
ALDH2 gene.
Description
[0001] This application is a divisional of Ser. No. 09/771,933,
filed Jan. 30, 2001 (allowed), the entire contents of which is
incorporated herein by reference.
FIELD OF THE INVENTION
[0002] The present invention relates to methods of assessing
disease susceptibility. In particular, it relates to methods of
assessing disease susceptibility associated with dietary and
lifestyle risk factors.
BACKGROUND TO THE INVENTION
[0003] Cancer is a disease influenced primarily by external
factors. Up to 80% of human cancers arise from exposure to
environmental agents. The majority of cancer is believed to be
preventable because exposure to these external factors should be
manageable (Giovannucci, 1999; Perera, 2000).
[0004] Human tumours result from a series of mutational events,
leading to the loss of the regulatory mechanisms that govern normal
cell behaviour and ultimately resulting in the formation of a
tumour with full metastatic (or invasive) potential (Smith, 1995).
All higher organisms have developed a complex variety of mechanisms
to protect themselves from environmental insult, for example from
ingested plant toxins. One of the most important protection
measures involves the metabolism of toxins (or xenobiotics) leading
to detoxification and ultimately excretion of the toxin (Smith,
1995). Unfortunately, the metabolic pathways do not always lead to
detoxification of the toxin. Indeed many chemical carcinogens are
activated by these same metabolic pathways to react with cellular
macromolecules.
[0005] Improvements in genetic analysis and the availability of
human genetic sequence information arising from the Human Genome
Project has added another facet to the analysis of cancer
susceptibility, that of inter-individual variation at the genome
level. Molecular epidemiology has already begun to clarify some of
the gene-environment interactions that may lead to disease. The
ultimate goal of molecular epidemiology is to develop risk
assessment models for individuals, and already the field has
provided insight into inter-individual variation in human cancer
risk (Shields, 2000). Molecular epidemiology focuses on three major
determinants of human cancer risk: inherited host susceptibility
factors, molecular dosimetry of carcinogen exposure, and biomarkers
of early effects of carcinogenic exposure. The variability in
metabolic activity, detoxification and DNA repair of the US
population could be as high as 85-500-fold with correspondingly
high variability in cancer risk (Hattis, 1986). Considering the
latency of cancer, the importance of correlating individual risk
with biomarkers at an early stage becomes apparent. These
biomarkers can help to identify populations or individuals at risk
of cancer resulting from specific environment-gene
interactions.
[0006] Defining the factors that contribute to inter-individual
variations in cancer susceptibility has been a major focus of
research for many years. Given the suggested role of environmental
factors in carcinogenesis, some of the candidate genes are those
that encode the xenobiotic-metabolising enzymes that activate or
inactivate carcinogens. Variable levels of expression of these
enzymes could result in increased or decreased carcinogen
activation. Other genetic factors that could contribute to cancer
susceptibility include genes involved in DNA repair,
proto-oncogenes, tumour suppressor genes, cell-cycle genes, as well
as genes involved in aspects of nutrition, hormonal status, and
immunological responses. Emerging data from the Human Genome
Project has led to studies that show combinations of metabolic
polymorphisms are increasingly being linked to a greater risk of
cancer (Perera, 1997). Studies which have measured the formation of
DNA adducts as a marker of enzyme activity have found that the
levels of DNA damage or protein adducts vary considerably between
persons with apparently similar exposure (Bryant, 1987; Perera,
1992; Mooney, 1995). The observed variability reflects a
combination of true biologic factors, unaccounted for by
differences in exposure or laboratory variation (Dickey, 1997). In
fact, lower exposures to carcinogens can result in proportionately
higher adduct levels because of a person's genetic predisposition
for increased carcinogen metabolic activation (Kato, 1995; Vineis,
1997).
[0007] The existence of multiple alleles at loci that encode
xenobiotic-metabolising enzymes can result in differential
susceptibilities of individuals to the carcinogenic effects of
various chemicals. Metabolism in humans occurs in two distinct
phases: Phase I Metabolism involves the addition of an oxygen atom
or a nitrogen atom to lipophilic (fat soluble) compounds such as
steroids, fatty acids, xenobiotics (from external sources like
diet, smoke, etc.) so that they can be conjugated to glutathione or
N-acetylated by the Phase II enzymes (thus made water-soluble) and
excreted from the body. There are superfamilies of
xenobiotic-metabolising enzymes: cytochrome P450's (Phase I), GSTs
(Phase II) and NATs (Phase I and II) which are thought to have
evolved as an adaptive response to environmental insult.
Alterations in the activity of these enzymes are predicted to
result in an altered susceptibility to cancer (Hirvonen, 1999).
[0008] Enzymatic activation of xenobiotics is not, however, the
only route to cancer development. Epidemiological studies suggest
that nutritional factors may also play a causative role in more
than 30% of human cancers. However, defining the precise roles of
specific dietary factors in the development of cancer is difficult
due to the multitude of variables involved (Perera, 2000). Specific
dietary factors are not easily measured as a single quantifiable
variable, such as number of cigarettes smoked per day. Further
complications arise due to differences in methodology, control
populations, types of carcinogens, and amounts of exposure to
carcinogens.
[0009] Priorities for studies relating to the interrelationship of
dietary factors and cancer susceptibility include identification of
genetic factors that contribute to individual cancer risk,
identification of cancer-preventative chemicals in fruits and
vegetables, better understanding of carcinogenic role of polycyclic
aromatic hydrocarbons and heterocyclic amines generated by cooking
meats at high temperature, and better understanding of the role of
increased caloric intake with increased cancer risk (Perera,
2000).
[0010] Increased consumption of vegetables and fruits is correlated
with a decreased risk of cancer, and studies of this aspect of
nutritional effects on cancer has led to the identification of
other enzymes and micronutrients involved in the maintenance of a
normal cellular phenotype (Giovannuci, 1999).
[0011] One quarter of the US population with low intake of fruits
and vegetables has roughly twice the cancer rate for most types of
cancer (lung, larynx, oral cavity, esophagus, stomach, colon and
rectum, bladder, pancreas, cervix, and ovary) when compared with
the quarter with the highest intake (Ames, 1999). Fruit and
vegetables are high in folate and antioxidants. Low intake can lead
to micronutrient deficiency, which has been shown to cause DNA
damage in a way that mimics radiation damage by causing single and
double-stranded breaks, oxidative lesions or both. The
micronutrients correlated with DNA-damaging activity include folate
(or folic acid), iron, zinc, and vitamins B12, B6, C and E (Ames,
1999).
[0012] Of the cancers that are correlated with nutritional effects,
colon cancer (colorectal neoplasia) has among the strongest links
to diet. In the US, colon cancer is the fourth most common incident
cancer and second most common cause of cancer death in the US, with
130,000 new cases and 55,000 deaths per year (Potter, 1999).
According to the WHO, colorectal cancers are the second most common
cause of cancer death in Britain (WHO, 1997). Worldwide colon
cancer represents 8.5% of new cancer cases reported, with the
highest rates seen in the developed world and the lowest rates in
India. Colon cancer occurs with approximately equal frequency in
men and women, and the occurrence appears to be highly sensitive to
changes in the environment. Immigrant populations assume the
incidence rates of the host country very rapidly, often within the
generation of the initial immigrant (Potter, 1999).
[0013] Risk factors for colon cancer include a positive family
history, meat consumption, smoking and alcohol consumption
(Giovannuci, 1999). There is an inverse relationship, i.e. lower
risk, associated with consumption of vegetables, high folate
intakes, use of non-steroidal anti-inflammatory drugs, hormone
replacement therapy and physical activity. Meat and tobacco smoke
are sources of carcinogens, while vegetables are a source of
folate, antioxidants, and have Phase II (detoxifying)
enzyme-inducing ability (Taningher, 1999).
[0014] Diets rich in raw vegetables, green vegetables, and
cruciferous vegetables have a decreased risk of colon cancer. Diets
high in fibre, from vegetables and cereals, have been associated
with a greater than two-fold decrease in risk of colorectal
adenomas in men. The data on fruit in the diet is not as consistent
to date (WCRF, 1997), but a recent report (Eberhart, 2000) measured
potent anti-oxidant activity of phytochemicals in apple skins with
the ability to inhibit growth of tumour cell lines in vitro, so it
is possible that more clearly defined links will emerge in the
future. Lower risk of colon cancer is associated with high folate
intakes, but actual consumption of vegetables, rather than specific
micronutrient preparations or vitamin supplements, has the most
consistent low risk (Potter, 1999).
[0015] Other cancers that have been correlated with nutrition
include prostate and breast. These malignancies are largely
influenced by a combination of factors related to diet and
nutrition. Prostate cancer is associated with high consumption of
milk, dairy products and meats. These products decrease levels of
1.25(OH)2 vitamin D, which is a cell differentiator. Low levels of
1.25(OH)2 vitamin D may enhance prostate carcinogenesis by
preventing cells from undergoing terminal differentiation and
continuing to proliferate (Giovannucci, 1999). Breast, colon, and
prostate cancers are relatively rare in less economically developed
countries, where malignancies of the upper gastrointestinal tract
are quite common. The cancers of the upper gastrointestinal tract
have been related to various food practices or preservation methods
other than refrigeration. For example, cancer of the mouth and
pharynx is the sixth most common cancer world-wide and has been
linked to alcohol consumption, tobacco, salt-preserved meat and
fish, smoked foods and charcoal-grilled meat, as well as ingestion
of beverages drunk very hot. Thus, diet can be a direct supply of
genotoxic compounds or may cause chronic irritation or inflammation
(Giovannucci, 1999).
[0016] In recent years, many genes involved in the processes
described above and other areas of metabolism have been found to
exist in allelic form. Therefore, certain populations,
subpopulations, races etc have greater or lesser susceptibility to
particular diseases linked with variation in alleles of some genes.
For many decades, health advice, for example relating to diet,
exercise, smoking, sunbathing has been issued by Governments,
charities and health advisory bodies, such advice has been directed
only at the population as a whole, or, at best, to groups such as
the elderly, children and pregnant women. Such advice can therefore
only be very general and cannot, by its very nature, take account
of the particular genotype of an individual. Moreover, in recent
years, there has been much media publicity of research findings on
links between particular foods, drugs etc and medical conditions,
often causing health scares. As the factors that contribute to
disease susceptibility, for example cancer, or cardiovascular
disease susceptibility vary between populations and between
individuals of populations, it is often impossible for an
individual to derive useful advice appropriate to his or her
particular circumstances from such reports.
SUMMARY OF THE INVENTION
[0017] In order to enable individuals to protect and manage their
own health, there is a need for individuals to have
personally-tailored information about risk factors which may be
important to that individual's well-being and personally-tailored
advice on reducing the risk of disease.
[0018] Accordingly, the invention provides a computer assisted
method of providing a personalized lifestyle advice plan for a
human subject comprising:
(i) providing a first dataset on a data processing means, said
first dataset comprising information correlating the presence of
individual alleles at genetic loci with a lifestyle risk factor,
wherein at least one allele of each genetic locus is known to be
associated with increased or decreased disease susceptibility; (ii)
providing a second dataset on a data processing means, said second
dataset comprising information matching each said risk factor with
at least one lifestyle recommendation; (iii) inputting a third
dataset identifying alleles at one or more of the genetic loci of
said first dataset of said human subject; (iv) determining the risk
factors associated with said alleles of said human subject using
said first dataset; (v) determining at least one appropriate
lifestyle recommendation based on each identified risk factor from
step (iv) using said second dataset; and (vi) generating a
personalized lifestyle advice plan based on said lifestyle
recommendations.
[0019] By lifestyle risk factors, it is meant risk factors
associated with dietary factors, exposure to environmental factors,
such as smoking, environmental chemicals or sunlight. Similarly
lifestyle recommendations should be interpreted as relating to
recommendations relating to dietary factors and exposure to
environmental factors, such as smoking, environmental chemicals or
sunlight. Disease susceptibility should be interpreted to include
susceptibility to conditions such as allergies.
[0020] Thus, the method allows individualised advice to be
generated based on the unique genetic profile of an individual and
the susceptibility to disease associated with the profile. By
individually assessing the genetic make-up of the client, specific
risk factors can be identified and dietary and other health advice
tailored to the individual's needs. In a preferred embodiment, the
lifestyle advice will include recommended minimum or maximum
amounts of foodtypes. (Note that an amount may be 0).
[0021] Information concerning the sex and health of the individual
and/or of the individual's family may also provide indications that
a particular polymorphism or group of polymorphisms associated with
a particular condition should be investigated. Such information may
therefore be used in selection of polymorphisms to be screened for
in the method of the invention.
[0022] Such factors may also be used in the determination of
appropriate lifestyle recommendations in step (v) of the method.
For example, recommendations relating to reducing susceptibility to
prostate cancer would not be given to women and recommendations
relating to susceptibility to ovarian cancer would not be given to
men. Other factors, such as information regarding the age, alcohol
consumption, and existing diet of the client may be incorporated
into the determination of appropriate lifestyle recommendations in
step (v).
[0023] The report comprising the personalised dietary advice may be
delivered to the client by any suitable means, for example by
letter, facsimile or electronic means, such as e-mail.
[0024] Alternatively, the report may be posted on a secure Web-page
of the service provider with access limited to the client by the
use of a unique identifier notified to the client either by
conventional or electronic mail. The report can therefore comprise
one or more hyperlinks to other documents of the report provider's
Web-site or to other Web-sites giving relevant information on the
particular polymorphisms identified, disease prevention and/or
dietary advice.
[0025] As such sites would be able to be updated and new hyperlinks
added to the report after the report is initially delivered to the
client, the information and advice would be able to be updated at
any time, thereby allowing the client to access up-to-date yet
personalised health and dietary advice over a prolonged period,
without the need for requesting another report.
[0026] Preferably, the method will involve assessing a variety of
loci in order to give a broad view of susceptibility and possible
means of minimising disease risk. Although individual polymorphisms
may be considered biomarkers for individual cancer risk, the
different biomarkers, when considered together, may also reveal a
significant cancer risk. For example, the correlation between
CYP1A1 activity and cancer susceptibility varies, dependent on the
presence of specific types of CYP1A1 polymorphism as well as the
presence of GSTM1 polymorphisms. An individual with an extremely
active CYP1A1 gene, leading to high Phase I P450 activity in
combination with a null GSTM1 genotype that lacks the detoxifying
Phase II activities has a very high risk of developing cancer
(Taningher, 1999).
[0027] The presence of a particular polymorphism may be indicative
of increased susceptibility to one disease while being indicative
of decreased susceptibility to another disease. For example, one
allele of the gene encoding epoxide hydrolase, which catalyses the
conversion of toxic PAH metabolites formed by CYP1A1 and CYP1A2
into less toxic and more water-soluble trans-dihydrodiols, has
recently been found to be associated with increased risk of
aflatoxin-induced liver cancer, but also with decreased risk of
ovarian cancer (Pluth, 200; Taningher, 1999).
[0028] Therefore, it will be important to assess the risk factors
associated with other polymorphisms to give meaningful advice on
maintaining optimal health.
[0029] Preferred genes for which polymorphisms are identified
include genes that encode Phase I metabolism enzymes responsible
for detoxification of xenobiotics, genes that encode Phase II
metabolism enzymes responsible for further detoxification and
excretion of xenobiotics, genes that encode enzymes that combat
oxidative stress, genes associated with micronutrient deficiency
(for example, deficiency of folate, B12 or B6), genes that encode
enzymes responsible for metabolism of alcohol, genes that encode
enzymes involved in lipid and/or cholesterol metabolism, genes that
encode enzymes involved in clotting, genes that encode trypsin
inhibitors, genes that encode enzymes related to susceptibility to
metal toxicity, genes which encode proteins required for normal
cellular metabolism and growth and genes which encoded HLA Class 2
molecules.
[0030] The method of the invention may include the step of
determining the presence of individual alleles at one or more
genetic loci of the DNA in a DNA sample of the subject, and
constructing the dataset used in step (iii) using results of that
determination.
[0031] Techniques for determining the presence or absence of
individual alleles are known to the skilled person. They may
include techniques such as hybridization with allele-specific
oligonucleotides (ASO) (Wallace, 1981; Ikuta, 1987; Nickerson,
1990, Varlaan-de Vries, 1986, Saiki, 1989 and Zhang, 1991) allele
specific PCR (Newton 1989, Gibbs, 1989), solid-phase minisequencing
(Syvanen, 1993), oligonucleotide ligation assay (OLA) (Wu, 1989,
Barany, 1991; Abravaya, 1995), 5' fluorogenic nuclease assay
(Holland, 1991 & 1992, Lee, 1998) U.S. Pat. Nos. 4,683,202,
4,683,195, 5,723,591 and 5,801,155, or Restriction fragment length
polymorphism (RFLP) (Donis-Keller, 1987).
[0032] In a preferred embodiment, the genetic loci are assessed via
a specialised type of PCR used to detect polymorphisms, commonly
referred to as the Taqman.RTM. assay, in which hybridisation of a
probe comprising a fluorescent reporter molecule, a fluorescent
quencher molecule and a minor groove binding chemical to a region
of interest is detected by removal of quenching of the fluorescent
molecule and detection of resultant fluorescence. Details are given
below.
[0033] In another embodiment, the genetic loci are assessed via
hybridisation with allele-specific oligonucleotides, the allele
specific oligonucleotides being preferably arranged as an array of
oligonucleotide spots stably associated with the surface of a solid
support.
[0034] The arrays suitable for use in the method of the invention
form a further aspect of the present invention.
[0035] In order to assay the sample for the alleles to be
identified the fragments of DNA comprising the gene(s) of interest
may be amplified to produce a sufficient amount of material to be
tested.
[0036] The present inventors have designed a number of specific
primer sets for amplification of gene regions of interest. Such
primers may be used in pairs to isolate a particular region of
interest in isolation. Therefore in a further aspect of the
invention, there is provided a primer having a sequence selected
from SEQ ID NO: 86-99, 104-163. In another aspect, there is
provided a primer pair comprising primers having SEQ ID NO:n, where
n is an even number from 86-98 or 104-162 in conjunction with a
primer having SEQ ID NO: (n+1).
[0037] Preferably, however, the primer sets will be used together
with other primer sets to provide multiplexed amplification of a
number of regions to allow determination of a number of
polymorphisms from the same sample. Therefore in a further aspect
of the invention, there is provided a primer set comprising at
least 5, more preferably 10, 15 primer pairs selected from SEQ ID
NO: 86-121.
BRIEF DESCRIPTION OF THE DRAWINGS
[0038] FIG. 1A and FIG. 1B show examples of databases 1 and 2 which
may be used in an embodiment of the present invention.
[0039] FIG. 2 is a flow chart illustrating an embodiment of the
invention.
DETAILED DESCRIPTION OF THE INVENTION
Selection of Genetic Polymorphisms for Datasets
[0040] The correct selection of genetic polymorphisms is important
to the provision of accurate and meaningful advice. Although not
limited to such classes of polymorphisms, in a preferred embodiment
of the present invention, markers for polymorphisms of one or more
of the following classes of genes are used:
[0041] The first dataset of the method of the invention may
comprise information relating to two or more alleles of one or more
genetic loci of genes selected from the group comprising:
(a) genes that encode enzymes responsible for detoxification of
xenobiotics in Phase I metabolism; (b) genes that encode enzymes
responsible for conjugation reactions in Phase II metabolism; (c)
genes that encode enzymes that help cells to combat oxidative
stress; (d) genes associated with micronutrient deficiency; (e)
genes that encode enzymes responsible for metabolism of alcohol.
(f) genes that encode enzymes involved in lipid and/or cholesterol
metabolism; (g) genes that encode enzymes involved in clotting; (h)
genes that encode trypsin inhibitors; (i) genes that encode enzymes
related to susceptibility to metal toxicity; (j) genes which encode
proteins required for normal cellular metabolism and growth; (k)
genes which encoded HLA Class 2 molecules.
[0042] The dataset will preferably comprise information relating to
two or more alleles of at least two genetic loci of genes selected
from the group comprising categories a-k as described above, for
example, a+b, a+c, a+d, a+e, a+f, a+g, a+h, a+i, a+j, a+k, b+c,
b+d, b+e etc., c+d, c+e etc, d+e, d+f etc, e+f, e+g etc, f+g, f+h
etc., g+h, g+i, g+k, h+i, h+k. Where the dataset comprises
information relating to two or more alleles of at least two genetic
loci, it is preferred that at least one of the genetic loci is of
category d, due to the central role of micronutrients in the
maintenance of proper cellular growth and DNA repair, and due to
the association of micronutrient metabolism or utilisation
disorders with several different types of diseases (Ames 1999;
Perera, 2000; Potter, 2000). More preferably, the dataset will
preferably comprise information relating to two or more alleles of
at least three genetic loci selected from the group comprising
categories a-k as described above. Where the dataset comprises
information relating to alleles of at least three genetic loci, it
is preferred that at least two of the genetic loci are of
categories d and e. Information relating to polymorphisms present
in both of these categories is particularly useful due to the
effects of alcohol consumption and metabolism on the efficiency of
enzymes related to micronutrient metabolism and utilisation
(Ulrich, 1999). In a further preferred embodiment, where the
dataset comprises information relating to alleles of at least three
genetic loci, it is preferred that at least two of the genetic loci
are of categories a and b due to the close interaction of Phase I
and Phase II enzymes in the metabolism of xenobiotics. Even more
preferably, the dataset will comprise information relating to two
or more alleles of at least four genetic loci of genes selected
from the group comprising categories a-k as defined above, for
example, a+b+c+d, a+b+c+e, a+b+d+e, a+c+d+e, b+c+d+e etc. Where the
dataset comprises information relating to alleles of at least four
genetic loci, it is preferred that at least three of the genetic
loci are of categories d and e and f Information relating to
polymorphisms present in these three categories is particularly
useful due to the strong correlation of polymorphisms of these
alleles with coronary artery disease due to the combined effects of
altered micronutrient utilisation, affected adversely by alcohol
metabolism, together with imbalances in fat and cholesterol
metabolism. Further, where the dataset comprises information
relating to alleles of at least five genetic loci, it is preferred
that at least four of the genetic loci are of categories a, b, d
and e. Information relating to polymorphisms present in these four
categories is particularly useful due to the combined effects of
micronutrients utilisation, alcohol metabolism, Phase 1 metabolism
of xenobiotics and Phase II metabolism on the further metabolism
and excretion of potentially harmful metabolites produced in the
body (Taningher, 1999; Ulrich, 1999). Similarly, the dataset may
comprise information relating to two or more alleles of at least
five, for example a, b, d, e and f, six, seven, eight, nine or ten
genetic loci of genes selected from the group comprising categories
a-k as defined above.
[0043] Preferably, the dataset will comprise information relating
to two or more alleles of one or more genetic loci of genes
selected from each member of the group comprising categories a-k as
described above. In a preferred embodiment, the first dataset
comprises information relating to two or more alleles of the
genetic loci of genes encoding each of the cytochrome P450
monooxygenase, N-acetyltransferase 1, N-acetyltransferase 2,
glutathione-S-transferase, manganese superoxide dismutase,
5,10-methylenetetrahydrofolatereductase and alcohol dehydrogenase 2
enzymes. In a more preferred embodiment the first dataset further
comprises information relating to two or more alleles of the
genetic loci of genes encoding one or more, preferably each of
epoxide hydrolase (EH), NADPH-quinone reductase (NQ01),
paraxonaoase (PON1), myeloperoxidase (MPO), alcohol dehydrogenase
1, alcohol dehydrogenase 3, cholesteryl ester transfer protein,
apolipoprotein A IV, apolipoprotein E, apolipoprotein C III,
angiotensin, factor VII, prothrombin 20210, .beta.-fibrinogen,
heme-oxygenase-1, .alpha.-antitrypsin, SPINK1,
.DELTA.-aminolevulinacid dehydratase, interleukin 1, interleukin 1,
vitamin D receptor, B1 kinin receptor, cystathionine-beta-synthase,
methionine synthase (B12 MS), 5-HT transporter, transforming growth
factor beta 1 (TGF.beta.1), L-myc, HLA Class 2 molecules,
T-lymphocyte associated antigen 4 (CTLA-4), interleukin 4,
interleukin 3, interleukin 6, IgA, and/or galactose metabolism gene
GALT.
[0044] Genes that Encode Enzymes Responsible for (a) Detoxification
of Xenobiotics in Phase I Metabolism; and (b) Conjugation Reactions
in Phase II Metabolism
[0045] Xenobiotics are potentially toxic compounds found in, for
example, char-grilled red meat. Meat consumption is associated with
increased risk of cancer, especially well-done meat cooked at high
temperatures (Sinha, 1999). Cooking meat in this fashion leads to
the production of heterocyclic amines (HCA), nitrosamines (NA), and
polycyclic aromatic hydrocarbons (PAH), which have known
carcinogenic activity in animals (Hirvonen, 1999; Layton,
1995).
[0046] Detoxification of xenobiotics occurs in 2 phases in humans:
Phase I metabolism involves the addition of an oxygen atom or a
nitrogen atom to lipophilic (fat soluble) compounds, such as
steroids, fatty acids, xenobiotics (from external sources like
diet, smoke, etc.) so that they can be conjugated by the Phase II
enzymes (thus made water-soluble) and excreted from the body
(Hirvonen, 1999). Individuals with genetic polymorphisms correlated
with cancer risk in these genes should avoid consumption of
char-grilled foods, smoked fish, well-done red meat whether grilled
or pan-fried (Sinha, 1999). They should also increase consumption
of food products known to increase Phase II metabolism so the
products of Phase I metabolism may be cleared more efficiently.
[0047] Specific examples of genes of category a for which
information relating to polymorphisms may be used in the present
invention include genes encoding cytochrome P450 monooxygenase
(CYP) e.g. CYP1A1, CYA1A2, CYP2C, CYP2D6, CYP2E1, CYP3A4, CYP11B2,
genes encoding N-acetyltransferase 1 e.g. NAT1, genes encoding
N-acetyltransferase 2 e.g. NAT2, genes encoding epoxide hydrolase
(EH), genes encoding NADPH-quinone reductase (NQ01, genes encoding
paraxonaoase (PON1), genes encoding myeloperoxidase (MPO).
[0048] CYP is also referred to as cytochromome P450 monooxygenase
(gene is called CYP, enzyme is called P450). P450 enzymes belong to
a super-family with wide substrate activity that catalyses the
insertion of an oxygen atom into a substrate. The reaction can
convert a molecule (procarcinogen) into a DNA-reactive
electrophilic carcinogen (Hirvonen, 1999; Smith, 1995).
Polymorphisms in genes encoding cytochrome P450 (CYP family of
genes) are associated with altered susceptibility to cancer, CAD
and altered metabolisim of various pharmaceutical agents (Poolsup,
2000; Miki, 1999; Cramer,2000; Marchand, 1999; Sinha, 1997).
[0049] CYP1A1 codes for a P450 enzyme that metabolises polycyclic
aromatic hydrocarbons (PAH). The CYP1A1 gene is polymorphic and is
inducible by PAH, which means that expression of the enzyme is
increased upon exposure to PAH (MacLeod, 1997). CYP1A1 is located
on chromosome 15q22-q24 (Smith, 1995). This gene has been linked to
colorectal, urinary bladder, breast, oral cavity, stomach, and lung
cancers (Perera, 2000; Garte, 1998). The gene product, the P450
enzyme, is inducible by exposure to the agents that it metabolises,
so the consumption of high levels of a potential source of
carcinogens, such as well-done red meat, would increase the
production of the enzyme and thus the creation of carcinogenic
substances (Mooney, 1996; Perera, 2000; Alexandrie, A. K., 2000).
Studies of polymorphisms of the CYP1A1 gene have revealed
considerable differences in enzyme activity, with corresponding
differences in cancer risk after exposure to known substrates of
the enzyme (Alexandrie, 2000; Rojas, 2000; Garte, 2000). Both the
Ile-Val polymorphism I, which comprises an A4889G substitution
(i.e. the adenine residue at position 4889 of the 5'-3' strand is
substituted by a guanine residue) and the CYP1A1*C polymorphism,
which comprises an T6235C substitution, are induced to a greater
extent than the wild type gene after exposure to PAH, and have been
associated with a significant increase in cancer risk (Taningher,
1999; Garte, 1998; Kawajiri, 1996; MacLeod, S., 1997; Smith, 1995).
Approximately 10 percent of the Caucasian population carries
polymorphisms linked to cancer risk, according to a recent American
review paper (Shields, 2000). Polymorphisms in genes encoding
CYP1A2, CYP2C, CYP2D6, CYP2E1, CYP3A4, CYP11B2 are associated with
altered susceptibility to cancer and drug sensitivity. (Poolsup,
2000; Miki, 1999; Cramer,2000; Marchand, 1999; Sinha, 1997).
[0050] NAT1 (N-acetyltransferase 1) and NAT2 (N-acetyltransferase
2) also activate PAH and heterocyclic amines (HAA). The enzymes
catalyse N-acetylation, O-acetylation, and N,O-acetylation. The
O-acetylation reaction is considered the most risky, with the
potential for forming chemical carcinogens that can bind to DNA.
The N-acetylation reaction can occur on a compound after a P450 has
inserted an oxygen, thus increasing the water solubility of the
compound so it may be excreted. Due to this activity, the NAT genes
are often considered as both Phase I and Phase II type enzymes. The
literature describing a cancer link focuses on the activation
activity of the enzymes, so they will be listed in the Phase I
section only. There are 3 separate N-acetyltransferase genes in
humans, two are active genes: NAT1 and NAT2, and a pseudogene,
NATP. Pseudogenes have the same sequence, but lack apparent
function and promoter elements and are not expressed in cells (i.e.
the gene is not transcribed into RNA then translated into amino
acids to make a protein/enzyme) (Perera, 2000). NAT1 and NAT2 genes
are located on chromosome 8 at 8p21.3-21.1, both genes are 870 bp
long and both code for a protein 290 amino acids in length. The
genes are highly polymorphic and epidemiological studies have
sometimes given conflicting information regarding links with
cancer. The genes show geographical and ethnic variation and the
enzyme activity varies considerably within different tissues or
organs. There are approximately 20 polymorphisms for NAT1 known to
date, but the list below only includes the polymorphisms that have
shown a link to cancer (Hein, 2000a). The current list of
nomenclature and polymorphisms is kept at a web site:
http://louisville.edu/medschool/pharmacology/NAT.html. Many of the
epidemiological studies of both NAT1 and NAT2 used phenotyping
assays, which measured enzyme activity, and found fast and slow
acetylator types, with the fast phenotype carrying an increased
risk for cancer in the colon (Perera, 2000). However, later
analysis of the results found that the fast/slow phenotype could
vary considerably depending on the substrate chosen for acetylation
(Hein, 2000a). Recent studies have used genetic sequence data to
more precisely match acetylator activity and cancer risk with
polymorphism (Hein, 2000b). Although the genes are the same size,
they do act on different substrates. For example, caffeine is a
substrate for NAT2 but not for NAT1.
[0051] NAT1 is expressed to a higher degree than NAT2 in the colon,
so NAT1 may be associated with localised activity of activated HAA
or PAH in the colon (Brockton, 2000; Perera, 2000). The
polymorphism NAT1*10, which comprises T1088A and C1095A
substitutions, and which has a fast phenotype, has been
consistently linked with an increased risk of colon cancer and
higher DNA adduct levels (i.e. DNA damage that can lead to cancer)
in colon tissue (Perera, 2000; Ilett, 1987). The NAT1*11
polymorphism has been linked to risk of breast cancer in women who
smoke or consume well-done red meat (Zheng, 1999). However, the
phenotype is not well understood, so this marker cannot be
categorized as a fast or slow acetylator (Doll, 1997). Two alleles
of the NAT1*11 polymorphism are known: the NAT1*11A polymorphism,
which comprises C(-344)T, A(-40)T, G445A, G459A, T640G, C1095A
substitutions and a .DELTA.9:1065-1090 deletion; and the NAT1*11B
polymorphism, which comprises C(-344)T, A(-40)T, G445A, G459A,
T640G substitutions and a .DELTA.9:1065-1090 deletion. References
to NAT1*11 polymorphisms should be understood to include reference
to NAT1*11A or NAT1*11B polymorphisms.
[0052] NAT1*14 on the other hand has little or no enzyme activity
(Brockton, 2000) and has been associated with increased lung cancer
risk (Bouchardy, C., 1998). Two alleles of the NAT1*14 polymorphism
are known: the NAT1*14A polymorphism, which comprises G560A, T1088A
and C1095A substitutions; and the NAT1*14B polymorphism, which
comprises a G560A substitution. References to NAT1*14 polymorphisms
should, except where the context dictates otherwise, be understood
to include reference to NAT1*14A or NAT1*14B polymorphisms. The
NAT1*14 polymorphism shares a restriction enzyme site with the
NAT1*11polymorphism, and some of the conflicting results reported
in the literature are believed to be due to the inability of the
assay used (restriction fragment length polymorphism assay (RFLP))
to distinguish the polymorphisms (Hein, 2000a). The oligonucleotide
array suitable for use in the present invention can distinguish all
polymorphisms and therefore will be more precise than the RFLP
procedure.
[0053] NAT2 is expressed primarily in the liver, but has been
linked with cancer incidence in other organs (Hein, 2000b).
[0054] NAT2*5A, which comprises T481C and T341C substitutions,
NAT2*6A, which comprises C282T and G590A substitutions, NAT2*7A,
which comprises a G857A substitution, have reduced acetylation
activity (Hein, 2000b) and have been linked to risk of bladder
cancer (Taningher, 1999; Lee, 1998). NAT2*4, is considered the
normal, or wild type, sequence. NAT2*4 has fast acetylator activity
and has been linked to increased cancer risk in several studies
(reviewed in Hein, 2000b; Gil, 1998), but especially in conjunction
with the NAT1*10 polymorphism (Bell, 1995). NAT2 rapid/intermediate
acetylators with at least one NAT2*4 allele have been linked to
breast cancer in women who consumed well-done red meat (Dietz,
1999). Approximately 55% of the Caucasian population carry NAT1
polymorphisms linked to cancer. (Shields, 2000).
[0055] Polymorphisms in genes encoding epoxide hydrolase are
associated with cancer and chronic obstructive pulmonary disease
(Pluth, 200; Miki,1999). Polymorphisms in genes encoding
NADPH-quinone reductase are associated with altered susceptibility
to cancer (Nakajima, 2000). Polymorphisms in genes encoding
paraxonoase are associated with altered susceptibility to cancer
and to CAD (MacKness, 2000). Polymorphisms in genes encoding
myeloperoxidase are associated with altered susceptibility to CAD
(Schabath, 2000).
[0056] Specific examples of genes of category b for which
information relating to polymorphisms may be used in the present
invention include genes encoding glutathione-S-transferase e.g
GSTM1, GSTP1, GSTT1.
[0057] Glutathione-S-transferases catalyse the reaction of
electrophilic compounds with glutathione so the compounds may be
excreted from the body. The enzymes belong to a super-family with
broad and overlapping substrate specificities.
Glutatione-S-transferases provide a major pathway of protection
against chemical toxins and carcinogens and are thought to have
evolved as an adaptive response to environmental insult, thus
accounting for their wide substrate specificity (Hirvonen, 1999).
There are 4 family members: alpha, mu, theta, and pi, also
designated as A, M, T and P. Polymorphisms have been identified in
each family (Perera, 2000). Individuals with low
glutathione-S-transferase activity should avoid meats cooked at
higher temperatures as above, and increase fruit and vegetable
consumption. Cruciferous vegetables such as broccoli and members of
the allium family such as garlic and onion have been shown to be
potent inducers of these enzymes, which would be expected to
increase clearance of toxic substances from the body (Cotton, 2000;
Giovannucci, 1999).
[0058] GSTmu, has 3 alleles: null, a, which is considered to be the
wild type, and b, which comprises a C534G substitution, with no
functional difference between the a and b alleles. The GSTmu
sub-type has the highest activity of the 4 types and is
predominately located in the liver (Hirvonen, 1999). Approximately
half of the population has a complete deletion of this gene with a
corresponding risk of lung, bladder, breast, liver, and oral cavity
cancer (Shields, 2000; Perera, 2000). It has been estimated that
17% of all lung and bladder cancers may be attributable to GSTM1
null genotypes (Hirvonen, 1999). GSTM1 null genotype together with
a highly active CYP1A1 polymorphism has been linked to a very high
cancer risk in several studies (Rojas, 2000; Shields, 2000). The
GSTM1 gene is located on chromosome 1p13.3 (Cotton, 2000).
[0059] GSTpi gene is located on chromosome 11q13. This sub-type is
known to metabolise many carcinogenic compounds and is the most
abundant sub-type in the lungs (Hirvonen, 1999). Two single
nucleotide polymorphisms have been linked to cancer to date
GSTP1*B, which comprises an A313G substitution, and GSTP1*C, which
comprises a C341T substitution. The enzymes of these polymorphic
genes have decreased activity compared to the wild type and a
corresponding increased risk of bladder, testicular, larynx and
lung cancer (Harries, 1997; Matthias, 1998; Ryberg, 1997).
[0060] GSTtheta gene is on chromosome 22q11.2 and is deleted in
approximately 20% of the Caucasian population. The enzyme is found
in a variety of tissues, including red blood cells, liver, and lung
(Potter, 1999). The deletion is associated with an increased risk
of lung, larynx and bladder cancers (Hirvonen, 1999). Links with
GSTM1 null genotypes are currently being searched, as it is
believed that individuals that have both GSTM1 and GSTT1 alleles
deleted will have a greatly increased risk of developing cancer
(Potter, 1999).
[0061] Genes that Code for Enzymes that Help Cells to Combat
Oxidative Stress
[0062] Specific examples of genes of category c for which
information relating to polymorphisms may be used in the present
invention include genes encoding manganese superoxide dismutase
(MnSOD or SOD2 gene).
[0063] Manganese superoxide dismutase is an enzyme that destroys
free radicals or a free-radical scavenger. The gene is located on
chromosome 6q25.3, but the enzyme is found within the mitochondria
of cells. There are 2 polymorphisms linked to cancer to date, an
Ile 58Thr allele, which comprises an T175C substitution, and a
Val(-9)Ala allele, which comprises a T(-28)C substitution. A study
of premenopausal women found a four-fold increased risk of breast
cancer in individuals with the Val(-9)Ala polymorphism and the
highest risk within this group is found in women who consumed low
amounts of fruits and vegetables (Ambrosone, 1999). This
polymorphism occurs in the signal sequence of the amino acid chain.
The signal sequence ensures transport of the enzyme into the
mitochondria of the cell, and so the polymorphism is believed to
reduce the amount of enzyme delivered to the mitochondria
(Ambrosone, 1999). The mitochondria is commonly referred to as the
workhorse of the cell, where the energy-yielding reactions take
place. This is the site of many oxidative reactions, so many free
radicals are generated here. Individuals with low activity of this
enzyme should be advised to take antioxidant supplements and
increase consumption of fruits and vegetables (Giovannucci, 1999;
Perera, 2000).
Genes Associated with Micronutrient Deficiency e.g. of Folate,
Vitamin 812 or Vitamin B6
[0064] Specific examples of genes of category d for which
information relating to polymorphisms may be used in the present
invention include the gene encoding
5,10-methylenetetrahydrofolatereductase (MTHFR) activity.
[0065] 5,10-methylenetetrahydrofolate reductase is active in the
folate-dependent methylation of DNA precursors. Low activity of
this enzyme leads to an increase of uracil incorporation into DNA
(instead of thymine) (Ames, 1999). The MTHFR gene is polymorphic
and has been linked to colon cancer, adult acute lymphocytic
leukaemia and infant leukaemia (Ames, 1999; Perera, 2000; Potter,
2000). Both the wt and polymorphic alleles have been linked to
disease, each being dependent on levels of folate in the diet.
Approximately 35% of the Caucasian population has genetic
polymorphisms at this locus with corresponding risk of colon cancer
(Shields, 2000). Polymorphisms at this locus include those with a
C677T or A1298C substitution. Dietary recommendations for
individuals lacking in MTHFR activity include taking supplements
with folate and increasing consumption of fruit and vegetables
(Ames, 1999). Low levels of vitamins B12 and B6 have been
associated with low MTHFR activity and increased cancer risk, so
individuals should increase intake of these vitamins; B12 is found
primarily in meat and B6 is found in whole grains, cereals,
bananas, and liver (Ames, 1999). Alcohol has a deleterious effect
on folate metabolism, affecting individuals with the A1298C
polymorphism most severely (Ulrich, 1999). These individuals should
be advised to avoid alcohol.
[0066] Genes that Code for Enzymes Responsible for Metabolism of
Alcohol
[0067] Specific examples of genes of category e for which
information relating to polymorphisms may be used in the present
invention include genes encoding alcohol dehydrogenase e.g. the
ALDH2 gene, ALDH1 gene and ALDB3 gene.
[0068] Alcohol dehydrogenase 2 (ALDH2) is involved in the second
step of ethanol utilisation. Reduced activity of this enzyme leads
to accumulation of acetaldehyde, a potent DNA adduct former
(Bosron, 1986). There has been one polymorphism identified to date,
the ALDH2*2 polymorphism, which comprises a G1156A substitution,
and which has links with oesophageal/throat cancer, stomach, lung,
and colon cancer (IARC, 1998; Yokoyama, 1998). The advice to
individuals with the polymorphism would be to avoid alcohol.
Polymorphisms in ALDH1 and 3 are associated with increased
susceptibility to cancers and Parkinson's disease.
[0069] Genes that Encode Enzymes Involved in Lipid and/or
Cholesterol Metabolism
[0070] Specific examples of genes of category f for which
information relating to polymorphisms may be used in the present
invention include genes encoding cholesteryl ester transfer protein
e.g. the CETP gene, polymorphisms of which genes are associated
with altered susceptibility to coronary artery disease (CAD)
((Raknew, 2000; Ordovas, 2000); genes encoding apolipoprotein A, IV
(ApoA-IV), polymorphisms of which genes are associated with altered
susceptibility to coronary artery disease (CAD) (Wallace,2000;
Heilbronn, 2000); apolipoprotein E(ApoE), polymorphisms of which
genes are associated with altered susceptibility to CAD and
Alzheimer's disease (Corbo,1999; Bullido, 2000); or apolipoprotein
C, III (ApoC-III), polymorphisms of which genes are associated with
altered susceptibility to CAD, hypertension and insulin resistance
(Salas, 1998).
[0071] Genes that Encode Enzymes Involved in Clotting
Mechanisms
[0072] Specific examples of genes of category g for which
information relating to polymorphisms may be used in the present
invention include genes encoding angiotensin (AGT-1) and
angiotensin converting enzyme (ACE), polymorphisms of which genes
are associated with altered susceptibility to hypertension (Brand
2000; de Padua Mansur, 2000), factor VII, polymorphisms of which
genes are associated with altered susceptibility to CAD (Donati,
2000; Di Castelnuovo, 2000); prothrombin 20210, polymorphisms of
which genes are associated with altered susceptibility to venous
thrombosis (Vicente, 1999); .beta.-fibrinogen, polymorphisms of
which genes are associated with altered susceptibility to CAD
(Humphries, 1999); or heme-oxygenase-1, polymorphisms of which
genes are associated with altered susceptibility to emphysema
(Yamada, 2000).
Genes that Encode Trypsin Inhibitors
[0073] Specific examples of genes of category h for which
information relating to polymorphisms may be used in the present
invention include genes encoding .alpha.-antitrypsin, polymorphisms
of which genes are associated with altered susceptibility to
chronic obstructive pulmonary disease (COPD) (Miki, 1999); or
serine protease inhibitor, Kazal type 1(SPINK), polymorphisms of
which genes are associated with altered susceptibility to
pancreatitis (Pfutzer, 2000).
Genes that Encode Enzymes Related to Susceptibility to Metal
Toxicity
[0074] Specific examples of genes of category i for which
information relating to polymorphisms may be used in the present
invention include genes encoding .DELTA.-aminolevulinacid
dehydratase, polymorphisms of which genes are associated with
altered susceptibility to lead toxicity (Costa, 2000).
Genes which Encode Proteins Required for Normal Cellular Metabolism
and Growth
[0075] Specific examples of genes of category j for which
information relating to polymorphisms may be used in the present
invention include genes encoding the vitamin D receptor,
polymorphisms of which genes are associated with altered
susceptibility to osteoporosis, tuberculosis, Graves disease, COPD,
and early periodontal disease (Ban, 2000; Wilkinson, 2000; Gelder,
2000; Miki, 1999; Hennig, 1999); the B1 kinin receptor (B1R),
polymorphisms of which genes are associated with altered
susceptibility to kidney disease (Zychma, 1999);
cystathionine-beta-synthase, polymorphisms of which genes are
associated with altered susceptibility to CAD (Tsai, 1999);
methionine synthase (B12 MS), polymorphisms of which genes are
associated with altered susceptibility to CAD (Tsai, 1999); the
5-HT transporter, polymorphisms of which genes are associated with
altered susceptibility to neurological disorders, Alzheimer's
disease, schizophrenia, other disorders of the serotonin pathway
(Oliveira, 1999); tumour necrosis factor receptor 2 (TNFR2),
polymorphisms of which genes are associated with altered
susceptibility to CAD (Fernandez-Real, 2000); galactose metabolism
gene GALT, polymorphisms of which genes are associated with altered
susceptibility to ovarian cancer (Cramer, 2000); transforming
growth factor beta 1 (TGF.beta.1), polymorphisms of which genes are
associated with altered susceptibility to CAD and cancers (Yokota,
2000); and L-myc, polymorphisms of which genes are associated with
altered susceptibility to CAD (especially in relation to tolerance
to smoking) and cancers (Togo, 2000).
Genes which Encoded Proteins Associate with Immunological
Susceptibility
[0076] Specific examples of genes of category k for which
information relating to polymorphisms may be used in the present
invention include genes encoding HLA Class 2 molecules,
polymorphisms of which genes are associated with altered
susceptibility to cervical cancer and human papilloma virus (HPV)
infection (Maciag, 2000); T-lymphocyte associated antigen 4
(CTLA-4), polymorphisms of which genes are associated with altered
susceptibility to liver disease (Argawal, 2000); interleukin 1
(IL-1), polymorphisms of which are associated with cardiovascular
disease and periodontal disease (macaiag, 2000; Nakajima, 2000);
IL-4, polymorphisms of which genes are associated with altered
susceptibility to atopy and asthma (Rosa-Rosa, 1999); IL-3,
polymorphisms of which genes are associated with altered
susceptibility to atopy and asthma (Rosa-Rosa, 1999); IL-6,
polymorphisms of which genes are associated with altered
susceptibility to osteoporosis; and IgA, polymorphisms of which
genes are associated with altered susceptibility to COPD (Miki,
1999).
Detection of Polymorphisms
[0077] As described above, the method of the invention may include
the step of analysing a DNA sample of a human subject in order to
construct the dataset to be used in the method of the
invention.
Testing of Samples
Collection of Tissue Samples
[0078] DNA for analysis using the method or arrays of the invention
can be isolated from any suitable client or patient cell sample.
For convenience, it is preferred that the DNA is isolated from
cheek (buccal) cells. This enables easy and painless collection of
cells by the client, with the convenience of being able to post the
sample to the provider of the genetic test without the problems
associated with posting a liquid sample.
[0079] Cells may be isolated from the inside of the mouth using a
disposable scraping device with a plastic or paper matrix "brush",
for example, the C.E.P. Swab.TM. (Life Technologies Ltd., UK).
Cells are deposited onto the matrix upon gentle abrasion of the
inner cheek, resulting in the collection of approximately 2000
cells (Aron, 1994). The paper brush can then be left to dry
completely, ejected from the handle placed into a microcentrifuge
tube and posted by the client or patient to the provider of the
genetic test.
Isolation of DNA from Samples
[0080] DNA from the cell samples can be isolated using conventional
procedures. For example DNA may be immobilised onto filters, column
matrices, or magnetic beads. Numerous commercial kits, such as the
Qiagen QIAamp kit (Quiagen, Crawley, UK) may be used. Briefly, the
cell sample may be placed in a microcentrifuge tube and combined
with Proteinase K, mixed, and allowed to incubate to lyse the
cells. Ethanol is then added and the lysate is transferred to a
QIAamp spin column from which DNA is eluted after several
washings.
[0081] The amount of DNA isolated by the particular method used may
be quantified to ensure that sufficient DNA is available for the
assay and to determine the dilution required to achieve the desired
concentration of DNA for PCR amplification. For example, the
desired target DNA concentration may be in the range 10 ng and 50
ng. DNA concentrations outside this range may impact the PCR
amplification of the individual alleles and thus impact the
sensitivity and selectivity of the polymorphism determination
step.
[0082] The quantity of DNA obtained from a sample may be determined
using any suitable technique. Such techniques are well known to
persons skilled in the art and include UV (Maniatis, 1982) or
fluorescence based methods. As UV methods may suffer from the
interfering absorbance caused by contaminating molecules such as
nucleotides, RNA, EDTA and phenol and the dynamic range and
sensitivity of this technique is not as great as that of
fluorescent methods, fluorescence methods are preferred.
Commercially available fluorescence based kits such as the
PicoGreen dsDNA Quantification (Molecular Probes, Eugene, Oreg.,
USA).
Primers
[0083] Prior to the testing of a sample, the nucleic acids in the
sample may be selectively amplified, for example using Polymerase
Chain Reaction (PCR) amplification, as described in U.S. Pat. Nos.
4,683,202 AND 4,683,195.
[0084] Preferred primers for use in the present invention are from
18 to 23 nucleotides in length, without internal homology or
primer-primer homology.
[0085] Furthermore, to ensure amplification of the region of
interest and specificity, the two primers of a pair are preferably
selected to hybridise to either side of the region of interest so
that about 150 bases in length are amplified, although
amplification of shorter and longer fragments may also be used.
Ideally, the site of polymorphism should be at or near the centre
of the region amplified.
[0086] Table 1 provides preferred examples of primer pairs which
may be used in the invention, particularly when the Taqman.RTM.
assay is used in the method of the invention. The primers are shown
together with the gene targets and preferred examples of the wt
probes and polymorphism probes used in the Taqman.RTM. assay for
each gene target.
[0087] Table 2 provides preferred examples of the primer pairs
which may be used in the invention together with the gene targets
and the size of the fragment isolated using the primers, which they
amplify.
[0088] The primers and primer pairs form a further aspect of the
invention. Therefore the invention provides a primer having a
sequence selected from SEQ ID NO: 86-99, 104-163. In another
aspect, there is provided a primer pair comprising primers having
SEQ ID NO:n, where n is an even number from 86-98 or 104-162 in
conjunction with a primer having SEQ ID NO: (n+1).
[0089] In a preferred embodiment of the invention, multiplexed
amplification of a number of sequences are envisioned in order to
allow determination of the presence of a plurality of polymorphisms
using, for example the DNA array method. Therefore, primer pairs to
be used in the same reaction are preferably selected by position,
similarity of melting temperature, internal stability, absence of
internal homology or homology to each other to prevent
self-hybridisation or hybridisation with other primers and lack of
propensity of each primer to form a stable hairpin loop structure.
Thus, the sets of primer pairs to be coamplified together
preferably have approximately the same thermal profile, so that
they can be effectively coamplified together. This may be achieved
by having groups of primer pairs with approximately the same length
and the same G/C content.
[0090] Therefore in a further aspect of the invention, there is
provided a primer set comprising at least 5, more preferably 10, 15
primer pairs selected from SEQ ID NO: 86-121.
TABLE-US-00001 TABLE 1 Forward Reverse Polymorphhism Gene primer
primer WT Probe probe 1. CYP1A1 A4889G CATGGGCAAGCGGAAG
CAGGATAGCCAGGAA CGGTGAGACCaTTG CGGTGAGACCgTTG TG GAGAAAGAC (SEQ ID
NO: 164) (SEQ ID NO: 165) (SEQ ID NO: 122) (SEQ ID NO: 123) T6235C
AGACAGGGTCCCCAGG CAGAGGCTGAGGTGG CTCCACCTCCtGGG CTCCACCTCCcGGG TCAT
GAGAA (SEQ ID NO: 166) (SEQ ID NO: 167) (SEQ ID NO: 124) (SEQ ID
NO: 125) 2. NAT1 G445A GGAGTTAATTTCTGGG TGGTCTAGATACCAG
GCCTTGTgTCTTC TGCCTTGTaTCTTC AAGGATCAG AATCCATTCTCTT (SEQ. ID NO:
168) (SEQ ID NO: 169) (SEQ ID NO: 126) (SEQ ID NO: 127) G459A
GGCAGCCTCTGGAGTT TTCCCTTCTGATTTG CGTTTGACgGAAGAG CGTTTGACaGAAGAG
AATTTCT GTCTAGATACC (SEQ ID NO: 170) (SEQ ID NO: 171) (SEQ ID NO:
128) (SEQ ID NO: 129) G560A GGGAACAGTACATTCC TGTTCGAGGCTTAAG
AATACCgAAAAATC CAAATACCaAAAAAT AAATGAAGA AGTAAAGGAGT (SEQ ID NO:
172) (SEQ ID NO: 173) (SEQ ID NO: 130) (SEQ ID NO: 131) T640G
AACAATTGAAGATTTT TCTGCAAGGAACAAA CATCTCCAtCATCTG ACATCTCCAgCATCT
GAGTCTATGAATACA ATGATTTACTAGT (SEQ ID NO: 174) (SEQ ID NO: 175)
(SEQ ID NO: 132) (SEQ ID NO: 133) T1088A GAAACATAACCACAAA
AAATCACCAATTTCC CCATCTTTAAAATACA CATCTTTAAAATACA CCTTTTCAAA
AAGATAACCA TTTaTTA TTTtTTA (SEQ ID NO: 134) (SEQ ID NO: 135) (SEQ
ID NO: 203) (SEQ ID NO: 204) C1095A AAACATAACCACAAAC
AAATCACCAATTTCC GCCATCTTTAAAAgAC GCCATCTTTAAAAtA CTTTTCAAATAAT
AAGATAACCA AT CATT (SEQ ID NO: 136) (SEQ ID NO: 137) (SEQ ID NO:
178) (SEQ ID NO: 177) 3. A30NAT2 C > T AATCAACTTCTGTACT
CCATGCCAGTGCTGT AGGGTATTTTTAcATC AGGGTATTTTTAtAT GGGCTCTGA ATTTGTT
CCT CCCTC (SEQ ID NO: 138) (SEQ ID NO: 139) (SEQ ID NO: 178) (SEQ
ID NO: 179) C > T2 TGCATTTTCTGCTTGA TTTGTTTGTAATATA
TCTGGTACCTGGACCA AATCTGGTACtTGGA CAGAAGA CTGCTCTGTCCTGAT A CCAA
(SEQ ID NO: 140) (SEQ ID NO: 141) (SEQ ID NO: 180) (SEQ ID NO: 181)
G > A GCCAAAGAAGAAACAC AAATGATGTGGTTAT TGAACCTCgAACAAT
TTGAACCTCaAACAA CAAAAAAT TAAATGAAGATGTTG (SEQ ID No: 182) TT (SEQ
ID NO: 142) (SEQ ID NO: 143) (SEQ ID NO: 183) G > A2
AAGAGGTTGAAGAAGT ATACATACACAAGGG CTGGTGATGgATCC CTGGTGATGaATCC
GCTGAAAAATAT TTTATTTTGTTCCT (SEQ ID NO: 184) (SEQ ID NO: 185) (SEQ
ID NO: 144) (SEQ ID NO: 145) 4. GSTM1 C5345 GTTCCAGCCCACACAT
CGGGAGATGAAGTCC CAAGCAgTTGGGC CAAGCAcTTGGGC TCTTG TTCAGATT (SEQ ID
NO: 186) (SEQ ID NO: 187) (SEQ ID NO: 146) (SEQ ID NO: 147) 5.
GSTP1 A313G CCTGGTGGACATGGTG GCAGATGCTCACATA GCAAATACaTCTCCCT
GCAAATACgTCTCCC AATG GTTGGTGTAG (SEQ ID NO: 188) T (SEQ ID NO: 148)
(SEQ ID NO: 149) (SEQ ID NO: 189) C341T GGGATGAGAGTAGGAT
GGGTCTCAAAAGGCT CCTTGCCCgCCTC CTTGCCCaCCTCC GATACATGGT TCAGTTG (SEQ
ID NO: 190) (SEQ ID NO: 191) (SEQ ID NO: 150) (SEQ ID NO: 151) 6.
GSTTI TCATTCTGAAGGCCAA CAGGGCATCAGCTTC CCTGCAGACCCC N/A GGACTT
TGCTT (SEQ ID NO: 192) (SEQ ID NO: 152) (SEQ ID NO: 153) 7.
A45MnSOD T-28C GGCTGTGCTTTCTCGT TTCTGCCTGGAGCCC ACCCCAAAaCCGGA
ACCCCAAAgCCGGA CTTCA AGAT (SEQ ID NO: 193) (SEQ ID NO: 194) (SEQ ID
NO: 154) (SEQ ID NO: 155) T175C GTGTTGCATTTACTTC TCCAGAAAATGCTAT
AGCCCAGAtAGCT AGCCCAGAcAGCT AGGAGATGTT GATTGATATGAC (SEQ ID NO:
195) (SEQ ID NO: 196) (SEQ ID NO: 156) (SEQ ID NO: 157 8. MTHFR
C677T GACCTGAAGCACTTGA TCAAAGAAAAGCTGC AAATCGgCTCCCGC
AAATCGaCTCCCGCA AGGAGAA GTGATGA (SEQ ID NO: 197) GA (SEQ ID NO:
158) (SEQ ID NO: 159) (SEQ ID NO: 198) A1298C AAGAGCAAGTCCCCCA
CTTTGTGACCATTCC CAGTGAAGaAAGTGTC AGTGAAGcAAGTGTC AGGA GGTTTG (SEQ
ID NO: 199) (SEQ ID NO: 200) (SEQ ID NO: 160) (SEQ ID NO: 161) 9.
ALDH2 G1156A CCCTTTGGTGGCTACA AGACCCTCAAGCCCC TCACAGTTTTCACTTc
TCACAGTTTTCACTT AGATGT AACA AGTGT tAGTGT (SEQ ID NO: 162) (SEQ ID
NO: 163) (SEQ ID NO: 201) (SEQ ID NO: 202)
TABLE-US-00002 TABLE 2 Examples of Primer pairs Primer Gene set
Forward Reverse Size NAT1 1 N/A same genotype as set 3 2 N/A same
genotype as set 3 3 5'ggg ttt gga cgc tca 5'aat gta ctg ttc cct tct
141 bp tca c (SEQ ID NO: 86) gat ttg g (SEQ ID NO: 87) 4b 5'tcc gtt
tga cgg aag 5' ggg tct gca agg aac 234 bp aga at (SEQ ID NO: 88)
aaa at (SEQ ID NO: 89) 5 5'gaa aca taa cca caa 5'caa caa taa acc
aac att 241 bp acc (SEQ ID NO: 90) aaa agc (SEQ ID NO: 91) NAT2 1
5'act tct gta ctg ggc 5'gca tcg aca atg taa ttc 150 bp tct gac c
ctg c (SEQ ID NO: 93) (SEQ ID NO: 92) 380 bp 2 5'aat aca gca ctg
gca 5'caa gga aca aaa tga tgt tgg (SEQ ID NO: 94) gg (SEQ ID NO:
95) 3 5'gtg ggc ttc atc ctc 5' ggg tga tac ata cac 209 bp acc ta
(SEQ ID NO: 96) aag ggt tt (SEQ ID NO: 97) MTHFR 1 5' agg tta ccc
caa 5'gca agt gat gcc cat gtc 166 bp aag cca cc g (SEQ ID NO: 101)
(SEQ ID NO: 100) 2 5'tct tct acc tga aga 5'caa gtc act ttg tga cca
142 bp gca agt cc ttc c (SEQ ID NO: 103) (SEQ ID NO: 102) CYP1A1 1b
5'cct gaa ctg cca ctt 5'cca gga aga gaa aga cct 199 bp cag c (SEQ
ID NO: 104) cc (SEQ ID NO: 105) 2 5' ccc att ctg tgt 5' aga ggc tga
ggt ggg 213 bp ttg ggt ttt t aga at (SEQ ID NO: 107) (SEQ ID NO:
106) GSTT1 1 5'gag gtc att ctg aag 5'ttt gtg gac tgc tga 133 bp gcc
aag g gga cg (SEQ ID NO: 109) (SEQ ID NO: 108) .beta.- 1b 5'tcc tca
gat cat tgc 5'taa cgc aac taa gtc ata 175 bp actin tcc (SEQ ID NO:
110) gtc c (SEQ ID NO: 111) MnSOD 1 5'ggc tgt gct ttc tcg 5'ggt gac
gtt cag gtt gtt 194 bp tct tc (SEQ ID NO: 112) ca (SEQ ID NO: 113)
2 5' aca gtg gtt gaa 5'caa aat gta gat aag ggt 205 bp aaa gta gg gc
(SEQ ID NO: 115) (SEQ ID NO: 114) ALDH2 1 5'ttg gtg gct aca aga
5'agg tcc tga act tcc agc 345 bp tgt cg (SEQ ID NO: 116) ag (SEQ ID
NO: 117) GSTP1 1 5'gct cta tgg gaa gga 5' aag cca cct gag ggg 192
bp cca gc (SEQ ID NO: 118) taa gg (SEQ ID NO: 119) 2 5'cag cag ggt
ctc aaa 5' gat gga cag gca gaa 250 bp agg (SEQ ID NO: 120) tgg (SEQ
ID NO: 121)
[0091] Having obtained a sample of DNA, preferably with amplified
regions of interest, individual polymorphisms may be identified.
Identification of the markers for the polymorphisms involves the
discriminative detection of allelic forms of the same gene that
differ by nucleotide substitution, or in the case of some genes,
for example the GSTM1 and GSTT1 genes, deletion of the entire gene.
Methods for the detection of known nucleotide differences are well
known to the skilled person. These may include, but are not limited
to:
a. Hybridization with allele-specific oligonucleotides (ASO),
(Wallace, 1981; Ikuta, 1987; Nickerson, 1990, Varlaan, 1986, Saiki,
1989 and Zhang, 1991). b. Allele specific PCR, (Newton 1989, Gibbs,
1989). c. Solid-phase minisequencing (Syvanen, 1993). d.
Oligonucleotide ligation assay (OLA) (Wu, 1989, Barany, 1991;
Abravaya, 1995). e. The 5' fluorogenic nuclease assay (Holland,
1991 & 1992, Lee, 1998, U.S. Pat. Nos. 4,683,202, 4,683,195,
5,723,591 and 5,801,155). f. Restriction fragment length
polymorphism (RFLP), (Donis-Keller, 1987).
[0092] In a preferred embodiment, the genetic loci are assessed via
a specialised type of PCR used to detect polymorphisms, commonly
referred to as the Taqman.RTM. assay and performed using an AB7700
instrument (Applied Blosystems, Warrington, UK). In this method, a
probe is synthesised which hybridises to a region of interest
containing the polymorphism. The probe contains three
modifications: a fluorescent reporter molecule, a fluorescent
quencher molecule and a minor groove binding chemical to enhance
binding to the genomic DNA strand. The probe may be bound to either
strand of DNA. For example, in the case of binding to the coding
strand, when the Taq polymerase enzyme begins to synthesise DNA
from the 5' upstream primer, the polymerase will encounter the
probe and begin to remove bases from the probe one at a time using
a 5'-3' exonuclease activity. When the base bound to the
fluorescent reporter molecule is removed, the fluorescent molecule
is no longer quenched by the quencher molecule and the molecule
will begin to fluoresce. This type of reaction can only take place
if the probe has hybridised perfectly to the matched genomic
sequence. As successive cycles of amplification take place, i.e.
more probes and primers are bound to the DNA present in the
reaction mixture, the amount of fluorescence will increase and a
positive result will be detected. If the genomic DNA does not have
a sequence that matches the probe perfectly, no fluorescent signal
is detected.
[0093] Examples of oligonucleotide probes which may be used in the
invention, particularly when the Tagman.RTM. assay is used in the
method of the invention together with primers which may be used.
These oligonucleotide probes form another aspect of the present
invention.
[0094] Therefore in a further aspect of the invention, there is
provided an oligonucleotide having a sequence selected from SEQ ID
NO: 164-202. The invention further provides a set of
oligonucleotides comprising at least 5, 10, 20, 30, 40, 50, 60 or
70 oligonucleotides selected from the group comprising SEQ ID
NO:164-202.
Arrays
[0095] In a preferred embodiment of the invention, hybridisation
with allele specific oligonucleotides is conveniently carried out
using oligonucleotide arrays, preferably microarrays, to determine
the presence of particular polymorphisms.
[0096] Such microarrays allow miniaturisation of assays, e.g.
making use of binding agents (such as nucleic acid sequences)
immobilised in small, discrete locations (microspots) and/or as
arrays on solid supports or on diagnostic chips. These approaches
can be particularly valuable as they can provide great sensitivity
(particularly through the use of fluorescent labelled reagents),
require only very small amounts of biological sample from
individuals being tested and allow a variety of separate assays to
be carried out simultaneously. This latter advantage can be useful
as it provides an assay for different a number of polymorphisms of
one or more genes to be carried out using a single sample. Examples
of techniques enabling this miniaturised technology are provided in
WO84/01031, WO88/1058, WO89/01157, WO93/8472,
WO95/18376/WO95/18377, WO95/24649 and EP-A-0373203, the subject
matter of which are herein incorporated by reference.
[0097] DNA microarrays have been shown to provide appropriate
discrimination for polymorphism detection. Yershov, 1996; Cheung,
1999 and Schena 1999 have described the principles of the
technique. In brief, the DNA microarray may be generated using
oligonucleotides that have been selected to hybridise with the
specific target polymorphism. These oligonucleotides may be applied
by a robot onto a predetermined location of a glass slide, e.g. at
predetermined X,Y cartesian coordinates, and immobilised. The PCR
product (e.g. fluorescently labelled RNA or DNA) is introduced on
to the DNA microarray and a hybridisation reaction conducted so
that sample RNA or DNA binds to complementary sequences of
oligonucleotides in a sequence-specific manner, and allow unbound
material to be washed away. Gene target polymorphisms can thus be
detected by their ability to bind to complementary oligonucleotides
on the array and produce a signal. The absence of a fluorescent
signal for a specific oligonucleotide probe indicates that the
client does not have the corresponding polymorphism. Of course, the
method is not limited to the use of fluorescence labelling but may
use other suitable labels known in the art. the fluorescence at
each coordinate can be read using a suitable automated detector in
order to correlate each fluorescence signal with a particular
oligonucleotide.
[0098] Oligonucleotides for use in the array may be selected to
span the site of the polymorphism, each oligonucleotide comprising
one of the following at a central location within the sequence:
a. wild-type or normal base at the position of interest in the
leading strand b. wild-type or normal base at the position of
interest in the lag (non-coding) strand c. altered base at the
position of interest in the leading strand d. altered complementary
base at the position of interest in the lag strand
[0099] The arrays used in the present method form another
independent aspect of the present invention. Arrays of the
invention comprise a set of two or more oligonucleotides, each
oligonucleotide being specific to a sequence comprising one or more
polymorphisms of a gene selected from the group comprising
categories a-k as defined above.
[0100] Preferably, the array will comprise oligonucleotides each
being specific to a sequence comprising one or more polymorphisms
of an individual gene of at least two different categories a-k as
defined above, for example a+b (i.e. at least one oligonucleotide
specific for a sequence comprising one or more polymorphisms of a
first gene, the first gene being of category a and at least one
oligonucleotide specific for a sequence comprising one or more
polymorphisms of a second gene, the second gene being of category
b), a+c, a+d, a+e, a+f, a+g, a+h, a+i, a+j, a+k, b+c, b+d, b+e
etc., c+d, c+e etc, d+e, d+f etc, e+f, e+g etc, f+g, f+h etc., g+h,
g+i, g+k, h+i, h+k. Where the array comprises two or more
oligonucleotides, it is preferred that at least one of the
oligonucleotides is an oligonucleotide specific for a sequence of a
polymorphism of a gene of category d, due to the central role of
micronutrients in the maintenance of proper cellular growth and DNA
repair, and due to the association of micronutrient metabolism or
utilisation disorders with several different types of diseases
(Ames 1999; Perera, 2000; Potter, 2000). More preferably, the array
will comprise oligonucleotides each being specific to a sequence
comprising one or more polymorphisms of an individual gene of at
least three different categories a-k as defined above, for example,
a+b+c, a+b+d, a+b+e, a+b+f, a+b+g, a+b+h, a+b+i, a+b+j, a+b+k
a+c+d, a+c+e etc, a+d+e, etc, b+c+d, etc, c+d+e etc, d+e+f etc, and
all other combinations of three categories. Where the array
comprises three or more oligonucleotides, it is preferred that at
least two of the oligonucleotides are oligonucleotides specific for
a sequence of a polymorphism of a gene of categories d and e.
Information relating to polymorphisms present in both of these
categories is particularly useful due to the effects of alcohol
consumption and metabolism on the efficiency of enzymes related to
micronutrient metabolism and utilisation. (Ulrich, 1999). In a
further preferred embodiment where the array comprises three or
more oligonucleotides, it is preferred that at least two of the
oligonucleotides are oligonucleotides specific for a sequence of a
polymorphism of a gene of c categories a and b due to the close
interaction of Phase I and Phase II enzymes in the metabolism of
xenobiotics. Even more preferably, the array will comprise
oligonucleotides each being specific to a sequence comprising one
or more polymorphisms of an individual gene of at least four
different categories a-k as defined above, for example, a+b+c+d,
a+b+c+e, a+b+d+e, a+c+d+e, b+c+d+e etc. Where the array comprises
four or more oligonucleotides, it is preferred that at least three
of the oligonucleotides are oligonucleotides specific for a
sequence of a polymorphism of a gene of categories d and e and f
Information relating to polymorphisms present in these three
categories is particularly useful due to the strong correlation of
polymorphisms of these alleles with coronary artery disease due to
the combined effects of altered micronutrient utilisation, affected
adversely by alcohol metabolism, together with imbalances in fat
and cholesterol metabolism. Where the array comprises five or more
oligonucleotides, it is preferred that at least four of the
oligonucleotides are oligonucleotides specific for a sequence of a
polymorphism of a gene of categories a, b, d and e. Information
relating to polymorphisms present in these four categories is
particularly useful due to the combined effects of micronutrients
utilisation, alcohol metabolism, Phase 1 metabolism of xenobiotics
and Phase II metabolism on the further metabolism and excretion of
potentially harmful metabolites produced in the body (Taningher,
1999; Ulrich, 1999). Similarly, the array may comprise
oligonucleotides each being specific to a sequence comprising one
or more polymorphisms of an individual gene of at least five, for
example a, b, d, e and f, six, seven, eight, nine or ten different
categories a-k as defined above.
[0101] Most preferably, the array will comprise oligonucleotides
each being specific to a sequence comprising one or more
polymorphisms of an individual gene of each of categories a-k as
defined above.
[0102] In one preferred embodiment, the array comprises
oligonucleotides each being specific to a sequence comprising one
or more polymorphisms of individual genes, the individual genes
comprising each member of the group comprising genes encoding
cytochrome P450 monooxygenase, N-acetyltransferase 1,
N-acetyltransferase 2, glutathione-S-transferase, manganese
superoxide dismutase, 5,10-methylenetetrahydrofolatereductase and
alcohol dehydrogenase 2 enzymes. genetic loci of genes encoding
each of the cytochrome P450 monooxygenase, N-acetyltransferase 1,
N-acetyltransferase 2, glutathione-S-transferase, manganese
superoxide dismutase, 5,10-methylenetetrahydrofolatereductase and
alcohol dehydrogenase 2 enzymes. In a more preferred embodiment the
array further comprises oligonucleotides specific for one or more
alleles of the genetic loci of genes encoding one or more,
preferably each of epoxide hydrolase (EH), NADPH-quinone reductase
(NQ01), paraxonaoase (PON1), myeloperoxidase (MPO), alcohol
dehydrogenase 1, alcohol dehydrogenase 3, cholesteryl ester
transfer protein, apolipoprotein A IV, apolipoprotein E,
apolipoprotein C III, angiotensin, factor VII, prothrombin 20210,
.beta.-fibrinogen, heme-oxygenase-1, .alpha.-antitrypsin, SPINK1,
.DELTA.-aminolevulinacid dehydratase, interleukin 1, interleukin 1,
vitamin D receptor, B1 kinin receptor, cystathionine-beta-synthase,
methionine synthase (B12 MS), 5-HT transporter, transforming growth
factor beta 1 (TGF.beta.1), L-myc, HLA Class 2 molecules,
T-lymphocyte associated antigen 4 (CTLA-4), interleukin 4,
interleukin 3, interleukin 6, IgA, and/or galactose metabolism gene
GALT.
[0103] In preferred arrays, the oligonucleotides in the array
comprise at least 5, 10, 20, 30, 40, 50, 60 or 70 oligonucleotides
selected from the group comprising SEQ ID NO:1-SEQ ID NO: 85
illustrated in TABLE 3 which shows preferred oligonucleotides
listed in the right column with the primer set used to amplify the
appropriate fragments of sample DNA listed in the left column.
[0104] In a preferred embodiment the array will comprise all of the
oligonucleotides SEQ ID NO:1-85.
TABLE-US-00003 TABLE 3 Gene Target 25 nt sequence 1. CYP1A1 Primer
set1 A4889G wt-lead 5' atc ggt gag acc Att gcc cgc tgg g (SEQ ID
NO: 1) Primer set1 A4889G wt-lag 5' ccc agc ggg caa Tgg tct cac cga
t (SEQ ID NO: 2) Primer set1 A4889G polymorph- 5' atc ggt gag acc
Gtt gcc cgc tgg g lead (SEQ ID NO: 3) Primer set1 A4889G polymorph-
5' ccc agc ggg caa Cgg tct cac cga t lag (SEQ ID NO: 4) Primer set2
T6235C wt-lead 5' acc tcc acc tcc Tgg gct cac acg a (SEQ ID NO: 5)
Primer sett T6235C wt-lag 5' tcg tgt gag ccc Agg agg tgg agg t (SEQ
ID NO: 6) Primer set2 T6235C polymorph- 5' acc tcc acc tcc Cgg gct
cac acg a lead (SEQ ID NO: 7) Primer set2 T6235C polymorph- 5' tcg
tgt gag ccc Ggg agg tgg agg t lag (SEQ ID NO: 8) 2. NAT1 Primer
set1 N/A Primer set2 N/A Primer set 3 G445A wt-lead 5' cag gtg cct
tgt Gtc ttc cgt ttg a (SEQ ID NO: 9) Primer set3 G445A wt-lag 5'
tca aac gga aga Cac aag gca cct g (SEQ ID NO: 10) Primer set3 G445A
polymorph- 5' cag gtg cct tqt Atc ttc cgt ttg a lead (SEQ ID NO:
11) Primer set3 G445A polymorph- 5' tca aac gga aga Tac aag gca cct
g lag (SEQ ID NO: 12) Primer set3 G459A wt-lead 5' ctt ccg ttt gac
Gga aga gaa tgg a (SEQ ID NO: 13) Primer set3 G459A wt-lag 5' tcc
att ctc ttc Cgt caa acg gaa g (SEQ ID NO: 14) Primer set3 G459A
polymorph- 5' ctt ccg ttt gac Aga aga gaa tgg a lead (SEQ ID NO:
15) Primer set3 G459A polymorph- 5' tcc att ctc ttc Tgt caa acg gaa
g lag (SEQ ID NO: 16) Primer set3 G560A wt-lead 5' aca gca aat acc
Gaa aaa tct act c (SEQ ID NO: 17) Primer set4 G560A wt-lag 5' gag
tag att ttt Cgg tat ttg ctg t (SEQ ID NO: 18) Primer set4 G560A
polymorph- 5' aca gca aat acc Aaa aaa tct act c lead (SEQ ID NO:
19) Primer set4 G560A polymorph- 5' gag tag att ttt Tcc tat ttg ctg
t lag (SEQ ID NO: 20) Primer set5 T1088A wt-lead*a 5' taa taa taa
tae Taa atg tct ttt a (SEQ ID NO: 21) Primer set5 T1088A wt-lag*a
5' taa aag aca ttt Att att att att a (SEQ ID NO: 22) Primer set5
T1038A wt-lead*b 5' taa taa taa taa Taa atg tat ttt a (SEQ ID NO:
23) Primer set5 T1088A wt-lag*b 5' taa aat aca ttt Att att tta att
a (SEQ ID NO: 24) Primer set5 T1088A polymorph- 5' taa taa taa taa
Aaa atg tct ttt a lead*a (SEQ ID NO: 25) Primer set5 T1088A
polymorph- 5' taa aag aca ttt Ttt att tta att a lag*a (SEQ ID NO:
26) Primer set5 T1088a polymorph- 5' taa taa taa taa Aaa atg tat
ttt a lead*b Primer set5 T1088A polymorph- 5' taa aat aca ttt Ttt
att tta att a lag*b (SEQ ID NO: 27) Primer set5 C1095A wt-lead*a 5'
aat aat aaa tgt Ctt tta aag atg g (SEQ ID NO: 28) Primer set5
C1095A wt-lag*a 5' cca tct tta aaa Gac att tat tat t (SEQ ID NO:
29) Primer set5 C1095A wt-lead*b 5' aat aaa aaa tgt Ctt tta aag atg
g (SEQ ID NO: 30) Primer set5 C1095A wt-lag*b 5' cca tct tta aaa
Gac att ttt tat t (SEQ ID NO: 31) Primer set5 C1095A polymorph- 5'
aat aat aaa tgt Att tta aag atg g lead*a (SEQ ID NO: 32) Primer
set5 C1095A polymorph- 5' caa tct tta aaa Tac att tat tat t lag*a
(SEQ ID NO: 33) Primer set5 C1095A polymorph- 5' aat aaa aaa tgt
Att tta aag atg g lead*b (SEQ ID NO: 34) Primer set5 C1095A
polymorph- 5' cca tct tta aaa Tac att ttt tat t lag*b (SEQ ID NO:
35) 3. NAT2 Primer set1 C282T wt-lead 5' agg gta ttt tta Cat ccc
tcc agt t (SEQ ID NO: 36) Primer set1 C282T wt-lag 5' aac tgg agg
gat Gta aaa ata ccc t (SEQ ID NO: 37) Primer set1 C282T polymorph-
5' agg gta ttt tta Tat ccc tcc agt t lead (SEQ ID NO: 38) Primer
set1 C282T polymorph- 5' aac tgg agg gat Ata aaa ata ccc t lag (SEQ
ID NO: 39) Primer set2 C481T wt-lead 5' gga atc tgg tac Ctg gac caa
atc a (SEQ ID NO: 40) Primer set2 C481T wt-lag 5' tga ttt ggt cca
Ggt acc aga tta c (SEQ ID NO: 41) Primer set2 C481T polymorph- 5'
gga atc tgg tac Ttg gac caa atc a lead (SEQ ID NO: 42) Primer set2
C481T polymorph- 5' tga ttt ggt cca Agt acc aga ttc c lag (SEQ ID
NO: 43) Primer set2 G590A wt-lead 5' cgc ttg aac ctc Gaa caa ttg
aag a (SEQ ID NO: 44) Primer set2 G590A wt-lag 5' tct tca att gtt
Cga ggt tca agc g (SEQ ID NO: 45) Primer set2 G590A polymorph- 5'
cgc ttg aac ctc Aaa caa ttg aag a lead (SEQ ID NO: 46) Primer set2
G590A polymorph- 5' tat tca att gtt Tga ggt tca agc g lag (SEQ ID
NO: 47) Primer set3 G857A wt-lead 5' aac ctg gtg atg Gat ccc tta
cta t (SEQ ID NO: 43) Primer set3 G857A wt-lag 5' ata gta agg gat
Cca tca ccc ggt t (SEQ ID NO: 49) Primer set3 G857A polymorph- 5'
aac ctg gtg atg Aat ccc tta cta t lead (SEQ ID NO: 50) Primer set3
G857A polymorph- 5' ata gta agg gat Tca tca cca ggt t lead (SEQ ID
NO: 51) 4. GSTM1 Primer set1 wt-lead 5' gct aca ttg ccc gca agc aca
acc t (SEQ ID NO: 52) Primer set1 wt-lag 5' agg ttg tgc ttg cgg gca
atg tag c (SEQ ID NO: 53) 5. GSTP1 Primer set1 A313G wt-lead 5' cgc
tgc aaa tac Atc tcc ctc atc t (SEQ ID NO: 54) Primer set1 A313G
wt-lag 5' aga tga ggg aga Tgt att tgc agc g (SEQ ID NO: 55) Primer
set1 A313G polymorph- 5' cgc tgc aaa tac Gtc tcc ctc atc t lead
(SEQ ID NO: 56) Primer set1 A313G polymorph- 5' aga tga ggg aga Cgt
att tgc agc g lag (SEQ ID NO: 57) Primer set2 C341T wt-lead 5' tct
ggc agg agg Cgg gca agg atg a (SEQ ID NO: 58) Primer set2 C341T
wt-lag 5' tca tcc ttg ccc Gcc tcc tgc cag a (SEQ ID NO: 59) Primer
set2 C341T polymorph- 5' tct ggc agg agg Tgg gca agg atg a lead
(SEQ ID NO: 60) Primer set2 C341T polymorph- 5' tca tcc ttg ccc Acc
tcc tgc cag a lag (SEQ ID NO: 61) 6. GSTT1 Primer set1 wt-lead 5'
acc ata aag cag aag ctg atg ccc t (SEQ ID NO: 62) Primer set2
wt-lag 5' agg gca tca gct tct gct tta tgg t (SEQ ID NO: 63) 7.
MnSOD Primer set1 T-26C wt-lead 5' agc tgg ctc cgg Ttt tgg ggt atc
t (SEQ ID NO: 64) Primer set1 T-26C wt-lag 5' aga tac ccc aaa Acc
gga gcc agc t (SEQ ID NO: 65) Primer set1 T-26C polymorph- 5' agc
tgg ctc cgg Ctt tgg ggt atc t lead (SEQ ID NO: 66) Primer set1
T-26C polymorph- 5' aga tac ccc aaa Gcc gga gcc agc t lag (SEQ ID
NO: 67) primer set2 T175C wt-lead 5' tta cag ccc aga Tag ctc ttc
agc c (SEQ ID NO: 68) Primer set2 T175C wt-lag 5' ggc tga aga gct
Atc tgg gct gta a (SEQ ID NO: 69) Primer set2 T175C polymorph- 5'
tta cag ccc aga Cag ctc ttc agc c lead (SEQ ID NO: 70) Primer set2
T175C polymorph- 5' ggc tga aga gct Gtc tgg gct gta a lag (SEQ ID
NO: 71) 8. MTHFR Primer set1 C677T wt-lead 5' tgt ctg cgg gag Ccg
att tca tca t (SEQ ID NO: 72) Primer set1 C677T wt-lag 5' atg atg
aaa tcg Gct ccc gca gac a (SEQ ID NO: 73) Primer set1 C677T
polymorph- 5' tgt ctg cgg gag Tcg att tca tca t lead (SEQ ID NO:
74) Primer set1 C677T polymorph- 5' atg atg aaa tcg Act ccc gca gac
a lag (SEQ ID NO: 75) Primer set2 A1298C wt-lead 5' tga cca gtg aag
Aaa gtg tct ttg a (SEQ ID NO: 76) Primer set2 A1298C wt-lag 5' tca
aag aca ctt Tct tca ctg gtc a (SEQ ID NO: 77) Primer set2 A1298C
polymorph- 5' tga cca gtg aag Caa gtg tct ttg a lead (SEQ ID NO:
78) Primer set2 A1298C polymorph- 5' tca aag aca ctt Gct tca ctg
gtc a lag (SEQ ID NO: 79)
9. ALDH2 Primer set1 wt-lead 5' cag gca tac act Gaa qtg aaa act g
(SEQ ID NO: 80) Primer set 1 wt-lag 5' cag ttt tca ctt Cag tat atg
cct g (SEQ ID NO: 81) Primer set1 polymorph-lead 5' cag gca tac act
Aaa gtg aaa act g (SEQ ID NO: 82) Primer set 1 polymorph-lag 5' cag
ttt tca ctt Tag tgt atg cct g (SEQ ID NO: 83) 10. beta-Actin Primer
set1-lead 5' tgc atc tct gcc tta cag atc atg t (SEQ ID NO: 84)
Primer set1-lag 5' aga tga tct gta agg cag aga tgc a (SEQ ID NO:
85) *redundancy due to adjacent polymorphisms
Advice Decision Tree
[0105] The results of genetic polymorphism analysis may be used to
correlate the genetic profile of the donor of the sample with
disease susceptibility using the first dataset, which provides
details of the relative disease susceptibility associated with
particular polymorphisms and their interactions. The risk factors
identified using dataset 1 can then be matched with dietary and
other lifestyle recommendations from dataset 2 to produce a
lifestyle advice plan individualised to the genetic profile of the
donor of the sample. Examples of datasets 1 and 2 which may be used
to generate such advice is illustrated in FIG. 1.
[0106] To enable appropriate advice to be tailored to particular
susceptibilities, a ranking system is preferably used to provide an
indication of the degree of susceptibility of a specific polymorph
to risk of cancer(s) and/or other conditions. The ranking system
may be designed to take into account of homozygous or heterozygous
alleles in the client's sample, i.e. the same or different alleles
being present in diploid nucleus. Five categories which may be used
are summarised below: [0107] (i) Reduced susceptibility: where an
allele has been shown to reduce susceptibility. [0108] (ii) (ii)
Normal susceptibility: where allele has been shown to have a normal
susceptibility of risk to cancer(s) or disease. This is generally
the homozygous wild type allele or a polymorphism that has been
shown to have similar function. [0109] (iii) Moderate
susceptibility: where a heterozygous genotype is present that
contains the wild type of the allele (i.e. normal susceptibility)
and an allele of the polymorphism known to give rise to higher
susceptibility to specific cancer(s) or disease. [0110] (iv) High
susceptibility: where a homozygous genotype that contains the
polymorphism is present with a higher risk of cancer
susceptibility. [0111] (v) Higher susceptibility: where a higher
susceptibility has been observed for specific cancer(s) or disease
due to the combined effects of two or more different gene
targets.
[0112] Using dataset 1, a susceptibility may be assigned to each
polymorphism identified and, from dataset 2, a lifestyle
recommendation corresponding to each susceptibility identified may
be assigned. For example, if an individual is found to have the
NAT1*10 polymorphism, the decision tree may indicate that the there
is an enhanced susceptibility of colonic cancer. Recommendations
appropriate to minimising the risk of colonic cancer are then
generated. For example, the recommendations may be to avoid
particular foods associated with increased risk and to increase
consumption of other foods associated with a protective effect
against such cancers. The totality of recommendations may be
combined to generate a lifestyle advice plan individualised to the
donor of the sample. The decision tree is preferably arranged to
recognise particular combinations of polymorphisms and/or
susceptibilities which interact either positively to produce a
susceptibility greater than would be expected from the risk factors
associated with each individually, and/or, which interact
negatively to reduce the susceptibility associated with each
individually. Where such combinations are identified, the advice
generated can be tailored accordingly. For example, the combination
of NAT2*4 and NAT1*10 polymorphisms have been linked to increased
cancer risk (Bell, 1995). Therefore, when such a combination of
polymorphisms is identified from a subject's DNA, the associated
very high susceptibility to cancer is assigned and the advice
tailored to emphasise the need to reduce consumption of
xenobiotics, e.g. by reducing or eliminating consumption of
char-grilled foodstuffs.
[0113] In generating the advice, other factors such as information
concerning the sex and health of the individual and/or of the
individual's family, age, alcohol consumption, and existing diet
may be used in the determination of appropriate lifestyle
recommendations.
EXPERIMENTAL
Example 1
Preparation of DNA Sample
[0114] DNA is prepared from a buccal cell sample on a brush using a
Qiagen QIAamp kit according to the manufacturer's instructions
(Qiagen, Crawley, UK). Briefly, the brush is cut in half and one
half stored at room temperature in a sealed tube in case retesting
is required. The other half of the brush is placed in a
microcentrifuge tube. 400 .mu.l PBS is added and the brush allowed
to rehydrate for 45 minutes at room temperature. Quiagen lysis
buffer and Proteinase K is then added, the contents are mixed, and
allowed to incubate at 56 C for 15 minutes to lyse the cells.
Ethanol is added and the lysate transferred to a QIAamp spin column
from which DNA is eluted after several washings.
Example 2
Quantification of DNA
[0115] In order to check that sufficient DNA has been isolated, a
quantification step is carried out using the PicoGreen dsDNA
Quantification kit (Molecular Probes, Eugene, Oreg., USA).
[0116] Briefly, client DNA samples are prepared by transferring a
10 .mu.l aliquot into a microcentrifuge tube with 90 .mu.l TE. 100
.mu.l of the working PicoGreen dsDNA quantification reagent is
added, mixed well, and transferred into a black 96 well plate with
flat well bottoms. The plate is then incubated for 5 minutes in the
dark before a fluorescent reading is taken. The quantity of DNA
present in the clients' samples is determined by extrapolating from
a calibration plot prepared using DNA standards.
[0117] A quantity of DNA in the range of 5-0 ng total is used in
the subsequent PCR step. Remaining client DNA sample is stored at
-20.degree. C. for retesting if required.
Example 3
Taqman.RTM. Assay to Identify the MTHFR A1298C Polymorphism
[0118] The modified reaction mixture contains Taq polymerase (1.25
units/.mu.l), optimised PCR buffer, dNTP (200 M each), 2 mM
MgCl.sub.2 and primer pairs SEQ ID NO: 160 and 161 and polymorphism
probe SEQ ID NO: 200.
[0119] The reaction mixture is initially incubated for 10 minutes
at 50.degree. C., then 5 minutes at 95.degree. C., followed by 40
cycles of 1 minute of annealing at between 55.degree. C. and
60.degree. C. and 30 seconds of denaturation at 95.degree. C. Both
during the cycles and at the end of the run, fluorescence of the
released reporter molecules of the probe is measured by an integral
CCD detection system of the AB7700 thermocycler. The presence of a
fluorescent signal which increases in magnitude through the course
of the run indicates a positive result.
[0120] The assay is then repeated with the same primer pair and wt
probe SEQ ID NO: 199. If the sample is homozygous for the
polymorphism, no fluorescence signal is seen with the wt probe.
However, if the sample is heterozygous for the polymorphism, a
fluorescence signal is also seen with the wt probe. If single
reporter results from homozygous wt, homozygous polymorphic and
heterozygous polymorphic samples are plotted are plotted on an X/Y
axis, the homozygous alleles will cluster at opposite ends of the
axes relative to each reporter, and the heterozygous alleles will
cluster at a midway region.
Example 4
DNA Array Method for Identifying Polymorphisms for Identifying
Multiple Polymorphisms
a) PCR Amplification
[0121] The PCR reaction mix contains Taq polymerase (1.25
units/reaction), optimised PCR buffer, dNTP's (200 .mu.M each) and
MgCl.sub.2 at an appropriate concentration of between 1 and 4 mM,
and 40 pmol of each primer(SEQ ID NOS: 1-8, 17-63) for
amplification of seven fragments and the sample DNA.
[0122] The reaction mixture is initially incubated at 95.degree. C.
for 1 minute, and then subjected to 45 cycles of PCR in a MWG
TC9600 thermocycler (MWG-Biotech-AG Ltd., Milton Keynes, UK) as
follows: [0123] annealing 50.degree. C., 1 minute [0124]
polymerisation 73.degree. C., 1 minute [0125] denaturation
95.degree. C., 30 seconds.
[0126] After a further annealing step at 50.degree. C., 1 minute,
there is a final polymerisation step at 73.degree. C. for 7
minutes.
[0127] (Instead of the MWG TC9600 thermocycler, other
thermocyclers, such as the Applied Biosystems 9700 thermocycler
(Applied Biosystems, Warrington, UK), may be used.
[0128] After amplification of the target genes, generation of
product is checked by electrophoresis separation using 2% agarose
gel, or a 3.5% NuSieve agarose gel.
[0129] The PCR amplification products are then purified using the
Qiagen QIAquick PCR Purification Kit (Qiagen, Crawley, UK) to
remove dNTPs, primers, and enzyme from the PCR product. The PCR
product is layered onto a QIAquick spin column, a vacuum applied to
separate the PCR product from the other reaction products and the
DNA eluted in buffer.
b) RNA Transcription and Fluorescent Labelling of PCR Products
[0130] The DNA is then transcribed into RNA using T3 and T7 RNA
polymerases together with fluorescently labelled UTP for
incorporation into the growing chain of RNA. The reaction mixture
comprises:
20 .mu.l 5.times. reaction buffer; 500 .mu.M ATP, CTP, GTP,
fluorescent UTP (Amersham Ltd, UK); DEPC treated dH.sub.2O; 1 unit
T3 RNA polymerase or 1 unit T7 RNA polymerase (Promega Ltd.,
Southampton, UK); 1 unit Rnasin ribonuclaese inhibitor and DNA from
PCR (1/3 of total, 10 .mu.l in dH.sub.2O).
[0131] The mixture is incubated at 37.degree. C. for 1 hour. The
mixture is then treated with DNAse to remove DNA so that only newly
synthesised fluorescent RNA is left. The RNA is then precipitated,
microcentrifuged and resuspended in buffer for hybridisation on the
array.
c) Polymorphism Analysis
[0132] The sample amplified fragments are then tested using a DNA
microarray
[0133] The DNA microarray used comprises oligonucleotides SEQ ID
NOs: 1-85. These oligonucleotides are applied by a robot onto a
glass slide and immobilised. The fluorescently labelled amplified
DNA is introduced onto the DNA microarray and a hybridisation
reaction conducted to bind any complementary sequences in the
sample, allowing unbound material to be washed away. The presence
of bound samples is detected using a scanner. The absence of a
fluorescent signal for a specific oligonucleotide probe indicates
that the client does not have the corresponding polymorphism.
Example 5
DNA Array Method for Identifying G560A Polymorphism
[0134] The PCR reaction mix contains Taq polymerase (1.25
units/reaction), optimised PCR buffer, dNTP's (200 .mu.M each) and
MgCl.sub.2 at an appropriate concentration of between 1 and 4 mM,
and 40 pmol of each primer (SEQ ID NOs: 88,89) for amplification of
the fragment. The methods used is the same as detailed in Example
4, with the array comprising oligonucleotides SEQ ID NO: 17, 18, 19
and 20.
[0135] The presence of bound samples is detected using a scanner as
described above. A highly fluorescent spot is detected at the
positions corresponding to the oligonucleotides SEQ ID NO: 19 and
20. No signal is seen at the spots corresponding to SEQ ID NO: 17
and 18, demonstrating that the sample is not heterozygous for the
20 wt allele.
Example 6
Generation of Report
[0136] The results of the microarray or Taqman.RTM. analysis are
input into a computer comprising a first dataset correlating the
presence of individual alleles with a risk factor and a second
dataset correlating risk factors with lifestyle advice. A report is
generated identifying the presence of particular polymorphisms and
providing lifestyle recommendations based on the identified
polymorphisms. An example of such a decision process is shown in
FIG. 2.
[0137] A sample of DNA is screened and the alleles identified input
to a dataprocessor as Dataset 3. Each allele is matched to
lifestyle risk factor from dataset 1, e.g. high susceptibility to
colon cancer due to the presence of the NAT1*10 allele and the
absence of the GSTM1 allele. The identified risk factor is then
matched with one or more lifestyle recommendations from dataset 2,
for example "avoid red meat, chargrilled food, smoked meats and
fish; stop smoking immediately" (in order to avoid production of
potentially toxic byproducts by Phase 1 enzymes with increased
activity) and "increase consumption of vegetables of the allium
family e.g. onions and garlic, and the brassaicae family e.g.
broccoli" (in order to increase the activity of Phase 11 enzymes
present, such as GSTP1 and GSTT1 and others, in order to increase
the excretion of toxic byproducts of Phase 1 metabolism). This is
then checked against other factors input into the dataprocessor,
e.g. age, sex and existing diet to modify the recommendation
accordingly before generating the final recommendation appropriate
to the allele. The lifestyle recommendations are then assembled to
generate a comprehensive personalised lifestyle advice plan.
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Sequence CWU 1
1
205125DNAArtificial SequenceDescription of Artificial Sequence
Oligonucleotide 1atcggtgaga ccattgcccg ctggg 25225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
2cccagcgggc aatggtctca ccgat 25325DNAArtificial SequenceDescription
of Artificial Sequence Oligonucleotide 3atcggtgaga ccgttgcccg ctggg
25425DNAArtificial SequenceDescription of Artificial Sequence
Oligonucleotide 4cccagcgggc aacggtctca ccgat 25525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
5acctccacct cctgggctca cacga 25625DNAArtificial SequenceDescription
of Artificial Sequence Oligonucleotide 6tcgtgtgagc ccaggaggtg gaggt
25725DNAArtificial SequenceDescription of Artificial Sequence
Oligonucleotide 7acctccacct cccgggctca cacga 25825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
8tcgtgtgagc ccgggaggtg gaggt 25925DNAArtificial SequenceDescription
of Artificial Sequence Oligonucleotide 9caggtgcctt gtgtcttccg tttga
251025DNAArtificial SequenceDescription of Artificial Sequence
Oligonucleotide 10tcaaacggaa gacacaaggc acctg 251125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
11caggtgcctt gtatcttccg tttga 251225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
12tcaaacggaa gatacaaggc acctg 251325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
13cttccgtttg acggaagaga atgga 251425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
14tccattctct tccgtcaaac ggaag 251525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
15cttccgtttg acagaagaga atgga 251625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
16tccattctct tctgtcaaac ggaag 251725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
17acagcaaata ccgaaaaatc tactc 251825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
18gagtagattt ttcggtattt gctgt 251925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
19acagcaaata ccaaaaaatc tactc 252025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
20gagtagattt tttcctattt gctgt 252125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
21taataataat aataaatgtc tttta 252225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
22taaaagacat ttattattat tatta 252325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
23taataataat aataaatgta tttta 252425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
24taaaatacat ttattatttt aatta 252525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
25taataataat aaaaaatgtc tttta 252625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
26taaaagacat tttttatttt aatta 252725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
27taaaatacat tttttatttt aatta 252825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
28aataataaat gtcttttaaa gatgg 252925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
29ccatctttaa aagacattta ttatt 253025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
30aataaaaaat gtcttttaaa gatgg 253125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
31ccatctttaa aagacatttt ttatt 253225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
32aataataaat gtattttaaa gatgg 253325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
33ccatctttaa aatacattta ttatt 253425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
34aataaaaaat gtattttaaa gatgg 253525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
35ccatctttaa aatacatttt ttatt 253625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
36agggtatttt tacatccctc cagtt 253725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
37aactggaggg atgtaaaaat accct 253825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
38agggtatttt tatatccctc cagtt 253925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
39aactggaggg atataaaaat accct 254025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
40ggaatctggt acctggacca aatca 254125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
41tgatttggtc caggtaccag attcc 254225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
42ggaatctggt acttggacca aatca 254325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
43tgatttggtc caagtaccag attcc 254425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
44cgcttgaacc tcgaacaatt gaaga 254525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
45tcttcaattg ttcgaggttc aagcg 254625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
46cgcttgaacc tcaaacaatt gaaga 254725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
47tcttcaattg tttgaggttc aagcg 254825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
48aacctggtga tggatccctt actat 254925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
49atagtaaggg atccatcacc aggtt 255025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
50aacctggtga tgaatccctt actat 255125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
51atagtaaggg attcatcacc aggtt 255225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
52gctacattgc ccgcaagcac aacct 255325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
53aggttgtgct tgcgggcaat gtagc 255425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
54cgctgcaaat acatctccct catct 255525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
55agatgaggga gatgtatttg cagcg 255625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
56cgctgcaaat acgtctccct catct 255725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
57agatgaggga gacgtatttg cagcg 255825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
58tctggcagga ggcgggcaag gatga 255925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
59tcatccttgc ccgcctcctg ccaga 256025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
60tctggcagga ggtgggcaag gatga 256125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
61tcatccttgc ccacctcctg ccaga 256225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
62accataaagc agaagctgat gccct 256325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
63agggcatcag cttctgcttt atggt 256425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
64agctggctcc ggttttgggg tatct 256525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
65agatacccca aaaccggagc cagct 256625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
66agctggctcc ggctttgggg tatct 256725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
67agatacccca aagccggagc cagct 256825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
68ttacagccca gatagctctt cagcc 256925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
69ggctgaagag ctatctgggc tgtaa 257025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
70ttacagccca gacagctctt cagcc 257125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
71ggctgaagag ctgtctgggc tgtaa 257225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
72tgtctgcggg agccgatttc atcat 257325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
73atgatgaaat cggctcccgc agaca 257425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
74tgtctgcggg agtcgatttc atcat 257525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
75atgatgaaat cgactcccgc agaca 257625DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
76tgaccagtga agaaagtgtc tttga 257725DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
77tcaaagacac tttcttcact ggtca 257825DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
78tgaccagtga agcaagtgtc tttga 257925DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
79tcaaagacac ttgcttcact ggtca 258025DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
80caggcataca ctgaagtgaa aactg 258125DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
81cagttttcac ttcagtgtat gcctg 258225DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
82caggcataca ctaaagtgaa aactg 258325DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
83cagttttcac tttagtgtat gcctg 258425DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
84tgcatctctg ccttacagat catgt 258525DNAArtificial
SequenceDescription of Artificial Sequence Oligonucleotide
85agatgatctg taaggcagag atgca 258619DNAArtificial
SequenceDescription of Artificial Sequence Primer 86gggtttggac
gctcatacc 198725DNAArtificial SequenceDescription of Artificial
Sequence Primer 87aatgtactgt tcccttctga tttgg 258820DNAArtificial
SequenceDescription of Artificial Sequence Primer 88tccgtttgac
ggaagagaat 208920DNAArtificial SequenceDescription of Artificial
Sequence Primer 89gggtctgcaa ggaacaaaat 209018DNAArtificial
SequenceDescription of Artificial Sequence Primer 90gaaacataac
cacaaacc 189124DNAArtificial SequenceDescription of Artificial
Sequence Primer 91caacaataaa ccaacattaa aagc 249222DNAArtificial
SequenceDescription of Artificial Sequence Primer 92acttctgtac
tgggctctga cc 229322DNAArtificial SequenceDescription of Artificial
Sequence Primer 93gcatcgacaa tgtaattcct gc 229418DNAArtificial
SequenceDescription of Artificial Sequence Primer 94aatacagcac
tggcatgg 189520DNAArtificial SequenceDescription of Artificial
Sequence Primer 95caaggaacaa aatgatgtgg 209620DNAArtificial
SequenceDescription of Artificial Sequence Primer 96gtgggcttca
tcctcaccta 209723DNAArtificial SequenceDescription of Artificial
Sequence Primer 97gggtgataca tacacaaggg ttt 239818DNAArtificial
SequenceDescription of Artificial Sequence Primer 98cagcccacac
attcttgg 189918DNAArtificial SequenceDescription of Artificial
Sequence Primer 99aagcgggaga tgaagtcc 1810020DNAArtificial
SequenceDescription of Artificial Sequence Primer 100aggttacccc
aaaggccacc 2010119DNAArtificial SequenceDescription of Artificial
Sequence Primer 101gcaagtgatg cccatgtcg 1910223DNAArtificial
SequenceDescription of Artificial Sequence Primer 102tcttctacct
gaagagcaag tcc 2310322DNAArtificial SequenceDescription of
Artificial Sequence Primer 103caagtcactt tgtgaccatt cc
2210419DNAArtificial SequenceDescription of Artificial Sequence
Primer 104cctgaactgc cacttcagc 1910520DNAArtificial
SequenceDescription of Artificial Sequence Primer 105ccaggaagag
aaagacctcc 2010622DNAArtificial SequenceDescription of Artificial
Sequence Primer 106cccattctgt gtttgggttt tt 2210720DNAArtificial
SequenceDescription of Artificial Sequence Primer 107agaggctgag
gtgggagaat 2010822DNAArtificial SequenceDescription of Artificial
Sequence Primer 108gaggtcattc tgaaggccaa gg 2210920DNAArtificial
SequenceDescription of Artificial Sequence Primer 109tttgtggact
gctgaggacg 2011018DNAArtificial SequenceDescription of Artificial
Sequence Primer 110tcctcagatc attgctcc 1811122DNAArtificial
SequenceDescription of Artificial Sequence Primer 111taacgcaact
aagtcatagt cc 2211220DNAArtificial SequenceDescription of
Artificial Sequence Primer 112ggctgtgctt tctcgtcttc
2011320DNAArtificial SequenceDescription of Artificial Sequence
Primer 113ggtgacgttc aggttgttca 2011420DNAArtificial
SequenceDescription of Artificial Sequence Primer 114acagtggttg
aaaaagtagg 2011520DNAArtificial SequenceDescription of Artificial
Sequence Primer 115caaaatgtag ataagggtgc
2011620DNAArtificial SequenceDescription of Artificial Sequence
Primer 116ttggtggcta caagatgtcg 2011720DNAArtificial
SequenceDescription of Artificial Sequence Primer 117aggtcctgaa
cttccagcag 2011820DNAArtificial SequenceDescription of Artificial
Sequence Primer 118gctctatggg aaggaccagc 2011920DNAArtificial
SequenceDescription of Artificial Sequence Primer 119aagccacctg
aggggtaagg 2012018DNAArtificial SequenceDescription of Artificial
Sequence Primer 120cagcagggtc tcaaaagg 1812118DNAArtificial
SequenceDescription of Artificial Sequence Primer 121gatggacagg
cagaatgg 1812218DNAArtificial SequenceDescription of Artificial
Sequence Primer 122catgggcaag cggaagtg 1812324DNAArtificial
SequenceDescription of Artificial Sequence Primer 123caggatagcc
aggaagagaa agac 2412420DNAArtificial SequenceDescription of
Artificial Sequence Primer 124agacagggtc cccaggtcat
2012520DNAArtificial SequenceDescription of Artificial Sequence
Primer 125cagaggctga ggtgggagaa 2012625DNAArtificial
SequenceDescription of Artificial Sequence Primer 126ggagttaatt
tctgggaagg atcag 2512728DNAArtificial SequenceDescription of
Artificial Sequence Primer 127tggtctagat accagaatcc attctctt
2812823DNAArtificial SequenceDescription of Artificial Sequence
Primer 128ggcagcctct ggagttaatt tct 2312926DNAArtificial
SequenceDescription of Artificial Sequence Primer 129ttcccttctg
atttggtcta gatacc 2613025DNAArtificial SequenceDescription of
Artificial Sequence Primer 130gggaacagta cattccaaat gaaga
2513126DNAArtificial SequenceDescription of Artificial Sequence
Primer 131tgttcgaggc ttaagagtaa aggagt 2613231DNAArtificial
SequenceDescription of Artificial Sequence Primer 132aacaattgaa
gattttgagt ctatgaatac a 3113328DNAArtificial SequenceDescription of
Artificial Sequence Primer 133tctgcaagga acaaaatgat ttactagt
2813426DNAArtificial SequenceDescription of Artificial Sequence
Primer 134gaaacataac cacaaacctt ttcaaa 2613525DNAArtificial
SequenceDescription of Artificial Sequence Primer 135aaatcaccaa
tttccaagat aacca 2513629DNAArtificial SequenceDescription of
Artificial Sequence Primer 136aaacataacc acaaaccttt tcaaataat
2913725DNAArtificial SequenceDescription of Artificial Sequence
Primer 137aaatcaccaa tttccaagat aacca 2513825DNAArtificial
SequenceDescription of Artificial Sequence Primer 138aatcaacttc
tgtactgggc tctga 2513922DNAArtificial SequenceDescription of
Artificial Sequence Primer 139ccatgccagt gctgtatttg tt
2214023DNAArtificial SequenceDescription of Artificial Sequence
Primer 140tgcattttct gcttgacaga aga 2314130DNAArtificial
SequenceDescription of Artificial Sequence Primer 141tttgtttgta
atatactgct ctctcctgat 3014224DNAArtificial SequenceDescription of
Artificial Sequence Primer 142gccaaagaag aaacaccaaa aaat
2414329DNAArtificial SequenceDescription of Artificial Sequence
Primer 143aaatgatgtg gttataaatg aagatgttg 2914428DNAArtificial
SequenceDescription of Artificial Sequence Primer 144aagaggttga
agaagtgctg aaaaatat 2814529DNAArtificial SequenceDescription of
Artificial Sequence Primer 145atacatacac aagggtttat tttgttcct
2914621DNAArtificial SequenceDescription of Artificial Sequence
Primer 146gttccagccc acacattctt g 2114723DNAArtificial
SequenceDescription of Artificial Sequence Primer 147cgggagatga
agtccttcag att 2314820DNAArtificial SequenceDescription of
Artificial Sequence Primer 148cctggtggac atggtgaatg
2014925DNAArtificial SequenceDescription of Artificial Sequence
Primer 149gcagatgctc acatagttgg tgtag 2515026DNAArtificial
SequenceDescription of Artificial Sequence Primer 150gggatgagag
taggatgata catggt 2615122DNAArtificial SequenceDescription of
Artificial Sequence Primer 151gggtctcaaa aggcttcagt tg
2215222DNAArtificial SequenceDescription of Artificial Sequence
Primer 152tcattctgaa ggccaaggac tt 2215320DNAArtificial
SequenceDescription of Artificial Sequence Primer 153cagggcatca
gcttctgctt 2015421DNAArtificial SequenceDescription of Artificial
Sequence Primer 154ggctgtgctt tctcgtcttc a 2115519DNAArtificial
SequenceDescription of Artificial Sequence Primer 155ttctgcctgg
agcccagat 1915626DNAArtificial SequenceDescription of Artificial
Sequence Primer 156gtgttgcatt tacttcagga gatgtt
2615727DNAArtificial SequenceDescription of Artificial Sequence
Primer 157tccagaaaat gctatgattg atatgac 2715823DNAArtificial
SequenceDescription of Artificial Sequence Primer 158gacctgaagc
acttgaagga gaa 2315922DNAArtificial SequenceDescription of
Artificial Sequence Primer 159tcaaagaaaa gctgcgtgat ga
2216020DNAArtificial SequenceDescription of Artificial Sequence
Primer 160aagagcaagt cccccaagga 2016121DNAArtificial
SequenceDescription of Artificial Sequence Primer 161ctttgtgacc
attccggttt g 2116222DNAArtificial SequenceDescription of Artificial
Sequence Primer 162ccctttggtg gctacaagat gt 2216319DNAArtificial
SequenceDescription of Artificial Sequence Primer 163agaccctcaa
gccccaaca 1916414DNAArtificial SequenceDescription of Artificial
Sequence Probe 164cggtgagacc attg 1416514DNAArtificial
SequenceDescription of Artificial Sequence Probe 165cggtgagacc gttg
1416614DNAArtificial SequenceDescription of Artificial Sequence
Probe 166ctccacctcc tggg 1416714DNAArtificial SequenceDescription
of Artificial Sequence Probe 167ctccacctcc cggg
1416813DNAArtificial SequenceDescription of Artificial Sequence
Probe 168gccttgtgtc ttc 1316914DNAArtificial SequenceDescription of
Artificial Sequence Probe 169tgccttgtat cttc 1417015DNAArtificial
SequenceDescription of Artificial Sequence Probe 170cgtttgacgg
aagag 1517115DNAArtificial SequenceDescription of Artificial
Sequence Probe 171cgtttgacag aagag 1517214DNAArtificial
SequenceDescription of Artificial Sequence Probe 172aataccgaaa aatc
1417315DNAArtificial SequenceDescription of Artificial Sequence
Probe 173caaataccaa aaaat 1517415DNAArtificial SequenceDescription
of Artificial Sequence Probe 174catctccatc atctg
1517515DNAArtificial SequenceDescription of Artificial Sequence
Probe 175acatctccag catct 1517618DNAArtificial SequenceDescription
of Artificial Sequence Probe 176gccatcttta aaagacat
1817719DNAArtificial SequenceDescription of Artificial Sequence
Probe 177gccatcttta aaatacatt 1917819DNAArtificial
SequenceDescription of Artificial Sequence Probe 178agggtatttt
tacatccct 1917920DNAArtificial SequenceDescription of Artificial
Sequence Probe 179agggtatttt tatatccctc 2018017DNAArtificial
SequenceDescription of Artificial Sequence Probe 180tctggtacct
ggaccaa 1718119DNAArtificial SequenceDescription of Artificial
Sequence Probe 181aatctggtac ttggaccaa 1918215DNAArtificial
SequenceDescription of Artificial Sequence Probe 182tgaacctcga
acaat 1518317DNAArtificial SequenceDescription of Artificial
Sequence Probe 183ttgaacctca aacaatt 1718414DNAArtificial
SequenceDescription of Artificial Sequence Probe 184ctggtgatgg atcc
1418514DNAArtificial SequenceDescription of Artificial Sequence
Probe 185ctggtgatga atcc 1418613DNAArtificial SequenceDescription
of Artificial Sequence Probe 186caagcagttg ggc 1318713DNAArtificial
SequenceDescription of Artificial Sequence Probe 187caagcacttg ggc
1318816DNAArtificial SequenceDescription of Artificial Sequence
Probe 188gcaaatacat ctccct 1618916DNAArtificial SequenceDescription
of Artificial Sequence Probe 189gcaaatacgt ctccct
1619013DNAArtificial SequenceDescription of Artificial Sequence
Probe 190ccttgcccgc ctc 1319113DNAArtificial SequenceDescription of
Artificial Sequence Probe 191cttgcccacc tcc 1319212DNAArtificial
SequenceDescription of Artificial Sequence Probe 192cctgcagacc cc
1219314DNAArtificial SequenceDescription of Artificial Sequence
Probe 193accccaaaac cgga 1419414DNAArtificial SequenceDescription
of Artificial Sequence Probe 194accccaaagc cgga
1419513DNAArtificial SequenceDescription of Artificial Sequence
Probe 195agcccagata gct 1319613DNAArtificial SequenceDescription of
Artificial Sequence Probe 196agcccagaca gct 1319714DNAArtificial
SequenceDescription of Artificial Sequence Probe 197aaatcggctc ccgc
1419817DNAArtificial SequenceDescription of Artificial Sequence
Probe 198aaatcgactc ccgcaga 1719916DNAArtificial
SequenceDescription of Artificial Sequence Probe 199cagtgaagaa
agtgtc 1620015DNAArtificial SequenceDescription of Artificial
Sequence Probe 200agtgaagcaa gtgtc 1520121DNAArtificial
SequenceDescription of Artificial Sequence Probe 201tcacagtttt
cacttcagtg t 2120221DNAArtificial SequenceDescription of Artificial
Sequence Probe 202tcacagtttt cactttagtg t 2120323DNAArtificial
SequenceDescription of Artificial Sequence Probe 203ccatctttaa
aatacattta tta 2320422DNAArtificial SequenceDescription of
Artificial Sequence Probe 204catctttaaa atacattttt ta
2220525DNAArtificial SequenceDescription of Artificial Sequence
Oligonucleotide 205taataataat aaaaaatgta tttta 25
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References