U.S. patent application number 17/006360 was filed with the patent office on 2020-12-31 for pathogenicity scoring system for human clinical genetics.
This patent application is currently assigned to Athena Diagnostics, Inc.. The applicant listed for this patent is Athena Diagnostics, Inc.. Invention is credited to Sat DEV BATISH, Corey BRAASTAD, Christina DIVINCENZO, Felicita DUBOIS, Christopher ELZINGA, Joseph HIGGINS, Jeffery JONES, Izabela KARBASSI, Jennifer LAPIERRE, Glenn MASTON, Michele MCCARTHY, Katelyn MEDEIROS.
Application Number | 20200411134 17/006360 |
Document ID | / |
Family ID | 1000005086729 |
Filed Date | 2020-12-31 |
United States Patent
Application |
20200411134 |
Kind Code |
A1 |
KARBASSI; Izabela ; et
al. |
December 31, 2020 |
PATHOGENICITY SCORING SYSTEM FOR HUMAN CLINICAL GENETICS
Abstract
Provided are methods and systems for determining the clinical
significance of a genetic variant. The methods entail determining,
for the variant, (a) a function score based on known impact of the
variant on a biological function of a cell or protein, (b) a
frequency score based on the frequency of the variant in a
population, (c) a co-occurrence score based on how the variant
co-occurs with a reference variant having known clinical
significance relating to a clinical disease or condition, and (d) a
family segregation score based on how the variant segregates with a
disease or condition in a family; and aggregating, on a computer,
the function score, the frequency score, the co-occurrence score,
the family segregation score to generate a clinical significance
score indicating the clinical significance of the genetic
variant.
Inventors: |
KARBASSI; Izabela; (San Juan
Capistrano, CA) ; ELZINGA; Christopher; (San Juan
Capistrano, CA) ; MASTON; Glenn; (San Juan
Capistrano, CA) ; HIGGINS; Joseph; (San Juan
Capistrano, CA) ; BATISH; Sat DEV; (San Juan
Capistrano, CA) ; DIVINCENZO; Christina; (San Juan
Capistrano, CA) ; MCCARTHY; Michele; (San Juan
Capistrano, CA) ; LAPIERRE; Jennifer; (San Juan
Capistrano, CA) ; DUBOIS; Felicita; (San Juan
Capistrano, CA) ; MEDEIROS; Katelyn; (San Juan
Capistrano, CA) ; JONES; Jeffery; (San Juan
Capistrano, CA) ; BRAASTAD; Corey; (San Juan
Capistrano, CA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Athena Diagnostics, Inc. |
Marlborough |
MA |
US |
|
|
Assignee: |
Athena Diagnostics, Inc.
Marlborough
MA
|
Family ID: |
1000005086729 |
Appl. No.: |
17/006360 |
Filed: |
August 28, 2020 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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15028190 |
Apr 8, 2016 |
10762981 |
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PCT/US14/61730 |
Oct 22, 2014 |
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17006360 |
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61894380 |
Oct 22, 2013 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G16B 20/00 20190201 |
International
Class: |
G16B 20/00 20060101
G16B020/00 |
Claims
1-23. (canceled)
24. A method, comprising, receiving, by a computing device, a
plurality of scores associated with a genetic variant; aggregating,
by the computing device, the plurality of scores to generate a
clinical significance score indicating a clinical significance of
the genetic variant; and determining that the generated clinical
significance score for the variant is above a threshold; and
wherein an individual identified as having the variant or an
immediate blood relative of the individual identified as having the
variant is tested for a condition associated with the biological
function of the cell or protein, responsive to the determination
that the generated clinical significance score for the variant is
above the threshold.
25. The method of claim 24, wherein aggregating the plurality of
scores further comprises summing up, by the computing device, the
plurality of scores with pre-determined weights.
26. The method of claim 24, wherein aggregating the plurality of
scores further comprises retrieving, by the computing device, a
value for the clinical significance score from a leaf node of a
decision tree, wherein each score of the plurality of scores is
associated with an internal node of the decision tree.
27. The method of claim 26, wherein a first value of a first score
of the plurality of scores is associated with a first branch of the
internal node of the decision tree corresponding to the first
score.
28. The method of claim 27, wherein the internal node of the
decision tree corresponding to the first score has at least three
branches corresponding to distinct values of the first score.
29. The method of claim 26, wherein the decision tree comprises at
least one leaf node at a first layer of the decision tree, and at
least one leaf node at a second, higher layer of the decision
tree.
30. The method of claim 24, further comprising, responsive to the
generated clinical significance score being above a first threshold
and below a second threshold, aggregating a second plurality of
scores to generate a second clinical significance score; wherein at
least one of the second plurality of scores is based on new data
accumulated after generating the clinical significance score.
31. The method of claim 24, further comprising excluding a second
variant from an output report, responsive to a generated clinical
significance score of the second variant being below the
threshold.
32. The method of claim 24, wherein the plurality of scores
comprise at least two of a function score based on known or
projected impact of the variant on a biological function of a cell
or protein; a frequency score based on the frequency of the variant
in a population; a co-occurrence score based on how the variant
co-occurs with a reference variant having known clinical
significance relating to a clinical disease or condition; a family
segregation score based on how the variant segregates with a
disease or condition in a family; and a minor evidence score based
on information from at least one functional impact prediction
algorithm, whether the variant occurs within a critical protein
domain, whether the variant would alter a post-translational
modification, whether other known pathogenic variants occur within
the same codon, and whether the variant is known to occur in at
least one patient of a disease or condition.
33. The method of claim 32, further comprising retrieving, by the
computing device from a database comprising a plurality of variants
and associated patients, co-occurrence or family segregation data
for the variant.
34. A system, comprising: a computing device comprising a processor
configured to: receive a plurality of scores associated with a
genetic variant, aggregate the plurality of scores to generate a
clinical significance score indicating a clinical significance of
the genetic variant, and determine that the generated clinical
significance score for the variant is above a threshold; and
wherein an individual identified as having the variant or an
immediate blood relative of the individual identified as having the
variant is tested for a condition associated with the biological
function of the cell or protein, responsive to the determination
that the generated clinical significance score for the variant is
above the threshold.
35. The system of claim 34, wherein the computing device is further
configured to sum up the plurality of scores with pre-determined
weights.
36. The system of claim 34, wherein the computing device is further
configured to retrieve a value for the clinical significance score
from a leaf node of a decision tree, wherein each score of the
plurality of scores is associated with an internal node of the
decision tree.
37. The system of claim 36, wherein a first value of a first score
of the plurality of scores is associated with a first branch of the
internal node of the decision tree corresponding to the first
score.
38. The system of claim 37, wherein the internal node of the
decision tree corresponding to the first score has at least three
branches corresponding to distinct values of the first score.
39. The system of claim 36, wherein the decision tree comprises at
least one leaf node at a first layer of the decision tree, and at
least one leaf node at a second, higher layer of the decision
tree.
40. The system of claim 34, wherein the computing device is further
configured to, responsive to the generated clinical significance
score being above a first threshold and below a second threshold,
aggregate a second plurality of scores to generate a second
clinical significance score; wherein at least one of the second
plurality of scores is based on new data accumulated after
generating the clinical significance score.
41. The system of claim 34, wherein the computing device is further
configured to exclude a second variant from an output report,
responsive to a generated clinical significance score of the second
variant being below the threshold.
42. The system of claim 34, wherein the plurality of scores
comprise at least two of a function score based on known or
projected impact of the variant on a biological function of a cell
or protein; a frequency score based on the frequency of the variant
in a population; a co-occurrence score based on how the variant
co-occurs with a reference variant having known clinical
significance relating to a clinical disease or condition; a family
segregation score based on how the variant segregates with a
disease or condition in a family; and a minor evidence score based
on information from at least one functional impact prediction
algorithm, whether the variant occurs within a critical protein
domain, whether the variant would alter a post-translational
modification, whether other known pathogenic variants occur within
the same codon, and whether the variant is known to occur in at
least one patient of a disease or condition.
43. The system of claim 42, wherein the computing device is further
configured to retrieve, from a database comprising a plurality of
variants and associated patients, co-occurrence or family
segregation data for the variant.
Description
BACKGROUND
[0001] When a DNA sequence variant is identified in a clinical lab,
its clinical significance needs be evaluated and appropriately
reported. Currently, a static mutation list is assembled at time of
discovery of the variant, which is not easy to update in real time.
Therefore, variants of unknown clinical significance (VUS) are not
routinely evaluated for pathogenicity.
SUMMARY
[0002] The present disclosure provides a custom database for the
collection and curation of variant-related data. The database not
only includes curation of the variants, such as the variants'
potential biological functions, but also includes information about
individuals having the variant. Such information includes, without
limitation, known or projected impact of the variant on a
biological function of a cell or protein, the frequency of the
variant in a population, co-occurrence of the variant with a
reference variant relating to a clinical disease or condition,
and/or occurrences of the variant in a family and segregation
between the variant and a disease or condition. By including such
information in an integrated database, the present technology is
able to determine the likely clinical significance of a variant of
unknown clinical significance (VUS).
[0003] Further, a scoring technique is provided for the
reproducible assessment of the clinical significance of a VUS using
information retrievable from the database. Also provided are custom
tools to create standardized or customizable reports for such
VUS.
[0004] Accordingly, disclosed herein, in some embodiments, is a
method for determining the clinical significance of a genetic
variant, comprising determining, for the variant, (a) a function
score based on known impact of the variant on a biological function
of a cell or protein, (b) a frequency score based on the frequency
of the variant in a population, (c) a co-occurrence score based on
how the variant co-occurs with a reference variant having known
clinical significance relating to a clinical disease or condition,
and (d) a family segregation score based on how the variant
segregates with a disease or condition in a family; and (e)
optionally, a minor evidence score based on information from at
least one functional impact prediction algorithm, whether the
variant occurs within a critical protein domain, whether the
variant would alter a post-translational modification, whether
other known pathogenic variants occur within the same codon, and
whether the variant is known to occur in at least one patient of a
disease or condition; and aggregating, on a computer, the function
score, the frequency score, the co-occurrence score, and the family
segregation score to generate a clinical significance score
indicating the clinical significance of the genetic variant. In
some embodiments, the method further comprises retrieving, from a
database hosted on a computer server, the known or projected impact
of the variant on a biological function of a cell or protein, the
frequency of the variant in a population, co-occurrence of the
variant with the reference variant relating to a clinical disease
or condition, and occurrences of the variant in a family and
segregation between the variant and a disease or condition. In some
embodiments, the aggregation comprises summing up the function
score, the frequency score, the co-occurrence score, the family
segregation score, and the minor evidence score with pre-determined
weights. In some embodiments, the aggregation comprises taking the
function score, the frequency score, the co-occurrence score, the
family segregation score, and the minor evidence score as inputs in
a decision tree. In some embodiments, the method further comprises
determining a curated clinical significance score, wherein the
aggregation further takes the curated clinical significance score
as an input to generate the clinical significance score. In some
embodiments, the known or projected impact comprises protein
activity change or protein expression level change, and wherein a
higher impact leads to a higher clinical significance score. In
some embodiments, the protein expression level change is caused by
a splicing or translation efficiency change due to the genetic
variant. In some embodiments, the frequency score comprises
frequency of the variant in normal population, and wherein higher
frequency leads to a lower clinical significance score. In some
embodiments, a higher co-occurrence with the reference variant
relating to a clinical disease or condition leads to a lower
clinical significance score. In some embodiments, a higher
segregation of the variant with a clinical disease or condition in
the family leads to a higher clinical significance score. In some
embodiments, the function impact prediction algorithm is selected
from SIFT (Sorting Intolerant From Tolerant) and PolyPhen
(Polymorphism Phenotyping). In some embodiments, the minor evidence
score is based on information from at least two functional impact
prediction algorithms.
[0005] Disclosed herein, in some embodiments, is a method for
identifying a potential therapeutic target for treating a disease
or condition, comprising querying, with a computer, a database
comprising genetic variants of a plurality of individuals, each
individual annotated with clinically diagnosed diseases or
conditions, wherein at least one variant has unknown clinical
significance and at least one reference variant has known clinical
significance, and wherein for each variant, the database comprises
known impact of the variant on a biological function of a cell or
protein, the frequency of the variant in a population,
co-occurrence of the variant with the reference variant relating to
a clinical disease or condition, and occurrences of the variant in
a family and segregation between the variant and a disease or
condition; determining a clinical significance score with a method
disclosed herein, for at least one variant in the database; and
correlating one of the variants to a disease or condition present
in the database, thereby identifying the variant as a potential
therapeutic target. In some embodiments, a minor evidence score is
included in determining the clinical significance score.
[0006] Disclosed herein, in some embodiments, is a method for
predicting whether an individual is likely to suffer from a disease
or condition, comprising querying, with a computer, a database
comprising genetic variants of a plurality of individuals, each
individual annotated with clinically diagnosed diseases or
conditions, wherein at least one variant has unknown clinical
significance and at least one reference variant has known clinical
significance, and wherein for each variant, the database comprises
known impact of the variant on a biological function of a cell or
protein, the frequency of the variant in a population,
co-occurrence of the variant with the reference variant relating to
a clinical disease or condition, and occurrences of the variant in
a family and segregation between the variant and a disease or
condition; determining a clinical significance score with a method
disclosed herein, for at least one variant in the database;
correlating one of the variants to a disease or condition present
in the database; and identifying an individual possessing the
variant as to likely to suffer from the disease or condition. In
some embodiments, a minor evidence score is included in determining
the clinical significance score.
[0007] Further, disclosed herein, in some embodiments, is a system
for determining the clinical significance of a genetic variant,
comprising a computer comprising: (a) a module configured to
generate a function score based on known impact of the variant on a
biological function of a cell or protein. (b) a module configured
to generate a frequency score based on the frequency of the variant
in a population, (c) a module configured to generate a
co-occurrence score based on how the variant co-occurs with a
reference variant having known clinical significance relating to a
clinical disease or condition, (d) a module configured to generate
a family segregation score based on how the variant segregates with
a disease or condition in a family, (e) optionally a module
configured to generate a minor evidence score based on information
from at least one functional impact prediction algorithm, whether
the variant occurs within a critical protein domain, whether the
variant would alter a post-translational modification, whether
other known pathogenic variants occur within the same codon, and
whether the variant is known to occur in at least one patient of a
disease or condition. In some embodiments, the system further
comprises a scoring module. In some embodiments, the system further
comprises a communications interface configured to receive data
inputs. In some embodiments, the system further comprises a display
module configured to display a visual representation of the
clinical significance of the genetic variant. In some embodiments,
the display module is housed within a user device connected to the
computer over a network.
[0008] Disclosed herein, in some embodiments, is a
computer-implemented method for analyzing the clinical significance
of a genetic variant, comprising: (a) processing a search query
related to the genetic variant, wherein the search query comprises
retrieving information from a database comprising genetic variants
from a plurality of individuals, each individual annotated with
clinically diagnosed diseases or conditions, wherein at least one
variant has unknown clinical significance and at least one
reference variant has known clinical significance, and wherein for
each variant, the database comprises known or projected impact of
the variant on a biological function of a cell or protein, the
frequency of the variant in a population, co-occurrence of the
variant with the reference variant relating to a clinical disease
or condition, and occurrences of the variant in a family and
segregation between the variant and a disease or condition,
information from at least one functional impact prediction
algorithm, information regarding whether the variant occurs within
a critical protein domain, information regarding whether the
variant would alter a post-translational modification, information
regarding whether other known pathogenic variants occur within the
same codon, and information regarding whether the variant is known
to occur in at least one patient of a disease or condition, (b)
retrieving results of the search query, (c) inferring measured
scores based on the results of the search query, (d) aggregating
the measured scores, and (e) rendering a visual representation of
the aggregation of the measured scores. In some embodiments, the
method further comprises sending the visual representation over a
network to a user device.
[0009] Disclosed herein, in some embodiments, is a visual
representation of the clinical significance of a genetic variant,
wherein the visual representation displays the results of a method
as disclosed herein.
[0010] Disclosed herein, in some embodiments, is an article of
manufacture, comprising a non-transitory computer-readable medium
comprising a non-transitory computer-readable medium comprising
computer readable instructions which when executed by a computer,
cause the computer to perform a method disclosed herein.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIG. 1 illustrates an exemplary process for determining a
clinical significance score for a variant of unknown clinical
significance (VUS).
[0012] FIG. 2 provides an example for determining a clinical
significance score for a VUS that causes change of at least an
amino acid in a protein sequence.
[0013] FIG. 3 provides an example for determining a clinical
significance score for a VUS that does not change the amino acid
sequence of a protein.
[0014] FIG. 4 exemplifies the content of a custom database
according to the present disclosure.
[0015] FIG. 5 illustrates the percent of variants where prediction
matches classification from SIFT (Sorting Intolerant From Tolerant)
and PolyPhen (Polymorphism phenotyping).
[0016] FIG. 6 illustrates the correlation between functional data
(with damaging function) of a variant and the clinical significance
score determined using the present technology.
[0017] FIG. 7 illustrates the correlation between functional data
(without damaging function) of a variant and the clinical
significance score determined using the present technology.
[0018] FIG. 8 illustrates how, upon receipt of additional
information from the literature, only a small number of variants
had their clinical significance score shifted up when their initial
clinical significance score was determined to be benign, and only a
small number of variants had their score shift down when their
initial clinical significance score was determined to be
pathogenic.
DETAILED DESCRIPTION
[0019] Provided are methods and systems of assessing and assigning
pathogenicity scores to variants and curating mutation lists. Prior
to the present disclosure, paper mutation lists were used in the
clinical operation which were much less frequently updated after
product launch. Additionally, there was little consistency between
individuals that assembled the mutation list. As such, a variant
assessed might be deemed pathogenic by one, but if assessed by
another might be considered a variant of unknown significance.
Finally, variants of unknown significance were listed on reports,
but offered the physician no guidance as to potential patient
impact.
[0020] All numerical designations, e.g., pH, temperature, time,
concentration, and molecular weight, including ranges, are
approximations which are varied (+) or (-) by increments of 0.1, 5%
or 10%. It is to be understood, although not always explicitly
stated that all numerical designations are preceded by the term
"about". The term "about" also includes the exact value "X" in
addition to minor increments of "X" such as "X+0.1" or "X-0.1." It
also is to be understood, although not always explicitly stated,
that the reagents described herein are merely exemplary and that
equivalents of such are known in the art.
[0021] The term "variant" or "genetic variant" refers to an
alternative form of a gene, a genomic sequence, or portions
thereof. A variant can also be referred to on a protein or RNA
level, corresponding to the genomic change. In some embodiments, a
variant causes changes of amino acids in a protein sequence, but
can also impact the function or activity of a protein or cell
otherwise, such as in terms of RNA splicing, translation, or on
other levels of transcription or translation regulation.
[0022] A "reference variant" or "mutation" with known clinical
significance refers to a variant on which a functional relationship
between the variant and a disease or condition has been
investigated and validated with supporting data. Such validation,
however, does not require regulatory approval or consensus in the
clinical community.
[0023] LOD stands for "logarithm of the odds." In the field of
genetics, the LOD score is a statistical estimate of whether two
genes, or a gene and a disease gene, are likely to be located near
each other on a chromosome. A LOD score of 3 or higher is generally
understood to mean that the odds are a thousand to one that two
genes are linked, and therefore inherited together.
Methods of Determining Pathogenicity of a Variant
[0024] One embodiment of the present disclosure provides a method
for determining the clinical significance of a genetic variant. The
method entails, in one aspect, determining, for the variant, (a) a
function score based on known impact of the variant on a biological
function of a cell or protein, (b) a frequency score based on the
frequency of the variant in a population, (c) a co-occurrence score
based on how the variant co-occurs with a reference variant having
known clinical significance relating to a clinical disease or
condition, and/or (d) a family segregation score based on how the
variant segregates with a disease or condition in a family and/or
e) a minor evidence score, based on information which can include,
but is not limited to, information from at least one functional
impact prediction algorithm, whether the variant occurs within a
critical protein domain, whether the variant would alter a
post-translational modification, whether other known pathogenic
variants occur within the same codon, and whether the variant is
known to occur in at least one patient of a disease or condition;
and aggregating, on a computer, the function score, the frequency
score, the co-occurrence score, and/or the family segregation score
to generate a clinical significance score indicating the clinical
significance of the genetic variant. In some embodiments,
calculated of at least one of the scores is accomplished by Chi
Squared Hypothesis testing.
[0025] FIG. 1 illustrates such a method. For a variant of unknown
clinical significance (VUS), a starting score of 4 is given; a
score of 7 indicates strong clinical significance and 1 indicates
weak clinical significance.
[0026] In one optional step, a curated clinical significance score
is given to the VUS, which score can be provided during curation of
the VUS in a database. Such curation can be based on a curator's
understanding of the gene function or on experimental
evidences.
[0027] FIG. 2 illustrates a process for a variant that causes an
amino acid substitution in a protein.
[0028] FIG. 3, on the other hand, illustrates a process for a
variant that does not cause amino acid substitution in a protein,
but instead may impact protein or cell function through splicing or
translation regulation.
[0029] In one embodiment, a variant database (as illustrated in
FIG. 4) is provided that includes information regarding known or
projected impact of a variant on a biological function of a cell or
protein, the frequency of the variant in a population,
co-occurrence of the variant with a reference variant relating to a
clinical disease or condition, and/or occurrences of the variant in
a family and segregation between the variant and a disease or
condition.
[0030] In some aspects, the disclosed method includes generation of
at least two, three, four, or five of the scores selected from the
function score, the frequency score, the co-occurrence score, the
family segregation score, the minor evidence score and/or the
curated clinical significance score. In some aspects, at least the
co-occurrence score, the family segregation score are generated. In
some aspects, the function score is also generated, or the
frequency score is also generated.
[0031] Once the required scores are generated, they can be
aggregated to obtain a clinical significance score. In one
embodiment, the aggregation includes summing up the function score,
the frequency score, the co-occurrence score, and the family
segregation score with pre-determined weights. In one embodiment,
the aggregation includes taking the function score, the frequency
score, the co-occurrence score, and the family segregation score as
inputs in the execution of a decision tree. FIG. 2-3 illustrate
such aggregation methods.
[0032] In some embodiments, aggregation to obtain a clinical
significance score comprises assigning the calculated scores a
pre-determined weight. In some embodiments, the predetermined
weight assigned to a score is a positive or negative numerical
value. In some embodiments, the predetermined weight assigned to a
score is a positive or negative integer value. In some embodiments,
the predetermined weight assigned to a score is zero.
Function Score
[0033] In some aspects, a function score is determined based on
known or projected impact of the variant on a biological function
of a cell or protein.
[0034] For a VUS that causes amino acid changes, the functional
impact can be determined or predicted based on the amino acid
sequence change. Methods are known in the art to make such
determination and prediction.
[0035] In some embodiments, determining the function score of a
variant comprises determining whether the variant is damaging to
protein function. In some embodiments, determining the function
score of a variant comprises determining whether a variant has no
impact on protein function.
[0036] It is contemplated that, in such aspects, the known or
projected impact comprises protein activity change or protein
expression level change, and wherein a higher impact leads to a
higher clinical significance score. In some aspects, the protein
expression level change is caused by a splicing or translation
efficiency change due to the genetic variant.
[0037] In some embodiments, the impact on protein function is
directly relevant to the molecular basis of a disease.
[0038] In some embodiments, determination of a function score
comprises analysis of all functions of a protein that are relevant
to a disease.
Frequency Score
[0039] Another score that can be generated in this process is a
frequency score based on the frequency of the variant in a
population.
[0040] In some aspects, the frequency score comprises frequency of
the variant in normal population, and wherein higher frequency
leads to a lower clinical significance score.
[0041] It is contemplated that a variant that is more frequently
present in normal population, a population without disease or
without a particular disease of concern, is less likely to have
clinical significance.
[0042] In some embodiments, determining the frequency score
comprises considering whether the variant frequency in the normal
population is greater than ten times higher than the disease allele
frequency. In some embodiments, determining the frequency score
comprises considering whether the variant frequency in the normal
population is greater than two times, five times, twenty times,
twenty five times, fifty times, or one hundred times higher than
the disease allele frequency.
[0043] In some embodiments, determining the frequency score
comprises determining whether the variant frequency in the normal
population is between 3 times and 10 times above disease allele
frequency. In some embodiments, determining the frequency score
comprises determining whether the variant frequency is equal up to
3 times higher than the disease allele frequency.
Co-Occurrence Score
[0044] Yet another score that can be generated in this process is a
co-occurrence score based on how the variant co-occurs with a
reference variant having known clinical significance relating to a
clinical disease or condition.
[0045] In some aspects, a higher co-occurrence with the reference
variant relating to a clinical disease or condition leads to a
lower clinical significance score.
[0046] In some embodiments, co-occurrence of certain
clinically-relevant results (especially otherwise positive results)
with the reference variant relating to a clinical disease or
condition leads to a lower clinical significance score.
[0047] In some aspects, the co-occurrence score is obtained by
comparing the occurrence of the variant to one, two, three or even
more reference variants that correlate with the variant in terms of
presence in patients, in particular among patients having the same
diseases or conditions. In some aspects, at least one of such
reference variants have known clinical significance. For reference
variants without known clinical significance, the presently
disclosed method can be used to predict its clinical
significance.
[0048] In some embodiments, determining the co-occurrence score
comprises determining whether a nonsynonymous change co-occurs with
an otherwise positive result in a single case.
[0049] In some embodiments, determining the co-occurrence score
comprises determining whether a variant co-occurs with a positive
variant in multiple cases.
[0050] In some embodiments, determining the co-occurrence score
comprises determining whether a variant in a recessive gene
co-occurs with one additional known pathogenic variant in multiple
cases. In some embodiments, in making such a determination,
co-occurrence must occur in at least 3 cases.
[0051] In some embodiments, co-occurrence must occur in a
statistically significant portion of patients for the variant to be
considered more likely to be pathogenic.
[0052] In some embodiments, calculation of a co-occurrence score is
based on how the variant co-occurs with a combination of reference
variants, in the case of recessive diseases or conditions.
[0053] In some embodiments, Chi Squared Hypothesis testing is used
to determine the co-occurrence score.
Family Segregation Score
[0054] Still another score that can be generated in this process is
a family segregation score based on how the variant segregates with
a disease or condition in a family.
[0055] In some aspects, a higher segregation of the variant with a
clinical disease or condition in the family leads to a higher
clinical significance score.
[0056] Both the co-occurrence score and the family segregation
score cannot be obtained from a single variant or a single patient,
and require a database that integrate variants and patients. This
highlights an additional advantage of the present disclosure, which
also provides a database of such integrated information.
[0057] In some embodiments, determining the family segregation
score includes determination of a LOD score. In some embodiments,
determining the family segregation score comprises determining
whether a LOD score is over 3.0. In some embodiments, determining
the family segregation score comprises determining whether a LOD
score is over 2.0 but under 3.0. In some embodiments, determining
the family segregation score comprises determining whether a LOD
score is over 1.0, but under 2.0. In some embodiments, determining
the family segregation score comprises determining whether a LOD
score is above -1.0, but above -2.0. In some embodiments,
determining the family segregation score comprises determining
whether a LOD score less than -2.0.
[0058] In some embodiments, determining the family segregation
score comprises determining whether a variant is de novo, wherein
paternity is not confirmed. In some embodiments, determining the
family segregation sore comprises determining whether a variant is
de novo, wherein paternity is confirmed. In some embodiments,
determining the family segregation sore comprises determining
whether there are two cases where a variant is de novo, wherein
paternity is not confirmed. In some embodiments, determining the
family segregation sore comprises determining whether a variant is
de novo in two cases, wherein paternity is confirmed. In some
embodiments, determining the family segregation score comprises
determining whether a variant is de novo in at least three cases,
wherein paternity is not confirmed.
[0059] In some embodiments, Chi Squared Hypothesis testing is used
to determine the family segregation score.
Minor Evidence Score
[0060] In some embodiments, a minor evidence score is utilized in
determining the clinical significant of a genetic variant.
[0061] In some embodiments, the minor evidence score includes
information based on prediction algorithms, knowledge regarding the
relevant protein domain, whether or not the variant has been
reported in a patient, whether other known pathogenic variants
occur at the same codon, and splicing predictions.
[0062] In some embodiments, the function impact prediction
algorithm is selected from SIFT (Sorting Intolerant From Tolerant)
and PolyPhen (Polymorphism Phenotyping).
[0063] In some embodiments, a functional impact prediction
algorithm analyzes a variant for potential effect on
post-translational modifications of an encoded protein. An example
of such an algorithm can be found online at
http://www.cbs.dtu.dk/services/
[0064] In some embodiments, the minor evidence score is based on
information from at least two functional impact prediction
algorithms.
Additional Methods
[0065] Also provided, in one embodiment, is a method for
identifying a potential therapeutic target for treating a disease
or condition. In one embodiment, the method entails querying, with
a computer, a database comprising genetic variants of a plurality
of individuals, each individual annotated with clinically diagnosed
diseases or conditions, wherein at least one variant has unknown
clinical significance and at least one reference variant has known
clinical significance, and wherein for each variant, the database
comprises known or projected impact of the variant on a biological
function of a cell or protein, the frequency of the variant in a
population, co-occurrence of the variant with the reference variant
relating to a clinical disease or condition, and occurrences of the
variant in a family and segregation between the variant and a
disease or condition; determining a clinical significance score
with a method of the present disclosure, for at least one variant
in the database; and correlating one of the variants to a disease
or condition present in the database, thereby identifying the
variant as a potential therapeutic target. In some embodiments, a
minor evidence score is included in determining the clinical
significance score.
[0066] Such a method demonstrates the technical advancement
provided by the present technology, both in terms of its ability to
predict the clinical significance of a particular variant and
identify a variant, among many variants in a variant database, as a
potential therapeutic target. Once the target is identified,
additional pharmaceutical research can be carried out to identify
pharmaceutical agents to target (e.g., activate, deactivate, or
alter) the potential therapeutic target, to achieve a therapeutic
purpose.
[0067] Also provided, in yet another embodiment, is a method for
predicting whether an individual is likely to suffer from a disease
or condition. The method entails, in some aspects, querying, with a
computer, a database comprising genetic variants of a plurality of
individuals, each individual annotated with clinically diagnosed
diseases or conditions, wherein at least one variant has unknown
clinical significance, the database comprises known or projected
impact of the variant on a biological function of a cell or
protein, the frequency of the variant in a population,
co-occurrence of the variant with the reference variant relating to
a clinical disease or condition, and occurrences of the variant in
a family and segregation between the variant and a disease or
condition; determining a clinical significance score with a method
of the present disclosure, for at least one variant in the
database; correlating one of the variants to a disease or condition
present in the database; and identifying an individual possessing
the variant as to likely to suffer from the disease or condition.
In some embodiments, the database comprises at least one reference
variant having known clinical significance. In some embodiments, a
minor evidence score is included in determining the clinical
significance score. The method can also include generating a report
including relevant scores and prediction methods and processes.
Computer Implementation
[0068] The methodology described here can be implemented on a
computer system or network.
[0069] Accordingly, disclosed herein, in some embodiments, is a
system for determining the clinical significance of a genetic
variant, comprising a computer comprising: (a) a module configured
to generate a function score based on known impact of the variant
on a biological function of a cell or protein. (b) a module
configured to generate a frequency score based on the frequency of
the variant in a population, (c) a module configured to generate a
co-occurrence score based on how the variant co-occurs with a
reference variant or variants having known clinical significance
relating to a clinical disease or condition, (d) a module
configured to generate a family segregation score based on how the
variant segregates with a disease or condition in a family, (c)
optionally a module configured to generate a minor evidence score
based on information from at least one functional impact prediction
algorithm, whether the variant occurs within a critical protein
domain, whether the variant would alter a post-translational
modification, whether other known pathogenic variants occur within
the same codon, and whether the variant is known to occur in at
least one patient of a disease or condition. In some embodiments,
the system further comprises a scoring module. In some embodiments,
the system further comprises a communications interface configured
to receive data inputs. In some embodiments, the system further
comprises a display module configured to display a visual
representation of the clinical significance of the genetic variant.
In some embodiments, the display module is housed within a user
device connected to the computer over a network. In some
embodiments, a module configured to generate a co-occurrence score
is based on how the variant co-occurs with a combination of
reference variants, in the case of recessive diseases or
conditions. In some embodiments, the computer comprises at least
one module configured to perform Chi Squared Hypothesis Testing. In
some embodiments, the module configured to generate a co-occurrence
score is configured to perform Chi Squared Hypothesis Testing. In
some embodiments, the module configured to generate a family
segregation score is configured to perform Chi Squared Hypothesis
Testing. In some embodiments, one or more of the modules is
configured to query a database to search for relevant published
literature. In some embodiments, one or more of the modules is
configured to query a gene-specific Leiden Open Variation Database
(LOVD). In some embodiments, one or more of the modules is
configured to query an independent database related to the gene of
interest.
[0070] Further disclosed herein, in some embodiments, is a
computer-implemented method for analyzing the clinical significance
of a genetic variant, comprising: (a) processing a search query
related to the genetic variant, wherein the search query comprises
retrieving information from a database comprising genetic variants
from a plurality of individuals, each individual annotated with
clinically diagnosed diseases or conditions, wherein at least one
variant has unknown clinical significance, and wherein for each
variant, the database comprises known or projected impact of the
variant on a biological function of a cell or protein, the
frequency of the variant in a population, co-occurrence of the
variant with the reference variant relating to a clinical disease
or condition, and occurrences of the variant in a family and
segregation between the variant and a disease or condition,
information from at least one functional impact prediction
algorithm, information regarding whether the variant occurs within
a critical protein domain, information regarding whether the
variant would alter a post-translational modification, information
regarding whether other known pathogenic variants occur within the
same codon, and information regarding whether the variant is known
to occur in at least one patient of a disease or condition, (b)
retrieving results of the search query, (c) inferring measured
scores based on the results of the search query, (d) aggregating
the measured scores, and (e) rendering a visual representation of
the aggregation of the measured scores. In some embodiments, the
database comprises information regarding at least one reference
variant having known clinical significance. In some embodiments,
the method further comprises sending the visual representation over
a network to a user device.
[0071] In some embodiments, a database disclosed herein comprises
information relevant to calculating one or more of the function
score, the frequency score, the co-occurrence score, the family
segregation score, and the minor evidence score. In some
embodiments, the database comprises published literature relevant
to a particular variant or gene. In some embodiments, the database
is a gene-specific Leiden Open Variation Database (LOVD). In some
embodiments, the database is an independent database related to the
gene or variant of interest. In some embodiments, the database
disclosed herein is housed on a SQL server. In some embodiments,
the database is housed on Microsoft Access software.
[0072] In some embodiments, the database is housed on a spreadsheet
software. In some embodiments, the spreadsheet software comprises
calculation tools and a macro programming language. In some
embodiments, the macro programming language is Visual Basic for
Applications.
[0073] Also disclosed herein, in some embodiments, is an article of
manufacture, comprising a non-transitory computer-readable medium
comprising a non-transitory computer-readable medium comprising
computer readable instructions which when executed by a computer,
cause the computer to perform a method disclosed herein. In some
embodiments, disclosed herein is an article of manufacture
comprising a non-transitory computer readable storage medium to
tangibly store instructions for performing the methods disclosed
herein, which, when executed, cause one or more computers in a
network of computer to: receive a request for displaying a report
on a portable computing device, display a report displaying a
visible representation of the clinical significance of a genetic
variant.
[0074] In some embodiments, a suitable computer system can include
at least a processor and memory; optionally, a computer-readable
medium that stores computer code for execution by the processor.
Once the code is executed, the computer system carries out the
described methodology.
[0075] In this regard, a "processor" is an electronic circuit that
can execute computer programs. Suitable processors are exemplified
by, but are not limited to, central processing units,
microprocessors, graphics processing units, physics processing
units, digital signal processors, network processors, front end
processors, coprocessors, data processors and audio processors. The
term "memory" connotes an electrical device that stores data for
retrieval. In one aspect, therefore, a suitable memory is a
computer unit that preserves data and assists computation. More
generally, suitable methods and devices for providing the requisite
network data transmission are known.
[0076] Also contemplated is a non-transitory computer readable
medium that includes executable code for carrying out the described
methodology. In certain embodiments, the medium further contains
data or databases needed for such methodology.
[0077] Information stored in or maintained in the one or more
databases may be provided in conformance with a database system
format such as, but not limited to, the Structured Query Language
(SQL) format. Database query and access instructions, for example,
in the form of one or more scripts, may be used which, when
executed by a processor, serve to access, store and retrieve data
maintained in the one or more databases according to the
instructions contained in the script.
[0078] The system may comprise application software instructions
which may implement a user interface portion for generating
interactive pages or display screens by which a user/participant
may provide data to and receive information from the system and the
database using a human-machine interface. In embodiments,
interactive pages may include user dialog boxes for accepting user
entered information. The human-machine interface may comprise a
Graphical User Interface (GUI) portion for prompting the user to
enter data by providing an interactive dialog box or message box
instructing the user to enter particular data, or to select from
among a multitude of options provided using a pull-down menu. In
embodiments, a user may interact with the system via the graphical
user interface by using a pointing device and/or other data entry
device. The GUI portion may place the output of the system in a
format for presentation to a user via the display. In embodiments,
the GUI may be implemented as a sequence of Java instructions.
[0079] In embodiments of the present invention, the various program
operations as described herein may be provided by the system in
response to the one or more processors executing one or more
sequences of computer-readable instructions contained in main
memory. Such instructions may be read into main memory from another
computer-readable medium. Execution of the sequences of
instructions contained in main memory may cause one or more
processors of the system to perform the process steps described
herein. It should be appreciated that embodiments of the system may
perform fewer or additional processes as compared to those
described herein. As noted, the one or more processors may be
arranged in a multi-processing arrangement. In embodiments,
hard-wired circuitry may be used in place of or in combination with
software instructions to implement the invention. Thus, embodiments
of the invention are not limited to any specific combination of
hardware circuitry and software.
[0080] Embodiments can include program products comprising
non-transitory machine-readable storage media for carrying or
having machine-executable instructions or data structures stored
thereon. Such machine-readable media may be any available media
that may be accessed by a general purpose or special purpose
computer or other machine with a processor. By way of example, such
machine-readable storage media may comprise RAM, ROM, EPROM,
EEPROM, CD-ROM or other optical disk storage, magnetic disk storage
or other magnetic storage devices, or any other medium which may be
used to store desired program code in the form of
machine-executable instructions or data structures and which may be
accessed by a general purpose or special purpose computer or other
machine with a processor. Combinations of the above also come
within the scope of "machine-readable media." Machine-executable
instructions comprise, for example, instructions and data that
cause a general purpose computer, special-purpose computer or
special-purpose processing machine(s) to perform a certain function
or group of functions.
[0081] In another embodiment of the present invention, software is
provided that performs the analysis of the clinical significance of
a variant. When a subject's genomic sequence is obtained, it may be
entered into the software. The software is designed to access a
database as described and perform the analysis of the clinical
significance of a variant, according to the present invention,
outputting the calculated significance score so that a doctor,
genetic counsel, other medical professional, or patient may obtain
the score, and optionally, a report of the score, as disclosed
herein. It is contemplated that the software of the present
invention may be software stored on a local computer, or may
alternatively be server or web-based, allowing for its access from
remote computers.
[0082] The system also comprises a communication interface for
providing one-way, two-way or multi-way data communication with the
network, and/or communication directly with other devices. In
embodiments, the communication interface may comprise a modem, a
transceiver Integrated Services Digital Network (ISDN) card, a WAN
card, an Ethernet interface, or the like, to provide a data
communication connection to a corresponding type of communication
medium. As another example, the communication interface may
comprise a LAN card to provide a data communication connection to a
compatible LAN. Wireless links may also be implemented. In such
wireless links, the communication interface may communicate with a
base station communicatively coupled to a network server. In any
such implementation, the communication interface sends and receives
electrical, electromagnetic, radio, infrared, laser, or optical
signals that carry digital data streams representing various types
of information. Any combination of the above interfaces may also be
implemented.
[0083] In embodiments, the communication interface may be
communicatively coupled to a web server configured in the one or
more processors to generate and output web content that is suitable
for display using a web browser at a computing device. In
embodiments, the server may generate and transmit requested
information through the communication interface to a requesting
terminal via Hypertext Transfer Markup Language (HTML) formatted
pages, eXtensible Markup Language (XML) formatted pages, or the
like, which may be provided as World Wide Web pages that may enable
navigation by hyperlinks. The server program may be used to receive
commands and data from clients' terminals, access and process data
from various sources, and output computer-executable instructions
and data using the network. Interactive pages transmitted and
received using the network may conform to necessary protocols.
[0084] In embodiments, the web server configured in the one or more
processors may correspond to a secure web application server behind
a web server program that a service provider employs to run one or
more web based application programs in a secure fashion. Such a
secure web application server may be configured to execute one or
more web based application programs, respond to commands and data
received from the clients (via a web page supported by the web
server), and provide data and results to the clients. The web
server and the web application server may be implemented using a
single computing platform. Alternatively, it may also be
implemented using multiple separate and distributed computing
platforms.
[0085] Embodiments of the present invention have been described in
the general context of method steps which may be implemented in one
embodiment by a program product including machine-executable
instructions, such as program code, for example in the form of
program modules executed by machines in networked environments.
Generally, program modules include routines, programs, logics,
objects, components, data structures, etc. that perform particular
tasks or implement particular abstract data types.
Machine-executable instructions, associated data structures, and
program modules represent examples of program code for executing
steps of the methods disclosed herein. The particular sequence of
such executable instructions or associated data structures
represent examples of corresponding acts for implementing the
functions described in such steps.
[0086] As previously indicated, embodiments of the present
invention may be practiced in a networked environment using logical
connections to one or more remote computers having processors.
Those skilled in the art will appreciate that such network
computing environments may encompass many types of computers,
including personal computers, hand-held devices, multi-processor
systems, microprocessor-based or programmable consumer electronics,
network PCs, minicomputers, mainframe computers, and so on.
Embodiments of the invention also may be practiced in distributed
and cloud computing environments where tasks are performed by local
and remote processing devices that are linked, by hardwired links,
by wireless links or by a combination of hardwired or wireless
links, through a communications network. In a distributed computing
environment, program modules may be located in both local and
remote memory storage devices.
[0087] In some embodiments, a user device may be any, device, or
machine for processing or displaying data, including by way of
example a programmable processor, a computer (such as a laptop), a
server, a mobile device such as a smart phone or a tablet, a system
on a chip, or multiple ones or combinations of the foregoing. In
some embodiments, the user device may generally include a browser
configured to display webpages.
[0088] Embodiments of the invention have been described in the
general context of method steps which may be implemented in
embodiments by a program product comprising machine-executable
instructions, such as program code, for example in the form of
program modules executed by machines in networked environments.
Generally, program modules include routines, programs, objects,
components, data structures, etc., that perform particular tasks or
implement particular data types. Multi-threaded applications may be
used, for example, based on Java or C++. Machine-executable
instructions, associated data structures, and program modules
represent examples of program code for executing steps of the
methods disclosed herein. The particular sequence of such
executable instructions or associated data structures represent
examples of corresponding acts for implementing the functions
described in such steps.
Reports
[0089] In some embodiments, the methods disclosed herein include
transformation of the relevant scores into a report.
[0090] In some embodiments, the report comprises a visual
representation of the calculated clinical significance score. In
some embodiments, the visual representation is a spectrum
representing the range from benign to pathogenic. In some
embodiments, the visual representation is a heat map representing
the range from benign to pathogenic. In some embodiments, the
visual representation is a visual indicator of the score, wherein
the visual indicator is a numerical value, or a letter value. In
some embodiments, the visible representation is a color gradient
chart, ranging from benign to pathogenic. In some embodiments, the
visible representation of the clinical significant is a display of
the calculated pathogenicity score, In some embodiments, the
display of the calculated pathogenicity score is accompanied by an
explanation of the level of pathogenicity associated with the
displayed score, and/or an explanation of the level of
pathogenicity associated with various possible scores. In some
embodiments, the report display reasons for the calculated
pathogenicity score.
[0091] In some embodiments the report displays indicators selected
from: gene name, gene type, chromosomal location, mutation
information (coding change and/or amino acid change), mutation
type, form of inheritance, clinical relevance, an associated PubMed
ID number, or an associated GenBank Accession No. In some
embodiments, the report displays information about a disease known
to be associated with the described gene or chromosomal
location.
[0092] Regarding the variant of unknown clinical significant, in
some embodiments, the report displays information selected from:
information regarding an amino acid change resulting from the
variant, information regarding segregation analysis, information
regarding co-occurrence of the variant; information regarding
general population frequency of the variant, information regarding
amino acid conservation of the codon at which the variant occurs,
information regarding SIFT or PolyPhen analysis of the variant,
information regarding the protein domain wherein the variant
occurs, and information regarding a dbSNP reference. In some
embodiments, the report displays citations for relevant peer
reviewed articles.
[0093] In some embodiments, the report contains recommendations for
the end user regarding the information displayed therein. In some
embodiments, said recommendations can be chosen from
recommendations for further resting of the individual, or the
individual's immediate blood relatives.
EXAMPLES
Example 1
[0094] This example demonstrates a method of the present
disclosure, that is a real-time, rule-based system for the
analysis, clinical reporting, and curation of DNA sequence variant
data in a CLIA-certified commercial reference laboratory.
Database
[0095] A variant database was generated from a collection of data
for a plurality of variants. This was done with a Microsoft Access
database that is now housed on a SQL server and was adapted to fit
the needs through the addition of many forms, subforms, queries and
relationships.
Improved Interpretation
[0096] The second part of the scoring process was the method of
weighing and evaluating the collected data in the database to
generate a pathogenicity score (a clinical significance score) for
each variant. The score is meant as a tool/indicator to help
communicate to a health care provider the assessment of the
relative likelihood that the variant is pathogenic (causative of
disease symptoms) to the patient who is carrying the variant. Each
point of data curated within the database was weighed, with weights
determined with machine learning methods.
Scoring Rules
[0097] The pathogenicity assessment/scoring process segregated
variants into seven ranked categories on a pathogenicity scale,
based on the evaluation of the totality of multiple independent
types of evidence available for a given variant. Known/certainly
pathogenic variants were assigned a score of `7,` known/certainly
normal variants were assigned a score of `1,` and variants of
unknown significance with no apparent tendency toward benign or
pathogenic were assigned a starting value of `4.` Between these
points, variants lacking enough data for classification were
assigned different scores associated with different degrees of
"probable" pathogenicity. This system created consistency between
investigators, and it reflected measurable differences in the
confidence of a pathogenicity assessment based on accumulated
evidence in the medical literature.
[0098] The disclosed process of generating a pathogenicity score is
exemplified visually, first in a generalized flowchart (FIG. 1),
and then in two example flowcharts directed to two different
classes of genetic variants (FIG. 2, missense change; FIG. 3,
intronic change outside the canonical splice site). These two
different classes of variants are those that alter a single amino
acid in a protein (termed UAA), and those that do not alter any
amino acid in a protein (a UP).
Scoring Validity
[0099] The system and method performed 11,771 pathogenicity
assessments on 8,813 unique variants focused on neurological,
endocrine, and nephrotic genetic disorders. FIG. 5-7 show high
concordance of the predicted clinical significance with other
parameters. In particular, FIG. 5 demonstrates the percent of
variants where prediction by either SIFT alone, PolyPhen alone, or
both, matched classification. FIG. 6 exemplifies the distribution
of pathogenicity scores of variants with "damaging" function data.
Only 8% of variants with "damaging" functional data score 4 or less
due to conflicting data. FIG. 7 exemplifies the distribution of
pathogenicity scores of variants with "not damaging" function data.
12% of variants with "not damaging" functional data study 4 or more
due to conflicting data.
[0100] The effectiveness of the above described scoring system was
measured by comparing the stability of variant scoring categories
as a function of new data accumulated over time. In a retrospective
analysis of the system (FIG. 8), variants scored as a `5` were
later downgraded in 5.2% of cases while variants scored as a `6`
were downgraded in only 1.8% of cases. Similarly, on the benign end
of the scale, variants scoring as 2 or 3 have significantly lower
probability of scoring back upward than do variants with higher
scores (see FIG. 8). This stability pattern establishes confidence
in the scoring categories, supports their inclusion in result
reports, and provides evidence that continuous review of variants
is needed to assure the quality of the risk interpretation.
Enhanced Reporting
[0101] Once the pathogenicity score was assigned, reports for
variants that were classified benign and/or pathogenic could be
prepared. Text statements were populated according to programming
that existed outside the context of this AI process. FIG. 9
exemplifies such a variant report.
[0102] The scoring system conforms to ACMG standard rules that
require multiple independent lines of evidence to classify a
variant as benign or pathogenic. The significance of any single
line of evidence is subject to publication bias. In this study,
protein functional studies (whether in vitro or in vivo) are more
susceptible to bias than other types of evidence. For example, this
example identified that 8% of published functional studies on
variants have other lines of evidence that directly contradict the
functional findings. This illustrates the importance of curating
multiple, independent lines of evidence before making a conclusive
variant classification.
[0103] This example shows that the presently disclosure method is a
stable scoring system that conveys confident pathogenicity
assessments, effectively communicates risk, and provides useful
diagnostic information.
[0104] Thus, it should be understood that although the present
disclosure has been specifically disclosed by preferred embodiments
and optional features, modification, improvement and variation of
the disclosures embodied therein herein disclosed may be resorted
to by those skilled in the art, and that such modifications,
improvements and variations are considered to be within the scope
of this disclosure. The materials, methods, and examples provided
here are representative of preferred embodiments, are exemplary,
and are not intended as limitations on the scope of the
disclosure.
[0105] The disclosure has been described broadly and generically
herein. Each of the narrower species and subgeneric groupings
falling within the generic disclosure also form part of the
disclosure. This includes the generic description of the disclosure
with a proviso or negative limitation removing any subject matter
from the genus, regardless of whether or not the excised material
is specifically recited herein.
[0106] In addition, where features or aspects of the disclosure are
described in terms of Markush groups, those skilled in the art will
recognize that the disclosure is also thereby described in terms of
any individual member or subgroup of members of the Markush
group.
[0107] All publications, patent applications, patents, and other
references mentioned herein are expressly incorporated by reference
in their entirety, to the same extent as if each were incorporated
by reference individually. In case of conflict, the present
specification, including definitions, will control.
[0108] The disclosures illustratively described herein may suitably
be practiced in the absence of any element or elements, limitation
or limitations, not specifically disclosed herein. Thus, for
example, the terms "comprising," "including," containing," etc.
shall be read expansively and without limitation. Additionally, the
terms and expressions employed herein have been used as terms of
description and not of limitation, and there is no intention in the
use of such terms and expressions of excluding any equivalents of
the features shown and described or portions thereof, but it is
recognized that various modifications are possible within the scope
of the disclosure claimed.
[0109] Other embodiments are set forth within the following
claims.
* * * * *
References