Genetic Mapping in Human Disease
Open accessAbstract
Genetic mapping provides a powerful approach to identify genes and biological processes underlying any trait influenced by inheritance, including human diseases. We discuss the intellectual foundations of genetic mapping of Mendelian and complex traits in humans, examine lessons emerging from linkage analysis of Mendelian diseases and genome-wide association studies of common diseases, and discuss questions and challenges that lie ahead.
AI snapshot
Written from the paper’s full text.
TL;DR
This review traces human genetic mapping from linkage analysis of Mendelian disease to genome-wide association studies of common disease, arguing that GWAS works but common variants typically have modest effects and explain only a small fraction of inherited risk. It outlines remaining challenges: larger and more diverse studies, resequencing for rare and structural variants, and mechanistic interpretation rather than risk prediction.
Key findings
- Linkage and positional cloning identified thousands of Mendelian disease genes—growing from ~100 in the late 1980s to >2200 by 2008—but the approach was unsuccessful for common complex diseases such as diabetes, heart disease, and cancer.
- Before 2006, only about two dozen reproducible associations outside the HLA locus had been discovered; by early 2008, more than 150 relationships between common SNPs and disease traits were identified. Most common-variant effects are modest, mostly risk increases of 1.1 to 1.5 per allele, with exceptions such as APOE4 in Alzheimer’s disease, CFH in age-related macular degeneration, and LOXL1 in exfoliative glaucoma showing effects of a factor of ≥2 per allele.
- Variants identified by GWAS explain only a small fraction of inherited risk—for example, ~10% of the variance for Crohn’s disease and ~5% for type 2 diabetes. Power has been low: achieving 90% power to detect an allele with 20% frequency and a factor of 1.2 effect at P = 10−8 requires 8600 samples; meta-analysis and replication increased yield from 29 associations to more than 100 replicated loci across type 2 diabetes, serum lipids, Crohn’s disease, and height.
- A single locus can contain multiple independent common risk variants and can harbor both common variants of weak effect and rare variants of large effect; many associations implicate non-protein-coding regions, and allele frequencies vary across human populations.
Methods
- Narrative review and synthesis of the intellectual foundations, lessons, and future directions of genetic mapping in human disease, covering linkage analysis, association studies, GWAS, SNP catalogs, linkage disequilibrium, copy-number variation, and statistical analysis.
- Draws on cited literature and examples, including the International HapMap Project, the SNP Consortium, the Wellcome Trust Case Control Consortium Crohn’s disease study, and power calculations for GWAS and resequencing studies.
- No new primary data are reported; the paper is a review article.
Limitations
- The paper states that most genes and mutations underlying GWAS findings remain to be defined, it remains unclear how much heritability of common disease they explain, current variance estimates assume simple additive interactions, searches have not yet found much evidence for epistasis but may lack power to assess interactions, and it is premature to make inferences about the overall genetic architecture of common disease. It also notes that environmental exposures are fundamentally difficult to measure and that there may be inherent limits to completely accounting for phenotypic variation.
- Evident from the text: this is a narrative review, not a systematic review, with no stated formal search or selection criteria; examples and cited studies are selective, and the evidence base is current only to 2008.
Model-written summary. Check it against the paper before relying on it.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
0 of 108 cited sources checked · 0 supported · 0 flagged
- Findingown data
A GWAS of 2000 cases and 2000 controls provides good power for a 1% allele causing a factor of 4 increase in risk, even at P < 10−8.
“A GWAS of 2000 cases and 2000 controls provides good power for a 1% allele causing a factor of 4 increase in risk (even at P < 10−8) (Fig. 2).”
Quote in the paperSubstantial claim - Interpretationnone given
Association studies of candidate genes were limited to specific variants in biological candidate genes, each with a tiny a priori probability of being disease-causing.
“They were limited to specific variants in biological candidate genes, each with a tiny a priori probability of being disease-causing.”
Quote in the paperSubstantial claim - Interpretationnone given
Mutations that cause strongly deleterious phenotypes, as most Mendelian diseases appear to be, are lost to purifying selection.
“Mutations that cause strongly deleterious phenotypes—as most Mendelian diseases appear to be—are lost to purifying selection.”
Quote in the paperNot a substantial claim - Interpretationnone given
The linkage-based approach proved unsuccessful for common forms of human diseases such as diabetes, heart disease, and cancer that show complex inheritance in the general population.
“Despite great hopes, the approach proved unsuccessful for common forms of human diseases—such as diabetes, heart disease, and cancer—that show complex inheritance in the general population.”
Quote in the paperSubstantial claim- Rests on an assumption: Common forms of human diseases such as diabetes, heart disease, and cancer show complex inheritance in the general population.
- Interpretationnone given
Loci for Mendelian diseases typically harbor many disease-causing alleles, mostly rare in the population.
“Loci typically harbor many disease-causing alleles, mostly rare in the population”
Quote in the paperNot a substantial claim
- Interpretationnone given
Over the past year, a new approach to genetic mapping has yielded the first general progress toward mapping loci that influence susceptibility to common human diseases.
“Over the past year, a new approach to genetic mapping has yielded the first general progress toward mapping loci that influence susceptibility to common human diseases.”
Quote in the paperNot a substantial claim - Interpretationcitation
Only about a dozen extensively reproduced associations of common variants outside the HLA locus were identified in the 20th century.
“Still, only about a dozen extensively reproduced associations of common variants (outside the HLA locus) were identified in the 20th century (24).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [24] Hirschhorn JN Lohmueller K Byrne E Hirschhorn K Genet. Med 2002 4 45 11882781 source
Not checked in the free run.
- Interpretationcitation
Mildly deleterious alleles can rise to moderate frequency, particularly in populations that have undergone recent expansion.
“Mildly deleterious alleles can rise to moderate frequency, particularly in populations that have undergone recent expansion (34).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [34] Reich DE Lander ES Trends Genet 2001 17 502 11525833 source
Not checked in the free run.
- Rests on an assumption: The human population has recently grown exponentially from a small size.
- Rests on an assumption: Common diseases often have late onset, with modest or no obvious impact on reproductive fitness.
- Interpretationnone given
Mendelian diseases often reveal great complexity, such as locus heterogeneity, incomplete penetrance, and variable expressivity.
“Mendelian diseases often revealed great complexity, such as locus heterogeneity, incomplete penetrance, and variable expressivity.”
Quote in the paperNot a substantial claim - Premisecitation
Humans have limited genetic variation: the heterozygosity rate for single-nucleotide polymorphisms (SNPs) is ~1 in 1000 bases.
“As predicted by classical theory (29), humans have limited genetic variation: The heterozygosity rate for single-nucleotide polymorphisms (SNPs) is ~1 in 1000 bases (30–32).”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [29] Kimura M Ota T Genetics 1973 75 199 4762875 PMC1212997 source
Not checked in the free run.
- cites [30] Harris H Proc. R. Soc. London Ser. B 1966 164 298 4379519 source
Not checked in the free run.
- cites [31] Li WH Sadler LA Genetics 1991 129 513 1743489 PMC1204640 source
Not checked in the free run.
- cites [32] Sachidanandam R Nature 2001 409 928 source
Not checked in the free run.
- Study design and conductcitation
Differences in ancestry between cases and controls would yield spurious associations.
“Differences in ancestry between cases and controls would yield spurious associations (65), suggesting the need for family-based controls (66).”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [65] Knowler WC Williams RC Pettitt DJ Steinberg AG Am. J. Hum. Genet 1988 43 520 3177389 PMC1715499
Not checked in the free run.
- cites [66] Spielman RS McGinnis RE Ewens WJ Am. J. Hum. Genet 1993 52 506 8447318 PMC1682161
Not checked in the free run.
- Study design and conductreasoning
Genome-wide studies provide their own internal control: mismatched ancestry is readily detectable because it produces frequency differences at thousands of SNPs, which could not all reflect causal associations.
“It was later recognized that genome-wide studies provide their own internal control: Mismatched ancestry is readily detectable because it produces frequency differences at thousands of SNPs, which could not all reflect causal associations.”
Quote in the paperSubstantial claim - Study design and conductreasoning
Stringent thresholds for statistical significance are needed to avoid false positives due to multiple hypothesis testing.
“Conversely, stringent thresholds for statistical significance are needed to avoid false positives due to multiple hypothesis testing.”
Quote in the paperSubstantial claim - Premisecitation
GWASs have shown that common genetic variation in LDLR and HMGCR influences LDL levels.
“More recently, GWASs have shown that common genetic variation in LDLR and HMGCR influences LDL levels (84, 85).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Searches have not yet found much evidence for epistasis.
“Although searches have not yet found much evidence for epistasis [e.g., (93, 94, 135)]”
Quote in the paperNot a substantial claim0 of 3 sources checked - Premisenone given
Variants so far identified by GWASs together explain only a small fraction of the overall inherited risk of each disease, for example ~10% of the variance for Crohn's and ~5% for T2D.
“Variants so far identified by GWASs together explain only a small fraction of the overall inherited risk of each disease (for example, ~10% of the variance for Crohn’s and ~5% for T2D).”
Quote in the paperNot a substantial claim - Premisecitation
An excess of rare mutations in renal salt-handling genes has been associated with lower blood pressure and protection against hypertension.
“An excess of rare mutations in renal salt-handling genes has been associated with lower blood pressure and protection against hypertension (131).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [131] Ji W Nat. Genet 2008 40 592 18391953 PMC3766631 source
Not checked in the free run.
- Interpretationreasoning
The primary value of genetic mapping is not risk prediction, but providing novel insights about mechanisms of disease.
“The primary value of genetic mapping is not risk prediction, but providing novel insights about mechanisms of disease.”
Quote in the paperNot a substantial claim - Premisecitation
Several recent studies report that patients with autism and schizophrenia may have an excess of rare deletions across the genome relative to unaffected controls.
“Moreover, several recent studies report that patients with autism and schizophrenia may have an excess of rare deletions across the genome relative to unaffected controls (133,134).”
Quote in the paperSubstantial claim0 of 2 sources checked - Premisecitation
Rare nonsynonymous mutations in MC4R are found in patients with extreme early-onset obesity.
“Rare nonsynonymous mutations in MC4R are found in patients with extreme early-onset obesity (129).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [129] Hirschhorn JN Altshuler D J. Clin. Endocrinol. Metab 2002 87 4438 12364414 source
Not checked in the free run.
- Interpretationreasoning
It is premature to make inferences about the overall genetic architecture of common disease.
“For these reasons, it is premature to make inferences about the overall genetic architecture of common disease.”
Quote in the paperNot a substantial claim - Interpretationreasoning
At disease loci already identified by GWAS, locus-attributable risk will often be higher than currently estimated.
“At disease loci already identified by GWAS, the locus-attributable risk will often be higher than currently estimated.”
Quote in the paperSubstantial claim - Interpretationnone given
Marker SNPs used in GWASs will typically be imperfect proxies for the actual causal mutation that led to the association signal.
“This is because marker SNPs used in GWASs will typically be imperfect proxies for the actual causal mutation that led to the association signal.”
Quote in the paperNot a substantial claim - Interpretationreasoning
The causal gene will often contain additional mutations not tagged by the initial marker SNPs, both common and rare.
“The causal gene will often contain additional mutations not tagged by the initial marker SNPs, both common and rare.”
Quote in the paperSubstantial claim - Interpretationreasoning
Larger, more comprehensive, and more diverse GWASs will reveal many more loci.
“Larger, more comprehensive, and more diverse GWASs will reveal many more loci.”
Quote in the paperSubstantial claim - Premisecitation
Rare nonsynonymous mutations in ABCA1 are more common in patients with extremely low HDL than in those with high HDL.
“Rare nonsynonymous mutations in ABCA1 are more common in patients with extremely low HDL than in those with high HDL (130).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [130] Cohen JC Science 2004 305 869 15297675 source
Not checked in the free run.
- Interpretationreasoning
Because rare mutations are numerous and individually rare, it is not possible to create a complete catalog in the general population.
“Because they are numerous and individually rare, it is not possible to create a complete catalog in the general population.”
Quote in the paperSubstantial claim - Interpretationreasoning
Knowledge of disease pathways can suggest strategies for prevention, diagnosis, and therapy.
“Knowledge of disease pathways (not limited to the causal genes and mutations) can suggest strategies for prevention, diagnosis, and therapy”
Quote in the paperSubstantial claim - Premisecitation
A recent GWAS of autism revealed that a highly penetrant, recurrent microdeletion and microduplication of a 593-kb region in 16p11.2 explains 1% of cases.
“A recent GWAS of autism revealed that a highly penetrant, recurrent microdeletion and microduplication of a 593-kb region in 16pll.2 explains 1% of cases (132).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [132] Weiss LA N. Engl. J. Med 2008 358 667 18184952 source
Not checked in the free run.
- Premisenone given
The vast majority of GWASs have been performed only in samples of European ancestry.
“Moreover, the vast majority of studies have been performed only in samples of European ancestry.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Achieving genome-wide significance for coding mutations will likely require resequencing studies of thousands of cases and controls, similar to GWASs.
“Achieving genome-wide significance will likely require resequencing studies of thousands of cases and controls, similar to GWASs (Fig. 2).”
Quote in the paperSubstantial claim - Interpretationreasoning
The universe of rare structural changes contributing to each disease may be as large and diverse as that of common SNPs.
“they suggest that the universe of rare structural changes contributing to each disease may be as large and diverse as that of common SNPs.”
Quote in the paperSubstantial claim - Interpretationreasoning
The lack of much evidence for epistasis may simply reflect limited power to assess the many possible modes of interaction, including pairwise interactions and threshold effects.
“this may simply reflect limited power to assess the many possible modes of interaction, including pairwise interactions and threshold effects.”
Quote in the paperSubstantial claim - Interpretationreasoning
Once patterns of association and interaction are understood, effects of specific gene and environmental exposures on each phenotype may be larger.
“Once patterns of association and interaction are understood, effects of specific gene and environmental exposures on each phenotype may be larger.”
Quote in the paperSubstantial claim- Rests on an assumption: Gene-gene and gene-environment interactions play important roles in disease risk.
- Interpretationreasoning
Many more disease loci remain to be identified by GWAS.
“Many more disease loci remain to be identified by GWAS.”
Quote in the paperSubstantial claim - Study design and conductreasoning
Current estimates of the variance explained are based on simplifying assumptions, including that variants interact in a simple additive manner.
“Current estimates of the variance explained are based on simplifying assumptions. Because the genotype-phenotype correlation has yet to be well characterized, the estimates assume that the variants interact in a simple additive manner.”
Quote in the paperNot a substantial claim - Interpretationreasoning
Disease loci containing only rare variants cannot be identified by study of common variants alone.
“Such loci (if not already found by Mendelian genetics) cannot be identified by study of common variants alone.”
Quote in the paperSubstantial claim - Interpretationreasoning
Because each rare variant is too rare to prove statistical evidence of association, mutations must be aggregated as a class to compare the overall frequency of cases versus controls.
“Moreover, because each variant is too rare to prove statistical evidence of association, the mutations must be aggregated as a class to compare the overall frequency of cases versus controls.”
Quote in the paperSubstantial claim - Interpretationnone given
Rare mutations likely also play an important role in common diseases.
“Rare mutations likely also play an important role in common diseases.”
Quote in the paperNot a substantial claim- Rests on an assumption: Alleles with strong deleterious effects are constrained by natural selection from becoming too common.
- Interpretationnone given
The sample size required for a genome-wide search based on coding mutations depends on the background frequency μ of mutations that confer disease risk and the level ω of increased risk for each such mutation.
“The sample size required to perform a genome-wide search based on coding mutations depends on the background frequency (μ) of mutations that confer disease risk and the level (ω) of increased risk for each such mutation.”
Quote in the paperSubstantial claim - Interpretationreasoning
Multiple instances of de novo coding mutations at a locus could provide particularly powerful association information, because the human mutation rate is so low (in the range of 10−8).
“Multiple instances of de novo coding mutations at a locus (by comparing affected individuals with parents) could provide particularly powerful association information, because the human mutation rate is so low (in the range of 10−8).”
Quote in the paperSubstantial claim- Rests on an assumption: The human mutation rate is in the range of 10−8.
- Interpretationreasoning
Identifying de novo mutations without being overwhelmed by false positives will require extraordinary sequencing accuracy, far better than finished genome sequence.
“But identifying de novo mutations without being overwhelmed by false positives will require extraordinary sequencing accuracy (far better than finished genome sequence).”
Quote in the paperSubstantial claim - Interpretationreasoning
Even if a variant has the same effect in all ancestry groups, it may be more readily detected in one population simply because it happens to have higher frequency.
“Even if a variant has the same effect in all ancestry groups, it may be more readily detected in one population simply because it happens to have higher frequency.”
Quote in the paperSubstantial claim - Interpretationcitation
Early data on rare single-nucleotide and structural variants indicate that similarly large samples will be needed to achieve the levels of statistical significance required to detect rare events in a genome-wide search.
“Moreover, early data on rare single-nucleotide (130, 131) and structural variants (133, 134, 136) indicate that similarly large samples will be needed to achieve the levels of statistical significance required to detect rare events in a genome-wide search.”
Quote in the paperSubstantial claim0 of 3 sources checked - Interpretationreasoning
Discovering genes at loci that harbor neither common nor rare structural variants will require sequencing in thousands of cases and controls.
“Discovering such genes will require sequencing in thousands of cases and controls.”
Quote in the paperSubstantial claim - Interpretationreasoning
Environmental exposures are fundamentally more difficult to measure than DNA.
“but environmental exposures are fundamentally more difficult to measure.”
Quote in the paperSubstantial claim- Rests on an assumption: Environmental exposures play a larger role in human phenotypic variation than does genetic variation.
- May combine two claims. 59
- Classified as probably not a substantial claim. 45
- The quote only partly states this claim. 2
May combine two claims.
Findingnone givenA study of 1000 cases and 1000 controls provides only 1% power to detect a 20% variant that increases risk by a factor of 1.3, but a study of 5000 cases and 5000 controls provides 98% power.
“A study of 1000 cases and 1000 controls provides only 1% power to detect a 20% variant that increases risk by a factor of 1.3, but a study of 5000 cases and 5000 controls provides 98% power (Fig. 2).”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenIn common forms of common disease, risk to relatives is lower than in Mendelian cases, and linkage studies with excellent power to detect a single causal gene yielded equivocal results.
“In common forms of common disease, risk to relatives is lower than in Mendelian cases, and linkage studies with excellent power to detect a single causal gene yielded equivocal results.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationPerhaps 90% of heterozygous sites in each individual are common variants, typically shared among continental populations.
“Moreover, perhaps 90% of heterozygous sites in each individual are common variants, typically shared among continental populations (33).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [33] Lewontin R Dobzhansky T Hecht MK Steere WC Evolutionary Biology 6 1972 New York Appleton-Century-Crofts 391 398
Not checked in the free run.
May combine two claims.
PremisecitationNearby variants form a block-like structure consisting of regions with little evidence for historical recombination and limited haplotype diversity; within such regions, genotypes of common SNPs can be inferred from a few empirically determined tag SNPs.
“Nearby variants were observed to form a block-like structure consisting of regions characterized by little evidence for historical recombination and limited haplo-type diversity (44, 45). Within such regions, which soon proved general (46), genotypes of common SNPs could be inferred from knowledge of only a few empirically determined tag SNPs (45–47).”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [44] Daly MJ Rioux JD Schaffner SF Hudson TJ Lander ES Nat. Genet 2001 29 229 11586305 source
Not checked in the free run.
- cites [45] Patil N Science 2001 294 1719 11721056 source
Not checked in the free run.
- cites [46] Gabriel SB Science 2002 published online 23 May 2002 296 2225 12029063 source
Not checked in the free run.
- cites [47] Johnson GC Nat. Genet 2001 29 233 11586306 source
Not checked in the free run.
May combine two claims.
PremisecitationThe SNP Consortium built an initial map of 1.4 million SNPs; this has grown to more than 10 million SNPs and is estimated to contain 80% of all SNPs with frequencies of >10%.
“A public-private partnership, the SNP Consortium, built an initial map of 1.4 million SNPs (32); this has grown to more than 10 million SNPs (36) and is estimated to contain 80% of all SNPs with frequencies of >10% (37).”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [32] Sachidanandam R Nature 2001 409 928 source
Not checked in the free run.
- cites [36] Entrez SNP (www.ncbi.nlm.nih.gov/sites/entrez?db=snp)
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [37] International HapMap Consortium Nature 2005 437 1299
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationcitationMendelian subtypes of common diseases were elucidated, but mutations in these genes explained few cases in the population.
“Mendelian subtypes of common diseases [such as breast cancer (15), hypertension (16), and diabetes (17)] were elucidated, but mutations in these genes explained few cases in the population.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [15] Welcsh PL King MC Hum. Mol. Genet 2001 10 705 11257103 source
Not checked in the free run.
- cites [16] Lifton RP Harvey Lect 2004 100 71 16970175
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [17] Bell GI Polonsky KS Nature 2001 414 788 11742410 source
Not checked in the free run.
May combine two claims.
InterpretationcitationAlthough many claims of associations were published, the statistical support tended to be weak and few were subsequently replicated.
“Although many claims of associations were published, the statistical support tended to be weak and few were subsequently replicated (25).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [25] Lohmueller KE Pearce CL Pike M Lander ES Hirschhorn NJ Nat. Genet 2003 33 177 12524541 source
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenDisease-causing mutations for Mendelian diseases often cause major changes in encoded proteins.
“Disease-causing mutations often cause major changes in encoded proteins”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningAssociation studies were susceptible to false positives due to population structure, because there was no way to assess differences in the genetic background of cases and controls.
“Moreover, association studies were susceptible to false positives due to population structure, because there was no way to assess differences in the genetic background of cases and controls.”
Quote in the paperSubstantial claimMay combine two claims.
PremisecitationLD mapping proved useful in fine-mapping the founder Δ508 mutation in CFTR as a cause of cystic fibrosis and in screening the entire genome in isolated populations such as Finland.
“This method soon proved useful in fine-mapping the founder Δ508 mutation in the transmembrane conductance regulator CFTR as a cause of cystic fibrosis (40) and in screening the entire genome in isolated populations such as Finland (41).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisereasoningBecause the recombination rate is low (~1 crossover per 100 megabases per generation), disease alleles in the population typically show association with nearby marker alleles for many generations, a phenomenon termed linkage disequilibrium (LD).
“Because the recombination rate is low [~1 crossover per 100 megabases (Mb) per generation], disease alleles in the population typically show association with nearby marker alleles for many generations, a phenomenon termed linkage disequilibrium (LD) (Fig. 1).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites Fig. 1
Not checked in the free run.
Probably not a substantial claim: may not pass S3 (load-bearing). May combine two claims.
Interpretationnone givenThe features of common disease were consistent with, but did not prove, a polygenic model.
“These features were consistent with, but did not prove, a polygenic model.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenMost of the genes and mutations underlying the GWAS findings remain to be defined, and it remains unclear how much of the heritability of common disease they explain.
“Still, most of the genes and mutations underlying these findings remain to be defined, let alone understood, and it remains unclear how much of the heritability of common disease they explain.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationnone givenThe candidate gene approach was inadequate for Mendelian disease gene discovery; most disease genes were completely unsuspected on the basis of previous knowledge.
“The “candidate gene” approach was woefully inadequate; most disease genes were completely unsuspected on the basis of previous knowledge”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA simulation study suggested that LD might typically be too short to be useful with a SNP every 5 kb (500,000 SNPs across the genome), providing very weak LD (average correlation r2 = 0.1).
“A simulation study suggested that LD might typically be too short to be useful with a SNP every 5 kb (500,000 SNPs across the genome) providing very weak LD (average correlation r2 = 0.1) (42).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [42] Kruglyak L Nat. Genet 1999 22 139 10369254 source
Not checked in the free run.
May combine two claims.
InterpretationcitationA subset of associations involve genes previously related to the disease; of 19 loci meeting genome-wide significance in a recent GWAS of LDL, HDL, or triglycerides, 12 contained genes with known functions in lipid biology.
“1) A subset of associations involve genes previously related to the disease. Of 19 loci meeting genome-wide significance in a recent GWAS of LDL, HDL, or triglyceride levels, 12 contained genes with known functions in lipid biology (84, 85).”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
InterpretationcitationThe risk of false negatives was illustrated by T2D and the Pro12 → Ala polymorphism in PPARγ: larger studies produced strong and consistent evidence of increased risk by a factor of 1.2, while negative studies lacked adequate power.
“Whereas an initial positive report (61) had not been confirmed in four modest-sized replication studies, larger studies produced strong and consistent evidence of increased risk by a factor of 1.2 (62, 63). The negative studies were actually consistent with the level of increased risk, but simply lacked adequate power to detect it.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [61] Deeb SS Nat. Genet 1998 20 284 9806549 source
Not checked in the free run.
- cites [62] Altshuler D Nat. Genet 2000 26 76 10973253 source
Not checked in the free run.
- cites [63] Florez JC Hirschhorn JN Altshuler D Annu. Rev. Genomics Hum. Genet 2003 4 257 14527304 source
Not checked in the free run.
May combine two claims. The quote only partly states this claim.
InterpretationcitationAssociation signals have identified small regions for study but have not yet identified causal genes and mutations; GWASs typically yield regions of 10 to 100 kb, and the causal mutation need not be a SNP (e.g., IRGM deletion upstream of promoter).
“4) Association signals have identified small regions for study but have not yet identified causal genes and mutations.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [91] McCarroll SA Nat. Genet 2008 40 1107 19165925 PMC2731799 source
Not checked in the free run.
May combine two claims.
InterpretationcitationBecause allele frequencies vary across human populations, the relative roles of common susceptibility genes can vary among ethnic groups; the 8q24 prostate cancer contribution is greater in African Americans because risk alleles occur at higher frequencies, not because they confer greater susceptibility.
“7) Because allele frequencies vary across human populations, the relative roles of common susceptibility genes can vary among ethnic groups. One example is the association of prostate cancer at 8q24: SNPs in the region play a role in all ethnic groups, but the contribution is greater in African Americans. This is not because the risk alleles yet found confer greater susceptibility in African”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [92] Haiman CA Nat. Genet 2007 39 638 17401364 PMC2638766 source
Not checked in the free run.
May combine two claims.
InterpretationcitationA single locus can harbor both common variants of weak effect and rare variants of large effect; of 19 lipid loci, nine were already known to carry rare Mendelian mutations with large effects.
“6) A single locus can harbor both common variants of weak effect and rare variants of large effect. In recent GWASs, studies of common SNPs enabled the identification of 19 loci as influencing low- or high-density lipoprotein (LDL, HDL) or triglycerides (84, 85). Nine of these 19 were already known to carry rare Mendelian mutations with large effects, such as the loci for the LDL receptor (LDLR)”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationcitationA single locus can contain multiple independent common risk variants; for example, seven independent alleles at 8q24 for prostate cancer, three at CFH for AMD, three at IRF5 for SLE, and two at IL23R for Crohn's disease.
“5) A single locus can contain multiple independent common risk variants. Intensive study has already identified seven independent alleles at 8q24 for prostate cancer (92), three at complement factor H (CFH) for age-related macular degeneration (93, 94), three at IRF5 for systemic lupus erythematosus (95), and two at IL23R for Crohn’s disease (96).”
Quote in the paperSubstantial claim0 of 4 sources checked- cites [92] Haiman CA Nat. Genet 2007 39 638 17401364 PMC2638766 source
Not checked in the free run.
- cites [93] Maller J Nat. Genet 2006 38 1055 16936732 source
Not checked in the free run.
- cites [94] Li M Nat. Genet 2006 38 1049 16936733 PMC1941700 source
Not checked in the free run.
- cites [95] Graham RR Proc. Natl. Acad. Sci. U.S.A 2007 104 6758
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationcitationEffect sizes for common variants are typically modest; in the vast majority of cases, estimated effects are increases in risk by a factor of 1.1 to 1.5 per associated allele, with a few exceptions of ≥2 (APOE4, CFH, LOXL1).
“2) Effect sizes for common variants are typically modest. In a few cases, common variants with effects of a factor of ≥2 per allele have been found: APOE4 in Alzheimer’s disease (23), CFH in age-related macular degeneration (77–79), and LOXL1 in exfoliative glaucoma (80). In the vast majority of cases, however, the estimated effects are much smaller—mostly increases in risk by a factor of 1.1 to 1”
Quote in the paperSubstantial claim0 of 5 sources checked- cites [23] Strittmatter WJ Roses AD Annu. Rev. Neurosci 1996 19 53 8833436 source
Not checked in the free run.
- cites [77] Klein RJ Science 2005 308 385 published online 10 March 2005
Not checked in the free run.
- cites [78] Edwards AO Science 2005 308 421 published online 10 March 2005
Not checked in the free run.
- cites [79] Haines JL Science 2005 308 419 published online 10 March 2005
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [80] Thorleifsson G Science 2007 317 1397 published online 9 August 2007 17690259 source
Not checked in the free run.
May combine two claims.
Study design and conductcitationA dense genome-wide scan of common variants involves the equivalent of ~1 million independent hypotheses, so a significance level of P = 5 × 10−8 represents a finding expected by chance once in 20 GWASs.
“Simulations indicated that a dense genome-wide scan of common variants involves the equivalent of ~1 million independent hypotheses (64). A significance level of P = 5 × 10−8 thus represents a finding expected by chance once in 20 GWASs.”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [64] Pe'er I Yelensky R Altshuler D Daly MJ Genet. Epidemiol 2008 32 381 18348202 source
Not checked in the free run.
May combine two claims.
InterpretationcitationMost associations do not involve previous candidate genes; some GWAS results immediately suggest new biological hypotheses, such as CFH in AMD, FGFR2 in breast cancer, and CDKN2A/CDKN2B in T2D.
“2) Most associations do not involve previous candidate genes. In some cases, GWAS results immediately suggest new biological hypotheses— for example, the role of complement factor H in age-related macular degeneration (77–79), FGFR2 in breast cancer (98), and CDKN2A and CDKN2B in T2D (99–101).”
Quote in the paperSubstantial claim0 of 7 sources checked- cites [77] Klein RJ Science 2005 308 385 published online 10 March 2005
Not checked in the free run.
- cites [78] Edwards AO Science 2005 308 421 published online 10 March 2005
Not checked in the free run.
- cites [79] Haines JL Science 2005 308 419 published online 10 March 2005
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [98] Easton DF Nature 2007 447 1087 17529967 PMC2714974 source
Not checked in the free run.
- cites [99] Zeggini E Science 2007 316 1336 published online 25 April 2007 17463249 PMC3772310 source
Not checked in the free run.
- cites [100] Scott LJ Science 2007 316 1341 published online 25 April 2007 17463248 PMC3214617 source
Not checked in the free run.
- cites [101] Diabetes Genetics Initiative of Broad Institute of Harvard MIT, Lund University, Novartis Institutes for BioMedical Research Science 2007 316 1331 published online 26 April 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims. The quote only partly states this claim.
InterpretationcitationThe power to detect associations has been low; first-wave GWASs identified only a fraction of loci findable with larger sample sizes, and increasing power by meta-analysis and replication increased yield to more than 100 replicated loci for T2D, serum lipids, Crohn's disease, and height.
“3) The power to detect associations has been low. Given the effect sizes now known to exist, and the need to exceed stringent statistical thresholds, the first wave of GWASs provided low power to discover disease-causing loci (81, 82).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [81] Wellcome Trust Case Control Consortium Nature 2007 447 661
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [82] Altshuler D Daly M Nat. Genet 2007 39 813 17597768 source
Not checked in the free run.
- cites [83] Zeggini E Nat. Genet 2008 40 638 18372903 PMC2672416 source
Not checked in the free run.
May combine two claims.
PremisecitationComparative genome analysis has shown that 5% of the human genome is evolutionarily conserved and thus functional; less than one-third of this 5% consists of genes that encode proteins.
“Comparative genome analysis has shown that 5% of the human genome is evolutionarily conserved and thus functional; less than one-third of this 5% consists of genes that encode proteins (108).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [108] Waterston RH Nature 2002 420 520 12466850 source
Not checked in the free run.
May combine two claims.
PremisecitationSequence data from the International HapMap Project confirmed that 500,000 SNPs provide excellent power to test >90% of common SNP variation in out-of-Africa populations, with roughly twice that number required in African populations.
“Sequence data collected by the project confirmed that the vast majority of common SNPs are strongly correlated to one or more nearby proxies: 500,000 SNPs provide excellent power to test >90% of common SNP variation in out-of-Africa populations, with roughly twice that number required in African populations (37).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [37] International HapMap Consortium Nature 2005 437 1299
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationcitationGWASs work: by early 2008, more than 150 relationships were identified between common SNPs and disease traits, and in most diseases studied GWASs revealed multiple independent loci.
“1) GWASs work. Before 2006, only about two dozen reproducible associations outside the HLA locus had been discovered (25). By early 2008, more than 150 relationships were identified between common SNPs and disease traits (table S1). In most diseases studied, GWASs have revealed multiple independent loci, although some traits have not yet yielded associations that meet stringent thresholds (e.g.,”
Quote in the paperSubstantial claim0 of 2 sources checked- cites [25] Lohmueller KE Pearce CL Pike M Lander ES Hirschhorn NJ Nat. Genet 2003 33 177 12524541 source
Not checked in the free run.
- cites table S1
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
May combine two claims.
InterpretationcitationMany associations implicate non-protein-coding regions; examples include 8q24 associated with prostate, breast, and colon cancer, 300 kb from the nearest gene, and 9q21 associated with myocardial infarction and T2D, 150 kb from CDKN2A/CDKN2B.
“Examples include the region at 8q24 associated with prostate, breast, and colon cancer, 300 kb from the nearest gene (103, 104), and the region at 9q21 associated with myocardial infarction and T2D, 150 kb from the nearest genes encoding CDKN2A and CDKN2B (99–101, 105–107).”
Quote in the paperSubstantial claim0 of 8 sources checked- cites [103] Amundadottir LT Nat. Genet 2006 38 652 16682969 source
Not checked in the free run.
- cites [104] Freedman ML Proc. Natl. Acad. Sci. U.S.A 2006 103 14068
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [99] Zeggini E Science 2007 316 1336 published online 25 April 2007 17463249 PMC3772310 source
Not checked in the free run.
- cites [100] Scott LJ Science 2007 316 1341 published online 25 April 2007 17463248 PMC3214617 source
Not checked in the free run.
- cites [101] Diabetes Genetics Initiative of Broad Institute of Harvard MIT, Lund University, Novartis Institutes for BioMedical Research Science 2007 316 1331 published online 26 April 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [105] McPherson R Science 2007 316 1488 published online 2 May 2007 17478681 PMC2711874 source
Not checked in the free run.
- cites [106] Samani NJ N. Engl. J. Med 2007 357 443 17634449 PMC2719290 source
Not checked in the free run.
- cites [107] Helgadottir A Science 2007 316 1491 published online 2 May 2007 17478679 source
Not checked in the free run.
May combine two claims.
Study design and conductcitationMethods were developed to detect and adjust for ancestry biases and unexpected relatedness between subjects.
“Methods were developed to detect and adjust for such biases (67–69) as well as unexpected relatedness between subjects.”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [67] Devlin B Roeder K Biometrics 1999 55 997 11315092 source
Not checked in the free run.
- cites [68] Pritchard JK Rosenberg NA Am. J. Hum. Genet 1999 65 220 10364535 PMC1378093 source
Not checked in the free run.
- cites [69] Price AL Nat. Genet 2006 38 904 16862161 source
Not checked in the free run.
May combine two claims.
InterpretationcitationSome regions contain expected associations across diseases and traits; the association of the same common polymorphisms in IL23R in Crohn's disease, psoriasis, and ankylosing spondylitis points to a shared molecular cause.
“4) Some regions contain expected associations across diseases and traits. Crohn’s disease, psoriasis, and ankylosing spondylitis have long been recognized to share clinical features; the association of the same common polymorphisms in IL23R in all three diseases points to a shared molecular cause (96, 109, 110).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [96] Duerr RH Science 2006 314 1461 published online 26 October 2006 17068223 PMC4410764 source
Not checked in the free run.
- cites [109] Burton PR Nat. Genet 2007 39 1329 17952073 PMC2680141 source
Not checked in the free run.
- cites [110] Cargill M Am. J. Hum. Genet 2007 80 273 17236132 PMC1785338 source
Not checked in the free run.
May combine two claims.
PremisecitationMany copy-number variations (CNVs) display tight LD with nearby SNPs and thus can be proxied by nearby SNPs in GWASs.
“Many CNVs display tight LD with nearby SNPs (56, 57) and thus can be proxied by nearby SNPs in GWASs.”
Quote in the paperNot a substantial claim0 of 2 sources checkedMay combine two claims.
PremisecitationThe gene encoding PCSK9 contains very rare mutations causing autosomal dominant hypercholesterolemia and high-frequency common variants with modest effects.
“The gene encoding PCSK9 contains very rare mutations causing autosomal dominant hypercholesterolemia (discovered by linkage analysis), as well as high-frequency common variants with modest effects.”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
PremisereasoningABCA1 is a favorable case because μ and ω are high, with an unusually large coding region of ~7 kb and mutations conferring a factor of ~6 increase in risk.
“ABCA1 is a favorable case because μ and ω are high (the gene has an unusually large coding region of ~7 kb, and mutations confer a factor of ~6 increase in risk).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe proportion of genetic variance explained is certain to grow in the coming years, but it is unlikely to approach 100% because of practical limitations such as detecting common variants with extremely small effects, genes harboring rare variants at very low frequency, and complex interactions among genes and with the environment.
“Although the proportion of genetic variance explained is certain to grow in the coming years, it is unlikely to approach 100% because of practical limitations, such as the difficulty of detecting common variants with extremely small effects, genes harboring rare variants at very low frequency, and complex interactions among genes and with the environment.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisereasoningBrown and Goldstein's studies of FH led to the discovery of the LDL receptor and supported the development of HMGCR inhibitors (statins) for lowering LDL, the use of which is not limited to FH carriers.
“Studies of FH led to the discovery of the LDL receptor and supported the development of HMGCR inhibitors (statins) for lowering LDL, the use of which is not limited to FH carriers.”
Quote in the paperSubstantial claimMay combine two claims.
Interpretationnone givenGWASs to date have had low statistical power and thus necessarily missed many loci with common variants of similar and smaller effects.
“As noted above, GWASs to date have had low statistical power and thus necessarily missed many loci with common variants of similar and smaller effects.”
Quote in the paperNot a substantial claimMay combine two claims.
Premisenone givenThe first GWASs did not have proxies for common structural variants and have failed to capture lower-frequency common variants (0.5 to 5%).
“The first studies did not have proxies for common structural variants and have failed to capture lower-frequency common variants (0.5 to 5%).”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe frequency of a genetic variant is not related to the magnitude of its effect, nor to the potential clinical value that may be obtained.
“From this perspective, the frequency of a genetic variant is not related to the magnitude of its effect, nor to the potential clinical value that may be obtained.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based).
InterpretationreasoningThe likely outcome of systematically exploring these directions is that different diseases will each be characterized by a different balance of allele frequencies, interactions, and types.
“Only by systematically exploring each of these directions over the coming years will a general picture emerge—with the likely outcome being that different diseases will each be characterized by a different balance of allele frequencies, interactions, and types.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationThe current HapMap provides reliable proxies for the vast majority of SNPs at frequencies above 5%, but its coverage declines rapidly for lower-frequency alleles.
“The current HapMap provides reliable proxies for the vast majority of SNPs at frequencies above 5%, but its coverage declines rapidly for lower-frequency alleles (37).”
Quote in the paperSubstantial claim0 of 1 sources checked- cites [37] International HapMap Consortium Nature 2005 437 1299
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
Probably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Premisenone givenFH affects ~0.2% of the population and accounts for a tiny fraction of the heritability of LDL and myocardial infarction.
“The classic example is Brown and Goldstein’s studies of FH, which affects ~0.2% of the population and accounts for a tiny fraction of the heritability of LDL and myocardial infarction.”
Quote in the paperNot a substantial claimMay combine two claims.
Interpretationnone givenThe effect of an inherited variant is limited by natural selection and pleiotropy, whereas the effect of a drug treatment is not.
“This is because the effect of an inherited variant is limited by natural selection and pleiotropy, whereas the effect of a drug treatment is not.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationHobbs and Cohen identified low-frequency common variants in PCSK9 at 0.5 to 1%, which allowed epidemiological research documenting a protective effect on myocardial infarction.
“Hobbs and Cohen sequenced the gene (126, 127) and identified low-frequency common variants (0.5 to 1%), which allowed epidemiological research documenting a protective effect on myocardial infarction (128).”
Quote in the paperSubstantial claim0 of 3 sources checked- cites [126] Kotowski IK Am. J. Hum. Genet 2006 78 410 16465619 PMC1380285 source
Not checked in the free run.
- cites [127] Cohen J Nat. Genet 2005 37 161 15654334 source
Not checked in the free run.
- cites [128] Cohen JC Boerwinkle E Mosley TH Jr Hobbs HH N. Engl. J. Med 2006 354 1264 16554528 source
Not checked in the free run.
May combine two claims.
PremisereasoningSNPs in HMGCR have only a small effect (~5%) on LDL levels, whereas drugs targeting the encoded protein decrease LDL levels by a much greater extent (~30%).
“Although SNPs in HMGCR have only a small effect (~5%) on LDL levels, drugs targeting the encoded protein decrease LDL levels by a much greater extent (~30%).”
Quote in the paperSubstantial claim0 of 2 sources checkedMay combine two claims.
InterpretationcitationSome regions reveal surprising associations; unexpected connections have emerged among T2D, inflammatory diseases (two loci), and cancer (four loci), including CDKAL1, GCKR, TCF2, JAZF1, and TCF7L2.
“5) Some regions reveal surprising associations. For example, unexpected connections have emerged among T2D, inflammatory diseases (two loci), and cancer (four loci). A single intron of CDKAL1 was found to contain a SNP associated with T2D and insulin secretion defects (99–101, 116), and another with Crohn’s disease and psoriasis (117).”
Quote in the paperSubstantial claim0 of 5 sources checked- cites [99] Zeggini E Science 2007 316 1336 published online 25 April 2007 17463249 PMC3772310 source
Not checked in the free run.
- cites [100] Scott LJ Science 2007 316 1341 published online 25 April 2007 17463248 PMC3214617 source
Not checked in the free run.
- cites [101] Diabetes Genetics Initiative of Broad Institute of Harvard MIT, Lund University, Novartis Institutes for BioMedical Research Science 2007 316 1331 published online 26 April 2007
Couldn’t be matched to a paper in Crossref, so it can’t be checked.
- cites [116] Steinthorsdottir V Nat. Genet 2007 39 770 17460697 source
Not checked in the free run.
- cites [117] Wolf N J. Med. Genet 2008 45 114 17993580 source
Not checked in the free run.
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenSome disease loci will contain only rare variants.
“Some disease loci will contain only rare variants.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningCurrent studies are underpowered for the types of SNP alleles that we now know exist, and available evidence indicates that increasing sample size will yield substantial returns.
“Current studies are underpowered for the types of SNP alleles that we now know exist, and available evidence indicates that increasing sample size will yield substantial returns.”
Quote in the paperSubstantial claimMay combine two claims.
InterpretationreasoningThe very rare PCSK9 mutations are too rare and the high-frequency common variants too weak to enable effective clinical study of PCSK9 with respect to coronary artery disease risk.
“The former are too rare and the latter too weak to enable effective clinical study of PCSK9 with respect to coronary artery disease risk.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningRare coding mutations with large effect will be especially valuable because physiological studies of mutation carriers can help illuminate the biological basis of the disease, and because coding mutations of large effect are more straightforwardly transferred to cellular and animal models for mechanistic studies.
“Rare coding mutations with large effect will be especially valuable, because physiological studies of mutation carriers can help illuminate the biological basis of the disease, and because coding mutations of large effect are more straightforwardly transferred to cellular and animal models for mechanistic studies.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenExtending GWASs to include structural variants and lower-frequency common variants will require comprehensive catalogs of genomic variation, as well as characterization of LD relationships.
“Extending GWASs to include structural variants and lower-frequency common variants will require comprehensive catalogs of genomic variation, as well as characterization of LD relationships.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenA particular challenge will be to identify mutations in regions without known function or evolutionary conservation.
“A particular challenge will be to identify mutations in regions without known function or evolutionary conservation.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing). May combine two claims.
InterpretationcitationUseful tools will include maps of evolutionary conservation and chromatin state, as well as databases of cell-state signatures, such as genome-wide expression patterns.
“Useful tools will include maps of evolutionary conservation (108) and chromatin state (140), as well as databases of cell-state signatures, such as genome-wide expression patterns, that may integrate aspects of cell biology under resting and provoked conditions (141).”
Quote in the paperNot a substantial claim0 of 3 sources checkedProbably not a substantial claim: may not pass S4 (based).
Premisenone givenThe high failure rate of clinical trials testifies to the limited predictive value of current approaches.
“The high failure rate of clinical trials testifies to the limited predictive value of current approaches.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing).
Interpretationnone givenInitially, resequencing of coding exons will be easiest to interpret.
“Initially, resequencing of coding exons will be easiest to interpret.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenGenetic effects will likely vary across groups because of modification by environment and behavior, which may vary more across groups than does genotype.
“Genetic effects will likely vary across groups because of modification by environment and behavior, which may vary more across groups than does genotype.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Premisenone givenNearly all GWASs to date have been performed in populations of European ancestry.
“Nearly all GWASs to date have been performed in populations of European ancestry.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Interpretationnone givenWith new massively parallel sequencing technologies, an accurate map of all 1% alleles (both single-nucleotide and structural) should be achievable.
“With new massively parallel sequencing technologies, an accurate map of all 1% alleles (both single-nucleotide and structural) should be achievable.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningBy focusing attention on genes and processes, human genetics has the potential to yield productive targets and predictive animal models.
“By focusing attention on genes and processes, human genetics has the potential to yield productive targets and predictive animal models.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenPhysiological studies in patients classified by genotype may inform disease processes and lead to useful nongenetic biomarkers.
“Physiological studies in patients classified by genotype may inform disease processes and lead to useful nongenetic bio-markers.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Interpretationnone givenSome loci may harbor neither common variants nor rare structural variants, and thus will be missed by array and LD-based approaches.
“Some loci may harbor neither common variants nor rare structural variants, and thus will be missed by array and LD-based approaches.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
Interpretationnone givenRoutine genome sequencing of deeply phenotyped cohorts will fundamentally change the nature of genetic mapping from a serial process to a joint estimation procedure combining variation information of all types, frequencies, and phenotypes.
“Routine genome sequencing of deeply phenotyped cohorts will fundamentally change the nature of genetic mapping: from the current serial process (in which initial localization by linkage or GWAS is followed by scrutiny of DNA variation and phenotypes) to a joint estimation procedure combining variation information of all types, frequencies, and phenotypes to discover and characterize genotype-pheno”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable). May combine two claims.
InterpretationreasoningKnowledge of a common variant that increases T2D risk by 20% may eventually lead to new understanding and therapeutic strategies, but whether an increase in absolute risk from 8% to 10% is useful for patients remains to be seen.
“Knowledge of a common variant that increases T2D risk by 20% may eventually lead to new understanding and therapeutic strategies, but whether an increase in absolute risk (from 8% to 10%) is useful for patients remains to be seen.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenAlthough it is tempting to think that knowledge of individual risk might promote greater adherence to a healthy lifestyle, human behavior is complex and risk estimates are challenging to interpret.
“Although it is tempting to think that knowledge of individual risk might promote greater adherence to a healthy lifestyle, human behavior is complex and risk estimates are challenging to interpret.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
InterpretationreasoningInitial studies will likely focus on exons, where functional mutations are enriched to the greatest extent.
“Initial studies will likely focus on exons, where functional mutations are enriched to the greatest extent.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenOur understanding of complex disease will be in constant flux over the coming years.
“Our understanding of complex disease will be in constant flux over the coming years.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
InterpretationreasoningGiven the limits of human clinical research, rare alleles of strong effect may be more useful than common alleles of weak effect.
“Given the limits of human clinical research, rare alleles of strong effect may be more useful than common alleles of weak effect.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based). May combine two claims.
Interpretationnone givenIt will be a challenge for the public to understand the difference between relative and absolute risk, and to figure in their thinking the larger component of genetic and environmental factors not yet captured by today's technologies.
“It will be a challenge for the public to understand the difference between relative and absolute risk, and to figure in their thinking the larger component of genetic and environmental factors not yet captured by today’s technologies.”
Quote in the paperNot a substantial claimMay combine two claims.
InterpretationreasoningThe SORT1 association provides increased statistical confidence, a biomarker for gene function, and pathophysiological insight.
“this provides not only increased statistical confidence, but also a biomarker for gene function and pathophysiological insight.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThere may be inherent limits to our ability to relate phenotypic variation and genotypic variation.
“There may be inherent limits to our ability to relate phenotypic variation and genotypic variation.”
Quote in the paperNot a substantial claimMay combine two claims.
PremisecitationNewly described variants on chromosome 1 near SORT1 are associated both with levels of LDL cholesterol and with risk of myocardial infarction.
“For example, newly described variants on chromosome 1 (near SORTI) are associated both with levels of LDL cholesterol (84, 85) and with risk of myocardial infarction (106);”
Quote in the paperNot a substantial claim0 of 3 sources checked- cites [84] Kathiresan S Nat. Genet 2008 40 189 18193044 PMC2682493 source
Not checked in the free run.
- cites [85] Willer CJ Nat. Genet 2008 40 161 18193043 PMC5206900 source
Not checked in the free run.
- cites [106] Samani NJ N. Engl. J. Med 2007 357 443 17634449 PMC2719290 source
Not checked in the free run.
Probably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe ability to measure genotype now far exceeds our ability to measure phenotype.
“The ability to measure genotype now far exceeds our ability to measure phenotype.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim.
Interpretationnone givenEven where genotype can predict response to a drug with a narrow therapeutic window, it cannot be assumed that genetic testing will necessarily lead to improved clinical outcomes.
“Even where genotype can predict response to a drug with a narrow therapeutic window, it cannot be assumed that genetic testing will necessarily lead to improved clinical outcomes.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenEventually, it will become practical to resequence entire genomes from thousands of cases and controls.
“Eventually, it will become practical to resequence entire genomes from thousands of cases and controls.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationA "1000 Genomes Project" was recently launched toward this end.
“A “1000 Genomes Project” was recently launched toward this end (138).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [138] 1000 Genomes (www.1000genomes.org)
Not checked in the free run.
Probably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningNew statistical methods will be required to combine evidence from rare and common alleles at a locus and across multiple loci, phenotypes, and nongenetic exposures.
“New statistical methods will be required to combine evidence from rare and common alleles at a locus and across multiple loci, phenotypes, and nongenetic exposures.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
Interpretationnone givenGenetic mapping is only a first step toward biological understanding and clinical application.
“Genetic mapping is only a first step toward biological understanding and clinical application.”
Quote in the paperNot a substantial claimClassified as probably not a substantial claim. May combine two claims.
Interpretationnone givenThe extent to which genetic information will figure in personalized medicine will depend on whether predictive accuracy beyond conventional measures can be attained, and whether there are interventions whose effectiveness is improved by knowledge of a genetic test.
“The extent to which genetic information will figure in “personalized medicine” will depend on whether predictive accuracy beyond conventional measures can be attained, and whether there are interventions whose effectiveness is improved by knowledge of a genetic test.”
Quote in the paperSubstantial claimProbably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenDNA is stable throughout life, with a single physical chemistry that enables generic approaches to measurement.
“DNA is stable throughout life, with a single physical chemistry that enables generic approaches to measurement.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenThe problem of interpretation will be much harder for noncoding functional elements, because it is unclear how to aggregate elements to achieve a large enough target size, or to develop ways to recognize function-altering changes.
“The problem of interpretation will be much harder for noncoding functional elements, because it is unclear either how to aggregate elements to achieve a large enough target size, or to develop ways to recognize function-altering changes.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenIn clinical trials, the ability to stratify patients by genotype or biological pathway may reveal differences in therapeutic response.
“In clinical trials, the ability to stratify patients by genotype or biological pathway may reveal differences in therapeutic response.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningBecause the prior probability of a true association is higher, such regions will be the best setting to develop methods for understanding the statistical significance and biological importance of rare mutations.
“Because the prior probability of a true association is higher, such regions will be the best setting to develop methods for understanding the statistical significance and biological importance of rare mutations.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable).
InterpretationreasoningThe lowest-hanging fruit will be to resequence loci that have been definitively implicated in disease by Mendelian genetics or by GWAS.
“The lowest-hanging fruit will be to resequence loci that have been definitively implicated in disease by Mendelian genetics or by GWAS.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based).
InterpretationreasoningTo the extent that disease is influenced by tiny effects at hundreds of loci or highly heterogeneous rare mutations, it may be impractical to assemble sufficiently large samples to give a complete accounting.
“To the extent that disease is influenced by tiny effects at hundreds of loci or highly heterogeneous rare mutations, it may be impractical to assemble sufficiently large samples to give a complete accounting.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S3 (load-bearing), S4 (based).
Interpretationnone givenCreation of disease models, both in human cell culture and nonhuman animals, will be key.
“Creation of disease models, both in human cell culture and nonhuman animals, will be key.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S4 (based).
Interpretationnone givenGenetics may increase the efficiency of outcome trials by focusing on patients at higher-than-average risk.
“Genetics may also increase the efficiency of outcome trials by focusing on patients at higher-than-average risk.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S2 (checkable), S4 (based). May combine two claims.
Interpretationnone givenAlthough genes play a role and can lead to new biological insight, our traits are powerfully shaped by the environment, and the solutions to important problems will often lie outside our genes.
“We must constantly remind the public—and ourselves— that although genes play a role (and can lead us to new biological insight), our traits are powerfully shaped by the environment, and the solutions to important problems will often lie outside our genes.”
Quote in the paperNot a substantial claim- Rests on an assumption: Environmental exposures play a larger role in human phenotypic variation than does genetic variation.
Probably not a substantial claim: may not pass S3 (load-bearing).
PremisecitationHighly parallel methods to capture hundreds of thousands of exons, and other targets of interest, are under development.
“Highly parallel methods to capture hundreds of thousands of exons, and other targets of interest, are under development (139).”
Quote in the paperNot a substantial claim0 of 1 sources checked- cites [139] Albert TJ Nat. Methods 2007 4 903 17934467 source
Not checked in the free run.
Probably not a substantial claim: may not pass S4 (based). May combine two claims.
Premisenone givenEnvironmental exposures are heterogeneous and may be fleeting.
“Environmental exposures are heterogeneous and may be fleeting.”
Quote in the paperNot a substantial claimProbably not a substantial claim: may not pass S3 (load-bearing), S4 (based).
Premisenone givenDirect-to-consumer marketing of genetic information is already under way.
“Direct-to-consumer marketing of genetic information is already under way.”
Quote in the paperNot a substantial claim
The paper relies on this without support.
Common forms of human diseases such as diabetes, heart disease, and cancer show complex inheritance in the general population.
“common forms of human diseases—such as diabetes, heart disease, and cancer—that show complex inheritance in the general population.”
The paper relies on this without support.
The human population has recently grown exponentially from a small size.
“The human population has recently grown exponentially from a small size.”
The paper relies on this without support.
Common diseases often have late onset, with modest or no obvious impact on reproductive fitness.
“Common diseases often have late onset, with modest or no obvious impact on reproductive fitness.”
The paper relies on this without support.
Common diseases show familial clustering.
“Geneticists were eager to apply genetic mapping to common diseases, which also show familial clustering.”
The paper relies on this without support.
Alleles with strong deleterious effects are constrained by natural selection from becoming too common.
“Alleles with strong deleterious effects are constrained by natural selection from becoming too common.”
The paper relies on this without support.
Most Mendelian diseases involve rare mutations that are essentially never observed in the general population.
“Most Mendelian diseases involve rare mutations that are essentially never observed in the general population.”
The paper relies on this without support.
Gene-gene and gene-environment interactions play important roles in disease risk.
“Yet gene-gene and gene-environment interactions play important roles in disease risk.”
The paper relies on this without support.
Environmental exposures play a larger role in human phenotypic variation than does genetic variation.
“Environmental exposures play a larger role in human phenotypic variation than does genetic variation, but environmental exposures are fundamentally more difficult to measure.”
The paper relies on this without support.
The human mutation rate is in the range of 10−8.
“because the human mutation rate is so low (in the range of 10−8).”
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Candidate gene studies often assess genes that have broad relevance to the immune system but do not drive disease risk per se.
“often assess genes that have broad relevance to the immune system but do not drive disease risk per se.22”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [22]
In “Genetic association in populations” (page unavailable), the paper says candidate-gene studies tested biological candidates with a low prior probability of being disease-causing, and that few reported associations were replicated. It does not say those candidates were often genes with broad immune-system relevance, or establish that the genes themselves did not affect disease risk. (LLM, conf=0.85)
Experimental — accuracy not yet measuredCandidate gene studies are underpowered to detect risk alleles for common complex disease.
“such studies are underpowered to detect risk alleles for common complex disease”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [22]
In “Statistical analysis” (page unavailable), the paper says four modest-sized replication studies lacked adequate power to detect a type 2 diabetes risk variant. But “Genetic association in populations” (page unavailable) describes the broader problem with candidate-gene studies as their limited choice of variants and weak statistical support; it does not say candidate-gene studies generally were underpowered to detect risk alleles for common complex disease. (LLM, conf=0.84)
Experimental — accuracy not yet measuredNon-MHC multiple sclerosis risk alleles have modest effects on disease, with odds ratios less than 1.2.
“These studies collectively showed that non‐MHC MS risk alleles have modest effects on disease (odds ratios < 1.2)”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [22]
The “Genome-Wide Associations: Lessons” section says common risk variants typically have modest effects. It gives a general risk-increase range of 1.1 to 1.5 per allele, however, and does not establish that non-MHC multiple sclerosis alleles specifically have odds ratios below 1.2. (LLM, conf=0.83)
Experimental — accuracy not yet measuredEven larger sample sizes, over 10,000 cases and controls, would be needed to identify more multiple sclerosis risk loci.
“and that even larger sample sizes (over 10 000 cases and controls) would be needed to identify more loci.22”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [22]
In “Genome-Wide Associations: Lessons” (page unavailable), the paper says larger studies can identify additional disease-associated loci. “Expanding clinical studies” (page unavailable) likewise says increasing sample size should yield substantial returns, but it does not specify multiple sclerosis or say that over 10,000 cases and controls would be needed. (LLM, conf=0.85)
Experimental — accuracy not yet measuredIdentifying causal variants in genome-wide association study loci through fine mapping remains difficult because linkage disequilibrium means many variants show evidence of association to disease, but only one is likely to be the causal one.
“Firstly, identifying the causal variants in GWAS loci through fine mapping remains difficult: linkage disequilibrium means that many variants will show evidence of association to disease, but only one is likely to be the causal one.”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [22]
Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.
Experimental — accuracy not yet measured
A limitation of GWAS is that it only reports the sentinel SNP, which serves as a tag for all other variants in LD; any one could be causal.
“A limitation of GWAS is that the approach only reports the sentinel single nucleotide polymorphism (SNP) at a given locus, which serves as a tag for all other variants in LD; as such, among this entire LD series of proxy SNPs, any one (or more) could be causal15.”
From Variant-to-function mapping of late-onset Alzheimer’s disease GWAS signals in human microglial cell models implicates <i>RTFDC1</i> at the <i>CASS4</i> locus (2024) · cites this paper as [15]
In “Cataloging SNPs and linkage disequilibrium” (page unavailable), the paper explains that tag SNPs can act as proxies for nearby variants. In “Genome-Wide Associations: Lessons” (page unavailable), it says association signals often do not identify the causal mutation, which may even be a non-SNP variant. It does not support the absolute claim that GWAS reports only one sentinel SNP per locus or that the sentinel tags all other variants in LD. (LLM, conf=0.86)
Experimental — accuracy not yet measuredCandidate gene studies suffer from population stratification and other artefacts.
“suffer from population stratification and other artefacts”
From Genome‐wide association studies of multiple sclerosis (2018) · cites this paper as [22]
The power to detect an association between a single rare variant is low even in very large samples.
“Association analyses involving rare variants are not as straightforward as analyses involving common variations since the power to detect an association between a single rare variant is low in even very large samples (Figure 1).14, 28, 29”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [29]
Testing rare variants individually with standard contingency table and regression methods is highly problematic because such tests have poor power to detect small rare variant frequency differences between groups.
“This strategy is highly problematic given, for example, the poor power that such statistical tests have to detect small rare variant frequency differences between diagnostic or phenotypic groups (figures 1A and 1B).14, 28, 29”
From Statistical analysis strategies for association studies involving rare variants (2010) · cites this paper as [29]
Typically, candidate genes for AMD have been selected based on a priori knowledge of the biological pathways involved in disease or on investigator prejudices about the pathways likely to contribute to disease susceptibility.
“Typically, these genes have been selected based on a priori knowledge of the biological pathways involved in disease or on investigator prejudices about the pathways likely to contribute to disease susceptibility (7, 149).”
From Unraveling a Multifactorial Late-Onset Disease: From Genetic Susceptibility to Disease Mechanisms for Age-Related Macular Degeneration (2009) · cites this paper as [7]
Cites
Principal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248 · see citing works
Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls
The Wellcome Trust Case Control Consortium, Management Committee, Burton, P. R., Clayton, D. G., Cardon, L. R., Craddock, N., Deloukas, P., Duncanson, A., Kwiatkowski, D. P., McCarthy, M. I., et al. (2007) · Nature · doi:10.1038/nature05911 · Cited by 9,442 · see citing works
Construction of a genetic linkage map in man using restriction fragment length polymorphisms.
Botstein, D., White, R. L., Skolnick, M. H., & Davis, R. W. (1980) · Europe PMC (PubMed Central) · Cited by 8,327 · see citing works
Initial sequencing and comparative analysis of the mouse genome
Mouse Genome Sequencing Consortium (2002) · Nature · doi:10.1038/nature01262 · Cited by 7,187 · see citing works
Davey Smith, G., & Ebrahim, S. (2003) · International Journal of Epidemiology · doi:10.1093/ije/dyg070 · Cited by 5,882 · see citing works
The Structure of Haplotype Blocks in the Human Genome
Gabriel, S. B., Schaffner, S. F., Nguyen, H., Moore, J. M., Roy, J., Blumenstiel, B., Higgins, J., DeFelice, M., Lochner, A., Faggart, M., et al. (2002) · Science · doi:10.1126/science.1069424 · Cited by 5,863 · see citing works
Self-citationA haplotype map of the human genome
The International HapMap Consortium (2005) · Nature · doi:10.1038/nature04226 · Cited by 5,858 · see citing works
The Future of Genetic Studies of Complex Human Diseases
Risch, N., & Merikangas, K. (1996) · Science · doi:10.1126/science.273.5281.1516 · Cited by 5,355 · see citing works
Lamb, J., Crawford, E. D., Peck, D., Modell, J. W., Blat, I. C., Wrobel, M. J., Lerner, J., Brunet, J.-P., Subramanian, A., Ross, K. N., et al. (2006) · Science · doi:10.1126/science.1132939 · Cited by 5,257 · see citing works
Self-citationComplement factor H polymorphism in age-related macular degeneration
Klein, R. J., Zeiss, C., Chew, E. Y., Tsai, J.-Y., Sackler, R. S., Haynes, C., Henning, A. K., SanGiovanni, J. P., Mane, S. M., Mayne, S. T., et al. (2005) · Science · doi:10.1126/science.1109557 · Cited by 4,492 · see citing works
A second generation human haplotype map of over 3.1 million SNPs
The International HapMap Consortium (2007) · Nature · doi:10.1038/nature06258 · Cited by 4,438 · see citing works
Global variation in copy number in the human genome
Redon, R., Ishikawa, S., Fitch, K. R., Feuk, L., Perry, G. H., Andrews, T. D., Fiegler, H., Shapero, M. H., Carson, A. R., Chen, W., et al. (2006) · Nature · doi:10.1038/nature05329 · Cited by 4,276 · see citing works
Identification of the Cystic Fibrosis Gene: Genetic Analysis
Kerem, B.-S., Rommens, J. M., Buchanan, J. A., Markiewicz, D., Cox, T. K., Chakravarti, A., Buchwald, M., & Tsui, L.-C. (1989) · Science · doi:10.1126/science.2570460 · Cited by 4,142 · see citing works
Genome-wide maps of chromatin state in pluripotent and lineage-committed cells
Mikkelsen, T. S., Ku, M., Jaffe, D. B., Issac, B., Lieberman, E., Giannoukos, G., Alvarez, P., Brockman, W., Kim, T.-K., Koche, R. P., et al. (2007) · Nature · doi:10.1038/nature06008 · Cited by 4,129 · see citing works
Self-citationSpielman, R. S., McGinnis, R. E., & Ewens, W. J. (1993) · PubMed · Cited by 3,679 · see citing works
Update on Key Emerging Challenges in Cystic Fibrosis
Jennings, M. T., Riekert, K. A., & Boyle, M. (2014) · Medical Principles and Practice · doi:10.1159/000357646 · Cited by 3,667 · see citing works
Sequence Variations in <i>PCSK9,</i> Low LDL, and Protection against Coronary Heart Disease
Cohen, J. C., Boerwinkle, E., Mosley, T. H., & Hobbs, H. H. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa054013 · Cited by 3,181 · see citing works
Genomic Control for Association Studies
Devlin, B., & Roeder, K. (1999) · Biometrics · doi:10.1111/j.0006-341x.1999.00997.x · Cited by 3,162 · see citing works
A Genome-Wide Association Study Identifies <i>IL23R</i> as an Inflammatory Bowel Disease Gene
Duerr, R. H., Taylor, K. D., Brant, S. R., Rioux, J. D., Silverberg, M. S., Daly, M. J., Steinhart, A. H., Abraham, C., Regueiro, M., Griffiths, A., et al. (2006) · Science · doi:10.1126/science.1135245 · Cited by 3,039 · see citing works
Self-citationA genome-wide association study identifies novel risk loci for type 2 diabetes
Sladek, R., Rocheleau, G., Rung, J., Dina, C., Shen, L., Serre, D., Boutin, P., Vincent, D., Belisle, A., Hadjadj, S., et al. (2007) · Nature · doi:10.1038/nature05616 · Cited by 2,993 · see citing works
A map of human genome sequence variation containing 1.42 million single nucleotide polymorphisms
The International SNP Map Working Group, Laboratories:, C. S. H., Sachidanandam, R., Weissman, D., Schmidt, S. C., Kakol, J. M., Stein, L. D., National Center for Biotechnology Information:, Marth, G., Sherry, S., et al. (2001) · Nature · doi:10.1038/35057149 · Cited by 2,977 · see citing works
Self-citationA comprehensive genetic map of the human genome based on 5,264 microsatellites
Dib, C., Fauré, S., Fizames, C., Samson, D. S., Drouot, N., Alain Vignal, A., Millasseau, P., Marc, S., Kazan, J., Seboun, E., et al. (1996) · Nature · doi:10.1038/380152a0 · Cited by 2,927 · see citing works
Detection of large-scale variation in the human genome
Iafrate, A. J., Feuk, L., Rivera, M. N., Listewnik, M. L., Donahoe, P. K., Qi, Y., Scherer, S. W., & Lee, C. (2004) · Nature Genetics · doi:10.1038/ng1416 · Cited by 2,892 · see citing works
Genome-wide association analysis identifies loci for type 2 diabetes and triglyceride levels
Saxena, R., Voight, B. F., Lyssenko, V., Burtt, N. P., de Bakker, P. I. W., Chen, H., Roix, J. J., Kathiresan, S., Hirschhorn, J. N., Daly, M. J., et al. (2007) · Science · doi:10.1126/science.1142358 · Cited by 2,843 · see citing works
Self-citationStrong association of de novo copy number mutations with autism
Sebat, J., Lakshmi, B., Malhotra, D., Troge, J., Lese-Martin, C., Walsh, T., Yamrom, B., Yoon, S., Krasnitz, A., Kendall, J., et al. (2007) · Science · doi:10.1126/science.1138659 · Cited by 2,795 · see citing works
A genome-wide association study of type 2 diabetes in Finns detects multiple susceptibility variants
Scott, L. J., Mohlke, K. L., Bonnycastle, L. L., Willer, C. J., Li, Y., Duren, W. L., Erdos, M. R., Stringham, H. M., Chines, P. S., Jackson, A. U., et al. (2007) · Science · doi:10.1126/science.1142382 · Cited by 2,753 · see citing works
The Wellcome Trust Case Control Consortium, U.K.
Mossman, K. (2008) · Scientific American · doi:10.1038/scientificamerican0108-42a · Cited by 2,714 · see citing works
A new multipoint method for genome-wide association studies by imputation of genotypes
Marchini, J., Howie, B., Myers, S., McVean, G., & Donnelly, P. (2007) · Nature Genetics · doi:10.1038/ng2088 · Cited by 2,609 · see citing works
Genome-wide association defines more than 30 distinct susceptibility loci for Crohn's disease
the NIDDK IBD Genetics Consortium, Barrett, J. C., the Belgian-French IBD Consortium, the Wellcome Trust Case Control Consortium, Hansoul, S., Nicolae, D. L., Cho, J. H., Duerr, R. H., Rioux, J. D., Brant, S. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.175 · Cited by 2,593 · see citing works
Self-citationLarge-scale copy number polymorphism in the human genome
Sebat, J., Lakshmi, B., Troge, J., Alexander, J., Young, J., Lundin, P., Månér, S., Massa, H., Walker, M., Chi, M., et al. (2004) · Science · doi:10.1126/science.1098918 · Cited by 2,557 · see citing works
Naehrlich, L., Mainz, J. G., Adams, C., Engel, C., Herrmann, G., Icheva, V., Lauer, J., Deppisch, C., Wirth, A., Unger, K., et al. (2013) · Cellular Physiology and Biochemistry · doi:10.1159/000350071 · Cited by 2,535 · see citing works
Complement factor H polymorphism and age-related macular degeneration
Edwards, A. O., Ritter, R., Abel, K. J., Manning, A., Panhuysen, C., & Farrer, L. A. (2005) · Science · doi:10.1126/science.1110189 · Cited by 2,449 · see citing works
Complement factor H variant increases the risk of age-related macular degeneration
Haines, J. L., Hauser, M. A., Schmidt, S., Scott, W. K., Olson, L. M., Gallins, P., Spencer, K. L., Kwan, S. Y., Noureddine, M., Gilbert, J. R., et al. (2005) · Science · doi:10.1126/science.1110359 · Cited by 2,424 · see citing works
A polymorphic DNA marker genetically linked to Huntington's disease
Gusella, J. F., Wexler, N. S., Conneally, P. M., Naylor, S. L., Anderson, M. A., Tanzi, R. E., Watkins, P. C., Ottina, K. A., Wallace, M. R., Sakaguchi, A. Y., et al. (1983) · Nature · doi:10.1038/306234a0 · Cited by 2,340 · see citing works
Genome-wide association study identifies novel breast cancer susceptibility loci
Easton, D. F., Pooley, K. A., Dunning, A. M., Pharoah, P. D. P., Thompson, D., Ballinger, D. G., Struewing, J. P., Morrison, J., Field, H., Luben, R., et al. (2007) · Nature · doi:10.1038/nature05887 · Cited by 2,319 · see citing works
Variant of transcription factor 7-like 2 (TCF7L2) gene confers risk of type 2 diabetes
Grant, S. F. A., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Manolescu, A., Sainz, J., Helgason, A., Stefansson, H., Emilsson, V., Helgadottir, A., et al. (2006) · Nature Genetics · doi:10.1038/ng1732 · Cited by 2,287 · see citing works
Replication of Genome-Wide Association Signals in UK Samples Reveals Risk Loci for Type 2 Diabetes
Zeggini, E., Weedon, M. N., Lindgren, C. M., Frayling, T. M., Elliott, K. S., Lango, H., Timpson, N. J., Perry, J. R. B., Rayner, N. W., Freathy, R. M., et al. (2007) · Science · doi:10.1126/science.1142364 · Cited by 2,194 · see citing works
Wang, D. G., Fan, J., Siao, C.-J., Berno, A. J., Young, P. R., Sapolsky, R., Ghandour, G., Perkins, N., Winchester, E., Spencer, J. B., et al. (1998) · Science · doi:10.1126/science.280.5366.1077 · Cited by 2,162 · see citing works
Self-citationGenomewide Association Analysis of Coronary Artery Disease
Samani, N. J., Erdmann, J., Hall, A. S., Hengstenberg, C., Mangino, M., Mayer, B., Dixon, R. J., Meitinger, T., Braund, P., Wichmann, H.-E., et al. (2007) · New England Journal of Medicine · doi:10.1056/nejmoa072366 · Cited by 2,044 · see citing works
Lohmueller, K. E., Pearce, C. L., Pike, M., Lander, E. S., & Hirschhorn, J. N. (2003) · Nature Genetics · doi:10.1038/ng1071 · Cited by 1,900 · see citing works
Self-citationWellcome Trust Case Control Consortium, Zeggini, E., Scott, L. J., Saxena, R., Voight, B. F., Marchini, J. L., Hu, T., de Bakker, P. I., Abecasis, G. R., Almgren, P., et al. (2008) · Nature Genetics · doi:10.1038/ng.120 · Cited by 1,864 · see citing works
Self-citationRare Structural Variants Disrupt Multiple Genes in Neurodevelopmental Pathways in Schizophrenia
Walsh, T., McClellan, J. M., McCarthy, S. E., Addington, A. M., Pierce, S. B., Cooper, G. M., Nord, A. S., Kusenda, M., Malhotra, D., Bhandari, A., et al. (2008) · Science · doi:10.1126/science.1155174 · Cited by 1,800 · see citing works
Rioux, J. D., Xavier, R. J., Taylor, K. D., Silverberg, M. S., Goyette, P., Huett, A., Green, T., Kuballa, P., Barmada, M. M., Datta, L. W., et al. (2007) · Nature Genetics · doi:10.1038/ng2032 · Cited by 1,769 · see citing works
Self-citationThe common PPARγ Pro12Ala polymorphism is associated with decreased risk of type 2 diabetes
Altshuler, D., Hirschhorn, J. N., Klannemark, M., Lindgren, C. M., Vohl, M.-C., Nemesh, J., Lane, C. R., Schaffner, S. F., Bolk, S., Brewer, C., et al. (2000) · Nature Genetics · doi:10.1038/79216 · Cited by 1,766 · see citing works
Self-citationA vision for the future of genomics research
Collins, F. S., Green, E. D., Guttmacher, A. E., Guyer, M. S., & on behalf of the US National Human Genome Research Institute (2003) · Nature · doi:10.1038/nature01626 · Cited by 1,752 · see citing works
Wacholder, S., Chanock, S. J., García‐Closas, M., ghormli, L. K. E., & Rothman, N. (2004) · JNCI Journal of the National Cancer Institute · doi:10.1093/jnci/djh075 · Cited by 1,743 · see citing works
High-resolution haplotype structure in the human genome
Daly, M. J., Rioux, J. D., Schaffner, S. F., Hudson, T. J., & Lander, E. S. (2001) · Nature Genetics · doi:10.1038/ng1001-229 · Cited by 1,717 · see citing works
Self-citationEfficiency and power in genetic association studies
de Bakker, P. I. W., Yelensky, R., Pe’er, I., Gabriel, S., Daly, M. J., & Altshuler, D. (2005) · Nature Genetics · doi:10.1038/ng1669 · Cited by 1,678 · see citing works
Self-citationA comprehensive review of genetic association studies
Hirschhorn, J. N., Lohmueller, K., Byrne, E., & Hirschhorn, K. (2002) · Genetics in Medicine · doi:10.1097/00125817-200203000-00002 · Cited by 1,674 · see citing works
Association between Microdeletion and Microduplication at 16p11.2 and Autism
Weiss, L. A., Shen, Y., Korn, J. M., Arking, D. E., Miller, D. T., Fossdal, R., Saemundsen, E., Stefansson, H., Ferreira, M. A. R., Green, T., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa075974 · Cited by 1,666 · see citing works
Self-citationA Common Variant on Chromosome 9p21 Affects the Risk of Myocardial Infarction
Helgadottir, A., Thorleifsson, G., Manolescu, A., Gretarsdottir, S., Blondal, T., Jonasdottir, A., Jonasdottir, A., Sigurdsson, A., Baker, A., Palsson, A., et al. (2007) · Science · doi:10.1126/science.1142842 · Cited by 1,594 · see citing works
A Common Allele on Chromosome 9 Associated with Coronary Heart Disease
McPherson, R., Pertsemlidis, A., Kavaslar, N., Stewart, A., Roberts, R., Cox, D. R., Hinds, D. A., Pennacchio, L. A., Tybjaerg-Hansen, A., Folsom, A. R., et al. (2007) · Science · doi:10.1126/science.1142447 · Cited by 1,587 · see citing works
Newly identified loci that influence lipid concentrations and risk of coronary artery disease
Willer, C. J., Sanna, S., Jackson, A. U., Scuteri, A., Bonnycastle, L. L., Clarke, R., Heath, S. C., Timpson, N. J., Najjar, S. S., Stringham, H. M., et al. (2008) · Nature Genetics · doi:10.1038/ng.76 · Cited by 1,585 · see citing works
Paterson, A. H., Lander, E. S., Hewitt, J. D., Peterson, S., Lincoln, S. E., & Tanksley, S. D. (1988) · Nature · doi:10.1038/335721a0 · Cited by 1,520 · see citing works
Self-citationProspects for whole-genome linkage disequilibrium mapping of common disease genes
Kruglyak, L. (1999) · Nature Genetics · doi:10.1038/9642 · Cited by 1,416 · see citing works
Kathiresan, S., Melander, O., Guiducci, C., Surti, A., Burtt, N. P., Rieder, M. J., Cooper, G. M., Roos, C., Voight, B. F., Havulinna, A. S., et al. (2008) · Nature Genetics · doi:10.1038/ng.75 · Cited by 1,386 · see citing works
Self-citationCohen, J., Pertsemlidis, A., Kotowski, I. K., Graham, R., Garcia, C. K., & Hobbs, H. H. (2005) · Nature Genetics · doi:10.1038/ng1509 · Cited by 1,381 · see citing works
Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants
Wellcome Trust Case Control Consortium, & The Australo-Anglo-American Spondylitis Consortium (TASC) (2007) · Nature Genetics · doi:10.1038/ng.2007.17 · Cited by 1,374 · see citing works
Deeb, S. S., Fajas, L., Nemoto, M., Pihlajamäki, J., Mykkänen, L., Kuusisto, J., Laakso, M., Fujimoto, W., & Auwerx, J. (1998) · Nature Genetics · doi:10.1038/3099 · Cited by 1,319 · see citing works
Genetics of gene expression and its effect on disease
Emilsson, V., Thorleifsson, G., Zhang, B., Leonardson, A. S., Zink, F., Zhu, J., Carlson, S., Helgason, A., Walters, G. B., Gunnarsdottir, S., et al. (2008) · Nature · doi:10.1038/nature06758 · Cited by 1,296 · see citing works
Whole-Genome Patterns of Common DNA Variation in Three Human Populations
Hinds, D., Stuve, L., Nilsen, G. B., Halperin, E., Eskin, E., Ballinger, D., Frazer, K., & Cox, D. (2005) · Science · doi:10.1126/science.1105436 · Cited by 1,245 · see citing works
Use of Unlinked Genetic Markers to Detect Population Stratification in Association Studies
Pritchard, J. K., & Rosenberg, N. A. (1999) · The American Journal of Human Genetics · doi:10.1086/302449 · Cited by 1,198 · see citing works
On the allelic spectrum of human disease
Reich, D. E., & Lander, E. S. (2001) · Trends in Genetics · doi:10.1016/s0168-9525(01)02410-6 · Cited by 1,185 · see citing works
Self-citationHaplotype tagging for the identification of common disease genes
Johnson, G. C. L., Esposito, L., Barratt, B. J., Smith, A. N., Heward, J., Di Genova, G., Ueda, H., Cordell, H. J., Eaves, I. A., Dudbridge, F., et al. (2001) · Nature Genetics · doi:10.1038/ng1001-233 · Cited by 1,174 · see citing works
The New Genomics: Global Views of Biology
Lander, E. S. (1996) · Science · doi:10.1126/science.274.5287.536 · Cited by 1,174 · see citing works
Self-citationBlocks of Limited Haplotype Diversity Revealed by High-Resolution Scanning of Human Chromosome 21
Patil, N., Berno, A. J., Hinds, D. A., Barrett, W. A., Doshi, J. M., Hacker, C. R., Kautzer, C. R., Lee, D. H., Marjoribanks, C., McDonough, D. P., et al. (2001) · Science · doi:10.1126/science.1065573 · Cited by 1,145 · see citing works
Gene–environment interactions in human diseases
Hunter, D. J. (2005) · Nature Reviews Genetics · doi:10.1038/nrg1578 · Cited by 1,132 · see citing works
Multiple Rare Alleles Contribute to Low Plasma Levels of HDL Cholesterol
Cohen, J. C., Kiss, R. S., Pertsemlidis, A., Marcel, Y. L., McPherson, R., & Hobbs, H. H. (2004) · Science · doi:10.1126/science.1099870 · Cited by 1,108 · see citing works
Systems Biology and New Technologies Enable Predictive and Preventative Medicine
Hood, L., Heath, J. R., Phelps, M. E., & Lin, B. (2004) · Science · doi:10.1126/science.1104635 · Cited by 1,108 · cited 3× · see citing works
“Systems biology provides novel experimental approaches to quantify molecular components of a biologic system, to assess their interactions, and to integrate such information into graphic models that may explain or predict emergent phenomena ( 23 ).”
BackgroundInfluentialCargill, M., Schrodi, S. J., Chang, M., Garcia, V. E., Brandon, R., Callis, K. P., Matsunami, N., Ardlie, K. G., Civello, D., Catanese, J. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/511051 · Cited by 1,086 · see citing works
A variant in CDKAL1 influences insulin response and risk of type 2 diabetes
Steinthorsdottir, V., Thorleifsson, G., Reynisdottir, I., Benediktsson, R., Jonsdottir, T., Walters, G. B., Styrkarsdottir, U., Gretarsdottir, S., Emilsson, V., Ghosh, S., et al. (2007) · Nature Genetics · doi:10.1038/ng2043 · Cited by 1,072 · see citing works
Patterns of linkage disequilibrium in the human genome
Ardlie, K., Kruglyak, L., & Seielstad, M. (2002) · Nature reviews genetics · doi:10.1038/nrg777 · Cited by 1,064 · see citing works
Variations on a Theme: Cataloging Human DNA Sequence Variation
Collins, F. S., Guyer, M. S., & Chakravarti, A. (1997) · Science · doi:10.1126/science.278.5343.1580 · Cited by 1,062 · see citing works
Fine-scale structural variation of the human genome
Tüzün, E., Sharp, A. J., Bailey, J. A., Kaul, R., Morrison, V., Pertz, L. M., Haugen, E., Hayden, H. S., Albertson, D. G., Pinkel, D., et al. (2005) · Nature Genetics · doi:10.1038/ng1562 · Cited by 991 · see citing works
The Fine-Scale Structure of Recombination Rate Variation in the Human Genome
McVean, G., Myers, S. R., Hunt, S. E., Deloukas, P., Bentley, D., & Donnelly, P. (2004) · Science · doi:10.1126/science.1092500 · Cited by 968 · see citing works
Integrated detection and population-genetic analysis of SNPs and copy number variation
McCarroll, S. A., Kuruvilla, F. G., Korn, J. M., Cawley, S., Nemesh, J., Wysoker, A., Shapero, M. H., de Bakker, P. I. W., Maller, J. B., Kirby, A., et al. (2008) · Nature Genetics · doi:10.1038/ng.238 · Cited by 936 · see citing works
Self-citationA genetic linkage map of the human genome
DONISKELLER, H. (1987) · Cell · doi:10.1016/0092-8674(87)90158-9 · Cited by 909 · see citing works
Multiple loci identified in a genome-wide association study of prostate cancer
Thomas, G. D., Jacobs, K. B., Yeager, M., Kraft, P., Wacholder, S., Orr, N., Yu, K. F., Chatterjee, N., Welch, R., Hutchinson, A. A., et al. (2008) · Nature Genetics · doi:10.1038/ng.91 · Cited by 899 · see citing works
A Specific Chemical Difference Between the Globins of Normal Human and Sickle-Cell Anæmia Hæmoglobin
INGRAM, V. M. (1956) · Nature · doi:10.1038/178792a0 · Cited by 896 · see citing works
Genome-wide strategies for detecting multiple loci that influence complex diseases
Marchini, J., Donnelly, P., & Cardon, L. R. (2005) · Nature Genetics · doi:10.1038/ng1537 · Cited by 894 · see citing works
A HapMap harvest of insights into the genetics of common disease
Manolio, T. A., Brooks, L. D., & Collins, F. S. (2008) · Journal of Clinical Investigation · doi:10.1172/jci34772 · Cited by 889 · cited 4× · see citing works
“Stern et al. ( 2 ) found smoking status to be an effect modifier of the association between the XPD codon 751 polymorphism and risk of bladder cancer.”
BackgroundInfluentialROTHMAN, K. J., GREENLAND, S., & WALKER, A. M. (1980) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113015 · Cited by 851 · see citing works
TCF7L2 Polymorphisms and Progression to Diabetes in the Diabetes Prevention Program
Florez, J. C., Jablonski, K. A., Bayley, N., Pollin, T. I., de Bakker, P. I. W., Shuldiner, A. R., Knowler, W. C., Nathan, D. M., & Altshuler, D. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa062418 · Cited by 834 · see citing works
Self-citationGenome-wide association analysis identifies 20 loci that influence adult height
Initiative, D. G., Weedon, M. N., The Wellcome Trust Case Control Consortium, Cambridge GEM Consortium, Lango, H., Lindgren, C. M., Wallace, C., Evans, D. M., Mangino, M., Freathy, R. M., et al. (2008) · Nature Genetics · doi:10.1038/ng.121 · Cited by 826 · see citing works
Rare independent mutations in renal salt handling genes contribute to blood pressure variation
Ji, W., Foo, J. N., O'Roak, B. J., Zhao, H., Larson, M. G., Simon, D. B., Newton-Cheh, C., State, M. W., Levy, D., & Lifton, R. P. (2008) · Nature Genetics · doi:10.1038/ng.118 · Cited by 812 · see citing works
Kan, Y., & Dozy, A. M. (1978) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.75.11.5631 · Cited by 804 · see citing works
Rivera, A., Fisher, S. A., Fritsche, L. G., Keilhauer, C. N., Lichtner, P., Meitinger, T., & Weber, B. H. F. (2005) · Human Molecular Genetics · doi:10.1093/hmg/ddi353 · Cited by 788 · see citing works
A common variant associated with prostate cancer in European and African populations
Amundadottir, L. T., Sulem, P., Gudmundsson, J., Helgason, A., Baker, A., Agnarsson, B. A., Sigurdsson, A., Benediktsdottir, K. R., Cazier, J.-B., Sainz, J., et al. (2006) · Nature Genetics · doi:10.1038/ng1808 · Cited by 787 · see citing works
Pe'er, I., Yelensky, R., Altshuler, D., & Daly, M. J. (2008) · Genetic Epidemiology · doi:10.1002/gepi.20303 · Cited by 783 · see citing works
Self-citationAn STS-Based Map of the Human Genome
Hudson, T. J., Stein, L. D., Gerety, S. S., Ma, J., Castle, A. B., Silva, J., Slonim, D. K., Baptista, R., Kruglyak, L., Xu, S., et al. (1995) · Science · doi:10.1126/science.270.5244.1945 · Cited by 773 · see citing works
Self-citationSturtevant, A. H. (1913) · Journal of Experimental Zoology · doi:10.1002/jez.1400140104 · Cited by 766 · see citing works
Gudmundsson, J., Sulem, P., Steinthorsdottir, V., Bergthorsson, J. T., Thorleifsson, G., Manolescu, A., Rafnar, T., Gudbjartsson, D., Agnarsson, B. A., Baker, A., et al. (2007) · Nature Genetics · doi:10.1038/ng2062 · Cited by 723 · see citing works
Common deletion polymorphisms in the human genome
McCarroll, S. A., Hadnott, T. N., Perry, G. H., Sabeti, P. C., Zody, M. C., Barrett, J. C., Dallaire, S., Gabriel, S. B., Lee, C., Daly, M. J., et al. (2006) · Nature Genetics · doi:10.1038/ng1696 · Cited by 701 · see citing works
Self-citationDirect selection of human genomic loci by microarray hybridization
Albert, T. J., Molla, M. N., Muzny, D. M., Nazareth, L., Wheeler, D., Song, X., Richmond, T. A., Middle, C. M., Rodesch, M. J., Packard, C. J., et al. (2007) · Nature Methods · doi:10.1038/nmeth1111 · Cited by 681 · see citing works
Common Sequence Variants in the <i>LOXL1</i> Gene Confer Susceptibility to Exfoliation Glaucoma
Thorleifsson, G., Magnusson, K. P., Sulem, P., Walters, G. B., Gudbjartsson, D. F., Stefansson, H., Jonsson, T., Jonasdottir, A., Jonasdottir, A., Stefansdottir, G., et al. (2007) · Science · doi:10.1126/science.1146554 · Cited by 677 · see citing works
Many sequence variants affecting diversity of adult human height
Gudbjartsson, D. F., Walters, G. B., Þorleifsson, G., Stefánsson, H., Halldórsson, B. V., Zusmanovich, P., Sulem, P., Thorlacius, S., Gylfason, A., Steinberg, S., et al. (2008) · Nature Genetics · doi:10.1038/ng.122 · Cited by 666 · see citing works
Multiple regions within 8q24 independently affect risk for prostate cancer
Haiman, C. A., Patterson, N., Freedman, M. L., Myers, S. R., Pike, M. C., Waliszewska, A., Neubauer, J., Tandon, A., Schirmer, C., McDonald, G. J., et al. (2007) · Nature Genetics · doi:10.1038/ng2015 · Cited by 663 · see citing works
Self-citationDeletion polymorphism upstream of IRGM associated with altered IRGM expression and Crohn's disease
McCarroll, S. A., Huett, A., Kuballa, P., Chilewski, S. D., Landry, A., Goyette, P., Zody, M. C., Hall, J. L., Brant, S. R., Cho, J. H., et al. (2008) · Nature Genetics · doi:10.1038/ng.215 · Cited by 655 · see citing works
Self-citationBRCA1 and BRCA2 and the genetics of breast and ovarian cancer
Welcsh, P. L. (2001) · Human Molecular Genetics · doi:10.1093/hmg/10.7.705 · Cited by 648 · see citing works
García‐Closas, M., Malats, N., Silverman, D. T., Dosemeci, M., Kogevinas, M., Hein, D. W., Tardón, A., Serra, C., Carrato, A., García-Closas, R., et al. (2005) · The Lancet · doi:10.1016/s0140-6736(05)67137-1 · Cited by 627 · see citing works
Polygenes, Risk Prediction, and Targeted Prevention of Breast Cancer
Pharoah, P. D. P., Antoniou, A. C., Easton, D. F., & Ponder, B. A. J. (2008) · New England Journal of Medicine · doi:10.1056/nejmsa0708739 · Cited by 616 · see citing works
Molecular Genetics of the Bithorax Complex in Drosophila melanogaster
Bender, W. W., Akam, M. E., Karch, F., Beachy, P. A., Peifer, M. A., Spierer, P., Lewis, E. B., & Hogness, D. S. (1983) · Science · doi:10.1126/science.221.4605.23 · Cited by 612 · see citing works
Admixture mapping identifies 8q24 as a prostate cancer risk locus in African-American men
Freedman, M. L., Haiman, C. A., Patterson, N., McDonald, G. J., Tandon, A., Waliszewska, A., Penney, K., Steen, R. G., Ardlie, K., John, E. M., et al. (2006) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0605832103 · Cited by 612 · see citing works
Self-citationC. Genetics of Man Enzyme polymorphisms in man
Harris, H. (1966) · Proceedings of the Royal Society of London. Series B. Biological Sciences · doi:10.1098/rspb.1966.0032 · Cited by 611 · see citing works
Maller, J., George, S., Purcell, S., Fagerness, J., Altshuler, D., Daly, M. J., & Seddon, J. M. (2006) · Nature Genetics · doi:10.1038/ng1873 · Cited by 599 · see citing works
Self-citationIdentification of ten loci associated with height highlights new biological pathways in human growth
Initiative, T. D. G., Lettre, G., FUSION, KORA, The Prostate, L. C. A. O. C. S. T., Study, T. N. H., SardiNIA, Jackson, A., Gieger, C., Schumacher, F. R., et al. (2008) · Nature Genetics · doi:10.1038/ng.125 · Cited by 583 · see citing works
Linkage disequilibrium mapping in isolated founder populations: diastrophic dysplasia in Finland
Hästbacka, J., de la Chapelle, A., Kaitila, I., Sistonen, P., Weaver, A., & Lander, E. (1992) · Nature Genetics · doi:10.1038/ng1192-204 · Cited by 558 · see citing works
Self-citationClayton, D. G., Walker, N. M., Smyth, D. J., Pask, R., Cooper, J. D., Maier, L. M., Smink, L. J., Lam, A. C., Ovington, N. R., Stevens, H. E., et al. (2005) · Nature Genetics · doi:10.1038/ng1653 · Cited by 526 · see citing works
A Spectrum of PCSK9 Alleles Contributes to Plasma Levels of Low-Density Lipoprotein Cholesterol
Kotowski, I. K., Pertsemlidis, A., Luke, A., Cooper, R. S., Vega, G. L., Cohen, J. C., & Hobbs, H. H. (2006) · The American Journal of Human Genetics · doi:10.1086/500615 · Cited by 517 · see citing works
Common Sequence Variants in the LOXL1 Gene Confer Susceptibility to Exfoliation Glaucoma
Myers, J. S. (2008) · Yearbook of Ophthalmology · doi:10.1016/s0084-392x(08)79151-2 · Cited by 517 · see citing works
Low nucleotide diversity in man.
Li, W. H., & Sadler, L. A. (1991) · Genetics · doi:10.1093/genetics/129.2.513 · Cited by 501 · see citing works
How many diseases does it take to map a gene with SNPs?
Weiss, K. M., & Terwilliger, J. D. (2000) · Nature Genetics · doi:10.1038/79866 · Cited by 478 · see citing works
Apolipoprotein E and Alzheimer's disease
Strittmatter, W. J., & Roses, A. D. (1996) · Annual Review of Neuroscience · doi:10.1146/annurev.ne.19.030196.000413 · Cited by 477 · see citing works
Diabetes mellitus and genetically programmed defects in β-cell function
Bell, G. I., & Polonsky, K. S. (2001) · Nature · doi:10.1038/414788a · Cited by 475 · see citing works
DNA sequence variants in the Gγ-, Aγ-, δ- and β-globin genes of man
Jeffreys, A. J. (1979) · Cell · doi:10.1016/0092-8674(79)90348-9 · Cited by 463 · see citing works
Graham, R. R., Kyogoku, C., Sigurdsson, S., Vlasova, I. A., Davies, L. R. L., Baechler, E. C., Plenge, R. M., Koeuth, T., Ortmann, W. A., Hom, G., et al. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0701266104 · Cited by 450 · see citing works
Self-citationKlein, J., & Sato, A. (2000) · New England Journal of Medicine · doi:10.1056/nejm200009143431106 · Cited by 445 · see citing works
Exploiting Gene-Environment Interaction to Detect Genetic Associations
Kraft, P., Yen, Y.-C., Stram, D. O., Morrison, J., & Gauderman, W. J. (2007) · Human Heredity · doi:10.1159/000099183 · Cited by 439 · see citing works
Aird, I., Bentall, H. H., Mehigan, J. A., et al. (1954) · BMJ · doi:10.1136/bmj.2.4883.315 · Cited by 426 · see citing works
Chapman, J. M., Cooper, J. D., Todd, J. A., & Clayton, D. G. (2003) · Human Heredity · doi:10.1159/000073729 · Cited by 414 · see citing works
Patterns of human genetic diversity: implications for human evolutionary history and disease.
Tishkoff, S., & Verrelli, B. (2003) · Annual review of genomics and human genetics (Print) · doi:10.1146/annurev.genom.4.070802.110226 · Cited by 408 · see citing works
A navigator for human genome epidemiology
Yu, W., GWINN, M. L., Clyne, M., Yesupriya, A., & Khoury, M. J. (2008) · Nature Genetics · doi:10.1038/ng0208-124 · Cited by 396 · see citing works
Common variants in the GDF5-UQCC region are associated with variation in human height
Sanna, S., Jackson, A., Nagaraja, R., Willer, C. J., Chen, W., Bonnycastle, L. L., Shen, H., Timpson, N. J., Lettre, G., Usala, G., et al. (2008) · Nature Genetics · doi:10.1038/ng.74 · Cited by 391 · see citing works
Nonrandom association of polymorphic restriction sites in the β-globin gene cluster
Antonarakis, S. E., Boehm, C. D., Giardina, P. J., & Kazazian, H. H. (1982) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.79.1.137 · Cited by 388 · see citing works
Gm3;5,13,14 and type 2 diabetes mellitus: an association in American Indians with genetic admixture.
Knowler, W. C., Williams, R. C., Pettitt, D. J., & Steinberg, A. G. (1988) · Europe PMC (PubMed Central) · Cited by 378 · see citing works
Saxena, R., Gianniny, L., Burtt, N. P., Lyssenko, V., Giuducci, C., Sjögren, M., Florez, J. C., Almgren, P., Isomaa, B., Orho‐Melander, M., et al. (2006) · Diabetes · doi:10.2337/db06-0381 · Cited by 373 · see citing works
Self-citationCommon deletions and SNPs are in linkage disequilibrium in the human genome
Hinds, D. A., Kloek, A. P., Jen, M., Chen, X., & Frazer, K. A. (2006) · Nature Genetics · doi:10.1038/ng1695 · Cited by 372 · see citing works
Reporting, Appraising, and Integrating Data on Genotype Prevalence and Gene-Disease Associations
Little, J., Bradley, L., Bray, M. S., Clyne, M., Dorman, J. S., Ellsworth, D. L., Hanson, J., Khoury, M. J., Lau, J., OʼBrien, T. R., et al. (2002) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a000179 · Cited by 366 · see citing works
Li, M., Atmaca-Sonmez, P., Othman, M., Branham, K. E. H., Khanna, R., Wade, M. S., Li, Y., Liang, L., Zareparsi, S., Swaroop, A., et al. (2006) · Nature Genetics · doi:10.1038/ng1871 · Cited by 354 · see citing works
Human genome sequence variation and the influence of gene history, mutation and recombination
Reich, D., Schaffner, S., Daly, M., McVean, G., Mullikin, J., Higgins, J., Richter, D., Lander, E., & Altshuler, D. (2002) · Nature Genetics · doi:10.1038/ng947 · Cited by 343 · see citing works
Self-citationRidker, P. M., Paré, G., Parker, A. N., Zee, R. Y. L., Danik, J. S., Buring, J. E., Kwiatkowski, D. J., Cook, N. R., Miletich, J. P., & Chasman, D. I. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.03.015 · Cited by 342 · see citing works
The Inherited Basis of Diabetes Mellitus: Implications for the Genetic Analysis of Complex Traits
Florez, J. C., Hirschhorn, J., & Altshuler, D. (2003) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.4.070802.110436 · Cited by 329 · see citing works
Self-citationLocke, D. P., Sharp, A. J., McCarroll, S. A., McGrath, S. D., Newman, T. L., Cheng, Z., Schwartz, S., Albertson, D. G., Pinkel, D., Altshuler, D., et al. (2006) · The American Journal of Human Genetics · doi:10.1086/505653 · Cited by 317 · see citing works
Self-citationGene-Environment Interaction in Genome-Wide Association Studies
Murcray, C. E., Lewinger, J. P., & Gauderman, W. J. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwn353 · Cited by 299 · see citing works
Evidence for substantial fine-scale variation in recombination rates across the human genome
Crawford, D. C., Bhangale, T., Li, N., Hellenthal, G., Rieder, M. J., Nickerson, D. A., & Stephens, M. (2004) · Nature Genetics · doi:10.1038/ng1376 · Cited by 271 · see citing works
Grarup, N., Rose, C. S., Galijatovic, E. A. A., Andersen, G., Nielsen, A. L., Albrechtsen, A., Clausen, J. O., Rasmussen, S. S., Jørgensen, T., Sandbæk, A., et al. (2007) · Diabetes · doi:10.2337/db07-0856 · Cited by 261 · see citing works
Pascoe, L. A., Tura, A., Patel, S. K., Ibrahim, I. M., Ferrannini, E., Zeggini, E., Weedon, M. N., Mari, A., Hattersley, A. T., McCarthy, M. I., et al. (2007) · Diabetes · doi:10.2337/db07-0634 · Cited by 253 · see citing works
THE AGE OF A NEUTRAL MUTANT PERSISTING IN A FINITE POPULATION
Kimura, M., & Ohta, T. (1973) · Genetics · doi:10.1093/genetics/75.1.199 · Cited by 241 · see citing works
Winckler, W., Weedon, M. N., Graham, R., McCarroll, S. A., Purcell, S., Almgren, P., Tuomilehto, J., Gaudet, D., Boström, K. B., Walker, M., et al. (2007) · Diabetes · doi:10.2337/db06-0202 · Cited by 201 · see citing works
Self-citationSimple Mendelian inheritance of the reiterated ribosomal DNA of yeast.
Petes, T. D., & Botstein, D. (1977) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.74.11.5091 · Cited by 199 · see citing works
Reiner, A. P., Barber, M., Guan, Y., Ridker, P. M., Lange, L. A., Chasman, D. I., Walston, J. D., Cooper, G. M., Jenny, N. S., Rieder, M. J., et al. (2008) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2008.03.017 · Cited by 186 · see citing works
Mapping Complex Genetic Traits in Humans: New Methods Using a Complete RFLP Linkage MapPreprint
Lander, E. S., & Botstein, D. (1986) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.1986.051.01.007 · Cited by 186 · see citing works
Self-citationOnce and Again—Issues Surrounding Replication in Genetic Association Studies
Hirschhorn, J. N., & Altshuler, D. (2002) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/jc.2002-021329 · Cited by 181 · see citing works
Self-citationMukherjee, B., & Chatterjee, N. (2007) · Biometrics · doi:10.1111/j.1541-0420.2007.00953.x · Cited by 180 · see citing works
Drinking from the Fire Hose — Statistical Issues in Genomewide Association Studies
Hunter, D. J., & Kraft, P. (2007) · New England Journal of Medicine · doi:10.1056/nejmp078120 · Cited by 172 · see citing works
Wolf, N., Quaranta, M., Prescott, N. J., Allen, M., Smith, R., Burden, A. D., Worthington, J., Griffiths, C. E. M., Mathew, C. G., Barker, J. N., et al. (2008) · Journal of Medical Genetics · doi:10.1136/jmg.2007.053595 · Cited by 171 · see citing works
Polymorphisms within Novel Risk Loci for Type 2 Diabetes Determine β-Cell Function
Staiger, H., Machicao, F. E., Stefan, N., Tschritter, O., Thamer, C., Kantartzis, K., Schäfer, S., Kirchhoff, K., Fritsche, A., & Häring, H. (2007) · PLoS ONE · doi:10.1371/journal.pone.0000832 · Cited by 163 · see citing works
Identification of SNP interactions using logic regression
Schwender, H., & Ickstadt, K. (2007) · Biostatistics · doi:10.1093/biostatistics/kxm024 · Cited by 160 · see citing works
Guilt beyond a reasonable doubt
Altshuler, D., & Daly, M. (2007) · Nature Genetics · doi:10.1038/ng0707-813 · Cited by 151 · see citing works
Self-citationA Mendelian Interpretation of Variation that is Apparently Continuous
East, E. M. (1910) · The American Naturalist · doi:10.1086/279117 · Cited by 135 · see citing works
Rothman, N., Wacholder, S., Caporaso, N., García‐Closas, M., Buetow, K. H., & Fraumeni, J. F. (2001) · Biochimica et Biophysica Acta (BBA) - Reviews on Cancer · doi:10.1016/s0304-419x(00)00021-4 · Cited by 111 · see citing works
A forest-based approach to identifying gene and gene–gene interactions
Chen, X. '., Liu, C., Zhang, M., & Heping Zhang, D. (2007) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709868104 · Cited by 110 · see citing works
An epidemiologic approach to ecogenetics.
Khoury, M. J., Adams, M. J., & Flanders, W. D. (1988) · PubMed · Cited by 109 · see citing works
The Emergence of Networks in Human Genome Epidemiology
Seminara, D., Khoury, M. J., O'Brien, T. R., Manolio, T. A., GWINN, M. L., Little, J., Higgins, J. P. T., Bernstein, J. L., Boffetta, P., Bondy, M. L., et al. (2006) · Epidemiology · doi:10.1097/01.ede.0000249540.17855.b7 · Cited by 94 · see citing works
Genetic dissection of human blood pressure variation: common pathways from rare phenotypes.
Lifton, R. P. (2004) · PubMed · Cited by 88 · see citing works
THE GENETIC BASIS OF TRUNCATE WING,—AN INCONSTANT AND MODIFIABLE CHARACTER IN DROSOPHILA
Altenburg, E., & Muller, H. J. (1920) · Genetics · doi:10.1093/genetics/5.1.1 · Cited by 85 · see citing works
Integrating epidemiology and genetic association: the challenge of gene–environment interaction
Kraft, P., & Hunter, D. (2005) · Philosophical Transactions of the Royal Society B Biological Sciences · doi:10.1098/rstb.2005.1692 · Cited by 81 · see citing works
From Darwin's Finches to Canaries in the Coal Mine — Mining the Genome for New Biology
Hunter, D. J., Altshuler, D., & Rader, D. J. (2008) · New England Journal of Medicine · doi:10.1056/nejmp0804318 · Cited by 80 · see citing works
Self-citationIsolation of the centromere-linked CDC10 gene by complementation in yeast.
Clarke, L., & Carbon, J. A. (1980) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.77.4.2173 · Cited by 78 · see citing works
Variation in TCF7L2 and Increased Risk of Colon Cancer
Folsom, A. R., Pankow, J. S., Peacock, J. M., Bielinski, S. J., HEISS, G. M., & Boerwinkle, E. (2008) · Diabetes Care · doi:10.2337/dc07-2131 · Cited by 75 · see citing works
New Mapping Project Splits the Community
Couzin, J. (2002) · Science · doi:10.1126/science.296.5572.1391 · Cited by 68 · see citing works
Association of the TCF7L2 polymorphism with colorectal cancer and adenoma risk
Hazra, A., Fuchs, C. S., Chan, A. T., Giovannucci, E. L., & Hunter, D. J. (2008) · Cancer Causes & Control · doi:10.1007/s10552-008-9164-3 · Cited by 34 · see citing works
A survey of data mining methods for linkage disequilibrium mapping
Onkamo, P., & Toivonen, H. T. T. (2006) · Human Genomics · doi:10.1186/1479-7364-2-5-336 · Cited by 28 · see citing works
Khoury, M. J., Beaty, T. H., & Hwang, S. (1995) · Teratology · doi:10.1002/tera.1420510510 · Cited by 21 · see citing works
Invited Commentary: Efficient Testing of Gene-Environment Interaction
Chatterjee, N., & Wacholder, S. (2008) · American Journal of Epidemiology · doi:10.1093/aje/kwn352 · Cited by 18 · see citing works
Schwartz, D. A. (2006) · Journal of Exposure Science & Environmental Epidemiology · doi:10.1038/sj.jes.7500531 · Cited by 11 · see citing works
Flagged first, then by citations
Research works printed but not linked: 10
- D. Botstein, R. L. White, M. Skolnick, R. W. Davis, Am. J. Hum. Genet.32, 314 (1980).
- Online Mendelian Inheritance in Man (www.ncbi.nlm.nih.gov/sites/entrez?db=omim).
- R. P. Lifton, Harvey Lect.100, 71 (2004).
- R. A. Fisher, Trans. R. Soc. Edinburgh52, 399 (1918).
- R. Lewontin, in Evolutionary Biology 6, T. Dobzhansky, M. K. Hecht, W. C. Steere, Eds. (Appleton-Century-Crofts, New York, 1972), pp. 391–398.
- Entrez SNP (www.ncbi.nlm.nih.gov/sites/entrez?db=snp).
- W. C. Knowler, R. C. Williams, D. J. Pettitt, A. G. Steinberg, Am. J. Hum. Genet.43, 520 (1988).
- R. S. Spielman, R. E. McGinnis, W. J. Ewens, Am. J. Hum. Genet.52, 506 (1993).
- N. Wolfet al., J. Med. Genet.45, 114 (2008).
- 10.1056/NEJMoa075974 · DOI · Paper page
Cited by
Sorted by citations
Sequencing technologies – the next generation
Metzker, M. L. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2626 · Cited by 7,066 · see citing works
Genetic and epigenetic fine mapping of causal autoimmune disease variants
Farh, K. K.-H., Marson, A., Zhu, J., Kleinewietfeld, M., Housley, W. J., Beik, S., Shoresh, N., Whitton, H., Ryan, R. J. H., Shishkin, A. A., et al. (2015) · Nature · doi:10.1038/nature13835 · Cited by 1,956 · see citing works
Self-citationThe NIH Roadmap Epigenomics Mapping Consortium
Bernstein, B. E., Stamatoyannopoulos, J. A., Costello, J. F., Ren, B., Milosavljevic, A., Meissner, A., Kellis, M., Marra, M. A., Beaudet, A. L., Ecker, J. R., et al. (2010) · Nature Biotechnology · doi:10.1038/nbt1010-1045 · Cited by 1,892 · see citing works
Self-citationLord, C., Brugha, T. S., Charman, T., Cusack, J., Dumas, G., Frazier, T., Jones, E. J. H., Jones, R. M., Pickles, A., State, M. W., et al. (2020) · Nature Reviews Disease Primers · doi:10.1038/s41572-019-0138-4 · Cited by 1,859 · see citing works
Interactome Networks and Human Disease
Vidal, M., Cusick, M. E., & Barabási, A.-L. (2011) · Cell · doi:10.1016/j.cell.2011.02.016 · Cited by 1,771 · see citing works
Sanders, S. J., Ercan-Sencicek, A. G., Hus, V., Luo, R., Murtha, M. T., Moreno-De-Luca, D., Chu, S. H., Moreau, M. P., Gupta, A. R., Thomson, S. A., et al. (2011) · Neuron · doi:10.1016/j.neuron.2011.05.002 · Cited by 1,263 · see citing works
A global genetic interaction network maps a wiring diagram of cellular function
Costanzo, M., VanderSluis, B., Koch, E. N., Baryshnikova, A., Pons, C., Tan, G., Wang, W., Usaj, M., Hanchard, J., Lee, S. D., et al. (2016) · Science · doi:10.1126/science.aaf1420 · Cited by 1,240 · see citing works
A high-resolution map of human evolutionary constraint using 29 mammals
Broad Institute Sequencing Platform and Whole Genome Assembly Team, Lindblad-Toh, K., Baylor College of Medicine Human Genome Sequencing Center Sequencing Team, Genome Institute at Washington University, Garber, M., Zuk, O., Lin, M. F., Parker, B. J., Washietl, S., Kheradpour, P., et al. (2011) · Nature · doi:10.1038/nature10530 · Cited by 1,108 · see citing works
Self-citationHuman genetic variation and its contribution to complex traits
Frazer, K. A., Murray, S. S., Schork, N. J., & Topol, E. J. (2009) · Nature Reviews Genetics · doi:10.1038/nrg2554 · Cited by 1,073 · see citing works
Initial impact of the sequencing of the human genome
Lander, E. S. (2011) · Nature · doi:10.1038/nature09792 · Cited by 1,044 · see citing works
Self-citationNejentsev, S., Walker, N., Riches, D., Egholm, M., & Todd, J. A. (2009) · Science · doi:10.1126/science.1167728 · Cited by 958 · see citing works
Advancing the understanding of autism disease mechanisms through genetics
de la Torre-Ubieta, L., Won, H., Stein, J. L., & Geschwind, D. H. (2016) · Nature Medicine · doi:10.1038/nm.4071 · Cited by 827 · see citing works
Association mapping: critical considerations shift from genotyping to experimental design
Myles, S., Peiffer, J., Brown, P. J., Ersoz, E. S., Zhang, Z., Costich, D. E., & Buckler, E. S. (2009) · The Plant Cell · doi:10.1105/tpc.109.068437 · Cited by 857 · see citing works
National Institute of Diabetes and Digestive Kidney Diseases Inflammatory Bowel Disease Genetics Consortium (NIDDK IBDGC), Rivas, M. A., United Kingdom Inflammatory Bowel Disease Genetics Consortium, International Inflammatory Bowel Disease Genetics Consortium, Beaudoin, M., Gardet, A., Stevens, C., Sharma, Y., Zhang, C. K., Boucher, G., et al. (2011) · Nature Genetics · doi:10.1038/ng.952 · Cited by 771 · see citing works
Self-citationValidating therapeutic targets through human genetics
Plenge, R. M., Scolnick, E. M., & Altshuler, D. (2013) · Nature Reviews Drug Discovery · doi:10.1038/nrd4051 · Cited by 712 · see citing works
Self-citationPooled Association Tests for Rare Variants in Exon-Resequencing Studies
Price, A. L., Kryukov, G. V., de Bakker, P. I. W., Purcell, S. M., Staples, J., Wei, L.-J., & Sunyaev, S. R. (2010) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2010.04.005 · Cited by 755 · see citing works
Genetics of coronary artery disease: discovery, biology and clinical translation
Khera, A. V., & Kathiresan, S. (2017) · Nature Reviews Genetics · doi:10.1038/nrg.2016.160 · Cited by 659 · see citing works
Computational solutions to large‐scale data management and analysis
Schadt, E. E., Linderman, M. D., Sorenson, J., Lee, L., & Nolan, G. P. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2857 · Cited by 631 · see citing works
DISEASES: Text mining and data integration of disease–gene associations
Pletscher-Frankild, S., Pallejà, A., Tsafou, K., Binder, J. X., & Jensen, L. J. (2015) · Methods · doi:10.1016/j.ymeth.2014.11.020 · Cited by 591 · see citing works
Liu, Y.-L., Reeves, H. L., Burt, A. D., Tiniakos, D., McPherson, S., Leathart, J. B. S., Allison, M. E. D., Alexander, G. J., Piguet, A.-C., Anty, R., et al. (2014) · Nature Communications · doi:10.1038/ncomms5309 · Cited by 623 · see citing works
Identifying Causal Variants at Loci with Multiple Signals of Association
Hormozdiari, F., Kostem, E., Kang, E. Y., Pasaniuc, B., & Eskin, E. (2014) · Genetics · doi:10.1534/genetics.114.167908 · Cited by 465 · see citing works
Mumbach, M. R., Satpathy, A. T., Boyle, E. A., Dai, C., Gowen, B. G., Cho, S. W., Nguyen, M. L., Rubin, A. J., Granja, J. M., Kazane, K. R., et al. (2017) · Nature Genetics · doi:10.1038/ng.3963 · Cited by 490 · see citing works
Statistical analysis strategies for association studies involving rare variants
Bansal, V., Libiger, O., Torkamani, A., & Schork, N. J. (2010) · Nature Reviews Genetics · doi:10.1038/nrg2867 · Cited by 455 · see citing works
Mobile DNA in Health and Disease
Kazazian, H. H., & Moran, J. V. (2017) · New England Journal of Medicine · doi:10.1056/nejmra1510092 · Cited by 445 · see citing works
Genome-wide meta-analysis identifies new susceptibility loci for migraine
North American Brain Expression Consortium, Anttila, V., UK Brain Expression Consortium, the International Headache Genetics Consortium, Winsvold, B. S., Gormley, P., Kurth, T., Bettella, F., McMahon, G., Kallela, M., et al. (2013) · Nature Genetics · doi:10.1038/ng.2676 · Cited by 410 · see citing works
Pathway and network-based analysis of genome-wide association studies in multiple sclerosis
Baranzini, S. E., Galwey, N. W., Wang, J., Khankhanian, P., Lindberg, R., Pelletier, D., Wu, W., Uitdehaag, B. M. J., Kappos, L., GeneMSA Consortium, et al. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp120 · Cited by 383 · see citing works
Smith, E. N., Bloss, C. S., Badner, J. A., Barrett, T., Belmonte, P. L., Berrettini, W., Byerley, W., Coryell, W., Craig, D., Edenberg, H. J., et al. (2009) · Molecular Psychiatry · doi:10.1038/mp.2009.43 · Cited by 363 · see citing works
Speliotes, E. K., Butler, J. L., Palmer, C. D., Voight, B. F., & Hirschhorn, J. N. (2010) · Hepatology · doi:10.1002/hep.23768 · Cited by 362 · see citing works
Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls
Platform, B. G., Flannick, J., DiscovEHR Collaboration, CHARGE, LuCamp, ProDiGY, GoT2D, ESP, SIGMA-T2D, T2D-GENES, et al. (2019) · Nature · doi:10.1038/s41586-019-1231-2 · Cited by 304 · see citing works
Self-citationEvans, D. M., Visscher, P. M., & Wray, N. R. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp295 · Cited by 297 · see citing works
Woo, D., Falcone, G. J., Devan, W. J., Brown, W. M., Biffi, A., Howard, T. D., Anderson, C. D., Brouwers, H. B., Valant, V., Battey, T. W. K., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.02.012 · Cited by 290 · see citing works
The conundrums of understanding genetic risks for autism spectrum disorders
State, M. W., & Levitt, P. (2011) · Nature Neuroscience · doi:10.1038/nn.2924 · Cited by 306 · see citing works
Yang, C., Farias, F. H. G., Ibanez, L., Suhy, A., Sadler, B., Fernandez, M. V., Wang, F., Bradley, J. L., Eiffert, B., Bahena, J. A., et al. (2021) · Nature Neuroscience · doi:10.1038/s41593-021-00886-6 · Cited by 290 · see citing works
A trans-acting locus regulates an anti-viral expression network and type 1 diabetes risk
Cardiogenics Consortium, Heinig, M., Petretto, E., Wallace, C., Bottolo, L., Rotival, M., Lu, H., Li, Y., Sarwar, R., Langley, S. R., et al. (2010) · Nature · doi:10.1038/nature09386 · Cited by 283 · see citing works
Swaroop, A., Chew, E. Y., Bowes Rickman, C., & Abecasis, G. R. (2009) · Annual Review of Genomics and Human Genetics · doi:10.1146/annurev.genom.9.081307.164350 · Cited by 270 · see citing works
The Genotype-Tissue Expression (GTEx) project
Lonsdale, J., Thomas, J., Salvatore, M., Phillips, R., Lo, E., Shad, S., Hasz, R., Walters, G., Garcia, F., Young, N., et al. (2013) · Nature Genetics · doi:10.1038/ng.2653 · Cited by 263 · see citing works
Association of a Low-Frequency Variant in <i>HNF1A</i> With Type 2 Diabetes in a Latino Population
Estrada, K., Aukrust, I., Bjørkhaug, L., Burtt, N. P., Mercader, J. M., García-Ortiz, H., Huerta-Chagoya, A., Moreno-Macías, H., Walford, G., Flannick, J., et al. (2014) · JAMA · doi:10.1001/jama.2014.6511 · Cited by 259 · see citing works
Self-citationControl of fetal hemoglobin: new insights emerging from genomics and clinical implications
Thein, S. L., Menzel, S., Lathrop, M., & Garner, C. (2009) · Human Molecular Genetics · doi:10.1093/hmg/ddp401 · Cited by 250 · see citing works
Genetic basis of chronotype in humans: insights from three landmark GWAS
Kalmbach, D. A., Schneider, L. D., Cheung, J., Bertrand, S. J., Kariharan, T., Pack, A. I., & Gehrman, P. R. (2017) · Sleep · doi:10.1093/sleep/zsw048 · Cited by 243 · see citing works
The study of eQTL variations by RNA-seq: from SNPs to phenotypes
Majewski, J., & Pastinen, T. (2011) · Trends in Genetics · doi:10.1016/j.tig.2010.10.006 · Cited by 232 · see citing works
The genetics of Tourette syndrome: A review
O'Rourke, J. A., Scharf, J. M., Yu, D., & Pauls, D. L. (2009) · Journal of Psychosomatic Research · doi:10.1016/j.jpsychores.2009.06.006 · Cited by 212 · see citing works
Review: a meta‐analysis of GWAS and age‐associated diseases
Jeck, W. R., Siebold, A. P., & Sharpless, N. E. (2012) · Aging Cell · doi:10.1111/j.1474-9726.2012.00871.x · Cited by 204 · see citing works
Zhu, J., Sova, P., Xu, Q., Dombek, K. M., Xu, E. Y., Vu, H., Tu, Z., Brem, R. B., Bumgarner, R. E., & Schadt, E. E. (2012) · PLoS Biology · doi:10.1371/journal.pbio.1001301 · Cited by 205 · see citing works
Momozawa, Y., Mni, M., Nakamura, K., Coppieters, W., Almer, S., Amininejad, L., Cleynen, I., Colombel, J.-F., de Rijk, P., Dewit, O., et al. (2011) · Nature Genetics · doi:10.1038/ng.733 · Cited by 189 · see citing works
How far from the SNP may the causative genes be?
Brodie, A., Azaria, J. R., & Ofran, Y. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw500 · Cited by 172 · see citing works
Progress and promise in understanding the genetic basis of common diseases
Price, A. L., Spencer, C. C. A., & Donnelly, P. (2015) · Proceedings of the Royal Society B: Biological Sciences · doi:10.1098/rspb.2015.1684 · Cited by 147 · see citing works
The genetics of child psychiatric disorders: focus on autism and Tourette syndrome
State, M. W. (2010) · Neuron · doi:10.1016/j.neuron.2010.10.004 · Cited by 162 · see citing works
Mansour, H. A., Talkowski, M. E., Wood, J., Chowdari, K. V., McClain, L., Prasad, K., Montrose, D., Fagiolini, A., Friedman, E. S., Allen, M. H., et al. (2009) · Bipolar Disorders · doi:10.1111/j.1399-5618.2009.00756.x · Cited by 161 · see citing works
McClay, J. L., Adkins, D. E., Åberg, K., Bukszár, J., Khachane, A. N., Keefe, R. S. E., Perkins, D. O., McEvoy, J. P., Stroup, T. S., Vann, R. E., et al. (2011) · Neuropsychopharmacology · doi:10.1038/npp.2010.193 · Cited by 124 · see citing works
Common variant at 16p11.2 conferring risk of psychosis
Steinberg, S., de Jong, S., Mattheisen, M., Costas, J., Demontis, D., Jamain, S., Pietiläinen, O. P. H., Lin, K., Papiol, S., Huttenlocher, J., et al. (2014) · Molecular Psychiatry · doi:10.1038/mp.2012.157 · Cited by 104 · see citing works
Genetic basis of autism: is there a way forward?
Eapen, V. (2011) · Current Opinion in Psychiatry · doi:10.1097/yco.0b013e328345927e · Cited by 102 · see citing works
Intellectual disability is associated with increased runs of homozygosity in simplex autism
Gamsiz, E. D., Viscidi, E. W., Frederick, A. M., Nagpal, S., Sanders, S. J., Murtha, M. T., Schmidt, M., Triche, E. W., Geschwind, D. H., State, M. W., et al. (2013) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.06.004 · Cited by 79 · see citing works
Genome‐wide association studies of multiple sclerosis
Cotsapas, C., & Mitrovic, M. (2018) · Clinical & Translational Immunology · doi:10.1002/cti2.1018 · Cited by 89 · see citing works
“As became obvious in retrospect, such studies are underpowered to detect risk alleles for common complex disease, suffer from population stratification and other artefacts and often assess genes that have broad relevance to the immune system but do not drive disease risk per se.(22) The development of genetic maps cov…”
BackgroundResultInfluentialPlatt, J., Bollinger, J., Dvoskin, R., Kardia, S. L. R., & Kaufman, D. (2014) · Genetics in Medicine · doi:10.1038/gim.2013.59 · Cited by 88 · see citing works
Pan, W. (2011) · Genetic Epidemiology · doi:10.1002/gepi.20567 · Cited by 71 · see citing works
Genome-wide association studies and the genetic dissection of complex traits
Sebastiani, P., Timofeev, N., Dworkis, D. A., Perls, T. T., & Steinberg, M. H. (2009) · American Journal of Hematology · doi:10.1002/ajh.21440 · Cited by 67 · see citing works
Sensitive detection of chromatin-altering polymorphisms reveals autoimmune disease mechanisms
del Rosario, R. C.-H., Poschmann, J., Rouam, S. L., Png, E., Khor, C. C., Hibberd, M. L., & Prabhakar, S. (2015) · Nature Methods · doi:10.1038/nmeth.3326 · Cited by 58 · see citing works
Nakaoka, H., Gurumurthy, A., Hayano, T., Ahmadloo, S., Omer, W. H., Yoshihara, K., Yamamoto, A., Kurose, K., Enomoto, T., Akira, S., et al. (2016) · PLOS Genetics · doi:10.1371/journal.pgen.1005893 · Cited by 46 · see citing works
A Survey of Gene Prioritization Tools for Mendelian and Complex Human Diseases
Zolotareva, O., & Kleine, M. (2019) · Journal of Integrative Bioinformatics · doi:10.1515/jib-2018-0069 · Cited by 46 · see citing works
Utility of genetic determinants of lipids and cardiovascular events in assessing risk
Holmes, M. V., Harrison, S., Talmud, P. J., Hingorani, A. D., & Humphries, S. E. (2011) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2011.6 · Cited by 44 · see citing works
Machine learning in Alzheimer’s disease drug discovery and target identification
Geng, C., Wang, Z., & Tang, Y. (2024) · Ageing Research Reviews · doi:10.1016/j.arr.2023.102172 · Cited by 34 · see citing works
Yang, J., Duan, S., Zhong, R., Yin, J., Pu, J., Ke, J., Lu, X., Zou, L., Zhang, H., Zhu, Z., et al. (2013) · Molecular Neurobiology · doi:10.1007/s12035-012-8392-4 · Cited by 31 · see citing works
The new therapeutic frontier--nuclear receptors and the liver
Karpen, S. J., & Trauner, M. (2010) · Journal of Hepatology · doi:10.1016/j.jhep.2009.12.002 · Cited by 29 · see citing works
Genomic Analysis of Left Ventricular Remodeling
Sarwar, R., & Cook, S. A. (2009) · Circulation · doi:10.1161/circulationaha.108.797225 · Cited by 13 · see citing works
Burton, E. A., Argenziano, M., Cook, K., Ridler, M., Lu, S., Su, C., Manduchi, E., Littleton, S. H., Leonard, M. E., Hodge, K. M., et al. (2024) · doi:10.1101/2024.08.22.609230 · Cited by 3 · see citing works
- Authors
- Altshuler, D., Daly, M. J., & Lander, E. S.
- Affiliations
- Broad Institute (US)
- Corresponding author
- Altshuler, David
- Daly, Mark J.
- Lander, Eric S.
- Venue
- Science
- Published
- 2008-11-07
- Volume
- 322
- Issue
- 5903
- Pages
- 881-888
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC2694957
- OpenAlex
- W2136078375
- Semantic Scholar
- 85282c18a9ea0cccaeeff9c767422a5fd655a1cb
- Cited by
- 1,452
- References
- 166
- Citations by year
- 2026: 17 · 2025: 24 · 2024: 31 · 2023: 43 · 2022: 55 · 2021: 43 · 2020: 41 · 2019: 55 · 2018: 68 · 2017: 65 · 2016: 79 · 2015: 91 · 2014: 79 · 2013: 108 · 2012: 128
- FWCI
- 16.37
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Human Genome Research Institute (U54HG003067)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Mapping and Diversity in Plants and Animals
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
- Keywords
- gene mapping, monogenic disorders, complex traits, linkage analysis, genome-wide association study, common diseases, heredity (biology), gene identification
- MeSH terms
- Chromosome Mapping, Cloning, Molecular, Disease, Genotype, Humans, Genetic Linkage, Mutation, Risk Factors, Selection, Genetic, Linkage Disequilibrium, Genome, Human, Quantitative Trait, Heritable, Physical Chromosome Mapping, Polymorphism, Single Nucleotide, Genome-Wide Association Study
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Claims read by deepseek-v4.1-flash under definition version 3 (extract-v3) on 2026-10-09.
Classified by jev-1.13-20260917 (gold-guideline-v0.2) on 2026-10-09.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review