Rare and common variants: twenty arguments

In the paper

“Very few of the thousands of GWAS significant associations have been shown using molecular genetics, biochemistry or biophysics to be the actual risk variant38, 109.”

What the sources say

• Not checked yetcites [38] Chorley, B. N. et al. Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: current and developing technologies. Mutat. Res. 659, 147–157 (2008). source
• Not checked yetcites [109] Bauer, R. C., Stylianou, I. M., Rader, D. J. Functional validation of new pathways in lipoprotein metabolism identified by human genetics. Curr. Opin. Lipidol. 22, 123–128 (2011). source

In the paper

“It must be noted that there is very little evidence from GWAS for either GxE or GxG interactions108, but such effects could be mild at the level of individual associations and be below the power of detection.”

What the sources say

• Not checked yetcites [108] Hamza, T. H. et al. Genome-wide gene-environment study identifies glutamate receptor gene GRIN2A as a Parkinson's disease modifier gene via interaction with coffee. PLoS Genet. 7, e1002237 (2011). source

In the paper

“and it is not clear that they are as efficient for schizophrenia, arthritis or intelligence75,76.”

What the sources say

• Not checked yetcites [75] Yang, J. et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nature Genet. 43, 519–525 (2011). source
• Not checked yetcites [76] Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011). source

In the paper

“whereas a significant excess of rare coding variants was found in 4 genes for hypertriglyceridemia116.”

What the sources say

• Not checked yetcites [116] Johansen, C. T. et al. Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia. Nature Genet. 42, 684–687 (2010). source

In the paper

“only 1 of 63 genes in an initial screen for inflammatory bowel disease found evidence for rare variant effects (and these were protective114, but see also115)”

What the sources say

• Not checked yetcites [113] Nejentsev, S., Walker, N., Riches, D., Egholm, M. & Todd, J. A. Rare variants of IFIH1, a gene implicated in antiviral responses, protect against type 1 diabetes. Science 324, 387–389 (2009). source
• Not checked yetcites [114] Momozawa, Y. et al. Resequencing of positional candidates identifies low frequency IL23R coding variants protecting against inflammatory bowel disease. Nature Genet. 43, 43–47 (2011). source
• Not checked yetcites [115] Rivas, M. A. et al. Deep resequencing of GWAS loci identifies independent rare variants associated with inflammatory bowel disease. Nature Genet. 43, 1066–1073 (2011). source

In the paper

“As more individuals are sequenced, many of these appear in healthy controls”

In the paper

“When GWAS began the field was dominated by the simple common disease-common variant (CD-CV) hypothesis1–4 has been refuted in light of the so-called ‘missing heritability problem’”

What the sources say

• Not checked yetcites [1] Lander, E. S. The new genomics: global views of biology. Science 274, 536–539 (1996). source
• Not checked yetcites [2] Reich, D. E. & Lander, E. S. On the allelic spectrum of human disease. Trends Genet. 17, 502–510 (2001). source
• Not checked yetcites [3] Pritchard, J. K. & Cox, N. J. The allelic architecture of human disease genes: common disease–common variant... or not? Hum. Mol. Genet. 11, 2417–2423 (2002). source
• Not checked yetcites [4] Botstein, D. & Risch, N. Discovering genotypes underlying human phenotypes: past successes for Mendelian disease, future approaches for complex disease. Nature Genet. 33, 228–237 (2003). source
• Not checked yetcites [5] Maher, B. Personal genomes: the case of the missing heritability. Nature 456, 18–21 (2008). source
• Not checked yetcites [6] Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). This paper provides a compendium of arguments, which were assembled by participants in a US National Institutes of Health (NIH) workshop, relating to the possible sources of missing heritability. source

In the paper

“affected individuals will tend to carry a slight excess of risk variants, since the overall distribution of the number of risk alleles per affected individual is skewed relative to unaffecteds.”

In the paper

“If hundreds of mutations each at a frequency of less than 1% all affect a particular disease, then many more people will be doubly or triply heterozygous for various combinations, than are homozygous for any one variant.”

In the paper

“as shown in Figure 2b, the vast majority of unaffected individuals are expected to carry one or more risk alleles.”

In the paper

“But selection is sufficiently efficient that even a fitness reduction of a fraction of a percent will keep allele frequencies from reaching common levels.”

In the paper

“we still lack efficient procedures for identifying enhancers and other regulatory regions that polymorphisms could disrupt38.”

What the sources say

• Not checked yetcites [38] Chorley, B. N. et al. Discovery and verification of functional single nucleotide polymorphisms in regulatory genomic regions: current and developing technologies. Mutat. Res. 659, 147–157 (2008). source

In the paper

“it is simply not the case that a few dozen loci of moderate effect and intermediate frequency each explain several percent of disease risk in a population”

In the paper

“Here I review 20 arguments for and against each of these models of the genetic basis of complex traits, and conclude that both classes of effect can be reconciled readily.”

In the paper

“the finding from whole-exome sequence data that non-synonymous substitutions are even more significantly skewed towards low frequencies almost certainly reflects the operation of purifying selection32–34.”

What the sources say

• Not checked yetcites [32] Cargill, M. et al. Characterization of single-nucleotide polymorphisms in coding regions of human genes. Nature Genet. 22, 231–238 (1999). source
• Not checked yetcites [33] Kryukov, G. V., Pennacchio, L. A. & Sunyaev, S. R. Most rare missense alleles are deleterious in humans: implications for complex disease and association studies. Am. J. Hum. Genet. 80, 727–739 (2007). source
• Not checked yetcites [34] Zhu, Q. et al. A genome-wide comparison of the functional properties of rare and common genetic variants in humans. Am. J. Hum. Genet. 88, 458–468 (2011). source

In the paper

“The total number of loci that may contribute to any disease is a function of the baseline disease incidence, the number of rare variants per locus, and the genotypic relative risk (GRR, namely, effect size).”

In the paper

“If half a dozen common variants explain 10% of risk in the population, the remainder is attributable to a myriad of variants that each explain considerably less than 1% and have genotype relative risks less than 1.112.”

What the sources say

• Not checked yetcites [12] Park, J. H. et al. Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nature Genet. 42, 570–575 (2010). This paper discusses how the true number of associations and their effect sizes can be inferred from observed GWAS results. source

In the paper

“As a class, amino acid substitutions appear to be deleterious.”

In the paper

“loci detected by GWAS almost without exception explain a small minority of the inferred genetic variance5,6”

What the sources say

• Not checked yetcites [5] Maher, B. Personal genomes: the case of the missing heritability. Nature 456, 18–21 (2008). source
• Not checked yetcites [6] Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). This paper provides a compendium of arguments, which were assembled by participants in a US National Institutes of Health (NIH) workshop, relating to the possible sources of missing heritability. source

In the paper

“The existence of disease-promoting variants reflects the balance between mutation creating new susceptibility variants, and selection preventing them from drifting into the population2,28.”

What the sources say

• Not checked yetcites [2] Reich, D. E. & Lander, E. S. On the allelic spectrum of human disease. Trends Genet. 17, 502–510 (2001). source
• Not checked yetcites [28] Bulmer, M. G. Maintenance of genetic variability by mutation-selection balance: a child's guide through the jungle. Genome 31, 761–767 (1989). source

In the paper

“since the heritability of risk is generally estimated as narrow sense variance, interaction effects should be considered secondary to the main effects of common and rare variants.”

In the paper

“If these follow the same distribution of allele frequencies as neutral variation, then they will include a large number of rare variants as well.”

In the paper

“However, the finding is consistent with the theory that selection keeps fitness-reducing alleles at a large proportion of genes at low frequency35.”

What the sources say

• Not checked yetcites [35] Lindblad-Toh, K. et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478, 476–482 (2011). source

In the paper

“If each of these variants explains most of the risk in just a handful of people, their effects will not explain enough of the variance in a total population to be detected by standard GWAS procedures.”

In the paper

“Animal breeders have been using ‘genomic selection’ methods with great success for the past decade72, basing their selection of sires and dams on the overall predicted breeding value determined from the full set of genomic markers that capture variation distributed throughout the genome.”

What the sources say

• Not checked yetcites [72] Goddard, M. E. & Hayes, B. J. Genomic selection. J. Animal Breed. Genet. 124, 323–330 (2007). source

In the paper

“If rare variants are contributing then they are doing so in the context of many other genetic variants in the pedigrees, as shown by a recent analysis of schizophrenia genetics54.”

What the sources say

• Not checked yetcites [54] Ruderfer, D. M. et al. A family-based study of common polygenic variation and risk of schizophrenia. Mol. Psychiatry 16, 887–888 (2011). source

In the paper

“common variants are often consistent across populations — such as between Caucasians and Asians — despite differences in allele frequencies65,66.”

What the sources say

• Not checked yetcites [65] Waters, K. M. et al. Consistent association of type 2 diabetes risk variants found in Europeans in diverse racial and ethnic groups. PLoS Genet. 6, e1001078 (2010). source
• Not checked yetcites [66] Shriner, D. et al. Transferability and fine-mapping of genome-wide associated loci for adult height across human populations. PLoS ONE 4, e8398 (2009). source

In the paper

“Similarly in humans, by taking all nominally significant SNPs rather than just the GWAS significant ones, it is possible to capture much more of the genetic variance than is explained by the highly significant loci73,74”

What the sources say

• Not checked yetcites [73] Purcell, S. M. et al. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature 460, 748–752 (2009). source
• Not checked yetcites [74] So, H.-C., Li, M. & Sham, P. C. Uncovering the total heritability explained by all true susceptibility variants in a genome-wide association study. Genet. Epidemiol. 35, 447–456 (2011).

In the paper

“Synthetic association is not expected to account for most of the missing heritability19, 51”

What the sources say

• Not checked yetcites [19] Wray, N. R., Purcell, S. M. & Visscher, P. M. Synthetic associations created by rare variants do not explain most GWAS results. PLoS Biol. 9, e1000579 (2011). source
• Not checked yetcites [51] Anderson, C. A., Soranzo, N. Barrett, J. C. & Zeggini, E. Synthetic associations are unlikely to account for many common disease genome-wide association signals. PLoS Biol. 9, e1000580 (2011). source

In the paper

“partitioning of the genetic variance on a chromosome-by-chromosome basis, for a diverse set of traits, shows that the proportion of variance explained is consistently proportional to chromosome length75,76.”

What the sources say

• Not checked yetcites [75] Yang, J. et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nature Genet. 43, 519–525 (2011). source
• Not checked yetcites [76] Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011). source

In the paper

“the demonstration that half of the cases of X-linked mental retardation can be ascribed to rare protein-coding mutations, which were discovered by comprehensive sequencing of X-chromosomal exons43.”

What the sources say

• Not checked yetcites [43] Tarpey, P. S. et al. A systematic, large-scale resequencing screen of X-chromosome coding exons in mental retardation. Nature Genet. 41, 535–543 (2009). This was one of the first whole-exome sequencing studies that was designed to detect rare variants of large effect. source

In the paper

“However, it turns out that rare variants can easily induce apparently additive effects statistically, because the homozygotes for the tagging variant are twice as likely as the heterozygotes to carry the rare variant.”

In the paper

“There is thus extensive precedent for rare variants contributing substantially to special cases of complex disease, including risk of infection44.”

What the sources say

• Not checked yetcites [44] George, J. et al. Two human MYD88 variants, S34Y and R98C, interfere with MyD88–IRAK4–Myddosome assembly. J. Biol. Chem. 286, 1341–1353 (2011). source

In the paper

“standard quantitative genetic theory provides ample support for the infinitesimal model7,8.”

What the sources say

• Not checked yetcites [7] Fisher, R. A. The Genetical Theory of Natural Selection (Oxford Univ. Press, Oxford, 1930). source
• Not checked yetcites [8] Visscher, P. M., Hill, W. G. & Wray, N. Heritability in the genomics era — errors and misconceptions. Nature Rev. Genet. 9, 255–266 (2008). This is an accessible modern introduction to the concept of heritability. source

In the paper

“A multivariate version of this approach, implemented by regression of phenotypic similarity on genetic relatedness, also implies that common variants capture the majority of the genetic variants71.”

What the sources say

• Not checked yetcites [71] Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nature Genet. 42, 565–569 (2010). This paper introduces a multivariate approach for capturing the effects of common variant associations genome-wide. source

In the paper

“Direct empirical support for the infinitesimal model comes from genomic variance analyses70, 71.”

What the sources say

• Not checked yetcites [70] Schork, N. J. Genome partitioning and whole genome analysis. Adv. Genet. 42, 299–322 (2001). source
• Not checked yetcites [71] Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nature Genet. 42, 565–569 (2010). This paper introduces a multivariate approach for capturing the effects of common variant associations genome-wide. source

In the paper

“Multiplicative interactions between rare variants cannot be measured in GWAS because of low power”

In the paper

“There is no evidence to support the hypothesis that rare single nucleotide variants at the same loci are the major source of genetic variance9”

What the sources say

• Not checked yetcites [9] Cirulli, E. T. & Goldstein, D. B. Uncovering the roles of rare variants in common disease through whole-genome sequencing. Nature Rev. Genet. 11, 415–425 (2010). source

In the paper

“Sibling recurrence rates are generally much higher than can be attributed to rare variants with the postulated effect sizes17.”

What the sources say

• Not checked yetcites [17] Bodmer, W. & Bonilla, C. Common and rare variants in multifactorial susceptibility to common diseases. Nature Genet. 40, 695–701 (2008). source

In the paper

“Five percent of cases of schizophrenia and of autism have each been attributed to CNVs at fewer than a half dozen genomic locations46–48.”

What the sources say

• Not checked yetcites [46] Stefansson, H. et al. Large recurrent microdeletions associated with schizophrenia. Nature 455, 232–236 (2008). source
• Not checked yetcites [47] Sebat, J. et al. Strong association of de novo copy number mutations with autism. Science 316, 445–449 (2007). This paper provided the first demonstration that rare copy number variants associate with psychiatric disease. source
• Not checked yetcites [48] Cook, E. H. Jr & Scherer, S. W. Copy-number variations associated with neuropsychiatric conditions. Nature 455, 919–923 (2008). source

In the paper

“considerations of linkage disequilibrium using standard quantitative genetic theory19 place strong constraints on the number of rare variants and their range of effect sizes that would be compatible with them making a major contribution yet remaining undetected in GWAS”

What the sources say

• Not checked yetcites [19] Wray, N. R., Purcell, S. M. & Visscher, P. M. Synthetic associations created by rare variants do not explain most GWAS results. PLoS Biol. 9, e1000579 (2011). source

In the paper

“In other words, rare variants alone cannot explain the demographic distribution of disease incidence.”

In the paper

“A major argument against rare variants as the predominant source of missing heritability comes from the analysis of allele frequency distributions of GWAS data19.”

What the sources say

• Not checked yetcites [19] Wray, N. R., Purcell, S. M. & Visscher, P. M. Synthetic associations created by rare variants do not explain most GWAS results. PLoS Biol. 9, e1000579 (2011). source

In the paper

“perusal of the Online Mendelian Inheritance in Man (OMIM) database provides examples of near-Mendelian cases of many relatively common disorders42.”

What the sources say

• Not checked yetcites [42] Hamosh, A. et al. Online Mendelian Inheritance in Man (OMIM), a knowledgebase of human genes and genetic disorders. Nucl. Acids Res. 30, 52–55 (2002). source

In the paper

“Thus, a common variant present in 20% of cases that mathematically explains one percent of disease susceptibility may actually simply report the activity of two or three rare variants that each substantially elevate risk in one or two percent of the cases.”

In the paper

“In many cases, causal common variants associated with a continuous endophenotype have been associated with disease [eg80–82]”

What the sources say

• Not checked yetcites [80] Kilpeläinen, T. O. et al. Genetic variation near IRS1 associates with reduced adiposity and an impaired metabolic profile. Nature Genet. 43, 753–760 (2011). source
• Not checked yetcites [81] Bis, J. C. et al. Meta-analysis of genome-wide association studies from the CHARGE consortium identifies common variants associated with carotid intima media thickness and plaque. Nature Genet. 43, 940–947 (2011). source
• Not checked yetcites [82] Speliotes, E. K. et al. Genome-wide association analysis identifies variants associated with nonalcoholic fatty liver disease that have distinct effects on metabolic traits. PLoS Genet. 7, e1001324 (2011). source

In the paper

“Due to improved methods for imputation, most minor alleles down to 5% frequency can now be inferred with high accuracy, if the reference panel is appropriately matched for population structure129.”

What the sources say

• Not checked yetcites [129] Shea, J. et al. Comparing strategies to fine-map the association of common SNPs at chromosome 9p21 with type 2 diabetes and myocardial infarction. Nature Genet. 43, 801–805 (2011). source

In the paper

“Thus, tumor samples have discrete transcriptome profile differences89,90”

What the sources say

• Not checked yetcites [89] Alizadeh, A. A. et al. Distinct types of diffuse large B-cell lymphoma identified by gene expression profiling. Nature 403, 503–511 (2000). source
• Not checked yetcites [90] Slavov, N. & Dawson, K. A. Correlation signature of the macroscopic states of the gene regulatory network in cancer. Proc. Natl Acad. Sci. USA 106, 4079–4084 (2009). source

In the paper

“Similarly, at least some cortex samples from autistic brains converge on a common transcriptional profile91.”

What the sources say

• Not checked yetcites [91] Voineagu, I. et al. Transcriptomic analysis of autistic brain reveals convergent molecular pathology. Nature 474, 380–384 (2011). source

In the paper

“the phenomenon of transgressive segregation in mapping populations of mice and flies established from eight founder strains provides strong empirical support for the existence of common polygenes94–96.”

What the sources say

• Not checked yetcites [94] Aylor, D. L. et al. Genetic analysis of complex traits in the emerging Collaborative Cross. Genome Res. 21, 1213–12122 (2011). source
• Not checked yetcites [95] Philip, V. M. et al. Genetic analysis in the Collaborative Cross breeding population. Genome Res. 21, 1223–1238 (2011). source
• Not checked yetcites [96] Macdonald, S. J. & Long, A. D. Joint estimates of quantitative trait locus effect and frequency using synthetic recombinant populations of Drosophila melanogaster. Genetics 176, 1261–1281 (2007). source

In the paper

“Threshold-dependent models77 postulate that disease is more likely to arise in individuals who have extreme values of underlying endophenotypes78,79.”

What the sources say

• Not checked yetcites [77] Falconer, D. S. Introduction to Quantitative Genetics Ch. 18 (Longman, New York, 1981).
• Not checked yetcites [78] Cannon, T. D. & Keller, M. C. Endophenotypes in the genetic analysis of mental disorders. Annu. Rev. Clin. Psychol. 2, 267–290 (2006). source
• Not checked yetcites [79] Kendler, K. S. & Meale, M. C. Endophenotype: a conceptual analysis. Mol. Psychiatry 15, 789–797 (2010). source

In the paper

“eQTL analysis shows that gene expression and splicing are heavily influenced by common variants, possibly for the majority of transcripts86–88.”

What the sources say

• Not checked yetcites [86] Cookson, W. et al. Mapping complex disease traits with global gene expression. Nature Rev. Genet. 10, 184–194 (2009). source
• Not checked yetcites [87] Majewski, J. & Pastinen, T. The study of eQTL variations by RNA-seq: from SNPs to phenotypes. Trends Genet. 27, 72–79 (2011). source
• Not checked yetcites [88] Lalonde, E. et al. RNA sequencing reveals the role of splicing polymorphisms in regulating human gene expression. Genome Res. 21, 545–554 (2011). source

In the paper

“In the infinitesimal model, disease risk ought to blend smoothly when unrelated people have children.”

In the paper

“It is the common variant of moderate effect version of the CD-CV model that needs to be discarded.”

In the paper

“The overwhelming evidence from classical quantitative genetics is that traits are regulated by many loci with a wide range of effect sizes.”

In the paper

“(i) the pervasiveness of differences in disease risk between geographic areas that are not obviously explained by genetic differentiation”

In the paper

“while in an unknown proportion of cases, QTL will turn out to be due to multiple linked variants that coarse mapping fails to resolve into individual SNPs103.”

What the sources say

• Not checked yetcites [103] Pasyukova, E. G., Vieira, C. & Mackay, T. F. C. Deficiency mapping of quantitative trait loci affecting longevity in Drosophila melanogaster. Genetics 156, 1129–1146 (2000). source

In the paper

“This does not counter the existence of thousands of small effect loci affecting each trait or disease risk profile, but it suggests that the narrow-sense genetic effects alone are unlikely to be sufficient explanation.”

In the paper

“Simply put, the data is generally consistent with the infinitesimal model to a first approximation, even where variants are yet to be identified.”

In the paper

“Granularity of traits is difficult to document, but facial features provide a good example of a suite of traits that do not simply follow either blending or Mendelian inheritance105.”

What the sources say

• Not checked yetcites [105] Jelenkovic, A., Poveda, A,, Susanne, C. & Rebato, E. Contribution of genetics and environment to craniofacial anthropometric phenotypes in Belgian nuclear families. Hum. Biol. 80, 637–654 (2008). source

In the paper

“By contrast, various blood disorders have been shown to correlate with extreme values for the major vectors of modules of gene expression92.”

What the sources say

• Not checked yetcites [92] Chaussabel, D. et al. A modular analysis framework for blood genomics studies: application to systemic lupus erythematosus. Immunity 29, 150–164 (2008). source

In the paper

“As with the rare allele model, infinitesimal effects are also not consistent with a wide range of demographic effects that are indicative of GxE interactions and complex genetic interactions.”

In the paper

“While there has been a very public focus on the failure of GWAS to find the missing heritability5,6, the simplest explanation for this is that the expectations were based on unrealistic prior assumption of effect sizes.”

What the sources say

• Not checked yetcites [5] Maher, B. Personal genomes: the case of the missing heritability. Nature 456, 18–21 (2008). source
• Not checked yetcites [6] Manolio, T. A. et al. Finding the missing heritability of complex diseases. Nature 461, 747–753 (2009). This paper provides a compendium of arguments, which were assembled by participants in a US National Institutes of Health (NIH) workshop, relating to the possible sources of missing heritability. source

In the paper

“In fact, sample sizes can be extrapolated from the range of variant effects in initial discovery samples12”

What the sources say

• Not checked yetcites [12] Park, J. H. et al. Estimation of effect size distribution from genome-wide association studies and implications for future discoveries. Nature Genet. 42, 570–575 (2010). This paper discusses how the true number of associations and their effect sizes can be inferred from observed GWAS results. source

In the paper

“The larger the number of alleles affecting a trait, the lower the among-individual variance should be under random mating since most individuals will share similar numbers of risk alleles.”

In the paper

“in the case of height, the GIANT consortium (http://www.broadinstitute.org/collaboration/giant/) confirmed the inferences from 30,000 individuals100 when they jumped to 180,000, finding an additional 180 or so loci14.”

What the sources say

• Not checked yetcites [100] Weedon, M. N. et al. Genome-wide association analysis identifies 20 loci that influence adult height. Nature Genet. 40, 575–583 (2008). source
• Not checked yetcites [14] Lango-Allen, H. et al. Hundreds of variants clustered in genomic loci and biological pathways affect human height. Nature 467, 832–838 (2010). source

In the paper

“GWAS has successfully identified thousands of common variants99”

What the sources say

• Not checked yetcites [99] Manolio, T. A., Brooks, L. D. & Collins, F. S. A HapMap harvest of insights into the genetics of common disease. J. Clin. Invest. 118, 1590–1605 (2008). source

In the paper

“re-sequencing of evolved outbred populations of Drosophila melanogaster has provided strong support for selection on thousands of variants being responsible for changes in the highly complex traits of body size and fecundity97,98.”

What the sources say

• Not checked yetcites [97] Burke, M. K. et al. Genome-wide analysis of a long-term evolution experiment with Drosophila. Nature 467, 587–590 (2010). This paper uses an 'evolve-and-resequence' strategy to demonstrate the pervasive polygenic basis of complex traits. source
• Not checked yetcites [98] Turner, T. L. et al. Population-based resequencing of experimentally evolved populations reveals the genetic basis of body size variation in Drosophila melanogaster. PLoS Genet. 7, e1001336 (2011). source

In the paper

“(iii) conditioning of the risk for one disease on another disease in the same individual106,107.”

What the sources say

• Not checked yetcites [106] Rzhetsky, A., Wajngurt, D., Park, N. & Zheng, T. Probing genetic overlap among complex human phenotypes. Proc. Natl Acad. Sci. USA 104, 11694–11699 (2007). source
• Not checked yetcites [107] Ashley, E. A. et al. Clinical assessment incorporating a personal genome. Lancet 375, 1525–1535 (2010). This study develops a strategy that integrates whole-genome sequence and environmental exposure information to assess personal risk of disease. source

In the paper

“Once it is accepted that most alleles are associated with relative risks less than 1.2, it becomes clear that hundreds of thousands of individuals are required to identify more than a few dozen loci than explain more than 20% of the variance.”

In the paper

“In many cases as well, the effect size estimated in the cross will be an overestimate due to the Beavis effect/winner’s curse101,102”

What the sources say

• Not checked yetcites [101] Xu, S. Theoretical basis of the Beavis effect. Genetics 165, 2259–2268 (2003). source
• Not checked yetcites [102] Zhong, R. & Prentice, R. L. Correcting “winner's curse” in odds ratios from genome-wide association findings for major complex human diseases. Genet. Epidemiol. 34, 78–91 (2010). source

In the paper

“This is as true of threshold-dependent characters and cryptic variation93 as it is of continuous variation.”

What the sources say

• Not checked yetcites [93] Gibson, G. & Dworkin, I. M. Uncovering cryptic genetic variation. Nature Rev. Genet. 5, 681–690 (2004). source

In the paper

“In model organism research, both pedigree analyses and genetic crosses in which linkage mapping is used to localize QTL almost always lead to the identification of multiple variants influencing the quantitative trait of interest20.”

What the sources say

• Not checked yetcites [20] Mackay, T. F. C. The genetic architecture of quantitative traits. Annu. Rev. Genet. 35, 303–339 (2001). source

In the paper

“in some cases these have been confirmed by in vitro biochemical assays for structural and regulatory effects [eg83–85].”

What the sources say

• Not checked yetcites [83] Musunuru, K. et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature 466, 714–719 (2010). This was an important case study showing how to go from association study to molecular function of a specific variant. source
• Not checked yetcites [84] Wang, Y. et al. Whole-genome association study identifies STK39 as a hypertension susceptibility gene. Proc. Natl Acad. Sci. USA 106, 226–231 (2009). source
• Not checked yetcites [85] Bertram, L., Lill, C. M. & Tanzi, R. E. The genetics of Alzheimer disease: back to the future. Neuron 68, 270–281 (2010). source

In the paper

“The typical resolution of the observation that disease is categorical (people are either cases or controls) yet genetic contributions are complex, is that disease is generally a threshold-dependent response superimposed over a continuous liability120.”

What the sources say

• Not checked yetcites [120] Rendel, J. M. Canalization and Gene Control (Academic Press, New York, 1967).

In the paper

“MutDB112(http://mutdb.org/) contains a much larger number of rare coding variants that are either associated with disease or predicted to be damaging.”

What the sources say

• Not checked yetcites [112] Stenson, P. D. et al. The Human Gene Mutation Database: 2008 update. Genome Med. 1, 13 (2009). source

In the paper

“Missing heritability is inferred with respect to heritability estimates that generally derive from family studies, where ironically direct estimates of the genetic contribution are lacking.”

In the paper

“but it must be recognized that even large effect alleles are subject to background modification and incomplete penetrance.”

In the paper

“Consequently, it is difficult to actually estimate how much of the variance GWAS-captured variants should explain in outbred populations.”

In the paper

“Liability is quite likely to be established by the additive and infinitesimal contributions of hundreds of polymorphisms, each regulating a series of biochemical traits that impinge on the phenotype: metabolite abundance, gene expression, and hormone levels, for example.”

In the paper

“However, in the case of height, where heritability is as high as 80%, over 50% of the phenotype can be attributed to common variants using the mixed linear modeling approach71”

What the sources say

• Not checked yetcites [71] Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nature Genet. 42, 565–569 (2010). This paper introduces a multivariate approach for capturing the effects of common variant associations genome-wide. source

In the paper

“and after adjustment for allele frequency skews and incomplete LD, essentially the entire genetic contribution has been ascribed to genotypic variation.”

What the sources say

• Not checked yetcites [71] Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nature Genet. 42, 565–569 (2010). This paper introduces a multivariate approach for capturing the effects of common variant associations genome-wide. source

In the paper

“Yet the same methods applied to BMI do not capture much more than half of the expected genotypic variance, and it is not clear that they are as efficient for schizophrenia, arthritis or intelligence75,76.”

What the sources say

• Not checked yetcites [75] Yang, J. et al. Genome partitioning of genetic variation for complex traits using common SNPs. Nature Genet. 43, 519–525 (2011). source
• Not checked yetcites [76] Davies, G. et al. Genome-wide association studies establish that human intelligence is highly heritable and polygenic. Mol. Psychiatry 16, 996–1005 (2011). source

In the paper

“over 50% of the phenotype can be attributed to common variants using the mixed linear modeling approach71”

What the sources say

• Not checked yetcites [71] Yang, J. et al. Common SNPs explain a large proportion of the heritability for human height. Nature Genet. 42, 565–569 (2010). This paper introduces a multivariate approach for capturing the effects of common variant associations genome-wide. source

In the paper

“The case of protection against anemia in chronic hepatitis C, where the initial GWAS discovery clearly captures two less common causal coding variants at the ITPA locus, is a good example110.”

What the sources say

• Not checked yetcites [110] Fellay, J. et al. ITPA gene variants protect against anemia in patients treated for chronic hepatitis C. Nature 464, 405–408 (2010). source

In the paper

“The notion that even rare variants have variable penetrance thus blurs the distinction between infinitesimal and major-effect models of disease susceptibility.”