Heritability, weak effects, and rare variants in genomewide association studies.

In less than 5 years, genomewide association studies (GWASs)2 have completely changed the landscape of human genetic research. Our increasing knowledge of the human genome sequence and its variation (http://hapmap.ncbi.nlm.nih.gov/) and technological advances in the design of genotyping microarrays have been instrumental in this evolution; however, an essential factor for success has been the use of large international collaborations for assembling studies that encompass genomewide data for tens or hundreds of thousands of individuals. The number of firmly replicated trait-associated loci that have been identified in GWASs is impressive (http://www.genome.gov/gwastudies), but the contribution of individual single-nucleotide polymorphisms (SNPs) to the studied phenotypes is weak, with rare exceptions. In this article, this aspect of GWASs and some of its implications are discussed. Heritability is the part of the variation of a trait in a population that is contributed by genetic differences among individuals. The heritabilities of common diseases that have been evaluated in family or twin studies are often quite high, frequently reaching 50%. GWAS results provide support for the concept of a polygenic framework underlying complex diseases in which genetic susceptibility (liability) is due to a large number of cumulative weak effects contributed by variants covering the entire range of allele frequencies. According to this model, common disorders may be considered quantitative traits (1). For example, consider height, a trait with a high heritability (approximately 80%). A metaanalysis of GWASs (meta-GWAS) comprising >200,000 individuals revealed 180 statistically significant SNPs that together explained approximately 10% of the variance in adult height (2). In another GWAS of height involving about 4000 individuals, the investigators, instead of testing SNPs one at a time, used a model that accounts for the genetic relatedness among pairs of individuals to estimate the genetic variance explained by the entire set of 300 000 markers on …

[1]  Gang Shi,et al.  Optimum designs for next‐generation sequencing to discover rare variants for common complex disease , 2011, Genetic epidemiology.

[2]  D. G. Clark,et al.  Common variants in MS4A4/MS4A6E, CD2uAP, CD33, and EPHA1 are associated with late-onset Alzheimer’s disease , 2011, Nature Genetics.

[3]  D. Allison,et al.  Beyond Missing Heritability: Prediction of Complex Traits , 2011, PLoS genetics.

[4]  Dan M Roden,et al.  A rare variant in MYH6 is associated with high risk of sick sinus syndrome , 2011, Nature Genetics.

[5]  Thomas W. Mühleisen,et al.  Large-scale association analysis identifies 13 new susceptibility loci for coronary artery disease , 2011, Nature Genetics.

[6]  Naomi R. Wray,et al.  Synthetic Associations Created by Rare Variants Do Not Explain Most GWAS Results , 2011, PLoS biology.

[7]  E. Zeggini,et al.  Synthetic Associations Are Unlikely to Account for Many Common Disease Genome-Wide Association Signals , 2011, PLoS biology.

[8]  P. Madsen,et al.  Sort1, encoded by the cardiovascular risk locus 1p13.3, is a regulator of hepatic lipoprotein export. , 2010, Cell metabolism.

[9]  E. Zeggini,et al.  Synthetic associations in the context of genome-wide association scan signals , 2010, Human molecular genetics.

[10]  Ayellet V. Segrè,et al.  Hundreds of variants clustered in genomic loci and biological pathways affect human height , 2010, Nature.

[11]  Olle Melander,et al.  From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus , 2010, Nature.

[12]  Tanya M. Teslovich,et al.  Biological, Clinical, and Population Relevance of 95 Loci for Blood Lipids , 2010, Nature.

[13]  V. Salomaa,et al.  Excess of rare variants in genes identified by genome-wide association study of hypertriglyceridemia , 2010, Nature Genetics.

[14]  P. Visscher,et al.  Common SNPs explain a large proportion of the heritability for human height , 2010, Nature Genetics.

[15]  Eric Boerwinkle,et al.  Association of Genome-Wide Variation With the Risk of Incident Heart Failure in Adults of European and African Ancestry: A Prospective Meta-Analysis From the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium , 2010, Circulation. Cardiovascular genetics.

[16]  David B. Goldstein,et al.  Rare Variants Create Synthetic Genome-Wide Associations , 2010, PLoS biology.

[17]  L. Peltonen,et al.  The impact of newly identified loci on coronary heart disease, stroke and total mortality in the MORGAM prospective cohorts , 2009, Genetic epidemiology.

[18]  R. Collins,et al.  Newly identified loci that influence lipid concentrations and risk of coronary artery disease , 2008, Nature Genetics.

[19]  C. Gieger,et al.  Genomewide association analysis of coronary artery disease. , 2007, The New England journal of medicine.

[20]  M. Pericak-Vance,et al.  Apolipoprotein E: high-avidity binding to beta-amyloid and increased frequency of type 4 allele in late-onset familial Alzheimer disease. , 1993, Proceedings of the National Academy of Sciences of the United States of America.

[21]  Tanya M. Teslovich,et al.  Association analyses of 249,796 individuals reveal 18 new loci associated with body mass index , 2010 .

[22]  N. Wray,et al.  Multi-locus models of genetic risk of disease , 2010, Genome Medicine.

[23]  L. Fauchier,et al.  A genome-wide association study identifies two loci associated with heart failure due to dilated cardiomyopathy , 2022 .