Estimation of effect size distribution from genome-wide association studies and implications for future discoveries.
We report a set of tools to estimate the number of susceptibility loci and the distribution of their effect sizes for a trait on the basis of discoveries from existing genome-wide association studies (GWASs). We propose statistical power calculations for future GWASs using estimated distributions of effect sizes. Using reported GWAS findings for height, Crohn's disease and breast, prostate and colorectal (BPC) cancers, we determine that each of these traits is likely to harbor additional loci within the spectrum of low-penetrance common variants. These loci, which can be identified from sufficiently powerful GWASs, together could explain at least 15-20% of the known heritability of these traits. However, for BPC cancers, which have modest familial aggregation, our analysis suggests that risk models based on common variants alone will have modest discriminatory power (63.5% area under curve), even with new discoveries.
Park
Ju-Hyun
JH
Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, US Department of Health and Human Services, Rockville, Maryland, USA.
Wacholder
Sholom
S
Gail
Mitchell H
MH
Peters
Ulrike
U
Jacobs
Kevin B
KB
Chanock
Stephen J
SJ
Chatterjee
Nilanjan
N
D000465:Algorithms; D001827:Body Height / Q000235:genetics; D001943:Breast Neoplasms / Q000235:genetics; D015179:Colorectal Neoplasms / Q000235:genetics; D003424:Crohn Disease / Q000235:genetics; D005260:Female; D005787:Gene Frequency; D020022:Genetic Predisposition to Disease / Q000235:genetics*; D055106:Genome-Wide Association Study / Q000379:methods*; D005838:Genotype; D006801:Humans; D008297:Male; D008957:Models, Genetic; D019683:Penetrance; D020641:Polymorphism, Single Nucleotide; D011471:Prostatic Neoplasms / Q000235:genetics; D018709:Statistics, Nonparametric