The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants

• Published in: European journal of human genetics : EJHG Vol. 24; no. 8; pp. 1202 - 1205
• Main Authors: Fadista, João, Manning, Alisa K, Florez, Jose C, Groop, Leif
• Format: Journal Article
• Language: English
• Published: England Nature Publishing Group 01.08.2016
• Subjects: Alleles; Basic Medicine; Bioinformatics; Consortia; Diabetes; Diabetes mellitus; Diabetes mellitus (non-insulin dependent); Diabetes Mellitus, Type 2 - genetics; Encyclopedias; Epidemiology; Exome; Exploration; Gene frequency; Genetic analysis; Genetic Heterogeneity; Genetics; Genome-Wide Association Study - methods; Genome-Wide Association Study - standards; Genomes; Haplotypes; Humans; Linkage Disequilibrium; Medical and Health Sciences; Medical Genetics; Medicin och hälsovetenskap; Medicine; Medicinsk genetik; Medicinska och farmaceutiska grundvetenskaper; Mutation Rate; Population genetics; Principal components analysis; Short Report; Denmark; Sweden; United States > US; Massachusetts; Finland
• ISSN: 1018-4813; 1476-5438; 1476-5438
• DOI: 10.1038/ejhg.2015.269

Genome-wide association studies (GWAS) have long relied on proposed statistical significance thresholds to be able to differentiate true positives from false positives. Although the genome-wide significance P-value threshold of 5 × 10(-8) has become a standard for common-variant GWAS, it has not been updated to cope with the lower allele frequency spectrum used in many recent array-based GWAS studies and sequencing studies. Using a whole-genome- and -exome-sequencing data set of 2875 individuals of European ancestry from the Genetics of Type 2 Diabetes (GoT2D) project and a whole-exome-sequencing data set of 13 000 individuals from five ancestries from the GoT2D and T2D-GENES (Type 2 Diabetes Genetic Exploration by Next-generation sequencing in multi-Ethnic Samples) projects, we describe guidelines for genome- and exome-wide association P-value thresholds needed to correct for multiple testing, explaining the impact of linkage disequilibrium thresholds for distinguishing independent variants, minor allele frequency and ancestry characteristics. We emphasize the advantage of studying recent genetic isolate populations when performing rare and low-frequency genetic association analyses, as the multiple testing burden is diminished due to higher genetic homogeneity.