title: Meta-Analysis of Genome-Wide Association Studies with Correlated Individuals: Application to the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).
abstract: Investigators often meta-analyze multiple genome-wide association studies (GWASs) to increase the power to detect associations of single nucleotide polymorphisms (SNPs) with a trait. Meta-analysis is also performed within a single cohort that is stratified by, e.g., sex or ancestry group. Having correlated individuals among the strata may complicate meta-analyses, limit power, and inflate Type 1 error. For example, in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), sources of correlation include genetic relatedness, shared household, and shared community. We propose a novel mixed-effect model for meta-analysis, "MetaCor," which accounts for correlation between stratum-specific effect estimates. Simulations show that MetaCor controls inflation better than alternatives such as ignoring the correlation between the strata or analyzing all strata together in a "pooled" GWAS, especially with different minor allele frequencies (MAFs) between strata. We illustrate the benefits of MetaCor on two GWASs in the HCHS/SOL. Analysis of dental caries (tooth decay) stratified by ancestry group detected a genome-wide significant SNP (rs7791001, P-value = 3.66×10-8, compared to 4.67×10-7 in pooled), with different MAFs between strata. Stratified analysis of body mass index (BMI) by ancestry group and sex reduced overall inflation from λGC=1.050 (pooled) to λGC=1.028 (MetaCor). Furthermore, even after removing close relatives to obtain nearly uncorrelated strata, a naïve stratified analysis resulted in λGC=1.058 compared to λGC=1.027 for MetaCor.
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
authors.forename: Tamar
authors.initials: T
authors.lastname: Sofer
authors.affiliation: Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania, United States of America.
authors.forename: John R
authors.initials: JR
authors.lastname: Shaffer
authors.affiliation: Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.
authors.forename: Mariaelisa
authors.initials: M
authors.lastname: Graff
authors.affiliation: Department of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, New York, United States of America.
authors.forename: Qibin
authors.initials: Q
authors.lastname: Qi
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
authors.forename: Adrienne M
authors.initials: AM
authors.lastname: Stilp
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
authors.forename: Stephanie M
authors.initials: SM
authors.lastname: Gogarten
authors.affiliation: Department of Epidemiology, University of North Carolina, Chapel Hill, North Carolina, United States of America.
authors.forename: Kari E
authors.initials: KE
authors.lastname: North
authors.affiliation: Department of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, New York, United States of America.
authors.forename: Carmen R
authors.initials: CR
authors.lastname: Isasi
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
authors.forename: Cathy C
authors.initials: CC
authors.lastname: Laurie
authors.affiliation: Department of Biostatistics, University of Washington, Seattle, Washington, United States of America.
authors.forename: Adam A
authors.initials: AA
authors.lastname: Szpiro
mesh_terms: D015992:Body Mass Index; D003731:Dental Caries / Q000235:genetics / Q000473:pathology; D005787:Gene Frequency; D055106:Genome-Wide Association Study; D006630:Hispanic or Latino / Q000235:genetics*; D006801:Humans; D008957:Models, Genetic; D010641:Phenotype; D020641:Polymorphism, Single Nucleotide; D011634:Public Health
keywords: effect heterogeneity; inflation; mixed models; stratified analysis