{"doi":"10.17615/s3pg-t077","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 (MAF) 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 MAF between strata. Stratified analysis of BMI by ancestry group and sex reduced over-all 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 compare to λGC = 1.027 for MetaCor.","journal":"UNC Libraries","year":2020,"id":141062,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9433,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2020-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":17004,"name":"Tamar Sofer","orcid":"0000-0001-8520-8860","position":1,"is_corresponding":false},{"id":91398,"name":"Carmen R. Isasi","orcid":"0000-0003-2700-9593","position":2,"is_corresponding":false},{"id":90132,"name":"Qibin Qi","orcid":"0000-0002-2687-1758","position":3,"is_corresponding":false},{"id":378328,"name":"John R. Shaffer","orcid":"0000-0003-1897-1131","position":4,"is_corresponding":false},{"id":6899,"name":"Cathy C. Laurie","orcid":"0000-0003-2572-4040","position":5,"is_corresponding":false},{"id":11261,"name":"Mariaelisa Graff","orcid":"0000-0001-6380-1735","position":6,"is_corresponding":false},{"id":25021,"name":"Adrienne M. Stilp","orcid":"0000-0002-3910-0776","position":7,"is_corresponding":false},{"id":11361,"name":"Kari E. North","orcid":"0000-0002-8903-0366","position":8,"is_corresponding":false},{"id":25023,"name":"Adam A. Szpiro","orcid":"0000-0003-4995-238X","position":9,"is_corresponding":false},{"id":24965,"name":"Stephanie M. Gogarten","orcid":"0000-0002-7231-9745","position":0,"is_corresponding":true}],"reference_count":0,"raw_metadata":null,"created_at":"2026-07-18T23:17:20.701143Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}