Summary Statistics: Systematic comparison of phenome-wide admixture mapping and genome-wide association at biobank-scale

This dataset contains GWAS and admixture mapping (AM) summary statistics from a phenome-wide comparison of AM and genome-wide association studies (GWAS) conducted in Hispanic/Latino (HL; N=14,876) and African American (AA; N=8,819) participants from the BioMe Biobank at the Icahn School of Medicine at Mount Sinai, New York. Summary statistics are provided for phenotypes reaching genome-wide significance thresholds in the HL and AA cohorts. Phenotypes were defined using the phecode mapping system (v1.2). GWAS analyses were performed using SAIGE v1.1.6.2 on TOPMed-imputed genotypes, accounting for sample relatedness via a genetic relationship matrix (GRM), with age, sex, genotyping chip, and the first 10 principal components included as covariates. Genome-wide significance was defined as p<5×10⁻⁸ with a post-hoc filter requiring a minimum allele count in cases of 40. Admixture mapping was performed using SAIGE v1.1.6.2 on local ancestry calls inferred using GNOMIX. Three-way local ancestry (EUR, AFR, NAT) was inferred in HL and two-way local ancestry (EUR, AFR) in AA. Genome-wide significance thresholds were p<4.88×10⁻⁶ in HL and p<1.60×10⁻⁵ in AA. Access can be requested for replication purposes by contacting the corresponding author at [e-mail] through appropriate data sharing agreements. Individual genetic and phenotypic information from BioMe are not publicly available due to data privacy laws. Additional summary statistics can be made available for the purposes of replicating the results by contacting the corresponding author and through appropriate collaboration and/or data sharing agreements. These summary statistics are provided to support open science and reproducibility in accordance with Nature Communications data sharing policies. Pipeline code is available at https://github.com/sinai-igh/admix_phewas/ (DOI: https://zenodo.org/records/19861147). This dataset is associated with the following publication: Cullina et al. (2026) "Systematic comparison of phenome-wide admixture mapping and genome-wide association at biobank-scale." Nature Communications.