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Background Transcriptome-wide association studies (TWAS) integrate genetically regulated gene expression with genome-wide association study (GWAS) data to identify gene–trait associations. These analyses rely on accurate gene expression prediction models trained using genotype and transcriptomic data from the same set of individuals. However, most publicly available TWAS models are based on resources that predominantly consist of participants of European ancestry. This European ancestry bias limits the transferability and generalizability of gene expression models across diverse populations. Description Using genotype and gene expression data from the Genotype-Tissue Expression (GTEx) Project, we curated datasets comprising 689 European ancestry individuals and 111 African American individuals after quality control and confounder adjustment. We then developed ancestry-specific cross-tissue gene expression imputation models using the UTMOST framework. These models are accessible through AGEMdb, a web-based database that allows users to browse, search, and download gene expression imputation models with flexible filtered options (e.g. by tissue and gene). By incorporating African American-specific models, AGEMdb addresses the European ancestry bias present in existing TWAS resources and supports more equitable gene–trait association analyses. Conclusion AGEMdb provides a valuable resource for ancestry-specific TWAS, which promotes more inclusive studies that support the advancement of equitable genomic research.
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Pagnuco et al. (2026) studied this question.
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