Abstract
PURPOSE: Genome-wide association studies have identified numerous loci associated with POAG. However, functional insights remain limited owing to challenges from noncoding regions and complex linkage disequilibrium. We aimed to bridge these gaps in POAG by integrating genomic and multitissue transcriptomic data and identifying novel systemic regulatory genes. METHODS: We analyzed POAG genomic data from FinnGen and expression quantitative trait loci data from GTEx v8 for cross-tissue transcriptome-wide association studies. The Unified Test for Molecular Signature identified cross-tissue associations, complemented by single-tissue Transcriptome-wide association studies using Functional Summary-based Imputation for tissue-specific insights, and the Multi-marker Analysis of Genomic Annotation validated and refined results. Significant findings from the Unified Test for Molecular Signature, Functional Summary-based Imputation, and Multi-marker Analysis of Genomic Annotation were intersected to identify robust candidate genes, followed by summary data-based Mendelian randomization and colocalization analyses to explore their functional implications. RESULTS: Six candidate genes (AFAP1, CALCRL, KREMEN1, MTMR3, GFPT1, and TRIOBP) were identified with intersection evidence. Among these, CALCRL, MTMR3, and GFPT1 were novel. Summary data-based Mendelian randomization confirmed that AFAP1 (odds ratio [OR], 0.83; 95% confidence interval [CI], 0.78-0.88), CALCRL (OR, 0.86; 95% CI, 0.79-0.94), KREMEN1 (OR, 0.86; 95% CI, 0.77-0.97), and MTMR3 (OR, 0.77; 95% CI, 0.63-0.93) exhibited protective effects, and GFPT1 (OR, 1.34; 95% CI, 1.13-1.59) was identified as a risk role for POAG. CONCLUSIONS: This study identified six genes associated with POAG, three of which were novel, offering novel insights into its genetic architecture and systemic regulatory mechanisms.