XuanLian-ops/ovarian-aging-multiomics-SMR-OPERA: Multi-omics pleiotropic association analyses reveal functionally relevant genes and druggable pathways for ovarian aging

Overview Ovarian aging is characterized by the gradual decline in both the quantity and quality of oocytes and represents a major determinant of female reproductive lifespan. In this study, we integrated genome-wide association study (GWAS) summary statistics with multiple omics datasets to identify molecular traits associated with ovarian aging. The analysis includes: Proteomics (pQTL) Transcriptomics (eQTL) Splicing QTL (sQTL) Metabolomics (mQTL) Using Mendelian randomization (SMR) and cross-omics integration (OPERA), we prioritized candidate genes and biological pathways associated with ovarian aging.