ArticleJournal of ovarian research2025
Integrative multi-omics analysis of druggable genes for therapeutic target identification in polycystic ovary syndrome.
Article in Journal of ovarian research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Integrative Multi-omics Analysis for Prioritization of Candidate Genes in Polycystic Ovary Syndrome.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Article
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7 authors.
Funding
Abstract
backgroundPolycystic ovary syndrome (PCOS) is a common endocrine disorders in women of reproductive age with limited targeted therapies. This study aimed to identify and prioritize potential druggable genes for PCOS through a purely computational, multi-omics approach.
methodWe conducted an integrated in silico analysis leveraging publicly available datasets. A multi-omics Mendelian randomization (MR) framework was applied to 2,888 druggable genes. Our workflow incorporated two-sample MR for initial discovery of gene-PCOS associations with false discovery rate (FDR) correction, followed by validation using summary-data-based MR (SMR) and colocalization. Tissue-specific effects were assessed via cis-expression quantitative trait loci (cis-eQTL) MR in ovary, uterus, and blood, and epigenetic regulation via methylation QTL (mQTL) MR. The ovarian microenvironment was characterized using CIBERSORT and single-cell RNA sequencing (scRNA-seq). We also assessed whether immune cell traits mediate the causal pathway between cis-eQTLs and PCOS. Finally, we predicted potential drug targets using the Comparative Toxicogenomics Database and thereby performed molecular docking simulations.
resultsWe identified seven FDR-significant druggable genes associated with PCOS risk: NRBP1, LGR6, GHRL, and IPP as risk-enhancing genes, and CBLN3, VIPR1, and TFRC as protective. SMR analysis confirmed that genetically predicted NRBP1 (OR = 1.5383, p = 8.67E-04), LGR6 (OR = 1.3442, p = 0.0107), GHRL (OR = 1.3391, p = 0.0413) increased PCOS risk, while CBLN3 (OR = 0.8605, p = 4.09E-04) decreased PCOS risk. Colocalization analysis prioritized CBLN3 (PP.H4 = 86.65%) and NRBP1 (PP.H4 = 78.46%) as high-confidence targets. CBLN3 expression was protective across tissues (blood: OR = 0.8586; ovary: OR = 0.8926; uterus: OR = 0.8713), while blood NRBP1 expression increased PCOS risk (OR = 2.1003). mQTL MR analysis revealed significant locus-specific causal effects for CBLN3 and NRBP1. Immune infiltration analysis revealed CBLN3 correlated positively with resting dendritic cells (r = 0.80), and inversely with eosinophils (r=-0.72) and neutrophils (r=-0.66), while NRBP1 associated positively with activated dendritic cells (r = 0.67) and inversely with resting CD4 T cells (r=-0.77). scRNA-seq identified four subtypes of PCOS theca cells, and the expression levels of CBLN3 and NRBP1 in four subtypes were explored. Mediation analysis suggested that the protective effect of CBLN3 may be partially mediated through NKT %lymphocytes. Primary compound screening identified nine high-affinity compounds binding both CBLN3 and NRBP1 (ΔG≤-5 kcal/mol).
conclusionsUsing a comprehensive bioinformatic framework, we prioritize CBLN3 as a novel protective target and NRBP1 as a risk-associated target with multi-omics validation, thus providing mechanistically informed candidates for the development of urgently needed PCOS therapeutics.
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