Global medical genetics · 2026
Integrating multi-omics and mendelian randomization identifies therapeutic targets for Lichen Sclerosus: A druggable genome-wide study.
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Wang Shuai, Wang Pengfei, Li Haiping, Guan Xinyi, Ji Shuling, Zhang Xian, Chen Yuanhong, Li Nan, Li Hu, Xue Lujiadai, Zhao Chunmei
Аннотация
BACKGROUND: Lichen sclerosus (LS) is a chronic inflammatory skin disease characterized by limited treatment options and an unclear pathogenesis. This study aimed to identify potential therapeutic targets for LS by integrating druggable genome (DG) data with multi-omics and Mendelian randomization (MR).
METHODS: Blood expression quantitative trait loci (eQTLs) were obtained from the eQTLGen consortium, and protein quantitative trait loci (pQTLs) were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) and the Decode cohorts. Outcome data for LS were derived from the FinnGen R12 database. We performed two-sample MR analyses to estimate the causal effects of druggable genes on LS, followed by sensitivity analyses, Steiger directionality tests, and multi-omics integration. For multi-omics integration, we cross-referenced eQTL- and pQTL-derived causal genes to identify overlapping genes supported by both transcriptomic and proteomic evidence. Functional concordance was further assessed by comparing effect directions and magnitudes between the two molecular layers. Potential drugs were predicted using the DGIdb database, and molecular docking was performed using CB-Dock2.
RESULTS: After rigorous screening and Holm-Bonferroni correction, we identified 50 druggable genes (eQTL-derived) and 35 druggable proteins (pQTL-derived) with causal effects on LS. Integrative multi-omics analysis revealed integrin subunit beta 2 (ITGB2) and poly(ADP-ribose) polymerase 1 (PARP1) as the most robust therapeutic targets. Phenome-wide association study (PheWAS) analysis indicated no significant pleiotropic effects for these genes. Protein-protein interaction and pathway enrichment analyses showed that these genes are involved in integrin-mediated cell adhesion and ADP-ribosylation processes. The DGIdb database predicted 24 potential drugs targeting ITGB2 and PARP1, and molecular docking confirmed strong binding affinities (Vina score < -5).
CONCLUSION: This integrative MR study identifies ITGB2 and PARP1 as promising therapeutic targets for LS, providing a foundation for future drug development and personalized treatment strategies.
METHODS: Blood expression quantitative trait loci (eQTLs) were obtained from the eQTLGen consortium, and protein quantitative trait loci (pQTLs) were sourced from the UK Biobank Pharma Proteomics Project (UKB-PPP) and the Decode cohorts. Outcome data for LS were derived from the FinnGen R12 database. We performed two-sample MR analyses to estimate the causal effects of druggable genes on LS, followed by sensitivity analyses, Steiger directionality tests, and multi-omics integration. For multi-omics integration, we cross-referenced eQTL- and pQTL-derived causal genes to identify overlapping genes supported by both transcriptomic and proteomic evidence. Functional concordance was further assessed by comparing effect directions and magnitudes between the two molecular layers. Potential drugs were predicted using the DGIdb database, and molecular docking was performed using CB-Dock2.
RESULTS: After rigorous screening and Holm-Bonferroni correction, we identified 50 druggable genes (eQTL-derived) and 35 druggable proteins (pQTL-derived) with causal effects on LS. Integrative multi-omics analysis revealed integrin subunit beta 2 (ITGB2) and poly(ADP-ribose) polymerase 1 (PARP1) as the most robust therapeutic targets. Phenome-wide association study (PheWAS) analysis indicated no significant pleiotropic effects for these genes. Protein-protein interaction and pathway enrichment analyses showed that these genes are involved in integrin-mediated cell adhesion and ADP-ribosylation processes. The DGIdb database predicted 24 potential drugs targeting ITGB2 and PARP1, and molecular docking confirmed strong binding affinities (Vina score < -5).
CONCLUSION: This integrative MR study identifies ITGB2 and PARP1 as promising therapeutic targets for LS, providing a foundation for future drug development and personalized treatment strategies.