Hou Haiyan, Jiang Zhuyi, Zhu Liying
Department of Infectious Diseases, The Second Affiliated Hospital of Harbin Medical University, Harbin Medical University, Harbin, Heilongjiang, China.
Department of Dermatology, China-Japan Friendship Hospital, Capital Medical University, Beijing, China.
Medicine (Baltimore). 2025 Sep 12;104(37):e44525. doi: 10.1097/MD.0000000000044525.
Cholelithiasis is the most prevalent biliary disease globally, and mitochondrial dysfunction has been implicated in its pathogenesis. However, the exact mechanisms remain poorly understood. In this study, we used Summary-data-based Mendelian randomization (SMR) and colocalization analysis, integrating multi-omics data, to investigate the association between mitochondrial-related genes and cholelithiasis. Summary-level quantitative trait loci (QTL) data at methylation, RNA, and protein levels were retrieved from European cohort studies. We integrated multi-omics data, including methylation QTL (mQTL), expression QTL (eQTL), and protein QTL (pQTL), alongside genome-wide association studies (GWAS) data from FinnGen and the UK Biobank. SMR and colocalization analysis were employed to evaluate the causal relationship between mitochondrial-related genes and cholelithiasis. Potential therapeutic targets for cholelithiasis were further validated through phenome-wide association studies (PheWAS), functional enrichment analysis, protein-protein interaction networks (PPI), drug prediction, and molecular docking. Following integration of the multi-omics evidence, we identified 4 mitochondrial-related genes, categorized by evidence strength as: Tier 1 genes (supported by 2 omics and colocalization evidence): LIAS, HEBP1, PNKD; Tier 2 genes (supported by 2 omics): TARS2. PheWAS analysis indicated that these 4 genes were not associated with other traits. Biologically, these genes are closely related to metabolic processes. Molecular docking analysis showed high binding affinities for candidate drugs, including olmesartan and neostigmine bromide. By integrating multi-omics data, we have constructed the first causal chain of linking mitochondrial-related genes, metabolic pathways, and cholelithiasis. This study provides a theoretical foundation for personalized therapies targeting the genes LIAS, TARS2, HEBP1, and PNKD.
胆结石是全球最常见的胆道疾病，线粒体功能障碍被认为与其发病机制有关。然而，确切机制仍知之甚少。在本研究中，我们使用基于汇总数据的孟德尔随机化（SMR）和共定位分析，整合多组学数据，以研究线粒体相关基因与胆结石之间的关联。从欧洲队列研究中检索甲基化、RNA和蛋白质水平的汇总水平定量性状位点（QTL）数据。我们整合了多组学数据，包括甲基化QTL（mQTL）、表达QTL（eQTL）和蛋白质QTL（pQTL），以及来自芬兰基因库和英国生物银行的全基因组关联研究（GWAS）数据。采用SMR和共定位分析来评估线粒体相关基因与胆结石之间的因果关系。通过全表型关联研究（PheWAS）、功能富集分析、蛋白质-蛋白质相互作用网络（PPI）、药物预测和分子对接，进一步验证了胆结石的潜在治疗靶点。整合多组学证据后，我们鉴定出4个线粒体相关基因，根据证据强度分类为：1级基因（由2种组学和共定位证据支持）：LIAS、HEBP1、PNKD；2级基因（由2种组学支持）：TARS2。PheWAS分析表明，这4个基因与其他性状无关。从生物学角度来看，这些基因与代谢过程密切相关。分子对接分析显示，包括奥美沙坦和溴新斯的明在内的候选药物具有高结合亲和力。通过整合多组学数据，我们构建了第一条连接线粒体相关基因、代谢途径和胆结石的因果链。本研究为针对LIAS、TARS2、HEBP1和PNKD基因的个性化治疗提供了理论基础。
