Dubey Anupama, Kumar Praveen, Khan Tahseen, Kateriya Suneel, Tripathi Dinesh Mani, Yadav Umesh C S
Special Center for Systems Medicine, Jawaharlal Nehru University, New Delhi, 110067, India; Special Center for Molecular Medicine, Jawaharlal Nehru University, New Delhi, 110067, India.
Special Center for Molecular Medicine, Jawaharlal Nehru University, New Delhi, 110067, India.
Comput Biol Med. 2025 Aug;194:110532. doi: 10.1016/j.compbiomed.2025.110532. Epub 2025 Jun 6.
Chronic obstructive pulmonary disease (COPD) and Metabolic dysfunction-associated steatotic liver disease (MASLD) are complex, heterogenous diseases caused by genetic, lifestyle, and environmental factors, with systemic inflammation and redox imbalance playing a significant role in the pathogenesis of both diseases. However, a common mechanism that correlates the two diseases remains unclear. Here, we have used a bioinformatics approach to understand the molecular network and pathway to predict potentially common genes that can be targeted to prevent these conditions. This study used three online databases and clinical datasets on Gene Expression Omnibus. PPI network analyses, gene-ontology, and pathway analysis were done utilizing advanced bioinformatics tools such as Enrichr, String, and Cytoscape. Furthermore, candidate drug prediction was also performed using DSigDB. Bioinformatic analysis of databases and datasets identified twelve common genes (CXCL8, MMP9, IL1β, ITGB2, SPP1, PTGS2, SOCS3, BAX, GDF15, S100A8, CCL2, and MYC) in COPD and MASLD. It revealed shared signaling pathways and gene ontology (biological processes, cellular components, and molecular functions) in both diseases. Five hub genes (CCL2, CCL5, CXCL8, CXCL10, and CXCL1) were also identified, which play a significant role in COPD and MASLD. The study also predicted potential drugs against the common differentially expressed proteins using DSigDB. We performed RT-qPCR to validate the differential expression of the common genes in COPD and MASLD models, which confirmed the in-silico data. Furthermore, we investigated the effect of one of the predicted drug molecules, NS-398, a selective COX-2 inhibitor, in the COPD and MASLD models, which showed significant inhibition of expression of many upregulated genes, highlighting its potential therapeutic impact. To conclude, data obtained from this study showed key common and hub genes that may be involved in COPD and MASLD pathophysiology and highlight the potential mechanisms underlying their activation.
慢性阻塞性肺疾病(COPD)和代谢功能障碍相关脂肪性肝病(MASLD)是由遗传、生活方式和环境因素引起的复杂异质性疾病,全身炎症和氧化还原失衡在这两种疾病的发病机制中起重要作用。然而,将这两种疾病联系起来的共同机制仍不清楚。在此,我们采用生物信息学方法来理解分子网络和途径,以预测可作为预防这些疾病靶点的潜在共同基因。本研究使用了三个在线数据库以及基因表达综合数据库(Gene Expression Omnibus)中的临床数据集。利用Enrichr、String和Cytoscape等先进的生物信息学工具进行了蛋白质-蛋白质相互作用(PPI)网络分析、基因本体分析和通路分析。此外,还使用DSigDB进行了候选药物预测。对数据库和数据集的生物信息学分析确定了COPD和MASLD中的12个共同基因(CXCL8、MMP9、IL1β、ITGB2、SPP1、PTGS2、SOCS3、BAX、GDF15、S100A8、CCL2和MYC)。研究揭示了两种疾病中共享的信号通路和基因本体(生物学过程、细胞成分和分子功能)。还确定了五个枢纽基因(CCL2、CCL5、CXCL8、CXCL10和CXCL1),它们在COPD和MASLD中起重要作用。该研究还使用DSigDB预测了针对常见差异表达蛋白的潜在药物。我们进行了逆转录定量聚合酶链反应(RT-qPCR)以验证COPD和MASLD模型中共同基因的差异表达,这证实了计算机模拟数据。此外,我们研究了一种预测的药物分子NS-398(一种选择性环氧化酶-2(COX-2)抑制剂)在COPD和MASLD模型中的作用,结果显示其对许多上调基因的表达有显著抑制作用,突出了其潜在的治疗作用。总之,本研究获得的数据显示了可能参与COPD和MASLD病理生理学的关键共同基因和枢纽基因,并突出了它们激活的潜在机制。