{"title":"Integrative proteomics and metabolomics reveal important pathways and potential biomarkers in high-altitude pulmonary hypertension.","authors":"Zhuo-Ga Dan-Zeng, Yang-Jin Bai-Ma, Ju Huang, Wang-Jie Suo-Lang, Qu-Zhen Ge-Sang, Yang-Zong Suo-Na, Yuan-Sheng Wang, Zhuo-Ga Baima, Luo-Bu Ge-Sang","doi":"10.1038/s41598-025-09477-y","DOIUrl":null,"url":null,"abstract":"<p><p>High-altitude pulmonary hypertension (HAPH) is a severe condition affecting highland residents, yet its molecular mechanisms remain incompletely understood. This study aimed to investigate the pathogenesis of HAPH through integrated metabolomic and proteomic analyses. We performed untargeted metabolomics and proteomics analyses on plasma samples from HAPH patients (n=30) and matched healthy controls (n=30). Differential expression analysis, pathway enrichment, and integrated multi-omics analysis were conducted. Key findings were validated using targeted proteomics (PRM). We identified 26 differentially expressed metabolites (12 upregulated, 14 downregulated) and 35 differentially expressed proteins (5 upregulated, 30 downregulated) in HAPH patients. Integrated pathway analysis revealed significant alterations in glycerophospholipid metabolism (PC(20:4/8Z,11Z), FC = 2.804, P.adjust = 0.047), immune response (IGLL1, FC = -1.557, P.adjust = 0.003), cytoskeletal organization (MYH10, FC = 7.574, P.adjust =0.189), and oxidative stress response pathways. PRM validation confirmed the differential expression of five key proteins: ACTG1, VNN1, CKB (upregulated), and APOF and CST3 (downregulated). Our integrated multi-omics analysis reveals a complex molecular network underlying HAPH pathogenesis, characterized by coordinated changes in lipid metabolism, immune function, and cellular structure. These findings provide new insights into HAPH mechanisms and identify potential therapeutic targets for intervention.</p>","PeriodicalId":21811,"journal":{"name":"Scientific Reports","volume":"15 1","pages":"24999"},"PeriodicalIF":3.8000,"publicationDate":"2025-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12246140/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientific Reports","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1038/s41598-025-09477-y","RegionNum":2,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
High-altitude pulmonary hypertension (HAPH) is a severe condition affecting highland residents, yet its molecular mechanisms remain incompletely understood. This study aimed to investigate the pathogenesis of HAPH through integrated metabolomic and proteomic analyses. We performed untargeted metabolomics and proteomics analyses on plasma samples from HAPH patients (n=30) and matched healthy controls (n=30). Differential expression analysis, pathway enrichment, and integrated multi-omics analysis were conducted. Key findings were validated using targeted proteomics (PRM). We identified 26 differentially expressed metabolites (12 upregulated, 14 downregulated) and 35 differentially expressed proteins (5 upregulated, 30 downregulated) in HAPH patients. Integrated pathway analysis revealed significant alterations in glycerophospholipid metabolism (PC(20:4/8Z,11Z), FC = 2.804, P.adjust = 0.047), immune response (IGLL1, FC = -1.557, P.adjust = 0.003), cytoskeletal organization (MYH10, FC = 7.574, P.adjust =0.189), and oxidative stress response pathways. PRM validation confirmed the differential expression of five key proteins: ACTG1, VNN1, CKB (upregulated), and APOF and CST3 (downregulated). Our integrated multi-omics analysis reveals a complex molecular network underlying HAPH pathogenesis, characterized by coordinated changes in lipid metabolism, immune function, and cellular structure. These findings provide new insights into HAPH mechanisms and identify potential therapeutic targets for intervention.
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