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山东大学学报 (医学版) ›› 2026, Vol. 64 ›› Issue (6): 104-114.doi: 10.6040/j.issn.1671-7554.0.2025.1159

• 公共卫生与预防医学 • 上一篇    

冠心病和慢性阻塞性肺疾病多效性基因识别的跨组学整合研究

陈心怡1,2,黄鑫3,4,孙秀彬1,2,王淑康1,2,袁中尚1,2   

  1. 1.山东大学齐鲁医学院公共卫生学院生物统计学系, 山东 济南 250012;2.国家健康医疗大数据研究院, 山东 济南 250003;3.山东第一医科大学附属省立医院神经内科, 山东 济南 250021;4.山东第一医科大学(山东省医学科学院)山东省脑科学与类脑研究院, 山东 济南 250021
  • 发布日期:2026-06-29
  • 通讯作者: 袁中尚. E-mail:yuanzhongshang@sdu.edu.cn
  • 基金资助:
    国家自然科学基金(82373686);中央高校青年教师科研创新能力支持项目(SRICSPYF-ZY2025123);山东省自然科学基金(ZR2024JQ029);山东省泰山学者项目(tsqn202211025)

Integrative cross-omics analysis identifies pleiotropic genes shared by coronary artery disease and chronic obstructive pulmonary disease

CHEN Xinyi1,2, HUANG Xin3,4, SUN Xiubin1,2, WANG Shukang1,2, YUAN Zhongshang1,2   

  1. 1. Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, Shandong University, Jinan 250012, Shandong, China;
    2. National Institute for Health and Medical Big Data, Jinan 250003, Shandong, China;
    3. Department of Neurology, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan 250021, Shandong, China;
    4. Institute of Brain Science and Brain-inspired Research, Shandong First Medical University (Shandong Academy of Medical Sciences), Jinan 250021, Shandong, China
  • Published:2026-06-29

摘要: 目的 整合全转录组关联分析和复合零假设下的多效性分析,从转录组学层面探讨冠心病(coronary artery disease, CAD)-慢性阻塞性肺疾病(chronic obstructive pulmonary disease, COPD)潜在的多效性基因,为深入了解CAD-COPD的共病机制提供新见解。 方法 利用来源于美国退伍军人事务部百万退伍军人计划的CAD和COPD的全基因组关联研究(genome-wide association study, GWAS)汇总数据以及来源于GTEx V8的外周全血数据,采用FUSION进行全转录组关联分析,并利用gPLACO方法分析CAD-COPD潜在的多效性基因。对识别出的多效性基因进行富集分析、蛋白质-蛋白质相互作用网络分析和孟德尔随机化分析,并基于GEO数据库验证多效性基因的差异表达。 结果 经Benjamini-Hochberg校正后,FUSION共识别出794个CAD相关基因及463个COPD相关基因。gPLACO识别出79个CAD-COPD多效性基因,其中,62个多效性基因在CAD和COPD的TWAS结果中同时显著。GO富集分析和转录因子靶基因富集结果揭示了CAD-COPD潜在的生物学通路,包括肉碱跨膜转运活性(P=6.03×10-7)和MEF2C靶基因(P=5.01×10-3)。多效性基因STARD3在蛋白质-蛋白质相互作用网络分析、孟德尔随机化分析以及差异表达基因分析中得到了进一步验证。 结论 STARD3可以作为潜在的CAD-COPD多效性基因;肉碱代谢和内皮功能在CAD-COPD共病中具有重要作用。

关键词: 冠心病, 慢性阻塞性肺疾病, 多效性基因, 跨组学数据整合, 全转录组关联分析

Abstract: Objective To integrate transcriptome-wide association studies(TWAS)with pleiotropy analysis under a composite null hypothesis and to explore potential pleiotropic genes for coronary artery disease(CAD)and chronic obstructive pulmonary disease(COPD)from a transcriptomic perspective, providing new insights into the comorbid mechanisms of CAD and COPD. Methods Genome-wide association study(GWAS)summary data for CAD and COPD were obtained from the Million Veteran Program of The Department of Veterans Affairs, and gene expression reference weights for whole blood were derived from GTEx V8. TWAS was conducted using FUSION, and potential pleiotropic genes for CAD and COPD were analyzed using the gPLACO method developed in this study. Furthermore, enrichment analysis, protein-protein interaction analysis, Mendelian randomization analysis, and differential gene expression analysis were conducted on the CAD-COPD pleiotropic genes. Results After Benjamini-Hochberg correction, FUSION identified a total of 794 genes associated with CAD and 463 genes associated with COPD. gPLACO identified 79 pleiotropic genes shared between CAD and COPD, of which 62 were simultaneously significant in TWAS results for both diseases. GO enrichment analysis and transcription factor target gene enrichment further revealed potential biological pathways underlying CAD-COPD comorbidity, including carnitinetransmembrane transporter activity(P=6.03×10-7)and MEF2C target gene(P=5.01×10-3). Further protein-protein interaction analysis, Mendelian randomization analysis, and differential gene expression analysis also suggested STARD3 as a potential pleiotropic gene for CAD-COPD. Conclusion STARD3 is a potential pleiotropic gene for CAD-COPD, underscoring the critical roles of carnitine metabolism and endothelial function in their shared pathophysiology.

Key words: Coronary artery disease, Chronic obstructive pulmonary disease, Pleiotropic genes, Multi-omics data integration, Transcriptome-wide association study

中图分类号: 

  • R541.4
[1] Daher A, Dreher M. The bidirectional relationship between chronic obstructive pulmonary disease and coronary artery disease [J]. Herz, 2020, 45(2): 110-117.
[2] 刘洪如, 武冬民, 李娜, 等. 慢性阻塞性肺疾病与冠心病共病研究进展 [J]. 实用心脑肺血管病杂志, 2023, 31(4): 126-131. LIU Hongru, WU Dongmin, LI Na, et al. Research progress on comorbidity of chronic obstructive pulmonary di-sease and coronary heart disease[J]. Practical Journal of Cardiac Cerebral Pneumal and Vascular Disease, 2023, 31(4): 126-131.
[3] Zheng Y, Hu Z, Seery S, et al. Global insights into chronic obstructive pulmonary disease and coronary artery disease: a systematic review and meta-analysis of 6,400,000 patients [J]. Rev Cardiovasc Med, 2024, 25(1): 25. doi: 10.31083/j.rcm2501025
[4] Sin DD, Man SF. Chronic obstructive pulmonary disease as a risk factor for cardiovascular morbidity and mortality [J]. Proc Am Thorac Soc, 2005, 2(1): 8-11.
[5] André S, Conde B, Fragoso E, et al. Copd and cardiovascular disease [J]. Pulmonology, 2019, 25(3): 168-176.
[6] Li Y, Zheng H, Yan W, et al. The impact of chronic obstructive pulmonary disease on the prognosis outcomes of patients with percutaneous coronary intervention or coronary artery bypass grafting: a meta-analysis [J]. Heart Lung, 2023, 60: 8-14. doi: 10.1016/j.hrtlng.2023.02.017
[7] Zhu Z, Wang X, Li X, et al. Genetic overlap of chronic obstructive pulmonary disease and cardiovascular disease-related traits: a large-scale genome-wide cross-trait analysis [J]. Respir Res, 2019, 20(1): 64. doi: 10.1186/s12931-019-1036-8
[8] Yang C, Li C, Wang Q, et al. Implications of pleiotropy: challenges and opportunities for mining big data in biomedicine [J]. Front Genet, 2015, 6: 229. doi: 10.3389/fgene.2015.00229
[9] Mai J, Lu M, Gao Q, et al. Transcriptome-wide association studies: recent advances in methods, applications and available databases [J]. Commun Biol, 2023, 6(1): 899. doi: 10.1038/s42003-023-05279-y
[10] 郭萍, 刘璐, 燕冉, 等. 全转录组关联研究的设计、分析与展望 [J]. 中国卫生统计, 2023, 40(1): 144-148. GUO Ping, LIU Lu, YAN Ran, et al. Design, analysis, and future perspectives of transcriptome-wide association studies[J]. Chinese Journal of Health Statistics, 2023, 40(1): 144-148.
[11] Gusev A, Mancuso N, Won H, et al. Transcriptome-wide association study of schizophrenia and chromatin activity yields mechanistic disease insights [J]. Nat Genet, 2018, 50(4): 538-548.
[12] Qiao J, Wang T, Shao Z, et al. Genetic correlation and gene-based pleiotropy analysis for four major neurodegenerative diseases with summary statistics [J]. Neurobiol Aging, 2023, 124: 117-128. doi: 10.1016/j.neurobiolaging.2022.12.012
[13] Verma A, Huffman JE, Rodriguez A, et al. Diversity and scale: genetic architecture of 2068 traits in the VA Million Veteran Program [J]. Science, 2024, 385(6706): eadj1182. doi: 10.1126/science.adj1182
[14] GTEx Consortium. The gtex consortium atlas of genetic regulatory effects across human tissues [J]. Science, 2020, 369(6509): 1318-1330.
[15] Gusev A, Ko A, Shi H, et al. Integrative approaches for large-scale transcriptome-wide association studies [J]. Nat Genet, 2016, 48(3): 245-252.
[16] Ray D, Chatterjee N. A powerful method for pleiotropic analysis under composite null hypothesis identifies novel shared loci between type 2 diabetes and prostate cancer [J]. PLoS Genet, 2020, 16(12): e1009218. doi: 10.1371/journal.pgen.1009218
[17] 吴飞, 李清丽, 肖振卫. 孟德尔随机化探究细胞因子与慢性肾脏病的因果关系 [J]. 山东大学学报(医学版), 2024, 62(11): 85-95. WU Fei, LI Qingli, XIAO Zhenwei. Causal association between cytokines and chronic kidney disease based on Mendelian randomization[J]. Journal of Shandong University(Health Sciences), 2024, 62(11): 85-95.
[18] Võsa U, Claringbould A, Westra HJ, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression [J]. Nat Genet, 2021, 53(9): 1300-1310.
[19] Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data [J]. Genet Epidemiol, 2013, 37(7): 658-665.
[20] Zhou Y, Zhou B, Pache L, et al. Metascape provides a biologist-oriented resource for the analysis of systems-level datasets [J]. Nat Commun, 2019, 10(1): 1523. doi: 10.1038/s41467-019-09234-6
[21] Gong W, Guo P, Liu L, et al. Integrative analysis of transcriptome-wide association study and mrna expression profiles identifies candidate genes associated with idiopathic pulmonary fibrosis [J]. Front Genet, 2020, 11: 604324. doi: 10.3389/fgene.2020.604324
[22] Szklarczyk D, Gable AL, Lyon D, et al. STRING v11: protein-protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets [J]. Nucleic Acids Res, 2019, 47(D1): D607-D613.
[23] Shannon P, Markiel A, Ozier O, et al. Cytoscape: a software environment for integrated models of biomole-cular interaction networks [J]. Genome Res, 2003, 13(11): 2498-2504.
[24] Barrett T, Wilhite SE, Ledoux P, et al. NCBI GEO: archive for functional genomics data sets-update [J]. Nucleic Acids Res, 2013, 41(Database issue): D991-995.
[25] Sakornsakolpat P, Morrow JD, Castaldi PJ, et al. Integrative genomics identifies new genes associated with severe COPD and emphysema [J]. Respir Res, 2018, 19(1): 46. doi: 10.1186/s12931-018-0744-9
[26] Wang Z, Li S, Cai G, et al. Mendelian randomization analysis identifies druggable genes and drugs repurposing for chronic obstructive pulmonary disease [J]. Front Cell Infect Microbiol, 2024, 14: 1386506. doi: 10.3389/fcimb.2024.1386506
[27] Xie L, Li YM. Lipoprotein lipase(LPL)polymorphism and the risk of coronary artery disease: a meta-analysis [J]. Int J Environ Res Public Health, 2017, 14(1): 84. doi: 10.3390/ijerph14010084
[28] Wilhelm LP, Wendling C, Védie B, et al. STARD3 mediates endoplasmic reticulum-to-endosome cholesterol transport at membrane contact sites [J]. Embo j, 2017, 36(10): 1412-1433.
[29] Li L, Liu Y, Liu X, et al. Regulatory roles of external cholesterol in human airway epithelial mitochondrial function through STARD3 signalling [J]. Clin Transl Med, 2022, 12(6): e902. doi: 10.1002/ctm2.902
[30] Borthwick F, Allen AM, Taylor JM, et al. Overexpression of STARD3 in human monocyte/macrophages induces an anti-atherogenic lipid phenotype [J]. Clin Sci(Lond), 2010, 119(7): 265-272.
[31] Sayols-Baixeras S, Lluís-Ganella C, Lucas G, et al. Pathogenesis of coronary artery disease: focus on genetic risk factors and identification of genetic variants [J]. Appl Clin Genet, 2014, 7: 15-32. doi: 10.2147/tacg.S35301
[32] Chen R, Michaeloudes C, Liang Y, et al. ORMDL3 regulates cigarette smoke-induced endoplasmic reticulum stress in airway smooth muscle cells [J]. J Allergy Clin Immunol, 2022, 149(4): 1445-1457.
[33] Moll M, Jackson VE, Yu B, et al. A systematic analysis of protein-altering exonic variants in chronic obstructive pulmonary disease [J]. Am J Physiol Lung Cell Mol Physiol, 2021, 321(1): L130-L143.
[34] Van Den Boomen DJH, Sienkiewicz A, Berlin I, et al. A trimeric Rab7 GEF controls NPC1-dependent lysosomal cholesterol export [J]. Nat Commun, 2020, 11(1): 5559. doi: 10.1038/s41467-020-19032-0
[35] Fredrick F, Aggarwal K, Reddy Meda AK, et al. Carnitine: its crucial role in metabolic health and cardiovascular function [J]. J Diet Suppl, 2025, 22(5): 664-679.
[36] Lee BJ, Lin JS, Lin YC, et al. Effects of L-carnitine supplementation on oxidative stress and antioxidant enzymes activities in patients with coronary artery disease: a randomized, placebo-controlled trial [J]. Nutr J, 2014, 13: 79. doi: 10.1186/1475-2891-13-79
[37] Lee BJ, Lin JS, Lin YC, et al. Antiinflammatory effects of L-carnitine supplementation(1000 mg/d)in coronary artery disease patients [J]. Nutrition, 2015, 31(3): 475-479. doi: 10.1016/j.nut.2014.10.001
[38] Borghi-Silva A, Baldissera V, Sampaio LM, et al. L-carnitine as an ergogenic aid for patients with chronic obstructive pulmonary disease submitted to whole-body and respiratory muscle training programs [J]. Braz J Med Biol Res, 2006, 39(4): 465-474.
[39] Conlon TM, Bartel J, Ballweg K, et al. Metabolomics screening identifies reduced L-carnitine to be associated with progressive emphysema [J]. Clin Sci(Lond), 2016, 130(4): 273-287.
[40] Theodorakopoulou MP, Alexandrou ME, Bakaloudi DR, et al. Endothelial dysfunction in COPD: a systematic review and meta-analysis of studies using different functional assessment methods [J]. ERJ Open Res, 2021, 7(2): 00983-2020.
[41] Xu Z, Yoshida T, Wu L, et al. Transcription factor MEF2C suppresses endothelial cell inflammation via regulation of NF-κB and KLF2 [J]. J Cell Physiol, 2015, 230(6): 1310-1320.
[42] Lu YW, Martino N, Gerlach BD, et al. MEF2(myocyte enhancer factor 2)is essential for endothelial homeostasis and the atheroprotective gene expression program [J]. Arterioscler Thromb Vasc Biol, 2021, 41(3): 1105-1123.
[43] Polverino F, Celli BR, Owen CA. COPD as an endothelial disorder: endothelial injury linking lesions in the lungs and other organs?(2017 grover conference series)[J]. Pulm Circ, 2018, 8(1): 2045894018758528. doi: 10.1177/2045894018758528
[44] Ambrosino P, Lupoli R, Iervolino S, et al. Clinical assessment of endothelial function in patients with chronic obstructive pulmonary disease: a systematic review with meta-analysis [J]. Intern Emerg Med, 2017, 12(6): 877-885.
[45] Vaes AW, Spruit MA, Theunis J, et al. Endothelial function in patients with chronic obstructive pulmonary disease: a systematic review of studies using flow mediated dilatation [J]. Expert Rev Respir Med, 2017, 11(12): 1021-1031.
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