Meta-Analysis and DIA-MS-Based Proteomic Investigation of COPD Patients and Asymptomatic Smokers in the Indian Population

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-22 DOI:10.1021/acs.jproteome.4c0046310.1021/acs.jproteome.4c00463
Gautam Sharma, Debarghya Pratim Gupta, Koustav Ganguly, Mahesh Padukudru Anand and Sanjeeva Srivastava*, 
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Abstract

Chronic obstructive pulmonary disease (COPD) is India’s second largest cause of death and is largely caused by smoking. Asymptomatic smokers develop COPD due to genetic, environmental, and molecular variables, making early screening crucial. Data-independent acquisition mass spectrometry (DIA-MS) based-proteomics offers an unbiased method to analyze proteomic profiles. This study is the first to use DIA-based proteomics to analyze individual serum samples from three distinct male cohorts: healthy individuals (n = 10), asymptomatic smokers (n = 10), and COPD patients (n = 10). This comprehensive approach identified 667 proteins with a 1% false discovery rate. Differentially expressed proteins included 40 in the normal versus asymptomatic comparison, 88 in the COPD versus normal comparison, and 40 in the COPD versus asymptomatic comparison. Among them, protein-associated genes such as PRDX6, ELANE, PRKCSH, PRTN3, and MNDA could help differentiate COPD from asymptomatic smokers, while ELANE, H3-3A, IGHE, SLC4A1, and SERPINA11 could differentiate COPD from healthy subjects. Pathway enrichment and protein–protein interaction analyses revealed significant alterations in hemostasis, immune system functions, fibrin clot formation, and post-translational protein modifications. Key proteins were validated using a parallel reaction monitoring assay. DIA data are available via ProteomeXchange with identifier PXD055242. Our findings reveal key protein classifiers in COPD patients, asymptomatic smokers, and healthy individuals, helping clinicians understand disease pathobiology and improve disease management and quality of life.

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印度人群中慢性阻塞性肺病患者和无症状吸烟者的元分析和基于 DIA-MS 的蛋白质组学研究
慢性阻塞性肺病(COPD)是印度第二大死因,主要由吸烟引起。由于遗传、环境和分子变量的影响,无症状的吸烟者会患上慢性阻塞性肺病,因此早期筛查至关重要。基于数据独立采集质谱(DIA-MS)的蛋白质组学提供了一种分析蛋白质组概况的无偏方法。本研究首次使用基于 DIA 的蛋白质组学方法分析了三个不同男性群体的个人血清样本:健康人(n = 10)、无症状吸烟者(n = 10)和慢性阻塞性肺病患者(n = 10)。这种综合方法鉴定出 667 种蛋白质,错误发现率为 1%。差异表达的蛋白质包括正常与无症状对比中的 40 个、慢性阻塞性肺病与正常对比中的 88 个以及慢性阻塞性肺病与无症状对比中的 40 个。其中,PRDX6、ELANE、PRKCSH、PRTN3和MNDA等蛋白相关基因有助于区分慢性阻塞性肺病和无症状吸烟者,而ELANE、H3-3A、IGHE、SLC4A1和SERPINA11则可以区分慢性阻塞性肺病和健康人。通路富集和蛋白质相互作用分析表明,止血、免疫系统功能、纤维蛋白凝块形成和蛋白质翻译后修饰发生了显著变化。利用平行反应监测测定法对关键蛋白质进行了验证。DIA数据可通过蛋白质组交换(ProteomeXchange)获得,标识符为PXD055242。我们的研究结果揭示了慢性阻塞性肺病患者、无症状吸烟者和健康人体内的关键蛋白质分类器,有助于临床医生了解疾病病理生物学,改善疾病管理和生活质量。
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4.30%
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567
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