Proteomic biomarkers of long-term lung function decline in textile workers: a 35-year longitudinal study.

IF 4.1 3区 医学 Q2 ENVIRONMENTAL SCIENCES Journal of Exposure Science and Environmental Epidemiology Pub Date : 2024-10-02 DOI:10.1038/s41370-024-00721-7
Mengsheng Zhao, Liangmin Wei, Longyao Zhang, Jingqing Hang, Fengying Zhang, Li Su, Hantao Wang, Ruyang Zhang, Feng Chen, David C Christiani, Yongyue Wei
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Abstract

Background: Occupational exposures contribute significantly to obstructive lung disease among textile workers. However, biomarkers associated with such declines are not available.

Objectives: We conducted a large-scale proteomic study to explore protein biomarkers potentially associated with long-term lung function decline.

Methods: Shanghai Textile Workers Cohort was established in 1981 with 35 years of follow-up, assessing textile workers' lung functions every five years. Quantitative serum proteomics was performed on all 453 workers at 2016 survey. We employed four distinct models to examine the association between forced expiratory volume in one second (FEV1) and proteins, and consolidated the findings using an aggregated Cauchy association test. Furthermore, proteomic data of UK Biobank (UKB) was used to explore the associations of potential protein markers and decline of FEV1, and the interactions of these proteins were examined through STRING database. Associations were also externally validated using two-sample Mendelian randomizations (MR).

Results: 15 of 907 analyzed proteins displayed potential associations with long-term FEV1 decline, including two hemoglobin subunits: hemoglobin subunit beta (HBB, FDR-qACAT = 0.040), alpha globin chain (HBA2, FDR-qACAT = 0.045), and four immunoglobulin subunits: immunoglobulin kappa variable 3-7 (IGKV3-7, FDR-qACAT = 0.003), immunoglobulin heavy chain variable region (IgH, FDR-qACAT = 0.011). Five proteins were significantly associated with the rate of decline of FEV1 in UKB, in which RAB6A, LRRN1, and BSG were also found to be associated with proteins identified in Shanghai Textile Workers Cohort using STRING database. MR indicated bidirectional associations between HBB and FEV1 (P < 0.05), while different immunoglobulin subunits exhibited varying associations with FEV1.

Impact statement: We performed a large-scale proteomic study of the longest-follow-up pulmonary function cohort of textile workers to date. We discovered multiple novel proteins associated with long-term decline of FEV1 that have potential for identifying new biomarkers associated with long-term lung function decline among occupational populations, and may identify individuals at risk, as well as potential pharmaceutical targets for early intervention.

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纺织工人长期肺功能下降的蛋白质组生物标志物:一项为期 35 年的纵向研究。
背景:职业暴露是纺织工人患阻塞性肺病的重要原因。然而,与这种肺功能下降相关的生物标志物尚不存在:我们进行了一项大规模的蛋白质组学研究,以探索与长期肺功能下降可能相关的蛋白质生物标志物:方法:1981 年建立了上海纺织工人队列,每五年对纺织工人的肺功能进行一次评估,随访 35 年。在 2016 年的调查中,对所有 453 名工人进行了血清定量蛋白质组学研究。我们采用了四种不同的模型来研究一秒钟用力呼气容积(FEV1)与蛋白质之间的关联,并使用聚合考奇关联检验对研究结果进行了整合。此外,研究人员还利用英国生物库(UKB)的蛋白质组数据探讨了潜在蛋白质标记物与 FEV1 下降之间的关联,并通过 STRING 数据库检验了这些蛋白质之间的相互作用。研究还使用双样本孟德尔随机化方法(MR)对相关性进行了外部验证:结果:907 个分析蛋白质中有 15 个显示与长期 FEV1 下降有潜在关联,包括两个血红蛋白亚基:血红蛋白亚基 beta(HBB,FDR-qACAT = 0.040)、α 球蛋白链(HBA2,FDR-qACAT = 0.045),以及四种免疫球蛋白亚基:免疫球蛋白卡帕可变区 3-7 (IGKV3-7,FDR-qACAT = 0.003)、免疫球蛋白重链可变区(IgH,FDR-qACAT = 0.011)。有五种蛋白质与 UKB 的 FEV1 下降率明显相关,其中 RAB6A、LRRN1 和 BSG 还与利用 STRING 数据库在上海纺织工人队列中发现的蛋白质相关。MR表明HBB与FEV1之间存在双向关联(P 1.Impact):我们对迄今为止随访时间最长的纺织工人肺功能队列进行了大规模蛋白质组学研究。我们发现了与 FEV1 长期下降相关的多种新型蛋白质,这些蛋白质有可能确定与职业人群长期肺功能下降相关的新生物标志物,并有可能确定高危人群以及早期干预的潜在药物目标。
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来源期刊
CiteScore
8.90
自引率
6.70%
发文量
93
审稿时长
3 months
期刊介绍: Journal of Exposure Science and Environmental Epidemiology (JESEE) aims to be the premier and authoritative source of information on advances in exposure science for professionals in a wide range of environmental and public health disciplines. JESEE publishes original peer-reviewed research presenting significant advances in exposure science and exposure analysis, including development and application of the latest technologies for measuring exposures, and innovative computational approaches for translating novel data streams to characterize and predict exposures. The types of papers published in the research section of JESEE are original research articles, translation studies, and correspondence. Reported results should further understanding of the relationship between environmental exposure and human health, describe evaluated novel exposure science tools, or demonstrate potential of exposure science to enable decisions and actions that promote and protect human health.
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