Ruvuna Lisa, Hijazi Kahkeshan, Guzman Daniel E, Guo Claire, Loureiro Joseph, Khokhlovich Edward, Morris Melody, Obeidat Ma'en, Pratte Katherine A, DiLillo Katarina M, Sharma Sunita, Kechris Katerina, Anzueto Antonio, Barjaktarevic Igor, Bleecker Eugene R, Casaburi Richard, Comellas Alejandro, Cooper Christopher B, DeMeo Dawn L, Foreman Marilyn, Flenaugh Eric L, Han MeiLan K, Hanania Nicola A, Hersh Craig P, Krishnan Jerry A, Labaki Wassim W, Martinez Fernando J, O'Neal Wanda K, Paine Robert, Peters Stephen P, Woodruff Prescott G, Wells J Michael, Wendt Christine H, Arnold Kelly B, Barr R Graham, Curtis Jeffrey L, Ngo Debby, Bowler Russell P
Pulmonary Sciences and Critical Care Medicine University of Colorado Denver, Colorado.
Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, United States.
medRxiv. 2024 Aug 8:2024.08.07.24311507. doi: 10.1101/2024.08.07.24311507.
Identification and validation of circulating biomarkers for lung function decline in COPD remains an unmet need.
Identify prognostic and dynamic plasma protein biomarkers of COPD progression.
We measured plasma proteins using SomaScan from two COPD-enriched cohorts, the Subpopulations and Intermediate Outcomes Measures in COPD Study (SPIROMICS) and Genetic Epidemiology of COPD (COPDGene), and one population-based cohort, Multi-Ethnic Study of Atherosclerosis (MESA) Lung. Using SPIROMICS as a discovery cohort, linear mixed models identified baseline proteins that predicted future change in FEV (prognostic model) and proteins whose expression changed with change in lung function (dynamic model). Findings were replicated in COPDGene and MESA-Lung. Using the COPD-enriched cohorts, Gene Set Enrichment Analysis (GSEA) identified proteins shared between COPDGene and SPIROMICS. Metascape identified significant associated pathways.
The prognostic model found 7 significant proteins in common (p < 0.05) among all 3 cohorts. After applying false discovery rate (adjusted p < 0.2), leptin remained significant in all three cohorts and growth hormone receptor remained significant in the two COPD cohorts. Elevated baseline levels of leptin and growth hormone receptor were associated with slower rate of decline in FEV. Twelve proteins were nominally but not FDR significant in the dynamic model and all were distinct from the prognostic model. Metascape identified several immune related pathways unique to prognostic and dynamic proteins.
We identified leptin as the most reproducible COPD progression biomarker. The difference between prognostic and dynamic proteins suggests disease activity signatures may be different from prognosis signatures.
鉴定和验证慢性阻塞性肺疾病（COPD）肺功能下降的循环生物标志物仍然是一项未满足的需求。
确定COPD进展的预后和动态血浆蛋白生物标志物。
我们使用SomaScan检测了来自两个富含COPD的队列（COPD研究中的亚组和中间结局测量研究[SPIROMICS]以及COPD基因流行病学研究[COPDGene]）和一个基于人群的队列（动脉粥样硬化多族裔研究[MESA]肺部研究）的血浆蛋白。以SPIROMICS作为发现队列，线性混合模型确定了预测未来第一秒用力呼气容积（FEV）变化的基线蛋白（预后模型）以及其表达随肺功能变化而改变的蛋白（动态模型）。研究结果在COPDGene和MESA肺部研究中得到重复验证。利用富含COPD的队列，基因集富集分析（GSEA）确定了COPDGene和SPIROMICS之间共有的蛋白。Metascape确定了显著相关的通路。
预后模型在所有3个队列中发现了7种共同的显著蛋白（p<0.05）。应用错误发现率（校正p<0.2）后，瘦素在所有3个队列中仍然显著，生长激素受体在两个COPD队列中仍然显著。瘦素和生长激素受体的基线水平升高与FEV下降速度较慢相关。在动态模型中有12种蛋白名义上显著但经错误发现率校正后不显著，且所有这些蛋白都与预后模型不同。Metascape确定了预后蛋白和动态蛋白特有的几个免疫相关通路。
我们确定瘦素是最具可重复性的COPD进展生物标志物。预后蛋白和动态蛋白之间的差异表明疾病活动特征可能与预后特征不同。
