Pandhi Paloma, Ter Maaten Jozine M, Anker Stefan D, Ng Leong L, Metra Marco, Samani Nilesh J, Lang Chim C, Dickstein Kenneth, de Boer Rudolf A, van Veldhuisen Dirk J, Voors Adriaan A, Sama Iziah E
Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands.
Department of Cardiology, Charité Universitätsmedizin, Berlin, Germany; Berlin-Brandenburg Center for Regenerative Therapies, German Centre for Cardiovascular Research, Charité Universitätsmedizin, Berlin, Germany.
JACC Heart Fail. 2022 Sep;10(9):623-632. doi: 10.1016/j.jchf.2022.05.013.
Congestion is the main driver behind symptoms of heart failure (HF), but pathophysiology related to congestion remains poorly understood.
Using pathway and differential expression analyses, the authors aim to identify biological processes and biomarkers associated with congestion in HF.
A congestion score (sum of jugular venous pressure, orthopnea, and peripheral edema) was calculated in 1,245 BIOSTAT-CHF patients with acute or worsening HF. Patients with a score ranking in the bottom or top categories of congestion were deemed noncongested (n = 408) and severely congested (n = 142), respectively. Plasma concentrations of 363 unique proteins (Olink Proteomics Multiplex CVD-II, CVD-III, Immune Response and Oncology II panels) were compared between noncongested and severely congested patients. Results were validated in an independent validation cohort of 1,342 HF patients (436 noncongested and 232 severely congested).
Differential protein expression analysis showed 107/363 up-regulated and 6/363 down-regulated proteins in patients with congestion compared with those without. FGF-23, FGF-21, CA-125, soluble ST2, GDF-15, FABP4, IL-6, and BNP were the strongest up-regulated proteins (fold change [FC] >1.30, false discovery rate [FDR], P < 0.05). KITLG, EGF, and PON3 were the strongest down-regulated proteins (FC <-1.30, FDR P < 0.05). Pathways most prominently involved in congestion were related to inflammation, endothelial activation, and response to mechanical stimulus. The validation cohort yielded similar findings.
Severe congestion in HF is mainly associated with inflammation, endothelial activation, and mechanical stress. Whether these pathways play a causal role in the onset or progression of congestion remains to be established. The identified biomarkers may become useful for diagnosing and monitoring congestion status.
充血是心力衰竭(HF)症状的主要驱动因素,但与充血相关的病理生理学仍知之甚少。
通过通路和差异表达分析,作者旨在识别与HF充血相关的生物学过程和生物标志物。
对1245例急性或病情恶化的BIOSTAT-CHF患者计算充血评分(颈静脉压、端坐呼吸和外周水肿的总和)。充血评分处于最低或最高类别的患者分别被视为非充血(n = 408)和严重充血(n = 142)。比较非充血和严重充血患者之间363种独特蛋白质(Olink蛋白质组学多重心血管疾病-II、心血管疾病-III、免疫反应和肿瘤学-II检测板)的血浆浓度。结果在1342例HF患者(436例非充血和232例严重充血)的独立验证队列中得到验证。
差异蛋白质表达分析显示,与无充血患者相比,充血患者中有107/363种蛋白质上调,6/363种蛋白质下调。FGF-23、FGF-21、CA-125、可溶性ST2、GDF-15、FABP4、IL-6和BNP是上调最强的蛋白质(倍数变化[FC]>1.30,错误发现率[FDR],P<0.05)。KITLG、EGF和PON3是下调最强的蛋白质(FC<-1.30,FDR P<0.05)。最显著参与充血的通路与炎症、内皮激活和对机械刺激的反应有关。验证队列得出了类似的结果。
HF中的严重充血主要与炎症、内皮激活和机械应激有关。这些通路是否在充血的发生或进展中起因果作用仍有待确定。所识别的生物标志物可能有助于诊断和监测充血状态。