Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands; Department of Biostatistics, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands.
Department of Cardiology, Erasmus MC, University Medical Center Rotterdam, Doctor Molewaterplein 40, Rotterdam, the Netherlands.
EBioMedicine. 2023 Jul;93:104655. doi: 10.1016/j.ebiom.2023.104655. Epub 2023 Jun 14.
HFrEF is a heterogenous condition with high mortality. We used serial assessments of 4210 circulating proteins to identify distinct novel protein-based HFrEF subphenotypes and to investigate underlying dynamic biological mechanisms. Herewith we aimed to gain pathophysiological insights and fuel opportunities for personalised treatment.
In 382 patients, we performed trimonthly blood sampling during a median follow-up of 2.1 [IQR:1.1-2.6] years. We selected all baseline samples and two samples closest to the primary endpoint (PEP; composite of cardiovascular mortality, HF hospitalization, LVAD implantation, and heart transplantation) or censoring, and applied an aptamer-based multiplex proteomic approach. Using unsupervised machine learning methods, we derived clusters from 4210 repeatedly measured proteomic biomarkers. Sets of proteins that drove cluster allocation were analysed via an enrichment analysis. Differences in clinical characteristics and PEP occurrence were evaluated.
We identified four subphenotypes with different protein profiles, prognosis and clinical characteristics, including age (median [IQR] for subphenotypes 1-4, respectively:70 [64, 76], 68 [60, 79], 57 [47, 65], 59 [56, 66]years), EF (30 [26, 36], 26 [20, 38], 26 [22, 32], 33 [28, 37]%), and chronic renal failure (45%, 65%, 36%, 37%). Subphenotype allocation was driven by subsets of proteins associated with various biological functions, such as oxidative stress, inflammation and extracellular matrix organisation. Clinical characteristics of the subphenotypes were aligned with these associations. Subphenotypes 2 and 3 had the worst prognosis compared to subphenotype 1 (adjHR (95%CI):3.43 (1.76-6.69), and 2.88 (1.37-6.03), respectively).
Four circulating-protein based subphenotypes are present in HFrEF, which are driven by varying combinations of protein subsets, and have different clinical characteristics and prognosis.
ClinicalTrials.gov Identifier: NCT01851538https://clinicaltrials.gov/ct2/show/NCT01851538.
EU/EFPIA IMI2JU BigData@Heart grant n°116074, Jaap Schouten Foundation and Noordwest Academie.
射血分数降低的心力衰竭（HFrEF）是一种死亡率较高的异质性疾病。我们使用 4210 种循环蛋白的连续评估来确定新的基于蛋白的 HFrEF 亚表型，并研究潜在的动态生物学机制。本研究旨在深入了解病理生理学，并为个性化治疗提供机会。
在 382 例患者中，我们在中位随访 2.1 [IQR：1.1-2.6] 年期间每三个月采集一次血样。我们选择所有基线样本和两个最接近主要终点（PEP；心血管死亡率、HF 住院、LVAD 植入和心脏移植的复合终点）或删失的样本，并应用基于适配体的多重蛋白质组学方法。使用无监督机器学习方法，我们从 4210 个重复测量的蛋白质生物标志物中得出聚类。通过富集分析分析驱动聚类分配的蛋白质集。评估临床特征和 PEP 发生的差异。
我们发现了四个具有不同蛋白谱、预后和临床特征的亚表型，包括年龄（亚表型 1-4 的中位数[IQR]分别为：70 [64，76]、68 [60，79]、57 [47，65]、59 [56，66]岁）、EF（30 [26，36]、26 [20，38]、26 [22，32]、33 [28，37]%）和慢性肾功能衰竭（45%、65%、36%、37%）。亚表型分配由与各种生物学功能相关的蛋白亚集驱动，如氧化应激、炎症和细胞外基质组织。亚表型的临床特征与这些关联一致。与亚表型 1 相比，亚表型 2 和 3 的预后最差（调整后的 HR（95%CI）：3.43（1.76-6.69）和 2.88（1.37-6.03））。
在 HFrEF 中存在四种基于循环蛋白的亚表型，这些亚表型由不同组合的蛋白亚集驱动，具有不同的临床特征和预后。
ClinicalTrials.gov 标识符：NCT01851538 https://clinicaltrials.gov/ct2/show/NCT01851538。
欧盟/EFPIA IMI2JU BigData@Heart 资助计划 n°116074、Jaap Schouten 基金会和 Noordwest Academie。
