Background Atrial fibrillation (AF) and concomitant cardiometabolic disease processes interact and combine to lead to adverse events such as stroke, heart failure, myocardial infarction, and cardiovascular death. Circulating biomolecules provide quantifiable proxies for cardiometabolic disease processes. Their role in defining subphenotypes of AF is not known. Methods and results This prespecified analysis of the EAST-AFNET4 biomolecule study assigned patients to clusters using polytomous variable latent class analysis (poLCA) based on baseline concentrations of thirteen precisely-quantified biomolecules potentially reflecting ageing, cardiac fibrosis, metabolic dysfunction, oxidative stress, cardiac load, endothelial dysfunction, and inflammation. In each cluster, rates of cardiovascular death, stroke, or hospitalization for heart failure or acute coronary syndrome, the primary outcome of EAST-AFNET 4, were calculated and compared between clusters over median 5.1 years follow-up. Findings were independently validated in a prospective cohort of 748 patients with AF (BBC-AF; median follow up 2.9 years). Unsupervised biomolecule analysis assigned 1586 patients (71 years old, 46% women) into four clusters. The highest-risk cluster was dominated by elevated BMP10, IGFBP7, NT-proBNP, ANGPT2 and GDF15. Patients in the lowest-risk cluster showed low concentrations of these biomolecules. Two intermediate-risk clusters differed by high or low concentrations of hsCRP, IL-6, and D-dimer. Patients in the highest-risk cluster had a 5-fold higher cardiovascular event rate than patients in the low-risk cluster. Early rhythm control was effective across clusters (pinteraction = 0.63). Sensitivity analyses and external validation in BBC-AF replicated clusters and risk gradients. Conclusions Biomolecule concentrations identify cardiometabolic subphenotypes in patients with atrial fibrillation at high and low cardiovascular risk.

中文翻译：

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心房颤动中基于血液的心脏代谢表型及其相关风险：EAST-AFNET 4 生物分子研究

背景 心房颤动 (AF) 和伴随的心脏代谢疾病过程相互作用并结合在一起，导致中风、心力衰竭、心肌梗死和心血管死亡等不良事件。循环生物分子为心脏代谢疾病过程提供了可量化的指标。它们在定义 AF 亚表型中的作用尚不清楚。方法和结果 EAST-AFNET4 生物分子研究的这项预先指定的分析，根据 13 种精确量化的生物分子的基线浓度，使用多级变量潜在类别分析 (poLCA) 将患者分配到不同的簇，这些生物分子可能反映衰老、心脏纤维化、代谢功能障碍、氧化应激、心脏功能障碍。负荷、内皮功能障碍和炎症。在每个组中，计算了心血管死亡、中风或因心力衰竭或急性冠脉综合征住院的发生率（EAST-AFNET 4 的主要结局），并在中位随访 5.1 年的时间里进行比较。研究结果在 748 名 AF 患者的前瞻性队列中得到独立验证（BBC-AF；中位随访 2.9 年）。无监督的生物分子分析将 1586 名患者（71 岁，46% 女性）分为四组。风险最高的簇主要是 BMP10、IGFBP7、NT-proBNP、ANGPT2 和 GDF15 升高。风险最低人群中的患者显示出这些生物分子的浓度较低。两个中等风险群的不同之处在于 hsCRP、IL-6 和 D-二聚体浓度的高低。最高风险组患者的心血管事件发生率是低风险组患者的 5 倍。早期节律控制在整个集群中都是有效的（pinteraction = 0.63）。 BBC-AF 复制集群和风险梯度的敏感性分析和外部验证。结论 生物分子浓度可识别高心血管风险和低心血管风险的房颤患者的心脏代谢亚表型。