利用血浆蛋白质组预测心力衰竭亚组患者的死亡率
Harnessing the Plasma Proteome to Predict Mortality in Heart Failure Subpopulations.
作者信息
Chadwick Jessica, Hinterberg Michael A, Asselbergs Folkert W, Biegel Hannah, Boersma Eric, Cappola Thomas P, Chirinos Julio A, Coresh Joseph, Ganz Peter, Gordon David A, Kureshi Natasha, Loupey Kelsey M, Orlenko Alena, Ostroff Rachel, Sampson Laura, Shrestha Sama, Sweitzer Nancy K, Williams Stephen A, Zhao Lei, Kardys Isabella, Lanfear David E
机构信息
Departments of Clinical Research and Development (J. Chadwick, R.O., K.M.L., S.A.W.), SomaLogic Operating Co Inc, Boulder, CO.
Bioinformatics (M.A.H., H.B., N.K., L.S., S.S.), SomaLogic Operating Co Inc, Boulder, CO.
出版信息
Circ Heart Fail. 2025 Apr;18(4):e011208. doi: 10.1161/CIRCHEARTFAILURE.123.011208. Epub 2025 Mar 7.
BACKGROUND
We derived and validated proteomic risk scores (PRSs) for heart failure (HF) prognosis that provide absolute risk estimates for all-cause mortality within 1 year.
METHODS
Plasma samples from individuals with HF with reduced ejection fraction (HFrEF; ejection fraction <40%; training/validation n=1247/762) and preserved ejection fraction (HFpEF; ejection fraction ≥50%; training/validation n=725/785) from 3 independent studies were run on the SomaScan Assay measuring ≈5000 proteins. Machine learning techniques resulted in unique 17- and 14-protein models for HFrEF and HFpEF that predict 1-year mortality. Discrimination was assessed via C-index and 1-year area under the curve (AUC), and survival curves were visualized. PRSs were also compared with Meta-Analysis Global Group in Chronic HF (MAGGIC) score and NT-proBNP (N-terminal pro-B-type natriuretic peptide) measurements and further assessed for sensitivity to disease progression in longitudinal samples (HFrEF: n=396; 1107 samples; HFpEF: n=175; 350 samples).
RESULTS
In validation, the HFpEF PRS performed significantly better (≤0.1) for mortality prediction (C-index, 0.79; AUC, 0.82) than MAGGIC (C-index, 0.71; AUC, 0.74) and NT-proBNP (PRS C-index, 0.76 and AUC, 0.81 versus NT-proBNP C-index, 0.72 and AUC, 0.76). The HFrEF PRS performed comparably to MAGGIC (PRS C-index, 0.76 and AUC, 0.83 versus MAGGIC C-index, 0.75 and AUC, 0.84) but had a significantly better C-Index (=0.026) than NT-proBNP (PRS C-index, 0.75 and AUC, 0.78 versus NT-proBNP C-index, 0.73 and AUC, 0.77). PRS included known HF pathophysiology biomarkers (93%) and novel proteins (7%). Longitudinal assessment revealed that HFrEF and HFpEF PRSs were higher and increased more over time in individuals who experienced a fatal event during follow-up.
CONCLUSIONS
PRSs can provide valid, accurate, and dynamic prognostic estimates for patients with HF. This approach has the potential to improve longitudinal monitoring of patients and facilitate personalized care.
背景
我们推导并验证了用于心力衰竭（HF）预后的蛋白质组学风险评分（PRSs），该评分可提供1年内全因死亡率的绝对风险估计。
方法
来自3项独立研究的射血分数降低的心力衰竭（HFrEF；射血分数<40%；训练/验证n = 1247/762）和射血分数保留的心力衰竭（HFpEF；射血分数≥50%；训练/验证n = 725/785）患者的血浆样本，通过SomaScan检测法检测约5000种蛋白质。机器学习技术得出了用于HFrEF和HFpEF的独特的17蛋白和14蛋白模型，可预测1年死亡率。通过C指数和1年曲线下面积（AUC）评估辨别力，并绘制生存曲线。还将PRSs与慢性心力衰竭Meta分析全球组（MAGGIC）评分和N末端B型利钠肽原（NT-proBNP）测量值进行比较，并进一步评估其对纵向样本中疾病进展的敏感性（HFrEF：n = 396；1107个样本；HFpEF：n = 175；350个样本）。
结果
在验证中，HFpEF的PRS在死亡率预测方面（C指数为0.79；AUC为0.82）比MAGGIC（C指数为0.71；AUC为0.74）和NT-proBNP（PRS的C指数为0.76，AUC为0.81，而NT-proBNP的C指数为0.72，AUC为0.76）表现显著更好（≤0.1）。HFrEF的PRS表现与MAGGIC相当（PRS的C指数为0.76，AUC为0.83，而MAGGIC的C指数为0.75，AUC为0.84），但C指数比NT-proBNP显著更好（=0.026）（PRS的C指数为0.75，AUC为0.78，而NT-proBNP的C指数为0.73，AUC为0.77）。PRS包括已知的HF病理生理学生物标志物（93%）和新蛋白（7%）。纵向评估显示，在随访期间发生致命事件的个体中，HFrEF和HFpEF的PRS更高且随时间增加更多。
结论
PRSs可为HF患者提供有效、准确和动态的预后估计。这种方法有可能改善对患者的纵向监测并促进个性化护理。
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