Proteomic Response Predictor (PRP) For Beta Blocker Survival Benefit In Heart Failure Patients With Reduced Ejection Fraction

Document Type

Conference Proceeding

Publication Date

1-1-2025

Publication Title

J Card Fail

Abstract

Background: To improve prediction of individual responses to beta-blocker (BB) therapy in Heart failure with reduced ejection fraction (HFrEF) patients, various novel approaches such as proteomics are being used. Aim: Our goal was to derive and validate a proteomic response predictor (PRP) for BB survival benefit in HFrEF patients. Methods: A total of 930 patients with Heart Failure (HF) and low ejection fraction (EF<50%) from the Heart Failure Pharmacogenomic Registry (HFPGR) were studied. Plasma was profiled using SOMAscan v4 (approximately 5k proteins). The cohort was randomly divided into a derivation subset of 623 patients and a validation set in the remaining n=307. The component proteins of PRP were selected using Lasso-penalized Cox regression of all-cause mortality focusing on protein-by-BB interaction, and adjusted for MAGGIC score, BB propensity score, and race. The PRP score was generated using the coefficients from the Cox model results. The PRP was then tested in the validation group as both a continuous variable and a dichotomized variable. Results: Ten proteins (Table 1) were selected for the optimal PRP in the derivation subset. In validation testing, the interaction of BB with PRP on mortality was significant (P=0.000635). To dichotomize the PRP, various cutoffs were compared across deciles within the derivation group. When PRP is dichotomized at the median, the HR associated with BB treatment in the in favorable response PRP group was 0.41 while in the PRP non-responder group and was 1.78 (95%CI = 1.08-2.93) which was statistically significant (Pinteraction=0.016). Conclusions: Using proteomic profiling of plasma, a 10 protein predictor of BB response in HFrEF was created and validated.

Volume

31

Issue

1

First Page

265

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