Prediction of cardiac death in patients with hypertrophic cardiomyopathy using RNA-sequencing of plasma small non-coding RNAS
Authors: Akita K , Hasegawa K , Maurer M S , Tower-Rader A , Fifer M A , Topkara V K , Reilly M P , Shimada Y J 
Published: November 2023

Abstract

Background
Hypertrophic cardiomyopathy (HCM) causes cardiac death through both sudden cardiac death (SCD) and heart failure (HF). Accuracy of the current prediction models for SCD remains suboptimal. No clinical model is available to predict HF death in HCM. Furthermore, the underlying molecular mechanisms underpinning cardiac death in HCM remain uncertain. Plasma RNA-sequencing (RNA-Seq) determines concentrations of thousands of small non-coding RNAs (sncRNAs) and has the potential to predict cardiac death in HCM.

Purpose
To develop plasma sncRNA-Seq-based model to predict cardiac death in patients with HCM and to determine signaling pathways dysregulated in those who subsequently experience cardiac death.

Methods
In this prospective, multi-center cohort study, we conducted RNA-Seq of 3740 plasma sncRNAs on 390 patients with HCM at enrollment. The outcome was cardiac death defined as a composite of heart transplant, death due to HF, SCD with or without successful resuscitation, and appropriate discharge of implanted cardioverter defibrillator (ICD). We developed a sncRNA-Seq-based prediction model with linear discriminant analysis to predict cardiac death using data from one institution (training set, n=271). We tested the predictive ability of the model in samples from the other institutions (test set, n=119). To examine the ability of the model to identify patients at high risk of cardiac death, we classified patients in the test set to high- and low-risk groups using the prediction model derived from the training set. We performed time-to-event analysis between the two groups in the test set using the log-rank test. We also performed pathway analysis of microRNAs significantly (i.e., nominal P&lt;0.05) associated with cardiac death.

Results
During a median follow-up of 2.7 [interquartile 1.8–5.1] years, a total of 9 patients in the training set (3.3%; heart transplant 1; death due to HF 5; SCD 2, appropriate ICD discharge 1) and 8 in the test set (6.7%; heart transplant 4; death due to HF 0; SCD 2, appropriate ICD discharge 5) experienced cardiac death. Using the prediction model developed in the training set, the area under the receiver-operating-characteristic curve to predict cardiac death was 0.73 (95% confidence interval 0.55–0.90) in the test set. In the time-to-event analysis in the test set, the high-risk group (n=74) had a significantly higher rate of developing cardiac death (log-rank P=0.03; Figure) compared to the low-risk group (n=45). The pathway analysis exhibited that both known pathways (e.g., TGF-β, metabolic, and inflammation) and novel pathways (e.g., Hippo) were dysregulated with false discovery rate &lt;0.01 in patients who subsequently experienced cardiac death (Table).

Conclusions
This study serves as the first to demonstrate the ability of plasma sncRNA-Seq to predict cardiac death in patients with HCM. Patients who subsequently experienced cardiac death exhibited dysregulation of both known and novel pathways.FigureTable