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Prediction of Major Adverse Cardiovascular Events in Patients With Hypertrophic Cardiomyopathy Using Proteomics
Yuichi J Shimada1,2, Yoshihiko Raita3, Lusha W Liang1
1Division of Cardiology, Department of Medicine (Y.J.S., L.W.L., M.S.M., M.P.K.), Columbia University Irving Medical Center, New York, NY.
Insights
This study introduces a novel proteomics model to predict major adverse cardiovascular events (MACE) in hypertrophic cardiomyopathy. The model identifies key signaling pathways, including Ras-MAPK, linked to MACE development.
Area of Science:
- Cardiovascular Medicine
- Proteomics
- Biomarker Discovery
Background:
- Hypertrophic cardiomyopathy (HCM) is a significant risk factor for major adverse cardiovascular events (MACE), including arrhythmias, stroke, heart failure, and sudden cardiac death.
- Currently, no predictive models or identified signaling pathways exist for MACE in HCM patients.
- Understanding these pathways is crucial for developing targeted interventions.
Purpose of the Study:
- To prospectively identify protein biomarkers capable of predicting MACE in patients with HCM.
- To elucidate the specific signaling pathways that are differentially regulated in patients who subsequently develop MACE.
Main Methods:
- A multi-center prospective cohort study involving 245 HCM patients.
- Plasma proteomics profiling of 4979 proteins was performed at enrollment.
- A proteomics-based model was developed and validated for MACE prediction, alongside time-to-event and pathway analyses.
Main Results:
- The proteomics-based model demonstrated good predictive ability for MACE in an independent test set (AUC 0.81).
- Patients identified as high-risk by the model had a significantly increased rate of MACE (HR 13.6, P=0.01).
- The Ras-MAPK pathway was notably upregulated in patients who developed MACE, along with inflammation and TGF-β pathways.
Conclusions:
- This research is the first to utilize proteomics profiling for MACE prediction in HCM.
- The study highlights the novel Ras-MAPK pathway and known pathways like TGF-β as differentially regulated in MACE development.
- These findings offer potential for improved risk stratification and therapeutic strategies in HCM.
Background:
Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE.
Methods:
In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of <0.001.
Results:
The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68-0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7-107]; P=0.01). The Ras-MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate<1.0×10-7). Pathways involved in inflammation and fibrosis-for example, the TGF (transforming growth factor)-β pathway-were also upregulated.
Conclusions:
This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg, Ras-MAPK) and known (eg, TGF-β) pathways differentially regulated in patients who subsequently experience MACE.
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