A systems proteolipidomic approach identifies novel circulatory biomarkers for idiopathic dilated cardiomyopathy

Shubham Saha1, Praveen Singh2, Abhi Dutta1

  • 1School of Biosciences and Bioengineering, IIT-Mandi, Mandi, India.

Insights

This study reveals a novel proteolipidomic signature for dilated cardiomyopathy (DCM) using advanced omics and machine learning. A combined biomarker panel of lipids and proteins (B2M, CLEC3B) achieved 0.99 AUC, outperforming NT-proBNP for enhanced DCM diagnosis.

Area of Science:

  • Cardiovascular Omics
  • Biomarker Discovery
  • Proteolipidomics

Background:

  • Dilated cardiomyopathy (DCM) is a leading cause of heart failure with limited diagnostic sensitivity of current markers.
  • Lipid and protein alterations in cardiac physiology may offer disease-specific diagnostic insights.
  • Comprehensive proteolipidomic studies and validated biomarkers for DCM are scarce.

Purpose of the Study:

  • To identify a proteolipidomic signature for DCM using an integrative omics approach.
  • To discover and validate novel protein and lipid biomarkers for DCM diagnosis.
  • To develop a multiparametric biomarker panel for improved diagnostic accuracy in DCM.

Main Methods:

  • High-resolution mass spectrometry-based integrative omics analysis of plasma samples from 360 participants (DCM patients and controls).
  • Machine learning (Boruta algorithm) for identifying discriminating lipids and proteins.
  • ELISA validation for protein biomarkers (β2-microglobulin [B2M], tetranectin [CLEC3B]).
  • Correlation analysis with lipid species and oxidative stress markers (8-OHdG).
  • Integrative receiver operating characteristic (ROC) analysis to assess diagnostic performance.

Main Results:

  • Identified 125 significantly altered lipids and 10 proteins in DCM plasma.
  • 39 lipids and 10 proteins were selected as primary discriminators by machine learning.
  • Validated B2M and CLEC3B as significant protein biomarkers for DCM.
  • A combined panel of top lipid discriminators, B2M, and CLEC3B achieved an AUC of 0.99.
  • The developed panel demonstrated superior diagnostic accuracy compared to NT-proBNP (AUC 0.96).

Conclusions:

  • This study presents the first comprehensive proteolipidomic signature for DCM.
  • A novel multiparametric biomarker panel combining lipids (e.g., PA) and proteins (B2M, CLEC3B) offers enhanced diagnostic precision for DCM.
  • The findings suggest potential links between identified biomarkers, oxidative stress, apoptosis, and ECM remodeling in DCM pathogenesis.

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