CardioRisk-DB

A multi-omics knowledgebase for phenotype-anchored cardiotoxicity risk prediction

Integrating transcriptomics, genetic evidence, and causal inference to identify cardiotoxic drugs and molecular mechanisms. Powered by PAMD and Split-GSVA contrastive modeling.

Database Overview

Core Genes
Compounds
Total Samples Analyzed
12
Datasets
0.857
Validation AUC

Scientific Framework

PAMD + Split-GSVA

Drug-induced transcriptional responses often contain non-specific cellular stress signals (e.g., heat shock, DNA repair) that obscure true cardiotoxic mechanisms.

Our framework utilizes Phenotype-Anchored Multi-omics Distillation (PAMD) combined with contrastive Split-GSVA scoring to filter out generic background noise and isolate cardiotoxicity-specific molecular signatures.



Explore Modules

Gene Explorer
Phenotype Network
Risk Calculator

Signature Architecture

Distribution of PAMD selected genes across the Upregulated (Risk) and Downregulated (Protective) directions.

Leave-One-Drug-Out (LODO) Audit & Stability

Model stability when selectively removing specific chemical classes from the training manifold.


Causal Forest Plot: Gene-Disease Associations

Mendelian Randomization (MR) evidence linking signature genes to clinical cardiovascular outcomes. Error bars indicate 95% CI.

Upload Data

Download Matrix Template

Prediction Report

About CardioRisk-DB

CardioRisk-DB is an open-source, multi-omics knowledgebase dedicated to evaluating the cardiotoxicity of environmental chemicals and pharmaceutical drugs.

Citation

If you use CardioRisk-DB in your research, please cite:

Zhang J, et al. (2026). Phenotype-Anchored Molecular Distillation reveals contrastive transcriptomic signatures for robust cardiotoxicity prediction.