Prevention & lipidsCross-sectional study
Metabolomic Atlas of Cardiovascular Diseases
- cross-sectional metabolite-disease associations
- nuclear magnetic resonance-based metabolomic data (325 metabolites)
- Logistic regression, random forest, and XGBoost models
- SHapley Additive exPlanations analysis
- Internal geographic validation used Scotland and Wales cohorts
Authors' conclusion
This comprehensive metabolomic atlas reveals both shared and subtype-specific metabolic alterations across prevalent CVD. The identified metabolite set provides a hypothesis-generating framework for understanding cardiovascular metabolic heterogeneity. However, the cross-sectional design and inclusion of treated patients preclude causal or predictive inference, requiring validation in prospective, treatment-naive cohorts.
Study context
- Population
- UK Biobank participants, including those with prevalent cardiovascular disease (CVDs) classified into 87 phenotypes (37 classes, 50 subclasses) using International Classification of Diseases-10th Revision codesUK Biobank participants, including 27,950 with prevalent CVDs
- Participants
- 244,567 participants
Main finding
As reported in the abstract
Metabolites consistently associated with multiple conditions, including Intermediate-Density Lipoprotein cholesteryl esters, linoleic acid percentage, and small very low_density lipoprotein particles
21
Observational data: associations, not effects.
Further findings
Cross-sectional discrimination of prevalent disease status
- chronic ischemic heart disease area under the curve
- 0.876
- moderate-to-high performance for prevalent disease status
Disease similarity clustering
- ischemic entities formed tight clusters, hypertensive-renal diseases showed graded patterns, while rheumatic and pulmonary conditions remained distinct
- These patterns were confirmed in geographic validation cohorts.
Original publication
Summarised from the published abstract; every number is checked against it