Cardiovascular-kidney-metabolic syndrome: candidate subtypes and genetic risk factors

TL;DR

This study identifies five distinct subtypes of cardiovascular-kidney-metabolic syndrome and finds new genetic risk factors specific to each subtype.

Contribution

The novel contribution is the identification of five CKM subtypes and 57 new genetic variants linked to these subtypes using combined biomarker analysis.

Findings

Five CKM subtypes were identified with distinct biomarker profiles including blood glucose, uric acid, and inflammation markers.

Genetic analysis revealed 57 genome-wide significant variants, 35 of which were not detected in single-biomarker studies.

Most genetic variants were subtype-specific, indicating different biological pathways underlie each CKM subtype.

Abstract

Cardiovascular-kidney-metabolic (CKM) syndrome is increasingly recognized as a distinct disorder with important implications for health outcomes, but its heterogeneity of presentation and genetic underpinning remains poorly understood. We aimed to identify potential CKM subtypes and their genetic basis by analyzing biomarkers and health outcomes in a large biobank.

Blood and urine biomarkers from 121,918 participants in the Lifelines cohort were analyzed using topic modelling. Candidate CKM subtypes were operationally defined as blood-urine topics that were simultaneously and positively associated with self-reported kidney disease, type 2 diabetes, and cardiovascular disease. Genome-wide association studies were performed on 52,727 genotyped participants to identify common genetic variants linked to these candidate subtypes.

Five candidate CKM subtypes were identified, each characterized by high levels of blood glucose, uric acid, urea and inflammation biomarkers, but differing in liver enzyme, cholesterol, and glycaemic profiles. Genetic analyses revealed 57 genome-wide significant variants, with the majority (35) not detected in single-biomarker analyses. Most variants were subtype-specific, suggesting that distinct biological pathways contribute to these candidate CKM subtypes.

Our analysis suggests distinct genetic architectures underlying different CKM manifestations and demonstrates that combining biomarkers in disease-relevant constellations improves detection of genetic variants.

The online version contains supplementary material available at 10.1186/s12920-026-02315-8.

Figures