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Beyond eGFR and Albuminuria: Biological Pathways and Multiomics in Cardiovascular-Kidney-Metabolic Disease
William R Marshall1,2, Thomas McDonnell1,2, Darren Green1,2
1Division of Cardiovascular Sciences, University of Manchester, Manchester, UK.
Kidney International Reports
|June 15, 2026
Summary
Cardiovascular-kidney-metabolic disease (CKM) risk stratification can be improved by integrating novel pathway-oriented biomarkers. These biomarkers identify early biological processes, enabling mechanism-informed risk prediction and personalized treatment strategies for CKM.
Area of Science:
- Integrative biology and precision medicine
- Biomarker discovery and development
- Cardiovascular-kidney-metabolic disease (CKM) research
Background:
- CKM disease is a growing public health concern linked to obesity, diabetes, and aging.
- Current risk stratification relies on conventional markers reflecting organ dysfunction, not upstream causes.
- Novel multi-omics approaches offer insights into CKM's underlying biological networks.
Purpose of the Study:
- To review molecular pathways and novel biomarkers in CKM.
- To explore integrated multiomics and AI for refining risk prediction and personalized treatment.
- To bridge understanding of CKM disease mechanisms with targeted therapeutic strategies.
Main Methods:
- Comprehensive literature review of CKM molecular pathways and biomarkers.
- Analysis of emerging multiomics technologies (proteomics, metabolomics, transcriptomics, genomics).
- Discussion of artificial intelligence applications in risk stratification and endotyping.
Main Results:
- CKM involves complex biological networks including immune activation, fibrosis, and metabolic dysfunction.
- Emerging biomarkers can detect biological activity before overt organ dysfunction.
- Novel biomarkers span inflammatory, fibrotic, metabolic, and microvascular biology.
Conclusions:
- Integrating pathway-oriented biomarkers with clinical measures can enhance CKM risk stratification.
- Biomarker innovation is crucial for aligning expanding therapeutic options with biological phenotypes.
- Multiomics and AI hold promise for identifying CKM molecular endotypes and guiding personalized therapy.
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