Chronic kidney disease onset, progression, and cardiovascular outcomes: proteomics informs biology and risk stratification
Authors' conclusion
This study deepens insights into disease biology and provides a foundation for early detection and integrated risk stratification in CKD and cardiovascular disease.
Study context
- Population
- UK Biobank participants free of prevalent chronic kidney disease (CKD), and participants with prevalent CKDfree of prevalent CKD
- Participants
- 44,779 participants
- Outcome
- Proteins associated with CKD, end stage kidney disease, CHD, stroke and HF
- Follow-up
- Median 12.2-12.6 years
Methodological detailsproteomics (Olink Explore 3072, 2,923 plasma proteins), Cox proportional hazards models, Mendelian randomization, pathway analyses, predictive models
- Proteomics (Olink Explore 3072, 2,923 plasma proteins)
- Cox proportional hazards models
- Mendelian randomization
- Pathway analyses
- Predictive models
Main finding
As reported in the abstract
Proteins shared across ≥ 2 diseases
598
20.5%
Shared proteins with consistent directions of associations
595
20.4%
Proteins unique to a single disease
471
16.1%
Proteins shared specifically by CKD and heart failure (HF) (largest number)
279
9.6%
Observational data: associations, not effects.
Further findings
Mendelian randomization
- Genetic associations supported for POLR2F with coronary heart disease (CHD) and IGFBP2 with hypertensive renal disease
Pathway analyses
- Cell adhesion, signal transduction and cytokine-cytokine receptor interaction highlighted for disease-associated proteins
Risk prediction adding predictive proteins to clinical models (CKD, CHD, stroke, HF)
- Harrell's C indices
- 0.750-0.818
- Increases in C index
- 0.027-0.090
Original publication
Chronic kidney disease onset, progression, and cardiovascular outcomes: proteomics informs biology and risk stratification. Cardiovasc Diabetol. Published 20 January 2026. doi:10.
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