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Assessment of Vascular Function in Patients With Chronic Kidney Disease
Published on: June 16, 2014
Cardiovascular disease protein biomarkers are associated with kidney function: The Framingham Heart Study
Amena Keshawarz1,2, Shih-Jen Hwang1,2, Gha Young Lee1,2
1Population Sciences Branch, Division of Intramural Research, National Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, United States of America.
Insights
Common biomarkers for chronic kidney disease (CKD) and cardiovascular disease (CVD) may indicate early impairments. This study identified specific protein biomarkers associated with kidney function decline, suggesting potential therapeutic targets for CKD prevention and treatment.
Area of Science:
- Biomarkers
- Nephrology
- Cardiology
Background:
- Shared biomarkers between chronic kidney disease (CKD) and cardiovascular disease (CVD) may indicate early underlying pathological processes.
- Investigating these shared biomarkers can provide insights into the interconnectedness of these conditions.
Purpose of the Study:
- To evaluate the association of 71 cardiovascular disease (CVD)-related plasma proteins with cross-sectional and longitudinal measures of kidney function (eGFR and ΔeGFR).
- To validate these associations in an independent cohort and explore potential causal relationships using Mendelian randomization (MR).
- To identify protein biomarkers that may serve as early indicators of kidney impairment and potential therapeutic targets.
Main Methods:
- Analysis of 71 CVD-related plasma proteins in 2,873 Framingham Heart Study (FHS) Offspring cohort participants.
- Assessment of associations with cross-sectional eGFR, longitudinal eGFR change (ΔeGFR), prevalent CKD, new-onset CKD, and rapid eGFR decline.
- Validation in 3,951 FHS Third Generation cohort participants and Mendelian randomization (MR) analysis for causal inference.
Main Results:
- 37 protein biomarkers associated with cross-sectional eGFR, with 20 validated in the second cohort.
- 27 protein biomarkers associated with longitudinal ΔeGFR, with 12 validated.
- Significant associations found for prevalent CKD (35 proteins), new-onset CKD (5 proteins), and rapid eGFR decline (17 proteins).
- MR analysis suggested causal roles for MCAM and EFEMP1 in relation to eGFR.
Conclusions:
- Eight protein biomarkers were consistently associated with kidney function across cross-sectional and longitudinal analyses in both cohorts, potentially indicating early kidney impairment.
- A subset of CVD protein biomarkers may causally contribute to kidney disease pathogenesis.
- These identified biomarkers warrant further investigation as potential targets for CKD treatment and early prevention strategies.
Background:
Biomarkers common to chronic kidney disease (CKD) and cardiovascular disease (CVD) may reflect early impairments underlying both diseases.
Methods:
We evaluated associations of 71 CVD-related plasma proteins measured in 2,873 Framingham Heart Study (FHS) Offspring cohort participants with cross-sectional continuous eGFR and with longitudinal change in eGFR from baseline to follow-up (ΔeGFR). We also evaluated the associations of the 71 CVD proteins with the following dichotomous secondary outcomes: prevalent CKD stage ≥3 (cross-sectional), new-onset CKD stage ≥3 (longitudinal), and rapid decline in eGFR (longitudinal). Proteins significantly associated with eGFR and ΔeGFR were subsequently validated in 3,951 FHS Third Generation cohort participants and were tested using Mendelian randomization (MR) analysis to infer putatively causal relations between plasma protein biomarkers and kidney function.
Results:
In cross-sectional analysis, 37 protein biomarkers were significantly associated with eGFR at FDR<0.05 in the FHS Offspring cohort and 20 of these validated in the FHS Third Generation cohort at p<0.05/37. In longitudinal analysis, 27 protein biomarkers were significantly associated with ΔeGFR at FDR<0.05 and 12 of these were validated in the FHS Third Generation cohort at p<0.05/27. Additionally, 35 protein biomarkers were significantly associated with prevalent CKD, five were significantly associated with new-onset CKD, and 17 were significantly associated with rapid decline in eGFR. MR suggested putatively causal relations of melanoma cell adhesion molecule (MCAM; -0.011±0.003 mL/min/1.73m2, p = 5.11E-5) and epidermal growth factor-containing fibulin-like extracellular matrix protein 1 (EFEMP1; -0.006±0.002 mL/min/1.73m2, p = 0.0001) concentration with eGFR.
Discussion/Conclusions:
Eight protein biomarkers were consistently associated with eGFR in cross-sectional and longitudinal analysis in both cohorts and may capture early kidney impairment; others were implicated in association and causal inference analyses. A subset of CVD protein biomarkers may contribute causally to the pathogenesis of kidney impairment and should be studied as targets for CKD treatment and early prevention.
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