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Clonal hematopoiesis of indeterminate potential and diabetic kidney disease: a nested case-control study.

By February 3, 2022January 9th, 2024Physicians & academics

Denicolò S, Vogi V, Keller F, Thöni S, Eder S, Heerspink HJL, Rosivall L, Wiecek A, Mark PB, Perco P, Leierer J, Kronbichler A, Steger M, Schwendinger S, Zschocke J, Mayer G, Jukic E. Kidney Int Rep. 2022 Feb 3;7(4):876-888. doi: 10.1016/j.ekir.2022.01.1064. eCollection 2022 Apr.

Introduction: The disease trajectory of diabetic kidney disease (DKD) shows a high interindividual variability not sufficiently explained by conventional risk factors. Clonal hematopoiesis of indeterminate potential (CHIP) is a proposed novel cardiovascular risk factor. Increased kidney fibrosis and glomerulosclerosis were described in mouse models of CHIP. Here, we aim to analyze whether CHIP affects the incidence or progression of DKD.

Methods: A total of 1419 eligible participants of the PROVALID Study were the basis for a nested case-control (NCC) design. A total of 64 participants who reached a prespecified composite endpoint within the observation period (initiation of kidney replacement therapy, death from kidney failure, sustained 40% decline in estimated glomerular filtration rate or sustained progression to macroalbuminuria) were identified and matched to 4 controls resulting in an NCC sample of 294 individuals. CHIP was assessed via targeted amplicon sequencing of 46 genes in peripheral blood. Furthermore, inflammatory cytokines were analyzed in plasma via a multiplex assay.

Results: The estimated prevalence of CHIP was 28.91% (95% CI 22.91%-34.91%). In contrast to other known risk factors (albuminuria, hemoglobin A1c, heart failure, and smoking) and elevated microinflammation, CHIP was not associated with incident or progressive DKD (hazard ratio [HR] 1.06 [95% CI 0.57-1.96]).

Conclusions: In this NCC study, common risk factors as well as elevated microinflammation but not CHIP were associated with kidney function decline in type 2 diabetes mellitus.

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DC-ren has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 848011.