Association of clonal hematopoiesis with cardiovascular-kidney-metabolic syndrome in 434,000 individuals
A Chang, D Ezzat, L Li, S Flynn, Z Yu, N De Moor, N Mohammadnia, A Schuermans, M Uddin, P Natarajan, M HonigbergAbstract
Background
Clonal hematopoiesis of indeterminate potential (CHIP), the age-related expansion of blood cells harboring somatic mutations, is associated with increased cardiometabolic risk. The recently proposed cardiovascular-kidney-metabolic (CKM) syndrome framework integrates the shared pathophysiology of cardiovascular disease, excess/dysfunctional adiposity, diabetes, and chronic kidney disease across five CKM stages. However, the relationship between CHIP and CKM syndrome is not well understood.
Purpose
To test the association of CHIP and gene-specific CHIP subtypes with CKM syndrome stage and progression.
Methods
Participants in the UK Biobank without a history of hematologic cancer were included. Co-primary exposures were any CHIP (variant allele fraction [VAF] ≥2%) and large CHIP (VAF ≥10%); major gene-specific CHIP subtypes (DNMT3A, non-DNMT3A, TET2, ASXL1, JAK2, spliceosome, and DNA damage repair CHIP) were examined as secondary exposures. Outcomes were (1) CKM syndrome stage at baseline, according to American Heart Association definitions, and (2) progression to stage 4 CKM syndrome during follow-up. Associations between CHIP and CKM stage were tested using logistic regression, and associations between CHIP and CKM progression were tested using Cox proportional hazards models among those with CKM stages 0-3 at baseline. Mediation analysis was performed to prioritize circulating proteins that represent putative mediators between CHIP and CKM progression. Models were adjusted for age, age², sex, race, smoking history, and Townsend deprivation index; models of CKM progression were further adjusted for baseline CKM stage.
Results
Among 433,924 participants (mean [SD] age, 56.5 [8.1] years; 235,364 females [54.2%]), 14,559 (3.4%) had CHIP. Compared with individuals without any CHIP, those with CHIP had greater odds of higher CKM stages (Figure 1), driven by associations with non-DNMT3A CHIP subtypes (adjusted OR [aOR] for stage 4 CKM associated with non-DNMT3A CHIP vs. no CHIP, 1.33; 95% CI 1.11-1.60; P=0.002), including TET2 CHIP (stage 4 CKM: aOR, 1.48; 95% CI, 1.09-2.02, P=0.01). Over a median of 13.6 years of follow-up, CHIP was independently associated with progression to stage 4 CKM syndrome (adjusted hazard ratio [aHR] 1.11; 95% CI, 1.07-1.15; P<0.001; Figure 2), again driven by associations with non-DNMT3A CHIP subtypes (aHR; 1.20; 95% CI, 1.13-1.28; P<0.001), including TET2 (aHR, 1.18; 95% CI, 1.08-1.30; P<0.001) and spliceosome CHIP (aHR, 1.50; 95% CI, 1.25-1.80; P<0.001). DNMT3A CHIP was not associated with baseline CKM stage or CKM progression. Protein mediators of CHIP-associated CKM progression included QPCT for TET2 CHIP, SIRPB1 for spliceosome CHIP, and REN for DNA damage repair CHIP.
Conclusions
Non-DNMT3A CHIP, including CHIP driven by TET2 mutations, is associated with CKM stage and progression. These findings may have implications for risk stratification and targeted treatment of CKM syndrome.