Associations between ambient air pollutants and clonal hematopoiesis of indeterminate potential (CHIP)

Abstract

BACKGROUND AND AIM: Biological mechanisms underlying the relationship between exposure to ambient air pollution and development of cardiovascular disease (CVD) have not been adequately described. One pathway could involve acquisition of somatic mutations associated with incidence of hematologic cancers and CVD termed “clonal hematopoiesis of indeterminate potential” (CHIP), most commonly mutated in DNMT3A. We assessed cross-sectional associations between long-term air pollutant concentrations and CHIP mutation prevalence. METHODS: CHIP mutations were identified in the Trans-omics for Precision Medicine program using blood DNA-derived whole genome sequencing for participants of the Multi-Ethnic Study of Atherosclerosis. A spatio-temporal modeling framework predicted individual-level average air pollution concentrations (particulate matter 2.5 µm, PM2.5; nitrogen dioxide, NO2; oxides of nitrogen, NOx) at residential locations one year before blood draw (Exams 1-3, 2000-2005). Primary exclusions were history of hematologic malignancy or myelosuppressive chemotherapeutics. Logistic regression estimated odds ratios (OR) of CHIP mutation per IQR increase in air pollutant concentration, adjusting for age, gender, smoking status, race/ethnicity, income, and calendar year. RESULTS:4,445 individuals were included and 196 (4.41%) had CHIP mutations. 67.9% of CHIP mutations were in DNMT3A. Adjusted ORs for CHIP per increase in air pollution were increased, however did not reach statistical significance. ORs for CHIP mutation were 1.05 (95% CI 0.90, 1.23) per 4 µg/m3 for PM2.5, 1.18 (95% CI 0.87, 1.59) per 16 ppb for NO2, and 1.21 (95% CI 0.93, 1.56) per 38 ppb for NOx. Adjusted ORs for DNMT3A-specific CHIP were 1.13 (95% CI 0.94, 1.36) for PM2.5, 1.26 (95% CI 0.87, 1.81) for NO2, and 1.28 (95% CI 0.93, 1.75) for NOx. CONCLUSIONS:Our results are suggestive of associations between long term concentrations in air pollution and prevalence of CHIP mutations, but not statistically significant. A larger sample size may be required to provide insight into the relationship between air pollution and CHIP. KEYWORDS: air pollution, pm2.5, no2, CHIP