Background
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.

Introduction: Obstructive sleep apnea (OSA) is a common disorder associated with increased risk of cardiovascular diseases and mortality. Recent observational admixture mapping analysis and gene enrichment analysis linked genes and pathways associated with heme metabolism to OSA traits, but the causal contribution is unclear. Iron and heme metabolism is associated with OSA comorbidities and carotid body ventilatory control mechanisms. In this study, we use gene expression data to examine whether iron and heme related pathways have a causal effect on OSA.
Methods: We performed Mendelian randomization (MR) analyses considering the expression level of 15 candidate Gene Ontology pathways as exposures and four OSA traits as outcomes, including the apnea hypopnea index (AHI), and three nocturnal oxygen saturation measurements. In discovery analysis, we performed two-sample MR using local expression trait loci (cis-eQTLs) from the Genotype-Tissue Expression (GTEx) portal and published genome-wide association summary statistics for OSA traits (N>19,000). Significant pathways were then followed-up by one-sample MR using high coverage DNA and RNA sequencing data from the Multi-Ethnic Study of Atherosclerosis generated by the NHLBI Trans-Omics for Precision Medicine (TOPMed) project.
Results: Discovery analysis identified putative causal associations between up-regulated heme biosynthetic process pathway on increased AHI and overnight hypoxemia (minimum P-value=0.018 across OSA traits). These associations were supported in European and Hispanic/Latino Americans but not in African Americans in replication analysis, consistent with prior ancestry-specific associations between a heme-related gene and OSA traits.

Conclusion: This study suggested a causal association between heme biosynthetic processes and OSA severity, suggesting novel biomarkers and possibly treatment targets. Future work is needed to identify the mechanisms for this association and to exclude reverse causality.

Support: This study was supported by Sleep Research Society Foundation Career
Development Award 018-JP-18 to H.W. and NHLBI R35HL135818 to S.R. Molecular data for the TOPMed MESA (phs001416) was supported by NHLBI.