Fine particulate matter (PM2.5) represents a mixture of components with potentially different toxicities. However, little is known about the relative effects of PM2.5 mass and PM2.5 components on mitochondrial DNA (mtDNA) abundance, which may lie on the pathway of PM2.5-associated disease.
We studied 646 elderly male participants in the Normative Aging Study from Greater Boston to investigate associations of long-term exposure to PM2.5 mass and PM2.5 components with mtDNA abundance. We estimated concentrations of pollutants for the 365-day preceding examination at each participant’s address using spatial- and temporal-resolved chemical transport models. We measured blood mtDNA abundance using RT-PCR. We applied a shrinkage and selection method (adaptive LASSO) to identify components most predictive of mtDNA abundance, and fit multipollutant linear mixed-effects models with subject-specific intercept to estimate the relative effects of individual PM component.
MtDNA abundance was negatively associated with PM2.5 mass in the previous year and—after adjusting for PM2.5 mass—several PM2.5 components, including organic carbon, sulfate (marginally), and nitrate. In multipollutant models including as independent variables PM2.5 mass and PM2.5 components selected by LASSO, nitrate was associated with mtDNA abundance. An SD increase in annual PM2.5-associated nitrate was associated with a 0.12 SD (95% confidence intervals [CI] = −0.18, −0.07) decrease in mtDNA abundance. Analyses restricted to PM2.5 annual concentration below the current 1-year U.S. Environmental Protection Agency standard produced similar results.
Long-term exposures to PM2.5-associated nitrate were related to decreased mtDNA abundance independent of PM2.5 mass. Mass alone may not fully capture the potential of PM2.5 to oxidize the mitochondrial genome.
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From the aChanning Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA; bVocational Health College, Canakkale Onsekiz Mart University, Çanakkale, Turkey; cDepartment of Developmental Neurobiology, National Institute of Perinatology, Mexico City, Mexico; dDepartment of Environmental Health, Harvard T. H. Chan School of Public Health, Boston, MA; eDepartment of Statistics, Colorado State University, Fort Collins, CO; fDepartment of Environmental Health Sciences, Columbia Mailman School of Public Health, New York, NY; gDepartment of Biostatistics, Harvard School of Public Health, Boston, MA; and hNormative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, MA.
Submitted May 10, 2016; accepted July 12, 2017.
The authors report no conflicts of interest.
The views expressed in this article are those of the authors and do not necessarily represent the views of the funding or supporting entities.
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Correspondence: Cheng Peng, Department of Environmental Health, Harvard School of Public Health, Building 1, G-7, 665 Huntington Avenue, Boston, MA 02115. E-mail: firstname.lastname@example.org.