title: Ambient particulate matter and microRNAs in extracellular vesicles: a pilot study of older individuals.
abstract: BACKGROUND
  Air pollution from particulate matter (PM) has been linked to cardiovascular morbidity and mortality; however the underlying biological mechanisms remain to be uncovered. Gene regulation by microRNAs (miRNAs) that are transferred between cells by extracellular vesicles (EVs) may play an important role in PM-induced cardiovascular risk. This study sought to determine if ambient PM2.5 levels are associated with expression of EV-encapsulated miRNAs (evmiRNAs), and to investigate the participation of such evmiRNAs in pathways related to cardiovascular disease (CVD).
  
  
  METHODS
  We estimated the short- (1-day), intermediate- (1-week and 1-month) and long-term (3-month, 6-month, and 1-year) moving averages of ambient PM2.5 levels at participants' addresses using a validated hybrid spatio-temporal land-use regression model. We collected 42 serum samples from 22 randomly selected participants in the Normative Aging Study cohort and screened for 800 miRNAs using the NanoString nCounter® platform. Mixed effects regression models, adjusted for potential confounders were used to assess the association between ambient PM2.5 levels and evmiRNAs. All p-values were adjusted for multiple comparisons. In-silico Ingenuity Pathway Analysis (IPA) was performed to identify biological pathways that are regulated by PM-associated evmiRNAs.
  
  
  RESULTS
  We found a significant association between long-term ambient PM2.5 exposures and levels of multiple evmiRNAs circulating in serum. In the 6-month window, ambient PM2.5 exposures were associated with increased levels of miR-126-3p (0.74 ± 0.21; p = 0.02), miR-19b-3p (0.52 ± 0.15; p = 0.02), miR-93-5p (0.78 ± 0.22; p = 0.02), miR-223-3p (0.74 ± 0.22; p = 0.02), and miR-142-3p (0.81 ± 0.21; p = 0.03). Similarly, in the 1-year window, ambient PM2.5 levels were associated with increased levels of miR-23a-3p (0.83 ± 0.23; p = 0.02), miR-150-5p (0.90 ± 0.24; p = 0.02), miR-15a-5p (0.70 ± 0.21; p = 0.02), miR-191-5p (1.20 ± 0.35; p = 0.02), and let-7a-5p (1.42 ± 0.39; p = 0.02). In silico pathway analysis on PM2.5-associated evmiRNAs identified several key CVD-related pathways including oxidative stress, inflammation, and atherosclerosis.
  
  
  CONCLUSIONS
  We found an association between long-term ambient PM2.5 levels and increased levels of evmiRNAs circulating in serum. Further observational studies are warranted to confirm and extend these important findings in larger and more diverse populations, and experimental studies are needed to elucidate the exact roles of evmiRNAs in PM-induced CVD.
authors.affiliation: Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. rrodosth@hsph.harvard.edu.
authors.forename: Rodosthenis S
authors.initials: RS
authors.lastname: Rodosthenous
authors.affiliation: Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. bcoull@hsph.harvard.edu.
authors.forename: Brent A
authors.initials: BA
authors.lastname: Coull
authors.affiliation: Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. qlu@hsph.harvard.edu.
authors.forename: Quan
authors.initials: Q
authors.lastname: Lu
authors.affiliation: VA Boston Healthcare System, Boston, MA, USA. Pantel.Vokonas@va.gov.
authors.forename: Pantel S
authors.initials: PS
authors.lastname: Vokonas
authors.affiliation: Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. jschwrtz@hsph.harvard.edu.
authors.forename: Joel D
authors.initials: JD
authors.lastname: Schwartz
authors.affiliation: Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA. abaccare@hsph.harvard.edu.
authors.forename: Andrea A
authors.initials: AA
authors.lastname: Baccarelli
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D000375:Aging / Q000097:blood* / Q000235:genetics; D000393:Air Pollutants / Q000009:adverse effects / Q000097:blood*; D015415:Biomarkers / Q000097:blood; D002318:Cardiovascular Diseases / Q000097:blood / Q000139:chemically induced / Q000235:genetics; D003198:Computer Simulation; D030541:Databases, Genetic; D000067128:Extracellular Vesicles / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000379:methods; D053263:Gene Regulatory Networks; D006801:Humans; D019570:Inhalation Exposure; D008297:Male; D035683:MicroRNAs / Q000097:blood* / Q000235:genetics; D008875:Middle Aged; D020411:Oligonucleotide Array Sequence Analysis; D010316:Particle Size; D052638:Particulate Matter / Q000009:adverse effects / Q000097:blood*; D010865:Pilot Projects; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors; D055815:Young Adult
chemical_list: D000393:Air Pollutants; D015415:Biomarkers; D035683:MicroRNAs; D052638:Particulate Matter