Non-Targeted Metabolite Profiling of Dried Blood Spots in a Field-Based Epidemiologic Study of Household Air Pollution

摘要

Household air pollution (HAP), primarily from solid fuel combustion in cookstoves, is a leading risk factor for the global burden of disease; however, direct evidence linking HAP with chronic disease endpoints is limited. Obtaining clinical chronic disease measures in rural settings of low- and middle-income countries is logistically challenging; consequently, focus has been placed on subclinical indicators of risk. The ability to conduct non-targeted metabolomics profiling from dried blood spots (DBS) represents an innovative approach with potential for biomarker discovery and characterization. We conducted a cross-sectional study among 107 women, aged 25-55 years, using wood-burning cookstoves in rural Honduras. Kitchen and personal 24-hour fine particulate matter (PM2.5) concentrations were collected via gravimetric sampling. DBS were collected via finger-stick. Global non-targeted metabolite profiling was performed using reverse phase ultra performance liquid chromatography and high resolution mass spectrometry. In separate linear models, we evaluated the association between 24-hour PM2.5 concentration and each metabolite, adjusting for age, body mass index, physical activity, and socio-economic status, using a correction for multiple testing. PM2.5 exposures were associated with 27 out of 1,395 metabolites; five metabolites were annotated (e.g., phenylalanine, terpene). Lysophosphatidylcholine 18:2, a metabolite previously identified as being protective for incident coronary heart disease, was inversely associated with kitchen PM2.5 concentrations. We will evaluate standards for annotated metabolites to quantify the PM2.5 relationships. The use of DBS could have far-reaching impacts on field-based sciences, such as HAP research, by expanding the ability to characterize environmental impacts on metabolomic profiles in rural populations where relevant measurements were previously not feasible.