Frontiers in Endocrinology (Dec 2022)

The relationship between hair metabolites, air pollution exposure and gestational diabetes mellitus: A longitudinal study from pre-conception to third trimester

  • Xuyang Chen,
  • Xuyang Chen,
  • Xue Zhao,
  • Xue Zhao,
  • Mary Beatrix Jones,
  • Alexander Harper,
  • Jamie V. de Seymour,
  • Yang Yang,
  • Yang Yang,
  • Yinyin Xia,
  • Ting Zhang,
  • Ting Zhang,
  • Ting Zhang,
  • Hongbo Qi,
  • Hongbo Qi,
  • Hongbo Qi,
  • John Gulliver,
  • Richard D. Cannon,
  • Richard Saffery,
  • Hua Zhang,
  • Hua Zhang,
  • Ting-Li Han,
  • Ting-Li Han,
  • Ting-Li Han,
  • Philip N. Baker

DOI
https://doi.org/10.3389/fendo.2022.1060309
Journal volume & issue
Vol. 13

Abstract

Read online

BackgroundGestational diabetes mellitus (GDM) is a metabolic condition defined as glucose intolerance with first presentation during pregnancy. Many studies suggest that environmental exposures, including air pollution, contribute to the pathogenesis of GDM. Although hair metabolite profiles have been shown to reflect pollution exposure, few studies have examined the link between environmental exposures, the maternal hair metabolome and GDM. The aim of this study was to investigate the longitudinal relationship (from pre-conception through to the third trimester) between air pollution exposure, the hair metabolome and GDM in a Chinese cohort.MethodsA total of 1020 women enrolled in the Complex Lipids in Mothers and Babies (CLIMB) birth cohort were included in our study. Metabolites from maternal hair segments collected pre-conception, and in the first, second, and third trimesters were analysed using gas chromatography-mass spectrometry (GC-MS). Maternal exposure to air pollution was estimated by two methods, namely proximal and land use regression (LUR) models, using air quality data from the air quality monitoring station nearest to the participant’s home. Logistic regression and mixed models were applied to investigate associations between the air pollution exposure data and the GDM associated metabolites.ResultsOf the 276 hair metabolites identified, the concentrations of fourteen were significantly different between GDM cases and non-GDM controls, including some amino acids and their derivatives, fatty acids, organic acids, and exogenous compounds. Three of the metabolites found in significantly lower concentrations in the hair of women with GDM (2-hydroxybutyric acid, citramalic acid, and myristic acid) were also negatively associated with daily average concentrations of PM2.5, PM10, SO2, NO2, CO and the exposure estimates of PM2.5 and NO2, and positively associated with O3.ConclusionsThis study demonstrated that the maternal hair metabolome reflects the longitudinal metabolic changes that occur in response to environmental exposures and the development of GDM.

Keywords