4.7 Article

PGC1α Promoter Methylation in Blood at 5-7 Years Predicts Adiposity From 9 to 14 Years (EarlyBird 50)

Journal

DIABETES
Volume 63, Issue 7, Pages 2528-2537

Publisher

AMER DIABETES ASSOC
DOI: 10.2337/db13-0671

Keywords

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Funding

  1. Bright Future Trust
  2. Bupa Health Foundation
  3. Kirby Laing Foundation
  4. Peninsula Foundation
  5. EarlyBird Diabetes Trust
  6. National Institute for Health Research Southampton Biomedical Research Centre in Nutrition
  7. Medical Research Council [MC_UU_12011/4, MC_UP_A620_1017] Funding Source: researchfish
  8. MRC [MC_UU_12011/4, MC_UP_A620_1017] Funding Source: UKRI

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The early environment, acting via epigenetic processes, is associated with differential risk of cardiometabolic disease (CMD), which can be predicted by epigenetic marks in proxy tissues. However, such measurements at time points disparate from the health outcome or the environmental exposure may be confounded by intervening stochastic and environmental variation. To address this, we analyzed DNA methylation in the peroxisome proliferator-activated receptor g coactivator 1 alpha promoter in blood from 40 children (20 boys) collected annually between 5 and 14 years of age by pyrosequencing. Body composition was measured annually by dual X-ray absorptiometry, physical activity by accelerometry, and pubertal timing by age at peak high velocity. The effect of methylation on transcription factor binding was investigated by electrophoretic mobility shift assays. Seven cytosine guanine dinucleotide (CpG) loci were identified that showed no significant temporal change or association with leukocyte populations. Modeling using generalized estimating equations showed that methylation of four loci predicted adiposity up to 14 years independent of sex, age, pubertal timing, and activity. Methylation of one predictive locus modified binding of the proadipogenic pre-B-cell leukemia homeobox-1/homeobox 9 complex. These findings suggest that temporally stable CpG loci measured in childhood may have utility in predicting CMD risk.

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