Journal of Developmental Origins of Health and DiseaseGenetic & Genomic MedicinePeer-reviewed journal article
Methylation profiles at birth linked to early childhood obesity
Delphine LarivièreiD, Sarah J. C. CraigiD, Ian M. PauliD, Emily E. HohmaniD, Jennifer S. SavageiD, Robert O. WrightiD, Francesca ChiaromonteiD, Kateryna D. MakovaiD, Matthew L. ReimherriD
Abstract
Childhood obesity represents a significant global health concern and identifying risk factors is crucial for developing intervention programs. Many omics factors associated with the risk of developing obesity have been identified, including genomic, microbiomic, and epigenomic factors. Here, using a sample of 48 infants, we investigated how the methylation profiles in cord blood and placenta at birth were associated with weight outcomes (specifically, conditional weight gain, body mass index, and weight-for-length ratio) at age six months. We characterized genome-wide DNA methylation profiles using the Illumina Infinium MethylationEpic chip, and incorporated information on child and maternal health, and various environmental factors into the analysis. We used regression analysis to identify genes with methylation profiles most predictive of infant weight outcomes, finding a total of 23 relevant genes in cord blood and 10 in placenta. Notably, in cord blood, the methylation profiles of three genes (PLIN4, UBE2F, and PPP1R16B) were associated with all three weight outcomes, which are also associated with weight outcomes in an independent cohort suggesting a strong relationship with weight trajectories in the first six months after birth. Additionally, we developed a Methylation Risk Score (MRS) that could be used to identify children most at risk for developing childhood obesity. While many of the genes identified by our analysis have been associated with weight-related traits (e.g., glucose metabolism, BMI, or hip-to-waist ratio) in previous genome-wide association and variant studies, our analysis implicated several others, whose involvement in the obesity phenotype should be evaluated in future functional investigations.
- organism: human
- assay: DNA methylation
- research focus: differential expression
- approach: statistical model
- Citations
- 8
- FWCI
- 5.42
- Field percentile
- top 5%
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