Autor: |
Gagné-Ouellet V; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada., Breton E; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada., Thibeault K; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada., Fortin CA; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada., Desgagné V; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.; Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean-Hôpital Universitaire de Chicoutimi, Saguenay, QC G7H 5H6, Canada., Girard Tremblay É; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada., Cardenas A; Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA 94720-7360, USA., Guérin R; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.; Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean-Hôpital Universitaire de Chicoutimi, Saguenay, QC G7H 5H6, Canada., Perron P; Department of Medicine, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.; Centre de Recherche du CHUS, Sherbrooke, QC J1H 5N4, Canada., Hivert MF; Department of Medicine, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.; Diabetes Unit, Massachusetts General Hospital, Boston, MA 02114, USA.; Department of Population Medicine, Harvard Pilgrim Health Care Institute, Harvard Medical School, Boston, MA 02115, USA., Bouchard L; Department of Biochemistry and Functional Genomics, Université de Sherbrooke, Sherbrooke, QC J1H 5N4, Canada.; Department of Medical Biology, CIUSSS Saguenay-Lac-Saint-Jean-Hôpital Universitaire de Chicoutimi, Saguenay, QC G7H 5H6, Canada.; Centre de Recherche du CHUS, Sherbrooke, QC J1H 5N4, Canada. |
Abstrakt: |
The aim of this study was to identify placental DNA methylation (DNAm) variations associated with adiposity at 3 years of age. We quantified placental DNAm using the Infinium MethylationEPIC BeadChips. We assessed associations between DNAm at single-CpGs and skinfold thickness using robust linear regression models adjusted for gestational age, child's sex, age at follow-up and cellular heterogeneity. We sought replication of DNAm association with child adiposity in an independent cohort. We quantified placental mRNA levels for annotated gene using qRT-PCR and tested for correlation with DNAm. Lower DNAm at cg22593959 and cg22436429 was associated with higher adiposity ( β = -1.18, q = 0.002 and β = -0.82, q = 0.04). The cg22593959 is located in an intergenic region (chr7q31.3), whereas cg22436429 is within the TFAP2E gene (1p34.3). DNAm at cg22593959 and cg22436429 was correlated with mRNA levels at FAM3C (r s = -0.279, p = 0.005) and TFAP2E (r s = 0.216, p = 0.03). In an independent cohort, the association between placental DNAm at cg22593959 and childhood adiposity was of similar strength and direction ( β = -3.8 ± 4.1, p = 0.36), yet non-significant. Four genomic regions were also associated with skinfold thickness within FMN1 , MAGI2 , SKAP2 and BMPR1B genes. We identified placental epigenetic variations associated with adiposity at 3 years of age suggesting that childhood fat accretion patterns might be established during fetal life. |