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Abstract
New insights into mechanisms linking obesity to poor health outcomes suggest a role for cellular aging pathways, casting obesity as a disease of accelerated biological aging. Although obesity has been linked to accelerated epigenetic aging in middle-aged adults, the impact during childhood remains unclear. We tested the association between body mass index (BMI) and accelerated epigenetic aging in a cohort of high-risk children. Participants were children (N = 273, aged 8 to 14 years, 82% investigated for maltreatment) recruited to the Child Health Study, an ongoing prospective study of youth investigated for maltreatment and a comparison youth. BMI was measured as a continuous variable. Accelerated epigenetic aging of blood leukocytes was defined as the age-adjusted residuals of several established epigenetic aging clocks (Horvath, Hannum, GrimAge, PhenoAge) along with a newer algorithm, the DunedinPoAm, developed to quantify the pace-of-aging. Hypotheses were tested with generalized linear models. Higher age-and sex- adjusted z-scored BMI was significantly correlated with household income, blood cell counts, and three of the accelerated epigenetic aging measures: GrimAge (r = 0.31, P < .0001), PhenoAge (r = 0.24, P < .0001), and DunedinPoAm (r = 0.38, P < .0001). In fully adjusted models, GrimAge (β = 0.07; P = .0009) and DunedinPoAm (β = 0.0017; P < .0001) remained significantly associated with higher age- and sex-adjusted z-scored BMI. Maltreatment-status was not associated with accelerated epigenetic aging. In a high-risk cohort of children, higher BMI predicted epigenetic aging as assessed by two epigenetic aging clocks. These results suggest the association between obesity and accelerated epigenetic aging begins in early life, with implications for future morbidity and mortality risk.
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1 The Pennsylvania State University, Department of Biobehavioral Health, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281)
2 The Pennsylvania State University, Department of Veterinary and Biomedical Sciences, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281)
3 The Pennsylvania State University, Department of Biobehavioral Health, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281); Humboldt-Universität Zu Berlin, Berlin Institute of Health (BIH), Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Institute of Medical Psychology, Berlin, Germany (GRID:grid.7468.d) (ISNI:0000 0001 2248 7639)
4 McGill University, Departments of Psychiatry and Neurology and Neurosurgery, Montreal, Canada (GRID:grid.14709.3b) (ISNI:0000 0004 1936 8649)
5 The Pennsylvania State University, Department of Human Development and Family Studies, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281)
6 Yale University, Yale Child Study Center, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710); Yale School of Medicine, Yale University, Department of Obstetrics Gynecology and Reproductive Sciences, New Haven, USA (GRID:grid.47100.32) (ISNI:0000000419368710)
7 Douglas Mental Health University Institute, McGill University, Ludmer Centre for Neuroinformatics and Mental Health, Montreal, Canada (GRID:grid.14709.3b) (ISNI:0000 0004 1936 8649)
8 The Pennsylvania State University, Department of Human Development and Family Studies, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281); The Pennsylvania State University, Edna Bennett Pierce Prevention Research Center, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281)
9 The Pennsylvania State University, Department of Human Development and Family Studies, University Park, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281); The Pennsylvania State University College of Medicine, Department of Pediatrics, Hershey, USA (GRID:grid.29857.31) (ISNI:0000 0001 2097 4281)