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DNA methylation and body mass index from birth to adolescence: meta-analyses of epigenome-wide association studies.
Vehmeijer, Florianne O L; Küpers, Leanne K; Sharp, Gemma C; Salas, Lucas A; Lent, Samantha; Jima, Dereje D; Tindula, Gwen; Reese, Sarah; Qi, Cancan; Gruzieva, Olena; Page, Christian; Rezwan, Faisal I; Melton, Philip E; Nohr, Ellen; Escaramís, Geòrgia; Rzehak, Peter; Heiskala, Anni; Gong, Tong; Tuominen, Samuli T; Gao, Lu; Ross, Jason P; Starling, Anne P; Holloway, John W; Yousefi, Paul; Aasvang, Gunn Marit; Beilin, Lawrence J; Bergström, Anna; Binder, Elisabeth; Chatzi, Leda; Corpeleijn, Eva; Czamara, Darina; Eskenazi, Brenda; Ewart, Susan; Ferre, Natalia; Grote, Veit; Gruszfeld, Dariusz; Håberg, Siri E; Hoyo, Cathrine; Huen, Karen; Karlsson, Robert; Kull, Inger; Langhendries, Jean-Paul; Lepeule, Johanna; Magnus, Maria C; Maguire, Rachel L; Molloy, Peter L; Monnereau, Claire; Mori, Trevor A; Oken, Emily; Räikkönen, Katri.
Afiliação
  • Vehmeijer FOL; The Generation R Study Group, Erasmus MC, University Medical Center Rotterdam, Room Na-2918, Erasmus MC, PO Box 2040, 3000 CA, Rotterdam, the Netherlands.
  • Küpers LK; Department of Pediatrics, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
  • Sharp GC; Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, Rotterdam, the Netherlands.
  • Salas LA; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
  • Lent S; Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK.
  • Jima DD; University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands.
  • Tindula G; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
  • Reese S; Geisel School of Medicine at Dartmouth, Lebanon, NH, USA.
  • Qi C; ISGlobal, Barcelona, Spain.
  • Gruzieva O; Universitat Pompeu Fabra (UPF), Barcelona, Spain.
  • Page C; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
  • Rezwan FI; Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA.
  • Melton PE; Bioinformatics Research Center, North Carolina State University, Raleigh, NC, USA.
  • Nohr E; Center for Human Health and the Environment, North Carolina State University, Raleigh, NC, USA.
  • Escaramís G; Children's Environmental Health Laboratory, Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, CA, USA.
  • Rzehak P; Department of Health and Human Services, Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, NC, USA.
  • Heiskala A; University of Groningen, University Medical Center Groningen, Department of Pediatric Pulmonology and Pediatric Allergy, Beatrix Children's Hospital, Groningen, The Netherlands.
  • Gong T; University Medical Center Groningen GRIAC Research Institute, University of Groningen, Groningen, the Netherlands.
  • Tuominen ST; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
  • Gao L; Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden.
  • Ross JP; Centre for Fertility and Health, Norwegian Institute of Public Health, Oslo, Norway.
  • Starling AP; Oslo Centre for Biostatistics and Epidemiology, Oslo University Hospital, Oslo, Norway.
  • Holloway JW; School of Water, Energy and Environment, Cranfield University, Cranfield, Bedfordshire, UK.
  • Yousefi P; Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK.
  • Aasvang GM; School of Pharmacy and Biomedical Sciences, Curtin University, Bentley, Western Australia, Australia.
  • Beilin LJ; School of Biomedical Sciences, The University of Western Australia, Crawley, Western Austalia, Australia.
  • Bergström A; Centre for Women's, Family and Child Health, University of South-Eastern Norway, Kongsberg, Norway.
  • Binder E; Institute of Clinical Research, University of Southern Denmark, Odense, Denmark.
  • Chatzi L; CIBER of Epidemiology and Public Health (CIBERESP), Madrid, Spain.
  • Corpeleijn E; Department of Biomedical Sciences, Faculty of Medicine and Health Sciences, University of Barcelona, Barcelona, Spain.
  • Czamara D; Research group on Statistics, Econometrics and Health (GRECS), University of Girona, Girona, Spain.
  • Eskenazi B; Division of Metabolic and Nutritional Medicine, Dr. von Hauner Children's Hospital, Ludwig-Maximilians Universität München (LMU), Munich, Germany.
  • Ewart S; Center for Life Course Health Research, University of Oulu, Oulu, Finland.
  • Ferre N; Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden.
  • Grote V; Department of Psychology and Logopedics, Faculty of Medicine, University of Helsinki, Helsinki, Finland.
  • Gruszfeld D; Department of Preventive Medicine, University of Southern California, Los Angeles, CA, USA.
  • Håberg SE; CSIRO Health and Biosecurity, North Ryde, New South Wales, Australia.
  • Hoyo C; Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA.
  • Huen K; Lifecourse Epidemiology of Adiposity and Diabetes (LEAD) Center, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
  • Karlsson R; Human Development and Health, Faculty of Medicine, Southampton General Hospital, University of Southampton, Southampton, UK.
  • Kull I; Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK.
  • Langhendries JP; MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.
  • Lepeule J; Department of Air Pollution and Noise, Norwegian Institute of Public Health, Oslo, Norway.
  • Magnus MC; Medical School, University of Western Australia, Perth, Australia.
  • Maguire RL; Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden.
  • Molloy PL; Centre for Occupational and Environmental Medicine, Region Stockholm, Stockholm, Sweden.
  • Monnereau C; Department of Translational Research in Psychiatry, Max-Planck-Institute of Psychiatry, Munich, Germany.
  • Mori TA; Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, GA, USA.
  • Oken E; Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.
  • Räikkönen K; University of Groningen, University Medical Center Groningen, Department of Epidemiology, Groningen, the Netherlands.
Genome Med ; 12(1): 105, 2020 11 25.
Article em En | MEDLINE | ID: mdl-33239103
ABSTRACT

BACKGROUND:

DNA methylation has been shown to be associated with adiposity in adulthood. However, whether similar DNA methylation patterns are associated with childhood and adolescent body mass index (BMI) is largely unknown. More insight into this relationship at younger ages may have implications for future prevention of obesity and its related traits.

METHODS:

We examined whether DNA methylation in cord blood and whole blood in childhood and adolescence was associated with BMI in the age range from 2 to 18 years using both cross-sectional and longitudinal models. We performed meta-analyses of epigenome-wide association studies including up to 4133 children from 23 studies. We examined the overlap of findings reported in previous studies in children and adults with those in our analyses and calculated enrichment.

RESULTS:

DNA methylation at three CpGs (cg05937453, cg25212453, and cg10040131), each in a different age range, was associated with BMI at Bonferroni significance, P < 1.06 × 10-7, with a 0.96 standard deviation score (SDS) (standard error (SE) 0.17), 0.32 SDS (SE 0.06), and 0.32 BMI SDS (SE 0.06) higher BMI per 10% increase in methylation, respectively. DNA methylation at nine additional CpGs in the cross-sectional childhood model was associated with BMI at false discovery rate significance. The strength of the associations of DNA methylation at the 187 CpGs previously identified to be associated with adult BMI, increased with advancing age across childhood and adolescence in our analyses. In addition, correlation coefficients between effect estimates for those CpGs in adults and in children and adolescents also increased. Among the top findings for each age range, we observed increasing enrichment for the CpGs that were previously identified in adults (birth Penrichment = 1; childhood Penrichment = 2.00 × 10-4; adolescence Penrichment = 2.10 × 10-7).

CONCLUSIONS:

There were only minimal associations of DNA methylation with childhood and adolescent BMI. With the advancing age of the participants across childhood and adolescence, we observed increasing overlap with altered DNA methylation loci reported in association with adult BMI. These findings may be compatible with the hypothesis that DNA methylation differences are mostly a consequence rather than a cause of obesity.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Índice de Massa Corporal / Metilação de DNA / Parto / Epigênese Genética / Obesidade Tipo de estudo: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Adolescent / Child / Child, preschool / Female / Humans / Male / Pregnancy Idioma: En Revista: Genome Med Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Holanda

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Índice de Massa Corporal / Metilação de DNA / Parto / Epigênese Genética / Obesidade Tipo de estudo: Observational_studies / Prevalence_studies / Prognostic_studies / Risk_factors_studies / Systematic_reviews Limite: Adolescent / Child / Child, preschool / Female / Humans / Male / Pregnancy Idioma: En Revista: Genome Med Ano de publicação: 2020 Tipo de documento: Article País de afiliação: Holanda