Birth weight associations with DNA methylation differences in an adult population

References

• Barker DJ. The developmental origins of adult disease. J Am Coll Nutr. 2004;23(6Suppl):588s–95s.
   Google Scholar
• Paneth N, Susser M. Early origin of coronary heart disease (the “Barker hypothesis”). Br Med J. 1995;310(6977):411–412.
   Google Scholar
• Rondo PHC, Ferreira RF, Nogueira F, et al. Maternal psychological stress and distress as predictors of low birth weight, prematurity and intrauterine growth retardation. Eur J Clin Nutr. 2003;57(2):266–272.
   Google Scholar
• Grote NK, Bridge JA, Gavin AR, et al. Meta-analysis of depression during pregnancy and the risk of preterm birth, low birth weight, and intrauterine growth restriction. Arch Gen Psychiatry. 2010;67(10):1012–1024.
   Google Scholar
• Rosen D, Seng JS, Tolman RM, et al. Intimate partner violence, depression, and posttraumatic stress disorder as additional predictors of low birth weight infants among low-income mothers. J Interpers Violence. 2007;22(10):1305–1314.
   Google Scholar
• Horikoshi M, Beaumont RN, Day FR, et al. Genome-wide associations for birth weight and correlations with adult disease. Nature. 2016;538(7624):248–252.
   Google Scholar
• Warrington NM, Beaumont RN, Horikoshi M, et al. Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors. Nat Genet. 2019;51(5):804–814.
   Google Scholar
• Huxley R, Owen CG, Whincup PH, et al. Is birth weight a risk factor for ischemic heart disease in later life? Am J Clin Nutr. 2007;85(5):1244–1250.
   Google Scholar
• Zanetti D, Tikkanen E, Gustafsson S, et al. Birthweight, type 2 diabetes mellitus, and cardiovascular disease addressing the barker hypothesis with mendelian randomization. Circ Genomic Precis Med. 2018;11(6). DOI: 10.1161/CIRCGEN.117.002054.
   Google Scholar
• Mu M, Wang SF, Sheng J, et al. Birth weight and subsequent blood pressure: A meta-analysis. Arch Cardiovasc Dis. 2012;105(2):99–113.
   Google Scholar
• Rich-Edwards JW, Kleinman K, Michels KB, et al. Longitudinal study of birth weight and adult body mass index in predicting risk of coronary heart disease and stroke in women. Br Med J. 2005;330(7500):1115–8A.
   Google Scholar
• Shenkin SD, Starr JM, Deary IJ. Birth weight and cognitive ability in childhood: A systematic review. Psychol Bull. 2004;130(6):989–1013.
   Google Scholar
• Wojcik W, Lee W, Colman I, et al. Foetal origins of depression? A systematic review and meta-analysis of low birth weight and later depression. Psychol Med. 2013;43(1):1–12.
   Google Scholar
• Kiserud T, Piaggio G, Carroli G, et al. The world health organization fetal growth charts: a multinational longitudinal study of ultrasound biometric measurements and estimated fetal weight. PLoS Med. 2017;14(1):1–36.
   Google Scholar
• Jaenisch R, Bird A. Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet. 2003;33:245–254.
   Google Scholar
• Simpkin AJ, Suderman M, Gaunt TR, et al. Longitudinal analysis of DNA methylation associated with birth weight and gestational age. Hum Mol Genet. 2015;24(13):3752–3763.
   Google Scholar
• Chen P-Y, Chu A, Liao -W-W, et al. Prenatal growth patterns and birthweight are associated with differential DNA methylation and gene expression of cardiometabolic risk genes in human placentas: a discovery-based approach. Reprod Sci. 2018;25(4):523–539. .
   Google Scholar
• Küpers LK, Monnereau C, Sharp GC, et al. Meta-analysis of epigenome-wide association studies in neonates reveals widespread differential DNA methylation associated with birthweight. Nat Commun. 2019;10(1):1893.
   Google Scholar
• Agha G, Hajj H, Rifas-Shiman SL, et al. Birth weight-for-gestational age is associated with DNA methylation at birth and in childhood. Clin Epigenetics. 2016;8. DOI:10.1186/s13148-016-0285-3.
   Google Scholar
• Felix JF, Cecil CAM. Population DNA methylation studies in the developmental origins of health and disease (DOHaD) framework. J Dev Orig Health Dis. 2019;10(3):306–313.
   Google Scholar
• Heijmans BT, Tobi EW, Stein AD, et al. Persistent epigenetic differences associated with prenatal exposure to famine in humans. Proc Nat Acad Sci. 2008;105(44):17046–17049.
   Google Scholar
• Hillary RF, Stevenson AJ, McCartney DL, et al. Epigenetic clocks predict prevalence and incidence of leading causes of death and disease burden. bioRxiv. 2020. 2020.01.31.928648.
   Google Scholar
• Horvath S. DNA methylation age of human tissues and cell types. Genome Biol. 2013;14(10):3156.
   Google Scholar
• Hannum G, Guinney J, Zhao L, et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Mol Cell. 2013;49(2):359–367.
   Google Scholar
• Levine ME, Lu AT, Quach A, et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY). 2018;10(4):573–591.
   Google Scholar
• Lu AT, Quach A, Wilson JG, et al. DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (Albany NY). 2019;11(2):303–327.
   Google Scholar
• Lu AT, Seeboth A, Tsai P-C, et al. DNA methylation-based estimator of telomere length. Aging (Albany NY). 2019;11(16):5895–5923.
   Google Scholar
• Wang Q, Zhan Y, Pedersen NL, et al. Telomere length and all-cause mortality: a meta-analysis. Ageing Res Rev. 2018;48:11–20.
   Google Scholar
• Smith BH, Campbell A, Linksted P, et al. Cohort profile: generation Scotland: Scottish family health study (GS:SFHS). The study, its participants and their potential for genetic research on health and illness. Int J Epidemiol. 2013;42(3):689–700.
   Google Scholar
• Leon DA, Lawlor DA, Clark H, et al. Cohort profile: the Aberdeen children of the 1950s study. Int J Epidemiol. 2006;35(3):549–552.
   Google Scholar
• Ayorinde AA, Wilde K, Lemon J, et al. Data resource profile: the aberdeen maternity and neonatal databank (AMND). Int J Epidemiol. 2016;45(2):389–394.
   Google Scholar
• Libby G, Smith A, F McEwan N, Chien P, Greene S, Forsyth S, et al. The Walker Project: A longitudinal study of 48 000 children born 1952-1966 (aged 36-50 years in 2002) and their families. Paediatric and perinatal epidemiology. 2004;18(8):302–12
   Google Scholar
• Ndc.scot.nhs.uk. ISD Scotland | information services division. 2018 [cited Nov 22]. Available from: http://www.ndc.scot.nhs.uk/Dictionary-A-Z/index.asp.
   Google Scholar
• Cairns BJ, Liu B, Clennell S, et al. Lifetime body size and reproductive factors: comparisons of data recorded prospectively with self reports in middle age. BMC Med Res Methodol. 2011;11(1):7.
   Google Scholar
• Team RC. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2018. Available from: https://www.R-project.org/
   Google Scholar
• Norris T, Seaton SE, Manktelow BN, et al. Updated birth weight centiles for England and Wales. Arch Dis Childhood-Fetal Neonatal Ed. 2018;103(6):F577–F82.
   Google Scholar
• McCartney DL, Stevenson AJ, Walker RM, et al. Investigating the relationship between DNA methylation age acceleration and risk factors for Alzheimer’s disease. Alzheimer’s Dementia Diagnosis Assess Dis Monit. 2018;10:429–437.
   Google Scholar
• Bermingham ML, Walker RM, Marioni RE, et al. Identification of novel differentially methylated sites with potential as clinical predictors of impaired respiratory function and COPD. bioRxiv. 2018;473629.
   Google Scholar
• Saffari A, Silver MJ, Zavattari P, et al. Estimation of a significance threshold for epigenome-wide association studies. Genet Epidemiol. 2018;42(1):20–33.
   Google Scholar
• World Health Organization. Preterm birth [Fact Sheet]. 2018.
   Google Scholar
• Martinson ML, Reichman NE. Socioeconomic inequalities in low birth weight in the United States, the United Kingdom, Canada, and Australia. Am J Public Health. 2016;106(4):748–754.
   Google Scholar
• Lam LL, Emberly E, Fraser HB, et al. Factors underlying variable DNA methylation in a human community cohort. Proc Nat Acad Sci. 2012;109(Supplement 2):17253–17260.
   Google Scholar
• Curhan GC, Chertow GM, Willett WC, et al. Birth weight and adult hypertension and obesity in women. Circulation. 1996;94(6):1310–1315.
   Google Scholar
• Dick KJ, Nelson CP, Tsaprouni L, et al. DNA methylation and body-mass index: a genome-wide analysis. Lancet. 2014;383(9933):1990–1998.
   Google Scholar
• Karlsson Linnér R, Marioni RE, Rietveld CA, et al. An epigenome-wide association study meta-analysis of educational attainment. Mol Psychiatry. 2017;22(12):1680–1690.
   Google Scholar
• McCartney DL, Hillary RF, Stevenson AJ, et al. Epigenetic prediction of complex traits and death. Genome Biol. 2018;19(1):136.
   Google Scholar
• Richards M, Hardy R, Kuh D, et al. Birthweight, postnatal growth and cognitive function in a national UK birth cohort. Int J Epidemiol. 2002;31(2):342–348.
   Google Scholar
• Chen C-P, Chen L-F, Yang S-R, et al. Functional characterization of the human placental fusogenic membrane protein syncytin 21. Biol Reprod. 2008;79(5):815–823.
   Google Scholar
• Charpentier Marta S, Christine Kathleen S, Amin Nirav M, et al. CASZ1 promotes vascular assembly and morphogenesis through the direct regulation of an EGFL7/RhoA-mediated pathway. Dev Cell. 2013;25(2):132–143.
   Google Scholar
• Merid SK, Novoloaca A, Sharp GC, et al. Epigenome-wide meta-analysis of blood DNA methylation in newborns and children identifies numerous loci related to gestational age. Genome Med. 2020;12(1):25.
   Google Scholar
• Kato N, Takeuchi F, Tabara Y, et al. Meta-analysis of genome-wide association studies identifies common variants associated with blood pressure variation in east Asians. Nat Genet. 2011;43(6):530–U57.
   Google Scholar
• Ehret GB, Ferreira T, Chasman DI, et al. The genetics of blood pressure regulation and its target organs from association studies in 342,415 individuals. Nat Genet. 2016;48(10):1171–1184.
   Google Scholar
• Roselli C, Chaffin MD, Weng LC, et al. Multi-ethnic genome-wide association study for atrial fibrillation. Nat Genet. 2018;50(9):1225-+.
   Google Scholar
• Malik R, Chauhan G, Traylor M, et al. Multiancestry genome-wide association study of 520,000 subjects identifies 32 loci associated with stroke and stroke subtypes. Nat Genet. 2018;50(4):524-+.
   Google Scholar
• Ross KM, Carroll JE, Horvath S, et al. Epigenetic age and pregnancy outcomes: grimAge acceleration is associated with shorter gestational length and lower birthweight. Clin Epigenetics. 2020;12(1):120.
   Google Scholar