Age Acceleration; Epigenetic Age; DNA Methylation; ALSPAC; Social Class; Social Environment
Résumé :
[en] Pace of aging is an epigenetic clock which captures the speed at which someone is biologically aging compared to the chronological-age peers. We here use data from the Avon Longitudinal Study of Parents and Children (ALSPAC) to investigate the interrelation between the study children’s parental social class at birth, and their pace of aging and cognitive skills measures in childhood and adolescence. We show that children from lower parental social classes display faster pace of aging and that the social class gradient in pace of aging is strongest in adolescence. About one third of this association can be explained by other socio-economic and demographic covariates, as well as life events. Similarly, study children’s pace of aging manifests a negative association with their measures of cognitive skills in late adolescence only. This association becomes stronger as the contemporary pace of aging of the mother becomes faster. Our results seem to identify adolescence as the period of life when pace of aging, family environment and cognitive skills measures begin to interact.
Disciplines :
Domaines particuliers de l’économie (santé, travail, transport...)
Auteur, co-auteur :
Niccodemi, Gianmaria
Menta, Giorgia; Luxembourg Institute of Socio-Economic Research - LISER
Turner, Jonathan; Luxembourg Institute of Health - LIH
d'Ambrosio, Conchita ; University of Luxembourg > Faculty of Humanities, Education and Social Sciences (FHSE) > Department of Behavioural and Cognitive Sciences (DBCS)
Co-auteurs externes :
no
Langue du document :
Anglais
Titre :
Pace of aging, family environment and cognitive skills in children and adolescents
Date de publication/diffusion :
2022
Titre du périodique :
SSM - Population Health
eISSN :
2352-8273
Maison d'édition :
Elsevier, Royaume-Uni
Peer reviewed :
Peer reviewed vérifié par ORBi
Projet FnR :
FNR13650569 - Age Acceleration And The Life Course, 2019 (01/09/2020-31/08/2023) - Conchita D'ambrosio
Alessie, R.J., Angelini, V., van den Berg, G.J., Mierau, J.O., Viluma, L., Economic conditions at birth and cardiovascular disease risk in adulthood: Evidence from post-1950 cohorts. Social Science & Medicine 224 (2019), 77–84.
Austin, M.K., Chen, E., Ross, K.M., McEwen, L.M., Maclsaac, J.L., Kobor, M.S., Miller, G.E., Early-life socioeconomic disadvantage, not current, predicts accelerated epigenetic aging of monocytes. Psychoneuroendocrinology 97 (2018), 131–134.
Barfield, R.T., Almli, L.M., Kilaru, V., Smith, A.K., Mercer, K.B., Duncan, R., Conneely, K.N., Accounting for population stratification in DNA methylation studies. Genetic Epidemiology 38 (2014), 231–241.
Belsky, D.W., Caspi, A., Arseneault, L., Baccarelli, A., Corcoran, D.L., Gao, X., Hannon, E., Harrington, H.L., Rasmussen, L.J., Houts, R., et al. Quantification of the pace of biological aging in humans through a blood test, the DunedinPoAm DNA methylation algorithm. Elife, 9, 2020, e54870.
Björklund, A., Salvanes, K.G., Education and family background: Mechanisms and policies. Handbook of the economics of education, 3, 2011, 201–247.
Boyd, A., Golding, J., Macleod, J., Lawlor, D.A., Fraser, A., Henderson, J., Molloy, L., Ness, A., Ring, S., Davey Smith, G., Cohort profile: The ‘Children of the 90s’; the index offspring of the Avon longitudinal study of Parents and children (ALSPAC). International Journal of Epidemiology 42 (2013), 111–127.
Chow, J.C., Yen, Z., Ziesche, S.M., Brown, C.J., Silencing of the mammalian X chromosome. Annual Review of Genomics and Human Genetics 6 (2005), 69–92.
Clark, A.E., D'Ambrosio, C., Barazzetta, M., Childhood circumstances and young adulthood outcomes: The role of mothers' financial problems. Health Economics 30 (2021), 342–357.
Connelly, R., Gayle, V., Lambert, P.S., A review of occupation-based social classifications for social survey research. Methodological Innovations 9 (2016), 1–14.
Etzel, L., Hastings, W.J., Hall, M.A., Heim, C.M., Meaney, M.J., Noll, J.G., Shalev, I., Obesity and accelerated epigenetic aging in a high-risk cohort of children. Scientific Reports 12 (2022), 1–9.
Fiorito, G., Caini, S., Palli, D., Bendinelli, B., Saieva, C., Ermini, I., Masala, G., DNA methylation-based biomarkers of aging were slowed down in a two-year diet and physical activity intervention trial: The DAMA study. Aging Cell, 20, 2021, e13439.
Fraga, M.F., Ballestar, E., Paz, M.F., Ropero, S., Setien, F., Ballestar, M.L., Heine-Suñer, D., Cigudosa, J.C., Urioste, M., Benitez, J., et al. Epigenetic differences arise during the lifetime of monozygotic twins. Proceedings of the National Academy of Sciences 102 (2005), 10604–10609.
Fraser, A., Macdonald-Wallis, C., Tilling, K., Boyd, A., Golding, J., Davey Smith, G., Henderson, J., Macleod, J., Molloy, L., Ness, A., Ring, S., Nelson, S.M., Lawlor, D.A., The Avon longitudinal study of Parents and children: ALSPAC mothers cohort. International Journal of Epidemiology 42 (2013), 97–110.
Gelbach, J.B., When do covariates matter? And which ones, and how much?. Journal of Labor Economics 34 (2016), 509–543.
Goldin, C., A grand gender convergence: Its last chapter. The American Economic Review 104 (2014), 1091–1119.
Goldin, C., Katz, L., A most egalitarian profession: Pharmacy and the evolution of a family-friendly occupation. Journal of Labor Economics 34 (2016), 705–746.
Hannum, G., Guinney, J., Zhao, L., Zhang, L., Hughes, G., Sadda, S., Klotzle, B., Bibikova, M., Fan, J.-B., Gao, Y., et al. Genome-wide methylation profiles reveal quantitative views of human aging rates. Molecular Cell 49 (2013), 359–367.
Horvath, S., DNA methylation age of human tissues and cell types. Genome Biology 14 (2013), 1–20.
Horvath, S., Erhart, W., Brosch, M., Ammerpohl, O., von Schönfels, W., Ahrens, M., Heits, N., Bell, J.T., Tsai, P.-C., Spector, T.D., et al. Obesity accelerates epigenetic aging of human liver. Proceedings of the National Academy of Sciences 111 (2014), 15538–15543.
Hughes, A., Smart, M., Gorrie-Stone, T., Hannon, E., Mill, J., Bao, Y., Burrage, J., Schalkwyk, L., Kumari, M., Socioeconomic position and DNA methylation age acceleration across the lifecourse. American Journal of Epidemiology 187 (2018), 2346–2354.
Jovanovic, T., Vance, L.A., Cross, D., Knight, A.K., Kilaru, V., Michopoulos, V., Klengel, T., Smith, A.K., Exposure to violence accelerates epigenetic aging in children. Scientific Reports 7 (2017), 1–7.
Lawn, R.B., Anderson, E.L., Suderman, M., Simpkin, A.J., Gaunt, T.R., Teschendorff, A.E., Wid-schwendter, M., Hardy, R., Kuh, D., Relton, C.L., et al. Psychosocial adversity and socioeconomic position during childhood and epigenetic age: Analysis of two prospective cohort studies. Human Molecular Genetics 27 (2018), 1301–1308.
Levine, M.E., Lu, A.T., Quach, A., Chen, B.H., Assimes, T.L., Bandinelli, S., Hou, L., Baccarelli, A.A., Stewart, J.D., Li, Y., et al. An epigenetic biomarker of aging for lifespan and healthspan. Aging (Albany NY), 10, 2018, 573.
Marioni, R.E., Shah, S., McRae, A.F., Chen, B.H., Colicino, E., Harris, S.E., Gibson, J., Henders, A.K., Redmond, P., Cox, S.R., et al. DNA methylation age of blood predicts all-cause mortality in later life. Genome Biology 16 (2015), 1–12.
Marioni, R.E., Shah, S., McRae, A.F., Ritchie, S.J., Muniz-Terrera, G., Harris, S.E., Gibson, J., Redmond, P., Cox, S.R., Pattie, A., et al. The epigenetic clock is correlated with physical and cognitive fitness in the Lothian Birth Cohort 1936. International Journal of Epidemiology 44 (2015), 1388–1396.
McCrory, C., Fiorito, G., Cheallaigh, C.N., Polidoro, S., Karisola, P., Alenius, H., Layte, R., Seeman, T., Vineis, P., Kenny, R.A., How does socio-economic position (SEP) get biologically embedded? A comparison of allostatic load and the epigenetic clock(s). Psychoneuroendocrinology 104 (2019), 64–73.
Perna, L., Zhang, Y., Mons, U., Holleczek, B., Saum, K.-U., Brenner, H., Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort. Clinical Epigenetics 8 (2016), 1–7.
Quach, A., Levine, M.E., Tanaka, T., Lu, A.T., Chen, B.H., Ferrucci, L., Ritz, B., Bandinelli, S., Neuhouser, M.L., Beasley, J.M., et al. Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging, 9, 2017, 419.
Raffington, L., Belsky, D.W., Kothari, M., Malanchini, M., Tucker-Drob, E.M., Harden, K.P., Socioeconomic disadvantage and the pace of biological aging in children. Pediatrics, 147, 2021, e2020024406.
Raffington, L., Tanksley, P.T., Sabhlok, A., Vinnik, L., Mallard, T., King, L.S., Goosby, B., Harden, K.P., Tucker-Drob, E.M., Socially stratified epigenetic profiles are associated with cognitive functioning in children and adolescents. bioRxiv Working, 2021, 456979.
Relton, C.L., Gaunt, T., McArdle, W., Ho, K., Duggirala, A., Shihab, H., Davey Smith, G., Data resource profile: Accessible resource for integrated epigenomic studies (ARIES). International Journal of Epidemiology 44 (2015), 1181–1190.
Russ, T.C., Hannah, J., Batty, G.D., Booth, C.C., Deary, I.J., Starr, J.M., Childhood cognitive ability and incident dementia: The 1932 Scottish Mental Survey cohort into their tenth decade. Epidemiology, 28, 2017, 361.
Sado, T., Okano, M., Li, E., Sasaki, H., De novo DNA methylation is dispensable for the initiation and propagation of X chromosome inactivation. Development 131 (2004), 975–982.
Shuttleworth-Edwards, A.B., Kemp, R.D., Rust, A.L., Muirhead, J.G., Hartman, N.P., Radloff, S.E., Cross-cultural effects on IQ test performance: A review and preliminary normative indications on WAIS-III test performance. Journal of Clinical and Experimental Neuropsychology 26 (2004), 903–920.
Simpkin, A.J., Cooper, R., Howe, L.D., Relton, C.L., Smith, G.D., Teschendorff, A., Widschwendter, M., Wong, A., Kuh, D., Hardy, R., Are objective measures of physical capability related to accelerated epigenetic age? Findings from a British birth cohort. British Medical Journal Open, 7, 2017, e016708.
Sumner, J.A., Colich, N.L., Uddin, M., Armstrong, D., McLaughlin, K.A., Early experiences of threat, but not deprivation, are associated with accelerated biological aging in children and adolescents. Biological Psychiatry 85 (2019), 268–278.
Whalley, L.J., Deary, I.J., Longitudinal cohort study of childhood IQ and survival up to age 76. British Medical Journal, 322, 2001, 819.
Wolf, E.J., Maniates, H., Nugent, N., Maihofer, A.X., Armstrong, D., Ratanatharathorn, A., Ashley-Koch, A.E., Garrett, M., Kimbrel, N.A., Lori, A., et al. Traumatic stress and accelerated DNA methylation age: A meta-analysis. Psychoneuroendocrinology 92 (2018), 123–134.
Wong, C.C.Y., Caspi, A., Williams, B., Craig, I.W., Houts, R., Ambler, A., Moffitt, T.E., Mill, J., A longitudinal study of epigenetic variation in twins. Epigenetics 5 (2010), 516–526.
Yoeli, H., Macnaughton, J., McLusky, S., Menopausal symptoms and work: A narrative review of women's experiences in casual, informal, or precarious jobs. Maturitas 150 (2021), 14–21.
