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2. Cuidado e solidariedade: prática social e institucional

Author

Acary Souza Bulle Oliveira, Aderbal Magno Caminada Sabra, Alfredo Attié, Ana Carolina Brochado Teixeira, Ana Carolina Cubria, Ana Maria Iencarelli, Ana Sofia Carvalho, Andrea Viviana Taubman, Antônio Carlos Mathias Coltro, Antônio Luiz França De Lima, Arruda Alvim, Atahualpa Fernandez, Augusto Drummond Lepage, B

Published
2021

36. La tryptase médullaire, un nouveau critère diagnostique de l’atteinte systémique de la mastocytose : étude multicentrique prospective

Author

Bulai Livideanu, C., primary, Lepage, B., additional, Apoil, P.A., additional, Delabesse, E., additional, Freire Severino, M., additional, Laurent, C., additional, Evrard, S., additional, Tournier, E., additional, Degboé, Y., additional, Mailhol, C., additional, Jendoubi, F., additional, Polomat, K., additional, Rossignol, J., additional, Hermine, O., additional, Barete, S., additional, Beylot-Barry, M., additional, Damaj, G.L., additional, and Paul, C., additional

Published
2020
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39. PDB21 EVALUATION OF THE ONE-YEAR EFFICIENCY OF THE EDUC@DOM TELEMONITORING AND TELE-EDUCATION PROGRAM FOR TYPE 2 DIABETIC PATIENTS

Author

Mounié, M., primary, Costa, N., additional, Martini, J., additional, Latorre, C., additional, Buisson, J.C., additional, Delaunay, J., additional, Schirrbonnans, S., additional, Taoui, S., additional, Lepage, B., additional, Colineaux, H., additional, Gourdy, P., additional, Hanaire, H., additional, Molinier, L., additional, and Turnin, M.C., additional

Published
2020
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41. Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis

Author

Fiorito, G., Mccrory, C., Robinson, O., Carmeli, C., Rosales, C. O., Zhang, Y., Colicino, E., Dugue, P. -A., Artaud, F., Mckay, G. J., Jeong, A., Mishra, P. P., Nost, T. H., Krogh, V., Panico, S., Sacerdote, C., Tumino, R., Palli, D., Matullo, G., Guarrera, S., Gandini, M., Bochud, M., Dermitzakis, E., Muka, T., Schwartz, J., Vokonas, P. S., Just, A., Hodge, A. M., Giles, G. G., Southey, M. C., Hurme, M. A., Young, I., Mcknight, A. J., Kunze, S., Waldenberger, M., Peters, A., Schwettmann, L., Lund, E., Baccarelli, A., Milne, R. L., Kenny, R. A., Elbaz, A., Brenner, H., Kee, F., Voortman, T., Probst-Hensch, N., Lehtimaki, T., Elliot, P., Stringhini, S., Vineis, P., Polidoro, S., Alberts, J., Alenius, H., Avendano, M., Baltar, V., Bartley, M., Barros, H., Bellone, M., Berger, E., Blane, D., Candiani, G., Carra, L., Castagne, R., Chadeau-Hyam, M., Cima, S., Clavel-Chapelon, F., Costa, G., Courtin, E., Delpierre, C., D'Errico, A., Dermitzakis, M., Elovainio, M., Elliott, P., Fagherazzi, G., Fraga, S., Gares, V., Gerbouin-Rerolle, P., Giles, G., Goldberg, M., Greco, D., Guessous, I., Haba-Rubio, J., Heinzer, R., Hodge, A., Joost, S., Karimi, M., Kelly-Irving, M., Kahonen, M., Karisola, P., Khenissi, L., Kivimaki, M., Laine, J., Lang, T., Laurent, A., Layte, R., Lepage, B., Lorsch, D., Macguire, F., Machell, G., Mackenbach, J., Marmot, M., de Mestral, C., Miller, C., Milne, R., Muennig, P., Nusselder, W., Petrovic, D., Pilapil, L., Preisig, M., Pulkki-Raback, L., Raitakari, O., Ribeiro, A. I., Ricceri, F., Recalcati, P., Reinhard, E., Valverde, J. R., Saba, S., Santegoets, F., Satolli, R., Simmons, T., Severi, G., Shipley, M. J., Tabak, A., Terhi, V., Tieulent, J., Vaccarella, S., Vigna-Taglianti, F., Vollenweider, P., Vuilleumier, N., Zins, M., Medical Research Council (MRC), Commission of the European Communities, BIOS Consortium, Lifepath consortium, Epidemiology, Dermitzakis, Emmanouil, and Stringhini, Silvia

Subjects
Male, Aging, Geriatrics & Gerontology, Disease, epigenetic clocks, Bioinformatics, 0601 Biochemistry and Cell Biology, DISEASE, Epigenesis, Genetic, Cohort Studies, 0302 clinical medicine, Risk Factors, DNA METHYLATION, media_common, 0303 health sciences, education, Lifepath consortium, VDP::Medisinske Fag: 700::Helsefag: 800::Samfunnsmedisin, sosialmedisin: 801, CARDIOVASCULAR RISK, Aged, Aging/genetics, Aging/psychology, DNA Methylation, Educational Status, Female, Humans, Life Style, Mutation, Social Class, biological aging, socioeconomic position, Longevity, ASSOCIATION, Biological aging, Education, Epigenetic clocks, Socioeconomic position, 3. Good health, WIDE METHYLATION, Aging/genetics/psychology, DNA methylation, Biomarker (medicine), HEALTH, BIOS Consortium, Life Sciences & Biomedicine, Research Paper, Cohort study, VDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710::Medisinsk genetikk: 714, media_common.quotation_subject, CANCER-RISK, 610 Medicine & health, VDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710::Medical genetics: 714, Biology, PERIPHERAL-BLOOD, 03 medical and health sciences, SDG 3 - Good Health and Well-being, Genetic, 360 Social problems & social services, 1112 Oncology and Carcinogenesis, Epigenetics, ddc:613, 030304 developmental biology, Science & Technology, Mechanism (biology), MUTATIONS, dNaM, Socioeconomic Position, Biological Aging, Epigenetic Clocks, Cell Biology, 0606 Physiology, DRIFT, VDP::Medical disciplines: 700::Health sciences: 800::Community medicine, Social medicine: 801, 030217 neurology & neurosurgery, Epigenesis
Abstract

Source at https://doi.org/10.18632/aging.101900. Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life. We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries. The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect. Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Published
2019
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42. Special Report: The Biology of Inequalities in Health: The Lifepath Consortium

Author

Vineis, P. (Paolo), Avendano-Pabon, M. (Mauricio), Barros, H. (Henrique), Bartley, M. (Mel), Carmeli, C. (Cristian), Carra, L. (Luca), Chadeau-Hyam, M. (Marc), Costa, G. (Giuseppe), Delpierre, C. (Cyrille), D'Errico, A. (Angelo), Fraga, S. (Silvia), Giles, G. (Graham), Goldberg, M. (Marcel), Kelly-Irving, M. (Michelle), Kivimaki, M. (Mika), Lepage, B. (Benoit), Lang, T. (Thierry), Layte, R. (Richard), MacGuire, F. (Frances), Mackenbach, J.P. (Johan), Marmot, M. (Michael), McCrory, C. (Cathal), Milne, R.L. (Roger), Muennig, P. (Peter), Nusselder, W.J. (Wilma), Petrovic, D. (Dusan), Polidoro, S. (Silvia), Ricceri, F. (Fulvio), Robinson, O. (Oliver), Stringhini, S. (Silvia), Zins, M. (Marie), Vineis, P. (Paolo), Avendano-Pabon, M. (Mauricio), Barros, H. (Henrique), Bartley, M. (Mel), Carmeli, C. (Cristian), Carra, L. (Luca), Chadeau-Hyam, M. (Marc), Costa, G. (Giuseppe), Delpierre, C. (Cyrille), D'Errico, A. (Angelo), Fraga, S. (Silvia), Giles, G. (Graham), Goldberg, M. (Marcel), Kelly-Irving, M. (Michelle), Kivimaki, M. (Mika), Lepage, B. (Benoit), Lang, T. (Thierry), Layte, R. (Richard), MacGuire, F. (Frances), Mackenbach, J.P. (Johan), Marmot, M. (Michael), McCrory, C. (Cathal), Milne, R.L. (Roger), Muennig, P. (Peter), Nusselder, W.J. (Wilma), Petrovic, D. (Dusan), Polidoro, S. (Silvia), Ricceri, F. (Fulvio), Robinson, O. (Oliver), Stringhini, S. (Silvia), and Zins, M. (Marie)

Abstract

Funded by the European Commission Horizon 2020 programme, the Lifepath research consortium aimed to investigate the effects of socioeconomic inequalities on the biology of healthy aging. The main research questions included the impact of inequalities on health, the role of behavioral and other risk factors, the underlying biological mechanisms, the efficacy of selected policies, and the general implications of our findings for theories and policies. The project adopted a life-course and comparative approach, considering lifetime effects from childhood and adulthood, and pooled data on up to 1.7 million participants of longitudinal cohort studies from Europe, USA, and Australia. These data showed that socioeconomic circumstances predicted mortality and functional decline as strongly as established risk factors currently targeted by global prevention programmes. Analyses also lo

Published
2020
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43. Special Report: The Biology of Inequalities in Health: The Lifepath Consortium

Author

Vineis, P, Avendano-Pabon, M, Barros, H, Bartley, M, Carmeli, C, Carra, L, Chadeau-Hyam, M, Costa, G, Delpierre, C, D'Errico, A, Fraga, S, Giles, G, Goldberg, M, Kelly-Irving, M, Kivimaki, M, Lepage, B, Lang, T, Layte, R, MacGuire, F, Mackenbach, JP, Marmot, M, McCrory, C, Milne, RL, Muennig, P, Nusselder, W, Petrovic, D, Polidoro, S, Ricceri, F, Robinson, O, Stringhini, S, Zins, M, Vineis, P, Avendano-Pabon, M, Barros, H, Bartley, M, Carmeli, C, Carra, L, Chadeau-Hyam, M, Costa, G, Delpierre, C, D'Errico, A, Fraga, S, Giles, G, Goldberg, M, Kelly-Irving, M, Kivimaki, M, Lepage, B, Lang, T, Layte, R, MacGuire, F, Mackenbach, JP, Marmot, M, McCrory, C, Milne, RL, Muennig, P, Nusselder, W, Petrovic, D, Polidoro, S, Ricceri, F, Robinson, O, Stringhini, S, and Zins, M

Abstract

Funded by the European Commission Horizon 2020 programme, the Lifepath research consortium aimed to investigate the effects of socioeconomic inequalities on the biology of healthy aging. The main research questions included the impact of inequalities on health, the role of behavioral and other risk factors, the underlying biological mechanisms, the efficacy of selected policies, and the general implications of our findings for theories and policies. The project adopted a life-course and comparative approach, considering lifetime effects from childhood and adulthood, and pooled data on up to 1.7 million participants of longitudinal cohort studies from Europe, USA, and Australia. These data showed that socioeconomic circumstances predicted mortality and functional decline as strongly as established risk factors currently targeted by global prevention programmes. Analyses also looked at socioeconomically patterned biological markers, allostatic load, and DNA methylation using richly phenotyped cohorts, unraveling their association with aging processes across the life-course. Lifepath studies suggest that socioeconomic circumstances are embedded in our biology from the outset-i.e., disadvantage influences biological systems from molecules to organs. Our findings have important implications for policy, suggesting that (a) intervening on unfavorable socioeconomic conditions is complementary and as important as targeting well-known risk factors, such as tobacco and alcohol consumption, low fruit and vegetable intake, obesity and a sedentary lifestyle, and that (b) effects of preventive interventions in early life integrate interventions in adulthood. The report has an executive summary that refers to the different sections of the main paper.

Published
2020

44. Maternal educational inequalities in measured body mass index trajectories in three European countries

Author

Mccrory, C., Leahy, S., Ribeiro, A. I., Fraga, S., Barros, H., Avendano, M., Vineis, P., Layte, R., Alenius, H., Baglietto, L., Bartley, M., Bellone, M., Berger, E., Bochud, M., Candiani, G., Carmeli, C., Carra, L., Castagne, R., Chadeau-Hyam, M., Cima, S., Costa, G., Courtin, E., Delpierre, C., D'Errico, A., Donkin, A., Dugue, P. -A., Elliott, P., Fagherazzi, G., Fiorito, G., Gandini, Martina, Gares, V., Gerbouin-Rerrolle, P., Giles, G., Goldberg, M., Greco, D., Guida, F., Hodge, A., Karimi, M., Karisola, P., Kelly, M., Kivimaki, M., Laine, J., Lang, T., Laurent, A., Lepage, B., Lorsch, D., Machell, G., Mackenbach, J., Marmot, M., Milne, David Robert, Muennig, P., Nusselder, W., Petrovic, D., Polidoro, S., Preisig, M., Recalcati, P., Reinhard, E., Ricceri, F., Robinson, O., Jose, R., Severi, PAULA GABRIELA, Simmons, T., Stringhini, S., Terhi, V., Than, J., Vergnaud, A. -C., Vigna-Taglianti, F., Vollenweider, P., Zins, M., Epidemiology, Public Health, HRB, and ERC

Subjects
Male, Pediatric Obesity, obesity, Adolescent, Inequality, Epidemiology, body mass index, children, cohort study, growth curves, overweight, social inequalities, media_common.quotation_subject, Social gradient, Mothers, Prospective data, 03 medical and health sciences, 0302 clinical medicine, 030225 pediatrics, Prevalence, medicine, Humans, Social inequality, Prospective Studies, Child, media_common, 2. Zero hunger, 030219 obstetrics & reproductive medicine, Portugal, business.industry, 4. Education, Health Status Disparities, medicine.disease, Obesity, United Kingdom, Millennium Cohort Study (United States), Child, Preschool, Pediatrics, Perinatology and Child Health, Cohort, Educational Status, Female, business, Ireland, Body mass index, Demography
Abstract

BACKGROUND: Social inequalities in the prevalence of childhood overweight and obesity are well-established, but less is known about when the social gradient first emerges and how it evolves across childhood and adolescence.OBJECTIVE: This study examines maternal education differentials in children's body mass trajectories in infancy, childhood and adolescence using data from four contemporary European child cohorts.METHODS: Prospective data on children's body mass index (BMI) were obtained from four cohort studies-Generation XXI (G21-Portugal), Growing Up in Ireland (GUI) infant and child cohorts, and the Millennium Cohort Study (MCS-UK)-involving a total sample of 41,399 children and 120,140 observations. Children's BMI trajectories were modelled by maternal education level using mixed-effect models.RESULTS: Maternal educational inequalities in children's BMI were evident as early as three years of age. Children from lower maternal educational backgrounds were characterised by accelerated BMI growth, and the extent of the disparity was such that boys from primary-educated backgrounds measured 0.42 kg/m2 (95% CI 0.24, 0.60) heavier at 7 years of age in G21, 0.90 kg/m2 (95% CI 0.60, 1.19) heavier at 13 years of age in GUI and 0.75 kg/m2 (95% CI 0.52, 0.97) heavier in MCS at 14 years of age. The corresponding figures for girls were 0.71 kg/m2 (95% CI 0.50, 0.91), 1.31 kg/m2 (95% CI 1.00, 1.62) and 0.76 kg/m2 (95% CI 0.53, 1.00) in G21, GUI and MCS, respectively.CONCLUSIONS: Maternal education is a strong predictor of BMI across European nations. Socio-economic differentials emerge early and widen across childhood, highlighting the need for early intervention.

Published
2019
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48. Maternal educational inequalities in measured body mass index trajectories in three European countries

Author

McCrory, C, Leahy, S, Ribeiro, AI, Fraga, S, Barros, H, Avendano, M, Vineis, P, Layte, R, Alenius, H, Baglietto, L, Bartley, M, Bellone, M, Berger, E, Bochud, M, Candiani, G, Carmeli, C, Carra, L, Castagne, R, Chadeau-Hyam, M, Cima, S, Costa, G, Courtin, E, Delpierre, C, D'Errico, A, Donkin, A, Dugue, P-A, Elliott, P, Fagherazzi, G, Fiorito, G, Gandini, M, Gares, V, Gerbouin-Rerrolle, P, Giles, G, Goldberg, M, Greco, D, Guida, F, Hodge, A, Karimi, M, Karisola, P, Kelly, M, Kivimaki, M, Laine, J, Lang, T, Laurent, A, Lepage, B, Lorsch, D, Machell, G, Mackenbach, J, Marmot, M, Milne, R, Muennig, P, Nusselder, W, Petrovic, D, Polidoro, S, Preisig, M, Recalcati, P, Reinhard, E, Ricceri, F, Robinson, O, Valverde, JR, Severi, G, Simmons, T, Stringhini, S, Terhi, V, Than, J, Vergnaud, A-C, Vigna-Taglianti, F, Vollenweider, P, Zins, M, McCrory, C, Leahy, S, Ribeiro, AI, Fraga, S, Barros, H, Avendano, M, Vineis, P, Layte, R, Alenius, H, Baglietto, L, Bartley, M, Bellone, M, Berger, E, Bochud, M, Candiani, G, Carmeli, C, Carra, L, Castagne, R, Chadeau-Hyam, M, Cima, S, Costa, G, Courtin, E, Delpierre, C, D'Errico, A, Donkin, A, Dugue, P-A, Elliott, P, Fagherazzi, G, Fiorito, G, Gandini, M, Gares, V, Gerbouin-Rerrolle, P, Giles, G, Goldberg, M, Greco, D, Guida, F, Hodge, A, Karimi, M, Karisola, P, Kelly, M, Kivimaki, M, Laine, J, Lang, T, Laurent, A, Lepage, B, Lorsch, D, Machell, G, Mackenbach, J, Marmot, M, Milne, R, Muennig, P, Nusselder, W, Petrovic, D, Polidoro, S, Preisig, M, Recalcati, P, Reinhard, E, Ricceri, F, Robinson, O, Valverde, JR, Severi, G, Simmons, T, Stringhini, S, Terhi, V, Than, J, Vergnaud, A-C, Vigna-Taglianti, F, Vollenweider, P, and Zins, M

Abstract

BACKGROUND: Social inequalities in the prevalence of childhood overweight and obesity are well-established, but less is known about when the social gradient first emerges and how it evolves across childhood and adolescence. OBJECTIVE: This study examines maternal education differentials in children's body mass trajectories in infancy, childhood and adolescence using data from four contemporary European child cohorts. METHODS: Prospective data on children's body mass index (BMI) were obtained from four cohort studies-Generation XXI (G21-Portugal), Growing Up in Ireland (GUI) infant and child cohorts, and the Millennium Cohort Study (MCS-UK)-involving a total sample of 41,399 children and 120,140 observations. Children's BMI trajectories were modelled by maternal education level using mixed-effect models. RESULTS: Maternal educational inequalities in children's BMI were evident as early as three years of age. Children from lower maternal educational backgrounds were characterised by accelerated BMI growth, and the extent of the disparity was such that boys from primary-educated backgrounds measured 0.42 kg/m2 (95% CI 0.24, 0.60) heavier at 7 years of age in G21, 0.90 kg/m2 (95% CI 0.60, 1.19) heavier at 13 years of age in GUI and 0.75 kg/m2 (95% CI 0.52, 0.97) heavier in MCS at 14 years of age. The corresponding figures for girls were 0.71 kg/m2 (95% CI 0.50, 0.91), 1.31 kg/m2 (95% CI 1.00, 1.62) and 0.76 kg/m2 (95% CI 0.53, 1.00) in G21, GUI and MCS, respectively. CONCLUSIONS: Maternal education is a strong predictor of BMI across European nations. Socio-economic differentials emerge early and widen across childhood, highlighting the need for early intervention.

Published
2019

49. Socioeconomic position, lifestyle habits and biomarkers of epigenetic aging: a multi-cohort analysis

Author

Fiorito, G, McCrory, C, Robinson, O, Carmeli, C, Rosales, CO, Zhang, Y, Colicino, E, Dugue, P-A, Artaud, F, Mckay, GJ, Jeong, A, Mishra, PP, Nost, TH, Krogh, V, Panico, S, Sacerdote, C, Tumino, R, Palli, D, Matullo, G, Guarrera, S, Gandini, M, Bochud, M, Dermitzakis, E, Muka, T, Schwartz, J, Vokonas, PS, Just, A, Hodge, AM, Giles, GG, Southey, MC, Hurme, MA, Young, I, McKnight, AJ, Kunze, S, Waldenberger, M, Peters, A, Schwettmann, L, Lund, E, Baccarelli, A, Milne, RL, Kenny, RA, Elbaz, A, Brenner, H, Kee, F, Voortman, T, Probst-Hensch, N, Lehtimaki, T, Elliot, P, Stringhini, S, Vineis, P, Polidoro, S, Alberts, J, Alenius, H, Avendano, M, Baltar, V, Bartley, M, Barros, H, Bellone, M, Berger, E, Blane, D, Candiani, G, Carra, L, Castagne, R, Chadeau-Hyam, M, Cima, S, Clavel-Chapelon, F, Costa, G, Courtin, E, Delpierre, C, D'Errico, A, Manolis, Dermitzakis, Elovainio, M, Elliott, P, Fagherazzi, G, Fraga, S, Gares, V, Gerbouin-Rerolle, P, Giles, G, Goldberg, M, Greco, D, Guessous, I, Haba-Rubio, J, Heinzer, R, Hodge, A, Joost, S, Karimi, M, Kelly-Irving, M, Kahonen, M, Karisola, P, Khenissi, L, Kivimaki, M, Laine, J, Lang, T, Laurent, A, Layte, R, Lepage, B, Lorsch, D, MacGuire, F, Machell, G, Mackenbach, J, Marmot, M, de Mestral, C, Miller, C, Milne, R, Muennig, P, Nusselder, W, Petrovic, D, Lourdes, Pilapil, Preisig, M, Pulkki-Raback, L, Raitakari, O, Ribeiro, AI, Ricceri, F, Recalcati, P, Reinhard, E, Valverde, JR, Saba, S, Santegoets, F, Satolli, R, Simmons, T, Severi, G, Shipley, MJ, Tabak, A, Terhi, V, Tieulent, J, Vaccarella, S, Vigna-Taglianti, F, Vollenweider, P, Vuilleumier, N, Zins, M, Fiorito, G, McCrory, C, Robinson, O, Carmeli, C, Rosales, CO, Zhang, Y, Colicino, E, Dugue, P-A, Artaud, F, Mckay, GJ, Jeong, A, Mishra, PP, Nost, TH, Krogh, V, Panico, S, Sacerdote, C, Tumino, R, Palli, D, Matullo, G, Guarrera, S, Gandini, M, Bochud, M, Dermitzakis, E, Muka, T, Schwartz, J, Vokonas, PS, Just, A, Hodge, AM, Giles, GG, Southey, MC, Hurme, MA, Young, I, McKnight, AJ, Kunze, S, Waldenberger, M, Peters, A, Schwettmann, L, Lund, E, Baccarelli, A, Milne, RL, Kenny, RA, Elbaz, A, Brenner, H, Kee, F, Voortman, T, Probst-Hensch, N, Lehtimaki, T, Elliot, P, Stringhini, S, Vineis, P, Polidoro, S, Alberts, J, Alenius, H, Avendano, M, Baltar, V, Bartley, M, Barros, H, Bellone, M, Berger, E, Blane, D, Candiani, G, Carra, L, Castagne, R, Chadeau-Hyam, M, Cima, S, Clavel-Chapelon, F, Costa, G, Courtin, E, Delpierre, C, D'Errico, A, Manolis, Dermitzakis, Elovainio, M, Elliott, P, Fagherazzi, G, Fraga, S, Gares, V, Gerbouin-Rerolle, P, Giles, G, Goldberg, M, Greco, D, Guessous, I, Haba-Rubio, J, Heinzer, R, Hodge, A, Joost, S, Karimi, M, Kelly-Irving, M, Kahonen, M, Karisola, P, Khenissi, L, Kivimaki, M, Laine, J, Lang, T, Laurent, A, Layte, R, Lepage, B, Lorsch, D, MacGuire, F, Machell, G, Mackenbach, J, Marmot, M, de Mestral, C, Miller, C, Milne, R, Muennig, P, Nusselder, W, Petrovic, D, Lourdes, Pilapil, Preisig, M, Pulkki-Raback, L, Raitakari, O, Ribeiro, AI, Ricceri, F, Recalcati, P, Reinhard, E, Valverde, JR, Saba, S, Santegoets, F, Satolli, R, Simmons, T, Severi, G, Shipley, MJ, Tabak, A, Terhi, V, Tieulent, J, Vaccarella, S, Vigna-Taglianti, F, Vollenweider, P, Vuilleumier, N, and Zins, M

Abstract

Differences in health status by socioeconomic position (SEP) tend to be more evident at older ages, suggesting the involvement of a biological mechanism responsive to the accumulation of deleterious exposures across the lifespan. DNA methylation (DNAm) has been proposed as a biomarker of biological aging that conserves memory of endogenous and exogenous stress during life.We examined the association of education level, as an indicator of SEP, and lifestyle-related variables with four biomarkers of age-dependent DNAm dysregulation: the total number of stochastic epigenetic mutations (SEMs) and three epigenetic clocks (Horvath, Hannum and Levine), in 18 cohorts spanning 12 countries.The four biological aging biomarkers were associated with education and different sets of risk factors independently, and the magnitude of the effects differed depending on the biomarker and the predictor. On average, the effect of low education on epigenetic aging was comparable with those of other lifestyle-related risk factors (obesity, alcohol intake), with the exception of smoking, which had a significantly stronger effect.Our study shows that low education is an independent predictor of accelerated biological (epigenetic) aging and that epigenetic clocks appear to be good candidates for disentangling the biological pathways underlying social inequalities in healthy aging and longevity.

Published
2019

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