Research Paper|Volume 11, Issue 7|pp 2045—2070

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

Giovanni Fiorito^1,⁴⁰, Cathal McCrory^2,⁴⁰, Oliver Robinson^3,⁴⁰, Cristian Carmeli^4,⁴⁰, Carolina Ochoa-Rosales^5,^6,⁴⁰, Yan Zhang^7,⁴⁰, Elena Colicino^8,⁴⁰, Pierre-Antoine Dugué^9,^10,^11,⁴⁰, Fanny Artaud^12,⁴⁰, Gareth J McKay^13,⁴⁰, Ayoung Jeong^14,^15,⁴⁰, Pashupati P Mishra^16,⁴⁰, Therese H Nøst^17,^18,⁴⁰, Vittorio Krogh¹⁹, Salvatore Panico²⁰, Carlotta Sacerdote²¹, Rosario Tumino²², Domenico Palli²³, Giuseppe Matullo^1,²⁴, Simonetta Guarrera^1,²⁴, Martina Gandini²⁵, Murielle Bochud⁴, Emmanouil Dermitzakis⁴, Taulant Muka^5,²⁶, Joel Schwartz²⁷, Pantel S Vokonas²⁸, Allan Just⁸, Allison M Hodge^9,¹⁰, Graham G Giles^9,^10,¹¹, Melissa C Southey^9,^11,²⁹, Mikko A Hurme³⁰, Ian Young¹³, Amy Jayne McKnight¹³, Sonja Kunze^31,³², Melanie Waldenberger^31,^32,³³, Annette Peters^31,^32,^33,³⁴, Lars Schwettmann^35,^36,⁴¹, Eiliv Lund^17,⁴¹, Andrea Baccarelli^37,⁴¹, Roger L Milne^9,^10,^11,⁴¹, Rose A Kenny^2,⁴¹, Alexis Elbaz^12,⁴¹, Hermann Brenner^7,^38,⁴¹, Frank Kee^13,⁴¹, Trudy Voortman^5,⁴¹, Nicole Probst-Hensch^14,^15,⁴¹, Terho Lehtimäki^16,⁴¹, Paul Elliot^3,⁴¹, Silvia Stringhini^4,^39,⁴¹, Paolo Vineis^3,⁴¹, Silvia Polidoro^1,⁴¹, the BIOS Consortium, the Lifepath consortium⁴²

¹Italian Institute for Genomic Medicine (IIGM), Turin, Italy
²The Irish Longitudinal Study on Ageing, Trinity College Dublin, Dublin, Ireland
³MRC-PHE Centre for Environment and Health, Imperial College London, London, UK
⁴Institute of Social and Preventive Medicine, Lausanne University Hospital (CHUV), Lausanne, Switzerland
⁵Department of Epidemiology, Erasmus University Medical Center, Rotterdam, the Netherlands
⁶Centro de Vida Saludable de la Universidad de Concepción, Concepción, Chile
⁷Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
⁸Icahn School of Medicine, Mount Sinai, New York, NY 10029, USA
⁹Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
¹⁰Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Victoria, Australia
¹¹Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
¹²CESP, Faculté de Médecine - Université Paris-Sud, Faculté de Médecine, UVSQ, Institut National de la Santé et de la Recherche Médicale, -, Université Paris, Saclay, France
¹³Centre for Public Health, Queen’s University Belfast, Belfast, Northern Ireland
¹⁴Swiss Tropical and Public Health Institute, Basel, Switzerland
¹⁵University of Basel, Basel, Switzerland
¹⁶Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center - Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33520, Finland
¹⁷Department of Community Medicine, Faculty of Health Sciences, UiT-The Arctic University of Norway, Tromsø, Norway
¹⁸NILU Norwegian Institute for Air Research, The Fram Centre, Tromsø, Norway
¹⁹Fondazione IRCCS - Istituto Nazionale dei Tumori, Milan, Italy
²⁰Department of Clinical Medicine and Surgery, University of Naples Federico II, Naples, Italy
²¹Piedmont Reference Centre for Epidemiology and Cancer Prevention (CPO Piemonte), Turin, Italy
²²Cancer Registry and Histopathology Department, 'Civic - M. P. Arezzo' Hospital, ASP Ragusa, Ragusa, Italy
²³Istituto per lo Studio, la Prevenzione e la Rete Oncologica (ISPRO Toscana), Florence, Italy
²⁴Department of Medical Sciences, University of Torino, Torino, Italy
²⁵Environmental Epidemiological Unit, Regional Environmental Protection Agency, Piedmont Region, Torino, Italy
²⁶Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
²⁷Department of Environmental Health and Department of Epidemiology, Harvard T.H. School of Public Health, Boston, MA 02115, USA
²⁸Department of Epidemiology, Boston University School of Public Health, Boston, MA 02115, USA
²⁹Department of Clinical Pathology, The University of Melbourne, Melbourne, Australia
³⁰Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, Tampere, 33014, Finland
³¹Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
³²Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
³³German Center for Cardiovascular Research (DZHK), Munich, Germany
³⁴Ludwig-Maximilians-Universität München, Munich, Germany
³⁵Institute of Health Economics and Health Care Management, Helmholtz Zentrum München, German Research Center for Environmental Health (GmbH), Neuherberg, D-85764, Germany
³⁶Department of Economics, Martin Luther University Halle-Wittenberg, Halle, Germany
³⁷Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY 10032, USA
³⁸Network Aging Research, University of Heidelberg, Heidelberg, Germany
³⁹Unit of Population Epidemiology, Primary Care Division, Geneva University Hospitals, Geneva, Switzerland
⁴⁰Equal contribution
⁴¹Equal senior researcher
⁴²See ACKNOWLEDGMENTS AND FUNDING

Received: November 16, 2018Accepted: March 31, 2019Published: April 14, 2019

https://doi.org/10.18632/aging.101900

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.