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      The role of adolescent lifestyle habits in biological aging: A prospective twin study

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          Abstract

          Background:

          Adolescence is a stage of fast growth and development. Exposures during puberty can have long-term effects on health in later life. This study aims to investigate the role of adolescent lifestyle in biological aging.

          Methods:

          The study participants originated from the longitudinal FinnTwin12 study (n = 5114). Adolescent lifestyle-related factors, including body mass index (BMI), leisure-time physical activity, smoking, and alcohol use, were based on self-reports and measured at ages 12, 14, and 17 years. For a subsample, blood-based DNA methylation (DNAm) was used to assess biological aging with six epigenetic aging measures in young adulthood (21–25 years, n = 824). A latent class analysis was conducted to identify patterns of lifestyle behaviors in adolescence, and differences between the subgroups in later biological aging were studied. Genetic and environmental influences on biological aging shared with lifestyle behavior patterns were estimated using quantitative genetic modeling.

          Results:

          We identified five subgroups of participants with different adolescent lifestyle behavior patterns. When DNAm GrimAge, DunedinPoAm, and DunedinPACE estimators were used, the class with the unhealthiest lifestyle and the class of participants with high BMI were biologically older than the classes with healthier lifestyle habits. The differences in lifestyle-related factors were maintained into young adulthood. Most of the variation in biological aging shared with adolescent lifestyle was explained by common genetic factors.

          Conclusions:

          These findings suggest that an unhealthy lifestyle during pubertal years is associated with accelerated biological aging in young adulthood. Genetic pleiotropy may largely explain the observed associations.

          Funding:

          This work was supported by the Academy of Finland (213506, 265240, 263278, 312073 to J.K., 297908 to M.O. and 341750, 346509 to E.S.), EC FP5 GenomEUtwin (J.K.), National Institutes of Health/National Heart, Lung, and Blood Institute (grant HL104125), EC MC ITN Project EPITRAIN (J.K. and M.O.), the University of Helsinki Research Funds (M.O.), Sigrid Juselius Foundation (J.K. and M.O.), Yrjö Jahnsson Foundation (6868), Juho Vainio Foundation (E.S.) and Päivikki and Sakari Sohlberg foundation (E.S.).

          eLife digest

          For most animals, events that occur early in life can have a lasting impact on individuals’ health. In humans, adolescence is a particularly vulnerable time when rapid growth and development collide with growing independence and experimentation. An unhealthy lifestyle during this period of rapid cell growth can contribute to later health problems like heart disease, lung disease, and premature death. This is due partly to accelerated biological aging, where the body deteriorates faster than what would be expected for an individual’s chronological age.

          One way to track the effects of lifestyle on biological aging is by measuring epigenetic changes. Epigenetic changes consist on adding or removing chemical ‘tags’ on genes. These tags can switch the genes on or off without changing their sequences. Scientists can measure certain epigenetic changes by measuring the levels of methylated DNA – DNA with a chemical ‘tag’ known as a methyl group – in blood samples. Several algorithms – known as ‘epigenetic clocks’ – are available that estimate how fast an individual is aging biologically based on DNA methylation.

          Kankaanpää et al. show that unhealthy lifestyles during adolescence may lead to accelerated aging in early adulthood. For their analysis, Kankaanpää et al. used data on the levels of DNA methylation in blood samples from 824 twins between 21 and 25 years old. The twins were participants in the FinnTwin12 study and had completed a survey about their lifestyles at ages 12, 14, and 17.

          Kankaanpää et al. classified individuals into five groups depending on their lifestyles. The first three groups, which included most of the twins, contained individuals that led relatively healthy lives. The fourth group contained individuals with a higher body mass index based on their height and weight. Finally, the last group included individuals with unhealthy lifestyles who binge drank, smoked and did not exercise.

          After estimating the biological ages for all of the participants, Kankaanpää et al. found that both the individuals with higher body mass indices and those in the group with unhealthy lifestyles aged faster than those who reported healthier lifestyles. However, the results varied depending on which epigenetic clock Kankaanpää et al. used to measure biological aging: clocks that had been developed earlier showed fewer differences in aging between groups; while newer clocks consistently found that individuals in the higher body mass index and unhealthy groups were older. Kankaanpää et al. also showed that shared genetic factors explained both unhealthy lifestyles and accelerated biological aging.

          The experiments performed by Kankaanpää et al. provide new insights into the vital role of an individual’s genetics in unhealthy lifestyles and cellular aging. These insights might help scientists identify at risk individuals early in life and try to prevent accelerated aging.

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          Most cited references65

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          Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives

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            The Hallmarks of Aging

            Aging is characterized by a progressive loss of physiological integrity, leading to impaired function and increased vulnerability to death. This deterioration is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular disorders, and neurodegenerative diseases. Aging research has experienced an unprecedented advance over recent years, particularly with the discovery that the rate of aging is controlled, at least to some extent, by genetic pathways and biochemical processes conserved in evolution. This Review enumerates nine tentative hallmarks that represent common denominators of aging in different organisms, with special emphasis on mammalian aging. These hallmarks are: genomic instability, telomere attrition, epigenetic alterations, loss of proteostasis, deregulated nutrient sensing, mitochondrial dysfunction, cellular senescence, stem cell exhaustion, and altered intercellular communication. A major challenge is to dissect the interconnectedness between the candidate hallmarks and their relative contributions to aging, with the final goal of identifying pharmaceutical targets to improve human health during aging, with minimal side effects. Copyright © 2013 Elsevier Inc. All rights reserved.
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              DNA methylation age of human tissues and cell types

              Background It is not yet known whether DNA methylation levels can be used to accurately predict age across a broad spectrum of human tissues and cell types, nor whether the resulting age prediction is a biologically meaningful measure. Results I developed a multi-tissue predictor of age that allows one to estimate the DNA methylation age of most tissues and cell types. The predictor, which is freely available, was developed using 8,000 samples from 82 Illumina DNA methylation array datasets, encompassing 51 healthy tissues and cell types. I found that DNA methylation age has the following properties: first, it is close to zero for embryonic and induced pluripotent stem cells; second, it correlates with cell passage number; third, it gives rise to a highly heritable measure of age acceleration; and, fourth, it is applicable to chimpanzee tissues. Analysis of 6,000 cancer samples from 32 datasets showed that all of the considered 20 cancer types exhibit significant age acceleration, with an average of 36 years. Low age-acceleration of cancer tissue is associated with a high number of somatic mutations and TP53 mutations, while mutations in steroid receptors greatly accelerate DNA methylation age in breast cancer. Finally, I characterize the 353 CpG sites that together form an aging clock in terms of chromatin states and tissue variance. Conclusions I propose that DNA methylation age measures the cumulative effect of an epigenetic maintenance system. This novel epigenetic clock can be used to address a host of questions in developmental biology, cancer and aging research.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                08 November 2022
                2022
                : 11
                : e80729
                Affiliations
                [1 ] Gerontology Research Center (GEREC), Faculty of Sport and Health Sciences, University of Jyväskylä ( https://ror.org/05n3dz165) Jyväskylä Finland
                [2 ] Methodology Center for Human Sciences, University of Jyväskylä ( https://ror.org/05n3dz165) Jyväskylä Finland
                [3 ] Institute for Molecular Medicine Finland (FIMM), HiLife, University of Helsinki ( https://ror.org/040af2s02) Helsinki Finland
                Max Planck Institute for Biology of Ageing ( https://ror.org/04xx1tc24) Germany
                McGill University ( https://ror.org/01pxwe438) Canada
                Max Planck Institute for Biology of Ageing ( https://ror.org/04xx1tc24) Germany
                Max Planck Institute for Biology of Ageing ( https://ror.org/04xx1tc24) Germany
                VU Amsterdam ( https://ror.org/008xxew50) Netherlands
                University of Bath ( https://ror.org/002h8g185) United Kingdom
                Author information
                https://orcid.org/0000-0002-6973-5385
                https://orcid.org/0000-0001-6430-8897
                https://orcid.org/0000-0001-5770-6475
                https://orcid.org/0000-0002-3716-2455
                https://orcid.org/0000-0003-3661-7400
                https://orcid.org/0000-0001-6375-959X
                Article
                80729
                10.7554/eLife.80729
                9642990
                36345722
                82244b46-04fc-4d24-8126-32dd54a7e385
                © 2022, Kankaanpää et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 01 June 2022
                : 01 October 2022
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 213506
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 297908
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 341750
                Award Recipient :
                Funded by: EC FP5 GenomEUtwin;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100000002, National Institutes of Health;
                Award ID: HL104125
                Award Recipient :
                Funded by: EC MC ITN Project EPITRAIN;
                Award Recipient :
                Funded by: University of Helsinki Research Funds;
                Award Recipient :
                Funded by: Sigrid Juselius Foundation;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/100010114, Yrjö Jahnsson Foundation;
                Award ID: 6868
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100004037, Juho Vainio Foundation;
                Award Recipient :
                Funded by: Päivikki and Sakari Sohlberg foundation;
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 312073
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 263278
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 265240
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100002341, Academy of Finland;
                Award ID: 346509
                Award Recipient :
                The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Epidemiology and Global Health
                Custom metadata
                Unhealthy lifestyle habits in adolescence associate with accelerated biological aging in young adulthood, but shared genetic factors underlying both lifestyle and biological aging may largely explain the observed associations.

                Life sciences
                dna methylation,adolescence,lifestyle,biological age,epigenetic aging,pace of aging,lifespan
                Life sciences
                dna methylation, adolescence, lifestyle, biological age, epigenetic aging, pace of aging, lifespan

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