Childhood adversity, accelerated GrimAge, and associated health consequences.
Childhood adversity
Childhood trauma
Epigenetic aging
GrimAge
Health outcomes
Journal
Journal of behavioral medicine
ISSN: 1573-3521
Titre abrégé: J Behav Med
Pays: United States
ID NLM: 7807105
Informations de publication
Date de publication:
18 May 2024
18 May 2024
Historique:
received:
14
08
2023
accepted:
01
05
2024
medline:
19
5
2024
pubmed:
19
5
2024
entrez:
18
5
2024
Statut:
aheadofprint
Résumé
Childhood adversity is linked to psychological, behavioral, and physical health problems, including obesity and cardiometabolic disease. Epigenetic alterations are one pathway through which the effects of early life stress and adversity might persist into adulthood. Epigenetic mechanisms have also been proposed to explain why cardiometabolic health can vary greatly between individuals with similar Body Mass Index (BMIs). We evaluated two independent cross-sectional cohorts of adults without known medical illness, one of which explicitly recruited individuals with early life stress (ELS) and control participants (n = 195), and the other a general community sample (n = 477). In these cohorts, we examine associations between childhood adversity, epigenetic aging, and metabolic health. Childhood adversity was associated with increased GrimAge Acceleration (GAA) in both cohorts, both utilizing a dichotomous yes/no classification (both p < 0.01) as well as a continuous measure using the Childhood Trauma Questionnaire (CTQ) (both p < 0.05). Further investigation demonstrated that CTQ subscales for physical and sexual abuse (both p < 0.05) were associated with increased GAA in both cohorts, whereas physical and emotional neglect were not. In both cohorts, higher CTQ was also associated with higher BMI and increased insulin resistance (both p < 0.05). Finally, we demonstrate a moderating effect of BMI on the relationship between GAA and insulin resistance where GAA correlated with insulin resistance specifically at higher BMIs. These results, which were largely replicated between two independent cohorts, suggest that interactions between epigenetics, obesity, and metabolic health may be important mechanisms through which childhood adversity contributes to long-term physical and metabolic health effects.
Identifiants
pubmed: 38762606
doi: 10.1007/s10865-024-00496-0
pii: 10.1007/s10865-024-00496-0
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : NIMH NIH HHS
ID : MH101107
Pays : United States
Organisme : NIMH NIH HHS
ID : T32MH019961
Pays : United States
Organisme : NIMH NIH HHS
ID : R25MH071584
Pays : United States
Organisme : NIMH NIH HHS
ID : MH101076
Pays : United States
Organisme : NIMH NIH HHS
ID : K23MH122587
Pays : United States
Organisme : NIDCR NIH HHS
ID : UL1-DE019586
Pays : United States
Organisme : NIDA NIH HHS
ID : PL1-DA024859
Pays : United States
Organisme : NIDA NIH HHS
ID : R01DA047063
Pays : United States
Organisme : NIDA NIH HHS
ID : R01DA054116
Pays : United States
Organisme : NIAAA NIH HHS
ID : R01-AA013892
Pays : United States
Organisme : NCATS NIH HHS
ID : UL1-TR001863
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20GM139767
Pays : United States
Organisme : NIGMS NIH HHS
ID : P20GM139743
Pays : United States
Organisme : Eunice Kennedy Shriver National Institute of Child Health and Human Development
ID : R01HD086487
Organisme : Eunice Kennedy Shriver National Institute of Child Health and Human Development
ID : HD101392
Informations de copyright
© 2024. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.
Références
Adam, T. C., & Epel, E. S. (2007). Stress, eating and the reward system. Physiology and Behavior, 91, 449–458.
pubmed: 17543357
doi: 10.1016/j.physbeh.2007.04.011
American Psychiatric, A.,& American Psychiatric, A., (2000) Task Force on D-I. Diagnostic and statistical manual of mental disorders : DSM-IV-TR. Washington, DC: American Psychiatric Association.
Andrade, S., Morais, T., Sandovici, I., Seabra, A. L., Constância, M., & Monteiro, M. P. (2021). Adipose tissue epigenetic profile in obesity-related dysglycemia - A systematic review. Front Endocrinol (lausanne), 12, 681649.
pubmed: 34290669
doi: 10.3389/fendo.2021.681649
Baker, M. (2016). 1,500 scientists lift the lid on reproducibility. Nature, 533, 452–454.
pubmed: 27225100
doi: 10.1038/533452a
Bell, C. G., Lowe, R., Adams, P. D., et al. (2019). DNA methylation aging clocks: Challenges and recommendations. Genome Biology, 20, 249.
pubmed: 31767039
pmcid: 6876109
doi: 10.1186/s13059-019-1824-y
Bellis, M. A., Hughes, K., Ford, K., Ramos Rodriguez, G., Sethi, D., & Passmore, J. (2019). Life course health consequences and associated annual costs of adverse childhood experiences across Europe and North America: A systematic review and meta-analysis. Lancet Public Health, 4, e517–e528.
pubmed: 31492648
pmcid: 7098477
doi: 10.1016/S2468-2667(19)30145-8
Bernstein, D. P., Stein, J. A., Newcomb, M. D., et al. (2003). Development and validation of a brief screening version of the childhood trauma questionnaire. Child Abuse and Neglect, 27, 169–190.
pubmed: 12615092
doi: 10.1016/S0145-2134(02)00541-0
Bifulco, A., Brown, G. W., & Harris, T. O. (1994). Childhood Experience of care and abuse (CECA): A retrospective interview measure. Journal of Child Psychology and Psychiatry., 35, 1419–1435.
pubmed: 7868637
doi: 10.1111/j.1469-7610.1994.tb01284.x
Bifulco, A., Brown, G. W., Lillie, A., & Jarvis, J. (1997). Memories of childhood neglect and abuse: Corroboration in a series of sisters. Journal of Child Psychology and Psychiatry., 38, 365–374.
pubmed: 9232482
doi: 10.1111/j.1469-7610.1997.tb01520.x
Block, J. P., He, Y., Zaslavsky, A. M., Ding, L., & Ayanian, J. Z. (2009). Psychosocial stress and change in weight among US adults. American Journal of Epidemiology, 170, 181–192.
pubmed: 19465744
pmcid: 2727271
doi: 10.1093/aje/kwp104
Boison, D. (2017). New insights into the mechanisms of the ketogenic diet. Current Opinion in Neurology, 30, 187–192.
pubmed: 28141738
pmcid: 5409832
doi: 10.1097/WCO.0000000000000432
Bray, G. A., Heisel, W. E., Afshin, A., et al. (2018). The science of obesity management: An endocrine society scientific statement. Endocrine Reviews, 39, 79–132.
pubmed: 29518206
pmcid: 5888222
doi: 10.1210/er.2017-00253
Bremne, J. D., & Vermetten, E. (2001). Stress and development: Behavioral and biological consequences. Development and Psychopathology, 13, 473–489.
pubmed: 11523844
doi: 10.1017/S0954579401003042
Camhi, S. M., Whitney Evans, E., Hayman, L. L., Lichtenstein, A. H., & Must, A. (2015). Healthy eating index and metabolically healthy obesity in U.S. adolescents and adults. Preventive Medicine, 77, 23–27.
pubmed: 25937589
doi: 10.1016/j.ypmed.2015.04.023
Cao-Lei, L., Dancause, K. N., Elgbeili, G., et al. (2015). DNA methylation mediates the impact of exposure to prenatal maternal stress on BMI and central adiposity in children at age 13½ years: Project Ice Storm. Epigenetics, 10, 749–761.
pubmed: 26098974
pmcid: 4623010
doi: 10.1080/15592294.2015.1063771
Chandraratne, N. K., Fernando, A. D., & Gunawardena, N. (2018). Physical, sexual and emotional abuse during childhood: Experiences of a sample of Sri Lankan young adults. Child Abuse and Neglect, 81, 214–224.
pubmed: 29753201
doi: 10.1016/j.chiabu.2018.05.004
Chao, A. M., Jastreboff, A. M., White, M. A., Grilo, C. M., & Sinha, R. (2017). Stress, cortisol, and other appetite-related hormones: Prospective prediction of 6-months changes in food cravings and weight. Obesity (silver Spring), 25, 713–720.
pubmed: 28349668
doi: 10.1002/oby.21790
Chen, M. A., LeRoy, A. S., Majd, M., et al. (2021). Immune and epigenetic pathways linking childhood adversity and health across the lifespan. Frontiers in Psychology, 12, 788351.
pubmed: 34899540
pmcid: 8662704
doi: 10.3389/fpsyg.2021.788351
Chen, X. Y., Lo, C. K. M., Chan, K. L., Leung, W. C., & Ip, P. (2022). Association between childhood exposure to family violence and telomere length: A meta-analysis. International Journal of Environmental Research and Public Health, 19, 12151.
pubmed: 36231453
pmcid: 9566190
doi: 10.3390/ijerph191912151
Colich, N. L., Rosen, M. L., Williams, E. S., & McLaughlin, K. A. (2020). Biological aging in childhood and adolescence following experiences of threat and deprivation: A systematic review and meta-analysis. Psychological Bulletin, 146, 721–764.
pubmed: 32744840
pmcid: 7484378
doi: 10.1037/bul0000270
Copeland, W. E., Shanahan, L., McGinnis, E. W., Aberg, K. A., & van den Oord, E. (2022). Early adversities accelerate epigenetic aging into adulthood: A 10-year, within-subject analysis. Journal of Child Psychology and Psychiatry, 63, 1308–1315.
pubmed: 35137412
doi: 10.1111/jcpp.13575
Cribb, L., Hodge, A. M., Yu, C., et al. (2022). Inflammation and epigenetic aging are largely independent markers of biological aging and mortality. Journals of Gerontology. Series a, Biological Sciences and Medical Sciences, 77, 2378–2386.
pubmed: 35926479
doi: 10.1093/gerona/glac147
Daigre, C., Rodríguez-Cintas, L., Tarifa, N., et al. (2015). History of sexual, emotional or physical abuse and psychiatric comorbidity in substance-dependent patients. Psychiatry Research, 229, 743–749.
pubmed: 26279128
doi: 10.1016/j.psychres.2015.08.008
Dallman, M. F., Pecoraro, N. C., & la Fleur, S. E. (2005). Chronic stress and comfort foods: Self-medication and abdominal obesity. Brain, Behavior, and Immunity, 19, 275–280.
pubmed: 15944067
doi: 10.1016/j.bbi.2004.11.004
Daniels, T. E., Mathis, K. J., Gobin, A. P., et al. (2023). Associations of early life stress with leptin and ghrelin in healthy young adults. Psychoneuroendocrinology, 149, 106007.
pubmed: 36577337
doi: 10.1016/j.psyneuen.2022.106007
Dayeh, T., Tuomi, T., Almgren, P., et al. (2016). DNA methylation of loci within ABCG1 and PHOSPHO1 in blood DNA is associated with future type 2 diabetes risk. Epigenetics, 11, 482–488.
pubmed: 27148772
pmcid: 4939923
doi: 10.1080/15592294.2016.1178418
Duffy, K. A., McLaughlin, K. A., & Green, P. A. (2018). Early life adversity and health-risk behaviors: Proposed psychological and neural mechanisms. Annals of the New York Academy of Sciences, 1428, 151–169.
pubmed: 30011075
pmcid: 6158062
doi: 10.1111/nyas.13928
Essex, M. J., Boyce, W. T., Hertzman, C., et al. (2013). Epigenetic vestiges of early developmental adversity: Childhood stress exposure and DNA methylation in adolescence. Child Development, 84, 58–75.
pubmed: 21883162
doi: 10.1111/j.1467-8624.2011.01641.x
Evans, G. W., Li, D., & Whipple, S. S. (2013). Cumulative risk and child development. Psychological Bulletin, 139, 1342–1396.
pubmed: 23566018
doi: 10.1037/a0031808
Fogelman, N., & Canli, T. (2019). Early life stress, physiology, and genetics: A review. Frontiers in Psychology, 10, 1668.
pubmed: 31428006
pmcid: 6688564
doi: 10.3389/fpsyg.2019.01668
Föhr, T., Waller, K., Viljanen, A., et al. (2021). Does the epigenetic clock GrimAge predict mortality independent of genetic influences: An 18 year follow-up study in older female twin pairs. Clinical Epigenetics, 13, 128.
pubmed: 34120642
doi: 10.1186/s13148-021-01112-7
Fumagalli, F., Molteni, R., Racagni, G., & Riva, M. A. (2007). Stress during development: Impact on neuroplasticity and relevance to psychopathology. Progress in Neurobiology, 81, 97–217.
doi: 10.1016/j.pneurobio.2007.01.002
Gayer-Anderson, C., Reininghaus, U., Paetzold, I., et al. (2020). A comparison between self-report and interviewer-rated retrospective reports of childhood abuse among individuals with first-episode psychosis and population-based controls. Journal of Psychiatric Research, 123, 145–150.
pubmed: 32065950
pmcid: 7054833
doi: 10.1016/j.jpsychires.2020.02.002
Gutiérrez-Repiso, C., Linares-Pineda, T. M., Gonzalez-Jimenez, A., et al. (2021). Epigenetic biomarkers of transition from metabolically healthy obesity to metabolically unhealthy obesity phenotype: A prospective study. International Journal of Molecular Sciences, 22, 10417.
pubmed: 34638758
pmcid: 8508854
doi: 10.3390/ijms221910417
Hamlat, E. J., Prather, A. A., Horvath, S., Belsky, J., & Epel, E. S. (2021). Early life adversity, pubertal timing, and epigenetic age acceleration in adulthood. Developmental Psychobiology, 63, 890–902.
pubmed: 33423276
pmcid: 8271092
doi: 10.1002/dev.22085
Hamlat, E. J., Neilands, T. B., Laraia, B., et al. (2023). Early life adversity predicts an accelerated cellular aging phenotype through early timing of puberty. Psychological Medicine, 53, 7720–7728.
pubmed: 37325994
doi: 10.1017/S0033291723001629
Han, L. K. M., Aghajani, M., Clark, S. L., et al. (2018). Epigenetic aging in major depressive disorder. American Journal of Psychiatry, 175, 774–782.
pubmed: 29656664
doi: 10.1176/appi.ajp.2018.17060595
Harvanek, Z. M., Fogelman, N., Xu, K., & Sinha, R. (2021). Psychological and biological resilience modulates the effects of stress on epigenetic aging. Translational Psychiatry, 11, 601.
pubmed: 34839356
pmcid: 8627511
doi: 10.1038/s41398-021-01735-7
Harvanek, Z. M., Boks, M. P., Vinkers, C. H., & Higgins-Chen, A. T. (2023). The cutting edge of epigenetic clocks: in search of mechanisms linking aging and mental health. Biological Psychiatry, 94, 694–705.
pubmed: 36764569
doi: 10.1016/j.biopsych.2023.02.001
Heim, C., Newport, D. J., Heit, S., et al. (2000). Pituitary-adrenal and autonomic responses to stress in women after sexual and physical abuse in childhood. JAMA, 284, 592–597.
pubmed: 10918705
doi: 10.1001/jama.284.5.592
Higgins-Chen, A. T., Thrush, K. L., Wang, Y., et al. (2022). A computational solution for bolstering reliability of epigenetic clocks: Implications for clinical trials and longitudinal tracking. Nature Aging, 2, 644–661.
pubmed: 36277076
pmcid: 9586209
doi: 10.1038/s43587-022-00248-2
Horvath, S. (2013). DNA methylation age of human tissues and cell types. Genome Biology, 14, R115.
pubmed: 24138928
pmcid: 4015143
doi: 10.1186/gb-2013-14-10-r115
Horvath, S., & Raj, K. (2018). DNA methylation-based biomarkers and the epigenetic clock theory of ageing. Nature Reviews Genetics, 19, 371–384.
pubmed: 29643443
doi: 10.1038/s41576-018-0004-3
Hostinar, C. E., Nusslock, R., & Miller, G. E. (2018). Future directions in the study of early-life stress and physical and emotional health: Implications of the neuroimmune network hypothesis. Journal of Clinical Child and Adolescent Psychology, 47, 142–156.
pubmed: 28107039
doi: 10.1080/15374416.2016.1266647
Houseman, E. A., Accomando, W. P., Koestler, D. C., et al. (2012). DNA methylation arrays as surrogate measures of cell mixture distribution. BMC Bioinformatics, 13, 86.
pubmed: 22568884
pmcid: 3532182
doi: 10.1186/1471-2105-13-86
Iacobini, C., Pugliese, G., Blasetti Fantauzzi, C., Federici, M., & Menini, S. (2019). Metabolically healthy versus metabolically unhealthy obesity. Metabolism, 92, 51–60.
pubmed: 30458177
doi: 10.1016/j.metabol.2018.11.009
Ikeda, Y., Suehiro, T., Nakamura, T., Kumon, Y., & Hashimoto, K. (2001). Clinical significance of the insulin resistance index as assessed by homeostasis model assessment. Endocrine Journal, 48, 81–86.
pubmed: 11403106
doi: 10.1507/endocrj.48.81
Joshi, D., Gonzalez, A., Lin, D., & Raina, P. (2023). The association between adverse childhood experiences and epigenetic age acceleration in the Canadian longitudinal study on aging (CLSA). Aging Cell, 22, e13779.
pubmed: 36650913
pmcid: 9924940
doi: 10.1111/acel.13779
Jung, J., McCartney, D. L., Wagner, J., et al. (2023). Additive effects of stress and alcohol exposure on accelerated epigenetic aging in alcohol use disorder. Biological Psychiatry, 93, 331–341.
pubmed: 36182531
doi: 10.1016/j.biopsych.2022.06.036
Jylhävä, J., Pedersen, N. L., & Hägg, S. (2017). Biological Age Predictors. eBioMedicine, 21, 29–36.
pubmed: 28396265
pmcid: 5514388
doi: 10.1016/j.ebiom.2017.03.046
Kalinowski, J., Huang, Y., Rivas, M. A., et al. (2022). Stress overload and dna methylation in african american women in the intergenerational impact of genetic and psychological factors on blood pressure study. Epigenet Insights., 15, 25168657221126310.
pubmed: 36246163
pmcid: 9554129
doi: 10.1177/25168657221126314
Kho, M., Wang, Y. Z., Chaar, D., et al. (2021). Accelerated DNA methylation age and medication use among African Americans. Aging (albany NY)., 13, 14604–14629.
pubmed: 34083497
pmcid: 8221348
doi: 10.18632/aging.203115
Kim, K., Joyce, B. T., Zheng, Y., et al. (2021). DNA methylation GrimAge and incident diabetes: the coronary artery risk development in young adults (CARDIA) study. Diabetes, 70, 1404–1413.
pubmed: 33820761
pmcid: 8275890
doi: 10.2337/db20-1167
Klopack, E. T., Crimmins, E. M., Cole, S. W., Seeman, T. E., & Carroll, J. E. (2022). Accelerated epigenetic aging mediates link between adverse childhood experiences and depressive symptoms in older adults: Results from the health and retirement study. SSM Popul Health., 17, 101071.
pubmed: 35313610
pmcid: 8933834
doi: 10.1016/j.ssmph.2022.101071
Leachman, J. R., Rea, M. D., Cohn, D. M., Xu, X., Fondufe-Mittendorf, Y. N., & Loria, A. S. (2020). Exacerbated obesogenic response in female mice exposed to early life stress is linked to fat depot-specific upregulation of leptin protein expression. American Journal of Physiology Endocrinology and Metabolism, 319, E852–E862.
pubmed: 32830551
pmcid: 7790118
doi: 10.1152/ajpendo.00243.2020
Li, Z., He, Y., Wang, D., Tang, J., & Chen, X. (2017). Association between childhood trauma and accelerated telomere erosion in adulthood: A meta-analytic study. Journal of Psychiatric Research, 93, 64–71.
pubmed: 28601667
doi: 10.1016/j.jpsychires.2017.06.002
Li, M., Bao, L., Zhu, P., & Wang, S. (2022). Effect of metformin on the epigenetic age of peripheral blood in patients with diabetes mellitus. Frontiers in Genetics, 13, 955835.
pubmed: 36226195
pmcid: 9548538
doi: 10.3389/fgene.2022.955835
Liang, X., Sinha, R., Justice, A. C., Cohen, M. H., Aouizerat, B. E., & Xu, K. (2022). A new monocyte epigenetic clock reveals nonlinear effects of alcohol consumption on biological aging in three independent cohorts (N = 2242). Alcoholism, Clinical and Experimental Research, 46, 736–748.
pubmed: 35257385
pmcid: 9117474
doi: 10.1111/acer.14803
Ling, C., & Rönn, T. (2019). Epigenetics in human obesity and type 2 diabetes. Cell Metabolism, 29, 1028–1044.
pubmed: 30982733
pmcid: 6509280
doi: 10.1016/j.cmet.2019.03.009
Lu, A. T., Quach, A., Wilson, J. G., et al. (2019). DNA methylation GrimAge strongly predicts lifespan and healthspan. Aging (albany NY), 11, 303–327.
pubmed: 30669119
doi: 10.18632/aging.101684
Luo, A., Jung, J., Longley, M., et al. (2020). Epigenetic aging is accelerated in alcohol use disorder and regulated by genetic variation in APOL2. Neuropsychopharmacology, 45, 327–336.
pubmed: 31466081
doi: 10.1038/s41386-019-0500-y
MacDonald, K., Thomas, M. L., Sciolla, A. F., et al. (2016). Minimization of childhood maltreatment is common and consequential: results from a large, multinational sample using the childhood trauma questionnaire. PLoS ONE, 11, e0146058.
pubmed: 26815788
pmcid: 4729672
doi: 10.1371/journal.pone.0146058
Marini, S., Davis, K. A., Soare, T. W., et al. (2020). Adversity exposure during sensitive periods predicts accelerated epigenetic aging in children. Psychoneuroendocrinology, 113, 104484.
pubmed: 31918390
doi: 10.1016/j.psyneuen.2019.104484
Marquez, F. D., Risica, P. M., Mathis, K. J., Sullivan, A., Gobin, A. P., & Tyrka, A. R. (2021). Do measures of healthy eating differ in survivors of early adversity? Appetite, 162, 105180.
pubmed: 33684530
pmcid: 8058294
doi: 10.1016/j.appet.2021.105180
Matthews, D. R., Hosker, J. P., Rudenski, A. S., Naylor, B. A., Treacher, D. F., & Turner, R. C. (1985). Homeostasis model assessment: Insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia, 28, 412–419.
pubmed: 3899825
doi: 10.1007/BF00280883
McCrory, C., Fiorito, G., Hernandez, B., et al. (2021). GrimAge outperforms other epigenetic clocks in the prediction of age-related clinical phenotypes and all-cause mortality. Journals of Gerontology. Series a, Biological Sciences and Medical Sciences, 76, 741–749.
pubmed: 33211845
doi: 10.1093/gerona/glaa286
McCrory, C., Fiorito, G., O’Halloran, A. M., Polidoro, S., Vineis, P., & Kenny, R. A. (2022). Early life adversity and age acceleration at mid-life and older ages indexed using the next-generation GrimAge and pace of aging epigenetic clocks. Psychoneuroendocrinology, 137, 105643.
pubmed: 34999481
doi: 10.1016/j.psyneuen.2021.105643
McGee, S. L., & Hargreaves, M. (2020). Exercise adaptations: Molecular mechanisms and potential targets for therapeutic benefit. Nature Reviews. Endocrinology, 16, 495–505.
pubmed: 32632275
doi: 10.1038/s41574-020-0377-1
Merz, M. P., & Turner, J. D. (2021). Is early life adversity a trigger towards inflammageing? Experimental Gerontology., 150, 111377.
pubmed: 33905877
doi: 10.1016/j.exger.2021.111377
Moore, L. D., Le, T., & Fan, G. (2013). DNA methylation and its basic function. Neuropsychopharmacology, 38, 23–38.
pubmed: 22781841
doi: 10.1038/npp.2012.112
Moser, S., Martins, J., Czamara, D., Lange, J., Müller-Myhsok, B., & Erhardt, A. (2022). DNA-methylation dynamics across short-term, exposure-containing CBT in patients with panic disorder. Translational Psychiatry, 12, 46.
pubmed: 35105872
pmcid: 8807826
doi: 10.1038/s41398-022-01802-7
Murlasits, Z., Kupai, K., & Kneffel, Z. (2022). Role of physical activity and cardiorespiratory fitness in metabolically healthy obesity: A narrative review. BMJ Open Sport and Exercise Medicine, 8, e001458.
pubmed: 36484059
pmcid: 9723844
doi: 10.1136/bmjsem-2022-001458
Nilsson, P. M., Korduner, J., & Magnusson, M. (2020). Metabolically healthy obesity (MHO)-new research directions for personalised medicine in cardiovascular prevention. Current Hypertension Reports, 22, 18.
pubmed: 32067105
pmcid: 7026231
doi: 10.1007/s11906-020-1027-7
Oblak, L., van der Zaag, J., Higgins-Chen, A. T., Levine, M. E., & Boks, M. P. (2021). A systematic review of biological, social and environmental factors associated with epigenetic clock acceleration. Ageing Research Reviews, 69, 101348.
pubmed: 33930583
doi: 10.1016/j.arr.2021.101348
Pedroso, J. A. B., Ramos-Lobo, A. M., & Donato, J., Jr. (2019). SOCS3 as a future target to treat metabolic disorders. Hormones (athens, Greece), 18, 127–136.
pubmed: 30414080
doi: 10.1007/s42000-018-0078-5
Pidsley, R., Zotenko, E., Peters, T. J., et al. (2016). Critical evaluation of the Illumina MethylationEPIC BeadChip microarray for whole-genome DNA methylation profiling. Genome Biology, 17, 208.
pubmed: 27717381
pmcid: 5055731
doi: 10.1186/s13059-016-1066-1
Puterman, E., Lin, J., Blackburn, E., O’Donovan, A., Adler, N., & Epel, E. (2010). The power of exercise: Buffering the effect of chronic stress on telomere length. PLoS ONE, 5, e10837.
pubmed: 20520771
pmcid: 2877102
doi: 10.1371/journal.pone.0010837
Quach, A., Levine, M. E., Tanaka, T., et al. (2017). Epigenetic clock analysis of diet, exercise, education, and lifestyle factors. Aging (albany NY), 9, 419–446.
pubmed: 28198702
doi: 10.18632/aging.101168
R (2020): A Language and Environment for Statistical Computing [computer program]. R Foundation for Statistical Computing.
Rampersaud, R., Protsenko, E., Yang, R., et al. (2022). Dimensions of childhood adversity differentially affect biological aging in major depression. Translational Psychiatry, 12, 431.
pubmed: 36195591
pmcid: 9532396
doi: 10.1038/s41398-022-02198-0
Ridout, K. K., Levandowski, M., Ridout, S. J., et al. (2018). Early life adversity and telomere length: A meta-analysis. Molecular Psychiatry, 23, 858–871.
pubmed: 28322278
doi: 10.1038/mp.2017.26
Rohde, K., Keller, M., la Cour, P. L., Blüher, M., Kovacs, P., & Böttcher, Y. (2019). Genetics and epigenetics in obesity. Metabolism, 92, 37–50.
pubmed: 30399374
doi: 10.1016/j.metabol.2018.10.007
Samblas, M., Milagro, F. I., & Martínez, A. (2019). DNA methylation markers in obesity, metabolic syndrome, and weight loss. Epigenetics, 14, 421–444.
pubmed: 30915894
pmcid: 6557553
doi: 10.1080/15592294.2019.1595297
Schmitz, L. L., Duffie, E., Zhao, W., et al. (2023). Associations of early-life adversity with later-life epigenetic aging profiles in the multi-ethnic study of atherosclerosis. American Journal of Epidemiology, 192, 1991–2005.
pubmed: 37579321
doi: 10.1093/aje/kwad172
Sheehan, D. V., Lecrubier, Y., Sheehan, K. H., et al. (1998). The Mini-International Neuropsychiatric Interview (MINI): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry., 59, 22–33.
pubmed: 9881538
Shenk, C. E., Felt, J. M., Ram, N., et al. (2022). Cortisol trajectories measured prospectively across thirty years of female development following exposure to childhood sexual abuse: Moderation by epigenetic age acceleration at midlife. Psychoneuroendocrinology, 136, 105606.
pubmed: 34896740
doi: 10.1016/j.psyneuen.2021.105606
Sinha, R., & Jastreboff, A. M. (2013). Stress as a common risk factor for obesity and addiction. Biological Psychiatry, 73, 827–835.
pubmed: 23541000
pmcid: 3658316
doi: 10.1016/j.biopsych.2013.01.032
Stefan, N., Häring, H. U., Hu, F. B., & Schulze, M. B. (2013). Metabolically healthy obesity: Epidemiology, mechanisms, and clinical implications. The Lancet Diabetes and Endocrinology, 1, 152–162.
pubmed: 24622321
doi: 10.1016/S2213-8587(13)70062-7
Stevens, A. J., Rucklidge, J. J., & Kennedy, M. A. (2018). Epigenetics, nutrition and mental health. Is there a relationship? Nutritional Neuroscience, 21(9), 602–613.
pubmed: 28553986
doi: 10.1080/1028415X.2017.1331524
Suderman, M., Borghol, N., Pappas, J. J., et al. (2014). Childhood abuse is associated with methylation of multiple loci in adult DNA. BMC Medical Genomics, 7, 13.
pubmed: 24618023
pmcid: 4007631
doi: 10.1186/1755-8794-7-13
Torres, S. J., & Nowson, C. A. (2007). Relationship between stress, eating behavior, and obesity. Nutrition, 23, 887–894.
pubmed: 17869482
doi: 10.1016/j.nut.2007.08.008
Tracy, E. L., Tracy, C. T., Kim, J. J., Yang, R., & Kim, E. (2020). Cascading effects of childhood abuse on physical health issues in later adulthood through trait anxiety and poor daily sleep quality. Journal of Health Psychology, 26, 2342–2348.
pubmed: 32114830
doi: 10.1177/1359105320909876
Tsatsoulis, A., & Paschou, S. A. (2020). Metabolically healthy obesity: criteria, epidemiology, controversies, and consequences. Current Obesity Reports, 9, 109–120.
pubmed: 32301039
doi: 10.1007/s13679-020-00375-0
Turner, R. J., Wheaton, B., & Lloyd, D. A. (1995). The epidemiology of social stress. American Sociological Review, 60(1), 104–125.
doi: 10.2307/2096348
Tyrka, A. R., Ridout, K. K., & Parade, S. H. (2016). Childhood adversity and epigenetic regulation of glucocorticoid signaling genes: Associations in children and adults. Development and Psychopathology, 28, 1319–1331.
pubmed: 27691985
pmcid: 5330387
doi: 10.1017/S0954579416000870
van Dijk, S. J., Tellam, R. L., Morrison, J. L., Muhlhausler, B. S., & Molloy, P. L. (2015). Recent developments on the role of epigenetics in obesity and metabolic disease. Clinical Epigenetics, 7, 66.
pubmed: 27408648
pmcid: 4940755
doi: 10.1186/s13148-015-0101-5
Viola, T. W., Salum, G. A., Kluwe-Schiavon, B., Sanvicente-Vieira, B., Levandowski, M. L., & Grassi-Oliveira, R. (2016). The influence of geographical and economic factors in estimates of childhood abuse and neglect using the childhood trauma questionnaire: A worldwide meta-regression analysis. Child Abuse and Neglect, 51, 1–11.
pubmed: 26704298
doi: 10.1016/j.chiabu.2015.11.019
Walaszczyk, E., Luijten, M., Spijkerman, A. M. W., et al. (2018). DNA methylation markers associated with type 2 diabetes, fasting glucose and HbA(1c) levels: A systematic review and replication in a case-control sample of the Lifelines study. Diabetologia, 61, 354–368.
pubmed: 29164275
doi: 10.1007/s00125-017-4497-7
Wang, S. H., Chung, P. S., Lin, Y. P., et al. (2021). Metabolically healthy obesity and physical fitness in military males in the CHIEF study. Science and Reports, 11, 9088.
doi: 10.1038/s41598-021-88728-0
Wegman, H. L., & Stetler, C. (2009). A meta-analytic review of the effects of childhood abuse on medical outcomes in adulthood. Psychosomatic Medicine, 71, 805–812.
pubmed: 19779142
doi: 10.1097/PSY.0b013e3181bb2b46
Wiss, D. A., & Brewerton, T. D. (2020). Adverse childhood experiences and adult obesity: A systematic review of plausible mechanisms and meta-analysis of cross-sectional studies. Physiology and Behavior, 223, 112964.
pubmed: 32479804
doi: 10.1016/j.physbeh.2020.112964
Wolfe, D. A., & McGee, R. (1994). Dimensions of child maltreatment and their relationship to adolescent adjustment. Development and Psychopathology, 6, 165–181.
doi: 10.1017/S0954579400005939
Womersley, J. S., Nothling, J., Toikumo, S., et al. (2022). Childhood trauma, the stress response and metabolic syndrome: A focus on DNA methylation. European Journal of Neuroscience, 55, 2253–2296.
pubmed: 34169602
doi: 10.1111/ejn.15370
Xu, K., Zhang, X., Wang, Z., Hu, Y., & Sinha, R. (2018). Epigenome-wide association analysis revealed that SOCS3 methylation influences the effect of cumulative stress on obesity. Biological Psychology, 131, 63–71.
pubmed: 27826092
doi: 10.1016/j.biopsycho.2016.11.001
Zannas, A. S., Arloth, J., Carrillo-Roa, T., et al. (2015). Lifetime stress accelerates epigenetic aging in an urban, African American cohort: Relevance of glucocorticoid signaling. Genome Biology, 16, 266.
pubmed: 26673150
pmcid: 4699359
doi: 10.1186/s13059-015-0828-5