Abstract
The relationship between cognitive performance, macro and microstructural brain anatomy and accelerated aging as measured by a highly accurate epigenetic biomarker of aging known as the epigenetic clock in healthy adolescents has not been studied. Healthy adolescents enrolled in the Cape Town Adolescent Antiretroviral Cohort Study were studied cross sectionally. The Illumina Infinium Methylation EPIC array was used to generate DNA methylation data from the blood samples of 44 adolescents aged 9 to 12 years old. The epigenetic clock software and method was used to estimate two measures, epigenetic age acceleration residual (AAR) and extrinsic epigenetic age acceleration (EEAA). Each participant underwent neurocognitive testing, T1 structural magnetic resonance imaging (MRI), and diffusion tensor imaging (DTI). Correlation tests were run between the two epigenetic aging measures and 10 cognitive functioning domains, to assess for differences in cognitive performance as epigenetic aging increases. In order to investigate the associations of epigenetic age acceleration on brain structure, we developed stepwise multiple regression models in R (version 3.4.3, 2017) including grey and white matter volumes, cortical thickness, and cortical surface area, as well as DTI measures of white matter microstructural integrity. In addition to negatively affecting two cognitive domains, visual memory (p = .026) and visual spatial acuity (p = .02), epigenetic age acceleration was associated with alterations of brain volumes, cortical thickness, cortical surface areas and abnormalities in neuronal microstructure in a range of regions. Stress was a significant predictor (p = .029) of AAR. Understanding the drivers of epigenetic age acceleration in adolescents could lead to valuable insights into the development of neurocognitive impairment in adolescents.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Armstrong NJ, Mather KA, Thalamuthu A, Wright MJ, Trollor JN, Ames D, Brodaty H, Schofield PR, Sachdev PS, Kwok JB (2017) Aging, exceptional longevity and comparisons of the Hannum and Horvath epigenetic clocks. Epigenomics 9:689–700. https://doi.org/10.2217/epi-2016-0179
Aryee MJ, Jaffe AE, Corrada-Bravo H, Ladd-Acosta C, Feinberg AP, Hansen KD, Irizarry RA (2014) Minfi: a flexible and comprehensive bioconductor package for the analysis of Infinium DNA methylation microarrays. Bioinformatics 30:1363–1369. https://doi.org/10.1093/bioinformatics/btu049
Benedict RHB, Schretlen D, Groninger L, Brandt J (1998) Hopkins verbal learning test ? Revised: normative data and analysis of inter-form and test-retest reliability. The Clinical Neuropsychologist (Neuropsychology, Development and Cognition: Section D) 12:43–55. https://doi.org/10.1076/clin.12.1.43.1726
Breitling LP, Saum K-U, Perna L, Schöttker B, Holleczek B, Brenner H (2016) Frailty is associated with the epigenetic clock but not with telomere length in a German cohort. Clin Epigenetics 8:1186. https://doi.org/10.1186/s13148-016-0186-5
Brenner LA, Penzenik M (2017) Center for Epidemiological Studies-Depression. In: Encyclopedia of clinical neuropsychology. Springer International Publishing, Cham, pp 1–3
Brooks BL, Sherman EMS, Strauss E (2009) NEPSY-II: a developmental neuropsychological assessment, second edition. Child Neuropsychology 16:80–101. https://doi.org/10.1080/09297040903146966
Bryden PJ, Roy EA (2005) Unimanual performance across the age span. Brain Cogn 57:26–29. https://doi.org/10.1016/j.bandc.2004.08.016
Chen BH, Marioni RE, Colicino E, Peters MJ, Ward-Caviness CK, Tsai PC, Roetker NS, Just AC, Demerath EW, Guan W, Bressler J, Fornage M, Studenski S, Vandiver AR, Moore AZ, Tanaka T, Kiel DP, Liang L, Vokonas P, Schwartz J, Lunetta KL, Murabito JM, Bandinelli S, Hernandez DG, Melzer D, Nalls M, Pilling LC, Price TR, Singleton AB, Gieger C, Holle R, Kretschmer A, Kronenberg F, Kunze S, Linseisen J, Meisinger C, Rathmann W, Waldenberger M, Visscher PM, Shah S, Wray NR, McRae AF, Franco OH, Hofman A, Uitterlinden AG, Absher D, Assimes T, Levine ME, Lu AT, Tsao PS, Hou L, Manson JAE, Carty CL, LaCroix AZ, Reiner AP, Spector TD, Feinberg AP, Levy D, Baccarelli A, van Meurs J, Bell JT, Peters A, Deary IJ, Pankow JS, Ferrucci L, Horvath S (2016) DNA methylation-based measures of biological age: meta-analysis predicting time to death. Aging (Albany NY) 8:1844–1865. https://doi.org/10.18632/aging.101020
Chouliaras L, Pishva E, Haapakoski R, Zsoldos E, Mahmood A, Filippini N, Burrage J, Mill J, Kivimäki M, Lunnon K, Ebmeier KP (2018) Peripheral DNA methylation, cognitive decline and brain aging: pilot findings from the Whitehall II imaging study. Epigenomics 10:585–595. https://doi.org/10.2217/epi-2017-0132
Christiansen L, Lenart A, Tan Q, Vaupel JW, Aviv A, McGue M, Christensen K (2015) DNA methylation age is associated with mortality in a longitudinal Danish twin study. Aging Cell 15:149–154. https://doi.org/10.1111/acel.12421
Cohen RA, Grieve S, Hoth KF, Paul RH, Sweet L, Tate D, Gunstad J, Stroud L, McCaffery J, Hitsman B, Niaura R, Clark CR, MacFarlane A, Bryant R, Gordon E, Williams LM (2006) Early life stress and morphometry of the adult anterior cingulate cortex and caudate nuclei. Biol Psychiatry 59:975–982. https://doi.org/10.1016/j.biopsych.2005.12.016
Dunning MJ, Barbosa-Morais NL, Lynch AG, Tavaré S, Ritchie ME (2008) Statistical issues in the analysis of Illumina data. BMC Bioinforma 9:85. https://doi.org/10.1186/1471-2105-9-85
Fagiolini M, Jensen CL, Champagne FA (2009) Epigenetic influences on brain development and plasticity. Curr Opin Neurobiol 19:207–212. https://doi.org/10.1016/j.conb.2009.05.009
Fischl B, Dale AM (2000) Measuring the thickness of the human cerebral cortex from magnetic resonance images. Proc Natl Acad Sci 97:11050–11055. https://doi.org/10.1073/pnas.200033797
Fischl B, Salat D, Kennedy D, Makris N, Albert M, Killiany R, Dale A (2001) Automatic segmentation of the structures in the human brain. Neuroimage 13:118. https://doi.org/10.1016/S1053-8119(01)91461-2
Fischl B, Salat DH, Busa E, Albert M, Dieterich M, Haselgrove C, van der Kouwe A, Killiany R, Kennedy D, Klaveness S, Montillo A, Makris N, Rosen B, Dale AM (2002) Whole brain segmentation: automated labeling of neuroanatomical structures in the human brain. Neuron 33:341–355
Gapp K, Woldemichael BT, Bohacek J, Mansuy IM (2014) Epigenetic regulation in neurodevelopment and neurodegenerative diseases. Neuroscience 264:99–111. https://doi.org/10.1016/j.neuroscience.2012.11.040
Garagnani P, Bacalini MG, Pirazzini C, Gori D, Giuliani C, Mari D, di Blasio AM, Gentilini D, Vitale G, Collino S, Rezzi S, Castellani G, Capri M, Salvioli S, Franceschi C (2012) Methylation of ELOVL2gene as a new epigenetic marker of age. Aging Cell 11:1132–1134. https://doi.org/10.1111/acel.12005
Garg E, Chen L, Nguyen TTT, Pokhvisneva I, Chen LM, Unternaehrer E, MacIsaac JL, McEwen LM, Mah SM, Gaudreau H, Levitan R, Moss E, Sokolowski MB, Kennedy JL, Steiner MS, Meaney MJ, Holbrook JD, Silveira PP, Karnani N, Kobor MS, O'Donnell KJ, Mavan Study Team (2018) The early care environment and DNA methylome variation in childhood. Dev Psychopathol 30:891–903. https://doi.org/10.1017/S0954579418000627
Hoare J, Phillips N, Joska JA, Paul R, Donald KA, Stein DJ, Thomas KGF (2016) Applying the HIV-associated neurocognitive disorder diagnostic criteria to HIV-infected youth. Neurology 87:86–93. https://doi.org/10.1212/WNL.0000000000002669
Hoare J, Fouche J-P, Phillips N, Joska JA, Myer L, Zar HJ, Stein DJ (2018) Structural brain changes in perinatally HIV infected young adolescents in South Africa AIDS 32:2707–2718. https://doi.org/10.1097/QAD.0000000000002024
Hoare J, Phillips N, Brittain K, Myer L, Zar HJ, Stein DJ (2019) Mental health and functional competence in the Cape Town adolescent antiretroviral cohort. J Acquir Immune Defic Syndr 81:e109–e116. https://doi.org/10.1097/QAI.0000000000002068
Horvath S (2013) DNA methylation age of human tissues and cell types. Genome Biol 14:R115. https://doi.org/10.1186/gb-2013-14-10-r115
Horvath S, Gurven M, Levine ME, Trumble BC, Kaplan H, Allayee H, Ritz BR, Chen B, Lu AT, Rickabaugh TM, Jamieson BD, Sun D, Li S, Chen W, Quintana-Murci L, Fagny M, Kobor MS, Tsao PS, Reiner AP, Edlefsen KL, Absher D, Assimes TL (2016) An epigenetic clock analysis of race/ethnicity, sex, and coronary heart disease. Genome Biol 17:171. https://doi.org/10.1186/s13059-016-1030-0
Horvath S, Phillips N, Heany SJ et al (2018) Perinatally acquired HIV infection accelerates epigenetic aging in South African adolescents. AIDS 32:1465–1474. https://doi.org/10.1097/QAD.0000000000001854
Jaenisch R, Bird A (2003) Epigenetic regulation of gene expression: how the genome integrates intrinsic and environmental signals. Nat Genet 33(Suppl):245–254. https://doi.org/10.1038/ng1089
Jensen SKG, Berens AE, Nelson CA 3rd (2017) Effects of poverty on interacting biological systems underlying child development. The Lancet Child & Adolescent Health 1:225–239. https://doi.org/10.1016/S2352-4642(17)30024-X
Kane AE, Sinclair DA (2019) Epigenetic changes during aging and their reprogramming potential. Critical reviews in biochemistry and molecular biology 54:61–83
Kieffer-Kristensen R, Teasdale TW, Bilenberg N (2011) Post-traumatic stress symptoms and psychological functioning in children of parents with acquired brain injury. Brain Inj 25:752–760. https://doi.org/10.3109/02699052.2011.579933
Kofink D, Boks MPM, Timmers HTM, Kas MJ (2013) Epigenetic dynamics in psychiatric disorders: environmental programming of neurodevelopmental processes. Neurosci Biobehav Rev 37:831–845. https://doi.org/10.1016/j.neubiorev.2013.03.020
Levine AJ, Quach A, Moore DJ, Achim CL, Soontornniyomkij V, Masliah E, Singer EJ, Gelman B, Nemanim N, Horvath S (2016) Accelerated epigenetic aging in brain is associated with pre-mortem HIV-associated neurocognitive disorders. J Neuro-Oncol 22:366–375. https://doi.org/10.1007/s13365-015-0406-3
Louw K-A, Ipser J, Phillips N, Hoare J (2016) Correlates of emotional and behavioural problems in children with perinatally acquired HIV in Cape Town, South Africa. AIDS Care:1–9. https://doi.org/10.1080/09540121.2016.1140892
Luby JL, Barch DM, Belden A, Gaffrey MS, Tillman R, Babb C, Nishino T, Suzuki H, Botteron KN (2012) Maternal support in early childhood predicts larger hippocampal volumes at school age. Proc Natl Acad Sci U S A 109:2854–2859. https://doi.org/10.1073/pnas.1118003109
Lupien SJ, McEwen BS, Gunnar MR, Heim C (2009) Effects of stress throughout the lifespan on the brain, behaviour and cognition. Nat Rev Neurosci 10:434–445. https://doi.org/10.1038/nrn2639
Micklesfield LK, Pedro TM, Kahn K, Kinsman J, Pettifor JM, Tollman S, Norris SA (2014) Physical activity and sedentary behavior among adolescents in rural South Africa: levels, patterns and correlates. BMC Public Health 14:1–10. https://doi.org/10.1186/1471-2458-14-40
Muñiz J, Elosua P, Hambleton RK, International Test Commission (2013) International test commission guidelines for test translation and adaptation: second edition. Psicothema 25:151–157
Osika W, Friberg P, Wahrborg P (2007) A new short self-rating questionnaire to assess stress in children. Int J Behav Med 14:108–117. https://doi.org/10.1007/BF03004176
Perna L, Zhang Y, Mons U, Holleczek B, Saum KU, Brenner H (2016) Epigenetic age acceleration predicts cancer, cardiovascular, and all-cause mortality in a German case cohort. Clin Epigenetics 8:6. https://doi.org/10.1186/s13148-016-0228-z
Phillips NJ, Hoare J, Stein DJ, Myer L, Zar HJ, Thomas KGF (2018) HIV-associated cognitive disorders in perinatally infected children and adolescents: a novel composite cognitive domains score. AIDS Care 30:1–9. https://doi.org/10.1080/09540121.2018.1466982
Plessis Du P, Reviews LCERA (2007) Children and poverty in South Africa: the right to social security
Rangasamy S, D’Mello SR, Narayanan V (2013) Epigenetics, autism spectrum, and neurodevelopmental disorders. Neurotherapeutics: the journal of the American Society for Experimental NeuroTherapeutics 10:742–756
Roth C (2011) Boston naming test. In: Encyclopedia of clinical neuropsychology. Springer New York, New York, pp 430–433
Roubroeks JAY, Smith RG, Hove DLA van den, Lunnon K (2017) Epigenetics and DNA methylomic profiling in Alzheimer’s disease and other neurodegenerative diseases. J Neurochem 143:158–170
Roy CA, Perry JC (2004) Instruments for the assessment of childhood trauma in adults. J Nerv Ment Dis 192:343–351. https://doi.org/10.1097/01.nmd.0000126701.23121.fa
Smigielski L, Jagannath V, Rössler W, Walitza S, Grünblatt E (2020) Epigenetic mechanisms in schizophrenia and other psychotic disorders: a systematic review of empirical human findings. Mol Psychiatry 12:357–31
Simmons RK, Stringfellow SA, Glover ME, Wagle AA, Clinton SM (2013) DNA methylation markers in the postnatal developing rat brain. Brain Res 1533:26–36. https://doi.org/10.1016/j.brainres.2013.08.005
Smith SM, Jenkinson M, Johansen-Berg H, Rueckert D, Nichols TE, Mackay CE, Watkins KE, Ciccarelli O, Cader MZ, Matthews PM, Behrens TEJ (2006) Tract-based spatial statistics: voxelwise analysis of multi-subject diffusion data. Neuroimage 31:1487–1505. https://doi.org/10.1016/j.neuroimage.2006.02.024
Steer RA, Kumar G, Beck JS, Beck AT (2016) Evidence for the construct validities of the Beck youth inventories with child psychiatric outpatients. Psychol Rep 89:559–565. https://doi.org/10.2466/pr0.2001.89.3.559
Triche TJ Jr, Weisenberger DJ, Van Den Berg D et al (2013) Low-level processing of Illumina Infinium DNA methylation BeadArrays. Nucleic Acids Res 41:e90–e90. https://doi.org/10.1093/nar/gkt090
Turecki G, Meaney MJ (2016) Effects of the social environment and stress on glucocorticoid receptor gene methylation: a systematic review. Biol Psychiatry 79:87–96. https://doi.org/10.1016/j.biopsych.2014.11.022
Urdinguio RG, Sanchez-Mut JV, Esteller M (2009) Epigenetic mechanisms in neurological diseases: genes, syndromes, and therapies. The Lancet. Neurology 8:1056–1072
Watanabe K, Ogino T, Nakano K, Hattori J, Kado Y, Sanada S, Ohtsuka Y (2005) The Rey-Osterrieth complex figure as a measure of executive function in childhood. Brain and Development 27:564–569. https://doi.org/10.1016/j.braindev.2005.02.007
Wechsler D (2003) Wechsler intelligence scale for children, fourth edition
Xu Z, Li H, Jin P (2012) Epigenetics-Based Therapeutics for Neurodegenerative Disorders. Current translational geriatrics and experimental gerontology reports 1:229–236
Funding
This study was funded primarily by R21MH107327-01 (AJL and JH).
Funding for CTAAC provided by R01-HD074051 (HJZ) and SA MRC.
HJZ and DJS are supported by the South African Medical Research Council.
Author information
Authors and Affiliations
Contributions
AJL, JH, DJS, and SH conceived of the study. AJL and JH are the PI’s of the R21 which primarily funded this study. HZ is PI of the CTAAC study, from which most of the data were derived. SJH and SE carried out the statistical analysis. JF extracted the brain imaging data. JH wrote the first draft of the article. The remaining authors conceived of and aided with the CTAAC study, including collection of the DNA samples and phenotypic data. All authors helped in the interpretation of the findings and the write up of the article.
Corresponding author
Ethics declarations
Conflict of interest
All authors: No reported conflicts.
Additional information
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Hoare, J., Stein, D.J., Heany, S.J. et al. Accelerated epigenetic aging in adolescents from low-income households is associated with altered development of brain structures. Metab Brain Dis 35, 1287–1298 (2020). https://doi.org/10.1007/s11011-020-00589-0
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11011-020-00589-0