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Nguyen S, McEvoy LK, Espeland MA, Whitsel EA, Lu A, Horvath S, Manson JE, Rapp SR, Shadyab AH. Associations of Epigenetic Age Estimators With Cognitive Function Trajectories in the Women's Health Initiative Memory Study. Neurology 2024; 103:e209534. [PMID: 38857479 DOI: 10.1212/wnl.0000000000209534] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/12/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Epigenetic age estimators indicating faster/slower biological aging vs chronological age independently associate with several age-related outcomes; however, longitudinal associations with cognitive function are understudied. We examined associations of epigenetic age estimators with cognitive function measured annually. METHODS This longitudinal study consisted of older women enrolled in the Women's Health Initiative Memory Study with DNA methylation (DNAm) collected at baseline (1995-1998) from 3 ancillary studies and were followed up to 13 years. Global cognitive function was measured annually by Modified Mini-Mental State Examination (3MS; baseline-2007) and by modified Telephone Interview for Cognitive Status (TICS-m, 2008-2021). We calculated 5 epigenetic age estimators: extrinsic AgeAccel, intrinsic AgeAccel, AgeAccelPheno, AgeAccelGrim2, Dunedin Pace of Aging Calculated From the Epigenome (DunedinPACE), and AgeAccelGrim2 components (DNA-based plasma protein surrogates). We estimated longitudinal epigenetic age estimator-cognitive function associations using linear mixed-effects models containing age, education, race or ethnicity, and subsequently alcohol, smoking, body mass index, and comorbidities. We examined effect modification by APOE ε4 carriage. RESULTS A total of 795 participants were enrolled. The mean baseline age was 70.8 ± 4 years (10.7% Black, 3.9% Hispanic or Latina, 85.4% White), A 1-SD (0.12) increment in DunedinPACE associated with faster annual declines in TICS-m scores in minimally adjusted (β = -0.118, 95% CI -0.202 to -0.034; p = 0.0006) and fully adjusted (β = -0.123, 95% CI -0.211 to -0.036; p = 0.006) models. AgeAccelPheno associated with faster annual declines in TICS-m with minimal adjustment (β = -0.091, 95% CI -0.176 to -0.006; p = 0.035) but not with full adjustment. No other epigenetic age estimators associated with changes in 3MS or TICS-m. Higher values of DNAm-based surrogates of growth differentiation factor 15, beta-2 microglobulin, Cystatin C, tissue inhibitor metalloproteinase 1, and adrenomedullin associated with faster annual declines in 3MS and TICS-m. Higher DNAm log A1c associated with faster annual declines in TICS-m only. DunedinPACE associated with faster annual declines in 3MS among APOE ε4 carriers but not among noncarriers (p-interaction = 0.020). DISCUSSION Higher DunedinPACE associated with faster declines in TICS-m and 3MS scores among APOE ε4 carriers. DunedinPACE may help identify older women at risk of future cognitive decline. Limitations include the ancillary studies that collected epigenetic data not designed to study epigenetics and cognitive function. We examined epigenetic age estimators with global cognitive function and not specific cognitive domains. Findings may not generalize to men and more diverse populations.
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Affiliation(s)
- Steve Nguyen
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Linda K McEvoy
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Mark A Espeland
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Eric A Whitsel
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Ake Lu
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Steve Horvath
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Joann E Manson
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Stephen R Rapp
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
| | - Aladdin H Shadyab
- From the Division of Epidemiology (S.N., L.K.M., A.H.S.), Herbert Wertheim School of Public Health and Human Longevity Science, University of California San Diego, La Jolla; Kaiser Permanente Washington Health Research Institute (L.K.M.), Seattle, WA; Departments of Internal Medicine and Biostatistics and Data Science (M.A.E.), Wake Forest University School of Medicine, Winston-Salem, NC; Department of Epidemiology (E.A.W.), Gillings School of Global Public Health; Department of Medicine (E.A.W.), School of Medicine, University of North Carolina, Chapel Hill; Altos Labs (A.L., S.H.), San Diego, CA; Department of Epidemiology (S.H.), UCLA Fielding School of Public Health, Los Angeles, CA; Division of Preventive Medicine (J.E.M.), Brigham and Women's Hospital, Harvard Medical School, Boston, MA; Department of Psychiatry & Behavioral Medicine (S.R.R.), Wake Forest School of Medicine, Winston-Salem, NC; and Division of Geriatrics, Gerontology, and Palliative Care (A.H.S.), Department of Medicine, University of California, San Diego, La Jolla
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Chen J, Moubadder L, Clausing ES, Kezios KL, Conneely KN, Hüls A, Baccarelli A, Factor-Litvak P, Cirrillo P, Shelton RC, Link BG, Suglia SF. Associations of childhood, adolescence, and midlife cognitive function with DNA methylation age acceleration in midlife. Aging (Albany NY) 2024; 16:9350-9368. [PMID: 38874516 DOI: 10.18632/aging.205943] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2023] [Accepted: 04/25/2024] [Indexed: 06/15/2024]
Abstract
Prior studies showed increased age acceleration (AgeAccel) is associated with worse cognitive function among old adults. We examine the associations of childhood, adolescence and midlife cognition with AgeAccel based on DNA methylation (DNAm) in midlife. Data are from 359 participants who had cognition measured in childhood and adolescence in the Child Health and Development study, and had cognition, blood based DNAm measured during midlife in the Disparities study. Childhood cognition was measured by Raven's Progressive Matrices and Peabody Picture Vocabulary Test (PPVT). Adolescent cognition was measured only by PPVT. Midlife cognition included Wechsler Test of Adult Reading (WTAR), Verbal Fluency (VF), Digit Symbol (DS). AgeAccel measures including Horvath, Hannum, PhenoAge, GrimAge and DunedinPACE were calculated from DNAm. Linear regressions adjusted for potential confounders were utilized to examine the association between each cognitive measure in relation to each AgeAccel. There are no significant associations between childhood cognition and midlife AgeAccel. A 1-unit increase in adolescent PPVT, which measures crystalized intelligence, is associated with 0.048-year decrease of aging measured by GrimAge and this association is attenuated after adjustment for adult socioeconomic status. Midlife crystalized intelligence measure WTAR is negatively associated with PhenoAge and DunedinPACE, and midlife fluid intelligence measure (DS) is negatively associated with GrimAge, PhenoAge and DunedinPACE. AgeAccel is not associated with VF in midlife. In conclusion, our study showed the potential role of cognitive functions at younger ages in the process of biological aging. We also showed a potential relationship of both crystalized and fluid intelligence with aging acceleration.
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Affiliation(s)
- Junyu Chen
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Leah Moubadder
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Elizabeth S Clausing
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- School of Global Integrative Studies, University of Nebraska, Lincoln, NE 68508, USA
| | - Katrina L Kezios
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Karen N Conneely
- Department of Human Genetics, School of Medicine, Emory University, Atlanta, GA 30322, USA
| | - Anke Hüls
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
- Gangarosa Department of Environmental Health, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
| | - Andrea Baccarelli
- Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Pam Factor-Litvak
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Piera Cirrillo
- Child Health and Development Studies, Public Health Institute, Washington, DC 20024, USA
| | - Rachel C Shelton
- Department of Sociomedical Sciences, Mailman School of Public Health, Columbia University, New York, NY 10032, USA
| | - Bruce G Link
- Department of Sociology, University of California Riverside, Riverside, CA 92507, USA
| | - Shakira F Suglia
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA 30322, USA
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deSteiguer AJ, Raffington L, Sabhlok A, Tanksley P, Tucker-Drob EM, Harden KP. Stability of DNA-Methylation Profiles of Biological Aging in Children and Adolescents. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.30.564766. [PMID: 37961459 PMCID: PMC10635005 DOI: 10.1101/2023.10.30.564766] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background and Objectives Methylation profile scores (MPSs) index biological aging and aging-related disease in adults and are cross-sectionally associated with social determinants of health in childhood. MPSs thus provide an opportunity to trace how aging-related biology responds to environmental changes in early life. Information regarding the stability of MPSs in early life is currently lacking. Method We use longitudinal data from children and adolescents ages 8-18 (N = 428, M age = 12.15 years) from the Texas Twin Project. Participants contributed two waves of salivary DNA-methylation data (mean lag = 3.94 years), which were used to construct four MPSs reflecting multi-system physiological decline and mortality risk (PhenoAgeAccel and GrimAgeAccel), pace of biological aging (DunedinPACE), and cognitive function (Epigenetic-g). Furthermore, we exploit variation among participants in whether they were exposed to the COVID-19 pandemic during the course of study participation, in order to test how a historical period characterized by environmental disruption might affect children's aging-related MPSs. Results All MPSs showed moderate longitudinal stability (test-retest rs = 0.42, 0.44, 0.46, 0.51 for PhenoAgeAccel, GrimAgeAccel, and Epigenetic-g, and DunedinPACE, respectively). No differences in the stability of MPSs were apparent between those whose second assessment took place after the onset of the COVID-19 pandemic vs. those for whom both assessments took place prior to the pandemic. Conclusions Aging-related DNA-methylation patterns are less stable in childhood than has been previously observed in adulthood. Further developmental research on the methylome is necessary to understand which environmental perturbations in childhood impact trajectories of biological aging and when children are most sensitive to those impacts.
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Affiliation(s)
- Abby J. deSteiguer
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - Laurel Raffington
- Max Planck Research Group Biosocial – Biology, Social Disparities, and Development, Max Planck Institute for Human Development, Berlin, Germany
| | - Aditi Sabhlok
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
| | - Peter Tanksley
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - Elliot M. Tucker-Drob
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
| | - K. Paige Harden
- Department of Psychology, University of Texas at Austin, Austin, TX, USA
- Population Research Center, The University of Texas at Austin, Austin, TX, USA
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5
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Sugden K, Moffitt TE, Arpawong TE, Arseneault L, Belsky DW, Corcoran DL, Crimmins EM, Hannon E, Houts R, Mill JS, Poulton R, Ramrakha S, Wertz J, Williams BS, Caspi A. Cross-National and Cross-Generational Evidence That Educational Attainment May Slow the Pace of Aging in European-Descent Individuals. J Gerontol B Psychol Sci Soc Sci 2023; 78:1375-1385. [PMID: 37058531 PMCID: PMC10394986 DOI: 10.1093/geronb/gbad056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Indexed: 04/15/2023] Open
Abstract
OBJECTIVES Individuals with more education are at lower risk of developing multiple, different age-related diseases than their less-educated peers. A reason for this might be that individuals with more education age slower. There are 2 complications in testing this hypothesis. First, there exists no definitive measure of biological aging. Second, shared genetic factors contribute toward both lower educational attainment and the development of age-related diseases. Here, we tested whether the protective effect of educational attainment was associated with the pace of aging after accounting for genetic factors. METHODS We examined data from 5 studies together totaling almost 17,000 individuals with European ancestry born in different countries during different historical periods, ranging in age from 16 to 98 years old. To assess the pace of aging, we used DunedinPACE, a DNA methylation algorithm that reflects an individual's rate of aging and predicts age-related decline and Alzheimer's disease and related disorders. To assess genetic factors related to education, we created a polygenic score based on the results of a genome-wide association study of educational attainment. RESULTS Across the 5 studies, and across the life span, higher educational attainment was associated with a slower pace of aging even after accounting for genetic factors (meta-analysis effect size = -0.20; 95% confidence interval [CI]: -0.30 to -0.10; p = .006). Further, this effect persisted after taking into account tobacco smoking (meta-analysis effect size = -0.13; 95% CI: -0.21 to -0.05; p = .01). DISCUSSION These results indicate that higher levels of education have positive effects on the pace of aging, and that the benefits can be realized irrespective of individuals' genetics.
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Affiliation(s)
- Karen Sugden
- Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
| | - Terrie E Moffitt
- Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Thalida Em Arpawong
- Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
| | - Louise Arseneault
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
| | - Daniel W Belsky
- Department of Epidemiology and Butler Columbia Aging Center, Columbia University Mailman School of Public Health, Columbia University, New York, New York, USA
| | - David L Corcoran
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Eileen M Crimmins
- Davis School of Gerontology, University of Southern California, Los Angeles, California, USA
| | - Eilis Hannon
- Complex Disease Epigenetics Group, University of Exeter Medical School, Exeter, UK
| | - Renate Houts
- Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
| | - Jonathan S Mill
- Complex Disease Epigenetics Group, University of Exeter Medical School, Exeter, UK
| | - Richie Poulton
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Sandhya Ramrakha
- Dunedin Multidisciplinary Health and Development Research Unit, Department of Psychology, University of Otago, Dunedin, New Zealand
| | - Jasmin Wertz
- Department of Psychology, School of Philosophy, Psychology & Language Sciences, University of Edinburgh, Edinburgh, UK
| | | | - Avshalom Caspi
- Psychology and Neuroscience, Duke University, Durham, North Carolina, USA
- Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, UK
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