Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Article
  • Published:

The effects of adverse life events on brain development in the ABCD study®: a propensity-weighted analysis

Molecular Psychiatry volume 30, pages 2463–2474 (2025)Cite this article

Subjects

Abstract

Longitudinal studies of the effects of adversity on human brain development are complicated by the association of stressful events with confounding variables. To counter this bias, we apply a propensity-weighted analysis of the first two years of The Adolescent Brain Cognitive DevelopmentSM (ABCD) Study® data, employing a machine learning analysis weighted by individuals’ propensity to experience adversity. Data included 338 resting-state functional connections from 7190 youth (46% female), divided into a training group (80%) and an independent testing group (20%). Propensity scores were computed using 390 variables to balance across two-year adverse life event exposures. Using elastic net regularization with and without inverse propensity weighting, we developed linear models in which changes in functional connectivity of brain connections during the two-year period served as predictors of the number of adverse events experienced during that same period. Haufe’s method was applied to forward-transform the backward prediction models. We also tested whether brain changes associated with adverse events correlated with concomitant changes in internalizing or externalizing behaviors or to academic achievement. In the propensity-weighted analysis, brain development significantly predicted the number of adverse events experienced during that period in both the training group (ρ = 0.14, p < 0.001) and the independent testing group (ρ = 0.10, p < 0.001). The predictor indicated a general pattern of decreased functional connectivity between large-scale networks and subcortical brain regions, particularly for cingulo-opercular and sensorimotor networks. These network-to-subcortical functional connectivity decreases inversely associated with the development of internalizing symptoms, suggesting adverse events promoted adaptive brain changes that may buffer against stress-related psychopathology. However, these same functional connections were also associated with poorer grades at the two-year follow-up. Although cortical-subcortical brain developmental responses to adversity potentially shield against stress-induced mood and anxiety disorders, they may be detrimental to other domains such as academic success.

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on SpringerLink
  • Instant access to the full article PDF.

USD 39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Circular plot of functional connections with significant negative (blue lines) associations with predicted values for the unweighted (left) and propensity-weighted (right) analyses.
Fig. 2: Functional connectivity by time point and number of adverse life events.
Fig. 3: Estimated effects of adverse life events on functional connectivity.

Similar content being viewed by others

Data availability

Data used in this study is publically available and was downloaded from the NIMH Data Archive (https://nda.nih.gov/).

References

  1. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, et al. Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: the adverse childhood experiences (ACE) study. Am J Prevent Med. 1998;14:245–58.

    Article  CAS  Google Scholar 

  2. Dube SR, Miller JW, Brown DW, Giles WH, Felitti VJ, Dong M, et al. Adverse childhood experiences and the association with ever using alcohol and initiating alcohol use during adolescence. J Adolesc Health. 2006;38:444.e441–444.e410.

    Article  Google Scholar 

  3. Enoch M-A. The role of early life stress as a predictor for alcohol and drug dependence. Psychopharmacology. 2011;214:17–31.

    Article  CAS  PubMed  Google Scholar 

  4. Anda RF, Whitfield CL, Felitti VJ, Chapman D, Edwards VJ, Dube SR, et al. Adverse childhood experiences, alcoholic parents, and later risk of alcoholism and depression. Psychiatr Serv. 2002;53:1001–9.

    Article  PubMed  Google Scholar 

  5. Pechtel P, Pizzagalli DA. Effects of early life stress on cognitive and affective function: an integrated review of human literature. Psychopharmacol (Berl). 2011;214:55–70.

    Article  CAS  Google Scholar 

  6. McLaughlin KA, Sheridan MA, Winter W, Fox NA, Zeanah CH, Nelson CA. Widespread reductions in cortical thickness following severe early-life deprivation: a neurodevelopmental pathway to attention-deficit/hyperactivity disorder. Biol Psychiatry. 2014;76:629–38.

    Article  PubMed  Google Scholar 

  7. Teicher MH, Samson JA, Anderson CM, Ohashi K. The effects of childhood maltreatment on brain structure, function and connectivity. Nat Rev Neurosci. 2016;17:652–66.

    Article  CAS  PubMed  Google Scholar 

  8. Kaiser RH, Clegg R, Goer F, Pechtel P, Beltzer M, Vitaliano G, et al. Childhood stress, grown-up brain networks: corticolimbic correlates of threat-related early life stress and adult stress response. Psychol Med. 2018;48:1157–66.

    Article  CAS  PubMed  Google Scholar 

  9. Taylor SE. Mechanisms linking early life stress to adult health outcomes. Proc Natl Acad Sci USA. 2010;107:8507–12.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  10. Malter Cohen M, Jing D, Yang RR, Tottenham N, Lee FS, Casey BJ. Early-life stress has persistent effects on amygdala function and development in mice and humans. Proc Natl Acad Sci USA. 2013;110:18274–8.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Boecker R, Holz NE, Buchmann AF, Blomeyer D, Plichta MM, Wolf I, et al. Impact of early life adversity on reward processing in young adults: EEG-fMRI results from a prospective study over 25 years. PloS one. 2014;9:e104185.

    Article  PubMed  PubMed Central  Google Scholar 

  12. Simmonds DJ, Hallquist MN, Asato M, Luna B. Developmental stages and sex differences of white matter and behavioral development through adolescence: A longitudinal diffusion tensor imaging (DTI) study. NeuroImage. 2014;92:356–68.

    Article  PubMed  Google Scholar 

  13. Lebel C, Walker L, Leemans A, Phillips L, Beaulieu C. Microstructural maturation of the human brain from childhood to adulthood. NeuroImage. 2008;40:1044–55.

    Article  CAS  PubMed  Google Scholar 

  14. Asato MR, Terwilliger R, Woo J, Luna B. White matter development in adolescence: a DTI study. Cereb Cortex. 2010;20:2122–31.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Choi EJ, Vandewouw MM, de Villa K, Inoue T, Taylor MJ. The development of functional connectivity within the dorsal striatum from early childhood to adulthood. Dev Cognitive Neurosci. 2023;61:101258.

  16. Rakesh D, Kelly C, Vijayakumar N, Zalesky A, Allen NB, Whittle S. Unraveling the consequences of childhood maltreatment: deviations from typical functional neurodevelopment mediate the relationship between maltreatment history and depressive symptoms. Biol Psychiat-Cogn N. 2021;6:329–42.

    Google Scholar 

  17. van Duijvenvoorde ACK, Westhoff B, de Vos F, Wierenga LM, Crone EA. A three-wave longitudinal study of subcortical-cortical resting-state connectivity in adolescence: testing age- and puberty-related changes. Hum Brain Mapp. 2019;40:3769–83.

    Article  PubMed  PubMed Central  Google Scholar 

  18. Gaffrey MS, Barch DM, Luby JL, Petersen SE. Amygdala functional connectivity is associated with emotion regulation and amygdala reactivity in 4-to 6-year-olds. J Am Acad Child Adolesc Psychiatry. 2021;60:176–85.

    Article  PubMed  Google Scholar 

  19. Connolly CG, Ho TC, Blom EH, LeWinn KZ, Sacchet MD, Tymofiyeva O, et al. Resting-state functional connectivity of the amygdala and longitudinal changes in depression severity in adolescent depression. J Affect Disord. 2017;207:86–94.

    Article  PubMed  Google Scholar 

  20. Gee DG, Humphreys KL, Flannery J, Goff B, Telzer EH, Shapiro M, et al. A developmental shift from positive to negative connectivity in human amygdala-prefrontal circuitry. J Neurosci. 2013;33:4584–93.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Bloom PA, VanTieghem M, Gabard-Durnam L, Gee DG, Flannery J, Caldera C, et al. Age-related change in task-evoked amygdala-prefrontal circuitry: A multiverse approach with an accelerated longitudinal cohort aged 4-22 years. Hum Brain Mapp. 2022;43:3221–44.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Rakesh D, Allen NB, Whittle S. Longitudinal changes in within-salience network functional connectivity mediate the relationship between childhood abuse and neglect, and mental health during adolescence. Psychol Med. 2023;53:1552–64.

    Article  PubMed  Google Scholar 

  23. Chahal R, Miller JG, Yuan JP, Buthmann JL, Gotlib IH. An exploration of dimensions of early adversity and the development of functional brain network connectivity during adolescence: Implications for trajectories of internalizing symptoms. Dev Psychopathol. 2022;34:557–71.

    Article  PubMed  PubMed Central  Google Scholar 

  24. Rakesh D, Elzeiny R, Vijayakumar N, Whittle S. A longitudinal study of childhood maltreatment, subcortical development, and subcortico-cortical structural maturational coupling from early to late adolescence. Psychol Med. 2023;53:7525–36.

    Article  PubMed  Google Scholar 

  25. Rakesh D, Zalesky A, Whittle S. Similar but distinct - Effects of different socioeconomic indicators on resting state functional connectivity: findings from the Adolescent Brain Cognitive Development (ABCD) Study. Dev Cognitive Neurosci. 2021;51:101005.

  26. Brieant AE, Sisk LM, Gee DG. Associations among negative life events, changes in cortico-limbic connectivity, and psychopathology in the ABCD Study. Dev Cogn Neurosci. 2021;52:101022.

    Article  PubMed  PubMed Central  Google Scholar 

  27. Thijssen S, Collins PF, Luciana M. Does pubertal stage mediate the association between family environment and structure and function of the amygdala-mPFC circuit? A replication study of the longitudinal ABCD cohort. Dev Cognitive Neurosci. 2022;56:101120.

  28. Pollmann A, Sasso R, Bates K, Fuhrmann D. Making connections: neurodevelopmental changes in brain connectivity after adverse experiences in early adolescence. J Neurosci. 2024;44:e0991232023.

  29. Rosenbaum PR, Rubin DB. The central role of the propensity score in observational studies for causal effects. Biometrika. 1983;70:41–55.

    Article  Google Scholar 

  30. Zhu JJ, Anderson CM, Ohashi K, Khan A, Teicher MH. Potential sensitive period effects of maltreatment on amygdala, hippocampal and cortical response to threat. Molecular Psychiatry. 2023;28:5128–39.

  31. Hagler DJ, Hatton S, Cornejo MD, Makowski C, Fair DA, Dick AS, et al. Image processing and analysis methods for the adolescent brain cognitive development study. NeuroImage. 2019;202:116091.

  32. Gordon EM, Laumann TO, Adeyemo B, Huckins JF, Kelley WM, Petersen SE. Generation and evaluation of a cortical area parcellation from resting-state correlations. Cereb Cortex. 2016;26:288–303.

    Article  PubMed  Google Scholar 

  33. Tiet QQ, Bird HR, Davies M, Hoven C, Cohen P, Jensen PS, et al. Adverse life events and resilience. J Am Acad Child Adolesc Psychiatry. 1998;37:1191–1200.

    Article  CAS  PubMed  Google Scholar 

  34. Elze MC, Gregson J, Baber U, Williamson E, Sartori S, Mehran R, et al. Comparison of propensity score methods and covariate adjustment evaluation in 4 cardiovascular studies. J Am Coll Cardiol. 2017;69:345–57.

    Article  PubMed  Google Scholar 

  35. Brookhart MA, Schneeweiss S, Rothman KJ, Glynn RJ, Avorn J, Sturmer T. Variable selection for propensity score models. Am J Epidemiol. 2006;163:1149–56.

    Article  PubMed  Google Scholar 

  36. Achenbach TM, Verhulst FC, Baron GD, Althaus M. A comparison of syndromes derived from the Child Behavior Checklist for American and Dutch boys aged 6-11 and 12-16. J Child Psychol Psychiatry. 1987;28:437–53.

    Article  CAS  PubMed  Google Scholar 

  37. Austin PC. An introduction to propensity score methods for reducing the effects of confounding in observational studies. Multivar Behav Res. 2011;46:399–424.

    Article  Google Scholar 

  38. Lunceford JK, Davidian M. Stratification and weighting via the propensity score in estimation of causal treatment effects: a comparative study. Stat Med. 2004;23:2937–60.

    Article  PubMed  Google Scholar 

  39. Zou H, Hastie T. Regularization and variable selection via the elastic net. J R. Stat Soc: Series B (Statistical Methodology). 2005;67:301–20.

  40. Haufe S, Meinecke F, Gorgen K, Dahne S, Haynes JD, Blankertz B, et al. On the interpretation of weight vectors of linear models in multivariate neuroimaging. NeuroImage. 2014;87:96–110.

    Article  PubMed  Google Scholar 

  41. Dick AS, Lopez DA, Watts AL, Heeringa S, Reuter C, Bartsch H, et al. Meaningful associations in the adolescent brain cognitive development study. NeuroImage. 2021;239:118262.

  42. Cohen J. A power primer. Psychol Bull. 1992;112:155–9.

    Article  CAS  PubMed  Google Scholar 

  43. Caqueo-Urízar A, Urzúa A, Villalonga-Olives E, Atencio-Quevedo D, Irarrázaval M, Flores J, et al. Children’s mental health: discrepancy between child self-reporting and parental reporting. Behav Sci-Basel. 2022;12:401.

  44. Piper BJ, Gray HM, Raber J, Birkett MA. Reliability and validity of brief problem monitor, an abbreviated form of the child behavior checklist. Psychiat Clin Neuros. 2014;68:759–67.

    Article  Google Scholar 

  45. Elton A, Tripathi SP, Mletzko T, Young J, Cisler JM, James GA, et al. Childhood maltreatment is associated with a sex-dependent functional reorganization of a brain inhibitory control network. Hum Brain Mapp. 2014;35:1654–67.

    Article  PubMed  Google Scholar 

  46. Kudielka BM, Kirschbaum C. Sex differences in HPA axis responses to stress: a review. Biol Psychol. 2005;69:113–32.

    Article  PubMed  Google Scholar 

  47. Herzberg MP, McKenzie KJ, Hodel AS, Hunt RH, Mueller BA, Gunnar MR, et al. Accelerated maturation in functional connectivity following early life stress: Circuit specific or broadly distributed? Dev Cogn Neurosci. 2021;48:100922.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Rakesh D, Cropley V, Zalesky A, Vijayakumar N, Allen NB, Whittle S. Neighborhood disadvantage and longitudinal brain-predicted-age trajectory during adolescence. Dev Cogn Neurosci. 2021;51:101002.

    Article  PubMed  PubMed Central  Google Scholar 

  49. Barch D, Pagliaccio D, Belden A, Harms MP, Gaffrey M, Sylvester CM, et al. Effect of hippocampal and amygdala connectivity on the relationship between preschool poverty and school-age depression. Am J Psychiatry. 2016;173:625–34.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Ilomaki M, Lindblom J, Salmela V, Flykt M, Vanska M, Salmi J, et al. Early life stress is associated with the default mode and fronto-limbic network connectivity among young adults. Front Behav Neurosci. 2022;16:958580.

  51. Uhlhaas PJ, Davey CG, Mehta UM, Shah J, Torous J, Allen NB, et al. Towards a youth mental health paradigm: a perspective and roadmap. Mol Psychiatry. 2023;28:3171–81.

  52. Supekar K, Musen M, Menon V. Development of large-scale functional brain networks in children. Plos Biology. 2009;7:e1000157.

  53. Larsen B, Sydnor VJ, Keller AS, Yeo BTT, Satterthwaite TD. A critical period plasticity framework for the sensorimotor-association axis of cortical neurodevelopment. Trends Neurosci. 2023;46:847–62.

  54. Teicher MH, Anderson CM, Ohashi K, Khan A, McGreenery CE, Bolger EA, et al. Differential effects of childhood neglect and abuse during sensitive exposure periods on male and female hippocampus. NeuroImage. 2018;169:443–52.

    Article  PubMed  Google Scholar 

  55. Sadaghiani S, D’Esposito M. Functional characterization of the cingulo-opercular network in the maintenance of tonic alertness. Cereb Cortex. 2015;25:2763–73.

    Article  PubMed  Google Scholar 

  56. Coste CP, Kleinschmidt A. Cingulo-opercular network activity maintains alertness. NeuroImage. 2016;128:264–72.

    Article  PubMed  Google Scholar 

  57. Machlin L, Egger HL, Stein CR, Navarro E, Carpenter KLH, Goel S, et al. Distinct associations of deprivation and threat with alterations in brain structure in early childhood. J Am Acad Child Adolesc Psychiatry. 2023;62:885.

    Article  PubMed  PubMed Central  Google Scholar 

  58. van Harmelen A-L, van Tol M-J, Demenescu LR, van der Wee NJA, Veltman DJ, Aleman A, et al. Enhanced amygdala reactivity to emotional faces in adults reporting childhood emotional maltreatment. Soc Cognit Affect Neurosci. 2012.

  59. Williams LM, Kemp AH, Felmingham K, Barton M, Olivieri G, Peduto A, et al. Trauma modulates amygdala and medial prefrontal responses to consciously attended fear. NeuroImage. 2006;29:347–57.

    Article  PubMed  Google Scholar 

  60. Savulich G, Riccelli R, Passamonti L, Correia M, Deakin JFW, Elliott R, et al. Effects of naltrexone are influenced by childhood adversity during negative emotional processing in addiction recovery. Transl Psychiatry. 2017;7:e1054.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Veer IM, Oei NYL, Spinhoven P, van Buchem MA, Elzinga BM, Rombouts SARB. Endogenous cortisol is associated with functional connectivity between the amygdala and medial prefrontal cortex. Psychoneuroendocrinology. 2012;37:1039–47.

    Article  CAS  PubMed  Google Scholar 

  62. Lees B, Squeglia LM, McTeague LM, Forbes MK, Krueger RF, Sunderland M, et al. Altered neurocognitive functional connectivity and activation patterns underlie psychopathology in preadolescence. Biol Psychiat-Cogn N. 2021;6:387–98.

    Google Scholar 

  63. Rodman. Neurobiological markers of resilience to depression following childhood maltreatment: the role of neural circuits supporting the cognitive control of emotion. Biol Psychiatry. 2019;86:464–73.

    Article  Google Scholar 

  64. Heitzeg MM, Nigg JT, Yau WYW, Zubieta JK, Zucker RA. Affective circuitry and risk for alcoholism in late adolescence: Differences in frontostriatal responses between vulnerable and resilient children of alcoholic parents. Alcohol-Clin Exp Res. 2008;32:414–26.

    Article  PubMed  PubMed Central  Google Scholar 

  65. Silvers JA, Lumian DS, Gabard-Durnam L, Gee DG, Goff B, Fareri DS, et al. Previous institutionalization is followed by broader amygdala-hippocampal-PFC network connectivity during aversive learning in human development. J Neurosci. 2016;36:6420–30.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Lee SW, Choi J, Lee JS, Yoo JH, Kim KW, Kim D, et al. Altered function of ventrolateral prefrontal cortex in adolescents with peer verbal abuse history. Psychiatry Investig. 2017;14:441–51.

    Article  PubMed  PubMed Central  Google Scholar 

  67. Sheynin J, Duval ER, Lokshina Y, Scott JC, Angstadt M, Kessler D, et al. Altered resting-state functional connectivity in adolescents is associated with PTSD symptoms and trauma exposure. Neuroimage-Clin. 2020;26:102215.

  68. Li L, Pan NF, Zhang LQ, Lui S, Huang XQ, Xu X, et al. Hippocampal subfield alterations in pediatric patients with post-traumatic stress disorder. Soc Cogn Affect Neurosci. 2021;16:334–44.

    Article  PubMed  Google Scholar 

  69. Eaton S, Cornwell H, Hamilton-Giachritsis C, Fairchild G. Resilience and young people’s brain structure, function and connectivity: A systematic review. Neurosci Biobehav Rev. 2022;132:936–56.

    Article  PubMed  Google Scholar 

  70. Zhang L, Rakesh D, Cropley V, Whittle S. Neurobiological correlates of resilience during childhood and adolescence - A systematic review. Clin Psychol Rev. 2023;105:102333.

  71. Ellwood-Lowe ME, Whitfield-Gabrieli S, Bunge SA. Brain network coupling associated with cognitive performance varies as a function of a child’s environment in the ABCD study. Nat Commun. 2021;12:7183.

  72. Sripada C, Angstadt M, Taxali A, Clark DA, Greathouse T, Rutherford S, et al. Brain-wide functional connectivity patterns support general cognitive ability and mediate effects of socioeconomic status in youth. Transl Psychiatry. 2021;11:571.

  73. Tomasi D, Volkow ND. Effects of family income on brain functional connectivity in US children: associations with cognition. Mol Psychiatry. 2023;28:4195–202.

    Article  PubMed  Google Scholar 

  74. Sheridan MA, Copeland WE, Machlin LS, Stein CR, Carpenter KLH, Egger HL. Neural structure is independently predicted by deprivation and threat in early childhood. J Am Acad Child Adolesc Psychiatry. 2019;58:S340–S340.

    Article  Google Scholar 

  75. Marek S, Tervo-Clemmens B, Calabro FJ, Montez DF, Kay BP, Hatoum AS, et al. Reproducible brain-wide association studies require thousands of individuals. Nature. 2022;605:654–60.

    Article  Google Scholar 

Download references

Acknowledgements

Data used in the preparation of this article were obtained from the Adolescent Brain Cognitive DevelopmentSM (ABCD) Study (https://abcdstudy.org), held in the NIMH Data Archive (NDA). This is a multisite, longitudinal study designed to recruit more than 10,000 children age 9–10 and follow them over 10 years into early adulthood. The ABCD Study is supported by the National Institutes of Health and additional federal partners under award numbers U01DA041048, U01DA050989, U01DA051016, U01DA041022, U01DA051018, U01DA051037, U01DA050987, U01DA041174, U01DA041106, U01DA041117, U01DA041028, U01DA041134, U01DA050988, U01DA051039, U01DA041156, U01DA041025, U01DA041120, U01DA051038, U01DA041148, U01DA041093, U01DA041089, U24DA041123, U24DA041147. A full list of supporters is available at https://abcdstudy.org/federal-partners.html. A listing of participating sites and a complete listing of the study investigators can be found at https://abcdstudy.org/consortium_members/. ABCD consortium investigators designed and implemented the study and/or provided data but did not necessarily participate in the analysis or writing of this report. This manuscript reflects the views of the authors and may not reflect the opinions or views of the NIH or ABCD consortium investigators. The ABCD data repository grows and changes over time. The ABCD data used in this report came from 10.15154/1523041. DOIs can be found at https://doi.org/10.15154/1523041. AE was supported by K01AA026334. BL was supported by K01AA026893.

Author information

Authors and Affiliations

  1. Department of Psychiatry, University of Florida, Gainesville, FL, 32610, USA

    Amanda Elton, Ben Lewis & Sara Jo Nixon

  2. Center for Addiction Research & Education, University of Florida, Gainesville, FL, 32610, USA

    Amanda Elton, Ben Lewis & Sara Jo Nixon

Authors
  1. Amanda Elton
    View author publications

    Search author on:PubMed Google Scholar

  2. Ben Lewis
    View author publications

    Search author on:PubMed Google Scholar

  3. Sara Jo Nixon
    View author publications

    Search author on:PubMed Google Scholar

Contributions

AE was involved in conceptualization, formal analysis, writing the original draft, and visualization of figures; BL contributed to conceptualization and reviewing and editing of the manuscript; SJN contributed to conceptualization and reviewing and editing the manuscript.

Corresponding author

Correspondence to Amanda Elton.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Elton, A., Lewis, B. & Nixon, S.J. The effects of adverse life events on brain development in the ABCD study®: a propensity-weighted analysis. Mol Psychiatry 30, 2463–2474 (2025). https://doi.org/10.1038/s41380-024-02850-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Version of record:

  • Issue date:

  • DOI: https://doi.org/10.1038/s41380-024-02850-9

This article is cited by

Search

Advanced search

Quick links