Examination of the association between exposure to childhood maltreatment and brain structure in young adults: a machine learning analysis.
Journal
Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology
ISSN: 1740-634X
Titre abrégé: Neuropsychopharmacology
Pays: England
ID NLM: 8904907
Informations de publication
Date de publication:
10 2021
10 2021
Historique:
received:
13
07
2020
accepted:
03
02
2021
revised:
17
01
2021
pubmed:
28
2
2021
medline:
18
9
2021
entrez:
27
2
2021
Statut:
ppublish
Résumé
Exposure to maltreatment during childhood is associated with structural changes throughout the brain. However, the structural differences that are most strongly associated with maltreatment remain unclear given the limited number of whole-brain studies. The present study used machine learning to identify if and how brain structure distinguished young adults with and without a history of maltreatment. Young adults (ages 18-21, n = 384) completed an assessment of childhood trauma exposure and a structural MRI as part of the IMAGEN study. Elastic net regularized regression was used to identify the structural features that identified those with a history of maltreatment. A generalizable model that included 7 cortical thicknesses, 15 surface areas, and 5 subcortical volumes was identified (area under the receiver operating characteristic curve = 0.71, p < 0.001). Those with a maltreatment history had reduced surface areas and cortical thicknesses primarily in fronto-temporal regions. This group also had larger cortical thicknesses in occipital regions and surface areas in frontal regions. The results suggest childhood maltreatment is associated with multiple measures of structure throughout the brain. The use of a large sample without exposure to adulthood trauma provides further evidence for the unique contribution of childhood trauma to brain structure. The identified regions overlapped with regions associated with psychopathology in adults with maltreatment histories, which offers insights as to how these disorders manifest.
Identifiants
pubmed: 33637836
doi: 10.1038/s41386-021-00987-7
pii: 10.1038/s41386-021-00987-7
pmc: PMC8429761
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
1888-1894Subventions
Organisme : NIMH NIH HHS
ID : K08 MH121654
Pays : United States
Organisme : MRF
ID : MRF_MRF-058-0004-RG-DESRI
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/R00465X/1
Pays : United Kingdom
Organisme : NIBIB NIH HHS
ID : U54 EB020403
Pays : United States
Organisme : NIA NIH HHS
ID : R56 AG058854
Pays : United States
Organisme : Medical Research Council
ID : MR/S020306/1
Pays : United Kingdom
Organisme : NIMH NIH HHS
ID : K08 MH107661
Pays : United States
Organisme : NCCIH NIH HHS
ID : R01 AT011267
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH085772
Pays : United States
Organisme : MRF
ID : MRF_MRF-058-0009-RG-DESR-C0759
Pays : United Kingdom
Organisme : Medical Research Council
ID : MR/N000390/1
Pays : United Kingdom
Commentaires et corrections
Type : CommentIn
Type : CommentIn
Informations de copyright
© 2021. The Author(s), under exclusive licence to American College of Neuropsychopharmacology.
Références
Edwards VJ, Holden GW, Felitti VJ, Anda RF. Relationship between multiple forms of childhood maltreatment and adult mental health in community respondents: results from the adverse childhood experiences study. Am J Psychiatry. 2003;160:1453–60.
doi: 10.1176/appi.ajp.160.8.1453
Teicher MH, Samson JA. Annual research review: enduring neurobiological effects of childhood abuse and neglect. J Child Psychol Psychiatry. 2016;57:241–66.
doi: 10.1111/jcpp.12507
Peverill M, Dirks MA, Narvaja T, Herts KL, Comer JS, McLaughlin KA. Socioeconomic status and child psychopathology in the United States: a meta-analysis of population-based studies. Clin Psychol Rev. 2021;83:101933.
doi: 10.1016/j.cpr.2020.101933
McLaughlin KA, Weissman D, Bitrán D. Childhood adversity and neural development: a systematic review. Annu Dev Dev Psychol. 2019;1:277–312.
doi: 10.1146/annurev-devpsych-121318-084950
McEwen BS. Brain on stress: how the social environment gets under the skin. Proc Natl Acad Sci. 2012;109:17180–5.
doi: 10.1073/pnas.1121254109
Gold AL, Sheridan MA, Peverill M, Busso DS, Lambert HK, Alves S, et al. Childhood abuse and reduced cortical thickness in brain regions involved in emotional processing. J Child Psychol Psychiatry. 2016;57:1154–64.
doi: 10.1111/jcpp.12630
Rinne-Albers MA, Pannekoek JN, van Hoof M-J, van Lang ND, Lamers-Winkelman F, Rombouts SA, et al. Anterior cingulate cortex grey matter volume abnormalities in adolescents with PTSD after childhood sexual abuse. Eur Neuropsychopharmacol. 2017;27:1163–71.
doi: 10.1016/j.euroneuro.2017.08.432
Rinne-Albers MA, Boateng CP, van der Werff SJ, Lamers-Winkelman F, Rombouts SA, Vermeiren RR, et al. Preserved cortical thickness, surface area and volume in adolescents with PTSD after childhood sexual abuse. Sci Rep. 2020;10:1–9.
doi: 10.1038/s41598-020-60256-3
Heim CM, Mayberg HS, Mletzko T, Nemeroff CB, Pruessner JC. Decreased cortical representation of genital somatosensory field after childhood sexual abuse. Am J Psychiatry. 2013;170:616–23.
doi: 10.1176/appi.ajp.2013.12070950
Lim L, Hart H, Mehta M, Worker A, Simmons A, Mirza K, et al. Grey matter volume and thickness abnormalities in young people with a history of childhood abuse. Psychol Med. 2018;48:1034–46.
doi: 10.1017/S0033291717002392
Everaerd D, Klumpers F, Zwiers M, Guadalupe T, Franke B, van Oostrom I, et al. Childhood abuse and deprivation are associated with distinct sex-dependent differences in brain morphology. Neuropsychopharmacology. 2016;41:1716–23.
doi: 10.1038/npp.2015.344
Jollans L, Whelan R. Neuromarkers for mental disorders: harnessing population neuroscience. Front Psychiatry. 2018;9:242–56.
doi: 10.3389/fpsyt.2018.00242
Whelan R, Garavan H. When optimism hurts: Inflated predictions in psychiatric neuroimaging. Biol Psychiatry. 2014;75:746–8.
doi: 10.1016/j.biopsych.2013.05.014
Clausen AN, Aupperle RL, Yeh H-W, Waller D, Payne J, Kuplicki R, et al. Machine learning analysis of the relationships between gray matter volume and childhood trauma in a transdiagnostic community-based sample. Biol Psychiatry Cogn Neurosci Neuroimaging. 2019;4:734–42.
pubmed: 31053534
pmcid: 6688962
Jollans L, Boyle R, Artiges E, Banaschewski T, Desrivières S, Grigis A, et al. Quantifying performance of machine learning methods for neuroimaging data. NeuroImage. 2019;199:351–65.
doi: 10.1016/j.neuroimage.2019.05.082
Popovic D, Ruef A, Dwyer DB, Antonucci LA, Eder J, Sanfelici R, et al. Traces of trauma: a multivariate pattern analysis of childhood trauma, brain structure, and clinical phenotypes. Biol Psychiatry. 2020. https://doi.org/10.1016/j.biopsych.2020.05.020 .
Blair KS, Aloi J, Crum K, Meffert H, White SF, Taylor BK, et al. Association of different types of childhood maltreatment with emotional responding and response control among youths. JAMA Netw Open. 2019;2:e194604.
doi: 10.1001/jamanetworkopen.2019.4604
Walker EA, Unutzer J, Rutter C, Gelfand A, Saunders K, VonKorff M, et al. Costs of health care use by women HMO members with a history of childhood abuse and neglect. Arch Gen Psychiatry. 1999;56:609–13.
doi: 10.1001/archpsyc.56.7.609
McLaughlin KA, Sheridan MA. Beyond cumulative risk: a dimensional approach to childhood adversity. Curr Dir Psychol Sci. 2016;25:239–45.
doi: 10.1177/0963721416655883
Bernstein F. Manual for the Childhood Trauma Questionnaire. San Antonio, TX, The Psychological Corporation 1998.
Bernstein DP, Ahuvalia T, Pogge D, Handelsman L. Validity of the Childhood Trauma Questionnaire in an Adolescent Psychiatric Population. J Am Acad Child Adolesc Psychiatry. 1997;36:340–8.
doi: 10.1097/00004583-199703000-00012
Goodman R. Psychometric properties of the Strengths and Difficulties Questionnaire. J Am Acad Child Adolesc Psychiatry. 2001;40:1337–45.
doi: 10.1097/00004583-200111000-00015
Yeates KO, Donders J. The WISC-IV and neuropsychological assessment. WISC-IV clinical use and interpretation: Scientist-practitioner perspectives. San Diego, CA: Elsevier Academic Press; 2005. p. 415–34
doi: 10.1016/B978-012564931-5/50014-1
Schumann G, Loth E, Banaschewski T, Barbot A, Barker G, Büchel C, et al. The IMAGEN study: reinforcement-related behaviour in normal brain function and psychopathology. Mol Psychiatry. 2010;15:1128–39.
doi: 10.1038/mp.2010.4
Klein A, Andersson J, Ardekani BA, Ashburner J, Avants B, Chiang M-C, et al. Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. NeuroImage. 2009;46:786–802.
doi: 10.1016/j.neuroimage.2008.12.037
Tozzi L, Garczarek L, Janowitz D, Stein DJ, Wittfeld K, Dobrowolny H, et al. Interactive impact of childhood maltreatment, depression, and age on cortical brain structure: mega-analytic findings from a large multi-site cohort. Psychol Med. 2020;50:1020–31.
doi: 10.1017/S003329171900093X
Fox MD, Corbetta M, Snyder AZ, Vincent JL, Raichle ME. Spontaneous neuronal activity distinguishes human dorsal and ventral attention systems. Proc Natl Acad Sci. 2006;103:10046–51.
doi: 10.1073/pnas.0604187103
Miller EK, Cohen JD. An integrative theory of prefrontal cortex function. Annu Rev Neurosci. 2001;24:167–202.
doi: 10.1146/annurev.neuro.24.1.167
Gibb BE, Schofield CA, Coles ME. Reported history of childhood abuse and young adults’ information-processing biases for facial displays of emotion. Child Maltreat. 2009;14:148–56.
doi: 10.1177/1077559508326358
Günther V, Dannlowski U, Kersting A, Suslow T. Associations between childhood maltreatment and emotion processing biases in major depression: results from a dot-probe task. BMC Psychiatry. 2015;15:123.
doi: 10.1186/s12888-015-0501-2
Lim L, Hart H, Mehta MA, Simmons A, Mirza K, Rubia K. Neurofunctional abnormalities during sustained attention in severe childhood abuse. PLoS ONE. 2016;11:e0165547.
doi: 10.1371/journal.pone.0165547
Sheffield JM, Williams LE, Woodward ND, Heckers S. Reduced gray matter volume in psychotic disorder patients with a history of childhood sexual abuse. Schizophr Res. 2013;143:185–91.
doi: 10.1016/j.schres.2012.10.032
Akiki TJ, Averill CL, Abdallah CG. A network-based neurobiological model of PTSD: evidence from structural and functional neuroimaging studies. Curr Psychiatry Rep. 2017;19:81.
doi: 10.1007/s11920-017-0840-4
DiGangi JA, Tadayyon A, Fitzgerald DA, Rabinak CA, Kennedy A, Klumpp H, et al. Reduced default mode network connectivity following combat trauma. Neurosci Lett. 2016;615:37–43.
doi: 10.1016/j.neulet.2016.01.010
Bluhm RL, Williamson PC, Osuch EA, Frewen PA, Stevens TK, Boksman K, et al. Alterations in default network connectivity in posttraumatic stress disorder related to early-life trauma. J Psychiatry Neurosci Jpn. 2009;34:187–94.
pubmed: 19448848
Andrews-Hanna JR, Reidler JS, Sepulcre J, Poulin R, Buckner RL. Functional-anatomic fractionation of the brain’s default network. Neuron. 2010;65:550–62.
doi: 10.1016/j.neuron.2010.02.005
Etkin A, Prater KE, Hoeft F, Menon V, Schatzberg AF. Failure of anterior cingulate activation and connectivity with the amygdala during implicit regulation of emotional processing in generalized anxiety disorder. Am J Psychiatry. 2010;167:545–54.
doi: 10.1176/appi.ajp.2009.09070931
Sripada RK, King AP, Welsh RC, Garfinkel SN, Wang X, Sripada CS, et al. Neural dysregulation in posttraumatic stress disorder: evidence for disrupted equilibrium between salience and default mode brain networks. Psychosom Med. 2012;74:904–11.
doi: 10.1097/PSY.0b013e318273bf33
Shin LM, Bush G, Milad MR, Lasko NB, Brohawn KH, Hughes KC, et al. Exaggerated activation of dorsal anterior cingulate cortex during cognitive interference: a monozygotic twin study of posttraumatic stress disorder. Am J Psychiatry. 2011;168:979–85.
doi: 10.1176/appi.ajp.2011.09121812
Zielinski BA, Prigge MBD, Nielsen JA, Froehlich AL, Abildskov TJ, Anderson JS, et al. Longitudinal changes in cortical thickness in autism and typical development. Brain. 2014;137:1799–812.
doi: 10.1093/brain/awu083
Teicher MH, Parigger A. The ‘maltreatment and abuse chronology of exposure’ (MACE) scale for the retrospective assessment of abuse and neglect during development. PLoS ONE. 2015;10:e0117423.
doi: 10.1371/journal.pone.0117423