Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

PRONIA-consortium

doi:10.1016/j.biopsych.2020.05.020

Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

PRONIA-consortium

Clinic of Psychiatry and Psychotherapy

46 Citations (Scopus)

Abstract

Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

Original language	English
Journal	Biological Psychiatry
Volume	88
Issue number	11
Pages (from-to)	829-842
Number of pages	14
ISSN	0006-3223
DOIs	https://doi.org/10.1016/j.biopsych.2020.05.020
Publication status	Published - 01.12.2020

Funding

This work was supported by “Else-Kröner-Fresenius-Stiftung” through the Clinician Scientist Program “EKFS-Translational Psychiatry” (to DP and OFO); BMBF and the Max Planck Society (to RS); National Health and Medical Research Council Senior Principal Research Fellowship Grant Nos. 628386 (to CP) and 1105825 (to CP); European Union- National Health and Medical Research Council Grant No. 1075379 (to CP); PRONIA, a Collaborative Project funded by the European Union under the 7th Framework Programme Grant No. 602152 (to all contributing authors). The funding organizations were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. This work was supported by ?Else-Kr?ner-Fresenius-Stiftung? through the Clinician Scientist Program ?EKFS-Translational Psychiatry? (to DP and OFO); BMBF and the Max Planck Society (to RS); National Health and Medical Research Council Senior Principal Research Fellowship Grant Nos. 628386 (to CP) and 1105825 (to CP); European Union-National Health and Medical Research Council Grant No. 1075379 (to CP); PRONIA, a Collaborative Project funded by the European Union under the 7th Framework Programme Grant No. 602152 (to all contributing authors). The funding organizations were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. DP and NK had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. DP, NK, LK-I, SR, JK, PF, RU, EM, SJW, PB, SB, and CP were involved in concept and design. DP, NK, LK-I, SR, AR, DBD, RS, MSD, JE, MP, KC, JK, TH, FS-L, GB, AB, RU, CP, SJW, PB, and SB were involved in acquisition, analysis, or interpretation of data. DP, AR, DBD, LAA, and NK were involved in drafting of the manuscript. DP, NK, LK-I, SR, AR, DBD, LAA, RS, OFO, RP, MP, KC, JK, TH, FS-L, PF, RU, GP, AB, RKRS, CP, EM, SJW, PB, and SB were involved in critical revision of the manuscript for important intellectual content. DP, AR, and NK were involved in statistical analysis. DP, NK, LK-I, SR, RKRS, CP, PB, SB, and SJW were involved in obtaining funding. NK, AR, MP, KC, TH, DH, RU, EM, AB, PB, and SB were involved in administrative, technical, or material support. NK, SR, FS-L, PF, SJW, PB, AB, RL, RU, SB, UD, and CP were involved in supervision. PRONIA consortium members listed here performed the screening, recruitment, rating, examination, and follow-up of the study participants and were involved in implementing the examination protocols of the study, setting up its information technological infrastructure, and organizing the flow and quality control of the data analyzed in this article between the local study sites and the central study database. We thank the Recognition and Prevention Program at the Zucker Hillside Hospital in New York, directed by Barbara Cornblatt, Ph.D. M.B.A. for providing the Global Functioning: Social and Role scales. We thank Andrea M. Auther, Ph.D. Associate Director of Recognition and Prevention Program and coauthor of the Global Functioning scales for overseeing the training and implementation of the scales. They were not compensated for their contributions. NK and RS received honoraria for talks presented at education meetings organized by Otsuka/Lundbeck. CP participated in advisory boards for Janssen-Cilag, AstraZeneca, Lundbeck, and Servier; and received honoraria for talks presented at educational meetings organized by AstraZeneca, Janssen-Cilag, Eli Lilly, Pfizer, Lundbeck, and Shire. RU received honoraria for talks presented at educational meetings organized by Sunovion. All other authors report no biomedical financial interests or potential conflicts of interest.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 3 Good Health and Well-being
SDG 10 Reduced Inequalities

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Academic Focus: Center for Brain, Behavior and Metabolism (CBBM)

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10.1016/j.biopsych.2020.05.020

Cite this

@article{ae5af70aa85a4603b90a117a20c76c8e,

title = "Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes",

abstract = "Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.",

author = "David Popovic and PRONIA-consortium and Anne Ruef and Dwyer, \{Dominic B.\} and Antonucci, \{Linda A.\} and Julia Eder and Rachele Sanfelici and Lana Kambeitz-Ilankovic and Oztuerk, \{Omer Faruk\} and Dong, \{Mark S.\} and Riya Paul and Marco Paolini and Dennis Hedderich and Theresa Haidl and Joseph Kambeitz and Stephan Ruhrmann and Katharine Chisholm and Frauke Schultze-Lutter and Peter Falkai and Giulio Pergola and Giuseppe Blasi and Alessandro Bertolino and Rebekka Lencer and Udo Dannlowski and Rachel Upthegrove and Salokangas, \{Raimo K.R.\} and Christos Pantelis and Eva Meisenzahl and Wood, \{Stephen J.\} and Paolo Brambilla and Stefan Borgwardt and Nikolaos Koutsouleris and Dong, \{Mark Sen\} and Anne Erkens and Eva Gussmann and Shalaila Haas and Alkomiet Hasan and Claudius Hoff and Ifrah Khanyaree and Aylin Melo and Susanna Muckenhuber-Sternbauer and Janis K{\"o}hler and {\"O}zt{\"u}rk, \{{\"O}mer Faruk\} and Nora Penzel and Adrian Rangnick and \{von Saldern\}, Sebastian and Moritz Spangemacher and Ana Tupac and Urquijo, \{Maria Fernanda\} and Johanna Weiske and Julian Wenzel",

note = "Funding Information: This work was supported by “Else-Kr{\"o}ner-Fresenius-Stiftung” through the Clinician Scientist Program “EKFS-Translational Psychiatry” (to DP and OFO); BMBF and the Max Planck Society (to RS); National Health and Medical Research Council Senior Principal Research Fellowship Grant Nos. 628386 (to CP) and 1105825 (to CP); European Union- National Health and Medical Research Council Grant No. 1075379 (to CP); PRONIA, a Collaborative Project funded by the European Union under the 7th Framework Programme Grant No. 602152 (to all contributing authors). The funding organizations were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Funding Information: This work was supported by ?Else-Kr?ner-Fresenius-Stiftung? through the Clinician Scientist Program ?EKFS-Translational Psychiatry? (to DP and OFO); BMBF and the Max Planck Society (to RS); National Health and Medical Research Council Senior Principal Research Fellowship Grant Nos. 628386 (to CP) and 1105825 (to CP); European Union-National Health and Medical Research Council Grant No. 1075379 (to CP); PRONIA, a Collaborative Project funded by the European Union under the 7th Framework Programme Grant No. 602152 (to all contributing authors). The funding organizations were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. DP and NK had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. DP, NK, LK-I, SR, JK, PF, RU, EM, SJW, PB, SB, and CP were involved in concept and design. DP, NK, LK-I, SR, AR, DBD, RS, MSD, JE, MP, KC, JK, TH, FS-L, GB, AB, RU, CP, SJW, PB, and SB were involved in acquisition, analysis, or interpretation of data. DP, AR, DBD, LAA, and NK were involved in drafting of the manuscript. DP, NK, LK-I, SR, AR, DBD, LAA, RS, OFO, RP, MP, KC, JK, TH, FS-L, PF, RU, GP, AB, RKRS, CP, EM, SJW, PB, and SB were involved in critical revision of the manuscript for important intellectual content. DP, AR, and NK were involved in statistical analysis. DP, NK, LK-I, SR, RKRS, CP, PB, SB, and SJW were involved in obtaining funding. NK, AR, MP, KC, TH, DH, RU, EM, AB, PB, and SB were involved in administrative, technical, or material support. NK, SR, FS-L, PF, SJW, PB, AB, RL, RU, SB, UD, and CP were involved in supervision. PRONIA consortium members listed here performed the screening, recruitment, rating, examination, and follow-up of the study participants and were involved in implementing the examination protocols of the study, setting up its information technological infrastructure, and organizing the flow and quality control of the data analyzed in this article between the local study sites and the central study database. We thank the Recognition and Prevention Program at the Zucker Hillside Hospital in New York, directed by Barbara Cornblatt, Ph.D. M.B.A. for providing the Global Functioning: Social and Role scales. We thank Andrea M. Auther, Ph.D. Associate Director of Recognition and Prevention Program and coauthor of the Global Functioning scales for overseeing the training and implementation of the scales. They were not compensated for their contributions. NK and RS received honoraria for talks presented at education meetings organized by Otsuka/Lundbeck. CP participated in advisory boards for Janssen-Cilag, AstraZeneca, Lundbeck, and Servier; and received honoraria for talks presented at educational meetings organized by AstraZeneca, Janssen-Cilag, Eli Lilly, Pfizer, Lundbeck, and Shire. RU received honoraria for talks presented at educational meetings organized by Sunovion. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: {\textcopyright} 2020 Society of Biological Psychiatry Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2020",

month = dec,

day = "1",

doi = "10.1016/j.biopsych.2020.05.020",

language = "English",

volume = "88",

pages = "829--842",

journal = "Biological Psychiatry",

issn = "0006-3223",

publisher = "Elsevier Inc.",

number = "11",

}

TY - JOUR

T1 - Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

AU - Popovic, David

AU - PRONIA-consortium

AU - Ruef, Anne

AU - Dwyer, Dominic B.

AU - Antonucci, Linda A.

AU - Eder, Julia

AU - Sanfelici, Rachele

AU - Kambeitz-Ilankovic, Lana

AU - Oztuerk, Omer Faruk

AU - Dong, Mark S.

AU - Paul, Riya

AU - Paolini, Marco

AU - Hedderich, Dennis

AU - Haidl, Theresa

AU - Kambeitz, Joseph

AU - Ruhrmann, Stephan

AU - Chisholm, Katharine

AU - Schultze-Lutter, Frauke

AU - Falkai, Peter

AU - Pergola, Giulio

AU - Blasi, Giuseppe

AU - Bertolino, Alessandro

AU - Lencer, Rebekka

AU - Dannlowski, Udo

AU - Upthegrove, Rachel

AU - Salokangas, Raimo K.R.

AU - Pantelis, Christos

AU - Meisenzahl, Eva

AU - Wood, Stephen J.

AU - Brambilla, Paolo

AU - Borgwardt, Stefan

AU - Koutsouleris, Nikolaos

AU - Dong, Mark Sen

AU - Erkens, Anne

AU - Gussmann, Eva

AU - Haas, Shalaila

AU - Hasan, Alkomiet

AU - Hoff, Claudius

AU - Khanyaree, Ifrah

AU - Melo, Aylin

AU - Muckenhuber-Sternbauer, Susanna

AU - Köhler, Janis

AU - Öztürk, Ömer Faruk

AU - Penzel, Nora

AU - Rangnick, Adrian

AU - von Saldern, Sebastian

AU - Spangemacher, Moritz

AU - Tupac, Ana

AU - Urquijo, Maria Fernanda

AU - Weiske, Johanna

AU - Wenzel, Julian

N1 - Funding Information: This work was supported by “Else-Kröner-Fresenius-Stiftung” through the Clinician Scientist Program “EKFS-Translational Psychiatry” (to DP and OFO); BMBF and the Max Planck Society (to RS); National Health and Medical Research Council Senior Principal Research Fellowship Grant Nos. 628386 (to CP) and 1105825 (to CP); European Union- National Health and Medical Research Council Grant No. 1075379 (to CP); PRONIA, a Collaborative Project funded by the European Union under the 7th Framework Programme Grant No. 602152 (to all contributing authors). The funding organizations were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Funding Information: This work was supported by ?Else-Kr?ner-Fresenius-Stiftung? through the Clinician Scientist Program ?EKFS-Translational Psychiatry? (to DP and OFO); BMBF and the Max Planck Society (to RS); National Health and Medical Research Council Senior Principal Research Fellowship Grant Nos. 628386 (to CP) and 1105825 (to CP); European Union-National Health and Medical Research Council Grant No. 1075379 (to CP); PRONIA, a Collaborative Project funded by the European Union under the 7th Framework Programme Grant No. 602152 (to all contributing authors). The funding organizations were not involved in the design and conduct of the study; the collection, management, analysis, and interpretation of the data; the preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. DP and NK had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. DP, NK, LK-I, SR, JK, PF, RU, EM, SJW, PB, SB, and CP were involved in concept and design. DP, NK, LK-I, SR, AR, DBD, RS, MSD, JE, MP, KC, JK, TH, FS-L, GB, AB, RU, CP, SJW, PB, and SB were involved in acquisition, analysis, or interpretation of data. DP, AR, DBD, LAA, and NK were involved in drafting of the manuscript. DP, NK, LK-I, SR, AR, DBD, LAA, RS, OFO, RP, MP, KC, JK, TH, FS-L, PF, RU, GP, AB, RKRS, CP, EM, SJW, PB, and SB were involved in critical revision of the manuscript for important intellectual content. DP, AR, and NK were involved in statistical analysis. DP, NK, LK-I, SR, RKRS, CP, PB, SB, and SJW were involved in obtaining funding. NK, AR, MP, KC, TH, DH, RU, EM, AB, PB, and SB were involved in administrative, technical, or material support. NK, SR, FS-L, PF, SJW, PB, AB, RL, RU, SB, UD, and CP were involved in supervision. PRONIA consortium members listed here performed the screening, recruitment, rating, examination, and follow-up of the study participants and were involved in implementing the examination protocols of the study, setting up its information technological infrastructure, and organizing the flow and quality control of the data analyzed in this article between the local study sites and the central study database. We thank the Recognition and Prevention Program at the Zucker Hillside Hospital in New York, directed by Barbara Cornblatt, Ph.D. M.B.A. for providing the Global Functioning: Social and Role scales. We thank Andrea M. Auther, Ph.D. Associate Director of Recognition and Prevention Program and coauthor of the Global Functioning scales for overseeing the training and implementation of the scales. They were not compensated for their contributions. NK and RS received honoraria for talks presented at education meetings organized by Otsuka/Lundbeck. CP participated in advisory boards for Janssen-Cilag, AstraZeneca, Lundbeck, and Servier; and received honoraria for talks presented at educational meetings organized by AstraZeneca, Janssen-Cilag, Eli Lilly, Pfizer, Lundbeck, and Shire. RU received honoraria for talks presented at educational meetings organized by Sunovion. All other authors report no biomedical financial interests or potential conflicts of interest. Publisher Copyright: © 2020 Society of Biological Psychiatry Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2020/12/1

Y1 - 2020/12/1

N2 - Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

AB - Background: Childhood trauma (CT) is a major yet elusive psychiatric risk factor, whose multidimensional conceptualization and heterogeneous effects on brain morphology might demand advanced mathematical modeling. Therefore, we present an unsupervised machine learning approach to characterize the clinical and neuroanatomical complexity of CT in a larger, transdiagnostic context. Methods: We used a multicenter European cohort of 1076 female and male individuals (discovery: n = 649; replication: n = 427) comprising young, minimally medicated patients with clinical high-risk states for psychosis; patients with recent-onset depression or psychosis; and healthy volunteers. We employed multivariate sparse partial least squares analysis to detect parsimonious associations between combinations of items from the Childhood Trauma Questionnaire and gray matter volume and tested their generalizability via nested cross-validation as well as via external validation. We investigated the associations of these CT signatures with state (functioning, depressivity, quality of life), trait (personality), and sociodemographic levels. Results: We discovered signatures of age-dependent sexual abuse and sex-dependent physical and sexual abuse, as well as emotional trauma, which projected onto gray matter volume patterns in prefronto-cerebellar, limbic, and sensory networks. These signatures were associated with predominantly impaired clinical state- and trait-level phenotypes, while pointing toward an interaction between sexual abuse, age, urbanicity, and education. We validated the clinical profiles for all three CT signatures in the replication sample. Conclusions: Our results suggest distinct multilayered associations between partially age- and sex-dependent patterns of CT, distributed neuroanatomical networks, and clinical profiles. Hence, our study highlights how machine learning approaches can shape future, more fine-grained CT research.

UR - https://www.scopus.com/pages/publications/85089187666

U2 - 10.1016/j.biopsych.2020.05.020

DO - 10.1016/j.biopsych.2020.05.020

M3 - Journal articles

C2 - 32782139

AN - SCOPUS:85089187666

SN - 0006-3223

VL - 88

SP - 829

EP - 842

JO - Biological Psychiatry

JF - Biological Psychiatry

IS - 11

ER -

Traces of Trauma: A Multivariate Pattern Analysis of Childhood Trauma, Brain Structure, and Clinical Phenotypes

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