Machine Learning Analysis of the Relationships Between Gray Matter Volume and Childhood Trauma in a Transdiagnostic Community-Based Sample

Tulsa 1000 Investigators

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10 Scopus citations

Abstract

Background: Childhood trauma is a significant risk factor for adult psychopathology. Previous investigations have implicated childhood trauma–related structural changes in anterior cingulate, dorsolateral prefrontal and orbitofrontal cortex, and hippocampus. Using a large transdiagnostic community sample, the goal of this investigation was to differentially associate regional gray matter (GM) volume with childhood trauma severity specifically, distinct from adult psychopathology. Methods: A total of 577 non–treatment-seeking adults (n = 207 men) completed diagnostic, childhood trauma, and structural magnetic resonance imaging assessments with regional GM volume estimated using FreeSurfer. Elastic net analysis was conducted in a nested cross-validation framework, with GM volumes, adult psychopathology, age, education, sex, and magnetic resonance imaging coil type as potential predictors for childhood trauma severity. Results: Elastic net identified age, education, sex, medical condition, adult psychopathology, and 13 GM regions as predictors of childhood trauma severity. GM regions identified included right caudate; left pallidum; bilateral insula and cingulate sulcus; left superior, inferior, and orbital frontal regions; and regions within temporal and parietal lobes and cerebellum. Conclusions: Results from this large, transdiagnostic sample implicate GM volume in regions central to current neurobiological theories of trauma (e.g., prefrontal cortex) as well as additional regions involved in reward, interoceptive, attentional, and sensory processing (e.g., striatal, insula, and parietal/occipital cortices). Future longitudinal studies examining the functional impact of structural changes in this broader network of regions are needed to clarify the role each may play in longer-term outcomes following trauma.

Original languageEnglish (US)
Pages (from-to)734-742
Number of pages9
JournalBiological Psychiatry: Cognitive Neuroscience and Neuroimaging
Volume4
Issue number8
DOIs
StatePublished - Aug 2019

Bibliographical note

Funding Information:
This work and all LIBR affiliates are supported by the William K. Warren Foundation , National Alliance for Research on Schizophrenia and Depression Young Investigator Grant (to W.K. Simmons), and National Institutes of Health (Grant No. K23MH108707 [to RLA], Grant No. K01MH096077 [to J. Savitz], and Grant No. K23MH112949 [to S.S. Khalsa]). Writing of the manuscript was partially supported by the Department of Veterans Affairs Office of Academic Affiliations Advanced Fellowship Program in Mental Illness Research and Treatment, Medical Research Service of the Durham VA Health Care System, and Department of Veterans Affairs Mid-Atlantic Mental Illness Research, Education, and Clinical Center. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government.

Funding Information:
This work and all LIBR affiliates are supported by the William K. Warren Foundation, National Alliance for Research on Schizophrenia and Depression Young Investigator Grant (to W.K. Simmons), and National Institutes of Health (Grant No. K23MH108707 [to RLA], Grant No. K01MH096077 [to J. Savitz], and Grant No. K23MH112949 [to S.S. Khalsa]). Writing of the manuscript was partially supported by the Department of Veterans Affairs Office of Academic Affiliations Advanced Fellowship Program in Mental Illness Research and Treatment, Medical Research Service of the Durham VA Health Care System, and Department of Veterans Affairs Mid-Atlantic Mental Illness Research, Education, and Clinical Center. The views expressed in this article are those of the authors and do not necessarily reflect the position or policy of the Department of Veterans Affairs or the United States Government. W.K. Simmons is an employee of Janssen Research and Development, LLC, of Johnson and Johnson. All other authors report no biomedical financial interests or potential conflicts of interest.

Publisher Copyright:
© 2019

Keywords

  • Adult psychopathology
  • Childhood
  • Elastic net
  • Gray matter volume
  • MRI
  • Trauma exposure

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