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Early life stress (ELS) contributes to this heterogeneity, but we do not know how a history of ELS influences traditionally defined brain signatures of PTSD. Here, we used a novel machine learning method \u2013 evolving partitions to improve classification (EPIC) \u2013 to identify shared and unique structural neuroimaging markers of ELS and PTSD in 97 combat\u2010exposed military veterans.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>METHODS<\/jats:title>\n                    <jats:p>\n                      We used EPIC with repeated cross\u2010validation (CV) to determine how combinations of cortical thickness, surface area, and subcortical brain volumes could contribute to classification of PTSD (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a040) versus controls (\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a057), and classification of ELS within the PTSD (ELS\n                      <jats:sup>+<\/jats:sup>\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a016; ELS\n                      <jats:sup>\u2212<\/jats:sup>\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a024) and control groups (ELS\n                      <jats:sup>+<\/jats:sup>\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a016; ELS\n                      <jats:sup>\u2212<\/jats:sup>\n                      <jats:italic>n<\/jats:italic>\n                      \u00a0=\u00a041). Additional inputs included intracranial volume, age, sex, adult trauma, and depression.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>On average, EPIC classified PTSD with 69% accuracy (SD\u00a0=\u00a05%), and ELS with 64% accuracy in the PTSD group (SD\u00a0=\u00a010%), and 62% accuracy in controls (SD\u00a0=\u00a06%). EPIC selected unique sets of individual features that classified each group with 75\u201085% accuracy in post hoc analyses; combinations of regions marginally improved classification from the individual atlas\u2010defined brain regions. Across analyses, surface area in the right posterior cingulate was the only variable that was repeatedly selected as an important feature for classification of PTSD and ELS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>EPIC revealed unique patterns of features that distinguished PTSD and ELS in this sample of combat\u2010exposed military veterans, which may represent distinct biotypes of stress\u2010related neuropathology.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1111\/jon.12600","type":"journal-article","created":{"date-parts":[[2019,2,4]],"date-time":"2019-02-04T00:25:04Z","timestamp":1549239904000},"page":"335-343","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Adaptive Identification of Cortical and Subcortical Imaging Markers of Early Life Stress and Posttraumatic Stress Disorder"],"prefix":"10.1111","volume":"29","author":[{"given":"Lauren E.","family":"Salminen","sequence":"first","affiliation":[{"name":"Imaging Genetics Center of the Mark and Mary Stevens Institute for Neuroimaging &amp; Informatics, Keck School of Medicine University of Southern California  Marina del Rey CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rajendra A.","family":"Morey","sequence":"additional","affiliation":[{"name":"Durham VA Medical Center  Durham NC"},{"name":"Duke University Medical Center  Durham NC"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Brandalyn C.","family":"Riedel","sequence":"additional","affiliation":[{"name":"Imaging Genetics Center of the Mark and Mary Stevens Institute for Neuroimaging &amp; Informatics, Keck School of Medicine University of Southern California  Marina del Rey CA"},{"name":"Department of Radiology and Imaging Sciences Indiana University School of Medicine  Indianapolis IN"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neda","family":"Jahanshad","sequence":"additional","affiliation":[{"name":"Imaging Genetics Center of the Mark and Mary Stevens Institute for Neuroimaging &amp; Informatics, Keck School of Medicine University of Southern California  Marina del Rey CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Emily L.","family":"Dennis","sequence":"additional","affiliation":[{"name":"Imaging Genetics Center of the Mark and Mary Stevens Institute for Neuroimaging &amp; Informatics, Keck School of Medicine University of Southern California  Marina del Rey CA"},{"name":"Psychiatry Neuroimaging Laboratory Harvard Medical School  Boston MA"},{"name":"Stanford Neurodevelopment, Affect, and Psychopathology Laboratory  Stanford CA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Paul M.","family":"Thompson","sequence":"additional","affiliation":[{"name":"Imaging Genetics Center of the Mark and Mary Stevens 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