Abstract

We sought to find clinical subtypes of posttraumatic stress disorder (PTSD) in veterans 6–10 years post-trauma exposure based on current symptom assessments and to examine whether blood biomarkers could differentiate them. Samples were males deployed to Iraq and Afghanistan studied by the PTSD Systems Biology Consortium: a discovery sample of 74 PTSD cases and 71 healthy controls (HC), and a validation sample of 26 PTSD cases and 36 HC. A machine learning method, random forests (RF), in conjunction with a clustering method, partitioning around medoids, were used to identify subtypes derived from 16 self-report and clinician assessment scales, including the clinician-administered PTSD scale for DSM-IV (CAPS). Two subtypes were identified, designated S1 and S2, differing on mean current CAPS total scores: S2 = 75.6 (sd 14.6) and S1 = 54.3 (sd 6.6). S2 had greater symptom severity scores than both S1 and HC on all scale items. The mean first principal component score derived from clinical summary scales was three times higher in S2 than in S1. Distinct RFs were grown to classify S1 and S2 vs. HCs and vs. each other on multi-omic blood markers feature classes of current medical comorbidities, neurocognitive functioning, demographics, pre-military trauma, and psychiatric history. Among these classes, in each RF intergroup comparison of S1, S2, and HC, multi-omic biomarkers yielded the highest AUC-ROCs (0.819–0.922); other classes added little to further discrimination of the subtypes. Among the top five biomarkers in each of these RFs were methylation, micro RNA, and lactate markers, suggesting their biological role in symptom severity.

Highlights

  • Distinct subtypes of posttraumatic stress disorder (PTSD), a heterogeneous disorder, have been sought to isolate differentiating clinical features and their biological mechanisms so that recommendations can be made for more precise treatments and prognostic indicators can be identified

  • While biological correlates of PTSD including multi-omic blood biomarkers[8], cortisol[9], neurocognitive markers[10], neuroimaging markers[11,12], and voice markers[13] have been studied, to date only a few studies have shown their value for characterizing subtypes

  • We considered a large array of clinical symptom items captured in 16 validated self-report and clinical assessment scales that are commonly used in practice to assess PTSD and its comorbidities in clinical research settings

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Summary

Introduction

Distinct subtypes of posttraumatic stress disorder (PTSD), a heterogeneous disorder, have been sought to isolate differentiating clinical features and their biological mechanisms so that recommendations can be made for more precise treatments and prognostic indicators can be identified. While biological correlates of PTSD including multi-omic blood biomarkers[8], cortisol[9], neurocognitive markers[10], neuroimaging markers[11,12], and voice markers[13] have been studied, to date only a few studies have shown their value for characterizing subtypes. Neurocognitive functioning has been shown to differentiate clinically defined severity subtypes[6]. Zhang et al.[14] demonstrated that electroencephalography (EEG) functional connectivity defined subtypes for PTSD and major depressive disorder (MDD) predict differential treatment response when comparing psychotherapy to placebo for PTSD, and antidepressant medication versus placebo for MDD. Epigenetic markers have been used to define PTSD subtypes, which are shown to differ on clinical characteristics[15], a reversal of the usual approach

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