Assessing the accuracy of blood RNA profiles to identify patients with post-concussion syndrome: A pilot study in a military patient population

Jimmaline J. Hardy, Scott R. Mooney, Andrea N. Pearson, Dawn McGuire, Daniel J. Correa, Roger P. Simon, Robert Meller

Research output: Contribution to journalArticlepeer-review

2 Scopus citations

Abstract

Mild traumatic brain injury (mTBI) is a complex, neurophysiological condition that can have detrimental outcomes. Yet, to date, no objective method of diagnosis exists. Physical damage to the blood-brain-barrier and normal waste clearance via the lymphatic system may enable the detection of biomarkers of mTBI in peripheral circulation. Here we evaluate the accuracy of whole transcriptome analysis of blood to predict the clinical diagnosis of post-concussion syndrome (PCS) in a military cohort. Sixty patients with clinically diagnosed chronic concussion and controls (no history of concussion) were recruited (retrospective study design). Male patients (46) were split into a training set comprised of 20 long-term concussed (> 6 months and symptomatic) and 12 controls (no documented history of concussion). Models were validated in a testing set (control = 9, concussed = 5). RNA_Seq libraries were prepared from whole blood samples for sequencing using a SOLiD5500XL sequencer and aligned to hg19 reference genome. Patterns of differential exon expression were used for diagnostic modeling using support vector machine classification, and then validated in a second patient cohort. The accuracy of RNA profiles to predict the clinical diagnosis of post-concussion syndrome patients from controls was 86% (sensitivity 80%; specificity 89%). In addition, RNA profiles reveal duration of concussion. This pilot study shows the potential utility of whole transcriptome analysis to establish the clinical diagnosis of chronic concussion syndrome.

Original languageEnglish (US)
Article numbere0183113
JournalPloS one
Volume12
Issue number9
DOIs
StatePublished - Sep 2017

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

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