Final Report: Continuation Study: A Systems Approach to Understanding Post-Traumatic Stress Disorder
Technical Report,23 Sep 2010,31 Oct 2016
University of California Santa Barbaraq Santa Barbara United States
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Post-Traumatic Stress Disorder PTSD is a complex anxiety disorder affecting many combat-exposed soldiers. Current diagnosis of PTSD is survey-based and is not used to diagnose stages of the disorder, reliably inform effective treatment strategies, or predict recoverysymptom changes. Thus, there is a need to identify robust biomarkers for accurate diagnosis, prognosis, and evaluation of therapeutics. Using the currently available blood data from the Systems Biology of PTSD Consortium, we sought to provide greater insights into the complex underlying biophysical networks of PTSD using a variety of statistical, machine learning, and dynamic modeling techniques. Primarily, our analysis was completed on an age and ethnicity-matched male cohort of 83 PTSD and 83 combat-exposed control subjects, a preliminary validation cohort for some data types, and a small of cohort of recalled subjects from the original 83-83 cohort. Using this available data, we focused our efforts on five aims 1 characterization of disease signals, and affected biological pathways in PTSD, 2 development and application of single omic biomarker identification tools, 3 integration of multi-omics datasets for biomarker identification, 4characterization of DNA methylation-based subtypes of PTSD, 5 development of an HPA-circadian metabolic dynamic model, and 6 development of data analysis pipelines for large molecular datasets.