Impact & Blast Traumatic Brain Injury: Implications for Therapy

Traumatic brain injury (TBI) is one of the most frequent causes of combat casualties in Operations Iraqi Freedom (OIF), Enduring Freedom (OEF), and New Dawn (OND). Although less common than combat-related blast exposure, there have been significant numbers of blast injuries in civilian populations in the United States. Current United States Department of Defense (DoD) ICD-9 derived diagnoses of TBI in the DoD Health Care System show that, for 2016, severe and moderate TBIs accounted for just 0.7% and 12.9%, respectively, of the total of 13,634 brain injuries, while mild TBIs (mTBIs) accounted for 86% of the total. Although there is a report that there are differences in the frequency of long-term complications in mTBI between blast and non-blast TBIs, clinical presentation is classified by severity score rather than mechanism because severity scoring is associated with prognosis in clinical practice. Blast TBI (bTBI) is unique in its pathology and mechanism, but there is no treatment specific for bTBIs—these patients are treated similarly to TBIs in general and therapy is tailored on an individual basis. Currently there is no neuroprotective drug recommended by the clinical guidelines based on evidence

Principal component analysis of blood microRNA datasets facilitates diagnosis of diverse diseases.

Early, ideally pre-symptomatic, recognition of common diseases (e.g., heart disease, cancer, diabetes, Alzheimer's disease) facilitates early treatment or lifestyle modifications, such as diet and exercise. Sensitive, specific identification of diseases using blood samples would facilitate early recognition. We explored the potential of disease identification in high dimensional blood microRNA (miRNA) datasets using a powerful data reduction method: principal component analysis (PCA). Using Qlucore Omics Explorer (QOE), a dynamic, interactive visualization-guided bioinformatics program with a built-in statistical platform, we analyzed publicly available blood miRNA datasets from the Gene Expression Omnibus (GEO) maintained at the National Center for Biotechnology Information at the National Institutes of Health (NIH). The miRNA expression profiles were generated from real time PCR arrays, microarrays or next generation sequencing of biologic materials (e.g., blood, serum or blood components such as platelets). PCA identified the top three principal components that distinguished cohorts of patients with specific diseases (e.g., heart disease, stroke, hypertension, sepsis, diabetes, specific types of cancer, HIV, hemophilia, subtypes of meningitis, multiple sclerosis, amyotrophic lateral sclerosis, Alzheimer's disease, mild cognitive impairment, aging, and autism), from healthy subjects. Literature searches verified the functional relevance of the discriminating miRNAs. Our goal is to assemble PCA and heatmap analyses of existing and future blood miRNA datasets into a clinical reference database to facilitate the diagnosis of diseases using routine blood draws