Identification of Whole Blood RNA Markers for TBI Magnitude and Temporal Dynamics
Name: Michael Neill
Organization: Henry M. Jackson Foundation for the Advancement of Military Medicine
Performance Site: Uniformed Services University of the Health Sciences, Bethesda, MD
Year Published: 2015
From 2000 to 2014, the total number of service members with traumatic brain injury (TBI) has tripled from 10,958 to 320,344. This increase in the number of TBI cases is of grave concern as research has demonstrated that TBI may lead to grim long-term neurological disabilities and disease. TBIs are classified as mild, moderate, and severe, with each posing a unique challenge, medically. mTBI represents the most prevalent number of cases to represent over 80% of all military TBI cases.
Due to the complexity and heterogeneity of clinical scenario for each patient, diagnosiing and monitoring TBI patients is difficult as current modalities used by clinicans are either too subjective in nature or because of their lack of cost effectiveness and the logistics of repeated sampling make them a poor option. Blood based biomarkers using second generation transcriptome analysis offer a solution. Recently, it was determined that the adaptive immune system can respond and develop memory to CNS injury. Leukocytes associated with responses to human injury/illness generate specific and identifiable gene expression signatures. However, it is currently unknown what the precise response and leukocyte gene expression signatures are after TBI.
Our goal in this proposed project is therefore, to identify candidate clinical biomarkers for stratification of the magnitude of TBI and correlate outcomes for TBI patients with whole blood RNA analysis from longitudinal sampling post-injury using second-generation sequencing. We hypothesize that traumatic brain injury induced expression of transcriptome biomarkers will provide a clinically relevant blood signature that is complements current modalities of assessment of magnitude of injury and monitoring response to treatments.
Aim #1: Characterize whole blood transcriptome biomarkers to construct profiles for assessing severity of TBI by using RNA sequencing to characterize RNA expression and validate by comparing results with current clincial diagnostc modalites.
Aim #2: Determine the effects of change in the biomarker profile over a longitudinal course of time after TBI to create a clinically relevant monitoring tool using transcriptome sequencing to identify the temporal nature of molecular biomarkers from 1-180 days post-TBI.