AUTHOR=Huie J. Russell , Nielson Jessica L. , Wolfsbane Jorden , Andersen Clark R. , Spratt Heidi M. , DeWitt Douglas S. , Ferguson Adam R. , Hawkins Bridget E. 

TITLE=Data-driven approach to integrating genomic and behavioral preclinical traumatic brain injury research

JOURNAL=Frontiers in Bioengineering and Biotechnology

VOLUME=Volume 10 - 2022

YEAR=2023

URL=https://www.frontiersin.org/journals/bioengineering-and-biotechnology/articles/10.3389/fbioe.2022.887898

DOI=10.3389/fbioe.2022.887898

ISSN=2296-4185

ABSTRACT=Understanding recovery from TBI is complex, involving multiple systems and modalities. The current study applied modern data science tools to manage this complexity and harmonize large-scale data to understand relationships between gene expression and behavioral outcomes in a preclinical model of chronic TBI (cTBI). Data collected by the Moody Project for Translational TBI Research included rats with no injury (naïve animals with similar amounts of anesthestic exposure to TBI and sham-injured animals), sham injury, or lateral fluid percussion TBI, followed by recovery periods up to 12 months. Behavioral measures included locomotor coordination (beam balance, neuroscore) and memory and cognition assessments (Morris Water Maze: MWM) at multiple time-points. Gene arrays were performed using hippocampal and cortical samples to probe 45,610 genes. To reduce the high dimensionality of molecular and behavioral domains and uncover gene-behavior associations, we performed non-linear principal components analyses (NL-PCA), which de-noised the data. Genomic NL-PCA unveiled 3 interpretable eigengene components (PC2, PC3, PC4). Ingenuity pathway analysis (IPA) identified the PCs as an integrated stress response (PC2; EIF2-mTOR, corticotropin signaling, etc), inflammatory factor translation (PC3; PI3K-p70S6K signaling), and neurite growth inhibition (PC4; Rho pathways). Behavioral PCA revealed 3 principal components reflecting the contribution of MWM overall speed and distance, neuroscore/beam walk, and MWM platform measures. Integrating the genomic and behavioral domains, we then performed a ‘metaPCA’ on individual PC scores for each rat from genomic and behavioral PCAs. This metaPCA uncovered three unique multimodal PCs, characterized by robust associations between inflammatory/stress response and neuroscore/beam walk performance (metaPC1), stress response and MWM performance (metaPC2), and stress response with neuroscore/beam walk performance (metaPC3). Multivariate analysis of variance (MANOVA) on genomic-behavioral metaPC scores tested separately on cortex and hippocampal samples revealed main effects of TBI and recovery time. These findings are a proof-of-concept for the integration of disparate data domains for translational knowledge-discovery, harnessing the full syndromic space of TBI.