Abstract P796: Integrated Analysis of Gait Parameters and Gene Expression Profiles in a Murine Model of Subarachnoid Hemorrhage

Abstract

Objective: Gait variability analysis has been adopted in clinical settings to characterize the presentation of various neurological diseases. However, literature and practice lack a comprehensive murine model assessment of the gait deficits that result from subarachnoid hemorrhage (SAH). Further, correlations between gait parameters and the gene expression profiles associated with SAH have yet to be identified. The present study quantitatively assesses gait deficits through a clinically relevant murine model of SAH to determine associations between gait deficits and SAH-related gene expressions. Methods: A total of 159 dynamic and static gait parameters from the endovascular perforation murine model for simulating clinical human SAH were measured using the CatWalk system. Pearson’s correlation analysis was applied, and 88 genes associated with SAH were identified from the Ingenuity Pathway Analysis database to aid the investigation of the relationship between gait variability and gene expression profiles. Results: Eighty gait parameters and the mRNA expression levels of 35 of the 88 SAH-associated genes exhibited significant change in the SAH models (p < 0.05). Totals of 42 and 38 gait parameters correlated with the 35 SAH-associated genes positively and negatively with Pearson’s correlation coefficients of > 0.7 and < -0.7, respectively. p-SP1 453 expression in the motor cortex in SAH animal models displays a significant correlation with a subset of gait parameters associated with muscular strength and coordination of limb movements. Conclusion: This examination of gait variability and its strong correlation to gene expression profiles provides a quantitative and reliable assessment of the SAH model’s motor performance. This research provides valuable insights into the study of disease progression and offers novel therapeutic interventions in the murine modeling of SAH. p-SP1 453 expression could act as a biomarker to monitor SAH pathological development and a therapeutic target for SAH.