Large-Scale Multivariate Analysis to Interrogate an Animal Model of Stroke: Novel Insights into Poststroke Pathology

Shenpeng R. Zhang, Hyun Ah Kim, Hannah X. Chu, Seyoung Lee, Megan A. Evans, Xia Li, Henry Ma, Grant R. Drummond, Christopher G. Sobey, Thanh G. Phan

Research output: Contribution to journalArticlepeer-review

Abstract

Background and Purpose: Preclinical stroke studies endeavor to model the pathophysiology of clinical stroke, assessing a range of parameters of injury and impairment. However, poststroke pathology is complex and variable, and associations between diverse parameters may be difficult to identify within the usual small study designs that focus on infarct size. Methods: We have performed a retrospective large-scale big data analysis of records from 631 C57BL/6 mice of either sex in which the middle cerebral artery was occluded by 1 of 5 surgeons either transiently for 1 hour followed by 23-hour reperfusion (transient middle cerebral artery occlusion [MCAO]; n=435) or permanently for 24 hours without reperfusion (permanent MCAO; n=196). Analyses included a multivariate linear mixed model with random intercept for different surgeons as a random effect to reduce type I and type II errors and a generalized ordinal regression model for ordinal data when random effects are low. Results: Analyses indicated that brain edema volume was associated with infarct volume at 24 hours (β, 0.52 [95% CI, 0.45-0.59]) and was higher after permanent MCAO than after transient MCAO (P<0.05). A more severe clinical score was associated with a greater infarct volume but not with the animal's age or edema volume. Further, a more severe clinical score was observed for a given brain infarct volume after transient MCAO versus permanent MCAO. Remarkably the animal's age, which corresponded with the period of young adulthood (6-40 weeks; equivalent to ≈18-35 years in humans), was positively associated with severity of lung infection (β, 0.65 [95% CI, 0.42-0.88]) and negatively with spleen weight (β, -0.36 [95% CI, -0.63 to -0.09]). Conclusions: Large-scale analysis of preclinical stroke data can provide researchers in our field with insight into relationships between variables not possible if individual studies are analyzed in isolation and has identified hypotheses for future study.

Original languageEnglish
Pages (from-to)3661-3669
Number of pages9
JournalStroke
Volume52
Issue number11
DOIs
Publication statusPublished - 1 Nov 2021
Externally publishedYes

Keywords

  • infarction
  • infections
  • ischemic stroke
  • multivariate analysis
  • surgeons

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