Abstract
Introduction: The presence of a native (pre-existing) collateral circulation in tissues lessens injury in stroke and other occlusive diseases. However, differences in genetic background are accompanied by wide variation in the number and diameter (extent) of native collaterals in mice, resulting in large variation in protection. Indirect evidence suggests a similar wide variation also exists in humans. However, methods of measurement in humans are indirect, invasive and not widely available. Hypothesis: We sought to determine if differences in genetic background in mice result in variation in branch-patterning of the retinal circulation, and if these differences predict differences in collateral extent and, in turn, differences in severity of ischemic stroke. Methods: Patterning metrics were obtained for the retinal arterial trees of 10 mouse strains (n=8 per strain) that differ widely in collateral extent in brain and other tissues. We also obtained pial collateral number and diameter, and infarct volume 24h after permanent middle cerebral artery occlusion. Forward- and reverse-stepwise multivariate regression analysis was conducted and model performance assessed using K-fold cross-validation. Results: Twenty-one metrics varied significantly with genetic strain (p<0.01). Ten metrics (eg, vessel caliber, bifurcation angle, lacunarity, optimality, branch length) strongly predicted collateral number and diameter across 7 regression models. The best models closely predicted (p<0.0001) collateral number (K-fold R2 =0.83-0.98), diameter (0.73-0.88) and infarct volume (0.85-0.87). Conclusions: Differences in retinal tree patterning are specified by genetic background and closely predict genetic variation in pial collateral extent and, in turn, stroke severity. If these findings can be confirmed in humans, and given that genetic variation in cerebral collaterals extends to other tissues at least in mice, a similar “retinal predictor index” could be developed as a biomarker for collateral extent in brain and other tissues. This could aid prediction of the risk-severity of tissue injury in occlusive disease as well as stratification of patients for treatment options and enrollment in clinical studies.
Published Version
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