Severity of stroke varies widely among individuals. Whether differences in the extent of the native (preexisting) pial collateral circulation exist and contribute to this variability is unknown. We addressed these questions and probed for potential genetic contributions using morphometric analysis of the collateral circulation in 15 inbred mouse strains recently shown to exhibit wide differences in infarct volume. Morphometrics were determined in the unligated left hemisphere (for native collaterals) and ligated right hemisphere (for remodeled collaterals) 6 days after permanent middle cerebral artery (MCA) occlusion. Variation among strains in native collateral number, diameter, MCA, anterior cerebral artery (ACA), and posterior cerebral artery (PCA) tree territories were, respectively: 56-fold, 3-fold, 42%, 56%, and 61%. Collateral length (P < 0.001) and the number of penetrating arterioles branching from them also varied (P < 0.05). Infarct volume correlated inversely with collateral number (P < 0.0001), diameter (P < 0.0001), and penetrating arteriole number (P < 0.05) and directly with MCA territory (P < 0.05). Relative collateral conductance and MCA territory, when factored together, strongly predicted infarct volume (P < 0.0001). Outward remodeling of collaterals in the ligated hemisphere varied B3-fold. These data show that the extent of the native pial collateral circulation and collateral remodeling after obstruction vary widely with genetic background, and suggest that this variability, due to natural polymorphisms, is a major contributor to variability in infarct volume.

Objective Aging is a major risk factor for increased ischemic tissue injury. Whether collateral rarefaction and impaired remodeling contribute to this is unknown. We quantified the number and diameter of native collaterals, and their remodeling in 3-, 16-, 24-, and 31-months-old mice. Methods and Results Aging caused an “age-dose-dependent” greater drop in perfusion immediately after femoral artery ligation, followed by a diminished recovery of flow and increase in tissue injury. These effects were associated with a decline in collateral number, diameter and remodeling. Angiogenesis was also impaired. Mechanistically, these changes were not accompanied by reduced recruitment of T-cells or macrophages to remodeling collaterals. However, eNOS signaling was dysfunctional, as indicated by increased protein nitrosylation and less phosphorylated eNOS and VASP in collateral wall cells. The cerebral circulation exhibited a similar age-dose-dependent loss of collateral number and diameter and increased tortuosity, resulting in an increase in collateral resistance and infarct volume (e.g., 6- and 3-fold, respectively, in 24-months-old mice) after artery occlusion. This was not associated with rarefaction of similarly-sized arterioles. Collateral remodeling was also reduced. Conclusions Our findings demonstrate that aging causes rarefaction and insufficiency of the collateral circulation in multiple tissues, resulting in more severe ischemic tissue injury.

The presence of a native collateral circulation in tissues lessens injury in occlusive vascular diseases. However, differences in genetic background cause wide variation in collateral number and diameter in mice, resulting in large variation in protection. Indirect estimates of collateral perfusion suggest wide variation also exists in humans. Unfortunately, methods used to obtain these estimates are invasive and not widely available. We sought to determine if differences in genetic background in mice result in variation in branch-patterning of the retinal arterial circulation, and if these differences predict strain-dependent differences in pial collateral extent and severity of ischemic stroke. Retinal patterning metrics, collateral extent, and infarct volume were obtained for 10 strains known to differ widely in collateral extent. Multivariate regression was conducted and model performance assessed using K-fold cross-validation. Twenty-one metrics varied with strain (p<0.01). Ten metrics (eg, bifurcation angle, lacunarity, optimality) predicted collateral number and diameter across 7 regression models, with the best model closely predicting (p<0.0001) number (± 1.2-3.4 collaterals, K-fold R2=0.83-0.98), diameter (± 1.2-1.9μm, R2=0.73-0.88) and infarct volume (± 5.1 mm3, R2=0.85-0.87). These metrics obtained for the middle cerebral artery tree in a subset of the above strains also predicted (p<0.0001) collateral number and diameter and diameter, although with less strength (K-fold R2=0.61-0.78) and 0.60-0.86, respectively). Thus, differences in arterial branch-patterning in the retina and the MCA trees are specified by genetic background and predict variation in collateral extent and stroke severity. If also true in human retina, and since genetic variation in cerebral collaterals extends to other tissues at least in mice, a similar “retinal predictor index” could serve as a non-or minimally invasive biomarker for collateral extent in brain and other tissues. This could aid prediction of severity of tissue injury in the event of an occlusive event or development of obstructive disease and in patient stratification for treatment options and clinical studies.

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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.