Activated microglia density (top), hypertrophic astrocyte density (middle), and GFAP stain density (bottom), have different behaviors as plaque sizes increase. Plaque equivalent radius = √(area/π). Comparisons were performed using a two-way ANOVA and Tukey’s multiple comparisons test (3 pairwise comparisons). For simplicity, only the comparisons for plaques up to 40-50µm are shown. * p<0.05, ** p<0.01, *** p<0.001, **** p<0.0001.
The ratio of microglia to astrocytes in the proximity of plaques as a function of age. Plaque proximity here is < 10µm from the plaques. ** p<0.01, *** p<0.001.
We quantified the cellular microenvironment as a function of plaque size. We observed that activated microglia accumulate directly on or around the plaque, with a density that increases rapidly in small plaques and plateau as plaque size increases. In contrast, hypertrophic astrocytes accumulate further away from the plaques. In the larger plaques, the astrocytic response becomes more global, with density increasing at 40-50 microns and becomes comparable to the astrocyte density at 0 to 10 micrometers. In addition, the cell density directly on the plaque starts to decrease compared to medium sized plaques.
This downward trend was not observed in the GFAP stain density, suggesting that the soma, but not the processes, are excluded from the larger plaques.
Because astrocytes and microglia have different behaviors in larger plaques, which are predominantly found in older groups, we hypothesized that a metric based on this phenomenon could help differentiate the 9 months and 12 months groups. The ratio of microglia to astrocyte in the plaque proximity was higher in the 12 months group compared to the other disease groups. This was the only metric that showed a statistically significant difference between the 9 month and 12 month groups. While the other metrics, such as the amyloid-β and GFAP stain density, generally trended higher in the 12 months group, none showed a statistically significant change between the two older groups.
This analysis shows how quantifying astrocyte-microglia interactions can provide a powerful complementary metric of disease progression and be valuable in preclinical therapeutic efficacy studies.