3-Dimensional morphological characterization of neuroretinal microglia in Alzheimer's disease via machine learning.

Alzheimer's Disease (AD) is a debilitating neurodegenerative disease that affects 47.5 million people worldwide. AD is characterised by the formation of plaques containing extracellular amyloid-β (Aβ) and neurofibrillary tangles composed of hyper-phosphorylated tau proteins (pTau). Aβ gradually accumulates in the brain up to 20 years before the clinical onset of dementia, making it a compelling candidate for early detection of AD. It has been shown that there is increased deposition of Aβs in AD patients' retinas. However, little is known about microglia's ability to function and clear Aβ within the retina of AD and control eyes. We labelled microglia with ionised calcium-binding adaptor molecule 1 (IBA-1) in AD and age-matched control donor retinas. We then used interactive machine learning to segment individual microglia in 3D. In the temporal mid-peripheral region, we found that the number of microglia was significantly lower in AD retinas compared to controls. Unexpectedly, the size of the microglia was significantly larger in the AD retinas compared to controls. We also labelled retinal microglia for Cluster of Differentiation 68 (CD68), a transmembrane glycoprotein expressed by cells in the monocyte lineage and a marker of phagocytic activity and activated microglia. The size of CD68 + cells was statistically different between AD and control microglial, with CD68 + cells being larger in AD. In contrast, there was no difference in either size or shape for CD68- microglia between the two groups, suggesting an important difference in the active states of CD68 + microglia in AD retina. There was also significantly increased CD68 immunoreactivity in individual microglia within the AD group. Overall, this study reveals unique differences in the size and activity of the retinal microglia, which may relate to their potential chronic activation due to increased levels of Aβs in the AD retina.