PhD Student University of California, Berkeley Berkeley, North Carolina, United States
Abstract: Despite approximately 95% of Alzheimer’s Disease cases being sporadic, there is limited understanding of how genetic and environmental factors come together to drive disease development. Here, we explore how two key risk factors - stress and blood-brain barrier dysfunction (BBBD) - independently and jointly influence known AD pathways and potentially drive pathology. Previous research in AD patients and mouse models has shown that elevated stress hormones and increased BBBD both precede hallmark AD pathology, such as the accumulation of amyloid-β plaques, hyperphosphorylated tau tangles, and neurodegeneration. However, human studies are limited in their ability to examine these mechanisms at the cellular and molecular levels, and transgenic mouse models predominantly reflect the rarer familial form of AD and only partially replicate the complexity of the disease. To address this gap, we employ advanced stem cell-derived 3D brain organoid models to explore the potential causal relationship between stress, BBBD, and AD progression at both the tissue and cellular levels. In our disease model, we add cortisol to mature organoid culture to recaptulate chronic stress and supply prolonged exposure to serum albumin, a blood-borne protein that transverses the blood-brain barrier when it is dysfunctional, to model BBBD. Preliminary results from these brain organoids indicate that serum albumin affects AD-related biomarkers, including elevated Aβ, increased tau phosphorylation, and decreased synaptogenesis. These results are supported by 2D culture of neurons and glial cells, where initial data suggests that stress modulates neuronal vulnerability, with an increased effect observed in cells pretreated with cortisol before serum albumin exposure. These findings indicate that stress and BBBD may combine to drive AD pathology. By leveraging cutting-edge stem cell-derived 3D disease models, this research provides valuable insights into the cellular and tissue-level mechanisms that underlie AD. These findings have important implications for neurodegenerative disease modeling, early AD detection, and the identification of potential therapeutic targets.
