Age-dependent mechanisms of sporadic Alzheimer’s Disease in patient-derived neurons

ended

Sporadic Alzheimer’s Disease (AD) accounts for the overwhelming majority of all AD cases and exclusively affects people at old age. However, mechanistic links between aging and AD pathology remain elusive. We recently discovered that in contrast to iPSC models, direct conversion of human fibroblasts into induced neurons (iNs) preserves signatures of aging, and we have started to develop a patient-based iN model system for AD. Our preliminary data suggests that AD iNs show a neuronal but de-differentiated transcriptome signature. In this project, we first combine cellular neuroscience assays and epigenetic landscape profiling to understand how neurons in AD fail to maintain their fully mature differentiated state, which might be key in permitting disease development. Next, using metabolome analysis including mass spec metabolite assessment, we explore a profound metabolic switch in AD iNs that shows surprisingly many aspects of aerobic glycolysis observed also in cancer. While this link might represent an interesting connection between two age-dependent and de-differentiation-associated diseases, it also opens new avenues to harness knowledge from the cancer field to better understand sporadic AD. We further focus on identifying and manipulating key metabolic regulators that appear to malfunction in an age-dependent manner, with the ultimate goal to define potential targets and treatment strategies. Finally, we will focus on early AD mechanisms by extending our model to mild cognitive impairment (MCI) patients. An agnostic transcriptome and epigenetic landscape approach of glutamatergic and serotonergic iNs will help to determine the earliest and probably most treatable disease mechanisms of AD, and to better understand the contribution of neuropsychiatric risk factors. We anticipate that this project will help to illuminate the mechanistic interface of cellular aging and the development of AD, and help to define new strategies for AD.