Dissecting Alzheimer’s Disease Phenotypes in Directly Reprogrammed Patient-Derived Neurons

Alzheimer’s disease (AD) is a neurodegenerative disorder in which aging plays a significant role as a risk factor. Understanding why aged human neurons become vulnerable to neurodegeneration can offer important insights into AD pathogenesis. To this end, generating human neurons that reflect the age of elderly individuals can help investigate the cellular factors underlying the onset of neuropathology. Our laboratory has pioneered the use of small RNA molecules known as microRNAs (miRNAs) to convert (reprogram) skin fibroblast cells directly into neurons. These miRNAs alter the genome architecture of fibroblasts, effectively erasing their identity and inducing a neuronal state. One key advantage of this approach is that the directly reprogrammed neurons retain the age signature from the original fibroblasts, thereby producing neurons that mirror the age of the donor. We have applied the miRNA-based neuronal reprogramming to model AD by directly converting patient-derived fibroblasts into cortical neurons. These neurons display hallmark neuropathological features of AD, such as extracellular deposition of amyloid beta (Aβ), formation of insoluble tau in dystrophic neurites and neurodegeneration. In the current Cure Alzheimer’s Fund proposal, we outline two research aims that will further our current effort in modeling AD. In Aim 1, we will develop reprogramming approaches to generate different subtypes of human neurons. We then will examine how AD neuropathology varies between different neuronal types derived from the same patient samples. In Aim 2, we will investigate changes in the genome architecture in AD neurons. Specifically, we aim to investigate epigenetic dysregulation in neurons affected by sporadic late-onset AD, in comparison with neurons from age- and sex-matched controls. Achieving these two goals will offer insights into different types of human neurons showing varying susceptibility to AD, and how changes in genome organization correlate with AD-associated neurodegeneration.