Utilizing gene-level biomarkers of AD to identify pathophysiological mechanisms in human neurons

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Abstract Summary Recent advances AD therapeutics increases the urgency to identify individuals at risk for developing Alzheimer’s disease (AD). This effort can likely be accelerated using stem cell biology approaches which have led to the ability to generate human induced neurons (HiN) directly from easily obtainable patient cells such as fibroblasts. This serves as a powerful tool for studying aging and disease-related processes in clinically relevant cell types. Meta-analysis studies of existing transcriptomic databanks from AD patients and healthy individuals without dementia (nonAD) have also provided new insight into underlying pathophysiological drivers contributing to a diagnosis of AD. While these gene expression profiles have been identified for AD risk which carryover from the individual to their directly transformed neurons (human induced neuron, HiN). This is a crucial missing link needed to capture the physiological outcomes of these gene network profiles in order to identify associated mechanisms of metabolic stress, pathological protein aggregation and synaptic pathophysiology – all key features of AD. Therefore, we will apply neurophysiological and cellular functional analyses to HiNs derived from representative individuals diagnosed with sporadic or familial AD, as well as age/sex-matched nonAD controls, to identify functional consequences of these genomic variations in the human population. Our overall objective is to identify gene-pathway based biomarkers or risk factors for AD and define the neuronal pathophysiological phenotypes associated with these gene pathways. We will test the hypothesis that synaptic signaling, metabolism and protein handling processes in neurons derived from the AD population will reflect the alterations in gene pathways that distinguish healthy aging processes from AD pathogenesis, and thus can serve as important biomarkers. In Aim 1 we will identify mitochondrial functional deficits associated with alterations in glucose metabolism gene pathways in AD. In Aim 2 we will identify pathological manifestations of altered gene pathways regulating autophagy and protein mishandling in AD patients. In Aim 3 we will identify neurophysiological and synaptic signaling effects corresponding with altered gene networks in AD that underlie cognitive decline. The combination of our expertise in induced neuron production as well as bioinformatics and neurophysiology assays makes this a powerful and innovative proposal that will provide important insights into risk factors and biomarkers of AD. This comes at a crucial time in the AD field where it is imperative to identify at risk individuals early in order to maximize benefits of new therapeutics becoming available.