P4‐670: DISCOVERING ALZHEIMER'S DISEASE NETWORKS IN ACCELERATING MEDICINES PARTNERSHIP – ALZHEIMER'S DISEASE DATASETS

Résumé fourni par la source

Despite decades of translation research in Alzheimer's Disease (AD) therapeutics, there are no drugs currently available to patients that modulate AD-pathology and slow cognitive decline. One challenge has been in creating animal models with reliable construct, face and predictive validity. Moreover, unlike mendelian diseases, sporadic AD is a complex-polygenic disease, where multiple pathways play a role in disease onset and progression, and analysis of multi-omics data holds promise in unraveling these pathways. Accelerated Medicine Partnership – Alzheimer's Disease (AMP-AD) data, derived from a consortium of academic and industry partners, represents one of the largest multi-omics datasets on Alzheimer's samples. NA. To address this, systems biology approaches were used to develop a consensus atlas of the human transcriptome through co-expression meta-analysis across AMP-AD consortium data sets. Using bulk-RNAseq data collected from 2114 postmortem samples across 7 brain regions and 3 research studies, 30 RNAseq network clusters (a.k.a. modules) were discovered from the consortia that represents transcriptional landscape of AD pathology in postmortem brain. We mapped AD-pathology traits such as amyloid plaques, tau-tangles & cognitive decline derived from Religious Order Study Memory and Aging Project (ROSMAP) RNAseq data to a co-expression network using MEGENA [4] and a protein-protein interaction (PPI) network of genes that are members of RNAseq modules recently published from AMP-AD consortia to identify modules representing proteostasis & neuroinflammation pathways using fisher-exact test. We identified two modules DLPFCBrown and CBEBrown, which are highly enriched for amyloid-associated genes. A deep-dive into these networks showed hot-spots of therapeutic interests for example, clusters of genes involved in different pathways e.g. Endocytosis, Lysosomes, Macroautophagy and E3 ligase and adapter proteins. In the study, we propose a prototype of the network analysis of AMP-AD derived network modules using Proteostasis Map (PMAP) network visualization tool. Our goal is to understand a target not only in terms of its disease association on its own, rather the context and connectivity of the gene with other differentially expressed genes.

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