Molecular Networks Underlying Resilience to Alzheimer's Disease Among APOE E4 Carriers

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PROJECT SUMMARY/ABSTRACT The e4 allele of the Apolipoprotein E (ApoE) gene has been identified as one of the strongest genetic determinants of late-onset Alzheimer’s disease (AD). In general, the e4 allele is associated with reductions in neural protection and repair, increasing a carrier’s vulnerability to damage accumulated over his/her lifetime. Nevertheless, while the penetrance of ApoE e4 is relatively high, a significant proportion of e4 carriers will never develop AD. The overall goal of this project is to model interactions across multiple omics networks to identify the biological pathways involved in sporadic AD susceptibility versus resilience among high-risk individuals. The multifactorial nature of AD suggests that it may manifest as a result of complex interactions across the genome, epigenome, transcriptome, and proteome. Identifying the central networks involved in AD pathogenesis will require integrative Systems Biology approaches. The proposed research offers a new and innovative way to integrate networks—a dominant feature in biology—across multiple tissues and omics platforms, in order to identify innate and dynamic precursors of resilience to AD, among a high-risk population (e4+). Towards this goal, we will: (1) employ newly developed GWAS-based network analysis, to identify SNP networks that alter the association between ApoE e4 and cognitive decline/dementia; (2) generate DNA methylation and RNA-seq data from brain samples that we will analyze using weighted gene correlation network analysis (WGCNA) to identify networks associated with AD neuropathology and cognitive decline among ApoE e4+; (3) generate proteomic data from brain and CSF samples that we will analyze using WGCNA to identify networks associated with AD neuropathology and cognitive decline among ApoE e4+; (4) use advanced integromic network analysis to identify multi-omics and multi-tissue pathways and biological systems involved in AD resilience. The integration of multiple 'omics' data using systems biology will be crucial for unraveling the connections and interactions between various functional levels involved in complex diseases, such as AD. Overall, our proposed research will improve understanding of the complex biology underlying AD susceptibility. These studies have the potential to identify novel therapeutic targets that could inform the development of future pharmacologic interventions aimed at preventing or slowing AD pathogenesis.