Harnessing Genetics, Genomics, Endophenotype, and Network Medicine for Alzheimer's Disease Target and Drug Discovery

Department of Computational Biology

Featuring Dr. Feixiong Cheng, Director, Genome Center, Cleveland Clinic
 

High-throughput DNA/RNA sequencing technologies have rapidly led to a robust body of genetic and genomic data in multiple national Alzheimer’s disease (AD) genome projects, such as the Alzheimer’s Disease Sequencing Project (ADSP) and the Alzheimer’s Disease Neuroimaging Initiative (ADNI); however, the predisposition to AD involves a complex, polygenic, and pleiotropic genetic architecture. Recent advances in genetics and systems biology have suggested that AD is governed by network-associated molecular determinants (termed disease module) of common endotypes or endophenotypes (e.g., Amyloid, Tau, and Microglial activation). Approaching AD with a simplistic single-target approach has been demonstrated effective for developing symptomatic therapies but ineffective when attempted for disease modification. Therapeutic approaches by specifically modulating genetic risk genes are essential for development of disease-modifying treatments in AD. However, existing data, including genomics, transcriptomics, proteomics, and interactomics (protein-protein interactions [PPIs]), have not yet been fully utilized and integrated to explore the roles of targeted therapeutic development for AD. Understanding AD from the point-of-view of how human protein interactome perturbations underlie the disease is the essence of network medicine. The main hypothesis of the AD network medicine is that cellular networks altered by genetic variants gradually rewire throughout disease pathogenesis and progression. Systematic identification and characterization of underlying AD pathogenesis and disease modules will serve as a foundation for identifying disease-modifying targets for AD. Integration of the genome, transcriptome, proteome, and the human interactome are essential for such identification. This seminar will introduce protein-protein interactome network-based, multimodal omics analytic technologies established by Cheng’s lab to identify novel drug targets and existing drugs for Alzheimer’s disease. Dr. Cheng will illustrate how his team combines tools from artificial intelligence (AI), network medicine, endophenotype models, multi-omics (GWAS, genomics, transcriptomics, and proteomics), electronic health records (EHRs), and experimental models (including patient iPSC-derived and transgenic animal models) to identify potential drug targets and repurposable drugs using Alzheimer’s disease as a prototypical example.

Seminar Host: Dr. Haiyuan Yu