Computational Techniques and Resources for Effective Translational Research in Alzheimer's Disease

PROJECT SUMMARY / ABSTRACT Alzheimer’s Disease (AD) is a complex and heterogenous disorder characterized by multiple clinical, neuropathological and molecular phenotypes. Despite considerable effort to date, there is currently a lack of interventions or cure, thus there is a clear need for a better understanding of the heterogenous disease

phenotypes and the underlying genetics to identify more effective preclinical strategies. Rapidly expanding genomic, transcriptomic, proteomic, metabolomic and epigenomic data sets, and emerging animal models of AD created by the Model Organism Development and Evaluation for Late-Onset Alzheimer’s Disease (MODEL-AD)

consortium, now provide new tools for accelerating our understanding of AD and enable interspecies analysis for mapping findings from mouse model systems of AD to human omics signatures. While multi-omics data sets derived from AD and animal models of AD are available to the scientific community through various data

ecosystems including the AD Knowledge Portal, a NIA designated FAIR (Findable, Accessible, Interoperable, and Reusable) data repository, a current barrier is mapping disease relevant molecular signatures between model organisms and humans. Thus, there is an emerging need to provide training in bioinformatics

methodologies for systematic interspecies translation of omics-derived signatures of AD. To address this need, we aim to provide a new, and increasingly diverse, generation of researchers, with awareness of available resources and to provide skills development for integrating multi-scale data from model systems and humans to

advance AD research and interventions. We propose a unique, annual, 4-day workshop at The Jackson Laboratory (JAX), that will leverage trainers and expertise from Sage Bionetwork, the host institution for The AD Knowledge Portal and Exceptional Longevity Data Management and Coordinating Center, and the MODEL-AD

Center at JAX. The proposed workshop, Computational Techniques and Resources for Effective Translational Research in Alzheimer’s Disease, will focus on enabling utilization of omics-driven computational techniques and analytical principles for cross species functional alignment. Active learning programming sessions will be

the core of the workshop, in combination with lectures and interactive forums. Participants will emerge from the workshop equipped with the knowledge and technical skills to conduct rigorous and reproducible computational research for more effective translational strategies in AD. To achieve this, we propose the following aims: 1)

foster utilization of existing data resources from human and model organism studies in AD; 2) deliver hands-on training on computational techniques that reinforce rigor and reproducibility principles for translational AD research, and; 3) create an inclusive environment for trainees that fosters networking, collaboration, and

experiential learning. Pro-active strategies, including provision of scholarships, will be employed to recruit participants from historically minoritized and disadvantaged backgrounds to gain their input, provide equitable educational opportunities, and to enhance future representation in the AD field.