Artificial Intelligence Based Methods to Identify Molecular Determiners of Exceptional Life and Health-An Interdisciplinary Workshop at the National Institute on Aging
Artificial intelligence (AI), a powerful tool for integrated analysis, has been developed to analyze the growing volume of data from multi-omics. This includes many clinical and research tasks like predicting disease risk or identifying potential therapeutic targets. AI has the potential to identify factors that contribute to exceptional human health and longevity, and translate these into novel interventions to enhance health and lifespan. However, this potential is not yet realized. Researchers on aging are accumulating large-scale data, both from human cohorts and models organisms. As a result, there is an opportunity to apply AI techniques in order to unravel the complex physiologic processes that modulate health. The use of new data mining techniques that can unravel the molecular mechanisms that are associated with healthy aging and long life expectancy could speed up the discovery of new therapeutics. In August 2018, the National Institute on Aging convened a workshop titled, \”Contributions of Artificial Intelligence in Research on Determinants of Health Spans and Life Spans\”. Experts in the fields related to aging, cancer, cardiology and computational science/AI participated in the workshop. They brainstormed on ways that AI could be used for the analysis of large data sets from human studies, animal models and comparative biology. This report summarizes discussions and recommendations made at the workshop regarding future applications of AI to improve our understanding of health and lifespan.
The aging process is described as the result of genetic, environmental, and lifestyle factors, with large variations in health and life spans between species and even within them (Newman et. al., 2013; Partridge, et. al. 2018; Singh, et. al., 2019. The extreme phenotype of exceptional life and health span is characterized by exceptionally long survival (well beyond the average life expectancy), delayed age-related disease onset (before 80 years old) (Pignolo 2019), and/or good health/function in comparison to peers (Perls, 2000,2002; Kaeberlein 2018). Identification of SNP associations that are associated with exceptional health and life span can be used to identify targets for interventions aimed at promoting healthy human aging.
Source:
https://www.frontiersin.org/articles/10.3389/frai.2019.00012/full
