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500 The Aging Exposome: Characterizing Bidirectional Effects of Exposures and Aging

Published online by Cambridge University Press:  24 April 2023

Ram Gouripeddi
Affiliation:
University of Utah
Caden Stewart
Affiliation:
University of Utah
Julio Facelli
Affiliation:
University of Utah
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Abstract

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OBJECTIVES/GOALS: The objective of this study is to synthetically generate and use records of exposure, and so that we can understand the effects of exposure on aging and vice-versa. METHODS/STUDY POPULATION: Quantifying bidirectional effects of environment and aging requires time series of data from all contributing exposures which can span endogenous processes within the body, biological responses of adaptation to environment, and socio-behavioral factors. Gaps in measured data may need to be filled with computationally modeled data. Essentially, the challenge in generating aging exposome is the absence of readily available records for individuals over the course of their life. Instead, these would need to be assimilated from historic person reported data (e.g. residential location, durations, behaviors) along with publically available data. This could lead to potential gaps and uncertainties that would need inform on how the exposomic records can be used for aging research. RESULTS/ANTICIPATED RESULTS: We present a pragmatic approach to generation of longitudinal exposomic and aging records as required for different study archetypes. Such records can then be used to understand the bidirectional effects of exposures and aging. DISCUSSION/SIGNIFICANCE: Effects of a lifetime of environmental and lifestyle exposures on aging or age-associated diseases are not well understood. Characterizing differential, additive and intense sporadic multi-agent exposures require advanced big data and artificial intelligence methods.

Type
Other
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s), 2023. The Association for Clinical and Translational Science