Routine omics collection is a golden opportunity for European human research in space and analog environments

Cope, Henry; Willis, Craig R.G.; MacKay, Matthew J.; Rutter, Lindsay A.; Toh, Li Shean; Williams, Philip M.; Herranz, Raúl; Borg, Joseph; Bezdan, Daniela; Giacomello, Stefania; Muratani, Masafumi; Mason, Christopher E.; Etheridge, Timothy; Szewczyk, Nathaniel J.

Abstract

Widespread generation and analysis of omics data have revolutionized molecular medicine on Earth, yet its power to yield new mechanistic insights and improve occupational health during spaceflight is still to be fully realized in humans. Nevertheless, rapid technological advancements and ever-regular spaceflight programs mean that longitudinal, standardized, and cost-effective collection of human space omics data are firmly within reach. Here, we consider the practicality and scientific return of different sampling methods and omic types in the context of human spaceflight. We also appraise ethical and legal considerations pertinent to omics data derived from European astronauts and spaceflight participants (SFPs). Ultimately, we propose that a routine omics collection program in spaceflight and analog environments presents a golden opportunity. Unlocking this bright future of artificial intelligence (AI)-driven analyses and personalized medicine approaches will require further investigation into best practices, including policy design and standardization of omics data, metadata, and sampling methods.

Citation

Cope, H., Willis, C. R., MacKay, M. J., Rutter, L. A., Toh, L. S., Williams, P. M., …Szewczyk, N. J. (2022). Routine omics collection is a golden opportunity for European human research in space and analog environments. Patterns, 3(10), Article 100550. https://doi.org/10.1016/j.patter.2022.100550

• Journal Article Type: Article
• Acceptance Date: Jun 17, 2022
• Online Publication Date: Jul 29, 2022
• Publication Date: Oct 14, 2022
• Deposit Date: Aug 8, 2022
• Publicly Available Date: Aug 10, 2022
• Journal: Patterns
• Electronic ISSN: 2666-3899
• Publisher: Elsevier BV
• Peer Reviewed: Peer Reviewed
• Volume: 3
• Issue: 10
• Article Number: 100550
• DOI: https://doi.org/10.1016/j.patter.2022.100550
• Keywords: General Decision Sciences
• Public URL: https://nottingham-repository.worktribe.com/output/9589443
• Publisher URL: https://www.cell.com/patterns/fulltext/S2666-3899(22)00155-6?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS2666389922001556%3Fshowall%3Dtrue