Tackling the Translational Challenges of Multi-omics Research in the Realm of European Personalised Medicine: A Workshop Report

Overview

Journal Front Mol Biosci

Specialty Biology

Date 2022 Oct 31

PMID 36310597

Authors

Emanuela Oldoni

Gary Saunders

Florence Bietrix

Maria Laura Garcia Bermejo

Anna Niehues

Peter A C t Hoen

Jessica Nordlund

Marian Hajduch

Andreas Scherer

Katja Kivinen

Esa Pitkanen

Tomi Pekka Makela

Ivo Gut

Serena Scollen

Lukasz Kozera

Manel Esteller

Leming Shi

Anton Ussi

Antonio L Andreu

Alain J van Gool

Affiliations

Soon will be listed here.

Abstract

Personalised medicine (PM) presents a great opportunity to improve the future of individualised healthcare. Recent advances in -omics technologies have led to unprecedented efforts characterising the biology and molecular mechanisms that underlie the development and progression of a wide array of complex human diseases, supporting further development of PM. This article reflects the outcome of the 2021 EATRIS-Plus Multi-omics Stakeholder Group workshop organised to 1) outline a global overview of common promises and challenges that key European stakeholders are facing in the field of multi-omics research, 2) assess the potential of new technologies, such as artificial intelligence (AI), and 3) establish an initial dialogue between key initiatives in this space. Our focus is on the alignment of agendas of European initiatives in multi-omics research and the centrality of patients in designing solutions that have the potential to advance PM in long-term healthcare strategies.

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References

Corpas M, Kovalevskaya N, McMurray A, Nielsen F . A FAIR guide for data providers to maximise sharing of human genomic data. PLoS Comput Biol. 2018; 14(3):e1005873. PMC: 5854239. DOI: 10.1371/journal.pcbi.1005873. View

Lubin I, Aziz N, Babb L, Ballinger D, Bisht H, Church D . Principles and Recommendations for Standardizing the Use of the Next-Generation Sequencing Variant File in Clinical Settings. J Mol Diagn. 2017; 19(3):417-426. PMC: 5417043. DOI: 10.1016/j.jmoldx.2016.12.001. View

Karczewski K, Snyder M . Integrative omics for health and disease. Nat Rev Genet. 2018; 19(5):299-310. PMC: 5990367. DOI: 10.1038/nrg.2018.4. View

Davies H, Bignell G, Cox C, Stephens P, Edkins S, Clegg S . Mutations of the BRAF gene in human cancer. Nature. 2002; 417(6892):949-54. DOI: 10.1038/nature00766. View

Vlahou A, Hallinan D, Apweiler R, Argiles A, Beige J, Benigni A . Data Sharing Under the General Data Protection Regulation: Time to Harmonize Law and Research Ethics?. Hypertension. 2021; 77(4):1029-1035. PMC: 7968961. DOI: 10.1161/HYPERTENSIONAHA.120.16340. View

Sadee W . Genomics and personalized medicine. Int J Pharm. 2011; 415(1-2):2-4. DOI: 10.1016/j.ijpharm.2011.04.048. View

Aslam B, Basit M, Nisar M, Khurshid M, Rasool M . Proteomics: Technologies and Their Applications. J Chromatogr Sci. 2017; 55(2):182-196. DOI: 10.1093/chromsci/bmw167. View

Adamo J, Bienvenu 2nd R, Fields F, Ghosh S, Jones C, Liebman M . The integration of emerging omics approaches to advance precision medicine: How can regulatory science help?. J Clin Transl Sci. 2019; 2(5):295-300. PMC: 6390395. DOI: 10.1017/cts.2018.330. View

Panahiazar M, Taslimitehrani V, Jadhav A, Pathak J . Empowering Personalized Medicine with Big Data and Semantic Web Technology: Promises, Challenges, and Use Cases. Proc IEEE Int Conf Big Data. 2015; 2014:790-795. PMC: 4333680. DOI: 10.1109/BigData.2014.7004307. View

10.

Adamo J, Bienvenu Ii R, Dolz F, Liebman M, Nilsen W, Steele S . Translation of Digital Health Technologies to Advance Precision Medicine: Informing Regulatory Science. Digit Biomark. 2020; 4(1):1-12. PMC: 7204775. DOI: 10.1159/000505289. View

11.

Berger M, Mardis E . The emerging clinical relevance of genomics in cancer medicine. Nat Rev Clin Oncol. 2018; 15(6):353-365. PMC: 6658089. DOI: 10.1038/s41571-018-0002-6. View

12.

Abul-Husn N, Kenny E . Personalized Medicine and the Power of Electronic Health Records. Cell. 2019; 177(1):58-69. PMC: 6921466. DOI: 10.1016/j.cell.2019.02.039. View

13.

Olivier M, Asmis R, Hawkins G, Howard T, Cox L . The Need for Multi-Omics Biomarker Signatures in Precision Medicine. Int J Mol Sci. 2019; 20(19). PMC: 6801754. DOI: 10.3390/ijms20194781. View

14.

Saunders G, Baudis M, Becker R, Beltran S, Beroud C, Birney E . Leveraging European infrastructures to access 1 million human genomes by 2022. Nat Rev Genet. 2019; 20(11):693-701. PMC: 7115898. DOI: 10.1038/s41576-019-0156-9. View

15.

Jandoo T . WHO guidance for digital health: What it means for researchers. Digit Health. 2020; 6:2055207619898984. PMC: 6952850. DOI: 10.1177/2055207619898984. View

16.

Wenk M . The emerging field of lipidomics. Nat Rev Drug Discov. 2005; 4(7):594-610. DOI: 10.1038/nrd1776. View

17.

Kalisky T, Oriel S, Bar-Lev T, Ben-Haim N, Trink A, Wineberg Y . A brief review of single-cell transcriptomic technologies. Brief Funct Genomics. 2017; 17(1):64-76. DOI: 10.1093/bfgp/elx019. View

18.

Glaab E, Rauschenberger A, Banzi R, Gerardi C, Garcia P, Demotes J . Biomarker discovery studies for patient stratification using machine learning analysis of omics data: a scoping review. BMJ Open. 2021; 11(12):e053674. PMC: 8650485. DOI: 10.1136/bmjopen-2021-053674. View

19.

Chen R, Snyder M . Promise of personalized omics to precision medicine. Wiley Interdiscip Rev Syst Biol Med. 2012; 5(1):73-82. PMC: 4154620. DOI: 10.1002/wsbm.1198. View

20.

Krassowski M, Das V, Sahu S, Misra B . State of the Field in Multi-Omics Research: From Computational Needs to Data Mining and Sharing. Front Genet. 2020; 11:610798. PMC: 7758509. DOI: 10.3389/fgene.2020.610798. View