Systems biology and big data in asthma and allergy: recent discoveries and emerging challenges.

Autor:	Tang HHF; Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia Howard.Tang@baker.edu.au.; Cambridge Baker Systems Genomics Initiative, Dept of Public Health and Primary Care, University of Cambridge, Cambridge, UK.; School of BioSciences, The University of Melbourne, Parkville, Australia., Sly PD; Queensland Children's Medical Research Institute, The University of Queensland, Brisbane, Australia.; Telethon Kids Institute, University of Western Australia, Perth, Australia., Holt PG; Queensland Children's Medical Research Institute, The University of Queensland, Brisbane, Australia.; Telethon Kids Institute, University of Western Australia, Perth, Australia., Holt KE; Dept of Infectious Diseases, Central Clinical School, Monash University, Melbourne, Australia.; London School of Hygiene and Tropical Medicine, London, UK., Inouye M; Cambridge Baker Systems Genomics Initiative, Baker Heart and Diabetes Institute, Melbourne, Australia.; Cambridge Baker Systems Genomics Initiative, Dept of Public Health and Primary Care, University of Cambridge, Cambridge, UK.; School of BioSciences, The University of Melbourne, Parkville, Australia.; The Alan Turing Institute, London, UK.
Jazyk:	angličtina
Zdroj:	The European respiratory journal [Eur Respir J] 2020 Jan 09; Vol. 55 (1). Date of Electronic Publication: 2020 Jan 09 (Print Publication: 2020).
DOI:	10.1183/13993003.00844-2019
Abstrakt:	Asthma is a common condition caused by immune and respiratory dysfunction, and it is often linked to allergy. A systems perspective may prove helpful in unravelling the complexity of asthma and allergy. Our aim is to give an overview of systems biology approaches used in allergy and asthma research. Specifically, we describe recent "omic"-level findings, and examine how these findings have been systematically integrated to generate further insight.Current research suggests that allergy is driven by genetic and epigenetic factors, in concert with environmental factors such as microbiome and diet, leading to early-life disturbance in immunological development and disruption of balance within key immuno-inflammatory pathways. Variation in inherited susceptibility and exposures causes heterogeneity in manifestations of asthma and other allergic diseases. Machine learning approaches are being used to explore this heterogeneity, and to probe the pathophysiological patterns or "endotypes" that correlate with subphenotypes of asthma and allergy. Mathematical models are being built based on genomic, transcriptomic and proteomic data to predict or discriminate disease phenotypes, and to describe the biomolecular networks behind asthma.The use of systems biology in allergy and asthma research is rapidly growing, and has so far yielded fruitful results. However, the scale and multidisciplinary nature of this research means that it is accompanied by new challenges. Ultimately, it is hoped that systems medicine, with its integration of omics data into clinical practice, can pave the way to more precise, personalised and effective management of asthma. Competing Interests: Conflict of interest: H.H.F. Tang has nothing to disclose. Conflict of interest: P.D. Sly has nothing to disclose. Conflict of interest: P.G. Holt has nothing to disclose. Conflict of interest: K.E. Holt has nothing to disclose. Conflict of interest: M. Inouye has nothing to disclose. (Copyright ©ERS 2020.)
Databáze:	MEDLINE
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