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Multi-omics to study chronic respiratory diseases and viral infections

  • Sobia Idrees
  • , Hao Chen
  • , Tayyaba Sadaf
  • , Saima Firdous Rehman
  • , Matt D. Johansen
  • , Keshav Raj Paudel
  • , Gang Liu
  • , Yuting Wang
  • , Malte D. Luecken
  • , Elinor Hortle
  • , Ashleigh S. Philp
  • , Kurtis F. Budden
  • , Matthew O'Rourke
  • , Gerard E. Kaiko
  • , Sionne E.M. Lucas
  • , Joanne L. Dickinson
  • , Peter C. Allen
  • , Joseph E. Powell
  • , Lai Ying Zhang
  • , Daniel C. Chambers
  • Tamera Corte, Gaetano Caramori, Maor Sauler, Peter A. Wark, Janine Gote-Schniering, Mareike Lehmann, Thomas M. Conlon, Theodore S. Kapellos, Ali Önder Yildirim, Rosa Faner, Shyamali C. Dharmage, Craig E. Wheelock, Maarten van den Berge, Martijn C. Nawijn, Francesca Polverino, Gabrielle T. Belz, Sanjay H. Chotirmall, Leopoldo N. Segal, Alen Faiz, Philip M. Hansbro
  • University of Technology Sydney
  • Institute of Computational Biology
  • Comprehensive Pneumology Center (CPC)
  • University of New South Wales
  • Hunter Medical Research Institute, Australia
  • University of Tasmania
  • Garvan Institute of Medical Research
  • University of Queensland
  • University of Parma
  • Yale University
  • Monash University
  • University of Bern
  • University of Marburg
  • Institute for Lung Health (ILH)
  • Ludwig Maximilian University of Munich
  • University of Barcelona
  • University of Melbourne
  • Karolinska Institutet
  • University of Groningen
  • Baylor College of Medicine
  • Tan Tock Seng Hospital
  • Nanyang Technological University
  • New York University

Research output: Contribution to journalReview articlepeer-review

3 Citations (Scopus)
8 Downloads (Pure)

Abstract

Despite recent advances, the underlying mechanisms of the development and progression of many chronic respiratory diseases remain to be elucidated. Factors such as heterogeneity and complexity of human diseases and difficulty interpreting large datasets hinder research into chronic respiratory diseases. Omics assesses the changes in specific biological entities, such as mRNA expression, epigenetics/epigenomics, genomics, proteomics, metagenomics and metabolomics, and provides valuable insights into the roles of these processes in chronic respiratory diseases. High-throughput omics at bulk, single-cell and spatial levels empower the exploration of disease-related changes through untargeted data-driven statistical methods. Multi-omics is the exploration and integration of multiple biological processes, which compared to a single-omics, can provide a substantially greater and more holistic overview of the pathogenic mechanisms that underpin complex diseases. Multi-omics analysis can comprehensively characterise the mechanisms that drive chronic respiratory diseases, capturing unique biological signatures and cellular interactions at different omics levels. Use of these methods has begun to identify key factors and biomarkers in chronic respiratory diseases. Here, we review current omics approaches and highlight recent advances in respiratory research achieved using multi-omics and integrative methods. Our review provides a valuable resource for researchers and clinicians in this area.

Original languageEnglish
Article number240286
Number of pages30
JournalEuropean respiratory review : an official journal of the European Respiratory Society
Volume35
Issue number179
DOIs
Publication statusPublished - Jan 2026
Externally publishedYes

Bibliographical note

Publisher Copyright:
© The authors 2026.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 3 - Good Health and Well-being
    SDG 3 Good Health and Well-being

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