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Systems Biology in Asthma

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Precision Approaches to Heterogeneity in Asthma

Part of the book series: Advances in Experimental Medicine and Biology ((AEMB,volume 1426))

Abstract

The application of mathematical and computational analysis, together with the modelling of biological and physiological processes, is transforming our understanding of the pathophysiology of complex diseases. This systems biology approach incorporates large amounts of genomic, transcriptomic, proteomic, metabolomic, breathomic, metagenomic and imaging data from disease sites together with deep clinical phenotyping, including patient-reported outcomes. Integration of these datasets will provide a greater understanding of the molecular pathways associated with severe asthma in each individual patient and determine their personalised treatment regime. This chapter describes some of the data integration methods used to combine data sets and gives examples of the results obtained using single datasets and merging of multiple datasets (data fusion and data combination) from several consortia including the severe asthma research programme (SARP) and the Unbiased Biomarkers Predictive of Respiratory Disease Outcomes (U-BIOPRED) consortia. These results highlight the involvement of several different immune and inflammatory pathways and factors in distinct subsets of patients with severe asthma. These pathways often overlap in patients with distinct clinical features of asthma, which may explain the incomplete or no response in patients undergoing specific targeted therapy. Collaboration between groups will improve the predictions obtained using a systems medicine approach in severe asthma.

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Abbreviations

DEG:

Differentially expressed genes

DIABLO:

Data Integration Analysis for Biomarker discovery using Latent Components

eNOSE:

Electronic nose

GC-MS:

Gas chromatography-mass spectroscopy

GSEA:

Gene set enrichment analysis

GSVA:

Gene set variation analysis

HBEC:

Human bronchial epithelial cells

IFN:

Interferon

IL:

Interleukin

ILC:

Innate lymphoid cells

IMI:

European Union Innovative Medicines Initiative

MDS:

Multi-dimensional scaling

OCS:

Oral corticosteroids

PCA:

Principal components analysis

RNA-seq:

RNA sequencing

ROC:

Receiver operator curve

SARP:

Severe asthma research program

SNF:

Similarity network fusion

T1:

Type 1 inflammation

T2:

Type 2 inflammation

TAC:

Transcriptome-associated clusters

TDA:

Topological data analysis

TopMD:

Topological analysis of omics data

U-BIOPRED:

Unbiased Biomarkers Predictive of Respiratory Disease Outcomes

VOC:

Volatile organic compounds

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Authors and Affiliations

  1. Data Science Institute, Imperial College London, London, UK

    Nazanin Zounemat Kermani

  2. National Heart & Lung Institute, Imperial College London, London, UK

    Nazanin Zounemat Kermani, Ian M. Adcock & Fan Chung

  3. NIHR Southampton Biomedical Research Centre, Clinical and Experimental Sciences, Faculty of Medicine, University of Southampton, Southampton, UK

    Ratko Djukanović

  4. Biomedical Research Unit, Royal Brompton & Harefield NHS Trust, London, UK

    Fan Chung

  5. Centre for Proteomic Research, Institute for Life Sciences, University of Southampton, Southampton, UK

    James P. R. Schofield

  6. TopMD Precision Medicine Ltd, Southampton, UK

    James P. R. Schofield

Authors
  1. Nazanin Zounemat Kermani
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  2. Ian M. Adcock
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  3. Ratko Djukanović
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  4. Fan Chung
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  5. James P. R. Schofield
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Corresponding author

Correspondence to Ratko Djukanović .

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Editors and Affiliations

  1. Department of Medicine, Division of Endocrinology Institute for Clinical and Translational Research, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA

    Allan R. Brasier

  2. Department of Medicine, Division of Allergy, Pulmonary and Critical Care, University of Wisconsin School of Medicine and Public Health, Madison, WI, USA

    Nizar N. Jarjour

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Kermani, N.Z., Adcock, I.M., Djukanović, R., Chung, F., Schofield, J.P.R. (2023). Systems Biology in Asthma. In: Brasier, A.R., Jarjour, N.N. (eds) Precision Approaches to Heterogeneity in Asthma. Advances in Experimental Medicine and Biology, vol 1426. Springer, Cham. https://doi.org/10.1007/978-3-031-32259-4_10

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