Network-based analysis reveals novel gene signatures in peripheral blood of patients with chronic obstructive pulmonary disease

Respiratory Research

Research

Peter J. Castaldi¹  Craig P. Hersh²  Stephen Rennard³  Bruce E. Miller⁴  Virginia Chen⁵  Raymond T. Ng⁵  Casey P. Shannon⁵  Bernett Lee⁶  Anand Kumar Andiappan⁶  Olaf Rotzschke⁶  Ma’en Obeidat⁷  Yunlong Nie⁷  Nick Fishbane⁷  Bruce McManus⁸  Peter D. Paré⁹  Don D. Sin⁹ 

[1] Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, USA;Division of General Internal Medicine and Primary Care, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA;Channing Division of Network Medicine, Brigham and Women’s Hospital, Boston, USA;Pulmonary and Critical Care Division, Brigham and Women’s Hospital and Harvard Medical School, Boston, USA;Division of Pulmonary and Critical Care Medicine, University of Nebraska Medical Center, Omaha, NE, USA;Clinical Discovery Unit, Early Clinical Development, AstraZeneca, Cambridge, UK;GlaxoSmithKline, King of Prussia, PA, USA;Prevention of Organ Failure (PROOF) Centre of Excellence, Vancouver, BC, Canada;Singapore Immunology Network, 8A Biomedical Grove, Singapore, Singapore;The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, 1081 Burrard Street, V6Z 1Y6, Vancouver, BC, Canada;The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, 1081 Burrard Street, V6Z 1Y6, Vancouver, BC, Canada;Prevention of Organ Failure (PROOF) Centre of Excellence, Vancouver, BC, Canada;The University of British Columbia Centre for Heart Lung Innovation, St Paul’s Hospital, 1081 Burrard Street, V6Z 1Y6, Vancouver, BC, Canada;Respiratory Division, Department of Medicine, University of British Columbia, Vancouver, BC, Canada;

关键词: COPD;    FEV;    Blood;    mRNA;    Gene expression;    Co-expression;    WGCNA;    Biomarker;    Transcriptome;   

DOI  :  10.1186/s12931-017-0558-1

 received in 2016-10-30, accepted in 2017-04-20,  发布年份 2017

来源: Springer

【 摘 要 】

BackgroundChronic obstructive pulmonary disease (COPD) is currently the third leading cause of death and there is a huge unmet clinical need to identify disease biomarkers in peripheral blood. Compared to gene level differential expression approaches to identify gene signatures, network analyses provide a biologically intuitive approach which leverages the co-expression patterns in the transcriptome to identify modules of co-expressed genes.MethodsA weighted gene co-expression network analysis (WGCNA) was applied to peripheral blood transcriptome from 238 COPD subjects to discover co-expressed gene modules. We then determined the relationship between these modules and forced expiratory volume in 1 s (FEV1). In a second, independent cohort of 381 subjects, we determined the preservation of these modules and their relationship with FEV1. For those modules that were significantly related to FEV1, we determined the biological processes as well as the blood cell-specific gene expression that were over-represented using additional external datasets.ResultsUsing WGCNA, we identified 17 modules of co-expressed genes in the discovery cohort. Three of these modules were significantly correlated with FEV1 (FDR < 0.1). In the replication cohort, these modules were highly preserved and their FEV1 associations were reproducible (P < 0.05). Two of the three modules were negatively related to FEV1 and were enriched in IL8 and IL10 pathways and correlated with neutrophil-specific gene expression. The positively related module, on the other hand, was enriched in DNA transcription and translation and was strongly correlated to CD4+, CD8+ T cell-specific gene expression.ConclusionsNetwork based approaches are promising tools to identify potential biomarkers for COPD.Trial registrationThe ECLIPSE study was funded by GlaxoSmithKline, under ClinicalTrials.gov identifier NCT00292552 and GSK No. SCO104960

【 授权许可】

CC BY   
© The Author(s). 2017