Source: Annual Congress 2010 - COPD: treatment and monitoring
Disease area: Airway diseases

Abstract

We tested a novel way of visualizing relationships between serum biomarkers and clinical outcomes using heat-map colors in 253 COPD and 92 non-COPD subjects over 3 years.
Using high sensitivity ELISA testing, we measured IL-6, IL-8, IL-16, TNF- as indicators of inflammation, VEGF, MMP-9 as indicators of injury and repair and, PARC, MCP-1 as novel markers. We explored differences in clinical descriptors between the highest and lowest quartiles of biomarkers‘ levels. We assessed the importance of differences in clinical variables using known MICD and expressed using heatmap colors. Differences associated with good outcomes are shown in green, poor outcomes in red and no differences in yellow.
COPD patients had a specific biomarker profile where upper quartiles of inflammatory cytokines and injury&repair cytokines were associated with poor and good outcomes, resp. This pattern replicated in all biomarkers, but IL-8 and PARC at subsequent annual visits. No specific profile was observed in non-COPD subjects.
We describe a new method to express COPD specific serum biomarkers profile that replicates during 3 year follow-up. The profile is not seen in non-COPD controls. The Heatmap-Clinical profile pattern is associated with several clinical expressions of COPD.
Data analysis support provided by GlaxoSmithKline R&D.
Figure: Heatmap-Clinical Pattern Profile of Serum Biomarkers in COPD Patients (Year2 Follow-Up Visit)

Rating:

Share or cite this content

Citations should be made in the following way:
H. Müllerova, V. Pinto-Plata, C. Casanova, J. P. de Torres, H. Corado, N. Varo, E. Cordoba, S. Zeineldine, F. Cortopassi, B. Celli (Uxbridge, United Kingdom; Boston, United States Of America; Santa Cruz de Tenerife, Pamplona, Spain). Novel method of expressing serum biomarkers profiling in COPD patients: The heatmap-clinical pattern profile. Eur Respir J 2010; 36: Suppl. 54, 1336

Member's Comments

No comment yet.

Related content which might interest you: A proteomic approach to the progression of COPD: protein expression profile in induced sputum samples Source: Eur Respir J 2006; 28: Suppl. 50, 824s Year: 2006 Plasma metabolomic signature in COPD patients: Associations to proteomic profile and clinical outcomes Source: Annual Congress 2013 –COPD mechanisms Year: 2013 Altered serum metabolomics in COPD: analysis of the SPIROMICS cohort Source: International Congress 2018 – COPD phenotypes: a1 antitrypsin deficiency and beyond Year: 2018 Novel patterns of serum biomarkers profiling using minimal important clinical outcomes (MICO) in the longidutinal study BODE cohort of COPD patients Source: Annual Congress 2010 - COPD: symptoms and staging Year: 2010 Simultaneous analysis of clinical markers for predicting increased lung function fluctability in stable asthma Source: Annual Congress 2012 - Clinical aspects and treatment of asthma and allergic respiratory diseases Year: 2012 The expression of selected biomarkers at the systemic and local level in patients with COPD Source: International Congress 2018 – Asthma, rhinitis and COPD: cells, mediators, biomarkers and genetics Year: 2018 Serum microRNA signatures identified in a genome-wide profiling predict the mortality of patients with sepsis Source: Annual Congress 2011 - New aspects in prevention and treatment of community-acquired pneumonia and lower respiratory tract infections Year: 2011 Candidate surrogate markers for COPD identified by differential gene expression Source: Eur Respir J 2002; 20: Suppl. 38, 583s Year: 2002 Identification of clinical phenotypes using cluster analyses in COPD patients Source: International Congress 2019 – Phenotypes and comorbidities of airway diseases Year: 2019 Changes in gene expression associated with COPD revealed by low density microarray analysis Source: Eur Respir J 2006; 28: Suppl. 50, 584s Year: 2006 Gene expression profiles of idiopathic interstitial pneumonias: Identification of disease-specific diagnostic markers and molecular therapeutic targets Source: Annual Congress 2012 - Idiopathic pulmonary fibrosis Year: 2012 Stability of serum biomarkers and their associations with clinical outcomes in COPD patients and controls: a longitudinal study Source: Annual Congress 2009 - Biomarkers and biology in COPD Year: 2009 The use of microarray analysis of gene signalling to determine heterogeneity of COPD exacerbation phenotypes Source: ERS Lung Science Conference 2016 Year: 2016 Microarray gene expression profiles in lung tissue of COPD patients Source: Eur Respir J 2007; 30: Suppl. 51, 537s Year: 2007 Expression of apoptotic markers in lung tissue of COPD patients: preliminary results Source: Eur Respir J 2006; 28: Suppl. 50, 748s Year: 2006 Integrated analysis of COPD gene expression data reveals specific pathway signatures Source: Annual Congress 2010 - Genetics of obstruction Year: 2010 Combined genome-wide transcriptomic and epigenetic profiling across disease stages identifies novel regulators of COPD in human lung fibroblasts Source: Virtual Congress 2020 – Physiological and cellular mechanisms affecting pulmonary pathologies Year: 2020 Evaluation of mRNA expression profiling of NF-?B mediated signaling in COPD patients. Source: Virtual Congress 2020 – Novel immunopathological mechanisms of lung disease: knowledge from translational studies Year: 2020 Gene expression profiling of induced sputum from COPD patients and healthy smokers Source: Eur Respir J 2006; 28: Suppl. 50, 746s Year: 2006 Human chitotriosidase analysis: a reliable biomarker of sarcoidosis severity Source: International Congress 2017 – The many faces of sarcoidosis Year: 2017