Application of ’omics technologies to biomarker discovery in inflammatory lung diseases

Abstract

Inflammatory lung diseases are highly complex in respect of pathogenesis and relationships between inflammation, clinical disease and response to treatment. Sophisticated large-scale analytical methods to quantify gene expression (transcriptomics), proteins (proteomics), lipids (lipidomics) and metabolites (metabolomics) in the lungs, blood and urine are now available to identify biomarkers that define disease in terms of combined clinical, physiological and patho-biological abnormalities. The aspiration is that these approaches will improve diagnosis, i.e. define pathological phenotypes, and facilitate the monitoring of disease and therapy, and also, unravel underlying molecular pathways. Biomarker studies can either select predefined biomarker(s) measured by specific methods or apply an ''unbiased'' approach involving detection platforms that are indiscriminate in focus. This article reviews the technologies presently available to study biomarkers of lung disease within the 'omics field. The contributions of the individual 'omics analytical platforms to the field of respiratory diseases are summarised, with the goal of providing background on their respective abilities to contribute to systems medicine-based studies of lung disease. @ERSpublications Summary of the application of 'omics-based analytical platforms for biomarker discovery in inflammatory lung diseases

Improving the diagnosis of eosinophilic asthma

“…But large multicenter trials such as U-BIOPRED study [79] validating this diagnostic 'biomarker' are currently underway. U-BIOPRED focusses on several new 'omics' techniques such as gene expression (transcriptomics), proteins (proteomics), lipids (lipidomics), and metabolites (metabolomics) in the lungs, blood, and urine [79]. Results of this large study are expected to reveal more accurate biomarkers for identification of all existing asthma phenotypes and endotypes.…”

Severe refractory asthma: an update

“…Unbiased cluster analysis has already revealed three to four subphenotypes of severe asthma [18,19]. In the near future, integrated high dimensional data will probably lead to more accurate phenotyping [104]. This will certainly improve our understanding of the patho-immunobiology of the different asthma phenoypes and will help clinicians to better predict the natural history and prognosis of an individual patient with asthma.…”

Disease stratification in idiopathic pulmonary fibrosis: the dawn of a new era?

“…In asthma, the novel anti-interleukin-13 monoclonal antibody, lebrikizumab, has been shown to improve airflow obstruction in individuals with elevated levels of the serum protein periostin, but not those with normal levels [10]. Whilst requiring further validation, this observation suggests that biomarker-driven therapy may become a reality in respiratory medicine in the near future [11]. For a disease as complex as IPF, stratification intuitively makes sense but what should come first, the treatment or the biomarker?…”