Asthma is a chronic obstructive respiratory disease characterised by bronchial inflammation. Its biological and clinical features have been widely explored and a number of pharmacological treatments are currently available. Currently several aspects of asthma pathophysiological background remain unclear, and this is represent a limitation for the traditional asthma phenotype approach. In this scenario, the identification of new molecular and clinical biomarkers may be helpful in order to better understand the disease, define specific diagnostic tools and highlight relevant novel targets for pharmacological treatments. Omics technologies offer innovative research tools for addressing the above mentioned goals. However, there is still a lot to do both in the fields of basic research and in the clinical application. Recently, genome-wide association studies, microRNAs and proteomics are contributing to enrich the available data for the identification of new asthma biomarkers. A precise approach to the patient with asthma, particularly with severe uncontrolled asthma, requires new and specific therapeutic targets, but also proper tools able to drive the clinician in tailoring the treatment. On the other hand, there is a need of predictors to treatment's response, particularly in the field of biological drugs, whose sustainability implies a correct and precise selection of the patients. Translating acquired omics knowledge in clinical practice may address the unmet needs described above, but large-scale studies are required in order to confirm their relevance and effectiveness in daily practice. Thus in our opinion the application of omics is still lagging in the real-life setting.

Towards precision medicine: The application of omics technologies in asthma management / Scelfo C.; Galeone C.; Bertolini F.; Caminati M.; Ruggiero P.; Facciolongo N.; Menzella F.. - In: F1000RESEARCH. - ISSN 2046-1402. - ELETTRONICO. - 7:(2018), pp. 423.1-423.9. [10.12688/f1000research.14309.2]

Towards precision medicine: The application of omics technologies in asthma management

Bertolini F.;
2018

Abstract

Asthma is a chronic obstructive respiratory disease characterised by bronchial inflammation. Its biological and clinical features have been widely explored and a number of pharmacological treatments are currently available. Currently several aspects of asthma pathophysiological background remain unclear, and this is represent a limitation for the traditional asthma phenotype approach. In this scenario, the identification of new molecular and clinical biomarkers may be helpful in order to better understand the disease, define specific diagnostic tools and highlight relevant novel targets for pharmacological treatments. Omics technologies offer innovative research tools for addressing the above mentioned goals. However, there is still a lot to do both in the fields of basic research and in the clinical application. Recently, genome-wide association studies, microRNAs and proteomics are contributing to enrich the available data for the identification of new asthma biomarkers. A precise approach to the patient with asthma, particularly with severe uncontrolled asthma, requires new and specific therapeutic targets, but also proper tools able to drive the clinician in tailoring the treatment. On the other hand, there is a need of predictors to treatment's response, particularly in the field of biological drugs, whose sustainability implies a correct and precise selection of the patients. Translating acquired omics knowledge in clinical practice may address the unmet needs described above, but large-scale studies are required in order to confirm their relevance and effectiveness in daily practice. Thus in our opinion the application of omics is still lagging in the real-life setting.
2018
Towards precision medicine: The application of omics technologies in asthma management / Scelfo C.; Galeone C.; Bertolini F.; Caminati M.; Ruggiero P.; Facciolongo N.; Menzella F.. - In: F1000RESEARCH. - ISSN 2046-1402. - ELETTRONICO. - 7:(2018), pp. 423.1-423.9. [10.12688/f1000research.14309.2]
Scelfo C.; Galeone C.; Bertolini F.; Caminati M.; Ruggiero P.; Facciolongo N.; Menzella F.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/903238
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