TY - JOUR
T1 - Novel therapeutic strategy in the management of COPD: a systems medicine approach
AU - Lococo, Filippo
AU - Cesario, Alfredo
AU - Del Bufalo, Alessandra
AU - Ciarrocchi, Alessia
AU - Prinzi, Giulia
AU - Mina, Marco
AU - Bonassi, Stefano
AU - Russo, Patrizia
PY - 2015
Y1 - 2015
N2 - Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as a result of a complex interaction between various genetic, environmental and life-style factors. In recent years, several investigations have been performed to better define such interactions, but the identification of the resulting phenotypes is still somewhat difficult, and may lead to inadequate assessment and management of COPD (usually based solely on the severity of airflow limitation parameter FEV1). In this new scenario, the management of COPD has been driven towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (also including advanced functional genomic assays) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for the development of new drugs). Therefore, according to the emerging “systems/network medicine”, COPD should be re.-evaluated considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized and participatory (“P4-medicine”). It clearly emerges that in the next future, new opportunities will become available for clinical research on rare COPD patterns and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SMapproaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.
AB - Respiratory diseases including chronic-obstructive-pulmonary-disease (COPD) are globally increasing, with COPD predicted to become the third leading cause of global mortality by 2020. COPD is a heterogeneous disease with COPD-patients displaying different phenotypes as a result of a complex interaction between various genetic, environmental and life-style factors. In recent years, several investigations have been performed to better define such interactions, but the identification of the resulting phenotypes is still somewhat difficult, and may lead to inadequate assessment and management of COPD (usually based solely on the severity of airflow limitation parameter FEV1). In this new scenario, the management of COPD has been driven towards an integrative and holistic approach. The degree of complexity requires analyses based on large datasets (also including advanced functional genomic assays) and novel computational biology approaches (essential to extract information relevant for the clinical decision process and for the development of new drugs). Therefore, according to the emerging “systems/network medicine”, COPD should be re.-evaluated considering multiple network(s) perturbations such as genetic and environmental changes. Systems Medicine (SM) platforms, in which patients are extensively characterized, offer a basis for a more targeted clinical approach, which is predictive, preventive, personalized and participatory (“P4-medicine”). It clearly emerges that in the next future, new opportunities will become available for clinical research on rare COPD patterns and for the identification of new biomarkers of comorbidity, severity, and progression. Herein, we overview the literature discussing the opportunity coming from the adoption of SMapproaches in COPD management, focusing on proteomics and metabolomics, and emphasizing the identification of disease sub-clusters, to improve the development of more effective therapies.
KW - Chemistry, Pharmaceutical
KW - Disease Management
KW - Humans
KW - Metabolomics
KW - Proteomics
KW - Pulmonary Disease, Chronic Obstructive
KW - Systems Analysis
KW - Chemistry, Pharmaceutical
KW - Disease Management
KW - Humans
KW - Metabolomics
KW - Proteomics
KW - Pulmonary Disease, Chronic Obstructive
KW - Systems Analysis
UR - http://hdl.handle.net/10807/99999
U2 - 10.2174/0929867322666150904113032
DO - 10.2174/0929867322666150904113032
M3 - Article
SN - 0929-8673
VL - 22
SP - 3655
EP - 3675
JO - Current Medicinal Chemistry
JF - Current Medicinal Chemistry
ER -