Author
Luis Serrano
Bio: Luis Serrano is an academic researcher. The author has contributed to research in topics: Precision medicine. The author has an hindex of 1, co-authored 1 publications receiving 61 citations.
Topics: Precision medicine
Papers
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TL;DR: The authors hope that, although it is not a systematic review on the subject, this document can be a useful reference for researchers, clinicians, healthcare managers, policy-makers, and industry parties interested in personalized respiratory medicine.
Abstract: This Pulmonary Perspective summarizes the content and main conclusions of an international workshop on personalized respiratory medicine coorganized by the Barcelona Respiratory Network (www.brn.cat) and the AJRCCM in June 2014. It discusses (1) its definition and historical, social, legal, and ethical aspects; (2) the view from different disciplines, including basic science, epidemiology, bioinformatics, and network/systems medicine; (3) the bottlenecks and opportunities identified by some currently ongoing projects; and (4) the implications for the individual, the healthcare system and the pharmaceutical industry. The authors hope that, although it is not a systematic review on the subject, this document can be a useful reference for researchers, clinicians, healthcare managers, policy-makers, and industry parties interested in personalized respiratory medicine.
67 citations
Cited by
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University of Oxford1, Wellington Management Company2, University of Barcelona3, University of Melbourne4, University of Amsterdam5, Ghent University Hospital6, Erasmus University Rotterdam7, National Institutes of Health8, Imperial College London9, Université de Montréal10, University of California, San Francisco11, Boston Children's Hospital12, University of Newcastle13, John Hunter Hospital14, Queen's University Belfast15, University of Western Australia16, Université Paris-Saclay17, French Institute of Health and Medical Research18, University of New South Wales19, University of Arizona20, Ludwig Maximilian University of Munich21, University of Pittsburgh22, University of Cape Town23
TL;DR: The only way to make progress in the future is to be much more clear about the meaning of the labels used for asthma and to acknowledge the assumptions associated with them, which are believed to be the most important causes of the stagnation in key clinical outcomes observed in the past 10 years.
712 citations
University of Barcelona1, University of Amsterdam2, University of Southampton3, University of Marburg4, Ghent University Hospital5, Erasmus University Rotterdam6, Southampton General Hospital7, University of Paris-Sud8, St George's, University of London9, University of Newcastle10, University Hospital of South Manchester NHS Foundation Trust11, Wellington Management Company12, University of Oxford13
TL;DR: This Perspective proposes a precision medicine strategy for chronic airway diseases in general, and asthma and COPD in particular, and a discussion of the concept of “treatable traits” as a way towards precision medicine of chronicAirway diseases.
Abstract: Asthma and chronic obstructive pulmonary disease (COPD) are two prevalent chronic airway diseases that have a high personal and social impact. They likely represent a continuum of different diseases that may share biological mechanisms (i.e. endotypes), and present similar clinical, functional, imaging and/or biological features that can be observed (i.e. phenotypes) which require individualised treatment. Precision medicine is defined as "treatments targeted to the needs of individual patients on the basis of genetic, biomarker, phenotypic, or psychosocial characteristics that distinguish a given patient from other patients with similar clinical presentations". In this Perspective, we propose a precision medicine strategy for chronic airway diseases in general, and asthma and COPD in particular.
709 citations
TL;DR: Network analysis of human diseases offers the possibility to improve understanding of disease pathobiological complexity and to help with the development of new treatment alternatives and, importantly, a reclassification of complex diseases.
201 citations
TL;DR: Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates, and four biomarkers can be used to predict the phenotype with high accuracy.
Abstract: Rationale We hypothesised that patients with acute respiratory distress syndrome (ARDS) can be clustered based on concentrations of plasma biomarkers and that the thereby identified biological phenotypes are associated with mortality. Methods Consecutive patients with ARDS were included in this prospective observational cohort study. Cluster analysis of 20 biomarkers of inflammation, coagulation and endothelial activation provided the phenotypes in a training cohort, not taking any outcome data into account. Logistic regression with backward selection was used to select the most predictive biomarkers, and these predicted phenotypes were validated in a separate cohort. Multivariable logistic regression was used to quantify the independent association with mortality. Results Two phenotypes were identified in 454 patients, which we named ‘uninflamed’ (N=218) and ‘reactive’ (N=236). A selection of four biomarkers (interleukin-6, interferon gamma, angiopoietin 1/2 and plasminogen activator inhibitor-1) could be used to accurately predict the phenotype in the training cohort (area under the receiver operating characteristics curve: 0.98, 95% CI 0.97 to 0.99). Mortality rates were 15.6% and 36.4% (p Conclusions Patients with ARDS can be clustered into two biological phenotypes, with different mortality rates. Four biomarkers can be used to predict the phenotype with high accuracy. The phenotypes were very similar to those found in cohorts derived from randomised controlled trials, and these results may improve patient selection for future clinical trials targeting host response in patients with ARDS.
196 citations
TL;DR: The epidemiology, mechanisms of disease, current attempts to define and diagnose ACOS, existing and potential treatment options, and new approaches to the phenotyping and taxonomy of airway diseases are considered.
149 citations