Stratification of asthma phenotypes by airway proteomic signatures

© 2019 Background: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy in prediction of treatment responses and a need for better understanding of the underlying mechanisms. Objective: We sought to identify molecular subphenotypes of asthma defined by proteomic signatures for improved stratification. Methods: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyze the proteomes of sputum supernatants from 246 participants (206 asthmatic patients) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. Results: Analysis of the sputum proteome resulted in 10 clusters (ie, proteotypes) based on similarity in proteomic features, representing discrete molecular subphenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined 3 of these as highly eosinophilic, 3 as highly neutrophilic, and 2 as highly atopic with relatively low granulocytic inflammation. For each of these 3 phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. Conclusion: This study provides further stratification of asthma currently classified based on quantification of granulocytic inflammation and provided additional insight into their underlying mechanisms, which could become targets for novel therapies

Oxidative stress and anti-oxidant response in allergen, virus, and corticosteroids withdrawal-induced asthma exacerbation.

Si stima che oltre 300 milioni persone di tutte le età e razze, soffrono di asma.1 L'onere di questa malattia per i governi, le famiglie, e i pazienti è in aumento a livello globale. L'asma è una condizione eterogenea e complessa causata da una combinazione di fattori genetici e ambientali. L'asma è caratterizzata da tosse ricorrente, respiro sibilante, senso di costrizione toracica, e responsività ai broncodilatatori. Iper-reattività bronchiale, infiammazione cronica, alterazioni strutturali delle vie aeree, e iper-secrezione ghiandolare sono altre caratteristiche dell asma. Lo stress ossidativo svolge un ruolo centrale nella patogenesi dell asma.2 Esso si verifica quando la produzione di specie ossidanti supera la capacità dei sistemi biologici di detossificazione o di riparo. La presenza di un alterato status ossidante è ben stabilita in pazienti asmatici. Tuttavia, non è stata ancora eseguita alcuna analisi sistematica del danno ossidativo e sulle risposte cellulari anti-ossidanti negli asmatici. Questa tesi è stata incentrata sulla valutazione dello stress ossidativo e risposta anti-ossidante nell'asma e durante la sua riacutizzazione. La presente tesi ha avuto lo scopo di valutare le conseguenze ossidative che le riacutizzazioni hanno sulle proteine cellulari e di individuare i principali meccanismi anti-ossidanti coinvolti nella risposta cito-protettiva. La tesi ha studiato la relazione tra stress ossidativo, stato anti-ossidante, e sintomi da riacutizzazione asmatica. Una valutazione bio-chimica completa dello stato ossidativo e delle risposte anti-ossidanti è necessaria per identificare la natura e la portata di eventuali deficit anti-ossidanti associati con l'asma e la sua riacutizzazione. Una piena comprensione dello stato ossido-riduttivo nelle riacutizzazioni dell'asma potrebbe sostenere lo sviluppo di nuovi interventi terapeutici sicuri ed efficaci. La popolazione che ha partecipato negli studi inclusi in questa tesi è composta da 4 gruppi di asmatici. Il primo gruppo di nove asmatici è stato esposto al Rhinovirus-16. Il secondo gruppo comprendeva venti asmatici atopici esposti all acaro della polvere. Il terzo trentasette individui sani impiegati in laboratori ed esposti ad allergeni da roditori per un periodo di due anni; alcuni di loro sono diventati allergici. Il quarto gruppo comprendeva ventitré asmatici in trattamento con corticosteroidi la cui sospensione è stata eseguita allo scopo di studiare la riacutizzazione asmatica indotta dalla sospensione di questi farmaci. Sono stati condotti diversi esperimenti in vivo, ex vivo e in vitro per chiarire la relazione tra stato ossidativo e la riacutizzazione asmatica. L ossidazione delle proteine cellulari è stata valutata come stabile indice biologico di stress ossidativo e il livello di espressione è stato misurato per diverse proteine anti-ossidanti nel plasma e nell espettorato indotto. È stata anche determinata la produzione di mediatori pro-infiammatori. I pazienti durante la riacutizzazione dell'asma, come previsto, mostravano livelli più alti di stress ossidativo. L entità del danno ossidativo risultava associata alla severità della sintomatologia. È stato interessante riscontrare che i pazienti durante una riacutizzazione asmatica erano anche più suscettibili a danni ossidativi delle proteine cellulari; questo è stato associato ad una riduzione della capacità anti-ossidante cellulare, ridotta traslocazione nucleare del principale fattore di trascrizione anti-ossidante, e maggiore produzione di mediatori pro-infiammatori. Inoltre, i livelli basali di stress ossidativo sono stati in grado di predire quali pazienti erano più inclini a sviluppare sintomi di riacutizzazione. Questi risultati suggeriscono che il rafforzamento dei meccanismi anti-ossidanti locali e sistemici in asmatici può attenuare l'infiammazione delle vie aeree e il suo aggravamento durante le fasi di riacutizzazione

Reduced Antioxidant and Cytoprotective Capacity in Allergy and Asthma

In asthma, reactive oxygen species induce damage to biomolecules like proteins. This oxidative stress can promote inflammation, but its contribution to asthma pathology is controversial, not in the least because antioxidant interventions have proven rather unsuccessful. Recent studies indicate that the oxidative stress at baseline can be predictive of the fall in FEV1 upon an allergen challenge and of sensitization to an allergen. Interestingly, this baseline oxidative stress correlated with the capacity of antioxidant and cytoprotective responses to deal with reactive oxygen species, but not with inflammatory parameters. These findings have led to several considerations in relation to antioxidant trials that are discussed. Trials should be complemented by in-depth analyses of the failing antioxidant and cytoprotective responses and their consequences for cellular function in asthm

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supematant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in >= 40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in >= 3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (Unbiased BIOmarkers Predictive of REspiratory Disease outcomes) international project. We present practical and analytical techniques to optimise the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy non-smoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The “core” sputum proteome (proteins detected in ≥40 % of participants) was composed of 284 proteins and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimise the accuracy and consistency of measurement of sputum proteins and analyse the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants’ samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high inter-individual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitisation. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance

Stratification of asthma phenotypes by airway proteomic signatures

BackgroundStratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy to predict treatment responses and a need for better understanding of the underlying mechanisms.ObjectiveIdentify molecular sub-phenotypes of asthma defined by proteomic signatures for improved stratification.MethodsUnbiased label-free quantitative mass spectrometry and topological data analysis were used to analyse the proteomes of sputum supernatants from 246 participants (206 asthmatics) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms.ResultsAnalysis of the sputum proteome resulted in 10 clusters, proteotypes, based on similarity in proteomics features, representing discrete molecular sub-phenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined three of these as highly eosinophilic, three as highly neutrophilic, and two as highly atopic with relatively low granulocytic inflammation. For each of these three phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms.ConclusionThis study provides further stratification of asthma currently classified by quantifying granulocytic inflammation and gives additional insight into their underlying mechanisms which could become targets for novel therapies

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The “core” sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants’ samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The “core” sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants’ samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance

Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome

Analysis of induced sputum supernatant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMS^E applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The “core” sputum proteome (proteins detected in ≥40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in ≥3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMS^E is influenced by several factors, with some proteins being measured in all participants’ samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance