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Exploring Inflammatory Asthma Phenotypes: Proteomic Signatures in Serum and Induced Sputum.

ABSTRACT: Asthma drug responses may differ due to inflammatory mechanisms triggered by the immune cells in the pulmonary microenvironment. Thus, asthma phenotyping based on the local inflammatory profile may aid in treatment definition and the identification of new therapeutic targets. Here, we investigated protein profiles of induced sputum and serum from asthma patients classified into eosinophilic, neutrophilic, mixed granulocytic, and paucigranulocytic asthma, according to inflammatory phenotypes. Proteomic analyses were performed using an ultra-performance liquid chromatography (ultra-HPLC) system coupled to the Q Exactive Hybrid Quadrupole Orbitrap Mass Spectrometer. Fifty-two (52) proteins showed significant differences in induced sputum among the groups, while only 12 were altered in patients' sera. Five proteins in the induced sputum were able to discriminate all phenotypic groups, while four proteins in the serum could differentiate all except the neutrophilic from the paucigranulocytic inflammatory pattern. This is the first report on comparative proteomics of inflammatory asthma phenotypes in both sputum and serum samples. We have identified a potential five-biomarker panel that may be able to discriminate all four inflammatory phenotypes in sputum. These findings not only provide insights into potential therapeutic targets but also emphasize the potential for personalized treatment approaches in asthma management.

SUBMITTER: Maia LP

PROVIDER: S-EPMC10971300 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature

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Exploring Inflammatory Asthma Phenotypes: Proteomic Signatures in Serum and Induced Sputum.

Maia Larissa Prado LP Cunha Thulio Marquez TM Santos Paula Souza PS Martins Mario Machado MM Briza Peter P Ferreira Fatima F Amorim Maria Marta MM Caetano Lilian Ballini LB Farias Camyla Fernandes CF Santoro Ilka Lopes IL Godoy Fernandes Ana Luisa AL Goulart Luiz Ricardo LR

International journal of molecular sciences 20240320 6

Asthma drug responses may differ due to inflammatory mechanisms triggered by the immune cells in the pulmonary microenvironment. Thus, asthma phenotyping based on the local inflammatory profile may aid in treatment definition and the identification of new therapeutic targets. Here, we investigated protein profiles of induced sputum and serum from asthma patients classified into eosinophilic, neutrophilic, mixed granulocytic, and paucigranulocytic asthma, according to inflammatory phenotypes. Pro ...[more]

PMID: 38542471

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Project description:BackgroundEosinophilic and neutrophilic asthma defined by high levels of blood and sputum eosinophils and neutrophils exemplifies the inflammatory heterogeneity of asthma, particularly severe asthma. We analysed the serum and sputum proteome to identify biomarkers jointly associated with these different phenotypes.MethodsProteomic profiles (N = 1129 proteins) were assayed in sputum (n = 182) and serum (n = 574) from two cohorts (U-BIOPRED and ADEPT) of mild-moderate and severe asthma by SOMAscan. Using least absolute shrinkage and selection operator (LASSO)-penalised logistic regression in a stability selection framework, we sought sparse sets of proteins associated with either eosinophilic or neutrophilic asthma with and without adjustment for established clinical factors including oral corticosteroid use and forced expiratory volume.FindingsWe identified 13 serum proteins associated with eosinophilic asthma, including 7 (PAPP-A, TARC/CCL17, ALT/GPT, IgE, CCL28, CO8A1, and IL5-Rα) that were stably selected while adjusting for clinical factors yielding an AUC of 0.84 (95% CI: 0.83-0.84) compared to 0.62 (95% CI: 0.61-0.63) for clinical factors only. Sputum protein analysis selected only PAPP-A (AUC = 0.81 [95% CI: 0.80-0.81]). 12 serum proteins were associated with neutrophilic asthma, of which 5 (MMP-9, EDAR, GIIE/PLA2G2E, IL-1-R4/IL1RL1, and Elafin) complemented clinical factors increasing the AUC from 0.63 (95% CI: 0.58-0.67) for the model with clinical factors only to 0.89 (95% CI: 0.89-0.90). Our model did not select any sputum proteins associated with neutrophilic status.InterpretationTargeted serum proteomic profiles are a non-invasive and scalable approach for subtyping of neutrophilic and eosinophilic asthma and for future functional understanding of these phenotypes.FundingU-BIOPRED has received funding from the Innovative Medicines Initiative (IMI) Joint Undertaking under grant agreement no. 115010, resources of which are composed of financial contributions from the European Union's Seventh Framework Programme (FP7/2007-2013), and European Federation of Pharmaceutical Industries and Associations (EFPIA) companies' in-kind contributions (www.imi.europa.eu). ADEPT was funded by Johnson & Johnson/Janssen pharmaceutical Company.

Project description:PurposeThe molecular links between metabolism and inflammation that drive different inflammatory phenotypes in asthma are poorly understood. We aimed to identify the metabolic signatures and underlying molecular pathways of different inflammatory asthma phenotypes.MethodsIn the discovery set (n = 119), untargeted ultra-high-performance liquid chromatography-mass spectrometry (UHPLC-MS) was applied to characterize the induced sputum metabolic profiles of asthmatic patients with different inflammatory phenotypes using orthogonal partial least-squares discriminant analysis (OPLS-DA), and pathway topology enrichment analysis. In the validation set (n = 114), differential metabolites were selected to perform targeted quantification. Correlations between targeted metabolites and clinical indices in asthmatic patients were analyzed. Logistic and negative binomial regression models were established to assess the association between metabolites and severe asthma exacerbations.ResultsSeventy-seven differential metabolites were identified in the discovery set. Pathway topology analysis uncovered that histidine metabolism, glycerophospholipid metabolism, nicotinate and nicotinamide metabolism, linoleic acid metabolism as well as phenylalanine, tyrosine and tryptophan biosynthesis were involved in the pathogenesis of different asthma phenotypes. In the validation set, 24 targeted quantification metabolites were significantly expressed between asthma inflammatory phenotypes. Finally, adenosine 5'-monophosphate (adjusted relative risk [adj RR] = 1.000; 95% confidence interval [CI] = 1.000-1.000; P = 0.050), allantoin (adj RR = 1.000; 95% CI = 1.000-1.000; P = 0.043) and nicotinamide (adj RR = 1.001; 95% CI = 1.000-1.002; P = 0.021) were demonstrated to predict severe asthma exacerbation rates.ConclusionsDifferent inflammatory asthma phenotypes have specific metabolic profiles in induced sputum. The potential metabolic signatures may identify therapeutic targets in different inflammatory asthma phenotypes.

Project description:BACKGROUND:The release of various inflammatory mediators into the bronchial lumen is thought to reflect both the type and degree of airway inflammation, eosinophilic Th2, and Th9, or neutrophilic Th1, and Th17, in patients with asthma. AIMS:We investigated whether cytokines and chemokines differed in sputum from subjects with more severe compared with milder asthma and whether unbiased factor analysis of cytokine and chemokine groupings indicates specific inflammatory pathways. METHODS:Cell-free supernatants from induced sputum were obtained from subjects with a broad range of asthma severity (n = 158) and assessed using Milliplex® Cytokines/Chemokine kits I, II and III, measuring 75 individual proteins. Each cytokine, chemokine or growth factor concentration was examined for differences between asthma severity groups, for association with leucocyte counts, and by factor analysis. RESULTS:Severe asthma subjects had 9 increased and 4 decreased proteins compared to mild asthma subjects and fewer differences compared to moderate asthma. Twenty-six mediators were significantly associated with an increasing single leucocyte type: 16 with neutrophils (3 interleukins [IL], 3 CC chemokines, 4 CXC chemokines, 4 growth factors, TNF-α and CX3CL1/Fractalkine); 5 with lymphocytes (IL-7, IL-16, IL-23, IFN-α2 and CCL4/MIP1β); IL-15 and CCL15/MIP1δ with macrophages; IL-5 with eosinophils; and IL-4 and TNFSF10/TRAIL with airway epithelial cells. Factor analysis grouped 43 cytokines, chemokines and growth factors which had no missing data onto the first 10 factors, containing mixes of Th1, Th2, Th9 and Th17 inflammatory and anti-inflammatory proteins. CONCLUSIONS:Sputum cytokines, chemokines and growth factors were increased in severe asthma, primarily with increased neutrophils. Factor analysis identified complex inflammatory protein interactions, suggesting airway inflammation in asthma is characterized by overlapping immune pathways. Thus, focus on a single specific inflammatory mediator or pathway may limit understanding the complexity of inflammation underlying airway changes in asthma and selection of appropriate therapy.

Project description:Sputum immunoglobulin G (Sp-IgG) has been discovered to induce cytolytic extracellular trap cell death in eosinophils, suggesting a potential autoimmune mechanism contributing to asthma. This study aimed to explore the potential origin of Sp-IgG and identify clinically relevant subtypes of Sp-IgG that may indicate autoimmune events in asthma. This study included 165 asthmatic patients and 38 healthy volunteers. We measured Sp-IgG and its five subtypes against eosinophil inflammatory proteins (Sp-IgGEPs), including eosinophil peroxidase, eosinophil major basic protein, eosinophil-derived neurotoxin, eosinophil cationic protein, and Charcot-Leyden Crystal protein in varying asthma severity. Clinical and Mendelian randomization (MR) analyses were conducted. A positive Sp-IgGEPs signature (Sp-IgGEPs+) was defined when any of the five Sp-IgGEPs values exceeded the predefined cutoff thresholds, calculated as the mean values of healthy controls plus twice the standard deviation. The levels of Sp-IgG and Sp-IgGEPs were significantly elevated in moderate/severe asthma than those in mild asthma/healthy groups (all p < 0.05). Sp-IgG levels were positively correlated with airway eosinophil and Sp-IgGEPs. MR analysis showed causality between eosinophil and IgG (OR = 1.02, 95%CI = 1.00-1.04, p = 0.020), and elevated IgG was a risk factor for asthma (OR = 2.05, 95%CI = 1.00-4.17, p = 0.049). Subjects with Sp-IgGEPs+ exhibited worse disease severity and served as an independent risk factor contributing to severe asthma (adjusted-OR = 5.818, adjusted-95% CI = 2.193-15.431, adjusted-p < 0.001). Receiver operating characteristic curve analysis demonstrated that the combination of Sp-IgGEPs+ with non-allergic status, an ACT score < 15, and age ≥ 45 years, effectively predicted severe asthma (AUC = 0.84, sensitivity = 86.20%, specificity = 67.80%). This study identifies a significant association between airway eosinophilic inflammation, Sp-IgG, and asthma severity. The Sp-IgGEPs panel potentially serves as the specific biomarker reflecting airway autoimmune events in asthma.

Dataset Information

Exploring Inflammatory Asthma Phenotypes: Proteomic Signatures in Serum and Induced Sputum.

Publications

Exploring Inflammatory Asthma Phenotypes: Proteomic Signatures in Serum and Induced Sputum.

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