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Deye N, Le Gouge A, François B, Chenevier-Gobeaux C, Daix T, Merdji H, Cariou A, Dequin PF, Guitton C, Mégarbane B, Callebert J, Giraudeau B, Mebazaa A, Vodovar N. Can Biomarkers Correctly Predict Ventilator-associated Pneumonia in Patients Treated With Targeted Temperature Management After Cardiac Arrest? An Exploratory Study of the Multicenter Randomized Antibiotic (ANTHARTIC) Study. Crit Care Explor 2024; 6:e1104. [PMID: 38957212 PMCID: PMC11219183 DOI: 10.1097/cce.0000000000001104] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 07/04/2024] Open
Abstract
IMPORTANCE Ventilator-associated pneumonia (VAP) frequently occurs in patients with cardiac arrest. Diagnosis of VAP after cardiac arrest remains challenging, while the use of current biomarkers such as C-reactive protein (CRP) or procalcitonin (PCT) is debated. OBJECTIVES To evaluate biomarkers' impact in helping VAP diagnosis after cardiac arrest. DESIGN SETTING AND PARTICIPANTS This is a prospective ancillary study of the randomized, multicenter, double-blind placebo-controlled ANtibiotherapy during Therapeutic HypothermiA to pRevenT Infectious Complications (ANTHARTIC) trial evaluating the impact of antibiotic prophylaxis to prevent VAP in out-of-hospital patients with cardiac arrest secondary to shockable rhythm and treated with therapeutic hypothermia. An adjudication committee blindly evaluated VAP according to predefined clinical, radiologic, and microbiological criteria. All patients with available biomarker(s), sample(s), and consent approval were included. MAIN OUTCOMES AND MEASURES The main endpoint was to evaluate the ability of biomarkers to correctly diagnose and predict VAP within 48 hours after sampling. The secondary endpoint was to study the combination of two biomarkers in discriminating VAP. Blood samples were collected at baseline on day 3. Routine and exploratory panel of inflammatory biomarkers measurements were blindly performed. Analyses were adjusted on the randomization group. RESULTS Among 161 patients of the ANTHARTIC trial with available biological sample(s), patients with VAP (n = 33) had higher body mass index and Acute Physiology and Chronic Health Evaluation II score, more unwitnessed cardiac arrest, more catecholamines, and experienced more prolonged therapeutic hypothermia duration than patients without VAP (n = 121). In univariate analyses, biomarkers significantly associated with VAP and showing an area under the curve (AUC) greater than 0.70 were CRP (AUC = 0.76), interleukin (IL) 17A and 17C (IL17C) (0.74), macrophage colony-stimulating factor 1 (0.73), PCT (0.72), and vascular endothelial growth factor A (VEGF-A) (0.71). Multivariate analysis combining novel biomarkers revealed several pairs with p value of less than 0.001 and odds ratio greater than 1: VEGF-A + IL12 subunit beta (IL12B), Fms-related tyrosine kinase 3 ligands (Flt3L) + C-C chemokine 20 (CCL20), Flt3L + IL17A, Flt3L + IL6, STAM-binding protein (STAMBP) + CCL20, STAMBP + IL6, CCL20 + 4EBP1, CCL20 + caspase-8 (CASP8), IL6 + 4EBP1, and IL6 + CASP8. Best AUCs were observed for CRP + IL6 (0.79), CRP + CCL20 (0.78), CRP + IL17A, and CRP + IL17C. CONCLUSIONS AND RELEVANCE Our exploratory study shows that specific biomarkers, especially CRP combined with IL6, could help to better diagnose or predict early VAP occurrence in cardiac arrest patients.
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Affiliation(s)
- Nicolas Deye
- Medical ICU, Lariboisiere University Hospital, Inserm UMR-S 942, APHP, Paris, France
| | | | - Bruno François
- Réanimation Polyvalente, INSERM CIC 1435 and UMR 1092, CHU Limoges, Limoges, France
| | | | - Thomas Daix
- Réanimation Polyvalente, INSERM CIC 1435 and UMR 1092, CHU Limoges, Limoges, France
| | - Hamid Merdji
- Service de Médecine Intensive–Réanimation, Nouvel Hôpital Civil, Hôpitaux Universitaires de Strasbourg, INSERM UMR 1260, Regenerative NanoMedicine, FMTS, Strasbourg, France
| | - Alain Cariou
- Medical ICU, Cochin University Hospital, AP-HP Centre Université Paris Cité, Paris, France
| | | | - Christophe Guitton
- Medecine Intensive Réanimation, Center Hospitalier Universitaire, Nantes, France
| | - Bruno Mégarbane
- Department of Medical and Toxicological Critical Care, Paris Cité University, Lariboisiere University Hospital, Inserm UMR-S 1144, Paris, France
| | - Jacques Callebert
- Biochemical Laboratory, Lariboisiere University Hospital, Inserm UMR-S 1144, Paris, France
| | | | - Alexandre Mebazaa
- Université de Paris, Inserm UMR-S 942 MASCOT, Paris, France
- Department of Anaesthesiology and Intensive Care, Lariboisière University Hospital, APHP, Paris, France
| | | | - for the Clinical Research in Intensive Care and Sepsis-TRIal Group for Global Evaluation and Research in SEPsis (TRIGGERSEP) Network and the ANtibiotherapy during Therapeutic HypothermiA to pRevenT Infectious Complications (ANTHARTIC) Study Group
- Medical ICU, Lariboisiere University Hospital, Inserm UMR-S 942, APHP, Paris, France
- Inserm CIC 1415, CHU de Tours, Tours, France
- Réanimation Polyvalente, INSERM CIC 1435 and UMR 1092, CHU Limoges, Limoges, France
- Biochemical Laboratory, Cochin University Hospital, APHP, Paris, France
- Service de Médecine Intensive–Réanimation, Nouvel Hôpital Civil, Hôpitaux Universitaires de Strasbourg, INSERM UMR 1260, Regenerative NanoMedicine, FMTS, Strasbourg, France
- Medical ICU, Cochin University Hospital, AP-HP Centre Université Paris Cité, Paris, France
- INSERM UMR 1100 and Médecine Intensive–Réanimation, Tours, France
- Medecine Intensive Réanimation, Center Hospitalier Universitaire, Nantes, France
- Department of Medical and Toxicological Critical Care, Paris Cité University, Lariboisiere University Hospital, Inserm UMR-S 1144, Paris, France
- Biochemical Laboratory, Lariboisiere University Hospital, Inserm UMR-S 1144, Paris, France
- Université de Paris, Inserm UMR-S 942 MASCOT, Paris, France
- Department of Anaesthesiology and Intensive Care, Lariboisière University Hospital, APHP, Paris, France
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Listyoko AS, Okazaki R, Harada T, Inui G, Yamasaki A. Impact of obesity on airway remodeling in asthma: pathophysiological insights and clinical implications. FRONTIERS IN ALLERGY 2024; 5:1365801. [PMID: 38562155 PMCID: PMC10982419 DOI: 10.3389/falgy.2024.1365801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2024] [Accepted: 03/07/2024] [Indexed: 04/04/2024] Open
Abstract
The prevalence of obesity among asthma patients has surged in recent years, posing a significant risk factor for uncontrolled asthma. Beyond its impact on asthma severity and patients' quality of life, obesity is associated with reduced lung function, increased asthma exacerbations, hospitalizations, heightened airway hyperresponsiveness, and elevated asthma-related mortality. Obesity may lead to metabolic dysfunction and immune dysregulation, fostering chronic inflammation characterized by increased pro-inflammatory mediators and adipocytokines, elevated reactive oxygen species, and reduced antioxidant activity. This chronic inflammation holds the potential to induce airway remodeling in individuals with asthma and obesity. Airway remodeling encompasses structural and pathological changes, involving alterations in the airway's epithelial and subepithelial layers, hyperplasia and hypertrophy of airway smooth muscle, and changes in airway vascularity. In individuals with asthma and obesity, airway remodeling may underlie heightened airway hyperresponsiveness and increased asthma severity, ultimately contributing to the development of persistent airflow limitation, declining lung function, and a potential increase in asthma-related mortality. Despite efforts to address the impact of obesity on asthma outcomes, the intricate mechanisms linking obesity to asthma pathophysiology, particularly concerning airway remodeling, remain incompletely understood. This comprehensive review discusses current research investigating the influence of obesity on airway remodeling, to enhance our understanding of obesity's role in the context of asthma airway remodeling.
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Affiliation(s)
- Aditya Sri Listyoko
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
- Pulmonology and Respiratory Medicine Department, Faculty of Medicine, Brawijaya University-Dr. Saiful Anwar General Hospital, Malang, Indonesia
| | - Ryota Okazaki
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Tomoya Harada
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Genki Inui
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Akira Yamasaki
- Division of Respiratory Medicine and Rheumatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
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Smilnak GJ, Lee Y, Chattopadhyay A, Wyss AB, White JD, Sikdar S, Jin J, Grant AJ, Motsinger-Reif AA, Li JL, Lee M, Yu B, London SJ. Plasma protein signatures of adult asthma. Allergy 2024; 79:643-655. [PMID: 38263798 PMCID: PMC10994188 DOI: 10.1111/all.16000] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/08/2023] [Accepted: 12/04/2023] [Indexed: 01/25/2024]
Abstract
BACKGROUND Adult asthma is complex and incompletely understood. Plasma proteomics is an evolving technique that can both generate biomarkers and provide insights into disease mechanisms. We aimed to identify plasma proteomic signatures of adult asthma. METHODS Protein abundance in plasma was measured in individuals from the Agricultural Lung Health Study (ALHS) (761 asthma, 1095 non-case) and the Atherosclerosis Risk in Communities study (470 asthma, 10,669 non-case) using the SOMAScan 5K array. Associations with asthma were estimated using covariate adjusted logistic regression and meta-analyzed using inverse-variance weighting. Additionally, in ALHS, we examined phenotypes based on both asthma and seroatopy (asthma with atopy (n = 207), asthma without atopy (n = 554), atopy without asthma (n = 147), compared to neither (n = 948)). RESULTS Meta-analysis of 4860 proteins identified 115 significantly (FDR<0.05) associated with asthma. Multiple signaling pathways related to airway inflammation and pulmonary injury were enriched (FDR<0.05) among these proteins. A proteomic score generated using machine learning provided predictive value for asthma (AUC = 0.77, 95% CI = 0.75-0.79 in training set; AUC = 0.72, 95% CI = 0.69-0.75 in validation set). Twenty proteins are targeted by approved or investigational drugs for asthma or other conditions, suggesting potential drug repurposing. The combined asthma-atopy phenotype showed significant associations with 20 proteins, including five not identified in the overall asthma analysis. CONCLUSION This first large-scale proteomics study identified over 100 plasma proteins associated with current asthma in adults. In addition to validating previous associations, we identified many novel proteins that could inform development of diagnostic biomarkers and therapeutic targets in asthma management.
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Affiliation(s)
- Gordon J. Smilnak
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Yura Lee
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Abhijnan Chattopadhyay
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Annah B. Wyss
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Julie D. White
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
- GenOmics and Translational Research Center, Biostatistics and Epidemiology Division, RTI International, Research Triangle Park, NC, USA
| | - Sinjini Sikdar
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
- Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, USA
| | | | - Andrew J. Grant
- MRC Biostatistics Unit, University of Cambridge, Cambridge, UK
| | - Alison A. Motsinger-Reif
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Jian-Liang Li
- Integrative Bioinformatics Support Group, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Mikyeong Lee
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Stephanie J. London
- Epidemiology Branch, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, NC, USA
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Akenroye A, Nopsopon T, Cho L, Moll M, Weiss ST. Lower myostatin and higher MUC1 levels are associated with better response to mepolizumab and omalizumab in asthma: a protein-protein interaction analyses. Respir Res 2023; 24:305. [PMID: 38057814 PMCID: PMC10698971 DOI: 10.1186/s12931-023-02620-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Accepted: 11/28/2023] [Indexed: 12/08/2023] Open
Abstract
INTRODUCTION Biomarkers are needed to inform the choice of biologic therapy in patients with asthma given the increasing number of biologics. We aimed to identify proteins associated with response to omalizumab and mepolizumab. METHODS Aptamer-based proteomic profiling (SomaScan) was used to assess 1437 proteins from 51 patients with moderate to severe asthma who received omalizumab (n = 29) or mepolizumab (n = 22). Response was defined as the change in asthma-related exacerbations in the 12 months following therapy initiation. All models were adjusted for age, sex, and pre-treatment exacerbation rate. Additionally, body mass index was included in the omalizumab model and eosinophil count in the mepolizumab model. We evaluated the association between molecular signatures and response using negative binomial regression correcting for the false discovery rate (FDR) and gene set enrichment analyses (GSEA) to identify associated pathways. RESULTS Over two-thirds of patients were female. The average age for omalizumab patients was 42 years and 57 years for mepolizumab. At baseline, the average exacerbation rate was 1.5/year for omalizumab and 2.4/year for mepolizumab. Lower levels of LOXL2 (unadjusted p: 1.93 × 10E-05, FDR-corrected: 0.028) and myostatin (unadjusted: 3.87 × 10E-05, FDR-corrected: 0.028) were associated with better response to mepolizumab. Higher levels of CD9 antigen (unadjusted: 5.30 × 10E-07, FDR-corrected: 0.0006) and MUC1 (unadjusted: 1.15 × 10E-06, FDR-corrected: 0.0006) were associated with better response to omalizumab, and LTB4R (unadjusted: 1.12 × 10E-06, FDR-corrected: 0.0006) with worse response. Protein-protein interaction network modeling showed an enrichment of the TNF- and NF-kB signaling pathways for patients treated with mepolizumab and multiple pathways involving MAPK, including the FcER1 pathway, for patients treated with omalizumab. CONCLUSIONS This study provides novel fundamental data on proteins associated with response to mepolizumab or omalizumab in severe asthma and warrants further validation as potential biomarkers for therapy selection.
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Affiliation(s)
- Ayobami Akenroye
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital, 60 Fenwood Road, BostonBoston, MA, 02115, USA.
| | - Tanawin Nopsopon
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Laura Cho
- Division of Allergy and Clinical Immunology, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Matthew Moll
- Channing Division of Network Medicine, Brigham and Women's Hospital, 60 Fenwood Road, BostonBoston, MA, 02115, USA
- Division of Pulmonary and Critical Care Medicine, Brigham and Women's Hospital, 60 Fenwood Road, Boston, MA, 02115, USA
| | - Scott T Weiss
- Channing Division of Network Medicine, Brigham and Women's Hospital, 60 Fenwood Road, BostonBoston, MA, 02115, USA
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Espuela-Ortiz A, Martin-Gonzalez E, Poza-Guedes P, González-Pérez R, Herrera-Luis E. Genomics of Treatable Traits in Asthma. Genes (Basel) 2023; 14:1824. [PMID: 37761964 PMCID: PMC10531302 DOI: 10.3390/genes14091824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/12/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023] Open
Abstract
The astounding number of genetic variants revealed in the 15 years of genome-wide association studies of asthma has not kept pace with the goals of translational genomics. Moving asthma diagnosis from a nonspecific umbrella term to specific phenotypes/endotypes and related traits may provide insights into features that may be prevented or alleviated by therapeutical intervention. This review provides an overview of the different asthma endotypes and phenotypes and the genomic findings from asthma studies using patient stratification strategies and asthma-related traits. Asthma genomic research for treatable traits has uncovered novel and previously reported asthma loci, primarily through studies in Europeans. Novel genomic findings for asthma phenotypes and related traits may arise from multi-trait and specific phenotyping strategies in diverse populations.
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Affiliation(s)
- Antonio Espuela-Ortiz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Tenerife, Spain; (A.E.-O.); (E.M.-G.)
| | - Elena Martin-Gonzalez
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Tenerife, Spain; (A.E.-O.); (E.M.-G.)
| | - Paloma Poza-Guedes
- Allergy Department, Hospital Universitario de Canarias, 38320 Santa Cruz de Tenerife, Tenerife, Spain; (P.P.-G.); (R.G.-P.)
- Severe Asthma Unit, Hospital Universitario de Canarias, 38320 San Cristóbal de La Laguna, Tenerife, Spain
| | - Ruperto González-Pérez
- Allergy Department, Hospital Universitario de Canarias, 38320 Santa Cruz de Tenerife, Tenerife, Spain; (P.P.-G.); (R.G.-P.)
- Severe Asthma Unit, Hospital Universitario de Canarias, 38320 San Cristóbal de La Laguna, Tenerife, Spain
| | - Esther Herrera-Luis
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
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