1
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Yang Y, Wang Y, Zhu G, Xu S, Liu J, Tang Z. Developing a predictive nomogram for mortality in patients with extrapulmonary acute respiratory distress syndrome: the prognostic value of serum soluble thrombomodulin, lung ultrasound score, and lactate. Front Pharmacol 2024; 15:1407825. [PMID: 39257391 PMCID: PMC11385278 DOI: 10.3389/fphar.2024.1407825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Accepted: 08/02/2024] [Indexed: 09/12/2024] Open
Abstract
Objective: This study aimed to elucidate the prognostic significance of serum soluble thrombomodulin (sTM), lung ultrasound score (LUS), and lactate levels in patients with extrapulmonary acute respiratory distress syndrome (ARDS), with the goal of refining mortality risk prediction in this cohort. Methods: In a prospective cohort of 95 patients with extrapulmonary ARDS admitted to the intensive care unit, we investigated the primary endpoint of 28-day mortality. Utilizing Lasso-Cox regression analysis, we identified independent prognostic factors for mortality. A predictive nomogram was developed incorporating these factors, and its performance was validated through several statistical measures, including the consistency index, calibration plot, internal validation curve, decision curve analysis, interventions avoided analysis, receiver operating characteristic curve analysis, and Kaplan-Meier survival analysis. We further conducted a subgroup analysis to examine the impact of prone positioning on patient outcomes. Results: The study identified baseline serum sTM, LUS, and lactate levels as independent predictors of 28-day mortality in extrapulmonary ARDS patients. The predictive nomogram demonstrated superior prognostic accuracy compared to the use of sTM, LUS, or lactate levels alone, and outperformed traditional prognostic tools such as the Acute Physiology and Chronic Health Evaluation II score and the partial pressure of arterial oxygen to fractional inspired oxygen ratio. The subgroup analysis did not show a significant impact of prone positioning on the predictive value of the identified biomarkers. Conclusion: Our study results support the development and validation of a novel prognostic nomogram that integrates key clinical biomarkers and ultrasound imaging scores to predict mortality in patients with extrapulmonary ARDS. While our research is preliminary, further studies and validation are required.
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Affiliation(s)
- Yang Yang
- Department of Intensive Care Unit, Hefei BOE Hospital Co., Ltd., Hefei, Anhui, China
| | - Yue Wang
- Department of Science and Education, Hefei BOE Hospital Co., Ltd., Hefei, Anhui, China
| | - Guoguo Zhu
- Department of Emergency, Central Theater General Hospital of the People's Liberation Army of China, Wuhan, Hubei, China
| | - Siya Xu
- Department of Emergency, Central Theater General Hospital of the People's Liberation Army of China, Wuhan, Hubei, China
| | - Jie Liu
- Department of Intensive Care Unit, Hefei BOE Hospital Co., Ltd., Hefei, Anhui, China
| | - Zhongzhi Tang
- Department of Emergency, Central Theater General Hospital of the People's Liberation Army of China, Wuhan, Hubei, China
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2
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Wang Y, Chen L, Yao C, Wang T, Wu J, Shang Y, Li B, Xia H, Huang S, Wang F, Wen S, Huang S, Lin Y, Dong N, Yao S. Early plasma proteomic biomarkers and prediction model of acute respiratory distress syndrome after cardiopulmonary bypass: a prospective nested cohort study. Int J Surg 2023; 109:2561-2573. [PMID: 37528797 PMCID: PMC10498873 DOI: 10.1097/js9.0000000000000434] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 04/21/2023] [Indexed: 08/03/2023]
Abstract
BACKGROUND Early recognition of the risk of acute respiratory distress syndrome (ARDS) after cardiopulmonary bypass (CPB) may improve clinical outcomes. The main objective of this study was to identify proteomic biomarkers and develop an early prediction model for CPB-ARDS. METHODS The authors conducted three prospective nested cohort studies of all consecutive patients undergoing cardiac surgery with CPB at Union Hospital of Tongji Medical College Hospital. Plasma proteomic profiling was performed in ARDS patients and matched controls (Cohort 1, April 2021-July 2021) at multiple timepoints: before CPB (T1), at the end of CPB (T2), and 24 h after CPB (T3). Then, for Cohort 2 (August 2021-July 2022), biomarker expression was measured and verified in the plasma. Furthermore, lung ischemia/reperfusion injury (LIRI) models and sham-operation were established in 50 rats to explore the tissue-level expression of biomarkers identified in the aforementioned clinical cohort. Subsequently, a machine learning-based prediction model incorporating protein and clinical predictors from Cohort 2 for CPB-ARDS was developed and internally validated. Model performance was externally validated on Cohort 3 (January 2023-March 2023). RESULTS A total of 709 proteins were identified, with 9, 29, and 35 altered proteins between ARDS cases and controls at T1, T2, and T3, respectively, in Cohort 1. Following quantitative verification of several predictive proteins in Cohort 2, higher levels of thioredoxin domain containing 5 (TXNDC5), cathepsin L (CTSL), and NPC intracellular cholesterol transporter 2 (NPC2) at T2 were observed in CPB-ARDS patients. A dynamic online predictive nomogram was developed based on three proteins (TXNDC5, CTSL, and NPC2) and two clinical risk factors (CPB time and massive blood transfusion), with excellent performance (precision: 83.33%, sensitivity: 93.33%, specificity: 61.16%, and F1 score: 85.05%). The mean area under the receiver operating characteristics curve (AUC) of the model after 10-fold cross-validation was 0.839 (95% CI: 0.824-0.855). Model discrimination and calibration were maintained during external validation dataset testing, with an AUC of 0.820 (95% CI: 0.685-0.955) and a Brier Score of 0.177 (95% CI: 0.147-0.206). Moreover, the considerably overexpressed TXNDC5 and CTSL proteins identified in the plasma of patients with CPB-ARDS, exhibited a significant upregulation in the lung tissue of LIRI rats. CONCLUSIONS This study identified several novel predictive biomarkers, developed and validated a practical prediction tool using biomarker and clinical factor combinations for individual prediction of CPB-ARDS risk. Assessing the plasma TXNDC5, CTSL, and NPC2 levels might identify patients who warrant closer follow-up and intensified therapy for ARDS prevention following major surgery.
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Affiliation(s)
- Yu Wang
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Lin Chen
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | | | - Tingting Wang
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Jing Wu
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - You Shang
- Department of Critical Care Medicine, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Bo Li
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Haifa Xia
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Shiqian Huang
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Fuquan Wang
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | - Shuyu Wen
- Department of Cardiovascular Surgery
| | - Shaoxin Huang
- SpecAlly Life Technology Co., Ltd., Wuhan, Hubei, People’s Republic of China
| | - Yun Lin
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
| | | | - Shanglong Yao
- Department of Anesthesiology
- Key Laboratory of Anesthesiology and Resuscitation (Huazhong University of Science and Technology), Ministry of Education
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3
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Batra R, Uni R, Akchurin OM, Alvarez-Mulett S, Gómez-Escobar LG, Patino E, Hoffman KL, Simmons W, Whalen W, Chetnik K, Buyukozkan M, Benedetti E, Suhre K, Schenck E, Cho SJ, Choi AMK, Schmidt F, Choi ME, Krumsiek J. Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS. Mol Med 2023; 29:13. [PMID: 36703108 PMCID: PMC9879238 DOI: 10.1186/s10020-023-00609-6] [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: 09/29/2022] [Accepted: 01/11/2023] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. METHODS We performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). To this end, we used two different approaches, first we compared the molecular omics profiles between ARDS groups, and second, we correlated clinical manifestations within each group with the omics profiles. RESULTS The comparison of the two ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. CONCLUSION In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.
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Affiliation(s)
- Richa Batra
- grid.5386.8000000041936877XDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021 USA
| | - Rie Uni
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY USA
| | - Oleh M. Akchurin
- grid.5386.8000000041936877XDivision of Pediatric Nephrology, Department of Pediatrics, Weill Cornell Medicine, New York, NY USA ,grid.413734.60000 0000 8499 1112New York-Presbyterian Hospital, New York, NY USA
| | - Sergio Alvarez-Mulett
- grid.5386.8000000041936877XDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Luis G. Gómez-Escobar
- grid.5386.8000000041936877XDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Edwin Patino
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY USA
| | - Katherine L. Hoffman
- grid.5386.8000000041936877XDivision of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY USA
| | - Will Simmons
- grid.5386.8000000041936877XDivision of Biostatistics, Department of Population Health Sciences, Weill Cornell Medicine, New York, NY USA
| | - William Whalen
- grid.5386.8000000041936877XDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Kelsey Chetnik
- grid.5386.8000000041936877XDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021 USA
| | - Mustafa Buyukozkan
- grid.5386.8000000041936877XDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021 USA
| | - Elisa Benedetti
- grid.5386.8000000041936877XDepartment of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021 USA
| | - Karsten Suhre
- grid.418818.c0000 0001 0516 2170Bioinformatics Core, Weill Cornell Medicine –Qatar, Qatar Foundation, Doha, Qatar
| | - Edward Schenck
- grid.5386.8000000041936877XDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Soo Jung Cho
- grid.5386.8000000041936877XDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Augustine M. K. Choi
- grid.5386.8000000041936877XDivision of Pulmonary and Critical Care Medicine, Department of Medicine, Weill Cornell Medicine, New York, NY USA
| | - Frank Schmidt
- Proteomics Core, Weill Cornell Medicine -Qatar, Qatar Foundation, Doha, Qatar.
| | - Mary E. Choi
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY USA
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY, 10021, USA.
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4
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Wu L, Lei Q, Gao Z, Zhang W. Research Progress on Phenotypic Classification of Acute Respiratory Distress Syndrome: A Narrative Review. Int J Gen Med 2022; 15:8767-8774. [PMID: 36601648 PMCID: PMC9807128 DOI: 10.2147/ijgm.s391969] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 12/15/2022] [Indexed: 12/30/2022] Open
Abstract
Acute respiratory distress syndrome (ARDS) is a clinical syndrome that is characterized by an acute onset and refractory hypoxemia. It remains an important contributor to high mortality in critically ill patients, and the majority of clinical randomized controlled trials on ARDS provide underwhelming findings, which is attributed in large part to its pathophysiological and clinical heterogeneity, among other aspects. It is now widely accepted that ARDS is highly heterogeneous, growing evidences support this. ARDS phenotypic and subphenotypic studies aim to further differentiate and identify ARDS heterogeneity in the hope that clinicians can benefit from it, then can diagnose ARDS faster and more accurately and provide targeted treatments. This review collates and evaluates the major phenotype-related research advances of recent years, with a specific focus on ARDS biomarkers and clinical factors.
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Affiliation(s)
- Linlin Wu
- Department of Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, People’s Republic of China
| | - Qian Lei
- Department of Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, People’s Republic of China
| | - Zirong Gao
- Department of Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, People’s Republic of China
| | - Wei Zhang
- Department of Critical Care Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou, People’s Republic of China,Correspondence: Wei Zhang, Email
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5
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Batra R, Whalen W, Alvarez-Mulett S, Gomez-Escobar LG, Hoffman KL, Simmons W, Harrington J, Chetnik K, Buyukozkan M, Benedetti E, Choi ME, Suhre K, Schenck E, Choi AMK, Schmidt F, Cho SJ, Krumsiek J. Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS. PLoS Pathog 2022; 18:e1010819. [PMID: 36121875 PMCID: PMC9484674 DOI: 10.1371/journal.ppat.1010819] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2022] [Accepted: 08/19/2022] [Indexed: 12/06/2022] Open
Abstract
BACKGROUND Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions. METHODS AND FINDINGS In this study, we compared COVID-19 ARDS (n = 43) and bacterial sepsis-induced (non-COVID-19) ARDS (n = 24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within- ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation. CONCLUSION We present a first comprehensive molecular characterization of differences between two ARDS etiologies-COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.
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Affiliation(s)
- Richa Batra
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - William Whalen
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Sergio Alvarez-Mulett
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Luis G. Gomez-Escobar
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Katherine L. Hoffman
- Department of Population Health Sciences, Division of Biostatistics, Weill Cornell Medicine, New York, New York, United States of America
| | - Will Simmons
- Department of Population Health Sciences, Division of Biostatistics, Weill Cornell Medicine, New York, New York, United States of America
| | - John Harrington
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Kelsey Chetnik
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Mustafa Buyukozkan
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Elisa Benedetti
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Mary E. Choi
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, New York, United States of America
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine–Qatar, Qatar Foundation, Doha, Qatar
| | - Edward Schenck
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Augustine M. K. Choi
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Frank Schmidt
- Proteomics Core, Weill Cornell Medicine–Qatar, Qatar Foundation, Doha, Qatar
| | - Soo Jung Cho
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, New York, United States of America
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, New York, United States of America
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6
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Batra R, Whalen W, Alvarez-Mulett S, Gómez-Escobar LG, Hoffman KL, Simmons W, Harrington J, Chetnik K, Buyukozkan M, Benedetti E, Choi ME, Suhre K, Schenck E, Choi AMK, Schmidt F, Cho SJ, Krumsiek J. Multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.05.16.22274587. [PMID: 35982655 PMCID: PMC9387161 DOI: 10.1101/2022.05.16.22274587] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
Background Acute respiratory distress syndrome (ARDS), a life-threatening condition characterized by hypoxemia and poor lung compliance, is associated with high mortality. ARDS induced by COVID-19 has similar clinical presentations and pathological manifestations as non-COVID-19 ARDS. However, COVID-19 ARDS is associated with a more protracted inflammatory respiratory failure compared to traditional ARDS. Therefore, a comprehensive molecular comparison of ARDS of different etiologies groups may pave the way for more specific clinical interventions. Methods and Findings In this study, we compared COVID-19 ARDS (n=43) and bacterial sepsis-induced (non-COVID-19) ARDS (n=24) using multi-omic plasma profiles covering 663 metabolites, 1,051 lipids, and 266 proteins. To address both between- and within-ARDS group variabilities we followed two approaches. First, we identified 706 molecules differently abundant between the two ARDS etiologies, revealing more than 40 biological processes differently regulated between the two groups. From these processes, we assembled a cascade of therapeutically relevant pathways downstream of sphingosine metabolism. The analysis suggests a possible overactivation of arginine metabolism involved in long-term sequelae of ARDS and highlights the potential of JAK inhibitors to improve outcomes in bacterial sepsis-induced ARDS. The second part of our study involved the comparison of the two ARDS groups with respect to clinical manifestations. Using a data-driven multi-omic network, we identified signatures of acute kidney injury (AKI) and thrombocytosis within each ARDS group. The AKI-associated network implicated mitochondrial dysregulation which might lead to post-ARDS renal-sequalae. The thrombocytosis-associated network hinted at a synergy between prothrombotic processes, namely IL-17, MAPK, TNF signaling pathways, and cell adhesion molecules. Thus, we speculate that combination therapy targeting two or more of these processes may ameliorate thrombocytosis-mediated hypercoagulation. Conclusion We present a first comprehensive molecular characterization of differences between two ARDS etiologies - COVID-19 and bacterial sepsis. Further investigation into the identified pathways will lead to a better understanding of the pathophysiological processes, potentially enabling novel therapeutic interventions.
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Affiliation(s)
- Richa Batra
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - William Whalen
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Sergio Alvarez-Mulett
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Luis G Gómez-Escobar
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Katherine L Hoffman
- Department of Population Health Sciences, Division of Biostatistics, Weill Cornell Medicine, New York, NY, USA
| | - Will Simmons
- Department of Population Health Sciences, Division of Biostatistics, Weill Cornell Medicine, New York, NY, USA
| | - John Harrington
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Kelsey Chetnik
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Mustafa Buyukozkan
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Elisa Benedetti
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Mary E Choi
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine - Qatar, Qatar Foundation, Doha, Qatar
| | - Edward Schenck
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Augustine M K Choi
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Frank Schmidt
- Proteomics Core, Weill Cornell Medicine - Qatar, Qatar Foundation, Doha, Qatar
| | - Soo Jung Cho
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
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7
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Batra R, Uni R, Akchurin OM, Alvarez-Mulett S, Gómez-Escobar LG, Patino E, Hoffman KL, Simmons W, Chetnik K, Buyukozkan M, Benedetti E, Suhre K, Schenck E, Cho SJ, Choi AMK, Schmidt F, Choi ME, Krumsiek J. Urine-based multi-omic comparative analysis of COVID-19 and bacterial sepsis-induced ARDS. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2022:2022.08.10.22277939. [PMID: 35982662 PMCID: PMC9387152 DOI: 10.1101/2022.08.10.22277939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Acute respiratory distress syndrome (ARDS), a life-threatening condition during critical illness, is a common complication of COVID-19. It can originate from various disease etiologies, including severe infections, major injury, or inhalation of irritants. ARDS poses substantial clinical challenges due to a lack of etiology-specific therapies, multisystem involvement, and heterogeneous, poor patient outcomes. A molecular comparison of ARDS groups holds the potential to reveal common and distinct mechanisms underlying ARDS pathogenesis. In this study, we performed a comparative analysis of urine-based metabolomics and proteomics profiles from COVID-19 ARDS patients (n = 42) and bacterial sepsis-induced ARDS patients (n = 17). The comparison of these ARDS etiologies identified 150 metabolites and 70 proteins that were differentially abundant between the two groups. Based on these findings, we interrogated the interplay of cell adhesion/extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis through a multi-omic network approach. Moreover, we identified a proteomic signature associated with mortality in COVID-19 ARDS patients, which contained several proteins that had previously been implicated in clinical manifestations frequently linked with ARDS pathogenesis. In summary, our results provide evidence for significant molecular differences in ARDS patients from different etiologies and a potential synergy of extracellular matrix molecules, inflammation, and mitochondrial dysfunction in ARDS pathogenesis. The proteomic mortality signature should be further investigated in future studies to develop prediction models for COVID-19 patient outcomes.
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Affiliation(s)
- Richa Batra
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Rie Uni
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA
| | - Oleh M Akchurin
- Department of Pediatrics, Division of Pediatric Nephrology, Weill Cornell Medicine, New York, NY, USA
- New York-Presbyterian Hospital, New York, NY, USA
| | - Sergio Alvarez-Mulett
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Luis G Gómez-Escobar
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Edwin Patino
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA
| | - Katherine L Hoffman
- Department of Population Health Sciences, Division of Biostatistics, Weill Cornell Medicine, New York, NY, USA
| | - Will Simmons
- Department of Population Health Sciences, Division of Biostatistics, Weill Cornell Medicine, New York, NY, USA
| | - Kelsey Chetnik
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Mustafa Buyukozkan
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Elisa Benedetti
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
| | - Karsten Suhre
- Bioinformatics Core, Weill Cornell Medicine - Qatar, Qatar Foundation, Doha, Qatar
| | - Edward Schenck
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Soo Jung Cho
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Augustine M K Choi
- Department of Medicine, Division of Pulmonary and Critical Care Medicine, Weill Cornell Medicine, New York, NY, USA
| | - Frank Schmidt
- Proteomics Core, Weill Cornell Medicine - Qatar, Qatar Foundation, Doha, Qatar
| | - Mary E Choi
- Division of Nephrology and Hypertension, Joan and Sanford I. Weill Department of Medicine, New York, NY, USA
| | - Jan Krumsiek
- Department of Physiology and Biophysics, Institute for Computational Biomedicine, Englander Institute for Precision Medicine, Weill Cornell Medicine, New York, NY 10021, USA
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8
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Wen XP, Zhang YZ, Wan QQ. Non-targeted proteomics of acute respiratory distress syndrome: clinical and research applications. Proteome Sci 2021; 19:5. [PMID: 33743690 PMCID: PMC7980750 DOI: 10.1186/s12953-021-00174-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2021] [Accepted: 03/11/2021] [Indexed: 01/08/2023] Open
Abstract
Acute respiratory distress syndrome (ARDS) is characterized by refractory hypoxemia caused by accumulation of pulmonary fluid with a high mortality rate, but the underlying mechanism is not yet fully understood, causing absent specific therapeutic drugs to treat with ARDS. In recent years, more and more studies have applied proteomics to ARDS. Non-targeted studies of proteomics in ARDS are just beginning and have the potential to identify novel drug targets and key pathways in this disease. This paper will provide a brief review of the recent advances in the application of non-targeted proteomics to ARDS.
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Affiliation(s)
- Xu-Peng Wen
- Transplantation Center, the Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China
| | - Yue-Zhong Zhang
- Clinical Medicine, Xiangya School of Medicine, Central South University, Changsha, 410083, Hunan, China
| | - Qi-Quan Wan
- Transplantation Center, the Third Xiangya Hospital, Central South University, Changsha, 410013, Hunan, China.
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9
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Wildi K, Livingstone S, Palmieri C, LiBassi G, Suen J, Fraser J. The discovery of biological subphenotypes in ARDS: a novel approach to targeted medicine? J Intensive Care 2021; 9:14. [PMID: 33478589 PMCID: PMC7817965 DOI: 10.1186/s40560-021-00528-w] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2020] [Accepted: 01/11/2021] [Indexed: 12/13/2022] Open
Abstract
The acute respiratory distress syndrome (ARDS) is a severe lung disorder with a high morbidity and mortality which affects all age groups. Despite active research with intense, ongoing attempts in developing pharmacological agents to treat ARDS, its mortality rate remains unaltered high and treatment is still only supportive. Over the years, there have been many attempts to identify meaningful subgroups likely to react differently to treatment among the heterogenous ARDS population, most of them unsuccessful. Only recently, analysis of large ARDS cohorts from randomized controlled trials have identified the presence of distinct biological subphenotypes among ARDS patients: a hypoinflammatory (or uninflamed; named P1) and a hyperinflammatory (or reactive; named P2) subphenotype have been proposed and corroborated with existing retrospective data. The hyperinflammatory subphenotyope was clearly associated with shock state, metabolic acidosis, and worse clinical outcomes. Core features of the respective subphenotypes were identified consistently in all assessed cohorts, independently of the studied population, the geographical location, the study design, or the analysis method. Additionally and clinically even more relevant treatment efficacies, as assessed retrospectively, appeared to be highly dependent on the respective subphenotype. This discovery launches a promising new approach to targeted medicine in ARDS. Even though it is now widely accepted that each ARDS subphenotype has distinct functional, biological, and mechanistic differences, there are crucial gaps in our knowledge, hindering the translation to bedside application. First of all, the underlying driving biological factors are still largely unknown, and secondly, there is currently no option for fast and easy identification of ARDS subphenotypes. This narrative review aims to summarize the evidence in biological subphenotyping in ARDS and tries to point out the current issues that will need addressing before translation of biological subohenotypes into clinical practice will be possible.
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Affiliation(s)
- Karin Wildi
- The Critical Care Research Group, The Prince Charles Hospital, Clinical Sciences Building, Level 3, Chermside, Brisbane, QLD, 4032, Australia. .,Faculty of Medicine, The University of Queensland, Brisbane, Australia. .,Cardiovascular Research Group, Basel, Switzerland.
| | - Samantha Livingstone
- The Critical Care Research Group, The Prince Charles Hospital, Clinical Sciences Building, Level 3, Chermside, Brisbane, QLD, 4032, Australia.,Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Chiara Palmieri
- School of Veterinary Science, the University of Queensland, Brisbane, Australia
| | - Gianluigi LiBassi
- The Critical Care Research Group, The Prince Charles Hospital, Clinical Sciences Building, Level 3, Chermside, Brisbane, QLD, 4032, Australia.,Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - Jacky Suen
- The Critical Care Research Group, The Prince Charles Hospital, Clinical Sciences Building, Level 3, Chermside, Brisbane, QLD, 4032, Australia.,Faculty of Medicine, The University of Queensland, Brisbane, Australia
| | - John Fraser
- The Critical Care Research Group, The Prince Charles Hospital, Clinical Sciences Building, Level 3, Chermside, Brisbane, QLD, 4032, Australia.,Faculty of Medicine, The University of Queensland, Brisbane, Australia
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10
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Stancioiu F, Papadakis GZ, Kteniadakis S, Izotov BN, Coleman MD, Spandidos DA, Tsatsakis A. A dissection of SARS‑CoV2 with clinical implications (Review). Int J Mol Med 2020; 46:489-508. [PMID: 32626922 PMCID: PMC7307812 DOI: 10.3892/ijmm.2020.4636] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 06/09/2020] [Indexed: 02/06/2023] Open
Abstract
We are being confronted with the most consequential pandemic since the Spanish flu of 1918‑1920 to the extent that never before have 4 billion people quarantined simultaneously; to address this global challenge we bring to the forefront the options for medical treatment and summarize SARS‑CoV2 structure and functions, immune responses and known treatments. Based on literature and our own experience we propose new interventions, including the use of amiodarone, simvastatin, pioglitazone and curcumin. In mild infections (sore throat, cough) we advocate prompt local treatment for the naso‑pharynx (inhalations; aerosols; nebulizers); for moderate to severe infections we propose a tried‑and‑true treatment: the combination of arginine and ascorbate, administered orally or intravenously. The material is organized in three sections: i) Clinical aspects of COVID‑19; acute respiratory distress syndrome (ARDS); known treatments; ii) Structure and functions of SARS‑CoV2 and proposed antiviral drugs; iii) The combination of arginine‑ascorbate.
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Affiliation(s)
| | | | | | - Boris Nikovaevich Izotov
- Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991 Moscow, Russia
| | - Michael D. Coleman
- School of Life and Health Sciences, Aston University, B4 7ET Birmingham, UK
| | | | - Aristidis Tsatsakis
- Department of Analytical and Forensic Medical Toxicology, Sechenov University, 119991 Moscow, Russia
- Department of Forensic Sciences and Toxicology, Faculty of Medicine, University of Crete, 71003 Heraklion, Greece
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11
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Wu AC, Kiley JP, Noel PJ, Amur S, Burchard EG, Clancy JP, Galanter J, Inada M, Jones TK, Kropski JA, Loyd JE, Nogee LM, Raby BA, Rogers AJ, Schwartz DA, Sin DD, Spira A, Weiss ST, Young LR, Himes BE. Current Status and Future Opportunities in Lung Precision Medicine Research with a Focus on Biomarkers. An American Thoracic Society/National Heart, Lung, and Blood Institute Research Statement. Am J Respir Crit Care Med 2019; 198:e116-e136. [PMID: 30640517 DOI: 10.1164/rccm.201810-1895st] [Citation(s) in RCA: 42] [Impact Index Per Article: 8.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Thousands of biomarker tests are either available or under development for lung diseases. In many cases, adoption of these tests into clinical practice is outpacing the generation and evaluation of sufficient data to determine clinical utility and ability to improve health outcomes. There is a need for a systematically organized report that provides guidance on how to understand and evaluate use of biomarker tests for lung diseases. METHODS We assembled a diverse group of clinicians and researchers from the American Thoracic Society and leaders from the National Heart, Lung, and Blood Institute with expertise in various aspects of precision medicine to review the current status of biomarker tests in lung diseases. Experts summarized existing biomarker tests that are available for lung cancer, pulmonary arterial hypertension, idiopathic pulmonary fibrosis, asthma, chronic obstructive pulmonary disease, sepsis, acute respiratory distress syndrome, cystic fibrosis, and other rare lung diseases. The group identified knowledge gaps that future research studies can address to efficiently translate biomarker tests into clinical practice, assess their cost-effectiveness, and ensure they apply to diverse, real-life populations. RESULTS We found that the status of biomarker tests in lung diseases is highly variable depending on the disease. Nevertheless, biomarker tests in lung diseases show great promise in improving clinical care. To efficiently translate biomarkers into tests used widely in clinical practice, researchers need to address specific clinical unmet needs, secure support for biomarker discovery efforts, conduct analytical and clinical validation studies, ensure tests have clinical utility, and facilitate appropriate adoption into routine clinical practice. CONCLUSIONS Although progress has been made toward implementation of precision medicine for lung diseases in clinical practice in certain settings, additional studies focused on addressing specific unmet clinical needs are required to evaluate the clinical utility of biomarkers; ensure their generalizability to diverse, real-life populations; and determine their cost-effectiveness.
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12
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Lin S, Yue X, Wu H, Han TL, Zhu J, Wang C, Lei M, Zhang M, Liu Q, Xu F. Explore potential plasma biomarkers of acute respiratory distress syndrome (ARDS) using GC-MS metabolomics analysis. Clin Biochem 2019; 66:49-56. [PMID: 30779905 DOI: 10.1016/j.clinbiochem.2019.02.009] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2019] [Revised: 02/06/2019] [Accepted: 02/15/2019] [Indexed: 12/16/2022]
Abstract
OBJECTIVES The aim of this study was to analyse the metabolomics of patients with acute respiratory distress syndrome (ARDS) for the identification of metabolic markers with potential diagnostic and prognostic value. METHODS The enrolled subjects included adult patients with ARDS that met the Berlin definition and healthy controls matched based on age, gender, and body mass index (BMI). Plasma samples were collected from 37 patients with ARDS and 28 healthy controls. The plasma metabolites were detected with gas chromatography-mass spectrometry (GC-MS), and the relevant metabolic pathways were predicted using the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. RESULTS A total of 222 metabolites were identified in our study, of which 128 were significantly altered in patients with ARDS compared with healthy controls. Phenylalanine, aspartic acid, and carbamic acid levels were significantly different between all groups of patients with ARDS classified from mild to severe. Furthermore, four metabolites, ornithine, caprylic acid, azetidine, and iminodiacetic acid, could serve as biomarkers to potentially predict the severity of ARDS. We discovered 92 pathways that were significantly different between ARDS and control groups, including 57 pathways linked to metabolism. CONCLUSIONS Plasma metabolomics may improve our understanding of ARDS biology. Specific products related to hypoxia may serve as early biomarkers for ARDS prediction, while the metabolites with significant correlations with partial pressure of arterial oxygen (PaO2)/percentage of inspired oxygen (FiO2) may play a role in determining ARDS severity. This study suggests that metabolomic analysis in patients at risk of ARDS or those with early ARDS may provide new insight into disease pathogenesis or prognosis.
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Affiliation(s)
- Shihui Lin
- The Chongqing Key Laboratory of Translation Medicine in Major Metabolic Diseases, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China; Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Xi Yue
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Hua Wu
- Stanford University, Center for Cognitive and Neurobiological Imaging, Palo Alto, CA, USA
| | - Ting-Li Han
- China-Canada-New Zealand Jointed International Mass Spectrometry Center of Maternal-Fetal Medicine, Chongqing Medical University, China; University of Auckland, Liggins Institute, Auckland, NZ, New Zealand
| | - Jing Zhu
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Chuanjiang Wang
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Ming Lei
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Mu Zhang
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Qiong Liu
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China
| | - Fang Xu
- Departmen of Emergency and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, China.
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13
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The peroxisome proliferator-activated receptor agonist pioglitazone and 5-lipoxygenase inhibitor zileuton have no effect on lung inflammation in healthy volunteers by positron emission tomography in a single-blind placebo-controlled cohort study. PLoS One 2018; 13:e0191783. [PMID: 29414995 PMCID: PMC5802889 DOI: 10.1371/journal.pone.0191783] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2017] [Accepted: 01/11/2018] [Indexed: 11/22/2022] Open
Abstract
Background Anti-inflammatory drug development efforts for lung disease have been hampered in part by the lack of noninvasive inflammation biomarkers and the limited ability of animal models to predict efficacy in humans. We used 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET) in a human model of lung inflammation to assess whether pioglitazone, a peroxisome proliferator-activated receptor-γ (PPAR-γ) agonist, and zileuton, a 5-lipoxygenase inhibitor, reduce lung inflammation. Methods For this single center, single-blind, placebo-controlled cohort study, we enrolled healthy volunteers sequentially into the following treatment cohorts (N = 6 per cohort): pioglitazone plus placebo, zileuton plus placebo, or dual placebo prior to bronchoscopic endotoxin instillation. 18F-FDG uptake pre- and post-endotoxin was quantified as the Patlak graphical analysis-determined Ki (primary outcome measure). Secondary outcome measures included the mean standard uptake value (SUVmean), post-endotoxin bronchoalveolar lavage (BAL) cell counts and differentials and blood adiponectin and urinary leukotriene E4 (LTE4) levels, determined by enzyme-linked immunosorbent assay, to verify treatment compliance. One- or two-way analysis of variance assessed for differences among cohorts in the outcome measures (expressed as mean ± standard deviation). Results Ten females and eight males (29±6 years of age) completed all study procedures except for one volunteer who did not complete the post-endotoxin BAL. Ki and SUVmean increased in all cohorts after endotoxin instillation (Ki increased by 0.0021±0.0019, 0.0023±0.0017, and 0.0024±0.0020 and SUVmean by 0.47±0.14, 0.55±0.15, and 0.54±0.38 in placebo, pioglitazone, and zileuton cohorts, respectively, p<0.001) with no differences among treatment cohorts (p = 0.933). Adiponectin levels increased as expected with pioglitazone treatment but not urinary LTE4 levels as expected with zileuton treatment. BAL cell counts (p = 0.442) and neutrophil percentage (p = 0.773) were similar among the treatment cohorts. Conclusions Endotoxin-induced lung inflammation in humans is not responsive to pioglitazone or zileuton, highlighting the challenge in translating anti-inflammatory drug efficacy results from murine models to humans. Trial registration ClinicalTrials.gov NCT01174056.
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14
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Kan M, Shumyatcher M, Himes BE. Using omics approaches to understand pulmonary diseases. Respir Res 2017; 18:149. [PMID: 28774304 PMCID: PMC5543452 DOI: 10.1186/s12931-017-0631-9] [Citation(s) in RCA: 77] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2017] [Accepted: 07/26/2017] [Indexed: 12/24/2022] Open
Abstract
Omics approaches are high-throughput unbiased technologies that provide snapshots of various aspects of biological systems and include: 1) genomics, the measure of DNA variation; 2) transcriptomics, the measure of RNA expression; 3) epigenomics, the measure of DNA alterations not involving sequence variation that influence RNA expression; 4) proteomics, the measure of protein expression or its chemical modifications; and 5) metabolomics, the measure of metabolite levels. Our understanding of pulmonary diseases has increased as a result of applying these omics approaches to characterize patients, uncover mechanisms underlying drug responsiveness, and identify effects of environmental exposures and interventions. As more tissue- and cell-specific omics data is analyzed and integrated for diverse patients under various conditions, there will be increased identification of key mechanisms that underlie pulmonary biological processes, disease endotypes, and novel therapeutics that are efficacious in select individuals. We provide a synopsis of how omics approaches have advanced our understanding of asthma, chronic obstructive pulmonary disease (COPD), acute respiratory distress syndrome (ARDS), idiopathic pulmonary fibrosis (IPF), and pulmonary arterial hypertension (PAH), and we highlight ongoing work that will facilitate pulmonary disease precision medicine.
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Affiliation(s)
- Mengyuan Kan
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, 402 Blockley Hall 423 Guardian Drive, Philadelphia, PA 19104 USA
| | - Maya Shumyatcher
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, 402 Blockley Hall 423 Guardian Drive, Philadelphia, PA 19104 USA
| | - Blanca E. Himes
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, 402 Blockley Hall 423 Guardian Drive, Philadelphia, PA 19104 USA
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15
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Rogers AJ, Contrepois K, Wu M, Zheng M, Peltz G, Ware LB, Matthay MA. Profiling of ARDS pulmonary edema fluid identifies a metabolically distinct subset. Am J Physiol Lung Cell Mol Physiol 2017; 312:L703-L709. [PMID: 28258106 DOI: 10.1152/ajplung.00438.2016] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2016] [Revised: 02/24/2017] [Accepted: 03/01/2017] [Indexed: 12/29/2022] Open
Abstract
There is considerable biological and physiological heterogeneity among patients who meet standard clinical criteria for acute respiratory distress syndrome (ARDS). In this study, we tested the hypothesis that there exists a subgroup of ARDS patients who exhibit a metabolically distinct profile. We examined undiluted pulmonary edema fluid obtained at the time of endotracheal intubation from 16 clinically phenotyped ARDS patients and 13 control patients with hydrostatic pulmonary edema. Nontargeted metabolic profiling was carried out on the undiluted edema fluid. Univariate and multivariate statistical analyses including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were conducted to find discriminant metabolites. Seven-hundred and sixty unique metabolites were identified in the pulmonary edema fluid of these 29 patients. We found that a subset of ARDS patients (6/16, 38%) presented a distinct metabolic profile with the overrepresentation of 235 metabolites compared with edema fluid from the other 10 ARDS patients, whose edema fluid metabolic profile was indistinguishable from those of the 13 control patients with hydrostatic edema. This "high metabolite" endotype was characterized by higher concentrations of metabolites belonging to all of the main metabolic classes including lipids, amino acids, and carbohydrates. This distinct group with high metabolite levels in the edema fluid was also associated with a higher mortality rate. Thus metabolic profiling of the edema fluid of ARDS patients supports the hypothesis that there is considerable biological heterogeneity among ARDS patients who meet standard clinical and physiological criteria for ARDS.
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Affiliation(s)
- Angela J Rogers
- Pulmonary and Critical Care Division, Department of Medicine, Stanford, California;
| | - Kévin Contrepois
- Department of Genetics, Stanford University School of Medicine, Stanford, California
| | - Manhong Wu
- Department of Anesthesia, Stanford University School of Medicine, Stanford, California
| | - Ming Zheng
- Department of Anesthesia, Stanford University School of Medicine, Stanford, California
| | - Gary Peltz
- Department of Anesthesia, Stanford University School of Medicine, Stanford, California
| | - Lorraine B Ware
- Division of Allergy, Pulmonary and Critical Care Medicine, Department of Medicine and Department of Pathology, Microbiology and Immunology, Vanderbilt University School of Medicine, Nashville, Tennessee; and
| | - Michael A Matthay
- Departments of Medicine and Anesthesia, Cardiovascular Research Institute, University of California, San Francisco, California
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