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Zhao L, Bian W, Shang Y, Zhi H, Ma X, He Y, Yu W, Liu C, Xu Y, Gong P, Gao Z. Plasma proteome analysis and validation of patients with community-acquired pneumonia: A cohort study. Proteomics Clin Appl 2024; 18:e202300069. [PMID: 38332320 DOI: 10.1002/prca.202300069] [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: 06/16/2023] [Revised: 12/16/2023] [Accepted: 12/21/2023] [Indexed: 02/10/2024]
Abstract
PURPOSE This study aimed to investigate the diagnostic potential of plasma biomarkers of community-acquired pneumonia (CAP) and their severity grading. EXPERIMENTAL DESIGN Plasma proteomes from cohort I (n = 32) with CAP were analyzed by data-independent acquisition mass spectrometry (MS). MetaboAnalyst 5.0 was used to statistically evaluate significant differences in proteins from different samples, and demographic and clinical data were recorded for all enrolled patients. Cohort II (n = 80) was used to validate candidate biomarkers. Plasma protein levels were determined using quantitative enzyme-linked immunosorbent assay (ELISA). Correlations were assessed using Pearson's correlation coefficient. A receiver operating characteristic curve was used to verify the association between the variables, CAP diagnosis, and prognosis. RESULTS 121 differentially expressed proteins (DEPs) were obtained between CAP and controls. These DEPs were mainly aggregated in pathways of phagosome(hsa04145) and complement and coagulation cascades (hsa04610). No significant differential proteins were detected in bacterial, viral, and mixed infection groups. The plasma levels of fetuin-A, alpha-1-antichymotrypsin (AACT), α1-acid glycoprotein (A1AG), and S100A8/S100A9 heterodimers detected by ELISA were consistent with those of MS. AACT, A1AG, S100A8/S100A9 heterodimer, and fetuin-A can potentially be used as diagnostic predictors, and fetuin-A and AACT are potential predictors of SCAP. CONCLUSIONS AND CLINICAL RELEVANCE Plasma protein profiling can successfully identify potential biomarkers for CAP diagnosis and disease severity assessment. These biomarkers should be further studied for their clinical application.
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Affiliation(s)
- Lili Zhao
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Wenjie Bian
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Ying Shang
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Hui Zhi
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Xinqian Ma
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Yukun He
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Wenyi Yu
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Chunyu Liu
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Yu Xu
- Department of Respiratory and Critical Care Medicine, Beijing Jishuitan Hospital, Beijing, China
| | - Pihua Gong
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
| | - Zhancheng Gao
- Department of Respiratory and Critical Care Medicine, Peking University People's Hospital, Beijing, China
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Wang Y, Huang X, Li F, Jia X, Jia N, Fu J, Liu S, Zhang J, Ge H, Huang S, Hui Y, Sun C, Xiao F, Cui X, Luu LDW, Qu D, Li J, Tai J. Serum-integrated omics reveal the host response landscape for severe pediatric community-acquired pneumonia. Crit Care 2023; 27:79. [PMID: 36859478 PMCID: PMC9976684 DOI: 10.1186/s13054-023-04378-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2022] [Accepted: 02/21/2023] [Indexed: 03/03/2023] Open
Abstract
OBJECTIVE Community-acquired pneumonia (CAP) is the primary cause of death for children under five years of age globally. Hence, it is essential to investigate new early biomarkers and potential mechanisms involved in disease severity. METHODS Proteomics combined with metabolomics was performed to identify biomarkers suitable for early diagnosis of severe CAP. In the training cohort, proteomics and metabolomics were performed on serum samples obtained from 20 severe CAPs (S-CAPs), 15 non-severe CAPs (NS-CAPs) and 15 healthy controls (CONs). In the verification cohort, selected biomarkers and their combinations were validated using ELISA and metabolomics in an independent cohort of 129 subjects. Finally, a combined proteomics and metabolomics analysis was performed to understand the major pathological features and reasons for severity of CAP. RESULTS The proteomic and metabolic signature was markedly different between S-CAPs, NS-CAPs and CONs. A new serum biomarker panel including 2 proteins [C-reactive protein (CRP), lipopolysaccharide (LBP)] and 3 metabolites [Fasciculol C, PE (14:0/16:1(19Z)), PS (20:0/22:6(4Z, 7Z, 10Z, 13Z, 16Z, 19Z))] was developed to identify CAP and to distinguish severe pneumonia. Pathway analysis of changes revealed activation of the cell death pathway, a dysregulated complement system, coagulation cascade and platelet function, and the inflammatory responses as contributors to tissue damage in children with CAP. Additionally, activation of glycolysis and higher levels of nucleotides led to imbalanced deoxyribonucleotide pools contributing to the development of severe CAP. Finally, dysregulated lipid metabolism was also identified as a potential pathological mechanism for severe progression of CAP. CONCLUSION The integrated analysis of the proteome and metabolome might open up new ways in diagnosing and uncovering the complexity of severity of CAP.
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Affiliation(s)
- Yi Wang
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China.
| | - Xiaolan Huang
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Fang Li
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Xinbei Jia
- Department of Otorhinolaryngology Head and Neck Surgery, Children's Hospital Capital Institute of Pediatrics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China
| | - Nan Jia
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Jin Fu
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Shuang Liu
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Jin Zhang
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Haiyan Ge
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Siyuan Huang
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Yi Hui
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Chunrong Sun
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Fei Xiao
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | - Xiaodai Cui
- Experimental Research Center, Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China
| | | | - Dong Qu
- Department of Critical Medicine, Children's Hospital Affiliated Capital Institute of Pediatrics, Beijing, 100020, People's Republic of China.
| | - Jieqiong Li
- Department of Respiratory and Critical Care Medicine, Beijing Institute of Respiratory Medicine, Beijing Chaoyang Hospital, Capital Medical University, Beijing, 100027, People's Republic of China.
| | - Jun Tai
- Department of Otorhinolaryngology Head and Neck Surgery, Children's Hospital Capital Institute of Pediatrics, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, People's Republic of China.
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Chen S, Su M, Lei W, Wu Z, Wu S, Liu J, Huang X, Chen G, Zhang Q, Zhong H, Rong F, Li X, Xiao Q. A Nomogram for Early Diagnosis of Community-Acquired Pneumonia Based on Bronchoalveolar Lavage Fluid Metabolomics. Infect Drug Resist 2023; 16:1237-1248. [PMID: 36883043 PMCID: PMC9985881 DOI: 10.2147/idr.s400390] [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: 12/21/2022] [Accepted: 02/21/2023] [Indexed: 03/06/2023] Open
Abstract
Purpose There is a high disease burden associated with community-acquired pneumonia (CAP) around the world. A timely and correct diagnosis of CAP can facilitate early treatment and prevent illness progression. The present study aimed to find some novel biomarkers of CAP by metabolic analysis and construct a nomogram model for precise diagnosis and individualized treatment of CAP patients. Patients and Methods 42 CAP patients and 20 controls were enrolled in this study. The metabolic profiles of bronchoalveolar lavage fluid (BALF) samples were identified by untargeted LC-MS/MS analysis. With a VIP score ≥ 1 in OPLS-DA analysis and P < 0.05, the significantly dysregulated metabolites were estimated as potential biomarkers of CAP, which were further included in the construction of the diagnostic prediction model along with laboratory inflammatory indexes via stepwise backward regression analysis. Discrimination, calibration, and clinical applicability of the nomogram were evaluated by the C-index, the calibration curve, and the decision curve analysis (DCA) estimated by bootstrap resampling. Results The metabolic profiles differed obviously between CAP patients and healthy controls, as shown by PCA and OPLS-DA plots. Seven metabolites significantly dysregulated in CAP were established: dimethyl disulfide, oleic acid (d5), N-acetyl-a-neuraminic acid, pyrimidine, choline, LPC (12:0/0:0) and PA (20:4/2:0). Multivariate logistic regression revealed that the expression levels of PA (20:4/2:0), N-acetyl-a-neuraminic acid, and CRP were associated with CAP. After being validated by bootstrap resampling, this model showed satisfactory diagnostic performance. Conclusion A novel nomogram prediction model containing metabolic potential biomarkers in BALF that was developed for the early diagnosis of CAP offers insights into the pathogenesis and host response in CAP.
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Affiliation(s)
- Siqin Chen
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Minhong Su
- Pulmonary and Critical Care Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, People's Republic of China
| | - Wei Lei
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Zhida Wu
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Shuhong Wu
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Jing Liu
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Xiaoyan Huang
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Guiyang Chen
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Qian Zhang
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Hua Zhong
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Fu Rong
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Xi Li
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
| | - Qiang Xiao
- Pulmonary and Critical Care Medicine, Shunde Hospital, Southern Medical University (The First People's Hospital of Shunde Foshan), Foshan, Guangdong, People's Republic of China
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Infection Biomarkers Based on Metabolomics. Metabolites 2022; 12:metabo12020092. [PMID: 35208167 PMCID: PMC8877834 DOI: 10.3390/metabo12020092] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/10/2022] [Accepted: 01/14/2022] [Indexed: 12/18/2022] Open
Abstract
Current infection biomarkers are highly limited since they have low capability to predict infection in the presence of confounding processes such as in non-infectious inflammatory processes, low capability to predict disease outcomes and have limited applications to guide and evaluate therapeutic regimes. Therefore, it is critical to discover and develop new and effective clinical infection biomarkers, especially applicable in patients at risk of developing severe illness and critically ill patients. Ideal biomarkers would effectively help physicians with better patient management, leading to a decrease of severe outcomes, personalize therapies, minimize antibiotics overuse and hospitalization time, and significantly improve patient survival. Metabolomics, by providing a direct insight into the functional metabolic outcome of an organism, presents a highly appealing strategy to discover these biomarkers. The present work reviews the desired main characteristics of infection biomarkers, the main metabolomics strategies to discover these biomarkers and the next steps for developing the area towards effective clinical biomarkers.
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Rombauts A, Abelenda-Alonso G, Cuervo G, Gudiol C, Carratalà J. Role of the inflammatory response in community-acquired pneumonia: clinical implications. Expert Rev Anti Infect Ther 2021; 20:1261-1274. [PMID: 33034228 DOI: 10.1080/14787210.2021.1834848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
INTRODUCTION Despite adequate antibiotic coverage, community-acquired pneumonia (CAP) remains a leading cause of hospitalization and mortality worldwide. It induces both a local pulmonary and a systemic inflammatory response, particularly significant in severe cases. The intensity of the dysregulated host response varies from patient to patient and has a negative impact on survival and other outcomes. AREAS COVERED This comprehensive review summarizes the pathophysiological aspects of the inflammatory response in CAP, briefly discusses the usefulness of biomarkers, and assesses the clinical evidence for modulating the inflammatory pathways. We searched PubMed for the most relevant studies, reviews, and meta-analysis until August 2020. EXPERT OPINION Notable efforts have been made to identify biomarkers that can accurately differentiate between viral and bacterial etiology, and indeed, to enhance risk stratification in CAP. However, none has proven ideal and no recommended biomarker-guided algorithms exist. Biomarker signatures from proteomic and metabolomic studies could be more useful for such assessments. To date, most studies have produced contradictory results concerning the role of immunomodulatory agents (e.g. corticosteroids, macrolides, and statins) in CAP. Adequately identifying the population who may benefit most from effective modulation of the inflammatory response remains a challenge.
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Affiliation(s)
- Alexander Rombauts
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain
| | - Gabriela Abelenda-Alonso
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain
| | - Guillermo Cuervo
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain
| | - Carlota Gudiol
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain.,Spanish Network for Research in Infectious Disease (REIPI), Instituto de Salud Carlos III, Madrid, Spain.,University of Barcelona, Barcelona, Spain.,Institut Català d'Oncologia (ICO), Hospitalet de Llobregat, Barcelona, Spain
| | - Jordi Carratalà
- Department of Infectious Diseases, Hospital Universitari de Bellvitge, Hospitalet de Llobregat, Barcelona, Spain.,Bellvitge Biomedical Research Institute (IDIBELL), Hospitalet de Llobregat, Spain.,Spanish Network for Research in Infectious Disease (REIPI), Instituto de Salud Carlos III, Madrid, Spain.,University of Barcelona, Barcelona, Spain
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