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Deng Y, Leng L, Wang C, Yang Q, Hu Y. Analyzing the molecular mechanism of Scutellaria Radix in the treatment of sepsis using RNA sequencing. BMC Infect Dis 2024; 24:695. [PMID: 38997656 PMCID: PMC11241924 DOI: 10.1186/s12879-024-09589-2] [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: 11/25/2023] [Accepted: 07/04/2024] [Indexed: 07/14/2024] Open
Abstract
BACKGROUND Sepsis is a life-threatening organ dysfunction, which seriously threatens human health. The clinical and experimental results have confirmed that Traditional Chinese medicine (TCM), such as Scutellariae Radix, has anti-inflammatory effects. This provides a new idea for the treatment of sepsis. This study systematically analyzed the mechanism of Scutellariae Radix treatment in sepsis based on network pharmacology, RNA sequencing and molecular docking. METHODS Gene expression analysis was performed using Bulk RNA sequencing on sepsis patients and healthy volunteers. After quality control of the results, the differentially expressed genes (DEGs) were analyzed. The active ingredients and targets of Scutellariae Radix were identified using The Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Gene Ontology (GO) and Protein-Protein Interaction (PPI) analysis were performed for disease-drug intersection targets. With the help of GEO database, Survival analysis and Meta-analysis was performed on the cross-targets to evaluate the prognostic value and screen the core targets. Subsequently, single-cell RNA sequencing was used to determine where the core targets are located within the cell. Finally, in this study, molecular docking experiments were performed to further clarify the interrelationship between the active components of Scutellariae Radix and the corresponding targets. RESULTS There were 72 active ingredients of Scutellariae Radix, and 50 common targets of drug and disease. GO and PPI analysis showed that the intersection targets were mainly involved in response to chemical stress, response to oxygen levels, response to drug, regulation of immune system process. Survival analysis showed that PRKCD, EGLN1 and CFLAR were positively correlated with sepsis prognosis. Meta-analysis found that the three genes were highly expressed in sepsis survivor, while lowly in non-survivor. PRKCD was mostly found in Macrophages, while EGLN1 and CFLAR were widely expressed in immune cells. The active ingredient Apigenin regulates CFLAR expression, Baicalein regulates EGLN1 expression, and Wogonin regulates PRKCD expression. Molecular docking studies confrmed that the three active components of astragalus have good binding activities with their corresponding targets. CONCLUSIONS Apigenin, Baicalein and Wogonin, important active components of Scutellaria Radix, produce anti-sepsis effects by regulating the expression of their targets CFLAR, EGLN1 and PRKCD.
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Affiliation(s)
- Yaxing Deng
- Department of General Surgery (Gastrointestinal Surgery), The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, China
| | - Linghan Leng
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, China
| | - Chenglin Wang
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, China
| | - Qingqiang Yang
- Department of General Surgery (Gastrointestinal Surgery), The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, China.
| | - Yingchun Hu
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, China.
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Chenoweth JG, Brandsma J, Striegel DA, Genzor P, Chiyka E, Blair PW, Krishnan S, Dogbe E, Boakye I, Fogel GB, Tsalik EL, Woods CW, Owusu-Ofori A, Oppong C, Oduro G, Vantha T, Letizia AG, Beckett CG, Schully KL, Clark DV. Sepsis endotypes identified by host gene expression across global cohorts. COMMUNICATIONS MEDICINE 2024; 4:120. [PMID: 38890515 PMCID: PMC11189468 DOI: 10.1038/s43856-024-00542-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 06/04/2024] [Indexed: 06/20/2024] Open
Abstract
BACKGROUND Sepsis from infection is a global health priority and clinical trials have failed to deliver effective therapeutic interventions. To address complicating heterogeneity in sepsis pathobiology, and improve outcomes, promising precision medicine approaches are helping identify disease endotypes, however, they require a more complete definition of sepsis subgroups. METHODS Here, we use RNA sequencing from peripheral blood to interrogate the host response to sepsis from participants in a global observational study carried out in West Africa, Southeast Asia, and North America (N = 494). RESULTS We identify four sepsis subtypes differentiated by 28-day mortality. A low mortality immunocompetent group is specified by features that describe the adaptive immune system. In contrast, the three high mortality groups show elevated clinical severity consistent with multiple organ dysfunction. The immunosuppressed group members show signs of a dysfunctional immune response, the acute-inflammation group is set apart by molecular features of the innate immune response, while the immunometabolic group is characterized by metabolic pathways such as heme biosynthesis. CONCLUSIONS Our analysis reveals details of molecular endotypes in sepsis that support immunotherapeutic interventions and identifies biomarkers that predict outcomes in these groups.
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Affiliation(s)
- Josh G Chenoweth
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA.
| | - Joost Brandsma
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Deborah A Striegel
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Pavol Genzor
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Elizabeth Chiyka
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Paul W Blair
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Subramaniam Krishnan
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
| | - Elliot Dogbe
- Laboratory Services Directorate, KATH, Kumasi, Ghana
| | - Isaac Boakye
- Research and Development Unit, KATH, Kumasi, Ghana
| | | | - Ephraim L Tsalik
- Center for Infectious Disease Diagnostics and Innovation, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Danaher Diagnostics, Washington, DC., USA
| | - Christopher W Woods
- Center for Infectious Disease Diagnostics and Innovation, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Alex Owusu-Ofori
- Laboratory Services Directorate, KATH, Kumasi, Ghana
- Department of Clinical Microbiology, Kwame Nkrumah University of Science and Technology (KNUST), Kumasi, Ghana
| | - Chris Oppong
- Accident and Emergency Department, KATH, Kumasi, Ghana
| | - George Oduro
- Accident and Emergency Department, KATH, Kumasi, Ghana
| | - Te Vantha
- Takeo Provincial Referral Hospital, Takeo, Cambodia
| | - Andrew G Letizia
- Naval Medical Research Unit EURAFCENT Ghana detachment, Accra, Ghana
| | - Charmagne G Beckett
- Naval Medical Research Command Infectious Diseases Directorate, Silver Spring, MD, USA
| | - Kevin L Schully
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), Biological Defense Research Directorate, Naval Medical Research Command-Frederick, Ft. Detrick, Maryland, MD, USA
| | - Danielle V Clark
- Austere environments Consortium for Enhanced Sepsis Outcomes (ACESO), The Henry M. Jackson Foundation for the Advancement of Military Medicine, Inc., Bethesda, MD, USA
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3
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Chen Z, Wei S, Yuan Z, Chang R, Chen X, Fu Y, Wu W. Machine learning reveals ferroptosis features and a novel ferroptosis classifier in patients with sepsis. Immun Inflamm Dis 2024; 12:e1279. [PMID: 38780016 PMCID: PMC11112629 DOI: 10.1002/iid3.1279] [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: 11/06/2023] [Revised: 04/24/2024] [Accepted: 05/06/2024] [Indexed: 05/25/2024] Open
Abstract
OBJECTIVE Sepsis is an organ malfunction disease that may become fatal and is commonly accompanied by severe complications such as multiorgan dysfunction. Patients who are already hospitalized have a high risk of death due to sepsis. Even though early diagnosis is very important, the technology and clinical approaches that are now available are inadequate. Hence, there is an immediate necessity to investigate biological markers that are sensitive, specific, and reliable for the prompt detection of sepsis to reduce mortality and improve patient prognosis. Mounting research data indicate that ferroptosis contributes to the occurrence, development, and prevention of sepsis. However, the specific regulatory mechanism of ferroptosis remains to be elucidated. This research evaluated the expression profiles of ferroptosis-related genes (FRGs) and the diagnostic significance of the ferroptosis-related classifiers in sepsis. METHODS AND RESULTS We collected three peripheral blood data sets from septic patients, integrated the clinical examination data and mRNA expression profile of these patients, and identified 13 FRGs in sepsis through a co-expression network and differential analysis. Then, an optimal classifier tool for sepsis was constructed by integrating a variety of machine learning algorithms. Two key genes, ATG16L1 and SRC, were shown to be shared between the algorithms, and thus were identified as the FRG signature of classifier. The tool exhibited satisfactory diagnostic efficiency in the training data set (AUC = 0.711) and two external verification data sets (AUC = 0.961; AUC = 0.913). In the rat cecal ligation puncture sepsis model, in vivo experiments verified the involvement of ATG16L1 and SRC in the early sepsis process. CONCLUSION These findings confirm that FRGs may participate in the development of sepsis, the ferroptosis related classifiers can provide a basis for the development of new strategies for the early diagnosis of sepsis and the discovery of new potential therapeutic targets for life-threatening infections.
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Affiliation(s)
- Zhigang Chen
- Department of Anesthesiology, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
| | - Shiyou Wei
- Department of Anesthesiology, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
| | - Zhize Yuan
- Department of Thoracic Surgery, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
| | - Rui Chang
- Medical Department, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
| | - Xue Chen
- Department of Anesthesiology, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
| | - Yu Fu
- Department of Anesthesiology, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
| | - Wei Wu
- Department of Anesthesiology, Shanghai Pulmonary Hospital, School of MedicineTongji UniversityShanghaiChina
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Chen W, Guo W, Li Y, Chen M. Integrative analysis of metabolomics and transcriptomics to uncover biomarkers in sepsis. Sci Rep 2024; 14:9676. [PMID: 38678059 PMCID: PMC11055861 DOI: 10.1038/s41598-024-59400-0] [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: 01/18/2024] [Accepted: 04/10/2024] [Indexed: 04/29/2024] Open
Abstract
To utilize metabolomics in conjunction with RNA sequencing to identify biomarkers in the blood of sepsis patients and discover novel targets for diagnosing and treating sepsis. In January 2019 and December 2020, blood samples were collected from a cohort of 16 patients diagnosed with sepsis and 11 patients diagnosed with systemic inflammatory response syndrome (SIRS). Non-targeted metabolomics analysis was conducted using liquid chromatography coupled with mass spectrometry (LC-MS/MS technology), while gene sequencing was performed using RNA sequencing. Afterward, the metabolite data and sequencing data underwent quality control and difference analysis, with a fold change (FC) greater than or equal to 2 and a false discovery rate (FDR) less than 0.05.Co-analysis was then performed to identify differential factors with consistent expression trends based on the metabolic pathway context; KEGG enrichment analysis was performed on the crossover factors, and Meta-analysis of the targets was performed at the transcriptome level using the public dataset. In the end, a total of five samples of single nucleated cells from peripheral blood (two normal controls, one with systemic inflammatory response syndrome, and two with sepsis) were collected and examined to determine the cellular location of the essential genes using 10× single cell RNA sequencing (scRNA-seq). A total of 485 genes and 1083 metabolites were found to be differentially expressed in the sepsis group compared to the SIRS group. Among these, 40 genes were found to be differentially expressed in both the metabolome and transcriptome. Functional enrichment analysis revealed that these genes were primarily involved in biological processes related to inflammatory response, immune regulation, and amino acid metabolism. Furthermore, a meta-analysis identified four genes, namely ITGAM, CD44, C3AR1, and IL2RG, which were highly expressed in the sepsis group compared to the normal group (P < 0.05). Additionally, scRNA-seq analysis revealed that the core genes ITGAM and C3AR1 were predominantly localized within the macrophage lineage. The primary genes ITGAM and C3AR1 exhibit predominant expression in macrophages, which play a significant role in inflammatory and immune responses. Moreover, these genes show elevated expression levels in the plasma of individuals with sepsis, indicating their potential as valuable subjects for further research in sepsis.
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Affiliation(s)
- Wenhao Chen
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Wentao Guo
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Yang Li
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Muhu Chen
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
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5
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Ko ER, Reller ME, Tillekeratne LG, Bodinayake CK, Miller C, Burke TW, Henao R, McClain MT, Suchindran S, Nicholson B, Blatt A, Petzold E, Tsalik EL, Nagahawatte A, Devasiri V, Rubach MP, Maro VP, Lwezaula BF, Kodikara-Arachichi W, Kurukulasooriya R, De Silva AD, Clark DV, Schully KL, Madut D, Dumler JS, Kato C, Galloway R, Crump JA, Ginsburg GS, Minogue TD, Woods CW. Host-response transcriptional biomarkers accurately discriminate bacterial and viral infections of global relevance. Sci Rep 2023; 13:22554. [PMID: 38110534 PMCID: PMC10728077 DOI: 10.1038/s41598-023-49734-6] [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: 12/27/2022] [Accepted: 12/11/2023] [Indexed: 12/20/2023] Open
Abstract
Diagnostic limitations challenge management of clinically indistinguishable acute infectious illness globally. Gene expression classification models show great promise distinguishing causes of fever. We generated transcriptional data for a 294-participant (USA, Sri Lanka) discovery cohort with adjudicated viral or bacterial infections of diverse etiology or non-infectious disease mimics. We then derived and cross-validated gene expression classifiers including: 1) a single model to distinguish bacterial vs. viral (Global Fever-Bacterial/Viral [GF-B/V]) and 2) a two-model system to discriminate bacterial and viral in the context of noninfection (Global Fever-Bacterial/Viral/Non-infectious [GF-B/V/N]). We then translated to a multiplex RT-PCR assay and independent validation involved 101 participants (USA, Sri Lanka, Australia, Cambodia, Tanzania). The GF-B/V model discriminated bacterial from viral infection in the discovery cohort an area under the receiver operator curve (AUROC) of 0.93. Validation in an independent cohort demonstrated the GF-B/V model had an AUROC of 0.84 (95% CI 0.76-0.90) with overall accuracy of 81.6% (95% CI 72.7-88.5). Performance did not vary with age, demographics, or site. Host transcriptional response diagnostics distinguish bacterial and viral illness across global sites with diverse endemic pathogens.
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Affiliation(s)
- Emily R Ko
- Division of General Internal Medicine, Department of Medicine, Duke Regional Hospital, Duke University Health System, Duke University School of Medicine, 3643 N. Roxboro St., Durham, NC, 27704, USA.
| | - Megan E Reller
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Duke Global Health Institute, Duke University, Durham, NC, USA
| | - L Gayani Tillekeratne
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Duke Global Health Institute, Duke University, Durham, NC, USA
- Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Champica K Bodinayake
- Duke Global Health Institute, Duke University, Durham, NC, USA
- Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Cameron Miller
- Clinical Research Unit, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Thomas W Burke
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ricardo Henao
- Department of Biostatistics and Informatics, Duke University, Durham, NC, USA
| | - Micah T McClain
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Sunil Suchindran
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | | | - Adam Blatt
- Division of Pediatric Infectious Diseases, Department of Pediatrics, Duke University School of Medicine, Durham, NC, USA
| | - Elizabeth Petzold
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ephraim L Tsalik
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Danaher Diagnostics, Washington, DC, USA
| | - Ajith Nagahawatte
- Department of Microbiology, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Vasantha Devasiri
- Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
| | - Matthew P Rubach
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Duke Global Health Institute, Duke University, Durham, NC, USA
- Programme in Emerging Infectious Diseases, Duke-National University of Singapore, Singapore, Singapore
- Kilimanjaro Christian Medical Center, Moshi, Tanzania
| | - Venance P Maro
- Kilimanjaro Christian Medical Center, Moshi, Tanzania
- Kilimanjaro Christian Medical University College, Moshi, Tanzania
| | - Bingileki F Lwezaula
- Kilimanjaro Christian Medical University College, Moshi, Tanzania
- Maswenzi Regional Referral Hospital, Moshi, Tanzania
| | | | | | - Aruna D De Silva
- General Sir John Kotelawala Defence University, Colombo, Sri Lanka
| | - Danielle V Clark
- The Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, USA
- Austere Environments Consortium for Enhanced Sepsis Outcomes (ACESO), Biological Defense Research Directorate, Naval Medical Research Center-Frederick, Ft. Detrick, MD, USA
| | - Kevin L Schully
- Austere Environments Consortium for Enhanced Sepsis Outcomes (ACESO), Biological Defense Research Directorate, Naval Medical Research Center-Frederick, Ft. Detrick, MD, USA
| | - Deng Madut
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Duke Global Health Institute, Duke University, Durham, NC, USA
| | - J Stephen Dumler
- Joint Departments of Pathology, School of Medicine, Uniformed Services University, Bethesda, MD, USA
| | - Cecilia Kato
- Centers for Disease Control and Prevention, National Center for Emerging Zoonotic Infectious Diseases, Atlanta, USA
| | - Renee Galloway
- Centers for Disease Control and Prevention, National Center for Emerging Zoonotic Infectious Diseases, Atlanta, USA
| | - John A Crump
- Duke Global Health Institute, Duke University, Durham, NC, USA
- Department of Medicine, Faculty of Medicine, University of Ruhuna, Galle, Sri Lanka
- Kilimanjaro Christian Medical Center, Moshi, Tanzania
- Kilimanjaro Christian Medical University College, Moshi, Tanzania
- Centre for International Health, University of Otago, Dunedin, New Zealand
| | - Geoffrey S Ginsburg
- Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- National Institute of Health, Bethesda, MD, USA
| | - Timothy D Minogue
- Diagnostic Systems Division, USAMRIID, Fort Detrick, Frederick, MD, USA
| | - Christopher W Woods
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Durham Veterans Affairs Health Care System, Durham, NC, USA
- Duke Global Health Institute, Duke University, Durham, NC, USA
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6
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Li Q, Qu L, Miao Y, Li Q, Zhang J, Zhao Y, Cheng R. A gene network database for the identification of key genes for diagnosis, prognosis, and treatment in sepsis. Sci Rep 2023; 13:21815. [PMID: 38071387 PMCID: PMC10710458 DOI: 10.1038/s41598-023-49311-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2023] [Accepted: 12/06/2023] [Indexed: 12/18/2023] Open
Abstract
Sepsis and sepsis-related diseases cause a high rate of mortality worldwide. The molecular and cellular mechanisms of sepsis are still unclear. We aim to identify key genes in sepsis and reveal potential disease mechanisms. Six sepsis-related blood transcriptome datasets were collected and analyzed by weighted gene co-expression network analysis (WGCNA). Functional annotation was performed in the gProfiler tool. DSigDB was used for drug signature enrichment analysis. The proportion of immune cells was estimated by the CIBERSORT tool. The relationships between modules, immune cells, and survival were identified by correlation analysis and survival analysis. A total of 37 stable co-expressed gene modules were identified. These modules were associated with the critical biology process in sepsis. Four modules can independently separate patients with long and short survival. Three modules can recurrently separate sepsis and normal patients with high accuracy. Some modules can separate bacterial pneumonia, influenza pneumonia, mixed bacterial and influenza A pneumonia, and non-infective systemic inflammatory response syndrome (SIRS). Drug signature analysis identified drugs associated with sepsis, such as testosterone, phytoestrogens, ibuprofen, urea, dichlorvos, potassium persulfate, and vitamin B12. Finally, a gene co-expression network database was constructed ( https://liqs.shinyapps.io/sepsis/ ). The recurrent modules in sepsis may facilitate disease diagnosis, prognosis, and treatment.
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Affiliation(s)
- Qingsheng Li
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Lili Qu
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Yurui Miao
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Qian Li
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Jing Zhang
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Yongxue Zhao
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China
| | - Rui Cheng
- Department of Pharmacy, Affiliated Hospital of Inner Mongolia Medical University, Hohhot, Inner Mongolia, 010050, People's Republic of China.
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7
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Buckel M, Maclean P, Knight JC, Lawler PR, Proudfoot AG. Extending the 'host response' paradigm from sepsis to cardiogenic shock: evidence, limitations and opportunities. Crit Care 2023; 27:460. [PMID: 38012789 PMCID: PMC10683227 DOI: 10.1186/s13054-023-04752-8] [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: 09/18/2023] [Accepted: 11/20/2023] [Indexed: 11/29/2023] Open
Abstract
Recent clinical and research efforts in cardiogenic shock (CS) have largely focussed on the restoration of the low cardiac output state that is the conditio sine qua non of the clinical syndrome. This approach has failed to translate into improved outcomes, and mortality has remained static at 30-50%. There is an unmet need to better delineate the pathobiology of CS to understand the observed heterogeneity of presentation and treatment effect and to identify novel therapeutic targets. Despite data in other critical illness syndromes, specifically sepsis, the role of dysregulated inflammation and immunity is hitherto poorly described in CS. High-dimensional molecular profiling, particularly through leukocyte transcriptomics, may afford opportunity to better characterise subgroups of patients with shared mechanisms of immune dysregulation. In this state-of-the-art review, we outline the rationale for considering molecular subtypes of CS. We describe how high-dimensional molecular technologies can be used to identify these subtypes, and whether they share biological features with sepsis and other critical illness states. Finally, we propose how the identification of molecular subtypes of patients may enrich future clinical trial design and identification of novel therapies for CS.
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Affiliation(s)
- Marie Buckel
- Department of Perioperative Medicine, Bart's Heart Centre, St. Bartholomew's Hospital, London, UK
| | - Patrick Maclean
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
| | - Julian C Knight
- Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK
- Chinese Academy of Medical Sciences Oxford Institute, University of Oxford, Oxford, UK
| | - Patrick R Lawler
- Peter Munk Cardiac Centre, University Health Network, University of Toronto, Toronto, ON, Canada
- McGill University Health Centre, McGill University, Montreal, QC, Canada
| | - Alastair G Proudfoot
- Department of Perioperative Medicine, Bart's Heart Centre, St. Bartholomew's Hospital, London, UK.
- Queen Mary University of London, London, UK.
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8
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Tuerdimaimaiti D, Abuduaini B, Kang S, Jiao J, Li M, Madeniyati W, Tuerdi B, Aili G, Tuerhong R, Kulaxi A. Genome-wide identification and functional analysis of dysregulated alternative splicing profiles in sepsis. J Inflamm (Lond) 2023; 20:31. [PMID: 37749550 PMCID: PMC10521395 DOI: 10.1186/s12950-023-00355-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2022] [Accepted: 08/10/2023] [Indexed: 09/27/2023] Open
Abstract
BACKGROUND An increasing body of evidence now shows that the long-term mortality of patients with sepsis are associated with various sepsis-related immune cell defects. Alternative splicing (AS), as a sepsis-related immune cell defect, is considered as a potential immunomodulatory therapy target to improve patient outcomes. However, our understanding of the role AS plays in sepsis is currently insufficient. AIM This study investigated possible associations between AS and the gene regulatory networks affecting immune cells. We also investigated apoptosis and AS functionality in sepsis pathophysiology. METHODS In this study, we assessed publicly available mRNA-seq data that was obtained from the NCBI GEO dataset (GSE154918), which included a healthy group (HLTY), a mild infection group (INF1), asepsis group (Seps), and a septic shock group (Shock). A total of 79 samples (excluding significant outliers) were identified by a poly-A capture method to generate RNA-seq data. The variable splicing events and highly correlated RNA binding protein (RBP) genes in each group were then systematically analyzed. RESULTS For the first time, we used systematic RNA-seq analysis of sepsis-related AS and identified 1505 variable AS events that differed significantly (p <= 0.01) across the four groups. In the sepsis group, the genes related to significant AS events, such as, SHISA5 and IFI27, were mostly enriched in the cell apoptosis pathway. Furthermore, we identified differential splicing patterns within each of the four groups. Significant differences in the expression of RNA Binding Protein(RBP) genes were observed between the control group and the sepsis group. RBP gene expression was highly correlated with variant splicing events in sepsis, as determined by co-expression analysis; The expression of DDX24, CBFA2T2, NOP, ILF3, DNMT1, FTO, PPRC1, NOLC1 RBPs were significant reduced in sepsis compared to the healthy group. Finally, we constructed an RBP-AS functional network. CONCLUSION Analysis indicated that the RBP-AS functional network serves as a critical post-transcriptional mechanism that regulates the development of sepsis. AS dysregulation is associated with alterations in the regulatory gene expression network that is involved in sepsis. Therefore, the RBP-AS expression network could be useful in refining biomarker predictions in the development of new therapeutic targets for the pathogenesis of sepsis.
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Affiliation(s)
- Dilixiati Tuerdimaimaiti
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Buzukela Abuduaini
- The Intensive Care Unit, The First Affiliated Hospital of Xinjiang Medical University, Wulumuqi, Xinjiang, 830054, China
| | - Shaotao Kang
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Jinliang Jiao
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Mengchen Li
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Wolazihan Madeniyati
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Baihetinisha Tuerdi
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China.
| | - Gulisitan Aili
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Reyila Tuerhong
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
| | - Ajiguli Kulaxi
- Department of RICU, The First Affiliated Hospital of Xinjiang Medical University, 393 South Li Yu Shan Road, Wulumuqi, Xinjiang, 830054, China
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Vaidie J, Peju E, Jandeaux LM, Lesouhaitier M, Lacherade JC, Guillon A, Wittebole X, Asfar P, Evrard B, Daix T, Vignon P, François B. Long-term immunosuppressive treatment is not associated with worse outcome in patients hospitalized in the intensive care unit for septic shock: the PACIFIC study. Crit Care 2023; 27:340. [PMID: 37660107 PMCID: PMC10475175 DOI: 10.1186/s13054-023-04626-z] [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: 06/02/2023] [Accepted: 08/27/2023] [Indexed: 09/04/2023] Open
Abstract
BACKGROUND Except in a few retrospective studies mainly including patients under chemotherapy, information regarding the impact of immunosuppressive therapy on the prognosis of patients admitted to the intensive care unit (ICU) for septic shock is scarce. Accordingly, the PACIFIC study aimed to asses if immunosuppressive therapy is associated with an increased mortality in patients admitted to the ICU for septic shock. METHODS This was a retrospective epidemiological multicentre study. Eight high enroller centres in septic shock randomised controlled trials (RCTs) participated in the study. Patients in the "exposed" group were selected from the screen failure logs of seven recent RCTs and excluded because of immunosuppressive treatment. The "non-exposed" patients were those included in the placebo arm of the same RCTs. A multivariate logistic regression model was used to estimate the risk of death. RESULTS Among the 433 patients enrolled, 103 were included in the "exposed" group and 330 in the "non-exposed" group. Reason for immunosuppressive therapy included organ transplantation (n = 45 [44%]) or systemic disease (n = 58 [56%]). ICU mortality rate was 24% in the "exposed" group and 25% in the "non-exposed" group (p = 0.9). Neither in univariate nor in multivariate analysis immunosuppressive therapy was associated with a higher ICU mortality (OR: 0.95; [95% CI 0.56-1.58]: p = 0.86 and 1.13 [95% CI 0.61-2.05]: p = 0.69, respectively) or 3-month mortality (OR: 1.13; [95% CI 0.69-1.82]: p = 0.62 and OR: 1.36 [95% CI 0.78-2.37]: p = 0.28, respectively). CONCLUSIONS In this study, long-term immunosuppressive therapy excluding chemotherapy was not associated with significantly higher or lower ICU and 3-month mortality in patients admitted to the ICU for septic shock.
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Affiliation(s)
- Julien Vaidie
- Réanimation Polyvalente, CHU de Limoges, 2 Avenue Martin Luther King, 87042, Limoges Cedex, France
| | - Edwige Peju
- Service de Médecine Intensive et Réanimation, Hôpital Cochin, Assistance Publique-Hôpitaux de Paris, Paris, France
| | - Louise-Marie Jandeaux
- Médecine Intensive et Réanimation, Nouvel Hôpital Civil, CHRU de Strasbourg, Strasbourg, France
| | - Mathieu Lesouhaitier
- Service de Maladies Infectieuses et Réanimation Médicale, CHU de Rennes, Rennes, France
| | | | - Antoine Guillon
- Médecine Intensive - Réanimation, CHRU Bretonneau, Tours, France
- Inserm UMR 1100, UFR de Médecine, Tours, France
| | - Xavier Wittebole
- Service de Soins Intensifs, Cliniques universitaires Saint Luc, Brussels, Belgium
| | - Pierre Asfar
- Médecine Intensive - Réanimation et médecine hyperbare, CHU Angers, Angers, France
| | - Bruno Evrard
- Réanimation Polyvalente, CHU de Limoges, 2 Avenue Martin Luther King, 87042, Limoges Cedex, France
- Inserm CIC 1435, CHU Dupuytren, Limoges, France
| | - Thomas Daix
- Réanimation Polyvalente, CHU de Limoges, 2 Avenue Martin Luther King, 87042, Limoges Cedex, France
- Inserm CIC 1435, CHU Dupuytren, Limoges, France
- Inserm UMR 1092, CHU Dupuytren, Limoges, France
| | - Philippe Vignon
- Réanimation Polyvalente, CHU de Limoges, 2 Avenue Martin Luther King, 87042, Limoges Cedex, France
- Inserm CIC 1435, CHU Dupuytren, Limoges, France
- Inserm UMR 1092, CHU Dupuytren, Limoges, France
| | - Bruno François
- Réanimation Polyvalente, CHU de Limoges, 2 Avenue Martin Luther King, 87042, Limoges Cedex, France.
- Inserm CIC 1435, CHU Dupuytren, Limoges, France.
- Inserm UMR 1092, CHU Dupuytren, Limoges, France.
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Zhao H, Wang P, Wang X, Du W, Yang HH, Liu Y, Cui SN, Huang W, Peng T, Chen J, Gao C, Wang Y, Sadayappan S, Ma C, Fan Y, Wang C, Fan GC. Lipocalin 10 is essential for protection against inflammation-triggered vascular leakage by activating LDL receptor-related protein 2-slingshot homologue 1 signalling pathway. Cardiovasc Res 2023; 119:1981-1996. [PMID: 37392461 PMCID: PMC10681662 DOI: 10.1093/cvr/cvad105] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 03/06/2023] [Accepted: 03/20/2023] [Indexed: 07/03/2023] Open
Abstract
AIMS Systemic inflammation occurs commonly during many human disease settings and increases vascular permeability, leading to organ failure, and lethal outcomes. Lipocalin 10 (Lcn10), a poorly characterized member of the lipocalin family, is remarkably altered in the cardiovascular system of human patients with inflammatory conditions. Nonetheless, whether Lcn10 regulates inflammation-induced endothelial permeability remains unknown. METHODS AND RESULTS Systemic inflammation models were induced using mice by injection of endotoxin lipopolysaccharide (LPS) or caecal ligation and puncture (CLP) surgery. We observed that the expression of Lcn10 was dynamically altered only in endothelial cells (ECs), but not in either fibroblasts or cardiomyocytes isolated from mouse hearts following the LPS challenge or CLP surgery. Using in vitro gain- and loss-of-function approaches and an in vivo global knockout mouse model, we discovered that Lcn10 negatively regulated endothelial permeability upon inflammatory stimuli. Loss of Lcn10 augmented vascular leakage, leading to severe organ damage and higher mortality following LPS challenge, compared to wild-type controls. By contrast, overexpression of Lcn10 in ECs displayed opposite effects. A mechanistic analysis revealed that both endogenous and exogenous elevation of Lcn10 in ECs could activate slingshot homologue 1 (Ssh1)-Cofilin signalling cascade, a key axis known to control actin filament dynamics. Accordingly, a reduced formation of stress fibre and increased generation of cortical actin band were exhibited in Lcn10-ECs, when compared to controls upon endotoxin insults. Furthermore, we identified that Lcn10 interacted with LDL receptor-related protein 2 (LRP2) in ECs, which acted as an upstream factor of the Ssh1-Confilin signalling. Finally, injection of recombinant Lcn10 protein into endotoxic mice showed therapeutic effects against inflammation-induced vascular leakage. CONCLUSION This study identifies Lcn10 as a novel regulator of EC function and illustrates a new link in the Lcn10-LRP2-Ssh1 axis to controlling endothelial barrier integrity. Our findings may provide novel strategies for the treatment of inflammation-related diseases.
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Affiliation(s)
- Hongyan Zhao
- Department of Critical Care Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Peng Wang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
- Department of Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Xiaohong Wang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Wa Du
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Hui-Hui Yang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Yueying Liu
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Shu-Nan Cui
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
- Department of Anesthesiology, Beijing Cancer Hospital, Peking University School of Oncology, Beijing, China
| | - Wei Huang
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Tianqing Peng
- The Centre for Critical Illness Research, Lawson Health Research Institute, London, Ontario, Canada
| | - Jing Chen
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, USA
| | - Chen Gao
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Yigang Wang
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Sakthivel Sadayappan
- Division of Cardiovascular Health and Disease, Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Chengen Ma
- Department of Critical Care Medicine, The Second Hospital, Cheeloo College of Medicine, Shandong University, Jinan, Shandong, China
| | - Yanbo Fan
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Chunting Wang
- Department of Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Guo-Chang Fan
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
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11
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Kapellos TS, Baßler K, Fujii W, Nalkurthi C, Schaar AC, Bonaguro L, Pecht T, Galvao I, Agrawal S, Saglam A, Dudkin E, Frishberg A, de Domenico E, Horne A, Donovan C, Kim RY, Gallego-Ortega D, Gillett TE, Ansari M, Schulte-Schrepping J, Offermann N, Antignano I, Sivri B, Lu W, Eapen MS, van Uelft M, Osei-Sarpong C, van den Berge M, Donker HC, Groen HJM, Sohal SS, Klein J, Schreiber T, Feißt A, Yildirim AÖ, Schiller HB, Nawijn MC, Becker M, Händler K, Beyer M, Capasso M, Ulas T, Hasenauer J, Pizarro C, Theis FJ, Hansbro PM, Skowasch D, Schultze JL. Systemic alterations in neutrophils and their precursors in early-stage chronic obstructive pulmonary disease. Cell Rep 2023; 42:112525. [PMID: 37243592 PMCID: PMC10320832 DOI: 10.1016/j.celrep.2023.112525] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2022] [Revised: 03/18/2023] [Accepted: 05/01/2023] [Indexed: 05/29/2023] Open
Abstract
Systemic inflammation is established as part of late-stage severe lung disease, but molecular, functional, and phenotypic changes in peripheral immune cells in early disease stages remain ill defined. Chronic obstructive pulmonary disease (COPD) is a major respiratory disease characterized by small-airway inflammation, emphysema, and severe breathing difficulties. Using single-cell analyses we demonstrate that blood neutrophils are already increased in early-stage COPD, and changes in molecular and functional neutrophil states correlate with lung function decline. Assessing neutrophils and their bone marrow precursors in a murine cigarette smoke exposure model identified similar molecular changes in blood neutrophils and precursor populations that also occur in the blood and lung. Our study shows that systemic molecular alterations in neutrophils and their precursors are part of early-stage COPD, a finding to be further explored for potential therapeutic targets and biomarkers for early diagnosis and patient stratification.
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Affiliation(s)
- Theodore S Kapellos
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Kevin Baßler
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Wataru Fujii
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Christina Nalkurthi
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia
| | - Anna C Schaar
- Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Lorenzo Bonaguro
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Tal Pecht
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Izabela Galvao
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia
| | - Shobhit Agrawal
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Adem Saglam
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Erica Dudkin
- Computational Life Sciences, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Amit Frishberg
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany; Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Elena de Domenico
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Arik Horne
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Chantal Donovan
- University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia; Immune Health, Hunter Medical Research Institute, New Lambton and The University of Newcastle, Newcastle, NSW 2305, Australia
| | - Richard Y Kim
- University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia; Immune Health, Hunter Medical Research Institute, New Lambton and The University of Newcastle, Newcastle, NSW 2305, Australia
| | - David Gallego-Ortega
- School of Biomedical Engineering, Faculty of Engineering and IT, University of Technology Sydney, Garvan Institute of Medical Research, and St Vincent's Clinical School, Faculty of Medicine, University of New South Wales, Sydney, NSW 2010, Australia
| | - Tessa E Gillett
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; GRIAC Research Institute, University Medical Center Groningen, 9700 RB Groningen, the Netherlands
| | - Meshal Ansari
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Jonas Schulte-Schrepping
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Nina Offermann
- Immunregulation, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Ignazio Antignano
- Immunregulation, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Burcu Sivri
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Wenying Lu
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Mathew S Eapen
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Martina van Uelft
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Collins Osei-Sarpong
- Immunogenomics & Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Maarten van den Berge
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands
| | - Hylke C Donker
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands
| | - Harry J M Groen
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; Department of Pulmonary Diseases, University of Groningen, University Medical Center Groningen, 9713 GZ Groningen, the Netherlands
| | - Sukhwinder S Sohal
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Johanna Klein
- Department of Internal Medicine II, Pneumology, University Hospital Bonn, 53127 Bonn, Germany
| | - Tina Schreiber
- Department of Internal Medicine II, Pneumology, University Hospital Bonn, 53127 Bonn, Germany
| | - Andreas Feißt
- University Clinics for Radiology, University Hospital Bonn, 53127 Bonn, Germany
| | - Ali Önder Yildirim
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Herbert B Schiller
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Martijn C Nawijn
- Department of Pathology and Medical Biology, University of Groningen, University Medical Center Groningen, 9700 AB Groningen, the Netherlands; GRIAC Research Institute, University Medical Center Groningen, 9700 RB Groningen, the Netherlands
| | - Matthias Becker
- Modular HPC and AI, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Kristian Händler
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany; Institute of Human Genetics, University of Lübeck, 23562 Lübeck, Germany
| | - Marc Beyer
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany; Immunogenomics & Neurodegeneration, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Melania Capasso
- Immunregulation, German Center for Neurodegenerative Diseases (DZNE), 53127 Bonn, Germany
| | - Thomas Ulas
- Platform for Single Cell Genomics and Epigenomics (PRECISE), German Center for Neurodegenerative Diseases and the University of Bonn, 53127 Bonn, Germany
| | - Jan Hasenauer
- Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany; Computational Life Sciences, Life & Medical Sciences (LIMES) Institute, University of Bonn, 53115 Bonn, Germany
| | - Carmen Pizarro
- Department of Internal Medicine II, Pneumology, University Hospital Bonn, 53127 Bonn, Germany
| | - Fabian J Theis
- Institute of Computational Biology (ICB), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany
| | - Philip M Hansbro
- Centre for Inflammation, Centenary Institute and University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia; University of Technology Sydney, School of Life Sciences, Faculty of Science, Sydney, NSW 2007, Australia
| | - Dirk Skowasch
- Respiratory Translational Research Group, Department of Laboratory Medicine, School of Health Sciences, College of Health and Medicine, University of Tasmania, Launceston, 7250 TAS, Australia
| | - Joachim L Schultze
- Comprehensive Pneumology Center (CPC), Institute of Lung Health and Immunity (LHI), Member of the German Center for Lung Research (DZL), Helmholtz Zentrum München, 85764 Neuherberg, Germany; Department of Mathematics, Technische Universität München, 85748 Garching, Germany.
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12
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Zhang Q, Wang C, Li S, Li Y, Chen M, Hu Y. Screening of core genes prognostic for sepsis and construction of a ceRNA regulatory network. BMC Med Genomics 2023; 16:37. [PMID: 36855106 PMCID: PMC9976425 DOI: 10.1186/s12920-023-01460-8] [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: 09/03/2022] [Accepted: 02/13/2023] [Indexed: 03/02/2023] Open
Abstract
OBJECTIVE To screen out core genes potentially prognostic for sepsis and construct a competing endogenous RNA (ceRNA) regulatory network. METHODS Subjects included in this project were 23 sepsis patients and 10 healthy people. RNA-seq for lncRNA, miRNA and mRNA was performed in the peripheral blood samples. Differentially expressed RNAs (DER) were screened out for further analysis. GO annotation and GSEA functional clustering were performed to view the functional enrichment of DEmRNAs. Core genes of prognostic significance were screened out with the weighted correlation network analysis (WGCNA). Meta-analysis and Survival analysis was devised in different microarray datasets. RT-qPCR was conducted to validate these core genes. A ceRNA network was accordingly constructed according to the correlation analysis and molecular interaction prediction. RESULTS RNA-seq and differential analysis screened out 1,044 DEmRNAs, 66 DEmiRNAs and 155 DElncRNAs. The GO and GSEA analysis revealed that DEmRNAs are mainly involved in inflammatory response, immune regulation, neutrophil activation. WGCNA revealed 4 potential core genes, including CD247, IL-2Rβ, TGF-βR3 and IL-1R2. In vitro cellular experiment showed up-regulated expression of IL-1R2 while down-regulated of CD247, IL-2Rβ, TGF-βR3 in sepsis patients. Correspondingly, a ceRNA regulatory network was build based on the core genes, and multiple lncRNAs and miRNAs were identified to have a potential regulatory role in sepsis. CONCLUSION This study identified four core genes, including CD247, IL-1R2, IL-2Rβ and TGF-βR3, with potential to be novel biomarkers for the prognosis of sepsis. In the meantime, a ceRNA network was constructed aiming to guide further study on prognostic mechanism in sepsis.
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Affiliation(s)
- Qian Zhang
- Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Chenglin Wang
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Shilin Li
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Yang Li
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Muhu Chen
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China
| | - Yingchun Hu
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, Sichuan, China.
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Wang C, Li S, Shen Y, Li Y, Chen M, Wang Y, Lan Y, Hu Y. Mechanisms of Panax Ginseng on Treating Sepsis by RNA-Seq Technology. Infect Drug Resist 2022; 15:7667-7678. [PMID: 36582454 PMCID: PMC9793795 DOI: 10.2147/idr.s393654] [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: 11/12/2022] [Accepted: 12/16/2022] [Indexed: 12/25/2022] Open
Abstract
Purpose To explore the potential active targets and mechanisms of Panax Ginseng in the treatment of sepsis using network pharmacology and RNA-seq technology. Patients and Methods Patients with sepsis and healthy volunteers were collected according to SEPSIS 3.0, and their peripheral blood was used for RNA-seq analysis. The active ingredients and targets of Panax Ginseng were obtained using the TCMSP database, PPI and GO analysis were performed for disease-drug intersection targets. Then, we used Meta-analysis to screen core genes. Finally, single-cell RNA-seq was used to perform cell localization analysis on core genes. Results RNA-seq analysis collected 4521 sepsis-related genes, TCMSP database obtained 86 Panax Ginseng active ingredients and their 294 active targets. PPI and GO analysis showed intersection targets were closely linked, and mainly involved in cellular response to chemical stress, response to drug and molecule of bacterial origin, etc. Then, core targets, IL1B, ALOX5, BCL2 and IL4R, were sorted by Meta-analysis, and all four genes have high expression in the sepsis survivor group compared to the sepsis non-survivor group; single-cell RNA-seq revealed that IL1B was mainly localized in macrophages, ALOX5 was mainly localized in macrophages and B cells, BCL2 was mainly localized in natural killer cells, T cells and B cells, IL4R was widely distributed in immune cells. Finally, according to the correspondence between the active ingredients and targets of Panax Ginseng in TCMSP database, we found that Ginsenoside rh2 regulates the expression of IL1B, Ginsenoside rf regulates the expression of IL1B and IL4R, Kaempferol regulates the expression of ALOX5 and BCL2, and β-sitosterol regulates the expression of BCL2. Conclusion Ginsenoside rh2, Ginsenoside rf, Kaempferol and β-sitosterol may produce anti-sepsis effects by regulating the expression of IL1B, ALOX5, BCL2 and IL4R, thus improving the survival rate of sepsis patients.
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Affiliation(s)
- Chenglin Wang
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China
| | - Shilin Li
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China
| | - Yuzhou Shen
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China
| | - Yang Li
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China
| | - Muhu Chen
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China
| | - Youqiang Wang
- Department of Laboratory Medicine, The Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, People’s Republic of China
| | - Youyu Lan
- Department of Rheumatology and Immunology, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China,Youyu Lan, Department of Rheumatology and Immunology, The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, People’s Republic of China, Tel +86-18090861701, Fax +86-0830-3165120, Email
| | - Yingchun Hu
- Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, Luzhou, People’s Republic of China,Correspondence: Yingchun Hu, Department of Emergency Medicine, The Affiliated Hospital of Southwest Medical University, 25 Taiping Street, Jiangyang District, Luzhou, Sichuan, People’s Republic of China, Tel +86-15228232720, Fax +86-0830-3165120, Email
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Fiorino C, Liu Y, Henao R, Ko ER, Burke TW, Ginsburg GS, McClain MT, Woods CW, Tsalik EL. Host Gene Expression to Predict Sepsis Progression. Crit Care Med 2022; 50:1748-1756. [PMID: 36178298 PMCID: PMC9671818 DOI: 10.1097/ccm.0000000000005675] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
Abstract
OBJECTIVES Sepsis causes significant mortality. However, most patients who die of sepsis do not present with severe infection, hampering efforts to deliver early, aggressive therapy. It is also known that the host gene expression response to infection precedes clinical illness. This study seeks to develop transcriptomic models to predict progression to sepsis or shock within 72 hours of hospitalization and to validate previously identified transcriptomic signatures in the prediction of 28-day mortality. DESIGN Retrospective differential gene expression analysis and predictive modeling using RNA sequencing data. PATIENTS Two hundred seventy-seven patients enrolled at four large academic medical centers; all with clinically adjudicated infection were considered for inclusion in this study. MEASUREMENTS AND MAIN RESULTS Sepsis progression was defined as an increase in Sepsis 3 category within 72 hours. Transcriptomic data were generated using RNAseq of whole blood. Least absolute shrinkage and selection operator modeling was used to identify predictive signatures for various measures of disease progression. Four previously identified gene signatures were tested for their ability to predict 28-day mortality. There were no significant differentially expressed genes in 136 subjects with worsened Sepsis 3 category compared with 141 nonprogressor controls. There were 1,178 differentially expressed genes identified when sepsis progression was defined as ICU admission or 28-day mortality. A model based on these genes predicted progression with an area under the curve of 0.71. Validation of previously identified gene signatures to predict sepsis mortality revealed area under the receiver operating characteristic values of 0.70-0.75 and no significant difference between signatures. CONCLUSIONS Host gene expression was unable to predict sepsis progression when defined by an increase in Sepsis-3 category, suggesting this definition is not a useful framework for transcriptomic prediction methods. However, there was a differential response when progression was defined as ICU admission or death. Validation of previously described signatures predicted 28-day mortality with insufficient accuracy to offer meaningful clinical utility.
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Affiliation(s)
- Cassandra Fiorino
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Yiling Liu
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Ricardo Henao
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA
| | - Emily R. Ko
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Duke Regional Hospital, Durham, NC, USA
| | - Thomas W. Burke
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Geoffrey S. Ginsburg
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
| | - Micah T. McClain
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Christopher W. Woods
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
- Medical Service, Durham Veterans Affairs Health Care System, Durham, NC, USA
| | - Ephraim L. Tsalik
- Duke Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, NC, USA
- Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, NC, USA
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, NC, USA
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15
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Assessment of Infection Progression per Host Gene Expression. Crit Care Med 2022; 50:1834-1837. [PMID: 36394402 DOI: 10.1097/ccm.0000000000005677] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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16
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Prospective validation of a transcriptomic severity classifier among patients with suspected acute infection and sepsis in the emergency department. Eur J Emerg Med 2022; 29:357-365. [PMID: 35467566 PMCID: PMC9432813 DOI: 10.1097/mej.0000000000000931] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/04/2023]
Abstract
BACKGROUND AND IMPORTANCE mRNA-based host response signatures have been reported to improve sepsis diagnostics. Meanwhile, prognostic markers for the rapid and accurate prediction of severity in patients with suspected acute infections and sepsis remain an unmet need. IMX-SEV-2 is a 29-host-mRNA classifier designed to predict disease severity in patients with acute infection or sepsis. OBJECTIVE Validation of the host-mRNA infection severity classifier IMX-SEV-2. DESIGN, SETTINGS AND PARTICIPANTS Prospective, observational, convenience cohort of emergency department (ED) patients with suspected acute infections. OUTCOME MEASURES AND ANALYSIS Whole blood RNA tubes were analyzed using independently trained and validated composite target genes (IMX-SEV-2). IMX-SEV-2-generated risk scores for severity were compared to the patient outcomes in-hospital mortality and 72-h multiorgan failure. MAIN RESULTS Of the 312 eligible patients, 22 (7.1%) died in hospital and 58 (18.6%) experienced multiorgan failure within 72 h of presentation. For predicting in-hospital mortality, IMX-SEV-2 had a significantly higher area under the receiver operating characteristic (AUROC) of 0.84 [95% confidence intervals (CI), 0.76-0.93] compared to 0.76 (0.64-0.87) for lactate, 0.68 (0.57-0.79) for quick Sequential Organ Failure Assessment (qSOFA) and 0.75 (0.65-0.85) for National Early Warning Score 2 (NEWS2), ( P = 0.015, 0.001 and 0.013, respectively). For identifying and predicting 72-h multiorgan failure, the AUROC of IMX-SEV-2 was 0.76 (0.68-0.83), not significantly different from lactate (0.73, 0.65-0.81), qSOFA (0.77, 0.70-0.83) or NEWS2 (0.81, 0.75-0.86). CONCLUSION The IMX-SEV-2 classifier showed a superior prediction of in-hospital mortality compared to biomarkers and clinical scores among ED patients with suspected infections. No improvement for predicting multiorgan failure was found compared to established scores or biomarkers. Identifying patients with a high risk of mortality or multiorgan failure may improve patient outcomes, resource utilization and guide therapy decision-making.
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17
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Zhang M, Ke B, Zhuo H, Guo B. Diagnostic model based on bioinformatics and machine learning to distinguish Kawasaki disease using multiple datasets. BMC Pediatr 2022; 22:512. [PMID: 36042431 PMCID: PMC9425821 DOI: 10.1186/s12887-022-03557-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/29/2022] [Accepted: 08/17/2022] [Indexed: 12/03/2022] Open
Abstract
Background Kawasaki disease (KD), characterized by systemic vasculitis, is the leading cause of acquired heart disease in children. Herein, we developed a diagnostic model, with some prognosis ability, to help distinguish children with KD. Methods Gene expression datasets were downloaded from Gene Expression Omnibus (GEO), and gene sets with a potential pathogenic mechanism in KD were identified using differential expressed gene (DEG) screening, pathway enrichment analysis, random forest (RF) screening, and artificial neural network (ANN) construction. Results We extracted 2,017 DEGs (1,130 with upregulated and 887 with downregulated expression) from GEO. The Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses showed that the DEGs were significantly enriched in innate/adaptive immune response-related processes. Subsequently, the results of weighted gene co-expression network analysis and DEG screening were combined and, using RF and ANN, a model with eight genes (VPS9D1, CACNA1E, SH3GLB1, RAB32, ADM, GYG1, PGS1, and HIST2H2AC) was constructed. Classification results of the new model for KD diagnosis showed excellent performance for different datasets, including those of patients with KD, convalescents, and healthy individuals, with area under the curve values of 1, 0.945, and 0.95, respectively. Conclusions We used machine learning methods to construct and validate a diagnostic model using multiple bioinformatic datasets, and identified molecules expected to serve as new biomarkers for or therapeutic targets in KD. Supplementary Information The online version contains supplementary material available at 10.1186/s12887-022-03557-y.
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Affiliation(s)
- Mengyi Zhang
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, No. 20, Section 3, Renmin South Road, Chengdu, 610041, PR, Sichuan Province, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Bocuo Ke
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, No. 20, Section 3, Renmin South Road, Chengdu, 610041, PR, Sichuan Province, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Huichuan Zhuo
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, No. 20, Section 3, Renmin South Road, Chengdu, 610041, PR, Sichuan Province, China.,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China
| | - Binhan Guo
- Department of Laboratory Medicine, West China Second University Hospital, Sichuan University, No. 20, Section 3, Renmin South Road, Chengdu, 610041, PR, Sichuan Province, China. .,Key Laboratory of Birth Defects and Related Diseases of Women and Children (Sichuan University), Ministry of Education, Chengdu, China.
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18
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Kreitmann L, Bodinier M, Fleurie A, Imhoff K, Cazalis MA, Peronnet E, Cerrato E, Tardiveau C, Conti F, Llitjos JF, Textoris J, Monneret G, Blein S, Brengel-Pesce K. Mortality Prediction in Sepsis With an Immune-Related Transcriptomics Signature: A Multi-Cohort Analysis. Front Med (Lausanne) 2022; 9:930043. [PMID: 35847809 PMCID: PMC9280291 DOI: 10.3389/fmed.2022.930043] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2022] [Accepted: 06/08/2022] [Indexed: 12/29/2022] Open
Abstract
Background Novel biomarkers are needed to progress toward individualized patient care in sepsis. The immune profiling panel (IPP) prototype has been designed as a fully-automated multiplex tool measuring expression levels of 26 genes in sepsis patients to explore immune functions, determine sepsis endotypes and guide personalized clinical management. The performance of the IPP gene set to predict 30-day mortality has not been extensively characterized in heterogeneous cohorts of sepsis patients. Methods Publicly available microarray data of sepsis patients with widely variable demographics, clinical characteristics and ethnical background were co-normalized, and the performance of the IPP gene set to predict 30-day mortality was assessed using a combination of machine learning algorithms. Results We collected data from 1,801 arrays sampled on sepsis patients and 598 sampled on controls in 17 studies. When gene expression was assayed at day 1 following admission (1,437 arrays sampled on sepsis patients, of whom 1,161 were alive and 276 (19.2%) were dead at day 30), the IPP gene set showed good performance to predict 30-day mortality, with an area under the receiving operating characteristics curve (AUROC) of 0.710 (CI 0.652-0.768). Importantly, there was no statistically significant improvement in predictive performance when training the same models with all genes common to the 17 microarray studies (n = 7,122 genes), with an AUROC = 0.755 (CI 0.697-0.813, p = 0.286). In patients with gene expression data sampled at day 3 following admission or later, the IPP gene set had higher performance, with an AUROC = 0.804 (CI 0.643-0.964), while the total gene pool had an AUROC = 0.787 (CI 0.610-0.965, p = 0.811). Conclusion Using pooled publicly-available gene expression data from multiple cohorts, we showed that the IPP gene set, an immune-related transcriptomics signature conveys relevant information to predict 30-day mortality when sampled at day 1 following admission. Our data also suggests that higher predictive performance could be obtained when assaying gene expression at later time points during the course of sepsis. Prospective studies are needed to confirm these findings using the IPP gene set on its dedicated measurement platform.
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Affiliation(s)
- Louis Kreitmann
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Maxime Bodinier
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Aurore Fleurie
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Katia Imhoff
- Data Science, bioMérieux S.A., Marcy-l’Etoile, France
| | - Marie-Angelique Cazalis
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Estelle Peronnet
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Elisabeth Cerrato
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Claire Tardiveau
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
| | - Filippo Conti
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Immunology Laboratory, Edouard Herriot Hospital – Hospices Civils de Lyon, Lyon, France
| | - Jean-François Llitjos
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
- Anaesthesia and Critical Care Medicine Department, Hospices Civils de Lyon, Edouard Herriot Hospital, Lyon, France
| | | | - Guillaume Monneret
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Immunology Laboratory, Edouard Herriot Hospital – Hospices Civils de Lyon, Lyon, France
| | - Sophie Blein
- Data Science, bioMérieux S.A., Marcy-l’Etoile, France
| | - Karen Brengel-Pesce
- EA 7426 “Pathophysiology of Injury-Induced Immunosuppression”, Joint Research Unit Université Claude Bernard Lyon 1 – Hospices Civils de Lyon – bioMérieux, Lyon, France
- Open Innovation and Partnerships (OIP), bioMérieux S.A., Marcy-l’Étoile, France
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19
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Li Q, Li Y, Huang W, Wang X, Liu Z, Chen J, Fan Y, Peng T, Sadayappan S, Wang Y, Fan GC. Loss of Lipocalin 10 Exacerbates Diabetes-Induced Cardiomyopathy via Disruption of Nr4a1-Mediated Anti-Inflammatory Response in Macrophages. Front Immunol 2022; 13:930397. [PMID: 35757735 PMCID: PMC9226549 DOI: 10.3389/fimmu.2022.930397] [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] [Received: 04/27/2022] [Accepted: 05/11/2022] [Indexed: 11/13/2022] Open
Abstract
Metabolic disorders (i.e., hyperglycemia, hyperlipidemia, and hyperinsulinemia) cause increased secretion of inflammatory cytokines/chemokines, leading to gradual loss of cardiac resident macrophage population and increased accumulation of inflammatory monocytes/macrophages in the heart. Such self-perpetuating effect may contribute to the development of cardiomyopathy during diabetes. Recent meta-analysis data reveal that lipocalin 10 (Lcn10) is significantly downregulated in cardiac tissue of patients with heart failure but is increased in the blood of septic patients. However, the functional role of Lcn10 in cardiac inflammation triggered by metabolic disorders has never been investigated. In this study, we demonstrate that the expression of Lcn10 in macrophages was significantly decreased under multiple metabolic stress conditions. Furthermore, Lcn10-null macrophages exhibited pro-inflammatory phenotype in response to inflammation stimuli. Next, using a global Lcn10-knockout (KO) mouse model to induce type-2 diabetes (T2D), we observed that loss of Lcn10 promoted more pro-inflammatory macrophage infiltration into the heart, compared to controls, leading to aggravated insulin resistance and impaired cardiac function. Similarly, adoptive transfer of Lcn10-KO bone marrow cells into X-ray irradiated mice displayed higher ratio of pro-/anti-inflammatory macrophages in the heart and worsened cardiac function than those mice received wild-type (WT) bone marrows upon T2D conditions. Mechanistically, RNA-sequencing analysis showed that Nr4a1, a nuclear receptor known to have potent anti-inflammatory effects, is involved in Lcn10-mediated macrophage activation. Indeed, we found that nuclear translocation of Nr4a1 was disrupted in Lcn10-KO macrophages upon stimulation with LPS + IFNγ. Accordingly, treatment with Cytosporone B (CsnB), an agonist of Nr4a1, attenuated the pro-inflammatory response in Lcn10-null macrophages and partially improved cardiac function in Lcn10-KO diabetic mice. Together, these findings indicate that loss of Lcn10 skews macrophage polarization to pro-inflammatory phenotype and aggravates cardiac dysfunction during type-2 diabetes through the disruption of Nr4a1-mediated anti-inflammatory signaling pathway in macrophages. Therefore, reduction of Lcn10 expression observed in diabetic macrophages may be responsible for the pathogenesis of diabetes-induced cardiac dysfunction. It suggests that Lcn10 might be a potential therapeutic factor for diabetic heart failure.
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Affiliation(s)
- Qianqian Li
- Division of Pharmaceutical Sciences, James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH, United States
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Yutian Li
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Wei Huang
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Xiaohong Wang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Zhenling Liu
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Jing Chen
- Division of Biomedical Informatics, Cincinnati Children’s Hospital Medical Center, Cincinnati, OH, United States
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Yanbo Fan
- Department of Cancer Biology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Tianqing Peng
- The Centre for Critical Illness Research, Lawson Health Research Institute, London, ON, Canada
| | - Sakthivel Sadayappan
- Division of Cardiovascular Health and Disease, Department of Internal Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Yigang Wang
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, Cincinnati, OH, United States
| | - Guo-Chang Fan
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, United States
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20
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Ko ER, Henao R, Frankey K, Petzold EA, Isner PD, Jaehne AK, Allen N, Gardner-Gray J, Hurst G, Pflaum-Carlson J, Jayaprakash N, Rivers EP, Wang H, Ugalde I, Amanullah S, Mercurio L, Chun TH, May L, Hickey RW, Lazarus JE, Gunaratne SH, Pallin DJ, Jambaulikar G, Huckins DS, Ampofo K, Jhaveri R, Jiang Y, Komarow L, Evans SR, Ginsburg GS, Tillekeratne LG, McClain MT, Burke TW, Woods CW, Tsalik EL. Prospective Validation of a Rapid Host Gene Expression Test to Discriminate Bacterial From Viral Respiratory Infection. JAMA Netw Open 2022; 5:e227299. [PMID: 35420659 PMCID: PMC9011121 DOI: 10.1001/jamanetworkopen.2022.7299] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2021] [Accepted: 02/24/2022] [Indexed: 12/24/2022] Open
Abstract
Importance Bacterial and viral causes of acute respiratory illness (ARI) are difficult to clinically distinguish, resulting in the inappropriate use of antibacterial therapy. The use of a host gene expression-based test that is able to discriminate bacterial from viral infection in less than 1 hour may improve care and antimicrobial stewardship. Objective To validate the host response bacterial/viral (HR-B/V) test and assess its ability to accurately differentiate bacterial from viral infection among patients with ARI. Design, Setting, and Participants This prospective multicenter diagnostic study enrolled 755 children and adults with febrile ARI of 7 or fewer days' duration from 10 US emergency departments. Participants were enrolled from October 3, 2014, to September 1, 2019, followed by additional enrollment of patients with COVID-19 from March 20 to December 3, 2020. Clinical adjudication of enrolled participants identified 616 individuals as having bacterial or viral infection. The primary analysis cohort included 334 participants with high-confidence reference adjudications (based on adjudicator concordance and the presence of an identified pathogen confirmed by microbiological testing). A secondary analysis of the entire cohort of 616 participants included cases with low-confidence reference adjudications (based on adjudicator discordance or the absence of an identified pathogen in microbiological testing). Thirty-three participants with COVID-19 were included post hoc. Interventions The HR-B/V test quantified the expression of 45 host messenger RNAs in approximately 45 minutes to derive a probability of bacterial infection. Main Outcomes and Measures Performance characteristics for the HR-B/V test compared with clinical adjudication were reported as either bacterial or viral infection or categorized into 4 likelihood groups (viral very likely [probability score <0.19], viral likely [probability score of 0.19-0.40], bacterial likely [probability score of 0.41-0.73], and bacterial very likely [probability score >0.73]) and compared with procalcitonin measurement. Results Among 755 enrolled participants, the median age was 26 years (IQR, 16-52 years); 360 participants (47.7%) were female, and 395 (52.3%) were male. A total of 13 participants (1.7%) were American Indian, 13 (1.7%) were Asian, 368 (48.7%) were Black, 131 (17.4%) were Hispanic, 3 (0.4%) were Native Hawaiian or Pacific Islander, 297 (39.3%) were White, and 60 (7.9%) were of unspecified race and/or ethnicity. In the primary analysis involving 334 participants, the HR-B/V test had sensitivity of 89.8% (95% CI, 77.8%-96.2%), specificity of 82.1% (95% CI, 77.4%-86.6%), and a negative predictive value (NPV) of 97.9% (95% CI, 95.3%-99.1%) for bacterial infection. In comparison, the sensitivity of procalcitonin measurement was 28.6% (95% CI, 16.2%-40.9%; P < .001), the specificity was 87.0% (95% CI, 82.7%-90.7%; P = .006), and the NPV was 87.6% (95% CI, 85.5%-89.5%; P < .001). When stratified into likelihood groups, the HR-B/V test had an NPV of 98.9% (95% CI, 96.1%-100%) for bacterial infection in the viral very likely group and a positive predictive value of 63.4% (95% CI, 47.2%-77.9%) for bacterial infection in the bacterial very likely group. The HR-B/V test correctly identified 30 of 33 participants (90.9%) with acute COVID-19 as having a viral infection. Conclusions and Relevance In this study, the HR-B/V test accurately discriminated bacterial from viral infection among patients with febrile ARI and was superior to procalcitonin measurement. The findings suggest that an accurate point-of-need host response test with high NPV may offer an opportunity to improve antibiotic stewardship and patient outcomes.
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Affiliation(s)
- Emily R. Ko
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Hospital Medicine, Division of General Internal Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Department of Biostatistics and Informatics, Duke University, Durham, North Carolina
- Duke Clinical Research Institute, Durham, North Carolina
| | - Katherine Frankey
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Elizabeth A. Petzold
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Pamela D. Isner
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Anja K. Jaehne
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Nakia Allen
- Department of Pediatrics, Henry Ford Hospital System, Detroit, Michigan
| | - Jayna Gardner-Gray
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Gina Hurst
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Jacqueline Pflaum-Carlson
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Namita Jayaprakash
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Division of Pulmonary and Critical Care Medicine, Henry Ford Hospital System, Detroit, Michigan
| | - Emanuel P. Rivers
- Department of Emergency Medicine, Henry Ford Hospital System, Detroit, Michigan
- Department of Surgery, Henry Ford Hospital System, Detroit, Michigan
| | - Henry Wang
- McGovern Medical University of Texas Health, Houston
- Department of Emergency Medicine, The Ohio State University, Columbus
| | - Irma Ugalde
- McGovern Medical University of Texas Health, Houston
| | - Siraj Amanullah
- Department of Emergency Medicine, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
- Department of Pediatrics, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
| | - Laura Mercurio
- Department of Emergency Medicine, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
- Department of Pediatrics, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
| | - Thomas H. Chun
- Department of Emergency Medicine, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
- Department of Pediatrics, Alpert Medical School of Brown University, Hasbro Children’s Hospital, Providence, Rhode Island
| | - Larissa May
- Department of Emergency Medicine, University of California, Davis
| | - Robert W. Hickey
- Division of Pediatric Emergency Medicine, UPMC Children’s Hospital of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jacob E. Lazarus
- Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | - Shauna H. Gunaratne
- Division of Infectious Diseases, Department of Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
- Division of Infectious Diseases, Department of Medicine, Columbia University Irving Medical Center, New York, New York
| | - Daniel J. Pallin
- Department of Emergency Medicine, Brigham and Women’s Hospital, Boston, Massachusetts
| | | | - David S. Huckins
- Department of Emergency Medicine, Newton-Wellesley Hospital, Boston, Massachusetts
| | - Krow Ampofo
- Department of Pediatrics, University of Utah, Salt Lake City
| | - Ravi Jhaveri
- Department of Pediatrics, University of North Carolina at Chapel Hill
- Department of Pediatrics, Northwestern University Feinberg School of Medicine, Chicago, Illinois
| | - Yunyun Jiang
- The Biostatistics Center, George Washington University, Rockville, Maryland
| | - Lauren Komarow
- The Biostatistics Center, George Washington University, Rockville, Maryland
| | - Scott R. Evans
- The Biostatistics Center, George Washington University, Rockville, Maryland
| | - Geoffrey S. Ginsburg
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - L. Gayani Tillekeratne
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Medical Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
| | - Micah T. McClain
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Medical Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
| | - Thomas W. Burke
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
| | - Christopher W. Woods
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Medical Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
| | - Ephraim L. Tsalik
- Center for Applied Genomics and Precision Medicine, Duke University School of Medicine, Durham, North Carolina
- Division of Infectious Diseases, Department of Medicine, Duke University School of Medicine, Durham, North Carolina
- Emergency Medicine Service, Durham Veterans Affairs Health Care System, Durham, North Carolina
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21
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Yao L, Rey DA, Bulgarelli L, Kast R, Osborn J, Van Ark E, Fang LT, Lau B, Lam H, Teixeira LM, Neto AS, Bellomo R, Deliberato RO. Gene Expression Scoring of Immune Activity Levels for Precision Use of Hydrocortisone in Vasodilatory Shock. Shock 2022; 57:384-391. [PMID: 35081076 PMCID: PMC8868213 DOI: 10.1097/shk.0000000000001910] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Revised: 12/06/2021] [Accepted: 01/07/2022] [Indexed: 11/26/2022]
Abstract
PURPOSE Among patients with vasodilatory shock, gene expression scores may identify different immune states. We aimed to test whether such scores are robust in identifying patients' immune state and predicting response to hydrocortisone treatment in vasodilatory shock. MATERIALS AND METHODS We selected genes to generate continuous scores to define previously established subclasses of sepsis. We used these scores to identify a patient's immune state. We evaluated the potential for these states to assess the differential effect of hydrocortisone in two randomized clinical trials of hydrocortisone versus placebo in vasodilatory shock. RESULTS We initially identified genes associated with immune-adaptive, immune-innate, immune-coagulant functions. From these genes, 15 were most relevant to generate expression scores related to each of the functions. These scores were used to identify patients as immune-adaptive prevalent (IA-P) and immune-innate prevalent (IN-P). In IA-P patients, hydrocortisone therapy increased 28-day mortality in both trials (43.3% vs 14.7%, P = 0.028) and (57.1% vs 0.0%, P = 0.99). In IN-P patients, this effect was numerically reversed. CONCLUSIONS Gene expression scores identified the immune state of vasodilatory shock patients, one of which (IA-P) identified those who may be harmed by hydrocortisone. Gene expression scores may help advance the field of personalized medicine.
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Affiliation(s)
- Lijing Yao
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Diego Ariel Rey
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Lucas Bulgarelli
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Rachel Kast
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Jeff Osborn
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Emily Van Ark
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Li Tai Fang
- Department of Clinical Data Science, Endpoint Health Inc, Palo Alto, California
| | - Bayo Lau
- Bioinformatics Department, HypaHub Inc, San Jose, California, USA
| | - Hugo Lam
- Bioinformatics Department, HypaHub Inc, San Jose, California, USA
| | | | - Ary Serpa Neto
- Department of Critical Care Medicine, Hospital Israelita Albert Einstein, São Paulo, Brazil
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Department of Critical Care, Melbourne Medical School, University of Melbourne, Austin Hospital, Melbourne, Australia
- Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital, Melbourne, Australia
| | - Rinaldo Bellomo
- Australian and New Zealand Intensive Care Research Centre (ANZIC-RC), School of Public Health and Preventive Medicine, Monash University, Melbourne, Australia
- Department of Critical Care, Melbourne Medical School, University of Melbourne, Austin Hospital, Melbourne, Australia
- Data Analytics Research and Evaluation (DARE) Centre, Austin Hospital, Melbourne, Australia
- Department of Intensive Care, Austin Hospital, Melbourne, Australia
- Department of Intensive Care, Royal Melbourne Hospital, Melbourne, Australia
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22
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Yin ZX, Xing CY, Li GH, Pang LB, Wang J, Pan J, Zang R, Zhang S. A combined risk model for the multi-encompassing identification of heterogeneities of prognoses, biological pathway variations and immune states for sepsis patients. BMC Anesthesiol 2022; 22:16. [PMID: 34996374 PMCID: PMC8739717 DOI: 10.1186/s12871-021-01552-x] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2021] [Accepted: 12/21/2021] [Indexed: 12/21/2022] Open
Abstract
Background Sepsis is a highly heterogeneous syndrome with stratified severity levels and immune states. Even in patients with similar clinical appearances, the underlying signal transduction pathways are significantly different. To identify the heterogeneities of sepsis from multiple angles, we aimed to establish a combined risk model including the molecular risk score for rapid mortality prediction, pathway risk score for the identification of biological pathway variations, and immunity risk score for guidance with immune-modulation therapy. Methods We systematically searched and screened the mRNA expression profiles of patients with sepsis in the Gene Expression Omnibus public database. The screened datasets were divided into a training cohort and a validation cohort. In the training cohort, authentic prognostic predictor characteristics (differentially expressed mRNAs, pathway activity variations and immune cells) were screened for model construction through bioinformatics analysis and univariate Cox regression, and a P value less than 0.05 of univariate Cox regression on 28-day mortality was set as the cut-off value. The combined risk model was finally established by the decision tree algorithm. In the validation cohort, the model performance was assessed and validated by C statistics and the area under the receiver operating characteristic curve (AUC). Additionally, the current models were further compared in clinical value with traditional indicators, including procalcitonin (PCT) and interleukin-8 (IL-8). Results Datasets from two sepsis cohort studies with a total of 585 consecutive sepsis patients admitted to two intensive care units were downloaded as the training cohort (n = 479) and external validation cohort (n = 106). In the training cohort, 15 molecules, 20 pathways and 4 immune cells were eventually enrolled in model construction. These prognostic factors mainly reflected hypoxia, cellular injury, metabolic disorders and immune dysregulation in sepsis patients. In the validation cohort, the AUCs of the molecular model, pathway model, immune model, and combined model were 0.81, 0.82, 0.62 and 0.873, respectively. The AUCs of the traditional biomarkers (PCT and IL-8) were 0.565 and 0.585, respectively. The survival analysis indicated that patients in the high-risk group identified by models in the current study had a poor prognosis (P < 0.05). The above results indicated that the models in this study are all superior to the traditional biomarkers for the predicting the prognosis of sepsis patients. Furthermore, the current study provides some therapeutic recommendations for patients with high risk scores identified by the three submodels. Conclusions In summary, the present study provides opportunities for bedside tests that could quantitatively and rapidly measure heterogeneous prognosis, underlying biological pathway variations and immune dysfunction in sepsis patients. Further therapeutic recommendations for patients with high risk scores could improve the therapeutic system for sepsis. Supplementary Information The online version contains supplementary material available at 10.1186/s12871-021-01552-x.
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Affiliation(s)
- Zong-Xiu Yin
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Chun-Yan Xing
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Guan-Hua Li
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Long-Bin Pang
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jing Wang
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Jing Pan
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Rui Zang
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China.,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China
| | - Shi Zhang
- Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University and Shandong Academy of Medical Sciences, Cheeloo College of Medicine, Shandong University, No. 105 Jiefang Road, Jinan, 250013, Shandong Province, China. .,Department of Pulmonary and Critical Care Medicine, Jinan Central Hospital Affiliated to Shandong First Medical University, Jinan, China.
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23
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Jiang Y, Miao Q, Hu L, Zhou T, Hu Y, Tian Y. FYN and CD247: key Genes for Septic Shock Based on Bioinformatics and Meta-Analysis. Comb Chem High Throughput Screen 2021; 25:1722-1730. [PMID: 34397323 DOI: 10.2174/1386207324666210816123508] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2021] [Revised: 06/11/2021] [Accepted: 06/27/2021] [Indexed: 11/22/2022]
Abstract
BACKGROUND Septic shock is sepsis accompanied by hemodynamic instability and high clinical mortality. MATERIAL AND METHODS GSE95233, GSE57065, GSE131761 gene-expression profiles of healthy control subjects and septic shock patients were downloaded from the Gene-Expression Omnibus (GEO) database, and differences of expression profiles and their intersection were analysed using GEO2R. Function and pathway enrichment analysis was performed on common differentially expressed genes (DEG), and key genes for septic shock were screened using a protein-protein interaction network created with STRING. Also, data from the GEO database were used for survival analysis for key genes, and a meta-analysis was used to explore expression trends of core genes. Finally, high-throughput sequencing using the blood of a murine sepsis model was performed to analyse the expression of CD247 and FYN in mice. RESULTS A total of 539 DEGs were obtained (p < 0.05). Gene ontology analysis showed that key genes were enriched in functions, such as immune response and T cell activity, and DEGs were enriched in signal pathways, such as T cell receptors. FYN and CD247 are in the centre of the protein-protein interaction network, and survival analysis found that they are positively correlated with survival from sepsis. Further, meta-analysis results showed that FYN could be useful for the prognosis of patients, and CD247 might distinguish between sepsis and systemic inflammatory response syndrome patients. Finally, RNA sequencing using a mouse septic shock model showed low expression of CD247 and FYN in this model. CONCLUSION FYN and CD247 are expected to become new biomarkers of septic shock.
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Affiliation(s)
- Yue Jiang
- Department of Clinical Medicine, Affiliated of Southwest Medical University, Luzhou, 646000, China
| | - Qian Miao
- Department of Clinical Medicine, Affiliated of Southwest Medical University, Luzhou, 646000, China
| | - Lin Hu
- Department of Pediatrics, people's Hospital of Lushan County, Ya'an, 625600. 0
| | - Tingyan Zhou
- Department of Clinical Medicine, Affiliated of Southwest Medical University, Luzhou, 646000, China
| | - Yingchun Hu
- Department of Emergency, Affiliated of Southwest Medical University, 646000, China
| | - Ye Tian
- Department of Emergency, Affiliated of Southwest Medical University, 646000, China
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24
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Zhu T, Su Q, Wang C, Shen L, Chen H, Feng S, Peng X, Chen S, Wang Y, Jiang H, Chen J. SDF4 Is a Prognostic Factor for 28-Days Mortality in Patients With Sepsis via Negatively Regulating ER Stress. Front Immunol 2021; 12:659193. [PMID: 34326834 PMCID: PMC8313857 DOI: 10.3389/fimmu.2021.659193] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Accepted: 06/28/2021] [Indexed: 12/12/2022] Open
Abstract
Sepsis is a heterogeneous syndrome induced by infection and results in high mortality. Even though more than 100 biomarkers for sepsis prognosis were evaluated, prediction of patient outcomes in sepsis continues to be driven by clinical signs because of unsatisfactory specificity and sensitivity of these biomarkers. This study aimed to elucidate the key candidate genes involved in sepsis response and explore their downstream effects based on weighted gene co-expression network analysis (WGCNA). The dataset GSE63042 with sepsis outcome information was obtained from the Gene Expression Omnibus (GEO) database and then consensus WGCNA was conducted. We identified the hub gene SDF4 (stromal cell derived factor 4) from the M6 module, which was significantly associated with mortality. Subsequently, two datasets (GSE54514 and E-MTAB-4421) and cohort validation (n=89) were performed. Logistic regression analysis was used to build a prediction model and the combined score resulting in a satisfactory prognosis value (area under the ROC curve=0.908). The model was subsequently tested by another sepsis cohort (n=70, ROC= 0.925). We next demonstrated that endoplasmic reticulum (ER) stress tended to be more severe in patients PBMCs with negative outcomes compared to those with positive outcomes and SDF4 was related to this phenomenon. In addition, our results indicated that adenovirus-mediated Sdf4 overexpression attenuated ER stress in cecal ligation and puncture (CLP) mice lung. In summary, our study indicates that incorporation of SDF4 can improve clinical parameters predictive value for the prognosis of sepsis, and decreased expression levels of SDF4 contributes to excessive ER stress, which is associated with worsened outcomes, whereas overexpression of SDF4 attenuated such activation.
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Affiliation(s)
- Tingting Zhu
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Qun Su
- Critical Care Medicine Department, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China
| | - Cuili Wang
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Lingling Shen
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Hongjun Chen
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Shi Feng
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Xiaofeng Peng
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Siyu Chen
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Yucheng Wang
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Hong Jiang
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
| | - Jianghua Chen
- Kidney Disease Center, The First Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou, China.,Key Laboratory of Nephropathy, Hangzhou, China.,Institute of Nephropathy, Zhejiang University, Hangzhou, China
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25
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A single transcript for the prognosis of disease severity in COVID-19 patients. Sci Rep 2021; 11:12174. [PMID: 34108608 PMCID: PMC8190311 DOI: 10.1038/s41598-021-91754-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2021] [Accepted: 06/01/2021] [Indexed: 12/16/2022] Open
Abstract
With many countries strapped for medical resources due to the COVID-19 pandemic, it is highly desirable to allocate the precious resources to those who need them the most. Several markers have been found to be associated with the disease severity in COVID-19 patients. However, the established markers only display modest prognostic power individually and better markers are urgently needed. The aim of this study is to investigate the potential of S100A12, a prominent marker gene for bacterial infection, in the prognosis of disease severity in COVID-19 patients. To ensure the robustness of the association, a total of 1695 samples from 14 independent transcriptome datasets on sepsis, influenza infection and COVID-19 infection were examined. First, it was demonstrated that S100A12 was a marker for sepsis and severity of sepsis. Then, S100A12 was found to be a marker for severe influenza infection, and there was an upward trend of S100A12 expression as the severity level of influenza infection increased. As for COVID-19 infection, it was found that S100A12 expression was elevated in patients with severe and critical COVID-19 infection. More importantly, S100A12 expression at hospital admission was robustly correlated with future quantitative indexes of disease severity and outcome in COVID-19 patients, superior to established prognostic markers including CRP, PCT, d-dimer, ferritin, LDH and fibrinogen. Thus, S100A12 is a valuable novel prognostic marker for COVID-19 severity and deserves more attention.
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26
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Devadoss D, Daly G, Manevski M, Houserova D, Hussain SS, Baumlin N, Salathe M, Borchert G, Langley RJ, Chand HS. A long noncoding RNA antisense to ICAM-1 is involved in allergic asthma associated hyperreactive response of airway epithelial cells. Mucosal Immunol 2021; 14:630-639. [PMID: 33122732 PMCID: PMC8081750 DOI: 10.1038/s41385-020-00352-9] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 10/11/2020] [Accepted: 10/14/2020] [Indexed: 02/04/2023]
Abstract
Epithelial cells of the conducting airways are a pivotal first line of defense against airborne pathogens and allergens that orchestrate inflammatory responses and mucociliary clearance. Nonetheless, the molecular mechanisms responsible for epithelial hyperreactivity associated with allergic asthma are not completely understood. Transcriptomic analysis of human airway epithelial cells (HAECs), differentiated in-vitro at air-liquid interface (ALI), showed 725 differentially expressed immediate-early transcripts, including putative long noncoding RNAs (lncRNAs). A novel lncRNA on the antisense strand of ICAM-1 or LASI was identified, which was induced in LPS-primed HAECs along with mucin MUC5AC and its transcriptional regulator SPDEF. LPS-primed expression of LASI, MUC5AC, and SPDEF transcripts were higher in ex-vivo cultured asthmatic HAECs that were further augmented by LPS treatment. Airway sections from asthmatics with increased mucus load showed higher LASI expression in MUC5AC+ goblet cells following multi-fluorescent in-situ hybridization and immunostaining. LPS- or IL-13-induced LASI transcripts were mostly enriched in the nuclear/perinuclear region and were associated with increased ICAM-1, IL-6, and CXCL-8 expression. Blocking LASI expression reduced the LPS or IL-13-induced epithelial inflammatory factors and MUC5AC expression, suggesting that the novel lncRNA LASI could play a key role in LPS-primed trained airway epithelial responses that are dysregulated in allergic asthma.
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Affiliation(s)
- Dinesh Devadoss
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, FL-33199
| | - Grant Daly
- Department of Pharmacology, University of South Alabama, Mobile, AL-36688
| | - Marko Manevski
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, FL-33199
| | - Dominika Houserova
- Department of Pharmacology, University of South Alabama, Mobile, AL-36688
| | - Shah S. Hussain
- Medicine-Pulmonary/Allergy/Critical Care, University of Alabama at Birmingham, Birmingham, AL-35233
| | - Nathalie Baumlin
- Miller School of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Miami, Miami, FL-33136,Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS-66160
| | - Matthias Salathe
- Miller School of Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Miami, Miami, FL-33136,Department of Internal Medicine, University of Kansas Medical Center, Kansas City, KS-66160
| | - Glen Borchert
- Department of Pharmacology, University of South Alabama, Mobile, AL-36688
| | - Raymond J. Langley
- Department of Pharmacology, University of South Alabama, Mobile, AL-36688
| | - Hitendra S. Chand
- Department of Immunology and Nano-Medicine, Herbert Wertheim College of Medicine, Florida International University, Miami, FL-33199
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27
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Li Y, Deng S, Wang X, Huang W, Chen J, Robbins N, Mu X, Essandoh K, Peng T, Jegga AG, Rubinstein J, Adams DE, Wang Y, Peng J, Fan GC. Sectm1a deficiency aggravates inflammation-triggered cardiac dysfunction through disruption of LXRα signalling in macrophages. Cardiovasc Res 2021; 117:890-902. [PMID: 32170929 PMCID: PMC8453795 DOI: 10.1093/cvr/cvaa067] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/20/2019] [Revised: 02/17/2020] [Accepted: 03/12/2020] [Indexed: 01/03/2023] Open
Abstract
AIMS Cardiac dysfunction is a prevalent comorbidity of disrupted inflammatory homeostasis observed in conditions such as sepsis (acute) or obesity (chronic). Secreted and transmembrane protein 1a (Sectm1a) has previously been implicated to regulate inflammatory responses, yet its role in inflammation-associated cardiac dysfunction is virtually unknown. METHODS AND RESULTS Using the CRISPR/Cas9 system, we generated a global Sectm1a-knockout (KO) mouse model and observed significantly increased mortality and cardiac injury after lipopolysaccharide (LPS) injection, when compared with wild-type (WT) control. Further analysis revealed significantly increased accumulation of inflammatory macrophages in hearts of LPS-treated KO mice. Accordingly, ablation of Sectm1a remarkably increased inflammatory cytokines levels both in vitro [from bone marrow-derived macrophages (BMDMs)] and in vivo (in serum and myocardium) after LPS challenge. RNA-sequencing results and bioinformatics analyses showed that the most significantly down-regulated genes in KO-BMDMs were modulated by LXRα, a nuclear receptor with robust anti-inflammatory activity in macrophages. Indeed, we identified that the nuclear translocation of LXRα was disrupted in KO-BMDMs when treated with GW3965 (LXR agonist), resulting in higher levels of inflammatory cytokines, compared to GW3965-treated WT-cells. Furthermore, using chronic inflammation model of high-fat diet (HFD) feeding, we observed that infiltration of inflammatory monocytes/macrophages into KO-hearts were greatly increased and accordingly, worsened cardiac function, compared to WT-HFD controls. CONCLUSION This study defines Sectm1a as a new regulator of inflammatory-induced cardiac dysfunction through modulation of LXRα signalling in macrophages. Our data suggest that augmenting Sectm1a activity may be a potential therapeutic approach to resolve inflammation and associated cardiac dysfunction.
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Affiliation(s)
- Yutian Li
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Shan Deng
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
| | - Xiaohong Wang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Wei Huang
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Jing Chen
- Division of Biomedical Informatics, Cincinnati Children’s Hospital, Cincinnati, OH 45267, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Nathan Robbins
- Department of Internal Medicine, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Xingjiang Mu
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Kobina Essandoh
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Tianqing Peng
- Critical Illness Research, Lawson Health Research Institute, London, ON N6A 4G5, Canada
| | - Anil G Jegga
- Division of Biomedical Informatics, Cincinnati Children’s Hospital, Cincinnati, OH 45267, USA
| | - Jack Rubinstein
- Department of Internal Medicine, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - David E Adams
- Division of Immunology, Allergy and Rheumatology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Yigang Wang
- Department of Pathology and Laboratory Medicine, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
| | - Jiangtong Peng
- Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China
| | - Guo-Chang Fan
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, 231 Albert Sabin Way, Cincinnati, OH 45267-0575, USA
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28
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Rethinking animal models of sepsis - working towards improved clinical translation whilst integrating the 3Rs. Clin Sci (Lond) 2021; 134:1715-1734. [PMID: 32648582 PMCID: PMC7352061 DOI: 10.1042/cs20200679] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Revised: 06/24/2020] [Accepted: 06/25/2020] [Indexed: 12/13/2022]
Abstract
Sepsis is a major worldwide healthcare issue with unmet clinical need. Despite extensive animal research in this area, successful clinical translation has been largely unsuccessful. We propose one reason for this is that, sometimes, the experimental question is misdirected or unrealistic expectations are being made of the animal model. As sepsis models can lead to a rapid and substantial suffering – it is essential that we continually review experimental approaches and undertake a full harm:benefit impact assessment for each study. In some instances, this may require refinement of existing sepsis models. In other cases, it may be replacement to a different experimental system altogether, answering a mechanistic question whilst aligning with the principles of reduction, refinement and replacement (3Rs). We discuss making better use of patient data to identify potentially useful therapeutic targets which can subsequently be validated in preclinical systems. This may be achieved through greater use of construct validity models, from which mechanistic conclusions are drawn. We argue that such models could provide equally useful scientific data as face validity models, but with an improved 3Rs impact. Indeed, construct validity models may not require sepsis to be modelled, per se. We propose that approaches that could support and refine clinical translation of research findings, whilst reducing the overall welfare burden on research animals.
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29
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Aschenbrenner AC, Mouktaroudi M, Krämer B, Oestreich M, Antonakos N, Nuesch-Germano M, Gkizeli K, Bonaguro L, Reusch N, Baßler K, Saridaki M, Knoll R, Pecht T, Kapellos TS, Doulou S, Kröger C, Herbert M, Holsten L, Horne A, Gemünd ID, Rovina N, Agrawal S, Dahm K, van Uelft M, Drews A, Lenkeit L, Bruse N, Gerretsen J, Gierlich J, Becker M, Händler K, Kraut M, Theis H, Mengiste S, De Domenico E, Schulte-Schrepping J, Seep L, Raabe J, Hoffmeister C, ToVinh M, Keitel V, Rieke G, Talevi V, Skowasch D, Aziz NA, Pickkers P, van de Veerdonk FL, Netea MG, Schultze JL, Kox M, Breteler MMB, Nattermann J, Koutsoukou A, Giamarellos-Bourboulis EJ, Ulas T. Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients. Genome Med 2021; 13:7. [PMID: 33441124 DOI: 10.1101/2020.07.07.20148395] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 12/18/2020] [Indexed: 05/18/2023] Open
Abstract
BACKGROUND The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.
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Affiliation(s)
- Anna C Aschenbrenner
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maria Mouktaroudi
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Benjamin Krämer
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | - Marie Oestreich
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Nikolaos Antonakos
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Melanie Nuesch-Germano
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Konstantina Gkizeli
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Lorenzo Bonaguro
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Nico Reusch
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Kevin Baßler
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Maria Saridaki
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Rainer Knoll
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Tal Pecht
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Theodore S Kapellos
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Sarandia Doulou
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Charlotte Kröger
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Miriam Herbert
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Lisa Holsten
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Arik Horne
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Ioanna D Gemünd
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Nikoletta Rovina
- 1st Department of Pulmonary Medicine and Intensive Care Unit, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Shobhit Agrawal
- West German Genome Center (WGGC), University of Bonn, Bonn, Germany
| | - Kilian Dahm
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Martina van Uelft
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Anna Drews
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Lena Lenkeit
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Niklas Bruse
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jelle Gerretsen
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jannik Gierlich
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Matthias Becker
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Kristian Händler
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Michael Kraut
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Heidi Theis
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Simachew Mengiste
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Elena De Domenico
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Jonas Schulte-Schrepping
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Lea Seep
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Jan Raabe
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | | | - Michael ToVinh
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | - Verena Keitel
- Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Gereon Rieke
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | - Valentina Talevi
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Dirk Skowasch
- Department of Internal Medicine II, Section of Pneumology, University Hospital of Bonn (UKB), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Peter Pickkers
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank L van de Veerdonk
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
- Immunology & Metabolism, Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Joachim L Schultze
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Matthijs Kox
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Jacob Nattermann
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
- German Center for Infection Research (DZIF), Bonn, Germany
| | - Antonia Koutsoukou
- 1st Department of Pulmonary Medicine and Intensive Care Unit, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | | | - Thomas Ulas
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany.
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30
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Aschenbrenner AC, Mouktaroudi M, Krämer B, Oestreich M, Antonakos N, Nuesch-Germano M, Gkizeli K, Bonaguro L, Reusch N, Baßler K, Saridaki M, Knoll R, Pecht T, Kapellos TS, Doulou S, Kröger C, Herbert M, Holsten L, Horne A, Gemünd ID, Rovina N, Agrawal S, Dahm K, van Uelft M, Drews A, Lenkeit L, Bruse N, Gerretsen J, Gierlich J, Becker M, Händler K, Kraut M, Theis H, Mengiste S, De Domenico E, Schulte-Schrepping J, Seep L, Raabe J, Hoffmeister C, ToVinh M, Keitel V, Rieke G, Talevi V, Skowasch D, Aziz NA, Pickkers P, van de Veerdonk FL, Netea MG, Schultze JL, Kox M, Breteler MMB, Nattermann J, Koutsoukou A, Giamarellos-Bourboulis EJ, Ulas T. Disease severity-specific neutrophil signatures in blood transcriptomes stratify COVID-19 patients. Genome Med 2021; 13:7. [PMID: 33441124 PMCID: PMC7805430 DOI: 10.1186/s13073-020-00823-5] [Citation(s) in RCA: 161] [Impact Index Per Article: 53.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Accepted: 12/18/2020] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND The SARS-CoV-2 pandemic is currently leading to increasing numbers of COVID-19 patients all over the world. Clinical presentations range from asymptomatic, mild respiratory tract infection, to severe cases with acute respiratory distress syndrome, respiratory failure, and death. Reports on a dysregulated immune system in the severe cases call for a better characterization and understanding of the changes in the immune system. METHODS In order to dissect COVID-19-driven immune host responses, we performed RNA-seq of whole blood cell transcriptomes and granulocyte preparations from mild and severe COVID-19 patients and analyzed the data using a combination of conventional and data-driven co-expression analysis. Additionally, publicly available data was used to show the distinction from COVID-19 to other diseases. Reverse drug target prediction was used to identify known or novel drug candidates based on finding from data-driven findings. RESULTS Here, we profiled whole blood transcriptomes of 39 COVID-19 patients and 10 control donors enabling a data-driven stratification based on molecular phenotype. Neutrophil activation-associated signatures were prominently enriched in severe patient groups, which was corroborated in whole blood transcriptomes from an independent second cohort of 30 as well as in granulocyte samples from a third cohort of 16 COVID-19 patients (44 samples). Comparison of COVID-19 blood transcriptomes with those of a collection of over 3100 samples derived from 12 different viral infections, inflammatory diseases, and independent control samples revealed highly specific transcriptome signatures for COVID-19. Further, stratified transcriptomes predicted patient subgroup-specific drug candidates targeting the dysregulated systemic immune response of the host. CONCLUSIONS Our study provides novel insights in the distinct molecular subgroups or phenotypes that are not simply explained by clinical parameters. We show that whole blood transcriptomes are extremely informative for COVID-19 since they capture granulocytes which are major drivers of disease severity.
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Affiliation(s)
- Anna C Aschenbrenner
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Maria Mouktaroudi
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Benjamin Krämer
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | - Marie Oestreich
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Nikolaos Antonakos
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Melanie Nuesch-Germano
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Konstantina Gkizeli
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Lorenzo Bonaguro
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Nico Reusch
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Kevin Baßler
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Maria Saridaki
- 4th Department of Internal Medicine, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Rainer Knoll
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Tal Pecht
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Theodore S Kapellos
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Sarandia Doulou
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Charlotte Kröger
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Miriam Herbert
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Lisa Holsten
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Arik Horne
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Ioanna D Gemünd
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Nikoletta Rovina
- 1st Department of Pulmonary Medicine and Intensive Care Unit, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | - Shobhit Agrawal
- West German Genome Center (WGGC), University of Bonn, Bonn, Germany
| | - Kilian Dahm
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Martina van Uelft
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Anna Drews
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Lena Lenkeit
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Niklas Bruse
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jelle Gerretsen
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Jannik Gierlich
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Matthias Becker
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Kristian Händler
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Michael Kraut
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Heidi Theis
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Simachew Mengiste
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Elena De Domenico
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
| | - Jonas Schulte-Schrepping
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Lea Seep
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Jan Raabe
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | | | - Michael ToVinh
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | - Verena Keitel
- Department of Gastroenterology, Hepatology and Infectious Diseases, University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Gereon Rieke
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
| | - Valentina Talevi
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
| | - Dirk Skowasch
- Department of Internal Medicine II, Section of Pneumology, University Hospital of Bonn (UKB), Bonn, Germany
| | - N Ahmad Aziz
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Department of Neurology, Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Peter Pickkers
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Frank L van de Veerdonk
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Mihai G Netea
- Department of Internal Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
- Immunology & Metabolism, Life and Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Joachim L Schultze
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany
- Genomics and Immunoregulation, Life & Medical Sciences (LIMES) Institute, University of Bonn, Bonn, Germany
| | - Matthijs Kox
- Department of Intensive Care Medicine and Radboud Center for Infectious Diseases (RCI), Radboud University Medical Center, Nijmegen, The Netherlands
| | - Monique M B Breteler
- Population Health Sciences, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany
- Institute for Medical Biometry, Informatics and Epidemiology (IMBIE), Faculty of Medicine, University of Bonn, Bonn, Germany
| | - Jacob Nattermann
- Department I of Internal Medicine, University Hospital of Bonn (UKB), Bonn, Germany
- German Center for Infection Research (DZIF), Bonn, Germany
| | - Antonia Koutsoukou
- 1st Department of Pulmonary Medicine and Intensive Care Unit, National and Kapodistrian University of Athens, Medical School, Athens, Greece
| | | | - Thomas Ulas
- Systems Medicine, German Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
- PRECISE Platform for Single Cell Genomics and Epigenomics at the German Center for Neurodegenerative Diseases and the University of Bonn, Bonn, Germany.
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31
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Sectm1a Facilitates Protection against Inflammation-Induced Organ Damage through Promoting TRM Self-Renewal. Mol Ther 2020; 29:1294-1311. [PMID: 33279722 DOI: 10.1016/j.ymthe.2020.12.001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/15/2020] [Revised: 09/11/2020] [Accepted: 11/29/2020] [Indexed: 12/17/2022] Open
Abstract
Tissue-resident macrophages (TRMs) are sentinel cells for maintaining tissue homeostasis and organ function. In this study, we discovered that lipopolysaccharide (LPS) administration dramatically reduced TRM populations and suppressed their self-renewal capacities in multiple organs. Using loss- and gain-of-function approaches, we define Sectm1a as a novel regulator of TRM self-renewal. Specifically, at the earlier stage of endotoxemia, Sectm1a deficiency exaggerated acute inflammation-induced reduction of TRM numbers in multiple organs by suppressing their proliferation, which was associated with more infiltrations of inflammatory monocytes/neutrophils and more serious organ damage. By contrast, administration of recombinant Sectm1a enhanced TRM populations and improved animal survival upon endotoxin challenge. Mechanistically, we identified that Sectm1a-induced upregulation in the self-renewal capacity of TRM is dependent on GITR-activated T helper cell expansion and cytokine production. Meanwhile, we found that TRMs may play an important role in protecting local vascular integrity during endotoxemia. Our study demonstrates that Sectm1a contributes to stabling TRM populations through maintaining their self-renewal capacities, which benefits the host immune response to acute inflammation. Therefore, Sectm1a may serve as a new therapeutic agent for the treatment of inflammatory diseases.
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32
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Mu X, Wang P, Wang X, Li Y, Zhao H, Li Q, Essandoh K, Deng S, Peng T, Fan GC. Identification of a Novel Antisepsis Pathway: Sectm1a Enhances Macrophage Phagocytosis of Bacteria through Activating GITR. THE JOURNAL OF IMMUNOLOGY 2020; 205:1633-1643. [PMID: 32769121 DOI: 10.4049/jimmunol.2000440] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Accepted: 07/13/2020] [Indexed: 02/06/2023]
Abstract
The inability to effectively control invading bacteria or other pathogens is a major cause of multiple organ dysfunction and death in sepsis. As the first-line defense of the immune system, macrophages play a crucial role in the removal of pathogens during sepsis. In this study, we define secreted and transmembrane 1A (Sectm1a) as a novel ligand of glucocorticoid-induced TNFR (GITR) that greatly boosts macrophage phagocytosis and bactericidal capacity. Using a global Sectm1a knockout (KO) mouse model, we observed that Sectm1a deficiency significantly suppressed phagocytosis and bactericidal activity in both recruited macrophages and tissue-resident macrophages, which consequently aggravated bacterial burden in the blood and multiple organs and further increased systemic inflammation, leading to multiple organ injury and increased mortality during polymicrobial sepsis. By contrast, treatment of septic mice with recombinant Sectm1a protein (rSectm1a) not only promoted macrophage phagocytosis and bactericidal activity but also significantly improved survival outcome. Mechanistically, we identified that Sectm1a could bind to GITR in the surface of macrophages and thereby activate its downstream PI3K-Akt pathway. Accordingly, rSectm1a-mediated phagocytosis and bacterial killing were abolished in macrophages by either KO of GITR or pharmacological inhibition of the PI3K-Akt pathway. In addition, rSectm1a-induced therapeutic effects on sepsis injury were negated in GITR KO mice. Taken together, these results uncover that Sectm1a may represent a novel target for drug development to control bacterial dissemination during sepsis or other infectious diseases.
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Affiliation(s)
- Xingjiang Mu
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Peng Wang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267.,Department of Critical Care Medicine, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong 250021, China
| | - Xiaohong Wang
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Yutian Li
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Hongyan Zhao
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267.,Department of Critical Care Medicine, The Second Hospital of Shandong University, Jinan, Shandong 250033, China
| | - Qianqian Li
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267.,Division of Pharmaceutical Science, James L. Winkle College of Pharmacy, University of Cincinnati, Cincinnati, OH 45267
| | - Kobina Essandoh
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267
| | - Shan Deng
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267.,Department of Cardiology, Union Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430022, China; and
| | - Tianqing Peng
- The Centre for Critical Illness Research, Lawson Health Research Institute, London, Ontario N6C 2R5, Canada
| | - Guo-Chang Fan
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH 45267;
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33
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Obal D, Wu S, McKinstry-Wu A, Tawfik VL. A Guide to Understanding "State-of-the-Art" Basic Research Techniques in Anesthesiology. Anesth Analg 2020; 131:450-463. [PMID: 32371742 DOI: 10.1213/ane.0000000000004801] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Perioperative medicine is changing from a "protocol-based" approach to a progressively personalized care model. New molecular techniques and comprehensive perioperative medical records allow for detection of patient-specific phenotypes that may better explain, or even predict, a patient's response to perioperative stress and anesthetic care. Basic science technology has significantly evolved in recent years with the advent of powerful approaches that have translational relevance. It is incumbent on us as a primarily clinical specialty to have an in-depth understanding of rapidly evolving underlying basic science techniques to incorporate such approaches into our own research, critically interpret the literature, and improve future anesthesia patient care. This review focuses on 3 important and most likely practice-changing basic science techniques: next-generation sequencing (NGS), clustered regularly interspaced short palindromic repeat (CRISPR) modulations, and inducible pluripotent stem cells (iPSCs). Each technique will be described, potential advantages and limitations discussed, open questions and challenges addressed, and future developments outlined. We hope to provide insight for practicing physicians when confronted with basic science articles and encourage investigators to apply "state-of-the-art" technology to their future experiments.
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Affiliation(s)
- Detlef Obal
- From the Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, California.,Department of Anesthesiology, Perioperative, and Pain Medicine and Cardiovascular Institute, Stanford University School of Medicine, Stanford, California
| | - Shaogen Wu
- From the Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, California
| | - Andrew McKinstry-Wu
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania
| | - Vivianne L Tawfik
- From the Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University School of Medicine, Stanford, California
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Colón-Emeric C, Pieper CF, Schmader KE, Sloane R, Bloom A, McClain M, Magaziner J, Huffman KM, Orwig D, Crabtree DM, Whitson HE. Two Approaches to Classifying and Quantifying Physical Resilience in Longitudinal Data. J Gerontol A Biol Sci Med Sci 2020; 75:731-738. [PMID: 30993327 PMCID: PMC7328208 DOI: 10.1093/gerona/glz097] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2018] [Indexed: 01/26/2023] Open
Abstract
BACKGROUND Approaches for quantifying physical resilience in older adults have not been described. METHODS We apply two conceptual approaches to defining physical resilience to existing longitudinal data sets in which outcomes are measured after an acute physical stressor. A "recovery phenotype" approach uses statistical methods to describe how quickly and completely a patient recovers. Statistical methods using a recovery phenotype approach can consider multiple outcomes simultaneously in a composite score (eg, factor analysis and principal components analysis) or identify groups of patients with similar recovery trajectories across multiple outcomes (eg, latent class profile analysis). An "expected recovery differential" approach quantifies how patients' actual outcomes are compared to their predicted outcome based on a population-derived model and their individual clinical characteristics at the time of the stressor. RESULTS Application of the approaches identified different participants as being the most or least physically resilient. In the viral respiratory cohort (n = 186) weighted kappa for agreement across resilience quartiles was 0.37 (0.27-0.47). The expected recovery differential approach identified a group with more comorbidities and lower baseline function as highly resilient. In the hip fracture cohort (n = 541), comparison of the expected recovery differentials across 10 outcome measures within individuals provided preliminary support for the hypothesis that there is a latent resilience trait at the whole-person level. CONCLUSIONS We posit that recovery phenotypes may be useful in clinical applications such as prediction models because they summarize the observed outcomes across multiple measures. Expected recovery differentials offer insight into mechanisms behind physical resilience not captured by age and other comorbidities.
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Affiliation(s)
- Cathleen Colón-Emeric
- Division of Geriatrics, Duke University, Durham, North Carolina
- Geriatric Research Education Clinical Center, Durham Veteran Affairs Medical Center, North Carolina
- Duke Claude D. Pepper Older American Independence Center, Duke University, Durham, North Carolina
| | - Carl F Pieper
- Geriatric Research Education Clinical Center, Durham Veteran Affairs Medical Center, North Carolina
- Duke Claude D. Pepper Older American Independence Center, Duke University, Durham, North Carolina
| | - Kenneth E Schmader
- Division of Geriatrics, Duke University, Durham, North Carolina
- Geriatric Research Education Clinical Center, Durham Veteran Affairs Medical Center, North Carolina
- Duke Claude D. Pepper Older American Independence Center, Duke University, Durham, North Carolina
| | - Richard Sloane
- Geriatric Research Education Clinical Center, Durham Veteran Affairs Medical Center, North Carolina
- Duke Claude D. Pepper Older American Independence Center, Duke University, Durham, North Carolina
| | - Allison Bloom
- Center for Applied Genomics and Precision Medicine, Duke University Medical Centre, Durham, North Carolina
| | - Micah McClain
- Center for Applied Genomics and Precision Medicine, Duke University Medical Centre, Durham, North Carolina
| | - Jay Magaziner
- Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore
| | - Kim M Huffman
- Duke Molecular Physiology Institute, Duke University School of Medicine, Durham, North Carolina
| | - Denise Orwig
- Department of Epidemiology and Public Health, School of Medicine, University of Maryland, Baltimore
| | - Donna M Crabtree
- Duke Office of Clinical Research, School of Medicine, Duke University Medical Center, Durham, North Carolina
| | - Heather E Whitson
- Division of Geriatrics, Duke University, Durham, North Carolina
- Geriatric Research Education Clinical Center, Durham Veteran Affairs Medical Center, North Carolina
- Duke Claude D. Pepper Older American Independence Center, Duke University, Durham, North Carolina
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Dailey PJ, Elbeik T, Holodniy M. Companion and complementary diagnostics for infectious diseases. Expert Rev Mol Diagn 2020; 20:619-636. [PMID: 32031431 DOI: 10.1080/14737159.2020.1724784] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
INTRODUCTION Companion diagnostics (CDx) are important in oncology therapeutic decision-making, but specific regulatory-approved CDx for infectious disease treatment are officially lacking. While not approved as CDx, several ID diagnostics are used as CDx. The diagnostics community, manufacturers, and regulatory agencies have made major efforts to ensure that diagnostics for new antimicrobials are available at or near release of new agents. AREAS COVERED This review highlights the status of Complementary and companion diagnostic (c/CDx) in the infectious disease literature, with a focus on genotypic antimicrobial resistance testing against pathogens as a class of diagnostic tests. EXPERT OPINION CRISPR, sepsis markers, and narrow spectrum antimicrobials, in addition to current and emerging technologies, present opportunities for infectious disease c/CDx. Challenges include slow guideline revision, high costs for regulatory approval, lengthy buy in by agencies, discordant pharmaceutical/diagnostic partnerships, and higher treatment costs. The number of patients and available medications used to treat different infectious diseases is well suited to support competing diagnostic tests. However, newer approaches to treatment (for example, narrow spectrum antibiotics), may be well suited for a small number of patients, i.e. a niche market in support of a CDx. The current emphasis is rapid and point-of-care (POC) diagnostic platforms as well as changes in treatment.
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Affiliation(s)
- Peter J Dailey
- School of Public Health, University of California, Berkeley , Berkeley, CA, USA.,The Foundation for Innovative New Diagnostics (FIND) , Geneva, Switzerland
| | - Tarek Elbeik
- VA Palo Alto Health Care System, Department of Veterans Affairs , Palo Alto, CA, USA
| | - Mark Holodniy
- VA Palo Alto Health Care System, Department of Veterans Affairs , Palo Alto, CA, USA.,Division of Infectious Diseases and Geographic Medicine, Stanford University , Stanford, CA, USA
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Ahmad S, Singh P, Sharma A, Arora S, Shriwash N, Rahmani AH, Almatroodi SA, Manda K, Dohare R, Syed MA. Transcriptome Meta-Analysis Deciphers a Dysregulation in Immune Response-Associated Gene Signatures during Sepsis. Genes (Basel) 2019; 10:genes10121005. [PMID: 31817302 PMCID: PMC6947644 DOI: 10.3390/genes10121005] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2019] [Revised: 11/28/2019] [Accepted: 12/02/2019] [Indexed: 12/20/2022] Open
Abstract
Sepsis is a life-threatening disease induced by a systemic inflammatory response, which leads to organ dysfunction and mortality. In sepsis, the host immune response is depressed and unable to cope with infection; no drug is currently available to treat this. The lungs are frequently the starting point for sepsis. This study aimed to identify potential genes for diagnostics and therapeutic purposes in sepsis by a comprehensive bioinformatics analysis. Our criteria are to unravel sepsis-associated signature genes from gene expression datasets. Differentially expressed genes (DEGs) were identified from samples of sepsis patients using a meta-analysis and then further subjected to functional enrichment and protein‒protein interaction (PPI) network analysis for examining their potential functions. Finally, the expression of the topmost upregulated genes (ARG1, IL1R2, ELANE, MMP9) was quantified by reverse transcriptase-PCR (RT-PCR), and myeloperoxidase (MPO) expression was confirmed by immunohistochemistry (IHC) staining in the lungs of a well-established sepsis mouse model. We found that all the four genes were upregulated in semiquantitative RT-PCR studies; however, MMP9 showed a nonsignificant increase in expression. MPO staining showed strong immunoreactivity in sepsis as compared to the control. This study demonstrates the role of significant and widespread immune activation (IL1R2, MMP9), along with oxidative stress (ARG1) and the recruitment of neutrophils, in sepsis (ELANE, MPO).
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Affiliation(s)
- Shaniya Ahmad
- Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India; (S.A.); (A.S.); (S.A.)
| | - Prithvi Singh
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India;
| | - Archana Sharma
- Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India; (S.A.); (A.S.); (S.A.)
| | - Shweta Arora
- Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India; (S.A.); (A.S.); (S.A.)
| | - Nitesh Shriwash
- Department of Computer Science, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India;
| | - Arshad Husain Rahmani
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraidah 51452, Saudi Arabia; (A.H.R.); (S.A.A.)
| | - Saleh A. Almatroodi
- Department of Medical Laboratories, College of Applied Medical Sciences, Qassim University, Buraidah 51452, Saudi Arabia; (A.H.R.); (S.A.A.)
| | - Kailash Manda
- Institute of Nuclear Medicine and Applied Sciences, Defence Research Development Organization, New Delhi 110054, India;
| | - Ravins Dohare
- Centre for Interdisciplinary Research in Basic Sciences, Jamia Millia Islamia, New Delhi 110025, India;
- Correspondence: (R.D.); (M.A.S.); Tel.: +91-817-887-5779 (R.D.); +91-995-378-6440 (M.A.S.)
| | - Mansoor Ali Syed
- Translational Research Lab, Department of Biotechnology, Faculty of Natural Sciences, Jamia Millia Islamia, New Delhi 110025, India; (S.A.); (A.S.); (S.A.)
- Correspondence: (R.D.); (M.A.S.); Tel.: +91-817-887-5779 (R.D.); +91-995-378-6440 (M.A.S.)
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Abstract
The role of biomarkers for detection of sepsis has come a long way. Molecular biomarkers are taking front stage at present, but machine learning and other computational measures using bigdata sets are promising. Clinical research in sepsis is hampered by lack of specificity of the diagnosis; sepsis is a syndrome with no uniformly agreed definition. This lack of diagnostic precision means there is no gold standard for this diagnosis. The final conclusion is expert opinion, which is not bad but not perfect. Perhaps machine learning will displace expert opinion as the final and most accurate definition for sepsis.
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Affiliation(s)
- Steven M Opal
- Infectious Disease Division, Alpert Medical School of Brown University, Ocean State Clinical Coordinating Center at Rhode Island Hospital, 1 Virginia Avenue Suite 105, Providence, RI 02905, USA.
| | - Xavier Wittebole
- Critical Care Department, (Pr Laterre), Cliniques Universitaires Saint-Luc, Avenue Hippocrate 10, 1200 Brussels, Belgium
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Miller RR, Lopansri BK, Burke JP, Levy M, Opal S, Rothman RE, D'Alessio FR, Sidhaye VK, Aggarwal NR, Balk R, Greenberg JA, Yoder M, Patel G, Gilbert E, Afshar M, Parada JP, Martin GS, Esper AM, Kempker JA, Narasimhan M, Tsegaye A, Hahn S, Mayo P, van der Poll T, Schultz MJ, Scicluna BP, Klein Klouwenberg P, Rapisarda A, Seldon TA, McHugh LC, Yager TD, Cermelli S, Sampson D, Rothwell V, Newman R, Bhide S, Fox BA, Kirk JT, Navalkar K, Davis RF, Brandon RA, Brandon RB. Validation of a Host Response Assay, SeptiCyte LAB, for Discriminating Sepsis from Systemic Inflammatory Response Syndrome in the ICU. Am J Respir Crit Care Med 2019; 198:903-913. [PMID: 29624409 DOI: 10.1164/rccm.201712-2472oc] [Citation(s) in RCA: 73] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022] Open
Abstract
RATIONALE A molecular test to distinguish between sepsis and systemic inflammation of noninfectious etiology could potentially have clinical utility. OBJECTIVES This study evaluated the diagnostic performance of a molecular host response assay (SeptiCyte LAB) designed to distinguish between sepsis and noninfectious systemic inflammation in critically ill adults. METHODS The study employed a prospective, observational, noninterventional design and recruited a heterogeneous cohort of adult critical care patients from seven sites in the United States (n = 249). An additional group of 198 patients, recruited in the large MARS (Molecular Diagnosis and Risk Stratification of Sepsis) consortium trial in the Netherlands ( www.clinicaltrials.gov identifier NCT01905033), was also tested and analyzed, making a grand total of 447 patients in our study. The performance of SeptiCyte LAB was compared with retrospective physician diagnosis by a panel of three experts. MEASUREMENTS AND MAIN RESULTS In receiver operating characteristic curve analysis, SeptiCyte LAB had an estimated area under the curve of 0.82-0.89 for discriminating sepsis from noninfectious systemic inflammation. The relative likelihood of sepsis versus noninfectious systemic inflammation was found to increase with increasing test score (range, 0-10). In a forward logistic regression analysis, the diagnostic performance of the assay was improved only marginally when used in combination with other clinical and laboratory variables, including procalcitonin. The performance of the assay was not significantly affected by demographic variables, including age, sex, or race/ethnicity. CONCLUSIONS SeptiCyte LAB appears to be a promising diagnostic tool to complement physician assessment of infection likelihood in critically ill adult patients with systemic inflammation. Clinical trial registered with www.clinicaltrials.gov (NCT01905033 and NCT02127502).
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Affiliation(s)
- Russell R Miller
- 1 Intermountain Medical Center, Murray, Utah.,2 University of Utah School of Medicine, Salt Lake City, Utah
| | - Bert K Lopansri
- 1 Intermountain Medical Center, Murray, Utah.,2 University of Utah School of Medicine, Salt Lake City, Utah
| | - John P Burke
- 1 Intermountain Medical Center, Murray, Utah.,2 University of Utah School of Medicine, Salt Lake City, Utah
| | | | - Steven Opal
- 3 Brown University, Providence, Rhode Island
| | | | | | | | - Neil R Aggarwal
- 4 Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - Robert Balk
- 5 Rush Medical College and Rush University Medical Center, Chicago, Illinois
| | - Jared A Greenberg
- 5 Rush Medical College and Rush University Medical Center, Chicago, Illinois
| | - Mark Yoder
- 5 Rush Medical College and Rush University Medical Center, Chicago, Illinois
| | - Gourang Patel
- 5 Rush Medical College and Rush University Medical Center, Chicago, Illinois
| | - Emily Gilbert
- 6 Loyola University Medical Center, Maywood, Illinois
| | - Majid Afshar
- 6 Loyola University Medical Center, Maywood, Illinois
| | | | - Greg S Martin
- 7 Grady Memorial Hospital and Emory University School of Medicine, Atlanta, Georgia
| | - Annette M Esper
- 7 Grady Memorial Hospital and Emory University School of Medicine, Atlanta, Georgia
| | - Jordan A Kempker
- 7 Grady Memorial Hospital and Emory University School of Medicine, Atlanta, Georgia
| | | | | | - Stella Hahn
- 8 Northwell Healthcare, New Hyde Park, New York
| | - Paul Mayo
- 8 Northwell Healthcare, New Hyde Park, New York
| | | | | | | | - Peter Klein Klouwenberg
- 10 Department of Intensive Care, University Medical Center Utrecht, Utrecht, the Netherlands; and
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Mohammed A, Cui Y, Mas VR, Kamaleswaran R. Differential gene expression analysis reveals novel genes and pathways in pediatric septic shock patients. Sci Rep 2019; 9:11270. [PMID: 31375728 PMCID: PMC6677896 DOI: 10.1038/s41598-019-47703-6] [Citation(s) in RCA: 20] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 07/12/2019] [Indexed: 12/20/2022] Open
Abstract
Septic shock is a devastating health condition caused by uncontrolled sepsis. Advancements in high-throughput sequencing techniques have increased the number of potential genetic biomarkers under review. Multiple genetic markers and functional pathways play a part in development and progression of pediatric septic shock. We identified 53 differentially expressed pediatric septic shock biomarkers using gene expression data sampled from 181 patients admitted to the pediatric intensive care unit within the first 24 hours of their admission. The gene expression signatures showed discriminatory power between pediatric septic shock survivors and nonsurvivor types. Using functional enrichment analysis of differentially expressed genes, we validated the known genes and pathways in septic shock and identified the unexplored septic shock-related genes and functional groups. Differential gene expression analysis revealed the genes involved in the immune response, chemokine-mediated signaling, neutrophil chemotaxis, and chemokine activity and distinguished the septic shock survivor from non-survivor. The identification of the septic shock gene biomarkers may facilitate in septic shock diagnosis, treatment, and prognosis.
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Affiliation(s)
- Akram Mohammed
- University of Tennessee Health Science Center, Memphis, TN, USA
| | - Yan Cui
- University of Tennessee Health Science Center, Memphis, TN, USA
| | - Valeria R Mas
- University of Tennessee Health Science Center, Memphis, TN, USA
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Bloom AS, Suchindran S, Steinbrink J, McClain MT. Utility of predictive tools for risk stratification of elderly individuals with all-cause acute respiratory infection. Infection 2019; 47:617-627. [PMID: 30929142 DOI: 10.1007/s15010-019-01299-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/07/2018] [Accepted: 03/18/2019] [Indexed: 10/27/2022]
Abstract
PURPOSE A number of scoring tools have been developed to predict illness severity and patient outcome for proven pneumonia, however, less is known about the utility of clinical prediction scores for all-cause acute respiratory infection (ARI), especially in elderly subjects who are at increased risk of poor outcomes. METHODS We retrospectively analyzed risk factors and outcomes of individuals ≥ 60 years of age presenting to the emergency department with a clinical diagnosis of ARI. RESULTS Of 276 individuals in the study, 40 had proven viral infection and 52 proven bacterial infection, but 184 patients with clinically adjudicated ARI (67%) remained without a proven microbial etiology despite extensive clinical (and expanded research) workup. Patients who were older, had multiple comorbidities, or who had proven bacterial infection were more likely to require hospital and ICU admission. We identified a novel model based on 11 demographic and clinical variables that were significant risk factors for ICU admission or mortality in elderly subjects with all-cause ARI. As comparators, a modified PORT score was found to correlate more closely with all-cause ARI severity than a modified CURB-65 score (r, 0.54, 0.39). Interestingly, modified Jackson symptom scores were found to inversely correlate with severity (r, - 0.34) but show potential for differentiating viral and bacterial etiologies. CONCLUSIONS Modified PORT, CURB-65, Jackson symptom scores, and a novel ARI scoring tool presented herein all offer predictive ability for all-cause ARI in elderly subjects. Such broadly applicable scoring metrics have the potential to assist in treatment and triage decisions at the point of care.
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Affiliation(s)
| | - Sunil Suchindran
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA
| | - Julie Steinbrink
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA
| | - Micah T McClain
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, USA.
- Division of Infectious Diseases, Duke University Medical Center, Durham, NC, USA.
- Durham Veteran's Affairs Medical Center, Durham, NC, USA.
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Hu Y, Zhong W, Chen M, Zhang Q. Identifying crucial genes for prognosis in septic patients: Gene integration study based on PRISMA guidelines. Medicine (Baltimore) 2019; 98:e16807. [PMID: 31415393 PMCID: PMC6831352 DOI: 10.1097/md.0000000000016807] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/01/2023] Open
Abstract
BACKGROUND Sepsis is a serious clinical condition with a poor prognosis, despite improvements in diagnosis and treatment.Therefore, novel biomarkers are necessary that can help with estimating prognosis and improving clinical outcomes of patients with sepsis. METHODS The gene expression profiles GSE54514 and GSE63042 were downloaded from the GEO database. DEGs were screened by t test after logarithmization of raw data; then, the common DEGs between the 2 gene expression profiles were identified by up-regulation and down-regulation intersection. The DEGs were analyzed using bioinformatics, and a protein-protein interaction (PPI) survival network was constructed using STRING. Survival curves were constructed to explore the relationship between core genes and the prognosis of sepsis patients based on GSE54514 data. RESULTS A total of 688 common DEGs were identified between survivors and non-survivors of sepsis, and 96 genes were involved in survival networks. The crucial genes Signal transducer and activator of transcription 5A (STAT5A), CCAAT/enhancer-binding protein beta (CEBPB), Myc proto-oncogene protein (MYC), and REL-associated protein (RELA) were identified and showed increased expression in sepsis survivors. These crucial genes had a positive correlation with patients' survival time according to the survival analysis. CONCLUSIONS Our findings indicate that the genes STAT5A, CEBPB, MYC, and RELA may be important in predicting the prognosis of sepsis patients.
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Affiliation(s)
| | | | | | - Qian Zhang
- Department of Infectious Diseases, The Affiliated Hospital of Southwest Medical University, Lu Zhou, Si Chuan, China
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Mallet F, Perret M, Tran T, Meunier B, Guichard A, Tabone O, Mommert M, Brengel-Pesce K, Venet F, Pachot A, Monneret G, Reynier F, Védrine C, Leissner P, Moucadel V, Lepape A, Textoris J. Early herpes and TTV DNAemia in septic shock patients: a pilot study. Intensive Care Med Exp 2019; 7:28. [PMID: 31104220 PMCID: PMC6525672 DOI: 10.1186/s40635-019-0256-z] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Accepted: 05/03/2019] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Septic shock patients exhibit an increased incidence of viral reactivation. Precise timing of such reactivation-as an early marker of immune suppression, or as a consequence of the later-is not known precisely. Here, using a fully designed nucleic acid extraction automated procedure together with tailored commercial PCR kits, we focused on the description of early reactivation within the first week of ICU admission of several herpes viruses and Torque Teno virus (TTV) in 98 septic shock patients. RESULTS Most of septic shock patients had at least one viremia event during the first week (88%). TTV and herpesviruses were detected in 56% and 53% of septic shock patient, respectively. The two most frequent herpesviruses detected within the first week were EBV (35%) and HSV1 (26%). Different kinetic were observed among herpesviruses, faster for EBV and HSV1 than for CMV and HHV6. Although no association was found between herpes viremia and secondary infections, patients with herpesviridae-related viremia were more severe, e.g., higher SOFA scores and plasma lactate levels. While reactivating only 1 virus was not associated with mortality, patients with multiple viremia events had higher ICU mortality. Surprisingly, EBV + TTV early reactivation seemed associated with a lower D28 mortality. No clear association was observed between viremia and immune biomarkers. CONCLUSION Applying a semi-automated process of viral DNAemia determination to this cohort of 98 patients with septic shock, we observed that the number of patients with positive viremia increased during the first week in the ICU. Of note, there was no improvement in predicting the outcome when using viremia status. Nevertheless, this pilot study, introducing standardized procedures from extraction to detection, provides the basis for future standardized diagnostic criteria. A prospective longitudinal clinical study using these procedures will enable determination of whether such viremia is due to a lack of a latent virus control by the immune system or a true clinical viral infection.
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Affiliation(s)
- François Mallet
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France. .,Joint research unit, Hospice Civils de Lyon, bioMérieux, Centre Hospitalier Lyon Sud, 165 Chemin du Grand Revoyet, 69310, Pierre-Benite, France.
| | - Magali Perret
- BIOASTER Technology Research Institute, Lyon, France
| | - Trang Tran
- BIOASTER Technology Research Institute, Lyon, France
| | - Boris Meunier
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France.,Soladis, Lyon, France
| | - Audrey Guichard
- Joint research unit, Hospice Civils de Lyon, bioMérieux, Centre Hospitalier Lyon Sud, 165 Chemin du Grand Revoyet, 69310, Pierre-Benite, France
| | - Olivier Tabone
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France
| | - Marine Mommert
- Joint research unit, Hospice Civils de Lyon, bioMérieux, Centre Hospitalier Lyon Sud, 165 Chemin du Grand Revoyet, 69310, Pierre-Benite, France
| | - Karen Brengel-Pesce
- Joint research unit, Hospice Civils de Lyon, bioMérieux, Centre Hospitalier Lyon Sud, 165 Chemin du Grand Revoyet, 69310, Pierre-Benite, France
| | - Fabienne Venet
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France.,Hospices Civils de Lyon, Immunology Laboratory, Groupement Hospitalier Edouard Herriot, Lyon, France
| | - Alexandre Pachot
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France
| | - Guillaume Monneret
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France.,Hospices Civils de Lyon, Immunology Laboratory, Groupement Hospitalier Edouard Herriot, Lyon, France
| | | | | | | | - Virginie Moucadel
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France
| | - Alain Lepape
- Intensive Care Unit, Centre Hospitalier Lyon Sud, Hospices Civils de Lyon, Pierre Bénite, France.,Emerging Pathogens Laboratory, Epidemiology and International Health, International Center for Infectiology Research (CIRI), Lyon, France.,Hospices Civils de Lyon, bioMérieux Joint Research Unit, Groupement Hospitalier Edouard Herriot, Lyon, France
| | - Julien Textoris
- EA 7426 Pathophysiology of Injury-induced Immunosuppression, University of Lyon1-Hospices Civils de Lyon-bioMérieux, Hôpital Edouard Herriot, 5 Place d'Arsonval, 69437, Lyon Cedex 3, France. .,Hospices Civils de Lyon, Department of Anaesthesiology and Critical Care Medicine, Groupement Hospitalier Edouard Herriot, Université Claude Bernard Lyon 1, Lyon, France.
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Coulibaly A, Velásquez SY, Sticht C, Figueiredo AS, Himmelhan BS, Schulte J, Sturm T, Centner FS, Schöttler JJ, Thiel M, Lindner HA. AKIRIN1: A Potential New Reference Gene in Human Natural Killer Cells and Granulocytes in Sepsis. Int J Mol Sci 2019; 20:ijms20092290. [PMID: 31075840 PMCID: PMC6539838 DOI: 10.3390/ijms20092290] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2019] [Revised: 04/27/2019] [Accepted: 05/07/2019] [Indexed: 12/11/2022] Open
Abstract
Timely and reliable distinction of sepsis from non-infectious systemic inflammatory response syndrome (SIRS) supports adequate antimicrobial therapy and saves lives but is clinically challenging. Blood transcriptional profiling promises to deliver insights into the pathomechanisms of SIRS and sepsis and to accelerate the discovery of urgently sought sepsis biomarkers. However, suitable reference genes for normalizing gene expression in these disease conditions are lacking. In addition, variability in blood leukocyte subtype composition complicates gene profile interpretation. Here, we aimed to identify potential reference genes in natural killer (NK) cells and granulocytes from patients with SIRS and sepsis on intensive care unit (ICU) admission. Discovery by a two-step probabilistic selection from microarray data followed by validation through branched DNA assays in independent patients revealed several candidate reference genes in NK cells including AKIRIN1, PPP6R3, TAX1BP1, and ADRBK1. Initially, no candidate genes could be validated in patient granulocytes. However, we determined highly similar AKIRIN1 expression also in SIRS and sepsis granulocytes and no change by in vitro LPS challenge in granulocytes from healthy donors. Inspection of external neutrophil transcriptome datasets further support unchanged AKIRIN1 expression in human systemic inflammation. As a potential new reference gene in NK cells and granulocytes in infectious and inflammatory diseases, AKIRIN1 may improve our pathomechanistic understanding of SIRS and sepsis and help identifying new sepsis biomarkers.
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Affiliation(s)
- Anna Coulibaly
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Sonia Y Velásquez
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Carsten Sticht
- Medical Research Center, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Ana Sofia Figueiredo
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Bianca S Himmelhan
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Jutta Schulte
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Timo Sturm
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Franz-Simon Centner
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Jochen J Schöttler
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Manfred Thiel
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
| | - Holger A Lindner
- Department of Anesthesiology and Surgical Intensive Care Medicine, University Medical Center Mannheim, Medical Faculty Mannheim, Heidelberg University, 68167 Mannheim, Germany.
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Verboom DM, Koster-Brouwer ME, Varkila MRJ, Bonten MJM, Cremer OL. Profile of the SeptiCyte™ LAB gene expression assay to diagnose infection in critically ill patients. Expert Rev Mol Diagn 2019; 19:95-108. [PMID: 30623693 DOI: 10.1080/14737159.2019.1567333] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
Sepsis is a severe and frequently occurring clinical syndrome, caused by the inflammatory response to infections. Recent studies on the human transcriptome during sepsis have yielded several gene-expression assays that might assist physicians during clinical assessment of patients suspected of sepsis. SeptiCyte™ LAB (Immunexpress, Seattle, WA) is the first gene expression assay that was cleared by the FDA in the United States to distinguish infectious from non-infectious causes of systemic inflammation in critically ill patients. The test consists of the simultaneous amplification of four RNA transcripts (CEACAM4, LAMP1, PLAC8, and PLA2G7) in whole blood using a quantitative real-time PCR reaction. This review provides an overview of the challenges in the diagnosis of sepsis, the development of gene expression signatures, and a detailed description of available clinical performance studies evaluating SeptiCyte™ LAB.
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Affiliation(s)
- D M Verboom
- a Julius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht , The Netherlands.,b Department of Intensive Care , University Medical Center Utrecht , Utrecht , The Netherlands
| | - M E Koster-Brouwer
- a Julius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht , The Netherlands.,b Department of Intensive Care , University Medical Center Utrecht , Utrecht , The Netherlands
| | - M R J Varkila
- a Julius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht , The Netherlands.,b Department of Intensive Care , University Medical Center Utrecht , Utrecht , The Netherlands
| | - M J M Bonten
- a Julius Center for Health Sciences and Primary Care , University Medical Center Utrecht , Utrecht , The Netherlands.,c Department of Medical Microbiology , University Medical Center Utrecht , Utrecht , The Netherlands
| | - O L Cremer
- b Department of Intensive Care , University Medical Center Utrecht , Utrecht , The Netherlands
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Barcella M, Bollen Pinto B, Braga D, D'Avila F, Tagliaferri F, Cazalis MA, Monneret G, Herpain A, Bendjelid K, Barlassina C. Identification of a transcriptome profile associated with improvement of organ function in septic shock patients after early supportive therapy. CRITICAL CARE : THE OFFICIAL JOURNAL OF THE CRITICAL CARE FORUM 2018; 22:312. [PMID: 30463588 PMCID: PMC6249814 DOI: 10.1186/s13054-018-2242-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Accepted: 10/16/2018] [Indexed: 12/24/2022]
Abstract
Background Septic shock is the most severe complication of sepsis and this syndrome is associated with high mortality. Treatment of septic shock remains largely supportive of hemodynamics and tissue perfusion. Early changes in organ function assessed by the Sequential Organ Function Assessment (SOFA) score are highly predictive of the outcome. However, the individual patient’s response to supportive therapy is very heterogeneous, and the mechanisms underlying this variable response remain elusive. The aim of the study was to investigate the transcriptome of whole blood in septic shock patients with different responses to early supportive hemodynamic therapy assessed by changes in SOFA scores within the first 48 h from intensive care unit (ICU) admission. Methods We performed whole blood RNA sequencing in 31 patients: 17 classified as responders (R) and 14 as non-responders (NR). Gene expression was investigated at ICU admission (time point 1, or T1), comparing R with NR [padj < 0.01; Benjamini–Hochberg (BH)] and over time from T1 to T2 (48 h later) in R and NR independently (paired analysis, padj < 0.01; BH). Then the differences in gene expression trends over time were evaluated (Mann–Whitney, P <0.01). To identify enriched biological processes, we performed an over-representation analysis based on a right-sided hypergeometric test with Bonferroni step-down as multiple testing correction (padj < 0.05). Results At ICU admission, we did not identify differentially expressed genes (DEGs) between the two groups. In the transition from T1 to T2, the activation of genes involved in T cell–mediated immunity, granulocyte and natural killer (NK) cell functions, and pathogen lipid clearance was noted in the R group. Genes involved in acute inflammation were downregulated in both groups. Conclusions Within the limits of a small sample size, our results could suggest that early activation of genes of the adaptive immune response is associated with an improvement in organ function. Electronic supplementary material The online version of this article (10.1186/s13054-018-2242-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Matteo Barcella
- Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via Rudini 8, 20142, Milan, Italy.,Fondazione Filarete, Viale Ortles 22/4, 20139, Milan, Italy
| | - Bernardo Bollen Pinto
- Department of Anaesthesia, Pharmacology and Intensive Care, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva, 1205, Switzerland
| | - Daniele Braga
- Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via Rudini 8, 20142, Milan, Italy.,Fondazione Filarete, Viale Ortles 22/4, 20139, Milan, Italy
| | - Francesca D'Avila
- Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via Rudini 8, 20142, Milan, Italy.,Fondazione Filarete, Viale Ortles 22/4, 20139, Milan, Italy
| | - Federico Tagliaferri
- Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via Rudini 8, 20142, Milan, Italy.,Fondazione Filarete, Viale Ortles 22/4, 20139, Milan, Italy
| | - Marie-Angelique Cazalis
- Laboratoire Commun de Recherche HCL-bioMérieux, Hôpital Edouard Herriot, 376 Chemin de l'Orme, 6928 Marcy-l'Etoile, Lyon, France
| | - Guillaume Monneret
- Hospices Civils de Lyon, Hôpital Edouard Herriot, Laboratoire d'Immunologie, 5 Place d'Arsonval, 69437, Lyon cedex 03, France
| | - Antoine Herpain
- Department of Intensive Care, Hospital Erasme, Hospital, Université Libre de Bruxelles, Route de Lennik 808, Brussels, 1070, Belgium
| | - Karim Bendjelid
- Department of Anaesthesia, Pharmacology and Intensive Care, Geneva University Hospitals, Rue Gabrielle-Perret-Gentil 4, Geneva, 1205, Switzerland
| | - Cristina Barlassina
- Dipartimento di Scienze della Salute, Università degli Studi di Milano, Via Rudini 8, 20142, Milan, Italy. .,Fondazione Filarete, Viale Ortles 22/4, 20139, Milan, Italy.
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LINCS L1000 dataset-based repositioning of CGP-60474 as a highly potent anti-endotoxemic agent. Sci Rep 2018; 8:14969. [PMID: 30297806 PMCID: PMC6175892 DOI: 10.1038/s41598-018-33039-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 09/12/2018] [Indexed: 12/11/2022] Open
Abstract
Sepsis is one of the most common clinical syndromes that causes death and disability. Although many studies have developed drugs for sepsis treatment, none have decreased the mortality rate. The aim of this study was to identify a novel treatment option for sepsis using the library of integrated network-based cellular signatures (LINCS) L1000 perturbation dataset based on an in vitro and in vivo sepsis model. Sepsis-related microarray studies of early-stage inflammatory processes in patients and innate immune cells were collected from the Gene Expression Omnibus (GEO) data repository and used for candidate drug selection based on the LINCS L1000 perturbation dataset. The anti-inflammatory effects of the selected candidate drugs were analyzed using activated macrophage cell lines. CGP-60474, an inhibitor of cyclin-dependent kinase, was the most potent drug. It alleviated tumor necrosis factor-α (TNF-α) and interleukin-6 (IL-6) in activated macrophages by downregulating the NF-κB activity, and it reduced the mortality rate in LPS induced endotoxemia mice. This study shows that CGP-60474 could be a potential therapeutic candidate to attenuate the endotoxemic process. Additionally, the virtual screening strategy using the LINCS L1000 perturbation dataset could be a cost and time effective tool in the early stages of drug development.
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Langley RJ, Wong HR. Early Diagnosis of Sepsis: Is an Integrated Omics Approach the Way Forward? Mol Diagn Ther 2018. [PMID: 28624903 DOI: 10.1007/s40291-017-0282-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Sepsis remains one of the leading causes of death in the USA and it is expected to get worse as the population ages. Moreover, the standard of care, which recommends aggressive treatment with appropriate antibiotics, has led to an increase in multiple drug-resistant organisms. There is a dire need for the development of new antibiotics, improved antibiotic stewardship, and therapies that treat the host response. Development of new sepsis therapeutics has been a disappointment as no drugs are currently approved to treat the various complications from sepsis. Much of the failure has been blamed on animal models that do not accurately reflect the course of the disease. However, recent improvements in metabolomic, transcriptomic, genomic, and proteomic platforms have allowed for a broad-spectrum look at molecular changes in the host response using clinical samples. Integration of these multi-omic datasets allows researchers to perform systems biology approaches to identify novel pathophysiology of the disease. In this review, we highlight what is currently known about sepsis and how integrative omics has identified new diagnostic and predictive models of sepsis as well as novel mechanisms. These changes may improve patient care as well as guide future preclinical analysis of sepsis.
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Affiliation(s)
- Raymond J Langley
- Department of Pharmacology, University of South Alabama, Mobile, AL, USA
| | - Hector R Wong
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, 3333 Burnet Avenue, Cincinnati, OH, 45229, USA. .,Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, USA.
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Lydon EC, Ko ER, Tsalik EL. The host response as a tool for infectious disease diagnosis and management. Expert Rev Mol Diagn 2018; 18:723-738. [PMID: 29939801 DOI: 10.1080/14737159.2018.1493378] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
INTRODUCTION A century of advances in infectious disease diagnosis and treatment changed the face of medicine. However, challenges continue to develop including multi-drug resistance, globalization that increases pandemic risks, and high mortality from severe infections. These challenges can be mitigated through improved diagnostics, and over the past decade, there has been a particular focus on the host response. Since this article was originally published in 2015, there have been significant developments in the field of host response diagnostics, warranting this updated review. Areas Covered: This review begins by discussing developments in single biomarkers and pauci-analyte biomarker panels. It then delves into 'omics, an area where there has been truly exciting progress. Specifically, progress has been made in sepsis diagnosis and prognosis; differentiating viral, bacterial, and fungal pathogen classes; pre-symptomatic diagnosis; and understanding disease-specific diagnostic challenges in tuberculosis, Lyme disease, and Ebola. Expert Commentary: As 'omics have become faster, more precise, and less expensive, the door has been opened for academic, industry, and government efforts to develop host-based infectious disease classifiers. While there are still obstacles to overcome, the chasm separating these scientific advances from the patient's bedside is shrinking.
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Affiliation(s)
- Emily C Lydon
- a Duke University School of Medicine , Duke University , Durham , NC , USA
| | - Emily R Ko
- b Duke Center for Applied Genomics & Precision Medicine, Department of Medicine , Duke University , Durham , NC , USA.,c Duke Regional Hospital, Department of Medicine , Duke University , Durham , NC , USA
| | - Ephraim L Tsalik
- b Duke Center for Applied Genomics & Precision Medicine, Department of Medicine , Duke University , Durham , NC , USA.,d Division of Infectious Diseases & International Health, Department of Medicine , Duke University , Durham , NC , USA.,e Emergency Medicine Service , Durham Veterans Affairs Health Care System , Durham , NC , USA
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50
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Sweeney TE, Perumal TM, Henao R, Nichols M, Howrylak JA, Choi AM, Bermejo-Martin JF, Almansa R, Tamayo E, Davenport EE, Burnham KL, Hinds CJ, Knight JC, Woods CW, Kingsmore SF, Ginsburg GS, Wong HR, Parnell GP, Tang B, Moldawer LL, Moore FE, Omberg L, Khatri P, Tsalik EL, Mangravite LM, Langley RJ. A community approach to mortality prediction in sepsis via gene expression analysis. Nat Commun 2018; 9:694. [PMID: 29449546 PMCID: PMC5814463 DOI: 10.1038/s41467-018-03078-2] [Citation(s) in RCA: 126] [Impact Index Per Article: 21.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2017] [Accepted: 01/18/2018] [Indexed: 12/27/2022] Open
Abstract
Improved risk stratification and prognosis prediction in sepsis is a critical unmet need. Clinical severity scores and available assays such as blood lactate reflect global illness severity with suboptimal performance, and do not specifically reveal the underlying dysregulation of sepsis. Here, we present prognostic models for 30-day mortality generated independently by three scientific groups by using 12 discovery cohorts containing transcriptomic data collected from primarily community-onset sepsis patients. Predictive performance is validated in five cohorts of community-onset sepsis patients in which the models show summary AUROCs ranging from 0.765-0.89. Similar performance is observed in four cohorts of hospital-acquired sepsis. Combining the new gene-expression-based prognostic models with prior clinical severity scores leads to significant improvement in prediction of 30-day mortality as measured via AUROC and net reclassification improvement index These models provide an opportunity to develop molecular bedside tests that may improve risk stratification and mortality prediction in patients with sepsis.
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Affiliation(s)
- Timothy E Sweeney
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Division of Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Inflammatix Inc., Burlingame, CA, 94010, USA
| | | | - Ricardo Henao
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27708, USA
- Department of Electrical and Computer Engineering, Duke University, Durham, NC, 27708, USA
| | - Marshall Nichols
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27708, USA
| | - Judith A Howrylak
- Division of Pulmonary and Critical Care Medicine, Penn State Milton S. Hershey Medical Center, Hershey, PA, 17033, USA
| | - Augustine M Choi
- Department of Medicine, Cornell Medical Center, New York, NY, 10065, USA
| | | | - Raquel Almansa
- Hospital Clínico Universitario de Valladolid/IECSCYL, Valladolid, 47005, Spain
| | - Eduardo Tamayo
- Hospital Clínico Universitario de Valladolid/IECSCYL, Valladolid, 47005, Spain
| | - Emma E Davenport
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
- Partners Center for Personalized Genetic Medicine, Boston, MA, 02115, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, 02142, USA
| | - Katie L Burnham
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Charles J Hinds
- William Harvey Research Institute, Barts and The London School of Medicine, Queen Mary University, London, EC1M 6BQ, UK
| | - Julian C Knight
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, OX3 7BN, UK
| | - Christopher W Woods
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27708, USA
- Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC, 27710, USA
- Durham Veteran's Affairs Health Care System, Durham, NC, 27705, USA
| | | | - Geoffrey S Ginsburg
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27708, USA
| | - Hector R Wong
- Division of Critical Care Medicine, Cincinnati Children's Hospital Medical Center and Cincinnati Children's Research Foundation, Cincinnati, OH, 45223, USA
- Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, OH, 45267, USA
| | - Grant P Parnell
- Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Westmead, NSW, 2145, Australia
| | - Benjamin Tang
- Centre for Immunology and Allergy Research, Westmead Institute for Medical Research, Westmead, NSW, 2145, Australia
- Department of Intensive Care Medicine, Nepean Hospital, Sydney, Australia, Penrith, NSW, 2751, Australia
- Nepean Genomic Research Group, Nepean Clinical School, University of Sydney, Penrith, NSW, 2751, Australia
- Marie Bashir Institute for Infectious Diseases and Biosecurity, Westmead, NSW, 2145, Australia
| | - Lyle L Moldawer
- Department of Surgery, University of Florida College of Medicine, Gainesville, FL, 32610, USA
| | - Frederick E Moore
- Department of Surgery, University of Florida College of Medicine, Gainesville, FL, 32610, USA
| | | | - Purvesh Khatri
- Stanford Institute for Immunity, Transplantation and Infection, Stanford University School of Medicine, Stanford, CA, 94305, USA
- Division of Biomedical Informatics Research, Department of Medicine, Stanford University School of Medicine, Stanford, CA, 94305, USA
| | - Ephraim L Tsalik
- Center for Applied Genomics and Precision Medicine, Department of Medicine, Duke University, Durham, NC, 27708, USA
- Division of Infectious Diseases and International Health, Department of Medicine, Duke University, Durham, NC, 27710, USA
- Durham Veteran's Affairs Health Care System, Durham, NC, 27705, USA
| | | | - Raymond J Langley
- Department of Pharmacology, University of South Alabama, Mobile, AL, 36688, USA.
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