1
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Zhang SS, Zhao Z, Zhang WX, Wu R, Li F, Yang H, Zhang Q, Wei TT, Xi J, Zhou Y, Wang T, Du J, Huang N, Ge Q, Lu QB. Lipidome is a valuable tool for the severity prediction of coronavirus disease 2019. Front Immunol 2024; 15:1337208. [PMID: 38799463 PMCID: PMC11116732 DOI: 10.3389/fimmu.2024.1337208] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2023] [Accepted: 04/24/2024] [Indexed: 05/29/2024] Open
Abstract
Objective To describe the lipid metabolic profile of different patients with coronavirus disease 2019 (COVID-19) and contribute new evidence on the progression and severity prediction of COVID-19. Methods This case-control study was conducted in Peking University Third Hospital, China. The laboratory-confirmed COVID-19 patients aged ≥18 years old and diagnosed as pneumonia from December 2022 to January 2023 were included. Serum lipids were detected. The discrimination ability was calculated with the area under the curve (AUC). A random forest (RF) model was conducted to determine the significance of different lipids. Results Totally, 44 COVID-19 patients were enrolled with 16 mild and 28 severe patients. The top 5 super classes were triacylglycerols (TAG, 55.9%), phosphatidylethanolamines (PE, 10.9%), phosphatidylcholines (PC, 6.8%), diacylglycerols (DAG, 5.9%) and free fatty acids (FFA, 3.6%) among the 778 detected lipids from the serum of COVID-19 patients. Certain lipids, especially lysophosphatidylcholines (LPCs), turned to have significant correlations with certain immune/cytokine indexes. Reduced level of LPC 20:0 was observed in severe patients particularly in acute stage. The AUC of LPC 20:0 reached 0.940 in discriminating mild and severe patients and 0.807 in discriminating acute and recovery stages in the severe patients. The results of RF models also suggested the significance of LPCs in predicting the severity and progression of COVID-19. Conclusion Lipids probably have the potential to differentiate and forecast the severity, progression, and clinical outcomes of COVID-19 patients, with implications for immune/inflammatory responses. LPC 20:0 might be a potential target in predicting the progression and outcome and the treatment of COVID-19.
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Affiliation(s)
- Shan-Shan Zhang
- Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Zhiling Zhao
- Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China
| | - Wan-Xue Zhang
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Rui Wu
- Pulmonary and Critical Care Medicine, Peking University Third Hospital, Beijing, China
| | - Fei Li
- Department of General Surgery, Peking University Third Hospital, Beijing, China
| | - Han Yang
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
| | - Qiang Zhang
- Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China
| | - Ting-Ting Wei
- Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Jingjing Xi
- Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China
| | - Yiguo Zhou
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
| | - Tiehua Wang
- Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China
| | - Juan Du
- Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Ninghua Huang
- Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
| | - Qinggang Ge
- Department of Intensive Care Medicine, Peking University Third Hospital, Beijing, China
| | - Qing-Bin Lu
- Department of Laboratorial Science and Technology and Vaccine Research Center, School of Public Health, Peking University, Beijing, China
- Center for Infectious Disease and Policy Research and Global Health and Infectious Diseases Group, Peking University, Beijing, China
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China
- Department of Health Policy and Management, School of Public Health, Peking University, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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2
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Whiley L, Lawler NG, Zeng AX, Lee A, Chin ST, Bizkarguenaga M, Bruzzone C, Embade N, Wist J, Holmes E, Millet O, Nicholson JK, Gray N. Cross-Validation of Metabolic Phenotypes in SARS-CoV-2 Infected Subpopulations Using Targeted Liquid Chromatography-Mass Spectrometry (LC-MS). J Proteome Res 2024; 23:1313-1327. [PMID: 38484742 PMCID: PMC11002931 DOI: 10.1021/acs.jproteome.3c00797] [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: 11/17/2023] [Revised: 02/21/2024] [Accepted: 02/23/2024] [Indexed: 04/06/2024]
Abstract
To ensure biological validity in metabolic phenotyping, findings must be replicated in independent sample sets. Targeted workflows have long been heralded as ideal platforms for such validation due to their robust quantitative capability. We evaluated the capability of liquid chromatography-mass spectrometry (LC-MS) assays targeting organic acids and bile acids to validate metabolic phenotypes of SARS-CoV-2 infection. Two independent sample sets were collected: (1) Australia: plasma, SARS-CoV-2 positive (n = 20), noninfected healthy controls (n = 22) and COVID-19 disease-like symptoms but negative for SARS-CoV-2 infection (n = 22). (2) Spain: serum, SARS-CoV-2 positive (n = 33) and noninfected healthy controls (n = 39). Multivariate modeling using orthogonal projections to latent structures discriminant analyses (OPLS-DA) classified healthy controls from SARS-CoV-2 positive (Australia; R2 = 0.17, ROC-AUC = 1; Spain R2 = 0.20, ROC-AUC = 1). Univariate analyses revealed 23 significantly different (p < 0.05) metabolites between healthy controls and SARS-CoV-2 positive individuals across both cohorts. Significant metabolites revealed consistent perturbations in cellular energy metabolism (pyruvic acid, and 2-oxoglutaric acid), oxidative stress (lactic acid, 2-hydroxybutyric acid), hypoxia (2-hydroxyglutaric acid, 5-aminolevulinic acid), liver activity (primary bile acids), and host-gut microbial cometabolism (hippuric acid, phenylpropionic acid, indole-3-propionic acid). These data support targeted LC-MS metabolic phenotyping workflows for biological validation in independent sample sets.
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Affiliation(s)
- Luke Whiley
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute Harry
Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Nathan G. Lawler
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute Harry
Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Annie Xu Zeng
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Alex Lee
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Sung-Tong Chin
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Maider Bizkarguenaga
- Centro
de Investigación Cooperativa en Biociencias—CIC bioGUNE,
Precision Medicine and Metabolism Laboratory, Basque Research and
Technology Alliance, Bizkaia Science and
Technology Park, Building
800, 48160 Derio, Spain
| | - Chiara Bruzzone
- Centro
de Investigación Cooperativa en Biociencias—CIC bioGUNE,
Precision Medicine and Metabolism Laboratory, Basque Research and
Technology Alliance, Bizkaia Science and
Technology Park, Building
800, 48160 Derio, Spain
| | - Nieves Embade
- Centro
de Investigación Cooperativa en Biociencias—CIC bioGUNE,
Precision Medicine and Metabolism Laboratory, Basque Research and
Technology Alliance, Bizkaia Science and
Technology Park, Building
800, 48160 Derio, Spain
| | - Julien Wist
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute Harry
Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Chemistry
Department, Universidad del Valle, Cali 76001, Colombia
| | - Elaine Holmes
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute Harry
Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Department
of Metabolism Digestion and Reproduction, Faculty of Medicine, Imperial
College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K.
| | - Oscar Millet
- Centro
de Investigación Cooperativa en Biociencias—CIC bioGUNE,
Precision Medicine and Metabolism Laboratory, Basque Research and
Technology Alliance, Bizkaia Science and
Technology Park, Building
800, 48160 Derio, Spain
| | - Jeremy K. Nicholson
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute Harry
Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Institute
of Global Health Innovation, Faculty Building South Kensington Campus, Imperial College London, London SW7 2AZ, U.K.
| | - Nicola Gray
- Australian
National Phenome Centre, Health Futures Institute Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
- Centre
for Computational and Systems Medicine, Health Futures Institute Harry
Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
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3
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Sala S, Nitschke P, Masuda R, Gray N, Lawler NG, Wood JM, Buckler JN, Berezhnoy G, Bolaños J, Boughton BA, Lonati C, Rössler T, Singh Y, Wilson ID, Lodge S, Morillon AC, Loo RL, Hall D, Whiley L, Evans GB, Grove TL, Almo SC, Harris LD, Holmes E, Merle U, Trautwein C, Nicholson JK, Wist J. Integrative Molecular Structure Elucidation and Construction of an Extended Metabolic Pathway Associated with an Ancient Innate Immune Response in COVID-19 Patients. J Proteome Res 2024; 23:956-970. [PMID: 38310443 PMCID: PMC10913068 DOI: 10.1021/acs.jproteome.3c00654] [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: 10/06/2023] [Revised: 12/01/2023] [Accepted: 12/29/2023] [Indexed: 02/05/2024]
Abstract
We present compelling evidence for the existence of an extended innate viperin-dependent pathway, which provides crucial evidence for an adaptive response to viral agents, such as SARS-CoV-2. We show the in vivo biosynthesis of a family of novel endogenous cytosine metabolites with potential antiviral activities. Two-dimensional nuclear magnetic resonance (NMR) spectroscopy revealed a characteristic spin-system motif, indicating the presence of an extended panel of urinary metabolites during the acute viral replication phase. Mass spectrometry additionally enabled the characterization and quantification of the most abundant serum metabolites, showing the potential diagnostic value of the compounds for viral infections. In total, we unveiled ten nucleoside (cytosine- and uracil-based) analogue structures, eight of which were previously unknown in humans allowing us to propose a new extended viperin pathway for the innate production of antiviral compounds. The molecular structures of the nucleoside analogues and their correlation with an array of serum cytokines, including IFN-α2, IFN-γ, and IL-10, suggest an association with the viperin enzyme contributing to an ancient endogenous innate immune defense mechanism against viral infection.
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Affiliation(s)
- Samuele Sala
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Philipp Nitschke
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Reika Masuda
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Nicola Gray
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Nathan G. Lawler
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - James M. Wood
- Ferrier
Research Institute, Victoria University
of Wellington, Wellington 6012, New Zealand
- The
Maurice Wilkins Centre for Molecular Biodiscovef Wellington, Welry, The University of Auckland, Auckland 1010, New Zealand
| | - Joshua N. Buckler
- Ferrier
Research Institute, Victoria University
of Wellington, Wellington 6012, New Zealand
| | - Georgy Berezhnoy
- Department
of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, 72074 Tübingen, Germany
| | - Jose Bolaños
- Chemistry
Department, Universidad del Valle, Cali 76001, Colombia
| | - Berin A. Boughton
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Caterina Lonati
- Center
for Preclinical Research, Fondazione IRCCS
Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy
| | - Titus Rössler
- Department
of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, 72074 Tübingen, Germany
| | - Yogesh Singh
- Institute
of Medical Genetics and Applied Genomics, University Hospital Tübingen, 72074 Tübingen, Germany
| | - Ian D. Wilson
- Division
of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College, Burlington Danes Building, Du Cane Road, London W12 0NN, U.K.
| | - Samantha Lodge
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Aude-Claire Morillon
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Ruey Leng Loo
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Drew Hall
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Luke Whiley
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
| | - Gary B. Evans
- Ferrier
Research Institute, Victoria University
of Wellington, Wellington 6012, New Zealand
- The
Maurice Wilkins Centre for Molecular Biodiscovef Wellington, Welry, The University of Auckland, Auckland 1010, New Zealand
| | - Tyler L. Grove
- Department
of Biochemistry, Albert Einstein College
of Medicine, Bronx, New York 10461, United States
| | - Steven C. Almo
- Department
of Biochemistry, Albert Einstein College
of Medicine, Bronx, New York 10461, United States
| | - Lawrence D. Harris
- Ferrier
Research Institute, Victoria University
of Wellington, Wellington 6012, New Zealand
- The
Maurice Wilkins Centre for Molecular Biodiscovef Wellington, Welry, The University of Auckland, Auckland 1010, New Zealand
| | - Elaine Holmes
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
- Division
of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College, Burlington Danes Building, Du Cane Road, London W12 0NN, U.K.
| | - Uta Merle
- Department
of Internal Medicine IV, University Hospital
Heidelberg, 69120 Heidelberg, Germany
| | - Christoph Trautwein
- Department
of Preclinical Imaging and Radiopharmacy, Werner Siemens Imaging Center, University Hospital Tübingen, 72074 Tübingen, Germany
| | - Jeremy K. Nicholson
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
- Institute
of Global Health Innovation, Faculty of
Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K.
| | - Julien Wist
- The
Australian National Phenome Centre and Computational and Systems Medicine,
Health Futures Institute, Murdoch University, Harry Perkins Building, Perth WA6150, Australia
- Chemistry
Department, Universidad del Valle, Cali 76001, Colombia
- Faculty of Medicine, Department of Metabolism,
Digestion and Reproduction,
Division of Digestive Diseases at Imperial College, London SW7 2AZ, U.K.
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4
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Mohammed Y, Tran K, Carlsten C, Ryerson C, Wong A, Lee T, Cheng MP, Vinh DC, Lee TC, Winston BW, Sweet D, Boyd JH, Walley KR, Haljan G, McGeer A, Lamontagne F, Fowler R, Maslove D, Singer J, Patrick DM, Marshall JC, Murthy S, Jain F, Borchers CH, Goodlett DR, Levin A, Russell JA. Proteomic Evolution from Acute to Post-COVID-19 Conditions. J Proteome Res 2024; 23:52-70. [PMID: 38048423 PMCID: PMC10775146 DOI: 10.1021/acs.jproteome.3c00324] [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: 05/30/2023] [Revised: 10/30/2023] [Accepted: 11/13/2023] [Indexed: 12/06/2023]
Abstract
Many COVID-19 survivors have post-COVID-19 conditions, and females are at a higher risk. We sought to determine (1) how protein levels change from acute to post-COVID-19 conditions, (2) whether females have a plasma protein signature different from that of males, and (3) which biological pathways are associated with COVID-19 when compared to restrictive lung disease. We measured protein levels in 74 patients on the day of admission and at 3 and 6 months after diagnosis. We determined protein concentrations by multiple reaction monitoring (MRM) using a panel of 269 heavy-labeled peptides. The predicted forced vital capacity (FVC) and diffusing capacity of the lungs for carbon monoxide (DLCO) were measured by routine pulmonary function testing. Proteins associated with six key lipid-related pathways increased from admission to 3 and 6 months; conversely, proteins related to innate immune responses and vasoconstriction-related proteins decreased. Multiple biological functions were regulated differentially between females and males. Concentrations of eight proteins were associated with FVC, %, and they together had c-statistics of 0.751 (CI:0.732-0.779); similarly, concentrations of five proteins had c-statistics of 0.707 (CI:0.676-0.737) for DLCO, %. Lipid biology may drive evolution from acute to post-COVID-19 conditions, while activation of innate immunity and vascular regulation pathways decreased over that period. (ProteomeXchange identifiers: PXD041762, PXD029437).
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Affiliation(s)
- Yassene Mohammed
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
- UVic-Genome
BC Proteomics Centre, University of Victoria, Victoria V8Z 5N3, BC Canada
- Gerald
Bronfman Department of Oncology, McGill
University, Montreal, QC H3A 0G4, Canada
| | - Karen Tran
- Division
of General Internal Medicine, Vancouver
General Hospital and University of British Columbia, 2775 Laurel St, Vancouver, BC V5Z 1M9, Canada
| | - Chris Carlsten
- Division
of Respiratory Medicine, Vancouver General Hospital, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
| | - Christopher Ryerson
- Division
of Respiratory Medicine, Vancouver General Hospital, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
| | - Alyson Wong
- Division
of Respiratory Medicine, Vancouver General Hospital, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
| | - Terry Lee
- Centre for
Health Evaluation and Outcome Science (CHEOS), St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
| | - Matthew P. Cheng
- Division
of Infectious Diseases, Department of Medicine, McGill University Health Centre, Montreal, PQ H4A 3J1, Canada
| | - Donald C. Vinh
- Division
of Infectious Diseases, Department of Medicine, McGill University Health Centre, Montreal, PQ H4A 3J1, Canada
| | - Todd C. Lee
- Division
of Infectious Diseases, Department of Medicine, McGill University Health Centre, Montreal, PQ H4A 3J1, Canada
| | - Brent W. Winston
- Departments
of Critical Care Medicine, Medicine and Biochemistry and Molecular
Biology, Foothills Medical Centre and University
of Calgary, 1403 29 Street
NW, Calgary, Alberta T2N 4N1, Canada
| | - David Sweet
- Division
of Critical Care Medicine, Vancouver General
Hospital, 2775 Laurel St, Vancouver, BC V5Z 1M9, Canada
| | - John H. Boyd
- Centre
for Heart Lung Innovation, St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
- Division of Critical Care Medicine, St.
Paul’s Hospital, University of British
Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
| | - Keith R. Walley
- Centre
for Heart Lung Innovation, St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
- Division of Critical Care Medicine, St.
Paul’s Hospital, University of British
Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
| | - Greg Haljan
- Department of Medicine, Surrey Memorial
Hospital, 13750 96th
Avenue, Surrey, BC V3V 1Z2, Canada
| | - Allison McGeer
- Mt. Sinai Hospital and University of Toronto, 600 University Avenue, Toronto, ON M5G 1X5, Canada
| | | | - Robert Fowler
- Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada
| | - David Maslove
- Department
of Critical Care, Kingston General Hospital
and Queen’s University, 76 Stuart Street, Kingston, ON K7L 2V7, Canada
| | - Joel Singer
- Centre for
Health Evaluation and Outcome Science (CHEOS), St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
| | - David M. Patrick
- British Columbia Centre for Disease Control
(BCCDC) and University
of British Columbia, 655 West 12th Avenue, Vancouver, BC V5Z 4R4, Canada
| | - John C. Marshall
- Department of Surgery, St. Michael’s
Hospital, 30 Bond Street, Toronto, ON M5B
1W8, Canada
| | - Srinivas Murthy
- BC Children’s Hospital and University of British Columbia, 4500 Oak Street, Vancouver, BC V6H 3N1, Canada
| | - Fagun Jain
- Black Tusk Research Group, Vancouver, BC V6Z 2C7, Canada
| | - Christoph H. Borchers
- Segal Cancer Proteomics, Centre, Lady Davis
Institute
for Medical Research, McGill University, Montreal, QC H3T 1E2, Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC H3T 1E2, Canada
- Division of Experimental Medicine, McGill
University, Montreal, QC H3T 1E2, Canada
- Department of Pathology, McGill
University, Montreal, QC H3T 1E2, Canada
| | - David R. Goodlett
- UVic-Genome
BC Proteomics Centre, University of Victoria, Victoria V8Z 5N3, BC Canada
| | - Adeera Levin
- Division of Nephrology, St.
Paul’s Hospital, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
| | - James A. Russell
- Centre
for Heart Lung Innovation, St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
- Division of Critical Care Medicine, St.
Paul’s Hospital, University of British
Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
| | - ARBs CORONA I Consortium
- Center
for Proteomics and Metabolomics, Leiden
University Medical Center, Leiden 2333 ZA, The Netherlands
- UVic-Genome
BC Proteomics Centre, University of Victoria, Victoria V8Z 5N3, BC Canada
- Gerald
Bronfman Department of Oncology, McGill
University, Montreal, QC H3A 0G4, Canada
- Division
of General Internal Medicine, Vancouver
General Hospital and University of British Columbia, 2775 Laurel St, Vancouver, BC V5Z 1M9, Canada
- Division
of Respiratory Medicine, Vancouver General Hospital, University of British Columbia, Vancouver, BC V5Z 1M9, Canada
- Centre for
Health Evaluation and Outcome Science (CHEOS), St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
- Division
of Infectious Diseases, Department of Medicine, McGill University Health Centre, Montreal, PQ H4A 3J1, Canada
- Departments
of Critical Care Medicine, Medicine and Biochemistry and Molecular
Biology, Foothills Medical Centre and University
of Calgary, 1403 29 Street
NW, Calgary, Alberta T2N 4N1, Canada
- Division
of Critical Care Medicine, Vancouver General
Hospital, 2775 Laurel St, Vancouver, BC V5Z 1M9, Canada
- Centre
for Heart Lung Innovation, St. Paul’s Hospital, University of British Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
- Division of Critical Care Medicine, St.
Paul’s Hospital, University of British
Columbia, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
- Department of Medicine, Surrey Memorial
Hospital, 13750 96th
Avenue, Surrey, BC V3V 1Z2, Canada
- Mt. Sinai Hospital and University of Toronto, 600 University Avenue, Toronto, ON M5G 1X5, Canada
- University of Sherbrooke, Sherbrooke, PQ J1K 2R1, Canada
- Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, ON M4N 3M5, Canada
- Department
of Critical Care, Kingston General Hospital
and Queen’s University, 76 Stuart Street, Kingston, ON K7L 2V7, Canada
- British Columbia Centre for Disease Control
(BCCDC) and University
of British Columbia, 655 West 12th Avenue, Vancouver, BC V5Z 4R4, Canada
- Department of Surgery, St. Michael’s
Hospital, 30 Bond Street, Toronto, ON M5B
1W8, Canada
- BC Children’s Hospital and University of British Columbia, 4500 Oak Street, Vancouver, BC V6H 3N1, Canada
- Black Tusk Research Group, Vancouver, BC V6Z 2C7, Canada
- Segal Cancer Proteomics, Centre, Lady Davis
Institute
for Medical Research, McGill University, Montreal, QC H3T 1E2, Canada
- Gerald Bronfman Department of Oncology, Jewish General Hospital, Montreal, QC H3T 1E2, Canada
- Division of Experimental Medicine, McGill
University, Montreal, QC H3T 1E2, Canada
- Department of Pathology, McGill
University, Montreal, QC H3T 1E2, Canada
- Division of Nephrology, St.
Paul’s Hospital, 1081 Burrard Street, Vancouver, BC V6Z 1Y6, Canada
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5
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Ahmad AF, Caparrós-Martin JA, Gray N, Lodge S, Wist J, Lee S, O'Gara F, Dwivedi G, Ward NC. Gut microbiota and metabolomics profiles in patients with chronic stable angina and acute coronary syndrome. Physiol Genomics 2024; 56:48-64. [PMID: 37811721 DOI: 10.1152/physiolgenomics.00072.2023] [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: 07/16/2023] [Revised: 10/05/2023] [Accepted: 10/05/2023] [Indexed: 10/10/2023] Open
Abstract
Cardiovascular disease (CVD) is the leading cause of death worldwide. The gut microbiota and its associated metabolites may be involved in the development and progression of CVD, although the mechanisms and impact on clinical outcomes are not fully understood. This study investigated the gut microbiome profile and associated metabolites in patients with chronic stable angina (CSA) and acute coronary syndrome (ACS) compared with healthy controls. Bacterial alpha diversity in stool from patients with ACS or CSA was comparable to healthy controls at both baseline and follow-up visits. Differential abundance analysis identified operational taxonomic units (OTUs) assigned to commensal taxa differentiating patients with ACS from healthy controls at both baseline and follow-up. Patients with CSA and ACS had significantly higher levels of trimethylamine N-oxide compared with healthy controls (CSA: 0.032 ± 0.023 mmol/L, P < 0.01 vs. healthy, and ACS: 0.032 ± 0.023 mmol/L, P = 0.02 vs. healthy, respectively). Patients with ACS had reduced levels of propionate and butyrate (119 ± 4 vs. 139 ± 5.1 µM, P = 0.001, and 14 ± 4.3 vs. 23.5 ± 8.1 µM, P < 0.001, respectively), as well as elevated serum sCD14 (2245 ± 75.1 vs. 1834 ± 45.8 ng/mL, P < 0.0001) and sCD163 levels (457.3 ± 31.8 vs. 326.8 ± 20.7 ng/mL, P = 0.001), compared with healthy controls at baseline. Furthermore, a modified small molecule metabolomic and lipidomic signature was observed in patients with CSA and ACS compared with healthy controls. These findings provide evidence of a link between gut microbiome composition and gut bacterial metabolites with CVD. Future time course studies in patients to observe temporal changes and subsequent associations with gut microbiome composition are required to provide insight into how these are affected by transient changes following an acute coronary event.NEW & NOTEWORTHY The study found discriminative microorganisms differentiating patients with acute coronary syndrome (ACS) from healthy controls. In addition, reduced levels of certain bacterial metabolites and elevated sCD14 and sCD163 were observed in patients with ACS compared with healthy controls. Furthermore, modified small molecule metabolomic and lipidomic signatures were found in both patient groups. Although it is not known whether these differences in profiles are associated with disease development and/or progression, the findings provide exciting options for potential new disease-related mechanism(s) and associated therapeutic target(s).
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Affiliation(s)
- Adilah F Ahmad
- Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Jose A Caparrós-Martin
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
| | - Nicola Gray
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
| | - Samantha Lodge
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
| | - Julien Wist
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
| | - Silvia Lee
- Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
- Department of Microbiology, PathWest Laboratory Medicine, Perth, Western Australia, Australia
| | - Fergal O'Gara
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
- BIOMERIT Research Centre, School of Microbiology, University College Cork, Cork, Ireland
| | - Girish Dwivedi
- Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medical Research, Perth, Western Australia, Australia
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
- Department of Cardiology, Fiona Stanley Hospital, Perth, Western Australia, Australia
| | - Natalie C Ward
- Dobney Hypertension Centre, Medical School, The University of Western Australia, Perth, Western Australia, Australia
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Ahmad AF, Caparrós-Martin JA, Gray N, Lodge S, Wist J, Lee S, O'Gara F, Shah A, Ward NC, Dwivedi G. Insights into the associations between the gut microbiome, its metabolites, and heart failure. Am J Physiol Heart Circ Physiol 2023; 325:H1325-H1336. [PMID: 37737730 DOI: 10.1152/ajpheart.00436.2023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 09/05/2023] [Accepted: 09/17/2023] [Indexed: 09/23/2023]
Abstract
Heart failure (HF) is the end stage of most cardiovascular diseases and remains a significant health problem globally. We aimed to assess whether patients with left ventricular ejection fraction ≤45% had alterations in both the gut microbiome profile and production of associated metabolites when compared with a healthy cohort. We also examined the associated inflammatory, metabolomic, and lipidomic profiles of patients with HF. This single center, observational study, recruited 73 patients with HF and 59 healthy volunteers. Blood and stool samples were collected at baseline and 6-mo follow-up, along with anthropometric and clinical data. When compared with healthy controls, patients with HF had reduced gut bacterial alpha diversity at follow-up (P = 0.004) but not at baseline. The stool microbiota of patients with HF was characterized by a depletion of operational taxonomic units representing commensal Clostridia at both baseline and follow-up. Patients with HF also had significantly elevated baseline plasma acetate (P = 0.007), plasma trimethylamine-N-oxide (TMAO) (P = 0.003), serum soluble CD14 (sCD14; P = 0.005), and soluble CD163 (sCD163; P = 0.004) levels compared with healthy controls. Furthermore, patients with HF had a distinct metabolomic and lipidomic profile at baseline when compared with healthy controls. Differences in the composition of the gut microbiome and the levels of associated metabolites were observed in patients with HF when compared with a healthy cohort. This was also associated with an altered metabolomic and lipidomic profile. Our study identifies microorganisms and metabolites that could represent new therapeutic targets and diagnostic tools in the pathogenesis of HF.NEW & NOTEWORTHY We found a reduction in gut bacterial alpha diversity in patients with heart failure (HF) and that the stool microbiota of patients with HF was characterized by depletion of operational taxonomic units representing commensal Clostridia at both baseline and follow-up. Patients with HF also had altered bacterial metabolites and increased inflammatory profiles compared with healthy controls. A distinct metabolomic and lipidomic profile was present in patients with HF at baseline when compared with healthy controls.
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Affiliation(s)
- Adilah F Ahmad
- Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medial Research, Perth, Western Australia, Australia
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Jose A Caparrós-Martin
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
| | - Nicola Gray
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
| | - Samantha Lodge
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
| | - Julien Wist
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, Western Australia, Australia
| | - Silvia Lee
- Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medial Research, Perth, Western Australia, Australia
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
- Department of Microbiology, PathWest Laboratory Medicine, Perth, Western Australia, Australia
| | - Fergal O'Gara
- Wal-Yan Respiratory Research Centre, Telethon Kids Institute, Perth, Western Australia, Australia
- BIOMERIT Research Centre, School of Microbiology, University College Cork, Cork, Ireland
| | - Amit Shah
- Department of Cardiology, Fiona Stanley Hospital, Perth, Western Australia, Australia
| | - Natalie C Ward
- Dobney Hypertension Centre, Medical School, The University of Western Australia, Perth, Western Australia, Australia
| | - Girish Dwivedi
- Department of Advanced Clinical and Translational Cardiovascular Imaging, Harry Perkins Institute of Medial Research, Perth, Western Australia, Australia
- Medical School, The University of Western Australia, Perth, Western Australia, Australia
- Department of Cardiology, Fiona Stanley Hospital, Perth, Western Australia, Australia
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7
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Demangel C, Surace L. Host-pathogen interactions from a metabolic perspective: methods of investigation. Microbes Infect 2023:105267. [PMID: 38007087 DOI: 10.1016/j.micinf.2023.105267] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Revised: 10/21/2023] [Accepted: 11/21/2023] [Indexed: 11/27/2023]
Abstract
Metabolism shapes immune homeostasis in health and disease. This review presents the range of methods that are currently available to investigate the dialog between metabolism and immunity at the systemic, tissue and cellular levels, particularly during infection.
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Affiliation(s)
- Caroline Demangel
- Institut Pasteur, Université Paris Cité, Inserm U1224, Immunobiology and Therapy Unit, Paris, France
| | - Laura Surace
- Institute of Clinical Chemistry and Clinical Pharmacology, University Hospital Bonn, University of Bonn, Bonn, Germany
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8
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Ryan MJ, Raby E, Whiley L, Masuda R, Lodge S, Nitschke P, Maker GL, Wist J, Holmes E, Wood FM, Nicholson JK, Fear MW, Gray N. Nonsevere Burn Induces a Prolonged Systemic Metabolic Phenotype Indicative of a Persistent Inflammatory Response Postinjury. J Proteome Res 2023. [PMID: 38104259 DOI: 10.1021/acs.jproteome.3c00516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2023]
Abstract
Globally, burns are a significant cause of injury that can cause substantial acute trauma as well as lead to increased incidence of chronic comorbidity and disease. To date, research has primarily focused on the systemic response to severe injury, with little in the literature reported on the impact of nonsevere injuries (<15% total burn surface area; TBSA). To elucidate the metabolic consequences of a nonsevere burn injury, longitudinal plasma was collected from adults (n = 35) who presented at hospital with a nonsevere burn injury at admission, and at 6 week follow up. A cross-sectional baseline sample was also collected from nonburn control participants (n = 14). Samples underwent multiplatform metabolic phenotyping using 1H nuclear magnetic resonance spectroscopy and liquid chromatography-mass spectrometry to quantify 112 lipoprotein and glycoprotein signatures and 852 lipid species from across 20 subclasses. Multivariate data modeling (orthogonal projections to latent structures-discriminate analysis; OPLS-DA) revealed alterations in lipoprotein and lipid metabolism when comparing the baseline control to hospital admission samples, with the phenotypic signature found to be sustained at follow up. Univariate (Mann-Whitney U) testing and OPLS-DA indicated specific increases in GlycB (p-value < 1.0e-4), low density lipoprotein-2 subfractions (variable importance in projection score; VIP > 6.83e-1) and monoacyglyceride (20:4) (p-value < 1.0e-4) and decreases in circulating anti-inflammatory high-density lipoprotein-4 subfractions (VIP > 7.75e-1), phosphatidylcholines, phosphatidylglycerols, phosphatidylinositols, and phosphatidylserines. The results indicate a persistent systemic metabolic phenotype that occurs even in cases of a nonsevere burn injury. The phenotype is indicative of an acute inflammatory profile that continues to be sustained postinjury, suggesting an impact on systems health beyond the site of injury. The phenotypes contained metabolic signatures consistent with chronic inflammatory states reported to have an elevated incidence postburn injury. Such phenotypic signatures may provide patient stratification opportunities, to identify individual responses to injury, personalize intervention strategies, and improve acute care, reducing the risk of chronic comorbidity.
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Affiliation(s)
- Monique J Ryan
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Edward Raby
- Burns Service of Western Australia, WA Department of Health, Murdoch, Western Australia 6150, Australia
- Department of Microbiology, PathWest Laboratory Medicine, Perth, Western Australia 6009, Australia
- Department of Infectious Diseases, Fiona Stanley Hospital, Perth, Western Australia 6150, Australia
| | - Luke Whiley
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Reika Masuda
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Philipp Nitschke
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Garth L Maker
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Julien Wist
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
| | - Elaine Holmes
- Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Department of Metabolism Digestion and Reproduction, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Fiona M Wood
- Burns Service of Western Australia, WA Department of Health, Murdoch, Western Australia 6150, Australia
- Burn Injury Research Unit, School of Biomedical Sciences, University of Western Australia, Perth, Western Australia 6009, Australia
- Fiona Wood Foundation, Perth, Western Australia 6150, Australia
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Institute of Global Health Innovation, Imperial College London, London SW7 2AZ, United Kingdom
| | - Mark W Fear
- Burn Injury Research Unit, School of Biomedical Sciences, University of Western Australia, Perth, Western Australia 6009, Australia
- Fiona Wood Foundation, Perth, Western Australia 6150, Australia
| | - Nicola Gray
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
- Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
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9
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Stadler JT, Habisch H, Prüller F, Mangge H, Bärnthaler T, Kargl J, Pammer A, Holzer M, Meissl S, Rani A, Madl T, Marsche G. HDL-Related Parameters and COVID-19 Mortality: The Importance of HDL Function. Antioxidants (Basel) 2023; 12:2009. [PMID: 38001862 PMCID: PMC10669705 DOI: 10.3390/antiox12112009] [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: 10/12/2023] [Revised: 11/03/2023] [Accepted: 11/15/2023] [Indexed: 11/26/2023] Open
Abstract
COVID-19, caused by the SARS-CoV-2 coronavirus, emerged as a global pandemic in late 2019, resulting in significant global public health challenges. The emerging evidence suggests that diminished high-density lipoprotein (HDL) cholesterol levels are associated with the severity of COVID-19, beyond inflammation and oxidative stress. Here, we used nuclear magnetic resonance spectroscopy to compare the lipoprotein and metabolic profiles of COVID-19-infected patients with non-COVID-19 pneumonia. We compared the control group and the COVID-19 group using inflammatory markers to ensure that the differences in lipoprotein levels were due to COVID-19 infection. Our analyses revealed supramolecular phospholipid composite (SPC), phenylalanine, and HDL-related parameters as key discriminators between COVID-19-positive and non-COVID-19 pneumonia patients. More specifically, the levels of HDL parameters, including apolipoprotein A-I (ApoA-I), ApoA-II, HDL cholesterol, and HDL phospholipids, were significantly different. These findings underscore the potential impact of HDL-related factors in patients with COVID-19. Significantly, among the HDL-related metrics, the cholesterol efflux capacity (CEC) displayed the strongest negative association with COVID-19 mortality. CEC is a measure of how well HDL removes cholesterol from cells, which may affect the way SARS-CoV-2 enters cells. In summary, this study validates previously established markers of COVID-19 infection and further highlights the potential significance of HDL functionality in the context of COVID-19 mortality.
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Affiliation(s)
- Julia T. Stadler
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
| | - Hansjörg Habisch
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (H.H.); (T.M.)
| | - Florian Prüller
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria;
| | - Harald Mangge
- Clinical Institute of Medical and Chemical Laboratory Diagnostics, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria;
| | - Thomas Bärnthaler
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
| | - Julia Kargl
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
- BioTechMed Graz, 8010 Graz, Austria
| | - Anja Pammer
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
| | - Michael Holzer
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
| | - Sabine Meissl
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
| | - Alankrita Rani
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
| | - Tobias Madl
- Gottfried Schatz Research Center for Cell Signaling, Metabolism and Aging, Molecular Biology and Biochemistry, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (H.H.); (T.M.)
- BioTechMed Graz, 8010 Graz, Austria
| | - Gunther Marsche
- Division of Pharmacology, Otto Loewi Research Center, Medical University of Graz, Neue Stiftingtalstraße 6, 8010 Graz, Austria; (J.T.S.); (T.B.); (J.K.); (A.P.); (M.H.); (S.M.); (A.R.)
- BioTechMed Graz, 8010 Graz, Austria
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10
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Albóniga OE, Moreno E, Martínez-Sanz J, Vizcarra P, Ron R, Díaz-Álvarez J, Rosas Cancio-Suarez M, Sánchez-Conde M, Galán JC, Angulo S, Moreno S, Barbas C, Serrano-Villar S. Differential abundance of lipids and metabolites related to SARS-CoV-2 infection and susceptibility. Sci Rep 2023; 13:15124. [PMID: 37704651 PMCID: PMC10500013 DOI: 10.1038/s41598-023-40999-5] [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: 05/10/2023] [Accepted: 08/20/2023] [Indexed: 09/15/2023] Open
Abstract
The mechanisms driving SARS-CoV-2 susceptibility remain poorly understood, especially the factors determining why unvaccinated individuals remain uninfected despite high-risk exposures. To understand lipid and metabolite profiles related with COVID-19 susceptibility and disease progression. We collected samples from an exceptional group of unvaccinated healthcare workers heavily exposed to SARS-CoV-2 but not infected ('non-susceptible') and subjects who became infected during the follow-up ('susceptible'), including non-hospitalized and hospitalized patients with different disease severity providing samples at early disease stages. Then, we analyzed their plasma metabolomic profiles using mass spectrometry coupled with liquid and gas chromatography. We show specific lipids profiles and metabolites that could explain SARS-CoV-2 susceptibility and COVID-19 severity. More importantly, non-susceptible individuals show a unique lipidomic pattern characterized by the upregulation of most lipids, especially ceramides and sphingomyelin, which could be interpreted as markers of low susceptibility to SARS-CoV-2 infection. This study strengthens the findings of other researchers about the importance of studying lipid profiles as relevant markers of SARS-CoV-2 pathogenesis.
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Affiliation(s)
- Oihane E Albóniga
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, 28660, Madrid, Spain
| | - Elena Moreno
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Javier Martínez-Sanz
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Pilar Vizcarra
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Raquel Ron
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Jorge Díaz-Álvarez
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Marta Rosas Cancio-Suarez
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Matilde Sánchez-Conde
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Juan Carlos Galán
- Department of Microbiology, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERESP, Instituto de Salud Carlos III, Madrid, Spain
| | - Santiago Angulo
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, 28660, Madrid, Spain
| | - Santiago Moreno
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain
| | - Coral Barbas
- Centro de Metabolómica y Bioanálisis (CEMBIO), Facultad de Farmacia, Universidad San Pablo-CEU, CEU Universities, Urbanización Montepríncipe, Boadilla del Monte, 28660, Madrid, Spain
| | - Sergio Serrano-Villar
- Department of Infectious Diseases, Hospital Universitario Ramón y Cajal, IRYCIS, 28034, Madrid, Spain.
- CIBERINFEC, Instituto de Salud Carlos III, Madrid, Spain.
- Department of Infectious Diseases, Hospital Universitario Ramon y Cajal, Facultad de Medicina, Universidad de Alcalá (IRYCIS), Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
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11
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Skrzydlewska E, Łuczaj W, Biernacki M, Wójcik P, Jarocka-Karpowicz I, Orehovec B, Baršić B, Tarle M, Kmet M, Lukšić I, Marušić Z, Bauer G, Žarković N. Preliminary Comparison of Molecular Antioxidant and Inflammatory Mechanisms Determined in the Peripheral Blood Granulocytes of COVID-19 Patients. Int J Mol Sci 2023; 24:13574. [PMID: 37686388 PMCID: PMC10488240 DOI: 10.3390/ijms241713574] [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: 07/19/2023] [Revised: 08/30/2023] [Accepted: 08/31/2023] [Indexed: 09/10/2023] Open
Abstract
The aim of this study was to evaluate selected parameters of redox signaling and inflammation in the granulocytes of COVID-19 patients who recovered and those who died. Upon admission, the patients did not differ in terms of any relevant clinical parameter apart from the percentage of granulocytes, which was 6% higher on average in those patients who died. Granulocytes were isolated from the blood of 15 healthy people and survivors and 15 patients who died within a week, and who were selected post hoc for analysis according to their matching gender and age. They differed only in the lethal outcome, which could not be predicted upon arrival at the hospital. The proteins level (respective ELISA), antioxidant activity (spectrophotometry), and lipid mediators (UPUPLC-MS) were measured in the peripheral blood granulocytes obtained via gradient centrifugation. The levels of Nrf2, HO-1, NFκB, and IL-6 were higher in the granulocytes of COVID-19 patients who died within a week, while the activity of cytoplasmic Cu,Zn-SOD and mitochondrial Mn-SOD and IL-2/IL-10 were lower in comparison to the levels observed in survivors. Furthermore, in the granulocytes of those patients who died, an increase in pro-inflammatory eicosanoids (PGE2 and TXB2), together with elevated cannabinoid receptors 1 and 2 (associated with a decrease in the anti-inflammatory 15d-PGJ2), were found. Hence, this study suggests that by triggering transcription factors, granulocytes activate inflammatory and redox signaling, leading to the production of pro-inflammatory eicosanoids while reducing cellular antioxidant capacity through SOD, thus expressing an altered response to COVID-19, which may result in the onset of systemic oxidative stress, ARDS, and the death of the patient.
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Affiliation(s)
- Elżbieta Skrzydlewska
- Department of Analytical Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.Ł.); (M.B.); (P.W.); (I.J.-K.)
| | - Wojciech Łuczaj
- Department of Analytical Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.Ł.); (M.B.); (P.W.); (I.J.-K.)
| | - Michał Biernacki
- Department of Analytical Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.Ł.); (M.B.); (P.W.); (I.J.-K.)
| | - Piotr Wójcik
- Department of Analytical Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.Ł.); (M.B.); (P.W.); (I.J.-K.)
| | - Iwona Jarocka-Karpowicz
- Department of Analytical Chemistry, Medical University of Bialystok, 15-222 Bialystok, Poland; (W.Ł.); (M.B.); (P.W.); (I.J.-K.)
| | - Biserka Orehovec
- Clinical Hospital Dubrava, HR-10000 Zagreb, Croatia; (B.O.); (B.B.); (M.T.); (M.K.); (I.L.)
| | - Bruno Baršić
- Clinical Hospital Dubrava, HR-10000 Zagreb, Croatia; (B.O.); (B.B.); (M.T.); (M.K.); (I.L.)
| | - Marko Tarle
- Clinical Hospital Dubrava, HR-10000 Zagreb, Croatia; (B.O.); (B.B.); (M.T.); (M.K.); (I.L.)
| | - Marta Kmet
- Clinical Hospital Dubrava, HR-10000 Zagreb, Croatia; (B.O.); (B.B.); (M.T.); (M.K.); (I.L.)
| | - Ivica Lukšić
- Clinical Hospital Dubrava, HR-10000 Zagreb, Croatia; (B.O.); (B.B.); (M.T.); (M.K.); (I.L.)
- School of Medicine, University of Zagreb, HR-10000 Zagreb, Croatia
| | - Zlatko Marušić
- Division of Pathology, Clinical Hospital Centre Zagreb, HR-10000 Zagreb, Croatia;
| | - Georg Bauer
- Institute of Virology, Medical Center–University of Freiburg, 79104 Freiburg, Germany;
| | - Neven Žarković
- Laboratory for Oxidative Stress (LabOS), Ruđer Bošković Institute, HR-10000 Zagreb, Croatia
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12
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Lodge S, Lawler NG, Gray N, Masuda R, Nitschke P, Whiley L, Bong SH, Yeap BB, Dwivedi G, Spraul M, Schaefer H, Gil-Redondo R, Embade N, Millet O, Holmes E, Wist J, Nicholson JK. Integrative Plasma Metabolic and Lipidomic Modelling of SARS-CoV-2 Infection in Relation to Clinical Severity and Early Mortality Prediction. Int J Mol Sci 2023; 24:11614. [PMID: 37511373 PMCID: PMC10380980 DOI: 10.3390/ijms241411614] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/10/2023] [Accepted: 07/15/2023] [Indexed: 07/30/2023] Open
Abstract
An integrative multi-modal metabolic phenotyping model was developed to assess the systemic plasma sequelae of SARS-CoV-2 (rRT-PCR positive) induced COVID-19 disease in patients with different respiratory severity levels. Plasma samples from 306 unvaccinated COVID-19 patients were collected in 2020 and classified into four levels of severity ranging from mild symptoms to severe ventilated cases. These samples were investigated using a combination of quantitative Nuclear Magnetic Resonance (NMR) spectroscopy and Mass Spectrometry (MS) platforms to give broad lipoprotein, lipidomic and amino acid, tryptophan-kynurenine pathway, and biogenic amine pathway coverage. All platforms revealed highly significant differences in metabolite patterns between patients and controls (n = 89) that had been collected prior to the COVID-19 pandemic. The total number of significant metabolites increased with severity with 344 out of the 1034 quantitative variables being common to all severity classes. Metabolic signatures showed a continuum of changes across the respiratory severity levels with the most significant and extensive changes being in the most severely affected patients. Even mildly affected respiratory patients showed multiple highly significant abnormal biochemical signatures reflecting serious metabolic deficiencies of the type observed in Post-acute COVID-19 syndrome patients. The most severe respiratory patients had a high mortality (56.1%) and we found that we could predict mortality in this patient sub-group with high accuracy in some cases up to 61 days prior to death, based on a separate metabolic model, which highlighted a different set of metabolites to those defining the basic disease. Specifically, hexosylceramides (HCER 16:0, HCER 20:0, HCER 24:1, HCER 26:0, HCER 26:1) were markedly elevated in the non-surviving patient group (Cliff's delta 0.91-0.95) and two phosphoethanolamines (PE.O 18:0/18:1, Cliff's delta = -0.98 and PE.P 16:0/18:1, Cliff's delta = -0.93) were markedly lower in the non-survivors. These results indicate that patient morbidity to mortality trajectories is determined relatively soon after infection, opening the opportunity to select more intensive therapeutic interventions to these "high risk" patients in the early disease stages.
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Affiliation(s)
- Samantha Lodge
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Nathan G. Lawler
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Nicola Gray
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Reika Masuda
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Philipp Nitschke
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Luke Whiley
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
| | - Bu B. Yeap
- Medical School, University of Western Australia, Perth, WA 6150, Australia; (B.B.Y.); (G.D.)
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | - Girish Dwivedi
- Medical School, University of Western Australia, Perth, WA 6150, Australia; (B.B.Y.); (G.D.)
- Department of Cardiology, Fiona Stanley Hospital, Perth, WA 6150, Australia
| | | | | | - Rubén Gil-Redondo
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Nieves Embade
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain; (R.G.-R.); (N.E.); (O.M.)
| | - Elaine Holmes
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK
| | - Julien Wist
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
| | - Jeremy K. Nicholson
- Australian National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia; (S.L.); (N.G.L.); (N.G.); (R.M.); (P.N.); (L.W.); (S.-H.B.); (E.H.)
- Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
- Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, Faculty Building, South Kensington Campus, London SW7 2NA, UK
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13
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Chin ST, Hoerlendsberger G, Wong KW, Li S, Bong SH, Whiley L, Wist J, Masuda R, Greeff J, Holmes E, Nicholson JK, Loo RL. Targeted lipidomics coupled with machine learning for authenticating the provenance of chicken eggs. Food Chem 2023; 410:135366. [PMID: 36641906 DOI: 10.1016/j.foodchem.2022.135366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 10/17/2022] [Accepted: 12/29/2022] [Indexed: 12/31/2022]
Abstract
Free-range eggs are ethically desirable but as with all high-value commercial products, the establishment of provenance can be problematic. Here, we compared a simple one-step isopropanol method to a two-step methyl-tert-butyl ether method for extracting lipid species in chicken egg yolks before liquid chromatography-tandem mass spectrometry (LC-MS/MS) analysis. The isopropanol method extracted 937 lipid species from 20 major lipid subclasses with high reproducibility (CV < 30 %). Machine learning techniques could differentiate conventional cage, barn, and free-range eggs using an external test dataset with an accuracy of 0.94, 0.82, and 0.82, respectively. Lipid species that differentiated cage eggs were predominantly phosphocholines and phosphoethanolamines whilst the free-range egg lipidomes were dominated by acylglycerides with up to three fatty acids. The lipid profiles were found to be characteristic of the cage, barns, and free-range eggs. The lipidomic analysis together with the statistical modeling approach thus provides an efficient tool for verifying the provenance of conventional chicken eggs.
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Affiliation(s)
- Sung-Tong Chin
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Gerhard Hoerlendsberger
- Discipline of Information Technology, Murdoch University, 90 South Street, Perth, WA 6150, Australia
| | - Kok Wai Wong
- Discipline of Information Technology, Murdoch University, 90 South Street, Perth, WA 6150, Australia
| | - Sirui Li
- Discipline of Information Technology, Murdoch University, 90 South Street, Perth, WA 6150, Australia
| | - Sze How Bong
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Luke Whiley
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Julien Wist
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Reika Masuda
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Johan Greeff
- Department of Primary Industries and Regional Development, 3 Baron-Hay Court, South Perth, WA 6151, Australia
| | - Elaine Holmes
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Nutrition Research, Department of Metabolism, Nutrition and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, London SW7 2AZ, U.K
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia
| | - Ruey Leng Loo
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, 5 Robin Warren Drive, Perth, WA 6150, Australia.
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14
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Consonni FM, Durante B, Manfredi M, Bleve A, Pandolfo C, Garlatti V, Vanella VV, Marengo E, Barberis E, Bottazzi B, Bombace S, My I, Condorelli G, Torri V, Sica A. Immunometabolic interference between cancer and COVID-19. Front Immunol 2023; 14:1168455. [PMID: 37063865 PMCID: PMC10090695 DOI: 10.3389/fimmu.2023.1168455] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2023] [Accepted: 03/16/2023] [Indexed: 03/31/2023] Open
Abstract
Even though cancer patients are generally considered more susceptible to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, the mechanisms driving their predisposition to severe forms of coronavirus disease 2019 (COVID-19) have not yet been deciphered. Since metabolic disorders are associated with homeostatic frailty, which increases the risk of infection and cancer, we asked whether we could identify immunometabolic pathways intersecting with cancer and SARS-CoV-2 infection. Thanks to a combined flow cytometry and multiomics approach, here we show that the immunometabolic traits of COVID-19 cancer patients encompass alterations in the frequency and activation status of circulating myeloid and lymphoid subsets, and that these changes are associated with i) depletion of tryptophan and its related neuromediator tryptamine, ii) accumulation of immunosuppressive tryptophan metabolites (i.e., kynurenines), and iii) low nicotinamide adenine dinucleotide (NAD+) availability. This metabolic imbalance is accompanied by altered expression of inflammatory cytokines in peripheral blood mononuclear cells (PBMCs), with a distinctive downregulation of IL-6 and upregulation of IFNγ mRNA expression levels. Altogether, our findings indicate that cancer not only attenuates the inflammatory state in COVID-19 patients but also contributes to weakening their precarious metabolic state by interfering with NAD+-dependent immune homeostasis.
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Affiliation(s)
- Francesca Maria Consonni
- Department of Pharmaceutical Sciences, University of Piemonte Orientale “A. Avogadro”, Novara, Italy
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
| | - Barbara Durante
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
| | - Marcello Manfredi
- Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Diseases, University of Piemonte Orientale, Novara, Italy
| | - Augusto Bleve
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
| | - Chiara Pandolfo
- Department of Pharmaceutical Sciences, University of Piemonte Orientale “A. Avogadro”, Novara, Italy
| | - Valentina Garlatti
- Department of Pharmaceutical Sciences, University of Piemonte Orientale “A. Avogadro”, Novara, Italy
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
| | - Virginia Vita Vanella
- Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Diseases, University of Piemonte Orientale, Novara, Italy
| | - Emilio Marengo
- Center for Translational Research on Autoimmune and Allergic Diseases, University of Piemonte Orientale, Novara, Italy
- Department of Sciences and Technological Innovation, University of Piemonte Orientale, Alessandria, Italy
| | - Elettra Barberis
- Department of Translational Medicine, University of Piemonte Orientale, Novara, Italy
- Center for Translational Research on Autoimmune and Allergic Diseases, University of Piemonte Orientale, Novara, Italy
| | - Barbara Bottazzi
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
| | - Sara Bombace
- Department of Cardiovascular Medicine, Humanitas Clinical and Research Center, Rozzano, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele-Milan, Italy
| | - Ilaria My
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele-Milan, Italy
| | - Gianluigi Condorelli
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
- Department of Cardiovascular Medicine, Humanitas Clinical and Research Center, Rozzano, Milan, Italy
- Department of Biomedical Sciences, Humanitas University, Pieve Emanuele-Milan, Italy
| | - Valter Torri
- Istituto di Ricerche Farmacologiche Mario Negri-IRCCS, Milan, Italy
| | - Antonio Sica
- Department of Pharmaceutical Sciences, University of Piemonte Orientale “A. Avogadro”, Novara, Italy
- IRCCS Humanitas Clinical and Research Centre, Rozzano, Milan, Italy
- *Correspondence: Antonio Sica,
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15
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Ryan MJ, Grant-St James A, Lawler NG, Fear MW, Raby E, Wood FM, Maker GL, Wist J, Holmes E, Nicholson JK, Whiley L, Gray N. Comprehensive Lipidomic Workflow for Multicohort Population Phenotyping Using Stable Isotope Dilution Targeted Liquid Chromatography-Mass Spectrometry. J Proteome Res 2023; 22:1419-1433. [PMID: 36828482 PMCID: PMC10167688 DOI: 10.1021/acs.jproteome.2c00682] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/26/2023]
Abstract
Dysregulated lipid metabolism underpins many chronic diseases including cardiometabolic diseases. Mass spectrometry-based lipidomics is an important tool for understanding mechanisms of lipid dysfunction and is widely applied in epidemiology and clinical studies. With ever-increasing sample numbers, single batch acquisition is often unfeasible, requiring advanced methods that are accurate and robust to batch-to-batch and interday analytical variation. Herein, an optimized comprehensive targeted workflow for plasma and serum lipid quantification is presented, combining stable isotope internal standard dilution, automated sample preparation, and ultrahigh performance liquid chromatography-tandem mass spectrometry with rapid polarity switching to target 1163 lipid species spanning 20 subclasses. The resultant method is robust to common sources of analytical variation including blood collection tubes, hemolysis, freeze-thaw cycles, storage stability, analyte extraction technique, interinstrument variation, and batch-to-batch variation with 820 lipids reporting a relative standard deviation of <30% in 1048 replicate quality control plasma samples acquired across 16 independent batches (total injection count = 6142). However, sample hemolysis of ≥0.4% impacted lipid concentrations, specifically for phosphatidylethanolamines (PEs). Low interinstrument variability across two identical LC-MS systems indicated feasibility for intra/inter-lab parallelization of the assay. In summary, we have optimized a comprehensive lipidomic protocol to support rigorous analysis for large-scale, multibatch applications in precision medicine. The mass spectrometry lipidomics data have been deposited to massIVE: data set identifiers MSV000090952 and 10.25345/C5NP1WQ4S.
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Affiliation(s)
- Monique J Ryan
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Alanah Grant-St James
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Nathan G Lawler
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Mark W Fear
- Burn Injury Research Unit, University of Western Australia, Perth, Western Australia 6009, Australia.,Fiona Wood Foundation, Perth, Western Australia 6150, Australia
| | - Edward Raby
- Department of Microbiology, PathWest Laboratory Medicine, Perth, Western Australia 6009, Australia.,Department of Infectious Diseases, Fiona Stanley Hospital, Perth, Western Australia 6150, Australia
| | - Fiona M Wood
- Burn Injury Research Unit, University of Western Australia, Perth, Western Australia 6009, Australia.,WA Department of Health, Burns Service WA, Perth, Western Australia 6009, Australia.,Fiona Wood Foundation, Perth, Western Australia 6150, Australia
| | - Garth L Maker
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Julien Wist
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Elaine Holmes
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
| | - Luke Whiley
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Perron Institute for Neurological and Translational Science, Nedlands, Western Australia 6009, Australia
| | - Nicola Gray
- Australian National Phenome Centre, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia.,Centre for Computational and Systems Medicine, Health Futures Institute, Harry Perkins Institute, Murdoch University, 5 Robin Warren Drive, Perth, Western Australia 6150, Australia
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16
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Bruzzone C, Conde R, Embade N, Mato JM, Millet O. Metabolomics as a powerful tool for diagnostic, pronostic and drug intervention analysis in COVID-19. Front Mol Biosci 2023; 10:1111482. [PMID: 36876049 PMCID: PMC9975567 DOI: 10.3389/fmolb.2023.1111482] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Accepted: 02/06/2023] [Indexed: 02/17/2023] Open
Abstract
COVID-19 currently represents one of the major health challenges worldwide. Albeit its infectious character, with onset affectation mainly at the respiratory track, it is clear that the pathophysiology of COVID-19 has a systemic character, ultimately affecting many organs. This feature enables the possibility of investigating SARS-CoV-2 infection using multi-omic techniques, including metabolomic studies by chromatography coupled to mass spectrometry or by nuclear magnetic resonance (NMR) spectroscopy. Here we review the extensive literature on metabolomics in COVID-19, that unraveled many aspects of the disease including: a characteristic metabotipic signature associated to COVID-19, discrimination of patients according to severity, effect of drugs and vaccination treatments and the characterization of the natural history of the metabolic evolution associated to the disease, from the infection onset to full recovery or long-term and long sequelae of COVID.
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Affiliation(s)
- Chiara Bruzzone
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bilbao, Bizkaia, Spain
| | - Ricardo Conde
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bilbao, Bizkaia, Spain
| | - Nieves Embade
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bilbao, Bizkaia, Spain
| | - José M Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bilbao, Bizkaia, Spain.,CIBERehd, Instituto de Salud Carlos III, Madrid, Spain
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Basque Research and Technology Alliance (BRTA), Bilbao, Bizkaia, Spain.,CIBERehd, Instituto de Salud Carlos III, Madrid, Spain
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17
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Rössler T, Berezhnoy G, Singh Y, Cannet C, Reinsperger T, Schäfer H, Spraul M, Kneilling M, Merle U, Trautwein C. Quantitative Serum NMR Spectroscopy Stratifies COVID-19 Patients and Sheds Light on Interfaces of Host Metabolism and the Immune Response with Cytokines and Clinical Parameters. Metabolites 2022; 12:metabo12121277. [PMID: 36557315 PMCID: PMC9781847 DOI: 10.3390/metabo12121277] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Revised: 12/08/2022] [Accepted: 12/13/2022] [Indexed: 12/23/2022] Open
Abstract
The complex manifestations of COVID-19 are still not fully decoded on the molecular level. We combined quantitative the nuclear magnetic resonance (NMR) spectroscopy serum analysis of metabolites, lipoproteins and inflammation markers with clinical parameters and a targeted cytokine panel to characterize COVID-19 in a large (534 patient samples, 305 controls) outpatient cohort of recently tested PCR-positive patients. The COVID-19 cohort consisted of patients who were predominantly in the initial phase of the disease and mostly exhibited a milder disease course. Concerning the metabolic profiles of SARS-CoV-2-infected patients, we identified markers of oxidative stress and a severe dysregulation of energy metabolism. NMR markers, such as phenylalanine, inflammatory glycoproteins (Glyc) and their ratio with the previously reported supramolecular phospholipid composite (Glyc/SPC), showed a predictive power comparable to laboratory parameters such as C-reactive protein (CRP) or ferritin. We demonstrated interfaces between the metabolism and the immune system, e.g., we could trace an interleukin (IL-6)-induced transformation of a high-density lipoprotein (HDL) to a pro-inflammatory actor. Finally, we showed that metadata such as age, sex and constitution (e.g., body mass index, BMI) need to be considered when exploring new biomarkers and that adding NMR parameters to existing diagnoses expands the diagnostic toolbox for patient stratification and personalized medicine.
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Affiliation(s)
- Titus Rössler
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
| | - Georgy Berezhnoy
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
| | - Yogesh Singh
- Institute of Medical Genetics & Applied Genomics, University Hospital Tübingen, 72076 Tübingen, Germany
| | - Claire Cannet
- Bruker BioSpin GmbH, Applied Industrial and Clinical Division, 76275 Ettlingen, Germany
| | - Tony Reinsperger
- Bruker BioSpin GmbH, Applied Industrial and Clinical Division, 76275 Ettlingen, Germany
| | - Hartmut Schäfer
- Bruker BioSpin GmbH, Applied Industrial and Clinical Division, 76275 Ettlingen, Germany
| | - Manfred Spraul
- Bruker BioSpin GmbH, Applied Industrial and Clinical Division, 76275 Ettlingen, Germany
| | - Manfred Kneilling
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
- Department of Dermatology, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
- Cluster of Excellence iFIT (EXC 2180) “Image-guided and Functionally Instructed Tumor Therapies”, Medical Faculty, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
| | - Uta Merle
- Department of Internal Medicine IV, University Hospital Heidelberg, 69120 Heidelberg, Germany
| | - Christoph Trautwein
- Werner Siemens Imaging Center, Department for Preclinical Imaging and Radiopharmacy, Eberhard Karls University Tübingen, 72076 Tübingen, Germany
- Correspondence:
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18
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An NMR-Based Model to Investigate the Metabolic Phenoreversion of COVID-19 Patients throughout a Longitudinal Study. Metabolites 2022; 12:metabo12121206. [PMID: 36557244 PMCID: PMC9788519 DOI: 10.3390/metabo12121206] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 11/19/2022] [Accepted: 11/28/2022] [Indexed: 12/03/2022] Open
Abstract
After SARS-CoV-2 infection, the molecular phenoreversion of the immunological response and its associated metabolic dysregulation are required for a full recovery of the patient. This process is patient-dependent due to the manifold possibilities induced by virus severity, its phylogenic evolution and the vaccination status of the population. We have here investigated the natural history of COVID-19 disease at the molecular level, characterizing the metabolic and immunological phenoreversion over time in large cohorts of hospitalized severe patients (n = 886) and non-hospitalized recovered patients that self-reported having passed the disease (n = 513). Non-hospitalized recovered patients do not show any metabolic fingerprint associated with the disease or immune alterations. Acute patients are characterized by the metabolic and lipidomic dysregulation that accompanies the exacerbated immunological response, resulting in a slow recovery time with a maximum probability of around 62 days. As a manifestation of the heterogeneity in the metabolic phenoreversion, age and severity become factors that modulate their normalization time which, in turn, correlates with changes in the atherogenesis-associated chemokine MCP-1. Our results are consistent with a model where the slow metabolic normalization in acute patients results in enhanced atherosclerotic risk, in line with the recent observation of an elevated number of cardiovascular episodes found in post-COVID-19 cohorts.
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19
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Kurano M, Okamoto K, Jubishi D, Hashimoto H, Sakai E, Saigusa D, Kano K, Aoki J, Harada S, Okugawa S, Doi K, Moriya K, Yatomi Y. Dynamic modulations of sphingolipids and glycerophospholipids in COVID-19. Clin Transl Med 2022; 12:e1069. [PMID: 36214754 PMCID: PMC9549873 DOI: 10.1002/ctm2.1069] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 09/14/2022] [Accepted: 09/21/2022] [Indexed: 01/28/2023] Open
Abstract
BACKGROUND A heterogeneous clinical phenotype is a characteristic of coronavirus disease 2019 (COVID-19). Therefore, investigating biomarkers associated with disease severity is important for understanding the mechanisms responsible for this heterogeneity and for developing novel agents to prevent critical conditions. This study aimed to elucidate the modulations of sphingolipids and glycerophospholipids, which have been shown to possess potent biological properties. METHODS We measured the serum sphingolipid and glycerophospholipid levels in a total of 887 samples from 215 COVID-19 subjects, plus 115 control subjects without infectious diseases and 109 subjects with infectious diseases other than COVID-19. RESULTS We observed the dynamic modulations of sphingolipids and glycerophospholipids in the serum of COVID-19 subjects, depending on the time course and severity. The elevation of C16:0 ceramide and lysophosphatidylinositol and decreases in C18:1 ceramide, dihydrosphingosine, lysophosphatidylglycerol, phosphatidylglycerol and phosphatidylinositol were specific to COVID-19. Regarding the association with maximum severity, phosphatidylinositol and phosphatidylcholine species with long unsaturated acyl chains were negatively associated, while lysophosphatidylethanolamine and phosphatidylethanolamine were positively associated with maximum severity during the early phase. Lysophosphatidylcholine and phosphatidylcholine had strong negative correlations with CRP, while phosphatidylethanolamine had strong positive ones. C16:0 ceramide, lysophosphatidylcholine, phosphatidylcholine and phosphatidylethanolamine species with long unsaturated acyl chains had negative correlations with D-dimer, while phosphatidylethanolamine species with short acyl chains and phosphatidylinositol had positive ones. Several species of phosphatidylcholine, phosphatidylethanolamine and sphingomyelin might serve as better biomarkers for predicting severe COVID-19 during the early phase than CRP and D-dimer. Compared with the lipid modulations seen in mice treated with lipopolysaccharide, tissue factor, or histone, the lipid modulations observed in severe COVID-19 were most akin to those in mice administered lipopolysaccharide. CONCLUSION A better understanding of the disturbances in sphingolipids and glycerophospholipids observed in this study will prompt further investigation to develop laboratory testing for predicting maximum severity and/or novel agents to suppress the aggravation of COVID-19.
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Affiliation(s)
- Makoto Kurano
- Department of Clinical Laboratory MedicineGraduate School of MedicineThe University of TokyoTokyoJapan
| | - Koh Okamoto
- Department of Infectious DiseasesGraduate School of MedicineThe University of TokyoTokyoJapan
| | - Daisuke Jubishi
- Department of Infectious DiseasesGraduate School of MedicineThe University of TokyoTokyoJapan
| | - Hideki Hashimoto
- Department of Infectious DiseasesGraduate School of MedicineThe University of TokyoTokyoJapan
| | - Eri Sakai
- Department of Clinical Laboratory MedicineGraduate School of MedicineThe University of TokyoTokyoJapan
| | - Daisuke Saigusa
- Laboratory of Biomedical and Analytical SciencesFaculty of Pharma‐ScienceTeikyo UniversityTokyoJapan
| | - Kuniyuki Kano
- Department of Health ChemistryGraduate School of Pharmaceutical SciencesThe University of TokyoTokyoJapan
| | - Junken Aoki
- Department of Health ChemistryGraduate School of Pharmaceutical SciencesThe University of TokyoTokyoJapan
| | - Sohei Harada
- Department of Infection Control and PreventionThe University of TokyoTokyoJapan
| | - Shu Okugawa
- Department of Infectious DiseasesGraduate School of MedicineThe University of TokyoTokyoJapan
| | - Kent Doi
- Department of Emergency and Critical Care MedicineThe University of Tokyo Hospital, Tokyo, Japan
| | - Kyoji Moriya
- Department of Infectious DiseasesGraduate School of MedicineThe University of TokyoTokyoJapan,Department of Infection Control and PreventionThe University of TokyoTokyoJapan
| | - Yutaka Yatomi
- Department of Clinical Laboratory MedicineGraduate School of MedicineThe University of TokyoTokyoJapan
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20
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Yau A, Fear MW, Gray N, Ryan M, Holmes E, Nicholson JK, Whiley L, Wood FM. Enhancing the accuracy of surgical wound excision following burns trauma via application of Rapid Evaporative IonisationMass Spectrometry (REIMS). Burns 2022; 48:1574-1583. [PMID: 36116996 DOI: 10.1016/j.burns.2022.08.021] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 08/13/2022] [Accepted: 08/30/2022] [Indexed: 11/02/2022]
Abstract
BACKGROUND Surgical wound excision is a necessary procedure for burn patients that require the removal of eschar. The extent of excision is currently guided by clinical judgement, with excessinto healthy tissue potentially leading to excessive scar, or inadequate debridement increasing risk of infection. Thus, an objective real-time measure to facilitate accurate excision could support clinical judgement and improve this surgical procedure. This study was designed to investigate the potential use of Rapid evaporative ionisation mass spectrometry (REIMS) as a tool to support data-driven objective tissue excision. METHODS Data were acquired using a multi-platform approach that consisted of both Rapid Evaporative Ionisation Mass Spectrometry (REIMS) performed on intact skin, and comprehensive liquid chromatography-mass spectrometry (LC-MS/MS) lipidomics performed on homogenised skin tissue extracts. Data were analysed using principal components analysis (PCA) and multivariate orthogonal projections to latent squares discriminant analysis (OPLS-DA) and logistic regression to determine the predictability of the models. RESULTS PCA and OPLS-DA models of the REIMS and LC-MS/MS lipidomics data reported separation of excised and healthy tissue. Molecular fingerprints generated from REIMS analysis of healthy skin tissue revealed a high degree of heterogeneity, however, intra-individual variance was smaller than inter-individual variance. Both platforms indicated high levels of skin classification accuracy. In addition, OPLS-DA of the LC-MS/MS lipidomic data revealed significant differences in specific lipid classes between healthy control and excised skin samples; including lower free fatty acids (FFA), monoacylglycerols (MAG), lysophosphatidylglycerol (LPG) and lysophosphatidylethanolamines (LPE) in excised tissue and higher lactosylceramides (LCER) and cholesterol esters (CE) compared to healthy control tissue. CONCLUSIONS Having established the heterogeneity in the biochemical composition of healthy skin using REIMS and LC-MS/MS, our data show that REIMS has the potential to distinguish between excied and healthy skin tissue samples. This pilot study suggests that REIMS may be an effective tool to support accurate tissue excision during burn surgery.
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Affiliation(s)
- Andrew Yau
- Burn Injury Research Unit, School of Biomedical sciences, University of Western Australia, Perth, WA, Australia
| | - Mark W Fear
- Burn Injury Research Unit, School of Biomedical sciences, University of Western Australia, Perth, WA, Australia; Fiona Wood Foundation, Perth, WA, Australia
| | - Nicola Gray
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia
| | - Monique Ryan
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia
| | - Elaine Holmes
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Institute of Global Health Innovation, Imperial College London, London SW7 2AZ, UK
| | - Luke Whiley
- Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Australian National Phenome Centre, Health Futures Institute, Murdoch University, Perth, WA 6150, Australia; Perron Institute for Neurological and Translational Science, Nedlands, WA 6009, Australia.
| | - Fiona M Wood
- Burn Injury Research Unit, School of Biomedical sciences, University of Western Australia, Perth, WA, Australia; Burns Service WA, WA Department of Health, Perth, WA, Australia; Fiona Wood Foundation, Perth, WA, Australia.
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21
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Ciccarelli M, Merciai F, Carrizzo A, Sommella E, Di Pietro P, Caponigro V, Salviati E, Musella S, Sarno VD, Rusciano M, Toni AL, Iesu P, Izzo C, Schettino G, Conti V, Venturini E, Vitale C, Scarpati G, Bonadies D, Rispoli A, Polverino B, Poto S, Pagliano P, Piazza O, Licastro D, Vecchione C, Campiglia P. Untargeted lipidomics reveals specific lipid profiles in COVID-19 patients with different severity from Campania region (Italy). J Pharm Biomed Anal 2022; 217:114827. [PMID: 35569273 PMCID: PMC9085356 DOI: 10.1016/j.jpba.2022.114827] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Revised: 05/04/2022] [Accepted: 05/05/2022] [Indexed: 02/08/2023]
Abstract
COVID-19 infection evokes various systemic alterations that push patients not only towards severe acute respiratory syndrome but causes an important metabolic dysregulation with following multi-organ alteration and potentially poor outcome. To discover novel potential biomarkers able to predict disease's severity and patient's outcome, in this study we applied untargeted lipidomics, by a reversed phase ultra-high performance liquid chromatography-trapped ion mobility mass spectrometry platform (RP-UHPLC-TIMS-MS), on blood samples collected at hospital admission in an Italian cohort of COVID-19 patients (45 mild, 54 severe, 21 controls). In a subset of patients, we also collected a second blood sample in correspondence of clinical phenotype modification (longitudinal population). Plasma lipid profiles revealed several lipids significantly modified in COVID-19 patients with respect to controls and able to discern between mild and severe clinical phenotype. Severe patients were characterized by a progressive decrease in the levels of LPCs, LPC-Os, PC-Os, and, on the contrary, an increase in overall TGs, PEs, and Ceramides. A machine learning model was built by using both the entire dataset and with a restricted lipid panel dataset, delivering comparable results in predicting severity (AUC= 0.777, CI: 0.639-0.904) and outcome (AUC= 0.789, CI: 0.658-0.910). Finally, re-building the model with 25 longitudinal (t1) samples, this resulted in 21 patients correctly classified. In conclusion, this study highlights specific lipid profiles that could be used monitor the possible trajectory of COVID-19 patients at hospital admission, which could be used in targeted approaches.
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Affiliation(s)
- Michele Ciccarelli
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | - Fabrizio Merciai
- Department of Pharmacy, University of Salerno, Fisciano, SA, Italy,PhD Program in Drug Discovery and Development, University of Salerno, Fisciano, SA, Italy
| | - Albino Carrizzo
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy,IRCCS Neuromed, Loc. Camerelle, Pozzilli, IS, Italy
| | - Eduardo Sommella
- Department of Pharmacy, University of Salerno, Fisciano, SA, Italy
| | - Paola Di Pietro
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | - Vicky Caponigro
- Department of Pharmacy, University of Salerno, Fisciano, SA, Italy
| | | | - Simona Musella
- Department of Pharmacy, University of Salerno, Fisciano, SA, Italy
| | | | | | - Anna Laura Toni
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | - Paola Iesu
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | - Carmine Izzo
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | | | - Valeria Conti
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | | | - Carolina Vitale
- San Giovanni di Dio e Ruggi D'Aragona University Hospital, Salerno, Italy
| | - Giuliana Scarpati
- San Giovanni di Dio e Ruggi D'Aragona University Hospital, Salerno, Italy
| | - Domenico Bonadies
- San Giovanni di Dio e Ruggi D'Aragona University Hospital, Salerno, Italy
| | - Antonella Rispoli
- San Giovanni di Dio e Ruggi D'Aragona University Hospital, Salerno, Italy
| | | | - Sergio Poto
- San Giovanni di Dio e Ruggi D'Aragona University Hospital, Salerno, Italy
| | - Pasquale Pagliano
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | - Ornella Piazza
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | | | - Carmine Vecchione
- Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy,IRCCS Neuromed, Loc. Camerelle, Pozzilli, IS, Italy,Corresponding author at: Department of Medicine and Surgery, University of Salerno, Baronissi, SA, Italy
| | - Pietro Campiglia
- Department of Pharmacy, University of Salerno, Fisciano, SA, Italy,Corresponding author
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22
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Oliveira LB, Mwangi VI, Sartim MA, Delafiori J, Sales GM, de Oliveira AN, Busanello ENB, Val FFDAE, Xavier MS, Costa FT, Baía-da-Silva DC, Sampaio VDS, de Lacerda MVG, Monteiro WM, Catharino RR, de Melo GC. Metabolomic Profiling of Plasma Reveals Differential Disease Severity Markers in COVID-19 Patients. Front Microbiol 2022; 13:844283. [PMID: 35572676 PMCID: PMC9094083 DOI: 10.3389/fmicb.2022.844283] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2021] [Accepted: 03/14/2022] [Indexed: 01/08/2023] Open
Abstract
The severity, disabilities, and lethality caused by the coronavirus 2019 (COVID-19) disease have dumbfounded the entire world on an unprecedented scale. The multifactorial aspect of the infection has generated interest in understanding the clinical history of COVID-19, particularly the classification of severity and early prediction on prognosis. Metabolomics is a powerful tool for identifying metabolite signatures when profiling parasitic, metabolic, and microbial diseases. This study undertook a metabolomic approach to identify potential metabolic signatures to discriminate severe COVID-19 from non-severe COVID-19. The secondary aim was to determine whether the clinical and laboratory data from the severe and non-severe COVID-19 patients were compatible with the metabolomic findings. Metabolomic analysis of samples revealed that 43 metabolites from 9 classes indicated COVID-19 severity: 29 metabolites for non-severe and 14 metabolites for severe disease. The metabolites from porphyrin and purine pathways were significantly elevated in the severe disease group, suggesting that they could be potential prognostic biomarkers. Elevated levels of the cholesteryl ester CE (18:3) in non-severe patients matched the significantly different blood cholesterol components (total cholesterol and HDL, both p < 0.001) that were detected. Pathway analysis identified 8 metabolomic pathways associated with the 43 discriminating metabolites. Metabolomic pathway analysis revealed that COVID-19 affected glycerophospholipid and porphyrin metabolism but significantly affected the glycerophospholipid and linoleic acid metabolism pathways (p = 0.025 and p = 0.035, respectively). Our results indicate that these metabolomics-based markers could have prognostic and diagnostic potential when managing and understanding the evolution of COVID-19.
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Affiliation(s)
- Lucas Barbosa Oliveira
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil
| | - Victor Irungu Mwangi
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil
| | - Marco Aurélio Sartim
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Programas de Pós-Graduação em Imunologia Básica e Aplicada (PPGIBA), Universidade Federal do Amazonas (UFAM), Manaus, Brazil.,Pró-reitoria de Pesquisa e Pós-graduação, Universidade Nilton Lins, Manaus, Brazil
| | - Jeany Delafiori
- Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - Geovana Manzan Sales
- Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - Arthur Noin de Oliveira
- Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - Estela Natacha Brandt Busanello
- Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - Fernando Fonseca de Almeida E Val
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil
| | - Mariana Simão Xavier
- Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil.,Instituto Nacional de Infectologia Evandro Chagas, Fundação Oswaldo Cruz, Rio de Janeiro, Brazil
| | - Fabio Trindade Costa
- Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - Djane Clarys Baía-da-Silva
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil
| | - Vanderson de Souza Sampaio
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil
| | - Marcus Vinicius Guimarães de Lacerda
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil.,Instituto de Pesquisas Leônidas & Maria Deane (FIOCRUZ-Amazonas), Manaus, Brazil
| | - Wuelton Marcelo Monteiro
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil
| | - Rodrigo Ramos Catharino
- Laboratório Innovare de Biomarcadores, Faculdade de Ciências Farmacêuticas, Universidade Estadual de Campinas (UNICAMP), Campinas, Brazil
| | - Gisely Cardoso de Melo
- Programa de Pós-Graduação em Medicina Tropical (PPGMT), Universidade do Estado do Amazonas (UEA), Manaus, Brazil.,Fundação de Medicina Tropical Heitor Vieira Dourado (FMT-HVD), Manaus, Brazil
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23
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Plasma Lipid Profiles Change with Increasing Numbers of Mild Traumatic Brain Injuries in Rats. Metabolites 2022; 12:metabo12040322. [PMID: 35448509 PMCID: PMC9025508 DOI: 10.3390/metabo12040322] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2022] [Revised: 03/23/2022] [Accepted: 03/23/2022] [Indexed: 11/16/2022] Open
Abstract
Mild traumatic brain injury (mTBI) causes structural, cellular and biochemical alterations which are difficult to detect in the brain and may persist chronically following single or repeated injury. Lipids are abundant in the brain and readily cross the blood-brain barrier, suggesting that lipidomic analysis of blood samples may provide valuable insight into the neuropathological state. This study used liquid chromatography-mass spectrometry (LC-MS) to examine plasma lipid concentrations at 11 days following sham (no injury), one (1×) or two (2×) mTBI in rats. Eighteen lipid species were identified that distinguished between sham, 1× and 2× mTBI. Three distinct patterns were found: (1) lipids that were altered significantly in concentration after either 1× or 2× F mTBI: cholesterol ester CE (14:0) (increased), phosphoserine PS (14:0/18:2) and hexosylceramide HCER (d18:0/26:0) (decreased), phosphoinositol PI(16:0/18:2) (increased with 1×, decreased with 2× mTBI); (2) lipids that were altered in response to 1× mTBI only: free fatty acid FFA (18:3 and 20:3) (increased); (3) lipids that were altered in response to 2× mTBI only: HCER (22:0), phosphoethanolamine PE (P-18:1/20:4 and P-18:0/20:1) (increased), lysophosphatidylethanolamine LPE (20:1), phosphocholine PC (20:0/22:4), PI (18:1/18:2 and 20:0/18:2) (decreased). These findings suggest that increasing numbers of mTBI induce a range of changes dependent upon the lipid species, which likely reflect a balance of damage and reparative responses.
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24
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Masuda R, Lodge S, Whiley L, Gray N, Lawler N, Nitschke P, Bong SH, Kimhofer T, Loo RL, Boughton B, Zeng AX, Hall D, Schaefer H, Spraul M, Dwivedi G, Yeap BB, Diercks T, Bernardo-Seisdedos G, Mato JM, Lindon JC, Holmes E, Millet O, Wist J, Nicholson JK. Exploration of Human Serum Lipoprotein Supramolecular Phospholipids Using Statistical Heterospectroscopy in n-Dimensions (SHY- n): Identification of Potential Cardiovascular Risk Biomarkers Related to SARS-CoV-2 Infection. Anal Chem 2022; 94:4426-4436. [PMID: 35230805 DOI: 10.1021/acs.analchem.1c05389] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022]
Abstract
SARS-CoV-2 infection causes a significant reduction in lipoprotein-bound serum phospholipids give rise to supramolecular phospholipid composite (SPC) signals observed in diffusion and relaxation edited 1H NMR spectra. To characterize the chemical structural components and compartmental location of SPC and to understand further its possible diagnostic properties, we applied a Statistical HeterospectroscopY in n-dimensions (SHY-n) approach. This involved statistically linking a series of orthogonal measurements made on the same samples, using independent analytical techniques and instruments, to identify the major individual phospholipid components giving rise to the SPC signals. Thus, an integrated model for SARS-CoV-2 positive and control adults is presented that relates three identified diagnostic subregions of the SPC signal envelope (SPC1, SPC2, and SPC3) generated using diffusion and relaxation edited (DIRE) NMR spectroscopy to lipoprotein and lipid measurements obtained by in vitro diagnostic NMR spectroscopy and ultrahigh-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS). The SPC signals were then correlated sequentially with (a) total phospholipids in lipoprotein subfractions; (b) apolipoproteins B100, A1, and A2 in different lipoproteins and subcompartments; and (c) MS-measured total serum phosphatidylcholines present in the NMR detection range (i.e., PCs: 16.0,18.2; 18.0,18.1; 18.2,18.2; 16.0,18.1; 16.0,20.4; 18.0,18.2; 18.1,18.2), lysophosphatidylcholines (LPCs: 16.0 and 18.2), and sphingomyelin (SM 22.1). The SPC3/SPC2 ratio correlated strongly (r = 0.86) with the apolipoprotein B100/A1 ratio, a well-established marker of cardiovascular disease risk that is markedly elevated during acute SARS-CoV-2 infection. These data indicate the considerable potential of using a serum SPC measurement as a metric of cardiovascular risk based on a single NMR experiment. This is of specific interest in relation to understanding the potential for increased cardiovascular risk in COVID-19 patients and risk persistence in post-acute COVID-19 syndrome (PACS).
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Affiliation(s)
- Reika Masuda
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Samantha Lodge
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Luke Whiley
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Nicola Gray
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Nathan Lawler
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Philipp Nitschke
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Sze-How Bong
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Torben Kimhofer
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Ruey Leng Loo
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Berin Boughton
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Annie X Zeng
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | - Drew Hall
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia
| | | | - Manfred Spraul
- Bruker Biospin GmbH, Silberstreifen, Ettlingen 76275, Germany
| | - Girish Dwivedi
- Department of Cardiology, Fiona Stanley Hospital, Medical School, University of Western Australia, Perth 6150, Western Australia, Australia
| | - Bu B Yeap
- Department of Endocrinology and Diabetes, Fiona Stanley Hospital, Medical School, University of Western Australia, Perth 6150, Western Australia, Australia
| | - Tammo Diercks
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - Ganeko Bernardo-Seisdedos
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - José M Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - John C Lindon
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - Elaine Holmes
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia.,Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160 Derio, Spain
| | - Julien Wist
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia.,Chemistry Department, Universidad del Valle, 76001 Cali, Colombia
| | - Jeremy K Nicholson
- Australian National Phenome Center, and Center for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth 6150, Western Australia, Australia.,Department of Cardiology, Fiona Stanley Hospital, Medical School, University of Western Australia, Perth 6150, Western Australia, Australia.,Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K
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25
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Nitschke P, Lodge S, Kimhofer T, Masuda R, Bong SH, Hall D, Schäfer H, Spraul M, Pompe N, Diercks T, Bernardo-Seisdedos G, Mato JM, Millet O, Susic D, Henry A, El-Omar EM, Holmes E, Lindon JC, Nicholson JK, Wist J. J-Edited DIffusional Proton Nuclear Magnetic Resonance Spectroscopic Measurement of Glycoprotein and Supramolecular Phospholipid Biomarkers of Inflammation in Human Serum. Anal Chem 2022; 94:1333-1341. [DOI: 10.1021/acs.analchem.1c04576] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Philipp Nitschke
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Torben Kimhofer
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Reika Masuda
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Sze-How Bong
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Drew Hall
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
| | - Hartmut Schäfer
- Bruker Biospin GmbH, Silberstreifen, 76287, Rheinstetten 76287, Germany
| | - Manfred Spraul
- Bruker Biospin GmbH, Silberstreifen, 76287, Rheinstetten 76287, Germany
| | - Niels Pompe
- Bruker Biospin GmbH, Silberstreifen, 76287, Rheinstetten 76287, Germany
| | - Tammo Diercks
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - Ganeko Bernardo-Seisdedos
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - José M. Mato
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio 48160, Spain
| | - Daniella Susic
- School of Women’s and Children’s Health, University of New South Wales, Sydney, New South Wales 2052, Australia
- UNSW Microbiome Research Centre, St George Hospital, Kogarah, New South Wales 2217, Australia
| | - Amanda Henry
- School of Women’s and Children’s Health, University of New South Wales, Sydney, New South Wales 2052, Australia
- UNSW Microbiome Research Centre, St George Hospital, Kogarah, New South Wales 2217, Australia
| | - Emad M El-Omar
- Microbiome Research Centre, St George & Sutherland Clinical School, University of New South Wales, Sydney, New South Wales 2052, Australia
| | - Elaine Holmes
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - John C. Lindon
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, U.K
| | - Jeremy K. Nicholson
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
- Institute of Global Health Innovation Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K
| | - Julien Wist
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, Western Australia 6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
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26
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Nitschke P, Lodge S, Hall D, Schaefer H, Spraul M, Embade N, Millet O, Holmes E, Wist J, Nicholson JK. Direct low field J-edited diffusional proton NMR spectroscopic measurement of COVID-19 inflammatory biomarkers in human serum. Analyst 2022; 147:4213-4221. [DOI: 10.1039/d2an01097f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
A JEDI NMR pulse experiment incorporating relaxation, diffusion and J-modulation peak editing was implemented at a low field (80 MHz) spectrometer system to quantify two recently discovered plasma markers of SARS-CoV-2 infection and general inflammation.
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Affiliation(s)
- Philipp Nitschke
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
| | - Samantha Lodge
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
| | - Drew Hall
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
| | - Hartmut Schaefer
- Bruker Biospin GmbH, Rudolf-Plank Strasse 23, 76275 Ettlingen, Germany
| | - Manfred Spraul
- Bruker Biospin GmbH, Rudolf-Plank Strasse 23, 76275 Ettlingen, Germany
| | - Nieves Embade
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio, Spain
| | - Oscar Millet
- Precision Medicine and Metabolism Laboratory, CIC bioGUNE, Parque Tecnológico de Bizkaia, Bld. 800, 48160, Derio, Spain
| | - Elaine Holmes
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington, London SW7 2AZ, UK
| | - Julien Wist
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Chemistry Department, Universidad del Valle, Cali 76001, Colombia
| | - Jeremy K. Nicholson
- Australian National Phenome Centre and Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Institute of Global Health Innovation, Faculty of Medicine, Imperial College London, Level 1, Faculty Building, South Kensington Campus, London, SW7 2NA, UK
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27
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Spick M, Lewis HM, Wilde MJ, Hopley C, Huggett J, Bailey MJ. Systematic review with meta-analysis of diagnostic test accuracy for COVID-19 by mass spectrometry. Metabolism 2022; 126:154922. [PMID: 34715115 PMCID: PMC8548837 DOI: 10.1016/j.metabol.2021.154922] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/27/2021] [Accepted: 10/21/2021] [Indexed: 12/12/2022]
Abstract
BACKGROUND The global COVID-19 pandemic has led to extensive development in many fields, including the diagnosis of COVID-19 infection by mass spectrometry. The aim of this systematic review and meta-analysis was to assess the accuracy of mass spectrometry diagnostic tests developed so far, across a wide range of biological matrices, and additionally to assess risks of bias and applicability in studies published to date. METHOD 23 retrospective observational cohort studies were included in the systematic review using the PRISMA-DTA framework, with a total of 2858 COVID-19 positive participants and 2544 controls. Risks of bias and applicability were assessed via a QUADAS-2 questionnaire. A meta-analysis was also performed focusing on sensitivity, specificity, diagnostic accuracy and Youden's Index, in addition to assessing heterogeneity. FINDINGS Sensitivity averaged 0.87 in the studies reviewed herein (interquartile range 0.81-0.96) and specificity 0.88 (interquartile range 0.82-0.98), with an area under the receiver operating characteristic summary curve of 0.93. By subgroup, the best diagnostic results were achieved by viral proteomic analyses of nasopharyngeal swabs and metabolomic analyses of plasma and serum. The performance of other sampling matrices (breath, sebum, saliva) was less good, indicating that these protocols are currently insufficiently mature for clinical application. CONCLUSIONS This systematic review and meta-analysis demonstrates the potential for mass spectrometry and 'omics in achieving accurate test results for COVID-19 diagnosis, but also highlights the need for further work to optimize and harmonize practice across laboratories before these methods can be translated to clinical applications.
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Affiliation(s)
- Matt Spick
- Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK
| | - Holly M Lewis
- Surrey Ion Beam Centre, University of Surrey, Guildford GU2 7XH, UK
| | - Michael J Wilde
- School of Chemistry, University of Leicester, Leicester LE1 7RH, UK
| | - Christopher Hopley
- National Measurement Laboratory, LGC, Queens Road, Teddington TW11 0LY, UK
| | - Jim Huggett
- National Measurement Laboratory, LGC, Queens Road, Teddington TW11 0LY, UK; School of Biosciences and Medicine, University of Surrey, Guildford GU2 7XH, UK
| | - Melanie J Bailey
- Faculty of Engineering and Physical Sciences, University of Surrey, Guildford GU2 7XH, UK; Surrey Ion Beam Centre, University of Surrey, Guildford GU2 7XH, UK.
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28
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Miller L, Berber E, Sumbria D, Rouse BT. Controlling the Burden of COVID-19 by Manipulating Host Metabolism. Viral Immunol 2022; 35:24-32. [PMID: 34905407 PMCID: PMC8863913 DOI: 10.1089/vim.2021.0150] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic caused by the coronavirus-severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) continues to cause global health problems, but its impact would be minimized if the many effective vaccines that have been developed were available and in widespread use by all societies. This ideal situation is not occurring so other means of controlling COVID-19 are needed. In this short review, we make the case that manipulating host metabolic pathways could be a therapeutic approach worth exploring. The rationale for such an approach comes from the fact that viruses cause metabolic changes in cells they infect, effective host defense mechanisms against viruses requires the activity of one or more metabolic pathways, and that hosts with metabolic defects such as diabetes are more susceptible to severe consequences after COVID-19. We describe the types of approaches that could be used to redirect various aspects of host metabolism and the success that some of these maneuvers have had at controlling other virus infections. Manipulating metabolic activities to control the outcome of COVID-19 has to date received minimal attention. Manipulating host metabolism will never replace vaccines to control COVID-19 but could be used as an adjunct therapy to the extent of ongoing infection.
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Affiliation(s)
- Logan Miller
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee, USA
| | - Engin Berber
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee, USA
| | - Deepak Sumbria
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee, USA
| | - Barry T. Rouse
- Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, Tennessee, USA
- Address correspondence to: Dr. Barry T. Rouse, Department of Biomedical and Diagnostic Sciences, College of Veterinary Medicine, University of Tennessee, Knoxville, TN 37996-4539, USA
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29
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Zhou R, Lv X, Chen T, Chen Q, Tian H, Yang C, Guo W, Liu C. Construction and external validation of a 5-gene random forest model to diagnose non-obstructive azoospermia based on the single-cell RNA sequencing of testicular tissue. Aging (Albany NY) 2021; 13:24219-24235. [PMID: 34738918 PMCID: PMC8610122 DOI: 10.18632/aging.203675] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 10/28/2021] [Indexed: 01/02/2023]
Abstract
Non-obstructive azoospermia (NOA) is among the most severe factors for male infertility, but our understandings of the latent biological mechanisms remain insufficient. The single-cell RNA sequencing (scRNA-seq) data of 432 testicular cells isolated from the patient with NOA was analyzed, and the cell samples were grouped into 5 cell clusters. A sum of 455 cell markers was identified and then included in the protein-protein interaction network. The Top 5 most critical genes in the network, including CCT8, CDC6, PSMD1, RPS4X, RPL36A, were selected for the diagnosis model construction through the random forest (RF). The RF model was a strong classifier for NOA and obstructive azoospermia (OA), which was validated in the training cohort (n = 58, AUC = 1) and external validation cohort (n = 20, AUC = 0.9). We collected the seminal plasma samples and testicular biopsy samples from 20 OA and 20 NOA cases from the local hospital, and the gene expression was detected via Real-Time quantitative Polymerase Chain Reaction (RT-qPCR) and Immunohistochemistry. The RF model also exhibited high accuracy (AUC = 0.725) in the local cohort. In summary, a novel gene signature was developed and externally validated based on scRNA-seq analysis, providing some new biomarkers to uncover the underlying mechanisms and a promising clinical tool for diagnosis in NOA.
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Affiliation(s)
- Ranran Zhou
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Xianyuan Lv
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Tianle Chen
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Qi Chen
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Hu Tian
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Cheng Yang
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Wenbin Guo
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Cundong Liu
- Department of Urology, The Third Affiliated Hospital of Southern Medical University, Guangzhou, China.,The Third School of Clinical Medicine, Southern Medical University, Guangzhou, China
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