1
|
Beger RD, Goodacre R, Jones CM, Lippa KA, Mayboroda OA, O'Neill D, Najdekr L, Ntai I, Wilson ID, Dunn WB. Analysis types and quantification methods applied in UHPLC-MS metabolomics research: a tutorial. Metabolomics 2024; 20:95. [PMID: 39110307 PMCID: PMC11306277 DOI: 10.1007/s11306-024-02155-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2024] [Accepted: 07/16/2024] [Indexed: 08/10/2024]
Abstract
BACKGROUND Different types of analytical methods, with different characteristics, are applied in metabolomics and lipidomics research and include untargeted, targeted and semi-targeted methods. Ultra High Performance Liquid Chromatography-Mass Spectrometry is one of the most frequently applied measurement instruments in metabolomics because of its ability to detect a large number of water-soluble and lipid metabolites over a wide range of concentrations in short analysis times. Methods applied for the detection and quantification of metabolites differ and can either report a (normalised) peak area or an absolute concentration. AIM OF REVIEW In this tutorial we aim to (1) define similarities and differences between different analytical approaches applied in metabolomics and (2) define how amounts or absolute concentrations of endogenous metabolites can be determined together with the advantages and limitations of each approach in relation to the accuracy and precision when concentrations are reported. KEY SCIENTIFIC CONCEPTS OF REVIEW The pre-analysis knowledge of metabolites to be targeted, the requirement for (normalised) peak responses or absolute concentrations to be reported and the number of metabolites to be reported define whether an untargeted, targeted or semi-targeted method is applied. Fully untargeted methods can only provide (normalised) peak responses and fold changes which can be reported even when the structural identity of the metabolite is not known. Targeted methods, where the analytes are known prior to the analysis, can also report fold changes. Semi-targeted methods apply a mix of characteristics of both untargeted and targeted assays. For the reporting of absolute concentrations of metabolites, the analytes are not only predefined but optimized analytical methods should be developed and validated for each analyte so that the accuracy and precision of concentration data collected for biological samples can be reported as fit for purpose and be reviewed by the scientific community.
Collapse
Affiliation(s)
- Richard D Beger
- National Center for Toxicological Research, US Food and Drug Administration, Jefferson, AR, 72079, USA
| | - Royston Goodacre
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Christina M Jones
- Office of Advanced Manufacturing, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Katrice A Lippa
- Office of Weights and Measures, National Institute of Standards and Technology, Gaithersburg, MD, 20899, USA
| | - Oleg A Mayboroda
- Center for Proteomics and Metabolomics, Leiden University Medical Centre, Leiden, The Netherlands
| | - Donna O'Neill
- School of Biosciences and Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Lukas Najdekr
- Faculty of Medicine and Dentistry, Institute of Molecular and Translational Medicine, Palacký University Olomouc, 779 00, Olomouc, Czech Republic
| | - Ioanna Ntai
- BioMarin Pharmaceutical Inc., San Rafael, CA, USA
| | - Ian D Wilson
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
- Computational and Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Warwick B Dunn
- Department of Biochemistry, Cell and Systems Biology, Centre for Metabolomics Research, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK.
| |
Collapse
|
2
|
Ryan M, 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 2024; 23:2893-2907. [PMID: 38104259 PMCID: PMC11302432 DOI: 10.1021/acs.jproteome.3c00516] [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: 08/16/2023] [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.
Collapse
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
| |
Collapse
|
3
|
Lodge S, Litton E, Gray N, Ryan M, Millet O, Fear M, Raby E, Currie A, Wood F, Holmes E, Wist J, Nicholson JK. Stratification of Sepsis Patients on Admission into the Intensive Care Unit According to Differential Plasma Metabolic Phenotypes. J Proteome Res 2024; 23:1328-1340. [PMID: 38513133 PMCID: PMC11002934 DOI: 10.1021/acs.jproteome.3c00803] [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: 11/20/2023] [Revised: 02/15/2024] [Accepted: 03/07/2024] [Indexed: 03/23/2024]
Abstract
Delayed diagnosis of patients with sepsis or septic shock is associated with increased mortality and morbidity. UPLC-MS and NMR spectroscopy were used to measure panels of lipoproteins, lipids, biogenic amines, amino acids, and tryptophan pathway metabolites in blood plasma samples collected from 152 patients within 48 h of admission into the Intensive Care Unit (ICU) where 62 patients had no sepsis, 71 patients had sepsis, and 19 patients had septic shock. Patients with sepsis or septic shock had higher concentrations of neopterin and lower levels of HDL cholesterol and phospholipid particles in comparison to nonsepsis patients. Septic shock could be differentiated from sepsis patients based on different concentrations of 10 lipids, including significantly lower concentrations of five phosphatidylcholine species, three cholesterol esters, one dihydroceramide, and one phosphatidylethanolamine. The Supramolecular Phospholipid Composite (SPC) was reduced in all ICU patients, while the composite markers of acute phase glycoproteins were increased in the sepsis and septic shock patients within 48 h admission into ICU. We show that the plasma metabolic phenotype obtained within 48 h of ICU admission is diagnostic for the presence of sepsis and that septic shock can be differentiated from sepsis based on the lipid profile.
Collapse
Affiliation(s)
- Samantha Lodge
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Edward Litton
- Intensive
Care Unit, Fiona Stanley Hospital, Murdoch, WA 6150, Australia
- Intensive
Care Unit, St John of God Hospital, Subiaco, WA 6009, Australia
- School
of Medicine, University of Western Australia, Crawley, WA 6009, Australia
| | - Nicola Gray
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Monique Ryan
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- Center
for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA 6150, Australia
| | - Oscar Millet
- Precision
Medicine and Metabolism Laboratory, CIC
bioGUNE, Parque Tecnológico
de Bizkaia, Bld. 800, Derio 48160, Spain
| | - Mark Fear
- Burn
Injury Research Unit, School of Biomedical Sciences, University of Western Australia, Perth, WA 6009, Australia
- Fiona
Wood Foundation, Perth, WA 6150, Australia
| | - Edward Raby
- Department
of Infectious Diseases, Fiona Stanley Hospital, Murdoch, WA 6150, Australia
| | - Andrew Currie
- School
of Medical, Molecular & Forensic Sciences, Murdoch University, Perth, WA 6150, Australia
- Centre
for Molecular Medicine & Innovative Therapeutics, Murdoch University, Perth, WA 6150, Australia
- Wesfarmers
Centre for Vaccines and Infectious Diseases, Telethon Kids Institute, University of Western Australia, Perth, WA 6009, Australia
| | - Fiona Wood
- Burn
Injury Research Unit, School of Biomedical Sciences, University of Western Australia, Perth, WA 6009, Australia
- Fiona
Wood Foundation, Perth, WA 6150, Australia
- Burns
service of Western Australia, WA Department
of Health, Murdoch, WA 6150, Australia
| | - Elaine Holmes
- 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, Level 1, Faculty Building, South Kensington Campus, London SW7 2NA, U.K.
| | - Julien Wist
- Australian
National Phenome Center, Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA6150, Australia
- 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
- 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 Center, 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, U.K.
| |
Collapse
|
4
|
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.
Collapse
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
| |
Collapse
|
5
|
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).
Collapse
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
| |
Collapse
|
6
|
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.
Collapse
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
| |
Collapse
|
7
|
Badal BD, Cox IJ, Bajaj JS. Are we ready to translate metabolomics into clinical practice for ACLF prediction and diagnosis? J Hepatol 2023; 79:1082-1084. [PMID: 37734684 DOI: 10.1016/j.jhep.2023.09.012] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 09/05/2023] [Accepted: 09/08/2023] [Indexed: 09/23/2023]
Affiliation(s)
- Bryan D Badal
- Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University and Richmond VA Medical Center, Richmond, Virginia, USA
| | - I Jane Cox
- The Roger Williams Institute of Hepatology, Foundation for Liver Research, London, UK; Faculty of Life Sciences & Medicine, King's College London, United Kingdom
| | - Jasmohan S Bajaj
- Division of Gastroenterology, Hepatology and Nutrition, Virginia Commonwealth University and Richmond VA Medical Center, Richmond, Virginia, USA.
| |
Collapse
|