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Mosley JD, Schock TB, Beecher CW, Dunn WB, Kuligowski J, Lewis MR, Theodoridis G, Ulmer Holland CZ, Vuckovic D, Wilson ID, Zanetti KA. Establishing a framework for best practices for quality assurance and quality control in untargeted metabolomics. Metabolomics 2024; 20:20. [PMID: 38345679 PMCID: PMC10861687 DOI: 10.1007/s11306-023-02080-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Accepted: 12/11/2023] [Indexed: 02/15/2024]
Abstract
BACKGROUND Quality assurance (QA) and quality control (QC) practices are key tenets that facilitate study and data quality across all applications of untargeted metabolomics. These important practices will strengthen this field and accelerate its success. The Best Practices Working Group (WG) within the Metabolomics Quality Assurance and Quality Control Consortium (mQACC) focuses on community use of QA/QC practices and protocols and aims to identify, catalogue, harmonize, and disseminate current best practices in untargeted metabolomics through community-driven activities. AIM OF REVIEW A present goal of the Best Practices WG is to develop a working strategy, or roadmap, that guides the actions of practitioners and progress in the field. The framework in which mQACC operates promotes the harmonization and dissemination of current best QA/QC practice guidance and encourages widespread adoption of these essential QA/QC activities for liquid chromatography-mass spectrometry. KEY SCIENTIFIC CONCEPTS OF REVIEW Community engagement and QA/QC information gathering activities have been occurring through conference workshops, virtual and in-person interactive forum discussions, and community surveys. Seven principal QC stages prioritized by internal discussions of the Best Practices WG have received participant input, feedback and discussion. We outline these stages, each involving a multitude of activities, as the framework for identifying QA/QC best practices. The ultimate planned product of these endeavors is a "living guidance" document of current QA/QC best practices for untargeted metabolomics that will grow and change with the evolution of the field.
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Affiliation(s)
- Jonathan D Mosley
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Athens, GA, 30605, USA.
| | - Tracey B Schock
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Charleston, SC, 29412, USA
| | | | - Warwick B Dunn
- Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
| | - Julia Kuligowski
- Neonatal Research Group, Health Research Institute La Fe, 46026, Valencia, Spain
| | - Matthew R Lewis
- Life Sciences Mass Spectrometry Division, Bruker UK Limited, Coventry, CV4 8HZ, UK
- National Phenome Centre & Division of Systems Medicine, Department of Metabolism, Digestion & Reproduction, Imperial College London, London, W12 0NN, UK
| | - Georgios Theodoridis
- BIOMIC_Auth, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Aristotle University Thessaloniki, 57001, Thermi, Greece
| | - Candice Z Ulmer Holland
- Eastern Laboratory, Office of Public Health Science (OPHS), Food Safety and Inspection Service (FSIS), Department of Agriculture (USDA), Athens, GA, 30605, USA
| | - Dajana Vuckovic
- Department of Chemistry and Biochemistry, Concordia University, Montreal, QC, H4B 1R6, Canada
| | - Ian D Wilson
- Centre for Metabolomics Research, Department of Biochemistry, Cell and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, Liverpool, L69 7ZB, UK
- Division of Systems Medicine, Department of Metabolism Department of Metabolism, Digestion and Reproduction, Imperial College, London, W12 0NN, UK
| | - Krista A Zanetti
- Office of Nutrition Research, Office of the Director, Division of Program Coordination, Planning, and Strategic Initiatives, National Institutes of Health, Bethesda, MD, USA
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Kragsnaes MS, Miguens Blanco J, Mullish BH, Serrano‐Contreras JI, Kjeldsen J, Horn HC, Pedersen JK, Munk HL, Nilsson AC, Salam A, Lewis MR, Chekmeneva E, Kristiansen K, Marchesi JR, Ellingsen T. Small Intestinal Permeability and Metabolomic Profiles in Feces and Plasma Associate With Clinical Response in Patients With Active Psoriatic Arthritis Participating in a Fecal Microbiota Transplantation Trial: Exploratory Findings From the FLORA Trial. ACR Open Rheumatol 2023; 5:583-593. [PMID: 37736702 PMCID: PMC10642255 DOI: 10.1002/acr2.11604] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 08/17/2023] [Accepted: 08/22/2023] [Indexed: 09/23/2023] Open
Abstract
OBJECTIVE We investigated intestinal permeability and fecal, plasma, and urine metabolomic profiles in methotrexate-treated active psoriatic arthritis (PsA) and how this related to clinical response following one sham or fecal microbiota transplantation (FMT). METHODS This exploratory study is based on the FLORA trial cohort, in which 31 patients with moderate-to-high peripheral PsA disease activity, despite at least 3 months of methotrexate-treatment, were included in a 26-week, double-blind, 1:1 randomized, sham-controlled trial. Participants were randomly allocated to receive either one healthy donor FMT (n = 15) or sham (n = 16) via gastroscopy. The primary trial end point was the proportion of treatment failures through 26 weeks. We performed a lactulose-to-mannitol ratio (LMR) test at baseline (n = 31) and at week 26 (n = 26) to assess small intestinal permeability. Metabolomic profiles in fecal, plasma, and urine samples collected at baseline, weeks 4, 12, and 26 were measured using 1 H Nuclear Magnetic Resonance. RESULTS Trial failures (n = 7) had significantly higher LMR compared with responders (n = 19) at week 26 (0.027 [0.017-0.33]) vs. 0.012 [0-0.064], P = 0.013), indicating increased intestinal permeability. Multivariate analysis revealed a significant model for responders (n = 19) versus failures (n = 12) at all time points based on their fecal (P < 0.0001) and plasma (P = 0.005) metabolomic profiles, whereas urine metabolomic profiles did not differ between groups (P = 1). Fecal N-acetyl glycoprotein GlycA correlated with Health Assessment Questionnaire Disability Index (coefficient = 0.50; P = 0.03) and fecal propionate correlated with American College of Rheumatology 20 response at week 26 (coefficient = 27, P = 0.02). CONCLUSION Intestinal permeability and fecal and plasma metabolomic profiles of patients with PsA were associated with the primary clinical trial end point, failure versus responder.
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Affiliation(s)
| | | | - Benjamin H. Mullish
- Imperial College London and St. Mary's Hospital, Imperial College Healthcare National Health Service TrustLondonUK
| | | | - Jens Kjeldsen
- Odense University Hospital and University of Southern DenmarkOdenseDenmark
| | | | | | | | | | - Ash Salam
- Imperial College London, Hammersmith Hospital CampusLondonUK
| | | | | | - Karsten Kristiansen
- University of Copenhagen, Copenhagen, Denmark, and Institute of Metagenomics, Qingdao‐Europe Advanced Institute for Life SciencesQingdaoChina
| | | | - Torkell Ellingsen
- Odense University Hospital and University of Southern DenmarkOdenseDenmark
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Kowalka AM, Alexiadou K, Cuenco J, Clarke RE, Minnion J, Williams EL, Bech P, Purkayastha S, Ahmed AR, Takats Z, Whitwell HJ, Romero MG, Bloom SR, Camuzeaux S, Lewis MR, Khoo B, Tan TM. The postprandial secretion of peptide YY 1-36 and 3-36 in obesity is differentially increased after gastric bypass versus sleeve gastrectomy. Clin Endocrinol (Oxf) 2023; 99:272-284. [PMID: 36345253 PMCID: PMC10952770 DOI: 10.1111/cen.14846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Revised: 10/13/2022] [Accepted: 11/04/2022] [Indexed: 11/09/2022]
Abstract
OBJECTIVES Peptide tyrosine tyrosine (PYY) exists as two species, PYY1-36 and PYY3-36 , with distinct effects on insulin secretion and appetite regulation. The detailed effects of bariatric surgery on PYY1-36 and PYY3-36 secretion are not known as previous studies have used nonspecific immunoassays to measure total PYY. Our objective was to characterize the effect of sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB) on fasting and postprandial PYY1-36 and PYY3-36 secretion using a newly developed liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay. DESIGN AND SUBJECTS Observational study in 10 healthy nonobese volunteers and 30 participants with obesity who underwent RYGB (n = 24) or SG (n = 6) at the Imperial Weight Centre [NCT01945840]. Participants were studied using a standardized mixed meal test (MMT) before and 1 year after surgery. The outcome measures were PYY1-36 and PYY3-36 concentrations. RESULTS Presurgery, the fasting and postprandial levels of PYY1-36 and PYY3-36 were low, with minimal responses to the MMT, and these did not differ from healthy nonobese volunteers. The postprandial secretion of both PYY1-36 and PYY3-36 at 1 year was amplified after RYGB, but not SG, with the response being significantly higher in RYGB compared with SG. CONCLUSIONS There appears to be no difference in PYY secretion between nonobese and obese volunteers at baseline. At 1 year after surgery, RYGB, but not SG, is associated with increased postprandial secretion of PYY1-36 and PYY3-36 , which may account for long-term differences in efficacy and adverse effects between the two types of surgery.
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Affiliation(s)
- Anna M. Kowalka
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Kleopatra Alexiadou
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Joyceline Cuenco
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | | | - James Minnion
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Emma L. Williams
- Department of Clinical Biochemistry, North West London PathologyCharing Cross HospitalLondonUK
| | - Paul Bech
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Sanjay Purkayastha
- Department of Surgery and CancerImperial College Healthcare NHS TrustLondonUK
| | - Ahmed R. Ahmed
- Department of Surgery and CancerImperial College Healthcare NHS TrustLondonUK
| | - Zoltan Takats
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Harry J. Whitwell
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Maria Gomez Romero
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Stephen R. Bloom
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Stephane Camuzeaux
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Matthew R. Lewis
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Bernard Khoo
- Endocrinology, Division of MedicineUniversity College LondonLondonUK
| | - Tricia M.‐M. Tan
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
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Kowalka AM, Alexiadou K, Cuenco J, Clarke RE, Camuzeaux S, Minnion J, Williams EL, Bech P, Purkayastha S, Ahmed AR, Takats Z, Khoo B, Whitwell HJ, Romero MG, Bloom SR, Lewis MR, Tan TM. Commentary on "The road to reliable peptide assays is paved with good guidelines". Clin Endocrinol (Oxf) 2023; 98:763-765. [PMID: 36915993 PMCID: PMC10952462 DOI: 10.1111/cen.14894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 02/14/2023] [Indexed: 03/16/2023]
Affiliation(s)
- Anna M. Kowalka
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Kleopatra Alexiadou
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Joyceline Cuenco
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | | | - Stephane Camuzeaux
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - James Minnion
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Emma L. Williams
- Department of Clinical Biochemistry, North West London PathologyCharing Cross HospitalLondonUK
| | - Paul Bech
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Sanjay Purkayastha
- Department of Surgery and CancerImperial College Healthcare NHS TrustLondonUK
| | - Ahmed R. Ahmed
- Department of Surgery and CancerImperial College Healthcare NHS TrustLondonUK
| | - Zoltan Takats
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Bernard Khoo
- Endocrinology, Division of MedicineUniversity College LondonLondonUK
| | - Harry J. Whitwell
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Maria G. Romero
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Stephen R. Bloom
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
| | - Matthew R. Lewis
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
- National Phenome CentreImperial College LondonLondonUK
| | - Tricia M.‐M. Tan
- Section of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and ReproductionImperial College LondonLondonUK
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Alexander JL, Posma JM, Scott A, Poynter L, Mason SE, Doria ML, Herendi L, Roberts L, McDonald JAK, Cameron S, Hughes DJ, Liska V, Susova S, Soucek P, der Sluis VHV, Gomez-Romero M, Lewis MR, Hoyles L, Woolston A, Cunningham D, Darzi A, Gerlinger M, Goldin R, Takats Z, Marchesi JR, Teare J, Kinross J. Pathobionts in the tumour microbiota predict survival following resection for colorectal cancer. Microbiome 2023; 11:100. [PMID: 37158960 PMCID: PMC10165813 DOI: 10.1186/s40168-023-01518-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2022] [Accepted: 03/15/2023] [Indexed: 05/10/2023]
Abstract
BACKGROUND AND AIMS The gut microbiota is implicated in the pathogenesis of colorectal cancer (CRC). We aimed to map the CRC mucosal microbiota and metabolome and define the influence of the tumoral microbiota on oncological outcomes. METHODS A multicentre, prospective observational study was conducted of CRC patients undergoing primary surgical resection in the UK (n = 74) and Czech Republic (n = 61). Analysis was performed using metataxonomics, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS), targeted bacterial qPCR and tumour exome sequencing. Hierarchical clustering accounting for clinical and oncological covariates was performed to identify clusters of bacteria and metabolites linked to CRC. Cox proportional hazards regression was used to ascertain clusters associated with disease-free survival over median follow-up of 50 months. RESULTS Thirteen mucosal microbiota clusters were identified, of which five were significantly different between tumour and paired normal mucosa. Cluster 7, containing the pathobionts Fusobacterium nucleatum and Granulicatella adiacens, was strongly associated with CRC (PFDR = 0.0002). Additionally, tumoral dominance of cluster 7 independently predicted favourable disease-free survival (adjusted p = 0.031). Cluster 1, containing Faecalibacterium prausnitzii and Ruminococcus gnavus, was negatively associated with cancer (PFDR = 0.0009), and abundance was independently predictive of worse disease-free survival (adjusted p = 0.0009). UPLC-MS analysis revealed two major metabolic (Met) clusters. Met 1, composed of medium chain (MCFA), long-chain (LCFA) and very long-chain (VLCFA) fatty acid species, ceramides and lysophospholipids, was negatively associated with CRC (PFDR = 2.61 × 10-11); Met 2, composed of phosphatidylcholine species, nucleosides and amino acids, was strongly associated with CRC (PFDR = 1.30 × 10-12), but metabolite clusters were not associated with disease-free survival (p = 0.358). An association was identified between Met 1 and DNA mismatch-repair deficiency (p = 0.005). FBXW7 mutations were only found in cancers predominant in microbiota cluster 7. CONCLUSIONS Networks of pathobionts in the tumour mucosal niche are associated with tumour mutation and metabolic subtypes and predict favourable outcome following CRC resection. Video Abstract.
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Affiliation(s)
- James L Alexander
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK
- Department of Gastroenterology, Imperial College Healthcare NHS Trust, London, UK
| | - Joram M Posma
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Alasdair Scott
- Department of Surgery & Cancer, Imperial College London, London, UK
| | - Liam Poynter
- Department of Surgery & Cancer, Imperial College London, London, UK
| | - Sam E Mason
- Department of Surgery & Cancer, Imperial College London, London, UK
| | - M Luisa Doria
- Department of Surgery & Cancer, Imperial College London, London, UK
| | - Lili Herendi
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, UK
| | - Lauren Roberts
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK
| | - Julie A K McDonald
- Department of Life Sciences, MRC Centre for Molecular Bacteriology and Infection, Imperial College London, London, UK
| | - Simon Cameron
- Institute of Global Food Security, School of Biosciences, Queen's University Belfast, Belfast, UK
| | - David J Hughes
- Cancer Biology and Therapeutics Group, School of Biomolecular and Biomedical Science, UCD Conway Institute, University College Dublin, Dublin, Ireland
| | - Vaclav Liska
- Department of Surgery, Faculty Hospital and Faculty of Medicine in Pilsen, Charles University in Prague, Pilsen, Czech Republic
| | - Simona Susova
- Faculty of Medicine in Pilsen, Biomedical Centre, Charles University in Prague, Pilsen, Czech Republic
| | - Pavel Soucek
- Faculty of Medicine in Pilsen, Biomedical Centre, Charles University in Prague, Pilsen, Czech Republic
| | - Verena Horneffer-van der Sluis
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, UK
| | - Maria Gomez-Romero
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, UK
| | - Matthew R Lewis
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, UK
| | - Lesley Hoyles
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK
- Department of Biosciences, Nottingham Trent University, Nottingham, NG11 8NS, UK
| | - Andrew Woolston
- Translational Oncogenomics Laboratory, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK
| | - David Cunningham
- GI Cancer Unit, Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, UK
| | - Ara Darzi
- Department of Surgery & Cancer, Imperial College London, London, UK
| | - Marco Gerlinger
- Translational Oncogenomics Laboratory, The Institute of Cancer Research, 237 Fulham Road, London, SW3 6JB, UK
- GI Cancer Unit, Department of Medical Oncology, Royal Marsden NHS Foundation Trust, London, UK
| | - Robert Goldin
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK
| | - Zoltan Takats
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, National Phenome Centre, Imperial College London, London, UK
| | - Julian R Marchesi
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Imperial College London, 10th Floor, QEQM Building, St. Mary's Hospital, Praed Street, London, W2 1NY, UK.
| | - Julian Teare
- Department of Surgery & Cancer, Imperial College London, London, UK
| | - James Kinross
- Department of Surgery & Cancer, Imperial College London, London, UK
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Stebbing J, Takis PG, Sands CJ, Maslen L, Lewis MR, Gleason K, Page K, Guttery D, Fernandez-Garcia D, Primrose L, Shaw JA. Comparison of phenomics and cfDNA in a large breast screening population: the Breast Screening and Monitoring Study (BSMS). Oncogene 2023; 42:825-832. [PMID: 36693953 PMCID: PMC10005936 DOI: 10.1038/s41388-023-02591-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 01/09/2023] [Accepted: 01/11/2023] [Indexed: 01/26/2023]
Abstract
To assess their roles in breast cancer diagnostics, we aimed to compare plasma cell-free DNA (cfDNA) levels with the circulating metabolome in a large breast screening cohort of women recalled for mammography, including healthy women and women with mammographically detected breast diseases, ductal carcinoma in situ and invasive breast cancer: the Breast Screening and Monitoring Study (BSMS). In 999 women, plasma was analyzed by nuclear magnetic resonance (NMR) and Ultra-Performance Liquid Chromatography-Mass Spectrometry (UPLC-MS) and then processed to isolate and quantify total cfDNA. NMR and UPLC-MS results were compared with data for 186 healthy women derived from the AIRWAVE cohort. Results showed no significant differences between groups for all metabolites, whereas invasive cancers had significantly higher plasma cfDNA levels than all other groups. When stratified the supervised OPLS-DA analysis and total cfDNA concentration showed high discrimination accuracy between invasive cancers and the disease/medication-free subjects. Furthermore, comparison of OPLS-DA data for invasive breast cancers with the AIRWAVE cohort showed similar discrimination between breast cancers and healthy controls. This is the first report of agreement between metabolomics and plasma cfDNA levels for discriminating breast cancer from healthy subjects in a true screening population. It also emphasizes the importance of sample standardization. Follow on studies will involve analysis of candidate features in a larger validation series as well as comparing results with serial plasma samples taken at the next routine screening mammography appointment. The findings here help establish the role of plasma analysis in the diagnosis of breast cancer in a large real-world cohort.
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Affiliation(s)
- Justin Stebbing
- Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK
- School of Life Sciences, Faculty of Science and Engineering, ARU, East Road, Cambridge, CB1 1PT, UK
| | - Panteleimon G Takis
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK.
| | - Caroline J Sands
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK
| | - Lynn Maslen
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK
| | - Matthew R Lewis
- National Phenome Centre and Imperial Clinical Phenotyping Centre & Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, IRDB Building, Imperial College London, Hammersmith Campus, London, W12 0NN, UK
| | - Kelly Gleason
- Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK
| | - Karen Page
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - David Guttery
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - Daniel Fernandez-Garcia
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - Lindsay Primrose
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
| | - Jacqueline A Shaw
- Department of Surgery and Cancer, Imperial College London, Du Cane Road, Hammersmith, London, W12 0NN, UK
- Leicester Cancer Research Centre, Department of Genetics and Genome Biology, University of Leicester, Robert Kilpatrick Clinical Sciences Building, Leicester Royal Infirmary, Leicester, LE2 7LX, UK
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7
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Sarmad S, Viant MR, Dunn WB, Goodacre R, Wilson ID, Chappell KE, Griffin JL, O'Donnell VB, Naicker B, Lewis MR, Suzuki T. A proposed framework to evaluate the quality and reliability of targeted metabolomics assays from the UK Consortium on Metabolic Phenotyping (MAP/UK). Nat Protoc 2023; 18:1017-1027. [PMID: 36828894 DOI: 10.1038/s41596-022-00801-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2022] [Accepted: 11/24/2022] [Indexed: 02/26/2023]
Abstract
Targeted metabolite assays that measure tens or hundreds of pre-selected metabolites, typically using liquid chromatography-mass spectrometry, are increasingly being developed and applied to metabolic phenotyping studies. These are used both as standalone phenotyping methods and for the validation of putative metabolic biomarkers obtained from untargeted metabolomics studies. However, there are no widely accepted standards in the scientific community for ensuring reliability of the development and validation of targeted metabolite assays (referred to here as 'targeted metabolomics'). Most current practices attempt to adopt, with modifications, the strict guidance provided by drug regulatory authorities for analytical methods designed largely for measuring drugs and other xenobiotic analytes. Here, the regulatory guidance provided by the European Medicines Agency, US Food and Drug Administration and International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use are summarized. In this Perspective, we have adapted these guidelines and propose a less onerous 'tiered' approach to evaluate the reliability of a wide range of metabolomics analyses, addressing the need for community-accepted, harmonized guidelines for tiers other than full validation. This 'fit-for-purpose' tiered approach comprises four levels-discovery, screening, qualification and validation-and is discussed in the context of a range of targeted and untargeted metabolomics assays. Issues arising with targeted multiplexed metabolomics assays, and how these might be addressed, are considered. Furthermore, guidance is provided to assist the community with selecting the appropriate degree of reliability for a series of well-defined applications of metabolomics.
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Affiliation(s)
- Sarir Sarmad
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, UK
| | - Mark R Viant
- Phenome Centre Birmingham, University of Birmingham, Birmingham, UK
| | - Warwick B Dunn
- Centre for Metabolomics Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, UK.,Institute of Metabolism and Systems Research, College of Medical and Dental Sciences, University of Birmingham, Birmingham, UK
| | - Royston Goodacre
- Centre for Metabolomics Research, Department of Biochemistry and Systems Biology, Institute of Systems, Molecular, and Integrative Biology, University of Liverpool, Liverpool, UK
| | - Ian D Wilson
- Division of Systems Medicine, Department of Metabolism, Digestion & Reproduction, Imperial College London, London, UK
| | - Katie E Chappell
- The National Phenome Centre, Department of Metabolism, Digestion & Reproduction, Imperial College London, London, UK
| | - Julian L Griffin
- School of Medicine, Medical Sciences and Nutrition, University of Aberdeen, Aberdeen, UK
| | - Valerie B O'Donnell
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff, UK
| | - Brendon Naicker
- Systems Immunity Research Institute, School of Medicine, Cardiff University, Cardiff, UK
| | - Matthew R Lewis
- The National Phenome Centre, Department of Metabolism, Digestion & Reproduction, Imperial College London, London, UK
| | - Toru Suzuki
- Department of Cardiovascular Sciences, University of Leicester and NIHR Leicester Biomedical Research Centre, Leicester, UK. .,The Institute of Medical Science, The University of Tokyo, Tokyo, Japan.
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8
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Lu H, George J, Eslam M, Villanueva A, Bolondi L, Reeves HL, McCain M, Chambers E, Ward C, Sartika D, Sands C, Maslen L, Lewis MR, Ramaswami R, Sharma R. Discriminatory Changes in Circulating Metabolites as a Predictor of Hepatocellular Cancer in Patients with Metabolic (Dysfunction) Associated Fatty Liver Disease. Liver Cancer 2023; 12:19-31. [PMID: 36872928 PMCID: PMC9982340 DOI: 10.1159/000525911] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 06/25/2022] [Indexed: 02/19/2023] Open
Abstract
Introduction The burden of metabolic (dysfunction) associated fatty liver disease (MAFLD) is rising mirrored by an increase in hepatocellular cancer (HCC). MAFLD and its sequelae are characterized by perturbations in lipid handling, inflammation, and mitochondrial damage. The profile of circulating lipid and small molecule metabolites with the development of HCC is poorly characterized in MAFLD and could be used in future studies as a biomarker for HCC. Methods We assessed the profile of 273 lipid and small molecule metabolites by ultra-performance liquid chromatography coupled to high-resolution mass spectrometry in serum from patients with MAFLD (n = 113) and MAFLD-associated HCC (n = 144) from six different centers. Regression models were used to identify a predictive model of HCC. Results Twenty lipid species and one metabolite, reflecting changes in mitochondrial function and sphingolipid metabolism, were associated with the presence of cancer on a background of MAFLD with high accuracy (AUC 0.789, 95% CI: 0.721-0.858), which was enhanced with the addition of cirrhosis to the model (AUC 0.855, 95% CI: 0.793-0.917). In particular, the presence of these metabolites was associated with cirrhosis in the MAFLD subgroup (p < 0.001). When considering the HCC cohort alone, the metabolic signature was an independent predictor of overall survival (HR 1.42, 95% CI: 1.09-1.83, p < 0.01). Conclusion These exploratory findings reveal a metabolic signature in serum which is capable of accurately detecting the presence of HCC on a background of MAFLD. This unique serum signature will be taken forward for further investigation of diagnostic performance as biomarker of early stage HCC in patients with MAFLD in the future.
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Affiliation(s)
- Haonan Lu
- Division of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, UK
| | - Jacob George
- Storr Liver Centre, The Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Westmead, New South Wales, Australia
| | - Mohammed Eslam
- Storr Liver Centre, The Westmead Institute for Medical Research, Westmead Hospital and University of Sydney, Westmead, New South Wales, Australia
| | | | - Luigi Bolondi
- Division of Internal Medicine, University of Bologna, Bologna, Italy
| | - Helen L. Reeves
- Newcastle University Translational Clinical Research Institute, Newcastle University Centre for Cancer, Newcastle-upon-Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne, UK
| | - Misti McCain
- Newcastle University Translational Clinical Research Institute, Newcastle University Centre for Cancer, Newcastle-upon-Tyne Hospitals NHS Foundation Trust, Newcastle-upon-Tyne, UK
| | - Edward Chambers
- Department of Medicine, Imperial College London, Hammersmith Hospital, London, UK
| | - Caroline Ward
- Division of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, UK
| | - Dewi Sartika
- Division of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, UK
| | - Caroline Sands
- National Phenome Centre, Imperial College London, London, UK
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Lynn Maslen
- National Phenome Centre, Imperial College London, London, UK
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Matthew R. Lewis
- National Phenome Centre, Imperial College London, London, UK
- Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Ramya Ramaswami
- Division of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, UK
| | - Rohini Sharma
- Division of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, UK
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9
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Mullish BH, Martinez-Gili L, Chekmeneva E, Correia GDS, Lewis MR, Horneffer-Van Der Sluis V, Roberts LA, McDonald JAK, Pechlivanis A, Walters JRF, McClure EL, Marchesi JR, Allegretti JR. Assessing the clinical value of faecal bile acid profiling to predict recurrence in primary Clostridioides difficile infection. Aliment Pharmacol Ther 2022; 56:1556-1569. [PMID: 36250604 DOI: 10.1111/apt.17247] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Revised: 08/30/2022] [Accepted: 09/26/2022] [Indexed: 01/30/2023]
Abstract
BACKGROUND Factors influencing recurrence risk in primary Clostridioides difficile infection (CDI) are poorly understood, and tools predicting recurrence are lacking. Perturbations in bile acids (BAs) contribute to CDI pathogenesis and may be relevant to primary disease prognosis. AIMS To define stool BA dynamics in patients with primary CDI and to explore signatures predicting recurrence METHODS: Weekly stool samples were collected from patients with primary CDI from the last day of anti-CDI therapy until recurrence or, otherwise, through 8 weeks post-completion. Ultra-high performance liquid chromatography-mass spectrometry was used to profile BAs. Stool bile salt hydrolase (BSH) activity was measured to determine primary BA bacterial deconjugation capacity. Multivariate and univariate models were used to define differential BA trajectories in patients with recurrence versus those without, and to assess faecal BAs as predictive markers for recurrence. RESULTS Twenty (36%) of 56 patients (median age: 57, 64% male) had recurrence; 80% of recurrences occurred within the first 9 days post-antibiotic treatment. Principal component analysis of stool BA profiles demonstrated clustering by recurrence status and post-treatment timepoint. Longitudinal faecal BA trajectories showed recovery of secondary BAs and their derivatives only in patients without recurrence. BSH activity increased over time only among non-relapsing patients (β = 0.056; likelihood ratio test p = 0.018). A joint longitudinal-survival model identified five stool BAs with area under the receiver operating characteristic curve >0.73 for predicting recurrence within 9 days post-CDI treatment. CONCLUSIONS Gut BA metabolism dynamics differ in primary CDI patients between those developing recurrence and those who do not. Individual BAs show promise as potential novel biomarkers to predict CDI recurrence.
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Affiliation(s)
- Benjamin H Mullish
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, St Mary's Hospital Campus, Imperial College London, London, UK.,Departments of Gastroenterology and Hepatology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - Laura Martinez-Gili
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, St Mary's Hospital Campus, Imperial College London, London, UK.,Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Elena Chekmeneva
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, National Phenome Centre, IRDB Building, Hammersmith House Campus, Imperial College London, London, UK.,Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Gonçalo D S Correia
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, National Phenome Centre, IRDB Building, Hammersmith House Campus, Imperial College London, London, UK.,Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Matthew R Lewis
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, National Phenome Centre, IRDB Building, Hammersmith House Campus, Imperial College London, London, UK.,Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Verena Horneffer-Van Der Sluis
- Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, National Phenome Centre, IRDB Building, Hammersmith House Campus, Imperial College London, London, UK.,Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.,Department for Diagnostics, Institute for Clinical Chemistry and Laboratory Medicine, University Hospital Hamburg-Eppendorf, Hamburg, Germany
| | - Lauren A Roberts
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, St Mary's Hospital Campus, Imperial College London, London, UK
| | - Julie A K McDonald
- MRC Centre for Molecular Bacteriology and Infection, Imperial College London, London, UK
| | - Alexandros Pechlivanis
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.,Laboratory of Analytical Chemistry, Department of Chemistry, Aristotle University of Thessaloniki, Thessaloniki, Greece.,Biomic_Auth, Bioanalysis and Omics Laboratory, Center for Interdisciplinary Research and Innovation (CIRI-AUTH), Thessaloniki, Greece
| | - Julian R F Walters
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, St Mary's Hospital Campus, Imperial College London, London, UK.,Departments of Gastroenterology and Hepatology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London, UK
| | - Emma L McClure
- Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Boston, Massachusetts, USA
| | - Julian R Marchesi
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, St Mary's Hospital Campus, Imperial College London, London, UK
| | - Jessica R Allegretti
- Division of Gastroenterology, Hepatology, and Endoscopy, Brigham and Women's Hospital, Boston, Massachusetts, USA.,Harvard Medical School, Boston, Massachusetts, USA
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10
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Gadgil MD, Kanaya AM, Sands C, Chekmeneva E, Lewis MR, Kandula NR, Herrington DM. Diet Patterns Are Associated with Circulating Metabolites and Lipid Profiles of South Asians in the United States. J Nutr 2022; 152:2358-2366. [PMID: 36774102 PMCID: PMC10157813 DOI: 10.1093/jn/nxac191] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Revised: 08/03/2022] [Accepted: 08/18/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND South Asians are at higher risk for cardiometabolic disease than many other racial/ethnic minority groups. Diet patterns in US South Asians have unique components associated with cardiometabolic disease. OBJECTIVES We aimed to characterize the metabolites associated with 3 representative diet patterns. METHODS We included 722 participants in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort study aged 40-84 y without known cardiovascular disease. Fasting serum specimens and diet and demographic questionnaires were collected at baseline and diet patterns previously generated through principal components analysis. LC-MS-based untargeted metabolomic and lipidomic analysis was conducted with targeted integration of known metabolite and lipid signals. Linear regression models of diet pattern factor score and log-transformed metabolites adjusted for age, sex, caloric intake, and BMI and adjusted for multiple comparisons were performed, followed by elastic net linear regression of significant metabolites. RESULTS There were 443 metabolites of known identity extracted from the profiling data. The "animal protein" diet pattern was associated with 61 metabolites and lipids, including glycerophospholipids phosphatidylethanolamine PE(O-16:1/20:4) and/or PE(P-16:0/20:4) (β: 0.13; 95% CI: 0.11, 0.14) and N-acyl phosphatidylethanolamines (NAPEs) NAPE(O-18:1/20:4/18:0) and/or NAPE(P-18:0/20:4/18:0) (β: 0.13; 95% CI: 0.11, 0.14), lysophosphatidylinositol (LPI) (22:6/0:0) (β: 0.14; 95% CI: 0.12, 0.17), and fatty acid (FA) (22:6) (β: 0.15; 95% CI: 0.13, 0.17). The "fried snacks, sweets, high-fat dairy" pattern was associated with 12 lipids, including PC(16:0/22:6) (β: -0.08; 95% CI: -0.09, -0.06) and FA (22:6) (β: 0.14; 95% CI: -0.17, -0.10). The "fruits, vegetables, nuts, and legumes" pattern was associated with 5 metabolites including proline betaine (β: 0.17; 95% CI: 0.09, 0.25) (P < 0.0002). CONCLUSIONS Three predominant dietary patterns in US South Asians are associated with circulating metabolites differentiated by lipids including glycerophospholipids and PUFAs and the amino acid proline betaine.
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Affiliation(s)
- Meghana D Gadgil
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
| | - Alka M Kanaya
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Caroline Sands
- National Phenome Centre, Imperial College London, London, United Kingdom
| | - Elena Chekmeneva
- National Phenome Centre, Imperial College London, London, United Kingdom
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, London, United Kingdom
| | - Namratha R Kandula
- Division of General Internal Medicine, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - David M Herrington
- Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, NC, USA
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11
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Valdivia-Garcia MA, Chappell KE, Camuzeaux S, Olmo-García L, van der Sluis VH, Radhakrishnan ST, Stephens H, Bouri S, de Campos Braz LM, Williams HT, Lewis MR, Frost G, Li JV. Improved quantitation of short-chain carboxylic acids in human biofluids using 3-nitrophenylhydrazine derivatization and liquid chromatography with tandem mass spectrometry (LC-MS/MS). J Pharm Biomed Anal 2022; 221:115060. [PMID: 36166933 DOI: 10.1016/j.jpba.2022.115060] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/02/2022] [Accepted: 09/14/2022] [Indexed: 10/31/2022]
Abstract
Short-chain carboxylic acids (SCCAs) produced by gut microbial fermentation may reflect gastrointestinal health. Their concentrations in serum and urine are indicative of specific metabolic pathway activity; therefore, accurate quantitation of SCCAs in different biofluids is desirable. However, it is often challenging to quantitate SCCAs since matrix effects, induced by the presence of a vast variety of other compounds other than SCCAs in complex biofluids, can suppress or enhance signals. Materials used for sample preparation may introduce further analytical challenges. This study reports for the first time a LC-MS/MS-based method to quantitate ten SCCAs (lactate, acetate, 2-hydroxybutyrate, propionate, isobutyrate, butyrate, 2-methylbutyrate, isovalerate, valerate and hexanoate) and evaluates the matrix effects in five human biofluids: serum, urine, stool, and contents from the duodenum and intestinal stoma bags. The optimized method, using 3-Nitrophenylhydrazone as a derivatization agent and a Charge Surface Hybrid reverse phase column, showed clear separation for all SCCAs at a concentration range of 0.1-100 µM, in a 10.5 min run without carry-over effects. The validation of the method showed a good linearity (R2 > 0.99), repeatability (CV ≤ 15%) assessed by intra- and inter-day monitoring. The lowest limit of detection (LLOD) was 25 nM and lowest limit of quantitation (LLOQ) was 50 nM for nine SCCA except acetate at 0.5 and 1 µM, respectively. Quantitative accuracy in all biofluids for most compounds was < ±15%. In summary, this methodology has the advantages over other techniques for its simple and fast sample preparation and a high level of selectivity, repeatability and robustness for SCCA quantification. It also reduced interferences from the matrix or sample containers, making it ideal for use in high-throughput analyses of biofluid samples from large-scale studies.
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Affiliation(s)
- Maria A Valdivia-Garcia
- Section of Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Katie E Chappell
- The National Phenome Centre, Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Stephane Camuzeaux
- The National Phenome Centre, Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Lucía Olmo-García
- The National Phenome Centre, Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Verena Horneffer van der Sluis
- The National Phenome Centre, Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Shiva T Radhakrishnan
- Departments of Gastroenterology and Hepatology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London W2 1NY, United Kingdom; Section of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Hannah Stephens
- Section of Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Sonia Bouri
- Inflammatory Bowel Disease Unit, St Mark's Hospital, London HA1 3UJ, United Kingdom
| | - Lucia M de Campos Braz
- Section of Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Horace T Williams
- Departments of Gastroenterology and Hepatology, St Mary's Hospital, Imperial College Healthcare NHS Trust, London W2 1NY, United Kingdom; Section of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Matthew R Lewis
- The National Phenome Centre, Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Gary Frost
- Section of Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Jia V Li
- Section of Nutrition Research, Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom.
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12
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Harshfield EL, Sands CJ, Tuladhar AM, de Leeuw FE, Lewis MR, Markus HS. Metabolomic profiling in small vessel disease identifies multiple associations with disease severity. Brain 2022; 145:2461-2471. [PMID: 35254405 PMCID: PMC9337813 DOI: 10.1093/brain/awac041] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/13/2021] [Revised: 12/20/2021] [Accepted: 01/11/2022] [Indexed: 11/17/2022] Open
Abstract
Cerebral small vessel disease is a major cause of vascular cognitive impairment and dementia. There are few treatments, largely reflecting limited understanding of the underlying pathophysiology. Metabolomics can be used to identify novel risk factors to better understand pathogenesis and to predict disease progression and severity. We analysed data from 624 patients with symptomatic cerebral small vessel disease from two prospective cohort studies. Serum samples were collected at baseline and patients underwent MRI scans and cognitive testing at regular intervals with up to 14 years of follow-up. Using ultra-performance liquid chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy, we obtained metabolic and lipidomic profiles from 369 annotated metabolites and 54 764 unannotated features and examined their association with respect to disease severity, assessed using MRI small vessel disease markers, cognition and future risk of all-cause dementia. Our analysis identified 28 metabolites that were significantly associated with small vessel disease imaging markers and cognition. Decreased levels of multiple glycerophospholipids and sphingolipids were associated with increased small vessel disease load as evidenced by higher white matter hyperintensity volume, lower mean diffusivity normalized peak height, greater brain atrophy and impaired cognition. Higher levels of creatine, FA(18:2(OH)) and SM(d18:2/24:1) were associated with increased lacune count, higher white matter hyperintensity volume and impaired cognition. Lower baseline levels of carnitines and creatinine were associated with higher annualized change in peak width of skeletonized mean diffusivity, and 25 metabolites, including lipoprotein subclasses, amino acids and xenobiotics, were associated with future dementia incidence. Our results show multiple distinct metabolic signatures that are associated with imaging markers of small vessel disease, cognition and conversion to dementia. Further research should assess causality and the use of metabolomic screening to improve the ability to predict future disease severity and dementia risk in small vessel disease. The metabolomic profiles may also provide novel insights into disease pathogenesis and help identify novel treatment approaches.
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Affiliation(s)
- Eric L Harshfield
- Correspondence to: Dr Eric L. Harshfield Stroke Research Group Department of Clinical Neurosciences University of Cambridge R3, Box 83, Cambridge Biomedical Campus Cambridge CB2 0QQ, UK E-mail:
| | - Caroline J Sands
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Anil M Tuladhar
- Department of Neurology, Donders Center for Medical Neuroscience, Radboud University Nijmegen Medical Center, 6500 HB Nijmegen, The Netherlands
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13
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Takis PG, Vuckovic I, Tan T, Denic A, Lieske JC, Lewis MR, Macura S. NMRpQuant: an automated software for large scale urinary total protein quantification by one-dimensional 1H NMR profiles. Bioinformatics 2022; 38:4437-4439. [PMID: 35861573 PMCID: PMC9477529 DOI: 10.1093/bioinformatics/btac502] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2022] [Revised: 06/24/2022] [Accepted: 07/06/2022] [Indexed: 12/24/2022] Open
Abstract
SUMMARY 1H nuclear magnetic resonance (NMR) spectroscopy is an established bioanalytical technology for metabolic profiling of biofluids in both clinical and large-scale population screening applications. Recently, urinary protein quantification has been demonstrated using the same 1D 1H NMR experimental data captured for metabolic profiling. Here, we introduce NMRpQuant, a freely available platform that builds on these findings with both novel and further optimized computational NMR approaches for rigorous, automated protein urine quantification. The results are validated by interlaboratory comparisons, demonstrating agreement with clinical/biochemical methodologies, pointing at a ready-to-use tool for routine protein urinalyses. AVAILABILITY AND IMPLEMENTATION NMRpQuant was developed on MATLAB programming environment. Source code and Windows/macOS compiled applications are available at https://github.com/pantakis/NMRpQuant, and working examples are available at https://doi.org/10.6084/m9.figshare.18737189.v1. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Ivan Vuckovic
- Metabolomics Core, Mayo Clinic, Rochester, MN 55905, USA
| | - Tricia Tan
- Division of Diabetes, Endocrinology and Metabolism, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK,Clinical Biochemistry, Blood Sciences, North West London Pathology, Charing Cross Hospital, London W6 8RF, UK
| | - Aleksandar Denic
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - John C Lieske
- Division of Nephrology and Hypertension, Department of Internal Medicine, Mayo Clinic, Rochester, MN 55905, USA
| | - Matthew R Lewis
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK,National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK
| | - Slobodan Macura
- Metabolomics Core, Mayo Clinic, Rochester, MN 55905, USA,Department of Biochemistry and Molecular Biology, Mayo Clinic, Rochester, MN 55905, USA
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14
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Wilshaw J, Boswood A, Chang YM, Sands CJ, Camuzeaux S, Lewis MR, Xia D, Connolly DJ. Evidence of altered fatty acid metabolism in dogs with naturally occurring valvular heart disease and congestive heart failure. Metabolomics 2022; 18:34. [PMID: 35635592 PMCID: PMC9151558 DOI: 10.1007/s11306-022-01887-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 04/06/2022] [Indexed: 12/13/2022]
Abstract
INTRODUCTION Myxomatous mitral valve disease (MMVD) is the most common cardiac condition in adult dogs. The disease progresses over several years and affected dogs may develop congestive heart failure (HF). Research has shown that myocardial metabolism is altered in cardiac disease, leading to a reduction in β-oxidation of fatty acids and an increased dependence upon glycolysis. OBJECTIVES This study aimed to evaluate whether a shift in substrate use occurs in canine patients with MMVD; a naturally occurring model of human disease. METHODS Client-owned dogs were longitudinally evaluated at a research clinic in London, UK and paired serum samples were selected from visits when patients were in ACVIM stage B1: asymptomatic disease without cardiomegaly, and stage C: HF. Samples were processed using ultra-performance liquid chromatography mass spectrometry and lipid profiles were compared using mixed effects models with false discovery rate adjustment. The effect of disease stage was evaluated with patient breed entered as a confounder. Features that significantly differed were screened for selection for annotation efforts using reference databases. RESULTS Dogs in HF had altered concentrations of lipid species belonging to several classes previously associated with cardiovascular disease. Concentrations of certain acylcarnitines, phospholipids and sphingomyelins were increased after individuals had developed HF, whilst some ceramides and lysophosphatidylcholines decreased. CONCLUSIONS The canine metabolome appears to change as MMVD progresses. Findings from this study suggest that in HF myocardial metabolism may be characterised by reduced β-oxidation. This proposed explanation warrants further research.
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Affiliation(s)
- Jenny Wilshaw
- Department of Clinical Science and Services, Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, AL9 7TA, London, United Kingdom.
| | - A Boswood
- Department of Clinical Science and Services, Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, AL9 7TA, London, United Kingdom
| | - Y M Chang
- Research Support Office, Royal Veterinary College, University of London, London, United Kingdom
| | - C J Sands
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - S Camuzeaux
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - M R Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom
| | - D Xia
- Research Support Office, Royal Veterinary College, University of London, London, United Kingdom
- Department of Comparative Biomedical Science, Royal Veterinary College, University of London, London, United Kingdom
| | - D J Connolly
- Department of Clinical Science and Services, Royal Veterinary College, University of London, Hawkshead Lane, North Mymms, Hatfield, Hertfordshire, AL9 7TA, London, United Kingdom
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15
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Correia GDS, Takis PG, Sands CJ, Kowalka AM, Tan T, Turtle L, Ho A, Semple MG, Openshaw PJM, Baillie JK, Takáts Z, Lewis MR. 1H NMR Signals from Urine Excreted Protein Are a Source of Bias in Probabilistic Quotient Normalization. Anal Chem 2022; 94:6919-6923. [PMID: 35503092 PMCID: PMC9118196 DOI: 10.1021/acs.analchem.2c00466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Normalization to account for variation in urinary dilution is crucial for interpretation of urine metabolic profiles. Probabilistic quotient normalization (PQN) is used routinely in metabolomics but is sensitive to systematic variation shared across a large proportion of the spectral profile (>50%). Where 1H nuclear magnetic resonance (NMR) spectroscopy is employed, the presence of urinary protein can elevate the spectral baseline and substantially impact the resulting profile. Using 1H NMR profile measurements of spot urine samples collected from hospitalized COVID-19 patients in the ISARIC 4C study, we determined that PQN coefficients are significantly correlated with observed protein levels (r2 = 0.423, p < 2.2 × 10-16). This correlation was significantly reduced (r2 = 0.163, p < 2.2 × 10-16) when using a computational method for suppression of macromolecular signals known as small molecule enhancement spectroscopy (SMolESY) for proteinic baseline removal prior to PQN. These results highlight proteinuria as a common yet overlooked source of bias in 1H NMR metabolic profiling studies which can be effectively mitigated using SMolESY or other macromolecular signal suppression methods before estimation of normalization coefficients.
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Affiliation(s)
- Gonçalo D. S. Correia
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- National
Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London W12 0NN, United Kingdom
- G. D. S. Correia.
| | - Panteleimon G. Takis
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- National
Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London W12 0NN, United Kingdom
- P. G. Takis.
| | - Caroline J. Sands
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- National
Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London W12 0NN, United Kingdom
| | - Anna M. Kowalka
- Division
of Diabetes, Endocrinology and Metabolism, Department of Metabolism,
Digestion and Reproduction, Imperial College
London, Du Cane Road, London W12 0NN, United Kingdom
- Clinical
Biochemistry, Blood Sciences, North West London Pathology, Charing Cross Hospital, London W6 8RF, United Kingdom
| | - Tricia Tan
- Division
of Diabetes, Endocrinology and Metabolism, Department of Metabolism,
Digestion and Reproduction, Imperial College
London, Du Cane Road, London W12 0NN, United Kingdom
- Clinical
Biochemistry, Blood Sciences, North West London Pathology, Charing Cross Hospital, London W6 8RF, United Kingdom
| | - Lance Turtle
- NIHR
Health Protection Research Unit in Emerging and Zoonotic Infections,
Institute of Infection and Global Health, University of Liverpool, Liverpool L69 7BE, United Kingdom
| | - Antonia Ho
- MRC-University
of Glasgow Centre for Virus Research, University
of Glasgow, Glasgow G61 1QH, United Kingdom
| | - Malcolm G. Semple
- NIHR
Health Protection Research Unit in Emerging and Zoonotic Infections,
Institute of Infection, Veterinary and Ecological Sciences, University of Liverpool, Liverpool L69 7BE, United Kingdom
- Respiratory
Medicine, Alder Hey Children’s Hospital, Liverpool L12 2AP, United Kingdom
| | - Peter J. M. Openshaw
- Faculty
of Medicine, National Heart and Lung Institute, Imperial College London, London SW3 6LY, United Kingdom
| | - J. Kenneth Baillie
- Roslin
Institute, University of Edinburgh, Edinburgh EH25 9RG, United Kingdom
| | - Zoltán Takáts
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- National
Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London W12 0NN, United Kingdom
| | - Matthew R. Lewis
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
- National
Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London W12 0NN, United Kingdom
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16
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Inglese P, Huang HX, Wu V, Lewis MR, Takats Z. Mass recalibration for desorption electrospray ionization mass spectrometry imaging using endogenous reference ions. BMC Bioinformatics 2022; 23:133. [PMID: 35428194 DOI: 10.1101/2021.03.29.437482] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 03/30/2022] [Indexed: 05/24/2023] Open
Abstract
BACKGROUND Mass spectrometry imaging (MSI) data often consist of tens of thousands of mass spectra collected from a sample surface. During the time necessary to perform a single acquisition, it is likely that uncontrollable factors alter the validity of the initial mass calibration of the instrument, resulting in mass errors of magnitude significantly larger than their theoretical values. This phenomenon has a two-fold detrimental effect: (a) it reduces the ability to interpret the results based on the observed signals, (b) it can affect the quality of the observed signal spatial distributions. RESULTS We present a post-acquisition computational method capable of reducing the observed mass drift by up to 60 ppm in biological samples, exploiting the presence of typical molecules with a known mass-to-charge ratio. The procedure, tested on time-of-flight and Orbitrap mass spectrometry analyzers interfaced to a desorption electrospray ionization (DESI) source, improves the molecular annotation quality and the spatial distributions of the detected ions. CONCLUSION The presented method represents a robust and accurate tool for performing post-acquisition mass recalibration of DESI-MSI datasets and can help to increase the reliability of the molecular assignment and the data quality.
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Affiliation(s)
- Paolo Inglese
- National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, W12 0NN, UK.
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
| | - Helen Xuexia Huang
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Vincen Wu
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, W12 0NN, UK
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Zoltan Takats
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
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Inglese P, Huang HX, Wu V, Lewis MR, Takats Z. Mass recalibration for desorption electrospray ionization mass spectrometry imaging using endogenous reference ions. BMC Bioinformatics 2022; 23:133. [PMID: 35428194 PMCID: PMC9013061 DOI: 10.1186/s12859-022-04671-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 03/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Mass spectrometry imaging (MSI) data often consist of tens of thousands of mass spectra collected from a sample surface. During the time necessary to perform a single acquisition, it is likely that uncontrollable factors alter the validity of the initial mass calibration of the instrument, resulting in mass errors of magnitude significantly larger than their theoretical values. This phenomenon has a two-fold detrimental effect: (a) it reduces the ability to interpret the results based on the observed signals, (b) it can affect the quality of the observed signal spatial distributions. RESULTS We present a post-acquisition computational method capable of reducing the observed mass drift by up to 60 ppm in biological samples, exploiting the presence of typical molecules with a known mass-to-charge ratio. The procedure, tested on time-of-flight and Orbitrap mass spectrometry analyzers interfaced to a desorption electrospray ionization (DESI) source, improves the molecular annotation quality and the spatial distributions of the detected ions. CONCLUSION The presented method represents a robust and accurate tool for performing post-acquisition mass recalibration of DESI-MSI datasets and can help to increase the reliability of the molecular assignment and the data quality.
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Affiliation(s)
- Paolo Inglese
- National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, W12 0NN, UK.
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
| | - Helen Xuexia Huang
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Vincen Wu
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, Hammersmith Campus, IRDB Building, London, W12 0NN, UK
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Zoltan Takats
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK.
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Lippa KA, Aristizabal-Henao JJ, Beger RD, Bowden JA, Broeckling C, Beecher C, Clay Davis W, Dunn WB, Flores R, Goodacre R, Gouveia GJ, Harms AC, Hartung T, Jones CM, Lewis MR, Ntai I, Percy AJ, Raftery D, Schock TB, Sun J, Theodoridis G, Tayyari F, Torta F, Ulmer CZ, Wilson I, Ubhi BK. Reference materials for MS-based untargeted metabolomics and lipidomics: a review by the metabolomics quality assurance and quality control consortium (mQACC). Metabolomics 2022; 18:24. [PMID: 35397018 PMCID: PMC8994740 DOI: 10.1007/s11306-021-01848-6] [Citation(s) in RCA: 36] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 10/07/2021] [Indexed: 12/17/2022]
Abstract
INTRODUCTION The metabolomics quality assurance and quality control consortium (mQACC) is enabling the identification, development, prioritization, and promotion of suitable reference materials (RMs) to be used in quality assurance (QA) and quality control (QC) for untargeted metabolomics research. OBJECTIVES This review aims to highlight current RMs, and methodologies used within untargeted metabolomics and lipidomics communities to ensure standardization of results obtained from data analysis, interpretation and cross-study, and cross-laboratory comparisons. The essence of the aims is also applicable to other 'omics areas that generate high dimensional data. RESULTS The potential for game-changing biochemical discoveries through mass spectrometry-based (MS) untargeted metabolomics and lipidomics are predicated on the evolution of more confident qualitative (and eventually quantitative) results from research laboratories. RMs are thus critical QC tools to be able to assure standardization, comparability, repeatability and reproducibility for untargeted data analysis, interpretation, to compare data within and across studies and across multiple laboratories. Standard operating procedures (SOPs) that promote, describe and exemplify the use of RMs will also improve QC for the metabolomics and lipidomics communities. CONCLUSIONS The application of RMs described in this review may significantly improve data quality to support metabolomics and lipidomics research. The continued development and deployment of new RMs, together with interlaboratory studies and educational outreach and training, will further promote sound QA practices in the community.
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Affiliation(s)
- Katrice A Lippa
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD, 20899, USA
| | - Juan J Aristizabal-Henao
- Department of Physiological Sciences, Center for Environmental and Human Toxicology, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32610, USA
- BERG LLC, 500 Old Connecticut Path, Building B, 3rd Floor, Framingham, MA, 01710, USA
| | - Richard D Beger
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), Jefferson, AR, 72079, USA
| | - John A Bowden
- Department of Physiological Sciences, Center for Environmental and Human Toxicology, College of Veterinary Medicine, University of Florida, Gainesville, FL, 32610, USA
| | - Corey Broeckling
- Analytical Resources Core: Bioanalysis and Omics Center, Colorado State University, Fort Collins, CO, 80523, USA
| | | | - W Clay Davis
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Charleston, SC, 29412, USA
| | - Warwick B Dunn
- School of Biosciences, Institute of Metabolism and Systems Research and Phenome Centre Birmingham, University of Birmingham, Birmingham, B15, 2TT, UK
| | - Roberto Flores
- Division of Program Coordination, Planning and Strategic Initiatives, Office of Nutrition Research, Office of the Director, National Institutes of Health (NIH), Bethesda, MD, 20892, USA
| | - Royston Goodacre
- Department of Biochemistry and Systems Biology, Institute of Systems, Molecular and Integrative Biology, University of Liverpool, BioSciences Building, Crown St., Liverpool, L69 7ZB, UK
| | - Gonçalo J Gouveia
- Department of Biochemistry and Molecular Biology, University of Georgia, Athens, GA, 30602, USA
| | - Amy C Harms
- Biomedical Metabolomics Facility Leiden, Leiden University, Einsteinweg 55, 2333 CC, Leiden, The Netherlands
| | - Thomas Hartung
- Bloomberg School of Public Health, Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, 21205, USA
| | - Christina M Jones
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Gaithersburg, MD, 20899, USA
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, London, SW7 2AZ, UK
| | - Ioanna Ntai
- Thermo Fisher Scientific, San Jose, CA, 95134, USA
| | - Andrew J Percy
- Cambridge Isotope Laboratories, Inc., Tewksbury, MA, 01876, USA
| | - Dan Raftery
- Northwest Metabolomics Research Center, University of Washington, Seattle, WA, 98109, USA
| | - Tracey B Schock
- Chemical Sciences Division, National Institute of Standards and Technology (NIST), Charleston, SC, 29412, USA
| | - Jinchun Sun
- Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration (FDA), Jefferson, AR, 72079, USA
| | | | - Fariba Tayyari
- Department of Internal Medicine, University of Iowa, Iowa City, IA, 52242, USA
| | - Federico Torta
- Centre for Life Sciences, National University of Singapore, 28 Medical Drive, Singapore, 117456, Singapore
| | - Candice Z Ulmer
- Centers for Disease Control and Prevention (CDC), Atlanta, GA, 30341, USA
| | - Ian Wilson
- Computational & Systems Medicine, Imperial College, Exhibition Rd, London, SW7 2AZ, UK
| | - Baljit K Ubhi
- MOBILion Systems Inc., 4 Hillman Drive Suite 130, Chadds Ford, PA, 19317, USA.
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Sliz E, Shin J, Ahmad S, Williams DM, Frenzel S, Gauß F, Harris SE, Henning AK, Hernandez MV, Hu YH, Jiménez B, Sargurupremraj M, Sudre C, Wang R, Wittfeld K, Yang Q, Wardlaw JM, Völzke H, Vernooij MW, Schott JM, Richards M, Proitsi P, Nauck M, Lewis MR, Launer L, Hosten N, Grabe HJ, Ghanbari M, Deary IJ, Cox SR, Chaturvedi N, Barnes J, Rotter JI, Debette S, Ikram MA, Fornage M, Paus T, Seshadri S, Pausova Z. Circulating Metabolome and White Matter Hyperintensities in Women and Men. Circulation 2022; 145:1040-1052. [PMID: 35050683 PMCID: PMC9645366 DOI: 10.1161/circulationaha.121.056892] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Accepted: 12/02/2021] [Indexed: 11/16/2022]
Abstract
BACKGROUND White matter hyperintensities (WMH), identified on T2-weighted magnetic resonance images of the human brain as areas of enhanced brightness, are a major risk factor of stroke, dementia, and death. There are no large-scale studies testing associations between WMH and circulating metabolites. METHODS We studied up to 9290 individuals (50.7% female, average age 61 years) from 15 populations of 8 community-based cohorts. WMH volume was quantified from T2-weighted or fluid-attenuated inversion recovery images or as hypointensities on T1-weighted images. Circulating metabolomic measures were assessed with mass spectrometry and nuclear magnetic resonance spectroscopy. Associations between WMH and metabolomic measures were tested by fitting linear regression models in the pooled sample and in sex-stratified and statin treatment-stratified subsamples. Our basic models were adjusted for age, sex, age×sex, and technical covariates, and our fully adjusted models were also adjusted for statin treatment, hypertension, type 2 diabetes, smoking, body mass index, and estimated glomerular filtration rate. Population-specific results were meta-analyzed using the fixed-effect inverse variance-weighted method. Associations with false discovery rate (FDR)-adjusted P values (PFDR)<0.05 were considered significant. RESULTS In the meta-analysis of results from the basic models, we identified 30 metabolomic measures associated with WMH (PFDR<0.05), 7 of which remained significant in the fully adjusted models. The most significant association was with higher level of hydroxyphenylpyruvate in men (PFDR.full.adj=1.40×10-7) and in both the pooled sample (PFDR.full.adj=1.66×10-4) and statin-untreated (PFDR.full.adj=1.65×10-6) subsample. In men, hydroxyphenylpyruvate explained 3% to 14% of variance in WMH. In men and the pooled sample, WMH were also associated with lower levels of lysophosphatidylcholines and hydroxysphingomyelins and a larger diameter of low-density lipoprotein particles, likely arising from higher triglyceride to total lipids and lower cholesteryl ester to total lipids ratios within these particles. In women, the only significant association was with higher level of glucuronate (PFDR=0.047). CONCLUSIONS Circulating metabolomic measures, including multiple lipid measures (eg, lysophosphatidylcholines, hydroxysphingomyelins, low-density lipoprotein size and composition) and nonlipid metabolites (eg, hydroxyphenylpyruvate, glucuronate), associate with WMH in a general population of middle-aged and older adults. Some metabolomic measures show marked sex specificities and explain a sizable proportion of WMH variance.
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Affiliation(s)
- Eeva Sliz
- The Hospital for Sick Children, and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Jean Shin
- The Hospital for Sick Children, and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Shahzad Ahmad
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Division of Systems Biomedicine and Pharmacology, Leiden Academic Centre for Drug Research, Leiden University, Leiden, The Netherlands
| | - Dylan M. Williams
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Stefan Frenzel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Friederike Gauß
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Sarah E. Harris
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Ann-Kristin Henning
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Maria Valdes Hernandez
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Yi-Han Hu
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Beatriz Jiménez
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Muralidharan Sargurupremraj
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000 Bordeaux, France
| | - Carole Sudre
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
- Centre for Medical Image Computing, Department of Computer Science, University College London
- School of Biomedical Engineering & Imaging Sciences, King’s College London
| | - Ruiqi Wang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Katharina Wittfeld
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Germany Center for Neurodegenerative Diseases (DZNE), partner site Rostock/Greifswald, Greifswald, Germany
| | - Qiong Yang
- Department of Biostatistics, Boston University, Boston, MA, USA
| | - Joanna M. Wardlaw
- Centre for Clinical Brain Sciences, UK Dementia Research Institute at the University of Edinburgh, Edinburgh, UK
| | - Henry Völzke
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Meike W. Vernooij
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
- Department of Radiology and Nuclear Medicine, and Department of Neurology, Erasmus Medical Center, Rotterdam, the Netherlands
| | - Jonathan M Schott
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Marcus Richards
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Petroula Proitsi
- King’s College London, Institute of Psychiatry, Psychology and Neuroscience, London, UK
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Matthew R. Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Lenore Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, Baltimore, MD, USA
| | - Norbert Hosten
- Institute of Diagnostic Radiology and Neuroradiology, University Medicine Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- Germany Center for Neurodegenerative Diseases (DZNE), partner site Rostock/Greifswald, Greifswald, Germany
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Ian J. Deary
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Simon R. Cox
- Lothian Birth Cohorts group, Department of Psychology, University of Edinburgh, Edinburgh, UK
| | - Nishi Chaturvedi
- MRC Unit for Lifelong Health and Ageing at UCL, University College London, London, UK
| | - Josephine Barnes
- Dementia Research Centre, UCL Queen Square Institute of Neurology, University College London, London, United Kingdom
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA USA
| | - Stephanie Debette
- University of Bordeaux, Inserm, Bordeaux Population Health Research Center, team VINTAGE, UMR 1219, 33000 Bordeaux, France
| | - M. Arfan Ikram
- Department of Epidemiology, Erasmus Medical Centre, Rotterdam, The Netherlands
| | - Myriam Fornage
- University of Texas Health Science Center at Houston McGovern Medical School, Houston, TX, USA
| | - Tomas Paus
- Departments of Psychiatry and Neuroscience and Centre Hospitalier Universitaire Sainte-Justine, University of Montreal, Montreal, QC, Canada
- ECOGENE-21, Chicoutimi, QC, Canada
- Departments of Psychology and Psychiatry, University of Toronto, Toronto, ON, Canada
| | - Sudha Seshadri
- The Framingham Heart Study, Framingham, MA, USA
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Zdenka Pausova
- The Hospital for Sick Children, and Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
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Gadgil MD, Sarkar M, Sands C, Lewis MR, Herrington DM, Kanaya AM. Associations of NAFLD with circulating ceramides and impaired glycemia. Diabetes Res Clin Pract 2022; 186:109829. [PMID: 35292328 PMCID: PMC9082931 DOI: 10.1016/j.diabres.2022.109829] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/13/2022] [Revised: 03/07/2022] [Accepted: 03/09/2022] [Indexed: 11/03/2022]
Abstract
AIM Determine the association of circulating ceramides with NAFLD and glycemic impairment. METHODS Sample: 669 participants in the Mediators of Atherosclerosis in South Asians Living in America (MASALA) cohort aged 40-84 years without cardiovascular disease, cirrhosis, or significant alcohol intake. CLINICAL MEASURES Computed tomography scans at baseline for hepatic attenuation. Fasting serum specimens at baseline and after 5 years. Lipidomics: LC-MS-based analysis of 19 known ceramide signals. STATISTICAL ANALYSIS Linear and logistic regression models of log-transformed ceramides, hepatic attenuation and glucose adjusted for age, sex, calories, study site, BMI, exercise, diet quality, alcohol, saturated fat, lipid-lowering medications and fasting glucose. RESULTS Average age was 55 years, 44% were women, mean BMI was 25.9 kg/m2, and 8% had NAFLD. In adjusted models, Cer(d16:1/20:0) and Cer(d18:1/18:0) were associated with lower mean hepatic attenuation (increased liver fat) (β -4.29; 95% CI [-5.98, -2.59]) and (β -3.40; 95% CI [-5.11, -1.70]), and LacCer(d18:1/16:0) with higher attenuation (β 4.44; 95% CI [2.15, 6.73]). All three ceramides partially mediated the relationship between hepatic attenuation and fasting glucose by 16%, 11% and 5%, respectively, after 5-years. CONCLUSIONS Three circulating ceramides were strongly associated with NAFLD and fasting glucose after 5 years, and partially mediated this association.
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Affiliation(s)
- Meghana D Gadgil
- Division of General Internal Medicine, Department of Medicine, University of California, 1545 Divisadero Street, Suite 320, San Francisco, CA 94143-0320, United States.
| | - Monika Sarkar
- Division of Gastroenterology, Department of Medicine, University of California, 513 Parnassus Avenue, MSB, San Francisco, CA 94117, United States
| | - Caroline Sands
- National Phenome Centre, Imperial College London, IRDB Building 5th Floor, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, IRDB Building 5th Floor, Hammersmith Hospital Campus, London W12 0NN, United Kingdom
| | - David M Herrington
- Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC 27157, United States
| | - Alka M Kanaya
- Division of General Internal Medicine, Department of Medicine, University of California, 1545 Divisadero Street, Suite 320, San Francisco, CA 94143-0320, United States
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21
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Climaco Pinto R, Karaman I, Lewis MR, Hällqvist J, Kaluarachchi M, Graça G, Chekmeneva E, Durainayagam B, Ghanbari M, Ikram MA, Zetterberg H, Griffin J, Elliott P, Tzoulaki I, Dehghan A, Herrington D, Ebbels T. Finding Correspondence between Metabolomic Features in Untargeted Liquid Chromatography-Mass Spectrometry Metabolomics Datasets. Anal Chem 2022; 94:5493-5503. [PMID: 35360896 PMCID: PMC9008693 DOI: 10.1021/acs.analchem.1c03592] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
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Integration
of multiple datasets can greatly enhance bioanalytical
studies, for example, by increasing power to discover and validate
biomarkers. In liquid chromatography–mass spectrometry (LC–MS)
metabolomics, it is especially hard to combine untargeted datasets
since the majority of metabolomic features are not annotated and thus
cannot be matched by chemical identity. Typically, the information
available for each feature is retention time (RT), mass-to-charge
ratio (m/z), and feature intensity
(FI). Pairs of features from the same metabolite in separate datasets
can exhibit small but significant differences, making matching very
challenging. Current methods to address this issue are too simple
or rely on assumptions that cannot be met in all cases. We present
a method to find feature correspondence between two similar LC–MS
metabolomics experiments or batches using only the features’
RT, m/z, and FI. We demonstrate
the method on both real and synthetic datasets, using six orthogonal
validation strategies to gauge the matching quality. In our main example,
4953 features were uniquely matched, of which 585 (96.8%) of 604 manually
annotated features were correct. In a second example, 2324 features
could be uniquely matched, with 79 (90.8%) out of 87 annotated features
correctly matched. Most of the missed annotated matches are between
features that behave very differently from modeled inter-dataset shifts
of RT, MZ, and FI. In a third example with simulated data with 4755
features per dataset, 99.6% of the matches were correct. Finally,
the results of matching three other dataset pairs using our method
are compared with a published alternative method, metabCombiner, showing
the advantages of our approach. The method can be applied using M2S
(Match 2 Sets), a free, open-source MATLAB toolbox, available at https://github.com/rjdossan/M2S.
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Affiliation(s)
- Rui Climaco Pinto
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W12 0BZ, U.K.,UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K
| | - Ibrahim Karaman
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W12 0BZ, U.K.,UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K
| | - Matthew R Lewis
- MRC-NIHR National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Jenny Hällqvist
- Centre for Translational Omics, Great Ormond Street Hospital, University College London, London WC1N 1EH, U.K.,Department of Clinical and Movement Neurosciences, Queen Square Institute of Neurology, University College London, London WC1N 3BG, U.K
| | - Manuja Kaluarachchi
- UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K.,Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Gonçalo Graça
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Elena Chekmeneva
- MRC-NIHR National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Brenan Durainayagam
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W12 0BZ, U.K.,UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K
| | - Mohsen Ghanbari
- Department of Epidemiology, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - M Arfan Ikram
- Department of Epidemiology, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at University of Gothenburg, 431 41 Mölndal, Sweden.,Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, 413 45 Mölndal, Sweden.,Department of Neurodegenerative Disease, University College London, Queen Square, London WC1N 3BG, U.K.,UK Dementia Research Institute, University College London, London WC1N 3BG, U.K
| | - Julian Griffin
- UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K.,Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W12 0BZ, U.K.,UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K
| | - Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W12 0BZ, U.K.,Department of Hygiene and Epidemiology, University of Ioannina School of Medicine, 451 10 Ioannina, Greece
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, London W12 0BZ, U.K.,UK Dementia Research Institute, Imperial College London, London W12 0BZ, U.K.,Department of Epidemiology, Erasmus University Medical Center, 3015 GD Rotterdam, The Netherlands
| | - David Herrington
- Department of Internal Medicine, Wake Forest School of Medicine, Winston-Salem, North Carolina 27101, United States
| | - Timothy Ebbels
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, U.K
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22
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Mehta R, Chekmeneva E, Jackson H, Sands C, Mills E, Arancon D, Li HK, Arkell P, Rawson TM, Hammond R, Amran M, Haber A, Cooke GS, Noursadeghi M, Kaforou M, Lewis MR, Takats Z, Sriskandan S. Antiviral metabolite 3'-deoxy-3',4'-didehydro-cytidine is detectable in serum and identifies acute viral infections including COVID-19. Med 2022; 3:204-215.e6. [PMID: 35128501 PMCID: PMC8801973 DOI: 10.1016/j.medj.2022.01.009] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 11/14/2021] [Accepted: 01/21/2022] [Indexed: 11/05/2022]
Abstract
BACKGROUND There is a critical need for rapid viral infection diagnostics to enable prompt case identification in pandemic settings and support targeted antimicrobial prescribing. METHODS Using untargeted high-resolution liquid chromatography coupled with mass spectrometry, we compared the admission serum metabolome of emergency department patients with viral infections (including COVID-19), bacterial infections, inflammatory conditions, and healthy controls. Sera from an independent cohort of emergency department patients admitted with viral or bacterial infections underwent profiling to validate findings. Associations between whole-blood gene expression and the identified metabolite of interest were examined. FINDINGS 3'-Deoxy-3',4'-didehydro-cytidine (ddhC), a free base of the only known human antiviral small molecule ddhC-triphosphate (ddhCTP), was detected for the first time in serum. When comparing 60 viral with 101 non-viral cases in the discovery cohort, ddhC was the most significantly differentially abundant metabolite, generating an area under the receiver operating characteristic curve (AUC) of 0.954 (95% CI: 0.923-0.986). In the validation cohort, ddhC was again the most significantly differentially abundant metabolite when comparing 40 viral with 40 bacterial cases, generating an AUC of 0.81 (95% CI 0.708-0.915). Transcripts of viperin and CMPK2, enzymes responsible for ddhCTP synthesis, were among the five genes most highly correlated with ddhC abundance. CONCLUSIONS The antiviral precursor molecule ddhC is detectable in serum and an accurate marker for acute viral infection. Interferon-inducible genes viperin and CMPK2 are implicated in ddhC production in vivo. These findings highlight a future diagnostic role for ddhC in viral diagnosis, pandemic preparedness, and acute infection management. FUNDING NIHR Imperial BRC; UKRI.
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Affiliation(s)
- Ravi Mehta
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | - Elena Chekmeneva
- National Phenome Centre, Imperial College London, London SW7 2AZ, UK
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Heather Jackson
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | - Caroline Sands
- National Phenome Centre, Imperial College London, London SW7 2AZ, UK
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Ewurabena Mills
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | | | - Ho Kwong Li
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
- MRC Centre for Molecular Bacteriology & Infection, Imperial College London, London SW7 2AZ, UK
| | - Paul Arkell
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Timothy M. Rawson
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
- Division of Infection & Immunity, University College London, London WC1 E6BT, UK
| | - Robert Hammond
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Maisarah Amran
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Anna Haber
- Imperial College Healthcare NHS Trust, London W12 0HS, UK
| | - Graham S. Cooke
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | - Mahdad Noursadeghi
- Division of Infection & Immunity, University College London, London WC1 E6BT, UK
| | - Myrsini Kaforou
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
| | - Matthew R. Lewis
- National Phenome Centre, Imperial College London, London SW7 2AZ, UK
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Zoltan Takats
- National Phenome Centre, Imperial College London, London SW7 2AZ, UK
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, UK
| | - Shiranee Sriskandan
- Department of Infectious Disease, Imperial College London, London W12 0NN, UK
- MRC Centre for Molecular Bacteriology & Infection, Imperial College London, London SW7 2AZ, UK
- NIHR Health Protection Research Unit in Healthcare-associated Infection & Antimicrobial Resistance, Imperial College London, London W12 0NN, UK
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23
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Gritti F, David M, Brothy P, Lewis MR. Model of retention time and density of gradient peak capacity for improved LC-MS method optimization: Application to metabolomics. Anal Chim Acta 2022; 1197:339492. [DOI: 10.1016/j.aca.2022.339492] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/02/2021] [Revised: 12/20/2021] [Accepted: 01/11/2022] [Indexed: 11/28/2022]
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24
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Graça G, Cai Y, Lau CHE, Vorkas PA, Lewis MR, Want EJ, Herrington D, Ebbels TMD. Automated Annotation of Untargeted All-Ion Fragmentation LC-MS Metabolomics Data with MetaboAnnotatoR. Anal Chem 2022; 94:3446-3455. [PMID: 35180347 PMCID: PMC8892435 DOI: 10.1021/acs.analchem.1c03032] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2021] [Accepted: 12/15/2021] [Indexed: 11/29/2022]
Abstract
Untargeted metabolomics and lipidomics LC-MS experiments produce complex datasets, usually containing tens of thousands of features from thousands of metabolites whose annotation requires additional MS/MS experiments and expert knowledge. All-ion fragmentation (AIF) LC-MS/MS acquisition provides fragmentation data at no additional experimental time cost. However, analysis of such datasets requires reconstruction of parent-fragment relationships and annotation of the resulting pseudo-MS/MS spectra. Here, we propose a novel approach for automated annotation of isotopologues, adducts, and in-source fragments from AIF LC-MS datasets by combining correlation-based parent-fragment linking with molecular fragment matching. Our workflow focuses on a subset of features rather than trying to annotate the full dataset, saving time and simplifying the process. We demonstrate the workflow in three human serum datasets containing 599 features manually annotated by experts. Precision and recall values of 82-92% and 82-85%, respectively, were obtained for features found in the highest-rank scores (1-5). These results equal or outperform those obtained using MS-DIAL software, the current state of the art for AIF data annotation. Further validation for other biological matrices and different instrument types showed variable precision (60-89%) and recall (10-88%) particularly for datasets dominated by nonlipid metabolites. The workflow is freely available as an open-source R package, MetaboAnnotatoR, together with the fragment libraries from Github (https://github.com/gggraca/MetaboAnnotatoR).
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Affiliation(s)
- Gonçalo Graça
- Section
of Bioinformatics, Division of Systems Medicine, Department of Metabolism,
Digestion and Reproduction, Imperial College
London, South Kensington Campus, Sir Alexander Fleming Building, London SW7 2AZ, U.K.
| | - Yuheng Cai
- Section
of Bioinformatics, Division of Systems Medicine, Department of Metabolism,
Digestion and Reproduction, Imperial College
London, South Kensington Campus, Sir Alexander Fleming Building, London SW7 2AZ, U.K.
| | - Chung-Ho E. Lau
- Department
of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London W2 1PG, U.K.
| | - Panagiotis A. Vorkas
- Section
of Biomolecular Medicine, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, Sir Alexander Fleming Building, London SW7 2AZ, U.K.
- Institute
of Applied Biosciences, Centre for Research
and Technology Hellas, Thessaloniki 57001, Greece
| | - Matthew R. Lewis
- Section
of Bioanalytical Chemistry and National Phenome Centre, Division of
Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London W12 0NN, U.K.
| | - Elizabeth J. Want
- Section
of Biomolecular Medicine, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, Sir Alexander Fleming Building, London SW7 2AZ, U.K.
| | - David Herrington
- Section on
Cardiovascular Medicine, Wake Forest School
of Medicine, Winston-Salem, North Carolina 27157, United States
| | - Timothy M. D. Ebbels
- Section
of Bioinformatics, Division of Systems Medicine, Department of Metabolism,
Digestion and Reproduction, Imperial College
London, South Kensington Campus, Sir Alexander Fleming Building, London SW7 2AZ, U.K.
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25
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Jones B, Sands C, Alexiadou K, Minnion J, Tharakan G, Behary P, Ahmed AR, Purkayastha S, Lewis MR, Bloom S, Li JV, Tan TM. The Metabolomic Effects of Tripeptide Gut Hormone Infusion Compared to Roux-en-Y Gastric Bypass and Caloric Restriction. J Clin Endocrinol Metab 2022; 107:e767-e782. [PMID: 34460933 PMCID: PMC8764224 DOI: 10.1210/clinem/dgab608] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/23/2021] [Indexed: 12/23/2022]
Abstract
CONTEXT The gut-derived peptide hormones glucagon-like peptide-1 (GLP-1), oxyntomodulin (OXM), and peptide YY (PYY) are regulators of energy intake and glucose homeostasis and are thought to contribute to the glucose-lowering effects of bariatric surgery. OBJECTIVE To establish the metabolomic effects of a combined infusion of GLP-1, OXM, and PYY (tripeptide GOP) in comparison to a placebo infusion, Roux-en-Y gastric bypass (RYGB) surgery, and a very low-calorie diet (VLCD). DESIGN AND SETTING Subanalysis of a single-blind, randomized, placebo-controlled study of GOP infusion (ClinicalTrials.gov NCT01945840), including VLCD and RYGB comparator groups. PATIENTS AND INTERVENTIONS Twenty-five obese patients with type 2 diabetes or prediabetes were randomly allocated to receive a 4-week subcutaneous infusion of GOP (n = 14) or 0.9% saline control (n = 11). An additional 22 patients followed a VLCD, and 21 underwent RYGB surgery. MAIN OUTCOME MEASURES Plasma and urine samples collected at baseline and 4 weeks into each intervention were subjected to cross-platform metabolomic analysis, followed by unsupervised and supervised modeling approaches to identify similarities and differences between the effects of each intervention. RESULTS Aside from glucose, very few metabolites were affected by GOP, contrasting with major metabolomic changes seen with VLCD and RYGB. CONCLUSIONS Treatment with GOP provides a powerful glucose-lowering effect but does not replicate the broader metabolomic changes seen with VLCD and RYGB. The contribution of these metabolomic changes to the clinical benefits of RYGB remains to be elucidated.
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MESH Headings
- Adult
- Aged
- Blood Glucose/analysis
- Caloric Restriction/methods
- Caloric Restriction/statistics & numerical data
- Diabetes Mellitus, Type 2/blood
- Diabetes Mellitus, Type 2/metabolism
- Diabetes Mellitus, Type 2/therapy
- Diabetes Mellitus, Type 2/urine
- Drug Therapy, Combination/methods
- Female
- Gastric Bypass/methods
- Gastric Bypass/statistics & numerical data
- Gastrointestinal Hormones/administration & dosage
- Glucagon-Like Peptide 1/administration & dosage
- Humans
- Infusions, Subcutaneous
- Male
- Metabolomics/statistics & numerical data
- Middle Aged
- Obesity, Morbid/blood
- Obesity, Morbid/metabolism
- Obesity, Morbid/therapy
- Obesity, Morbid/urine
- Oxyntomodulin/administration & dosage
- Peptide YY/administration & dosage
- Single-Blind Method
- Treatment Outcome
- Weight Loss
- Young Adult
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Affiliation(s)
- Ben Jones
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Caroline Sands
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Kleopatra Alexiadou
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - James Minnion
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - George Tharakan
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Preeshila Behary
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Ahmed R Ahmed
- Department of Surgery and Cancer, Imperial College Healthcare NHS Trust, London, UK
| | - Sanjay Purkayastha
- Department of Surgery and Cancer, Imperial College Healthcare NHS Trust, London, UK
| | - Matthew R Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Stephen Bloom
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Jia V Li
- Division of Digestive Diseases, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
| | - Tricia M Tan
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, UK
- Correspondence: Tricia M. Tan, MB, ChB, BSc, PhD, FRCP, FRCPath, 6th Floor, Commonwealth Building, Hammersmith Campus, Imperial College London, London W12 0HS, UK.
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26
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Albreht A, Hussain H, Jiménez B, Yuen AHY, Whiley L, Witt M, Lewis MR, Chekmeneva E. Structure Elucidation and Mitigation of Endogenous Interferences in LC-MS-Based Metabolic Profiling of Urine. Anal Chem 2022; 94:1760-1768. [PMID: 35026111 DOI: 10.1021/acs.analchem.1c04378] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
Abstract
Liquid chromatography-mass spectrometry (LC-MS) is the main workhorse of metabolomics owing to its high degree of analytical sensitivity and specificity when measuring diverse chemistry in complex biological samples. LC-MS-based metabolic profiling of human urine, a biofluid of primary interest for clinical and biobank studies, is not widely considered to be compromised by the presence of endogenous interferences and is often accomplished using a simple "dilute-and-shoot" approach. Yet, it is our experience that broad obscuring signals are routinely observed in LC-MS metabolic profiles and represent interferences that lack consideration in the relevant metabolomics literature. In this work, we chromatographically isolated the interfering metabolites from human urine and unambiguously identified them via de novo structure elucidation as two separate proline-containing dipeptides: N,N,N-trimethyl-l-alanine-l-proline betaine (l,l-TMAP) and N,N-dimethyl-l-proline-l-proline betaine (l,l-DMPP), the latter reported here for the first time. Offline LC-MS/MS, magnetic resonance mass spectrometry (MRMS), and nuclear magnetic resonance (NMR) spectroscopy were essential components of this workflow for the full chemical and spectroscopic characterization of these metabolites and for establishing the coexistence of cis and trans isomers of both dipeptides in solution. Analysis of these definitive structures highlighted intramolecular ionic interactions as responsible for slow interconversion between these isomeric forms resulting in their unusually broad elution profiles. Proposed mitigation strategies, aimed at increasing the quality of LC-MS-based urine metabolomics data, include modification of column temperature and mobile-phase pH to reduce the chromatographic footprint of these dipeptides, thereby reducing their interfering effect on the underlying metabolic profiles. Alternatively, sample dilution and internal standardization methods may be employed to reduce or account for the observed effects of ionization suppression on the metabolic profile.
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Affiliation(s)
- Alen Albreht
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom.,Analytical, Environmental & Forensic Sciences, Faculty of Life Sciences & Medicine, King's College London, Franklin-Wilkins Building, London SE1 9NH, United Kingdom.,Laboratory for Food Chemistry, Department of Analytical Chemistry, National Institute of Chemistry, Hajdrihova 19, 1000 Ljubljana, Slovenia
| | - Humma Hussain
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom.,Division of Anaesthetics, Pain Medicine and Intensive Care, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, London SW7 2AZ, United Kingdom
| | - Beatriz Jiménez
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, United Kingdom
| | - Ada H Y Yuen
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, United Kingdom
| | - Luke Whiley
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom
| | - Matthias Witt
- MRMS Solutions, Bruker Daltonics GmbH & Co. KG, MRMS Solutions, 28359 Bremen, Germany
| | - Matthew R Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, United Kingdom
| | - Elena Chekmeneva
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, London SW7 2AZ, United Kingdom
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27
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Yeung KTD, Penney N, Whiley L, Ashrafian H, Lewis MR, Purkayastha S, Darzi A, Holmes E. The impact of bariatric surgery on serum tryptophan-kynurenine pathway metabolites. Sci Rep 2022; 12:294. [PMID: 34996930 PMCID: PMC8741964 DOI: 10.1038/s41598-021-03833-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2021] [Accepted: 12/03/2021] [Indexed: 11/09/2022] Open
Abstract
This study aims to explore the immediate effects of bariatric surgery on serum tryptophan–kynurenine pathway metabolites in individuals with type 2 diabetes and BMI > 30. With the goal of providing insight into the link between tryptophan pathway metabolites, type 2 diabetes, and chronic obesity-induced inflammation. This longitudinal study included 20 participants. Half were diagnosed with type 2 diabetes. 11 and 9 underwent RYGB and SG respectively. Blood samples were obtained at pre-operative and 3 months post-operative timepoints. Tryptophan and downstream metabolites of the kynurenine pathway were quantified with an ultrahigh-performance liquid chromatography tandem mass spectrometry with electrospray ionisation method. At 3 months post-operation, RYGB led to significant reductions in tryptophan, kynurenic acid and xanthurenic acid levels when compared to baseline. Significant reductions of the same metabolites after surgery were also observed in individuals with T2D irrespective of surgical procedure. These metabolites were significantly correlated with serum HbA1c levels and BMI. Bariatric surgery, in particular RYGB reduces serum levels of tryptophan and its downstream kynurenine metabolites. These metabolites are associated with T2D and thought to be potentially mechanistic in the systemic processes of obesity induced inflammation leading to insulin resistance. Its reduction after surgery is associated with an improvement in glycaemic control (HbA1c).
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Affiliation(s)
- Kai Tai Derek Yeung
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Nicholas Penney
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Luke Whiley
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK.,Australian National Phenome Centre & Centre for Computational & Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.,Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington, London, UK
| | - Hutan Ashrafian
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, South Kensington, London, UK.,Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington, London, UK
| | - Sanjay Purkayastha
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Ara Darzi
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Elaine Holmes
- Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK. .,Australian National Phenome Centre & Centre for Computational & Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia.
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28
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Ferreira MR, Sands CJ, Li JV, Andreyev JN, Chekmeneva E, Gulliford S, Marchesi J, Lewis MR, Dearnaley DP. Impact of Pelvic Radiation Therapy for Prostate Cancer on Global Metabolic Profiles and Microbiota-Driven Gastrointestinal Late Side Effects: A Longitudinal Observational Study. Int J Radiat Oncol Biol Phys 2021; 111:1204-1213. [PMID: 34352290 PMCID: PMC8609156 DOI: 10.1016/j.ijrobp.2021.07.1713] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2021] [Revised: 07/17/2021] [Accepted: 07/26/2021] [Indexed: 12/18/2022]
Abstract
PURPOSE Radiation therapy to the prostate and pelvic lymph nodes (PLNRT) is part of the curative treatment of high-risk prostate cancer. Yet, the broader influence of radiation therapy on patient physiology is poorly understood. We conducted comprehensive global metabolomic profiling of urine, plasma, and stools sampled from patients undergoing PLNRT for high-risk prostate cancer. METHODS AND MATERIALS Samples were taken from 32 patients at 6 timepoints: baseline, 2 to 3 and 4 to 5 weeks of PLNRT; and 3, 6, and 12 months after PLNRT. We characterized the global metabolome of urine and plasma using 1H nuclear magnetic resonance spectroscopy and ultraperformance liquid chromatography-mass spectrometry, and of stools with nuclear magnetic resonance. Linear mixed-effects modeling was used to investigate metabolic changes between timepoints for each biofluid and assay and determine metabolites of interest. RESULTS Metabolites in urine, plasma and stools changed significantly after PLNRT initiation. Metabolic profiles did not return to baseline up to 1 year post-PLNRT in any biofluid. Molecules associated with cardiovascular risk were increased in plasma. Pre-PLNRT fecal butyrate levels directly associated with increasing gastrointestinal side effects, as did a sharper fall in those levels during and up to 1 year postradiation therapy, mirroring our previous results with metataxonomics. CONCLUSIONS We showed for the first time that an overall metabolic effect is observed in patients undergoing PLNRT up to 1 year posttreatment. These metabolic changes may effect on long-term morbidity after treatment, which warrants further investigation.
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Affiliation(s)
- Miguel R Ferreira
- Academic Radiotherapy Department, The Institute of Cancer Research, London, United Kingdom; Clinical Oncology Department, The Royal Marsden NHS Foundation Trust, London, United Kingdom; Clinical Oncology Department, Guys and St Thomas NHS Foundation Trust, London, United Kingdom; School of Cancer and Pharmaceutical Sciences, King's College London, London, United Kingdom.
| | - Caroline J Sands
- National Phenome Centre, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Jia V Li
- Department of Metabolism, Digestion and Reproduction, Imperial College, London, United Kingdom
| | - Jervoise N Andreyev
- Gastroenterology Department, United Lincolnshire Hospitals NHS Trust, Lincolnshire, United Kingdom
| | - Elena Chekmeneva
- National Phenome Centre, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Sarah Gulliford
- Academic Radiotherapy Department, The Institute of Cancer Research, London, United Kingdom; Radiotherapy Department, University College London Hospitals NHS Foundation Trust, London, United Kingdom
| | - Julian Marchesi
- Department of Metabolism, Digestion and Reproduction, Imperial College, London, United Kingdom; School of Biosciences, Cardiff University, Cardiff, United Kingdom
| | - Matthew R Lewis
- National Phenome Centre, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - David P Dearnaley
- Academic Radiotherapy Department, The Institute of Cancer Research, London, United Kingdom; Clinical Oncology Department, The Royal Marsden NHS Foundation Trust, London, United Kingdom
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29
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Wolfer AM, Correia GDS, Sands CJ, Camuzeaux S, Yuen AHY, Chekmeneva E, Takáts Z, Pearce JTM, Lewis MR. peakPantheR, an R package for large-scale targeted extraction and integration of annotated metabolic features in LC-MS profiling datasets. Bioinformatics 2021; 37:4886-4888. [PMID: 34125879 PMCID: PMC8665750 DOI: 10.1093/bioinformatics/btab433] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2020] [Revised: 04/09/2021] [Accepted: 06/12/2021] [Indexed: 11/12/2022] Open
Abstract
Untargeted LC-MS profiling assays are capable of measuring thousands of chemical compounds in a single sample, but unreliable feature extraction and metabolite identification remain considerable barriers to their interpretation and usefulness. peakPantheR (Peak Picking and ANnoTation of High-resolution Experiments in R) is an R package for the targeted extraction and integration of annotated features from LC-MS profiling experiments. It takes advantage of chromatographic and spectral databases and prior information of sample matrix composition to generate annotated and interpretable metabolic phenotypic datasets and power workflows for real time data quality assessment. AVAILABILITY peakPantheR is available via Bioconductor (https://bioconductor.org/packages/peakPantheR/). Documentation and worked examples are available at https://phenomecentre.github.io/peakPantheR.github.io/ and https://github.com/phenomecentre/metabotyping-dementia-urine. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Arnaud M Wolfer
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Roche Pharma Research and Early Development, pRED Informatics, Roche Innovation Center Basel, F. Hoffmann-La Roche Ltd, Basel, Switzerland
| | - Gonçalo D S Correia
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
| | - Caroline J Sands
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
| | - Stephane Camuzeaux
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
| | - Ada H Y Yuen
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
| | - Elena Chekmeneva
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
| | - Zoltán Takáts
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
| | - Jake T M Pearce
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK
| | - Matthew R Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, IRDB Building, London, UK.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London, UK
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30
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Li JV, Ashrafian H, Sarafian M, Homola D, Rushton L, Barker G, Cabrera PM, Lewis MR, Darzi A, Lin E, Gletsu-Miller NA, Atkin SL, Sathyapalan T, Gooderham NJ, Nicholson JK, Marchesi JR, Athanasiou T, Holmes E. Roux-en-Y gastric bypass-induced bacterial perturbation contributes to altered host-bacterial co-metabolic phenotype. Microbiome 2021; 9:139. [PMID: 34127058 PMCID: PMC8201742 DOI: 10.1186/s40168-021-01086-x] [Citation(s) in RCA: 19] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Accepted: 04/27/2021] [Indexed: 05/04/2023]
Abstract
BACKGROUND Bariatric surgery, used to achieve effective weight loss in individuals with severe obesity, modifies the gut microbiota and systemic metabolism in both humans and animal models. The aim of the current study was to understand better the metabolic functions of the altered gut microbiome by conducting deep phenotyping of bariatric surgery patients and bacterial culturing to investigate causality of the metabolic observations. METHODS Three bariatric cohorts (n = 84, n = 14 and n = 9) with patients who had undergone Roux-en-Y gastric bypass (RYGB), sleeve gastrectomy (SG) or laparoscopic gastric banding (LGB), respectively, were enrolled. Metabolic and 16S rRNA bacterial profiles were compared between pre- and post-surgery. Faeces from RYGB patients and bacterial isolates were cultured to experimentally associate the observed metabolic changes in biofluids with the altered gut microbiome. RESULTS Compared to SG and LGB, RYGB induced the greatest weight loss and most profound metabolic and bacterial changes. RYGB patients showed increased aromatic amino acids-based host-bacterial co-metabolism, resulting in increased urinary excretion of 4-hydroxyphenylacetate, phenylacetylglutamine, 4-cresyl sulphate and indoxyl sulphate, and increased faecal excretion of tyramine and phenylacetate. Bacterial degradation of choline was increased as evidenced by altered urinary trimethylamine-N-oxide and dimethylamine excretion and faecal concentrations of dimethylamine. RYGB patients' bacteria had a greater capacity to produce tyramine from tyrosine, phenylalanine to phenylacetate and tryptophan to indole and tryptamine, compared to the microbiota from non-surgery, normal weight individuals. 3-Hydroxydicarboxylic acid metabolism and urinary excretion of primary bile acids, serum BCAAs and dimethyl sulfone were also perturbed following bariatric surgery. CONCLUSION Altered bacterial composition and metabolism contribute to metabolic observations in biofluids of patients following RYGB surgery. The impact of these changes on the functional clinical outcomes requires further investigation. Video abstract.
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Affiliation(s)
- Jia V Li
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Hutan Ashrafian
- Division of Surgery, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Magali Sarafian
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Daniel Homola
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Laura Rushton
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Grace Barker
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Paula Momo Cabrera
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Matthew R Lewis
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Ara Darzi
- Division of Surgery, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Edward Lin
- Division of General and Gastrointestinal Surgery, Department of Surgery, Emory University School of Medicine, Atlanta, Georgia, 30322, USA
| | - Nana Adwoa Gletsu-Miller
- Department of Applied Health Science, School of Public Health, Indiana University Bloomington, 1025 E 7th Street, Bloomington, IN, 47405, USA
| | | | - Thozhukat Sathyapalan
- Department of Academic Endocrinology, Diabetes and Metabolism, Hull-York Medical School, Hull, UK
| | - Nigel J Gooderham
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Jeremy K Nicholson
- Centre for Computational and Systems Medicine, The Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA, 6150, Australia
| | - Julian R Marchesi
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK
| | - Thanos Athanasiou
- Division of Surgery, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Elaine Holmes
- Division of Digestive Disease, Department of Metabolism, Digestion and Reproduction, Imperial College London, London, SW7 2AZ, UK.
- Centre for Computational and Systems Medicine, The Health Futures Institute, Murdoch University, Harry Perkins Building, Perth, WA, 6150, Australia.
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31
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Takis PG, Jiménez B, Al-Saffar NMS, Harvey N, Chekmeneva E, Misra S, Lewis MR. A Computationally Lightweight Algorithm for Deriving Reliable Metabolite Panel Measurements from 1D 1H NMR. Anal Chem 2021; 93:4995-5000. [PMID: 33733737 PMCID: PMC8041249 DOI: 10.1021/acs.analchem.1c00113] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 03/05/2021] [Indexed: 12/23/2022]
Abstract
Small Molecule Enhancement SpectroscopY (SMolESY) was employed to develop a unique and fully automated computational solution for the assignment and integration of 1H nuclear magnetic resonance (NMR) signals from metabolites in challenging matrices containing macromolecules (herein blood products). Sensitive and reliable quantitation is provided by instant signal deconvolution and straightforward integration bolstered by spectral resolution enhancement and macromolecular signal suppression. The approach is highly efficient, requiring only standard one-dimensional 1H NMR spectra and avoiding the need for sample preprocessing, complex deconvolution, and spectral baseline fitting. The performance of the algorithm, developed using >4000 NMR serum and plasma spectra, was evaluated using an additional >8800 spectra, yielding an assignment accuracy greater than 99.5% for all 22 metabolites targeted. Further validation of its quantitation capabilities illustrated a reliable performance among challenging phenotypes. The simplicity and complete automation of the approach support the application of NMR-based metabolite panel measurements in clinical and population screening applications.
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Affiliation(s)
- Panteleimon G. Takis
- National
Phenome Centre, Imperial College London, Hammer-smith Campus, IRDB Building, London W12 0NN, United Kingdom
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Beatriz Jiménez
- National
Phenome Centre, Imperial College London, Hammer-smith Campus, IRDB Building, London W12 0NN, United Kingdom
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Nada M. S. Al-Saffar
- National
Phenome Centre, Imperial College London, Hammer-smith Campus, IRDB Building, London W12 0NN, United Kingdom
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Nikita Harvey
- National
Phenome Centre, Imperial College London, Hammer-smith Campus, IRDB Building, London W12 0NN, United Kingdom
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Elena Chekmeneva
- National
Phenome Centre, Imperial College London, Hammer-smith Campus, IRDB Building, London W12 0NN, United Kingdom
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Shivani Misra
- Section of
Metabolic Medicine, Division of Diabetes, Endocrinology and Metabolism,
Department of Metabolism, Digestion and Reproduction, Imperial College London, St. Mary’s Campus, London W1 1PG, United Kingdom
| | - Matthew R. Lewis
- National
Phenome Centre, Imperial College London, Hammer-smith Campus, IRDB Building, London W12 0NN, United Kingdom
- Section
of Bioanalytical Chemistry, Division of Systems Medicine, Department
of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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32
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de Haan LR, Verheij J, van Golen RF, Horneffer-van der Sluis V, Lewis MR, Beuers UHW, van Gulik TM, Olde Damink SWM, Schaap FG, Heger M, Olthof PB. Unaltered Liver Regeneration in Post-Cholestatic Rats Treated with the FXR Agonist Obeticholic Acid. Biomolecules 2021; 11:biom11020260. [PMID: 33578971 PMCID: PMC7916678 DOI: 10.3390/biom11020260] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/28/2020] [Revised: 01/25/2021] [Accepted: 02/02/2021] [Indexed: 12/29/2022] Open
Abstract
In a previous study, obeticholic acid (OCA) increased liver growth before partial hepatectomy (PHx) in rats through the bile acid receptor farnesoid X-receptor (FXR). In that model, OCA was administered during obstructive cholestasis. However, patients normally undergo PHx several days after biliary drainage. The effects of OCA on liver regeneration were therefore studied in post-cholestatic Wistar rats. Rats underwent sham surgery or reversible bile duct ligation (rBDL), which was relieved after 7 days. PHx was performed one day after restoration of bile flow. Rats received 10 mg/kg OCA per day or were fed vehicle from restoration of bile flow until sacrifice 5 days after PHx. Liver regeneration was comparable between cholestatic and non-cholestatic livers in PHx-subjected rats, which paralleled liver regeneration a human validation cohort. OCA treatment induced ileal Fgf15 mRNA expression but did not enhance post-PHx hepatocyte proliferation through FXR/SHP signaling. OCA treatment neither increased mitosis rates nor recovery of liver weight after PHx but accelerated liver regrowth in rats that had not been subjected to rBDL. OCA did not increase biliary injury. Conclusively, OCA does not induce liver regeneration in post-cholestatic rats and does not exacerbate biliary damage that results from cholestasis. This study challenges the previously reported beneficial effects of OCA in liver regeneration in cholestatic rats.
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Affiliation(s)
- Lianne R. de Haan
- Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, College of Medicine, Jiaxing University, Jiaxing 314001, Zhejiang, China;
- Department of Surgery, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (T.M.v.G.); (P.B.O.)
| | - Joanne Verheij
- Department of Pathology, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands;
| | - Rowan F. van Golen
- Department of Gastroenterology and Hepatology, Leiden University Medical Center, 2333 ZA Leiden, The Netherlands;
| | - Verena Horneffer-van der Sluis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; (V.H.-v.d.S.); (M.R.L.)
| | - Matthew R. Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, London W12 0NN, UK; (V.H.-v.d.S.); (M.R.L.)
| | - Ulrich H. W. Beuers
- Department of Gastroenterology & Hepatology and Tytgat Institute for Liver and Intestinal Research, Amsterdam Gastroenterology & Metabolism, Amsterdam UMC, Location AMC, 1105 AZ Amsterdam, The Netherlands;
| | - Thomas M. van Gulik
- Department of Surgery, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (T.M.v.G.); (P.B.O.)
| | - Steven W. M. Olde Damink
- Department of Surgery & NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, 6200 MD Maastricht, The Netherlands; (S.W.M.O.D.); (F.G.S.)
- Department of General, Visceral and Transplantation Surgery, RWTH University Hospital Aachen, 52074 Aachen, Germany
| | - Frank G. Schaap
- Department of Surgery & NUTRIM School of Nutrition and Translational Research in Metabolism, Maastricht University Medical Center, 6200 MD Maastricht, The Netherlands; (S.W.M.O.D.); (F.G.S.)
- Department of General, Visceral and Transplantation Surgery, RWTH University Hospital Aachen, 52074 Aachen, Germany
| | - Michal Heger
- Jiaxing Key Laboratory for Photonanomedicine and Experimental Therapeutics, Department of Pharmaceutics, College of Medicine, Jiaxing University, Jiaxing 314001, Zhejiang, China;
- Department of Surgery, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (T.M.v.G.); (P.B.O.)
- Department of Pharmaceutics, Utrecht Institute for Pharmaceutical Sciences, Utrecht University, 3584 CG Utrecht, The Netherlands
- Correspondence: or ; Tel.: +86-138-19345926 or +31-30-2533966
| | - Pim B. Olthof
- Department of Surgery, Amsterdam UMC, Location AMC, University of Amsterdam, 1105 AZ Amsterdam, The Netherlands; (T.M.v.G.); (P.B.O.)
- Department of Surgery, Erasmus Medical Center, 3015 GD Rotterdam, The Netherlands
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33
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Gadgil MD, Kanaya AM, Sands C, Lewis MR, Kandula NR, Herrington DM. Circulating metabolites and lipids are associated with glycaemic measures in South Asians. Diabet Med 2021; 38:e14494. [PMID: 33617033 PMCID: PMC8115216 DOI: 10.1111/dme.14494] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 11/30/2020] [Accepted: 12/03/2020] [Indexed: 12/30/2022]
Abstract
BACKGROUND South Asians are at higher risk for diabetes (DM) than many other racial/ethnic groups. Circulating metabolites are measurable products of metabolic processes that may explain the aetiology of elevated risk. We characterized metabolites associated with prevalent DM and glycaemic measures in South Asians. METHODS We included 717 participants from the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study, aged 40-84 years. We used baseline fasting serum for metabolomics and demographic, behavioural, glycaemic data from baseline and at 5 years. We performed LC-MS untargeted metabolomic and lipidomic analysis with targeted integration of known signals. Individual linear and ordinal logistic regression models were adjusted for age, sex, BMI, diet, exercise, alcohol, smoking and family history of DM followed by elastic net regression to identify metabolites most associated with the outcome. RESULTS There were 258 metabolites with detectable signal in >98% of samples. Thirty-four metabolites were associated with prevalent DM in an elastic net model. Predominant metabolites associated with DM were sphingomyelins, proline (OR 15.86; 95% CI 4.72, 53.31) and betaine (OR 0.03; 0.004, 0.14). Baseline tri- and di-acylglycerols [DG (18:0/16:0) (18.36; 11.79, 24.92)] were positively associated with fasting glucose and long-chain acylcarnitines [CAR 26:1 (-0.40; -0.54, -0.27)] were inversely associated with prevalent DM and HbA1c at follow-up. DISCUSSION A metabolomic signature in South Asians may help determine the unique aetiology of diabetes in this high-risk ethnic group. Future work will externally validate our findings and determine the effects of modifiable risk factors for DM.
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Affiliation(s)
- Meghana D. Gadgil
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, CA; 1545 Divisadero Street, Suite 320, San Francisco, CA 94143-0320
| | - Alka M. Kanaya
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, CA; 1545 Divisadero Street, Suite 320, San Francisco, CA 94143-0320
| | - Caroline Sands
- National Phenome Centre, Imperial College London, IRDB Building 5th Floor, Hammersmith Hospital Campus, London, W12 0NN
| | - Matthew R. Lewis
- National Phenome Centre, Imperial College London, IRDB Building 5th Floor, Hammersmith Hospital Campus, London, W12 0NN
| | - Namratha R. Kandula
- Division of General Internal Medicine and Geriatrics, Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL; Rubloff Building 10th Floor 750 N Lake Shore Chicago IL 60611
| | - David M. Herrington
- Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest School of Medicine; Medical Center Boulevard, Winston-Salem, NC 27157
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34
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Sands CJ, Gómez-Romero M, Correia G, Chekmeneva E, Camuzeaux S, Izzi-Engbeaya C, Dhillo WS, Takats Z, Lewis MR. Representing the Metabolome with High Fidelity: Range and Response as Quality Control Factors in LC-MS-Based Global Profiling. Anal Chem 2021; 93:1924-1933. [PMID: 33448796 DOI: 10.1021/acs.analchem.0c03848] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
Liquid chromatography-mass spectrometry (LC-MS) is a powerful and widely used technique for measuring the abundance of chemical species in living systems. Its sensitivity, analytical specificity, and direct applicability to biofluids and tissue extracts impart great promise for the discovery and mechanistic characterization of biomarker panels for disease detection, health monitoring, patient stratification, and treatment personalization. Global metabolic profiling applications yield complex data sets consisting of multiple feature measurements for each chemical species observed. While this multiplicity can be useful in deriving enhanced analytical specificity and chemical identities from LC-MS data, data set inflation and quantitative imprecision among related features is problematic for statistical analyses and interpretation. This Perspective provides a critical evaluation of global profiling data fidelity with respect to measurement linearity and the quantitative response variation observed among components of the spectra. These elements of data quality are widely overlooked in untargeted metabolomics yet essential for the generation of data that accurately reflect the metabolome. Advanced feature filtering informed by linear range estimation and analyte response factor assessment is advocated as an attainable means of controlling LC-MS data quality in global profiling studies and exemplified herein at both the feature and data set level.
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Affiliation(s)
- Caroline J Sands
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - María Gómez-Romero
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Gonçalo Correia
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Elena Chekmeneva
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Stephane Camuzeaux
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Chioma Izzi-Engbeaya
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0HS, United Kingdom
| | - Waljit S Dhillo
- Section of Endocrinology and Investigative Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0HS, United Kingdom
| | - Zoltan Takats
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Matthew R Lewis
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus, London W12 0NN, United Kingdom.,Section of Bioanalytical Chemistry, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus, London SW7 2AZ, United Kingdom
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Whiley L, Chappell KE, D'Hondt E, Lewis MR, Jiménez B, Snowden SG, Soininen H, Kłoszewska I, Mecocci P, Tsolaki M, Vellas B, Swann JR, Hye A, Lovestone S, Legido-Quigley C, Holmes E. Metabolic phenotyping reveals a reduction in the bioavailability of serotonin and kynurenine pathway metabolites in both the urine and serum of individuals living with Alzheimer's disease. Alzheimers Res Ther 2021; 13:20. [PMID: 33422142 PMCID: PMC7797094 DOI: 10.1186/s13195-020-00741-z] [Citation(s) in RCA: 51] [Impact Index Per Article: 17.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2020] [Accepted: 12/07/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND Both serotonergic signalling disruption and systemic inflammation have been associated with the pathogenesis of Alzheimer's disease (AD). The common denominator linking the two is the catabolism of the essential amino acid, tryptophan. Metabolism via tryptophan hydroxylase results in serotonin synthesis, whilst metabolism via indoleamine 2,3-dioxygenase (IDO) results in kynurenine and its downstream derivatives. IDO is reported to be activated in times of host systemic inflammation and therefore is thought to influence both pathways. To investigate metabolic alterations in AD, a large-scale metabolic phenotyping study was conducted on both urine and serum samples collected from a multi-centre clinical cohort, consisting of individuals clinically diagnosed with AD, mild cognitive impairment (MCI) and age-matched controls. METHODS Metabolic phenotyping was applied to both urine (n = 560) and serum (n = 354) from the European-wide AddNeuroMed/Dementia Case Register (DCR) biobank repositories. Metabolite data were subsequently interrogated for inter-group differences; influence of gender and age; comparisons between two subgroups of MCI - versus those who remained cognitively stable at follow-up visits (sMCI); and those who underwent further cognitive decline (cMCI); and the impact of selective serotonin reuptake inhibitor (SSRI) medication on metabolite concentrations. RESULTS Results revealed significantly lower metabolite concentrations of tryptophan pathway metabolites in the AD group: serotonin (urine, serum), 5-hydroxyindoleacetic acid (urine), kynurenine (serum), kynurenic acid (urine), tryptophan (urine, serum), xanthurenic acid (urine, serum), and kynurenine/tryptophan ratio (urine). For each listed metabolite, a decreasing trend in concentrations was observed in-line with clinical diagnosis: control > MCI > AD. There were no significant differences in the two MCI subgroups whilst SSRI medication status influenced observations in serum, but not urine. CONCLUSIONS Urine and serum serotonin concentrations were found to be significantly lower in AD compared with controls, suggesting the bioavailability of the neurotransmitter may be altered in the disease. A significant increase in the kynurenine/tryptophan ratio suggests that this may be a result of a shift to the kynurenine metabolic route due to increased IDO activity, potentially as a result of systemic inflammation. Modulation of the pathways could help improve serotonin bioavailability and signalling in AD patients.
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Affiliation(s)
- Luke Whiley
- UK Dementia Research Institute, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
- Health Futures Institute, Murdoch University, Perth, WA, 6105, Australia
- The Perron Institute for Neurological and Translational Science, Nedlands, WA, 6009, Australia
| | - Katie E Chappell
- Section of Bioanalytical Chemistry W12 0NN, UK, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
- National Phenome Centre, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
| | - Ellie D'Hondt
- imec, Exascience Life Lab, Kapeldreef 75, B-3001, Leuven, Belgium
| | - Matthew R Lewis
- Section of Bioanalytical Chemistry W12 0NN, UK, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
- National Phenome Centre, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
| | - Beatriz Jiménez
- National Phenome Centre, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
| | - Stuart G Snowden
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Present address: Core Metabolomics and Lipidomics Laboratory, Metabolic Research Laboratories, Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Hilkka Soininen
- Department of Neurology, University of Eastern Finland and Kuopio University Hospital, Kuopio, Finland
| | | | - Patrizia Mecocci
- Institute of Gerontology and Geriatrics, University of Perugia, Perugia, Italy
| | - Magda Tsolaki
- 3rd Department of Neurology, Aristotle University, Thessaloniki, Greece
| | - Bruno Vellas
- INSERM U 558, University of Toulouse, Toulouse, France
| | - Jonathan R Swann
- Section of Bioanalytical Chemistry W12 0NN, UK, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
| | - Abdul Hye
- INSERM U 558, University of Toulouse, Toulouse, France
| | - Simon Lovestone
- Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, UK
- Current affiliation at Janssen-Cilag Ltd, High Wycombe, UK
| | - Cristina Legido-Quigley
- Institute of Psychiatry, Psychology and Neuroscience, King's College London, London, UK
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
| | - Elaine Holmes
- UK Dementia Research Institute, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK.
- Health Futures Institute, Murdoch University, Perth, WA, 6105, Australia.
- The Perron Institute for Neurological and Translational Science, Nedlands, WA, 6009, Australia.
- Section for Nutrition Research, Imperial College, Hammersmith Campus Du Cane Road, London, W12 0NN, UK.
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Letertre MPM, Myridakis A, Whiley L, Camuzeaux S, Lewis MR, Chappell KE, Thaikkatil A, Dumas ME, Nicholson JK, Swann JR, Wilson ID. A targeted ultra performance liquid chromatography - Tandem mass spectrometric assay for tyrosine and metabolites in urine and plasma: Application to the effects of antibiotics on mice. J Chromatogr B Analyt Technol Biomed Life Sci 2020; 1164:122511. [PMID: 33460909 DOI: 10.1016/j.jchromb.2020.122511] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 12/11/2020] [Accepted: 12/14/2020] [Indexed: 12/20/2022]
Abstract
Tyrosine plays a key role in mammalian biochemistry and defects in its metabolism (e.g., tyrosinemia, alkaptonuria etc.) have significant adverse consequences for those affected if left untreated. In addition, gut bacterially-derived p-cresol and its metabolites are of interest as a result of various effects on host xenobiotic metabolism. A fit-for-purpose quantitative ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) assay was developed to target and quantify tyrosine and eleven metabolites in urine and plasma. Dansylation, using dansyl chloride, was used to improve chromatographic and mass spectral properties for tyrosine and nine phenolic metabolites, with detection using positive electrospray ionisation (ESI). The sulfate and glucuronide conjugates of p-cresol, where the phenol group was blocked, were quantified intact, using negative ESI via polarity switching during the same run. Sample preparation for urine and plasma involved deproteinization by solvent precipitation (of acetonitrile:isopropyl alcohol (1:1 v/v)) followed by in situ dansylation in 96 well plates. To minimize sample and solvent usage, and maximize sensitivity, analysis was performed using microbore reversed-phase gradient UPLC on a C8 phase with a 7.5 min. cycle time. The coefficients of variation obtained were <15%, with lower limits of quantification ranging from 5 to 250 nM depending upon the analyte. The method was applied to plasma and urine samples obtained from mice placed on a high tyrosine diet with one subgroup of animals subsequently receiving antibiotics to suppress the gut microbiota. Whilst plasma profiles were largely unaffected by antibiotic treatment clear reductions in the amount of p-cresol sulfate and p-cresol glucuronide excreted in the urine were observed for these mice.
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Affiliation(s)
- Marine P M Letertre
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK.
| | - Antonis Myridakis
- Department of Surgery and Cancer, Imperial College London, SW7 2AZ, UK
| | - Luke Whiley
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins South Building, Perth, WA 6150, Australia; Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Murdoch Perth, WA, 6150, Australia; National Phenome Centre, Dept of metabolism, Digestion and Reproduction, Imperial College London, W12 0NN
| | - Stéphane Camuzeaux
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK; National Phenome Centre, Dept of metabolism, Digestion and Reproduction, Imperial College London, W12 0NN
| | - Matthew R Lewis
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK; National Phenome Centre, Dept of metabolism, Digestion and Reproduction, Imperial College London, W12 0NN
| | - Katie E Chappell
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK; National Phenome Centre, Dept of metabolism, Digestion and Reproduction, Imperial College London, W12 0NN
| | - Annie Thaikkatil
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK
| | - Marc-Emmanuel Dumas
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK
| | - Jeremy K Nicholson
- Australian National Phenome Centre, Health Futures Institute, Murdoch University, Harry Perkins South Building, Perth, WA 6150, Australia; Institute of Global Health Innovation, Imperial College London, Level 1, Faculty Building South Kensington Campus, London SW72NA, UK
| | - Jonathan R Swann
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK; School of Human Development and Health, Faculty of Medicine, University of Southampton, UK
| | - Ian D Wilson
- Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, SW7 2AZ, UK.
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Evans AM, O'Donovan C, Playdon M, Beecher C, Beger RD, Bowden JA, Broadhurst D, Clish CB, Dasari S, Dunn WB, Griffin JL, Hartung T, Hsu PC, Huan T, Jans J, Jones CM, Kachman M, Kleensang A, Lewis MR, Monge ME, Mosley JD, Taylor E, Tayyari F, Theodoridis G, Torta F, Ubhi BK, Vuckovic D. Dissemination and analysis of the quality assurance (QA) and quality control (QC) practices of LC-MS based untargeted metabolomics practitioners. Metabolomics 2020; 16:113. [PMID: 33044703 PMCID: PMC7641040 DOI: 10.1007/s11306-020-01728-5] [Citation(s) in RCA: 46] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2020] [Accepted: 09/20/2020] [Indexed: 02/07/2023]
Abstract
INTRODUCTION The metabolomics quality assurance and quality control consortium (mQACC) evolved from the recognized need for a community-wide consensus on improving and systematizing quality assurance (QA) and quality control (QC) practices for untargeted metabolomics. OBJECTIVES In this work, we sought to identify and share the common and divergent QA and QC practices amongst mQACC members and collaborators who use liquid chromatography-mass spectrometry (LC-MS) in untargeted metabolomics. METHODS All authors voluntarily participated in this collaborative research project by providing the details of and insights into the QA and QC practices used in their laboratories. This sharing was enabled via a six-page questionnaire composed of over 120 questions and comment fields which was developed as part of this work and has proved the basis for ongoing mQACC outreach. RESULTS For QA, many laboratories reported documenting maintenance, calibration and tuning (82%); having established data storage and archival processes (71%); depositing data in public repositories (55%); having standard operating procedures (SOPs) in place for all laboratory processes (68%) and training staff on laboratory processes (55%). For QC, universal practices included using system suitability procedures (100%) and using a robust system of identification (Metabolomics Standards Initiative level 1 identification standards) for at least some of the detected compounds. Most laboratories used QC samples (>86%); used internal standards (91%); used a designated analytical acquisition template with randomized experimental samples (91%); and manually reviewed peak integration following data acquisition (86%). A minority of laboratories included technical replicates of experimental samples in their workflows (36%). CONCLUSIONS Although the 23 contributors were researchers with diverse and international backgrounds from academia, industry and government, they are not necessarily representative of the worldwide pool of practitioners due to the recruitment method for participants and its voluntary nature. However, both questionnaire and the findings presented here have already informed and led other data gathering efforts by mQACC at conferences and other outreach activities and will continue to evolve in order to guide discussions for recommendations of best practices within the community and to establish internationally agreed upon reporting standards. We very much welcome further feedback from readers of this article.
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Affiliation(s)
| | - Claire O'Donovan
- European Molecular Biology Laboratory (EMBL), The European Bioinformatics Institute, Cambridgeshire, UK
| | | | | | - Richard D Beger
- National Center for Toxicological Research, Food and Drug Administration, Jefferson, AR, USA
| | - John A Bowden
- College of Veterinary Medicine, University of Florida, Gainesville, FL, USA
| | - David Broadhurst
- Centre for Integrative Metabolomics & Computational Biology, School of Science, Edith Cowan University, Joondalup, WA, Australia
| | | | - Surendra Dasari
- Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA
| | - Warwick B Dunn
- School of Biosciences, Phenome Centre Birmingham and Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK
| | - Julian L Griffin
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Thomas Hartung
- Center for Alternatives To Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Ping- Ching Hsu
- University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Tao Huan
- Department of Chemistry, University of British Columbia, Vancouver, Canada
| | - Judith Jans
- University Medical Center Utrecht, Utrecht, Netherlands
| | - Christina M Jones
- Material Measurement Laboratory, National Institute of Standards and Technology, Gaithersburg, MD, USA
| | | | - Andre Kleensang
- Center for Alternatives To Animal Testing (CAAT), Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA
| | - Matthew R Lewis
- National Phenome Centre, Imperial College London, London, UK
| | - María Eugenia Monge
- Centro de Investigaciones en Bionanociencias (CIBION), Consejo Nacional de Investigaciones Científicas Y Técnicas (CONICET), C1425FQD, Ciudad de Buenos Aires, Argentina
| | - Jonathan D Mosley
- Center for Environmental Measurement and Modeling, Environmental Protection Agency, Washington, DC, USA
| | | | - Fariba Tayyari
- Department of Internal Medicine, Metabolomics Core, The University of Iowa, Iowa City, Iowa, USA
| | | | - Federico Torta
- Singapore Lipidomics Incubator, Department of Biochemistry, Life Sciences Institute and Yong Loo Lin School of Medicine, National University of Singapore, Kent Ridge, Singapore
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Takis PG, Jiménez B, Sands CJ, Chekmeneva E, Lewis MR. SMolESY: an efficient and quantitative alternative to on-instrument macromolecular 1H-NMR signal suppression. Chem Sci 2020; 11:6000-6011. [PMID: 34094091 PMCID: PMC8159292 DOI: 10.1039/d0sc01421d] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2020] [Accepted: 05/26/2020] [Indexed: 12/23/2022] Open
Abstract
One-dimensional (1D) proton-nuclear magnetic resonance (1H-NMR) spectroscopy is an established technique for measuring small molecules in a wide variety of complex biological sample types. It is demonstrably reproducible, easily automatable and consequently ideal for routine and large-scale application. However, samples containing proteins, lipids, polysaccharides and other macromolecules produce broad signals which overlap and convolute those from small molecules. NMR experiment types designed to suppress macromolecular signals during acquisition may be additionally performed, however these approaches add to the overall sample analysis time and cost, especially for large cohort studies, and fail to produce reliably quantitative data. Here, we propose an alternative way of computationally eliminating macromolecular signals, employing the mathematical differentiation of standard 1H-NMR spectra, producing small molecule-enhanced spectra with preserved quantitative capability and increased resolution. Our approach, presented in its simplest form, was implemented in a cheminformatic toolbox and successfully applied to more than 3000 samples of various biological matrices rich or potentially rich with macromolecules, offering an efficient alternative to on-instrument experimentation, facilitating NMR use in routine and large-scale applications.
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Affiliation(s)
- Panteleimon G Takis
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus London SW7 2AZ UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus IRDB Building London W12 0NN UK
| | - Beatriz Jiménez
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus London SW7 2AZ UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus IRDB Building London W12 0NN UK
| | - Caroline J Sands
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus London SW7 2AZ UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus IRDB Building London W12 0NN UK
| | - Elena Chekmeneva
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus London SW7 2AZ UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus IRDB Building London W12 0NN UK
| | - Matthew R Lewis
- Section of Bioanalytical Chemistry, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington Campus London SW7 2AZ UK
- National Phenome Centre, Department of Metabolism, Digestion and Reproduction, Imperial College London, Hammersmith Campus IRDB Building London W12 0NN UK
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Andreas NJ, Basu Roy R, Gomez-Romero M, Horneffer-van der Sluis V, Lewis MR, Camuzeaux SSM, Jiménez B, Posma JM, Tientcheu L, Egere U, Sillah A, Togun T, Holmes E, Kampmann B. Performance of metabonomic serum analysis for diagnostics in paediatric tuberculosis. Sci Rep 2020; 10:7302. [PMID: 32350385 PMCID: PMC7190829 DOI: 10.1038/s41598-020-64413-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2018] [Accepted: 03/13/2020] [Indexed: 12/31/2022] Open
Abstract
We applied a metabonomic strategy to identify host biomarkers in serum to diagnose paediatric tuberculosis (TB) disease. 112 symptomatic children with presumptive TB were recruited in The Gambia and classified as bacteriologically-confirmed TB, clinically diagnosed TB, or other diseases. Sera were analysed using 1H nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS). Multivariate data analysis was used to distinguish patients with TB from other diseases. Diagnostic accuracy was evaluated using Receiver Operating Characteristic (ROC) curves. Model performance was tested in a validation cohort of 36 children from the UK. Data acquired using 1H NMR demonstrated a sensitivity, specificity and Area Under the Curve (AUC) of 69% (95% confidence interval [CI], 56-73%), 83% (95% CI, 73-93%), and 0.78 respectively, and correctly classified 20% of the validation cohort from the UK. The most discriminatory MS data showed a sensitivity of 67% (95% CI, 60-71%), specificity of 86% (95% CI, 75-93%) and an AUC of 0.78, correctly classifying 83% of the validation cohort. Amongst children with presumptive TB, metabolic profiling of sera distinguished bacteriologically-confirmed and clinical TB from other diseases. This novel approach yielded a diagnostic performance for paediatric TB comparable to that of Xpert MTB/RIF and interferon gamma release assays.
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Affiliation(s)
- Nicholas J Andreas
- Centre for International Child Health, Department of Paediatrics, Imperial College London, St. Mary's Hospital, Praed Street, London, W2 1NY, United Kingdom
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Robindra Basu Roy
- Centre for International Child Health, Department of Paediatrics, Imperial College London, St. Mary's Hospital, Praed Street, London, W2 1NY, United Kingdom
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
- The Vaccine Centre, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | - Maria Gomez-Romero
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
- Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Verena Horneffer-van der Sluis
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
| | - Matthew R Lewis
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
- Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Stephane S M Camuzeaux
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
| | - Beatriz Jiménez
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
- MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, IRDB Building, Du Cane Road, London, W12 0NN, United Kingdom
- Clinical Phenotyping Centre, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Joram M Posma
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Leopold Tientcheu
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
| | - Uzochukwu Egere
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
| | - Abdou Sillah
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
| | - Toyin Togun
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia
- The Vaccine Centre, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom
| | - Elaine Holmes
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, South Kensington, London, SW7 2AZ, United Kingdom
| | - Beate Kampmann
- Centre for International Child Health, Department of Paediatrics, Imperial College London, St. Mary's Hospital, Praed Street, London, W2 1NY, United Kingdom.
- MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, Vaccines and Immunity Theme, Atlantic Road, Fajara, The Gambia.
- The Vaccine Centre, Department of Clinical Research, Faculty of Infectious and Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London, WC1E 7HT, United Kingdom.
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Sands CJ, Wolfer AM, Correia GDS, Sadawi N, Ahmed A, Jiménez B, Lewis MR, Glen RC, Nicholson JK, Pearce JTM. The nPYc-Toolbox, a Python module for the pre-processing, quality-control and analysis of metabolic profiling datasets. Bioinformatics 2019; 35:5359-5360. [PMID: 31350543 PMCID: PMC6954639 DOI: 10.1093/bioinformatics/btz566] [Citation(s) in RCA: 25] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2019] [Revised: 06/18/2019] [Accepted: 07/19/2019] [Indexed: 12/24/2022] Open
Abstract
SUMMARY As large-scale metabolic phenotyping studies become increasingly common, the need for systemic methods for pre-processing and quality control (QC) of analytical data prior to statistical analysis has become increasingly important, both within a study, and to allow meaningful inter-study comparisons. The nPYc-Toolbox provides software for the import, pre-processing, QC and visualization of metabolic phenotyping datasets, either interactively, or in automated pipelines. AVAILABILITY AND IMPLEMENTATION The nPYc-Toolbox is implemented in Python, and is freely available from the Python package index https://pypi.org/project/nPYc/, source is available at https://github.com/phenomecentre/nPYc-Toolbox. Full documentation can be found at http://npyc-toolbox.readthedocs.io/ and exemplar datasets and tutorials at https://github.com/phenomecentre/nPYc-toolbox-tutorials.
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Affiliation(s)
- Caroline J Sands
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
| | - Arnaud M Wolfer
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
| | - Gonçalo D S Correia
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
| | - Noureddin Sadawi
- Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Arfan Ahmed
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
| | - Beatriz Jiménez
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
- Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Matthew R Lewis
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
- Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Robert C Glen
- Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Jeremy K Nicholson
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
- Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
| | - Jake T M Pearce
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Surgery & Cancer, Imperial College London, London, UK
- Division of Integrative Systems Medicine and Digestive Diseases, Department of Surgery & Cancer, Imperial College London, South Kensington, London, UK
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Wang X, Nijman R, Camuzeaux S, Sands C, Jackson H, Kaforou M, Emonts M, Herberg JA, Maconochie I, Carrol ED, Paulus SC, Zenz W, Van der Flier M, de Groot R, Martinon-Torres F, Schlapbach LJ, Pollard AJ, Fink C, Kuijpers TT, Anderson S, Lewis MR, Levin M, McClure M. Plasma lipid profiles discriminate bacterial from viral infection in febrile children. Sci Rep 2019; 9:17714. [PMID: 31776453 PMCID: PMC6881435 DOI: 10.1038/s41598-019-53721-1] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2019] [Accepted: 11/03/2019] [Indexed: 11/16/2022] Open
Abstract
Fever is the most common reason that children present to Emergency Departments. Clinical signs and symptoms suggestive of bacterial infection are often non-specific, and there is no definitive test for the accurate diagnosis of infection. The 'omics' approaches to identifying biomarkers from the host-response to bacterial infection are promising. In this study, lipidomic analysis was carried out with plasma samples obtained from febrile children with confirmed bacterial infection (n = 20) and confirmed viral infection (n = 20). We show for the first time that bacterial and viral infection produces distinct profile in the host lipidome. Some species of glycerophosphoinositol, sphingomyelin, lysophosphatidylcholine and cholesterol sulfate were higher in the confirmed virus infected group, while some species of fatty acids, glycerophosphocholine, glycerophosphoserine, lactosylceramide and bilirubin were lower in the confirmed virus infected group when compared with confirmed bacterial infected group. A combination of three lipids achieved an area under the receiver operating characteristic (ROC) curve of 0.911 (95% CI 0.81 to 0.98). This pilot study demonstrates the potential of metabolic biomarkers to assist clinicians in distinguishing bacterial from viral infection in febrile children, to facilitate effective clinical management and to the limit inappropriate use of antibiotics.
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Affiliation(s)
- Xinzhu Wang
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom
| | - Ruud Nijman
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom
| | - Stephane Camuzeaux
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Metabolism, Digestion and Reproduction, IRDB Building, Du Cane Road, Imperial College London, London, W12 0NN, United Kingdom
| | - Caroline Sands
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Metabolism, Digestion and Reproduction, IRDB Building, Du Cane Road, Imperial College London, London, W12 0NN, United Kingdom
| | - Heather Jackson
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom
| | - Myrsini Kaforou
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom
| | - Marieke Emonts
- Great North Children's Hospital, Paediatric Immunology, Infectious Diseases & Allergy, Newcastle upon Tyne Hospitals NHS Foundation Trust, Newcastle upon Tyne, NE1 4LP, United Kingdom
- Translational and Clinical Research Institute, Newcastle University, Newcastle upon Tyne, NE2 4HH, United Kingdom
- NIHR Newcastle Biomedical Research Centre based at Newcastle upon Tyne Hospitals NHS Trust and Newcastle University, Newcastle upon Tyne, NE4 5PL, United Kingdom
| | - Jethro A Herberg
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom
| | - Ian Maconochie
- Department of Paediatric Emergency Medicine, St Mary's Hospital, Imperial College NHS Healthcare Trust, London, W2 1NY, United Kingdom
| | - Enitan D Carrol
- Institute of Infection and Global Health, University of Liverpool, Liverpool, L69 7BE, United Kingdom
- Department of Infectious Diseases, Alder Hey Children's NHS Foundation Trust, Liverpool, L12 2AP, United Kingdom
- Liverpool Health Partners, Liverpool, L3 5TF, United Kingdom
| | - Stephane C Paulus
- Department of Infectious Diseases, Alder Hey Children's NHS Foundation Trust, Liverpool, L12 2AP, United Kingdom
- Liverpool Health Partners, Liverpool, L3 5TF, United Kingdom
| | - Werner Zenz
- Department of General Paediatrics, Medical University of Graz, Graz, Auenbruggerplatz 34/2, 8036, Graz, Austria
| | - Michiel Van der Flier
- Pediatric Infectious Diseases and Immunology, Wilhelmina Children's Hospital, University Medical Center Utrecht, Utrecht, 3508 AB, The Netherlands
- Pediatric Infectious Diseases and Immunology, Amalia Children's Hospital, and Section Pediatric Infectious Diseases, Laboratory of Medical Immunology, Department of Laboratory Medicine, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, 6500 HB, The Netherlands
| | - Ronald de Groot
- Pediatric Infectious Diseases and Immunology, Amalia Children's Hospital, and Section Pediatric Infectious Diseases, Laboratory of Medical Immunology, Department of Laboratory Medicine, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, 6500 HB, The Netherlands
| | - Federico Martinon-Torres
- Genetic, Vaccines and Pediatric Infectious Diseases Research Group (GENVIP), Instituto de Investigación Sanitaria de Santiago and Universidad de Santiago de Compostela (USC), Galicia, Spain
- Translational Pediatrics and Infectious Diseases, Department of Pediatrics, Hospital Clínico Universitario de Santiago de Compostela, Galicia, 15706, Spain
| | - Luregn J Schlapbach
- Paediatirc Criticial Care Research Group, Child Health Research Centre, The University of Queensland and Paediatric Intensive Care Research Group, Queensland Children's Hospital, Brisbane, Australia
| | - Andrew J Pollard
- Department of Paediatrics, University of Oxford and the NIHR Oxford Biomedical Research Centre, Oxford, OX3 9DU, United Kingdom
| | - Colin Fink
- Micropathology Ltd, University of Warwick, Warwick, CV4 7EZ, United Kingdom
| | - Taco T Kuijpers
- Division of Pediatric Hematology, Immunology and Infectious diseases, Emma Children's Hospital Academic Medical Center, Amsterdam, 1105 AZ, The Netherlands
| | - Suzanne Anderson
- Medical Research Council Unit at the London School of Hygiene & Tropical Medicine, Banjul, The Gambia
| | - Matthew R Lewis
- National Phenome Centre and Imperial Clinical Phenotyping Centre, Department of Metabolism, Digestion and Reproduction, IRDB Building, Du Cane Road, Imperial College London, London, W12 0NN, United Kingdom
| | - Michael Levin
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom
| | - Myra McClure
- Department of Infectious Disease, Imperial College London, London, W2 1PG, United Kingdom.
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Whiley L, Chekmeneva E, Berry DJ, Jiménez B, Yuen AHY, Salam A, Hussain H, Witt M, Takats Z, Nicholson J, Lewis MR. Systematic Isolation and Structure Elucidation of Urinary Metabolites Optimized for the Analytical-Scale Molecular Profiling Laboratory. Anal Chem 2019; 91:8873-8882. [PMID: 31188566 PMCID: PMC6666900 DOI: 10.1021/acs.analchem.9b00241] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
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Annotation
and identification of metabolite biomarkers is critical
for their biological interpretation in metabolic phenotyping studies,
presenting a significant bottleneck in the successful implementation
of untargeted metabolomics. Here, a systematic multistep protocol
was developed for the purification and de novo structural elucidation
of urinary metabolites. The protocol is most suited for instances
where structure elucidation and metabolite annotation are critical
for the downstream biological interpretation of metabolic phenotyping
studies. First, a bulk urine pool was desalted using ion-exchange
resins enabling large-scale fractionation using precise iterations
of analytical scale chromatography. Primary urine fractions were collected
and assembled into a “fraction bank” suitable for long-term
laboratory storage. Secondary and tertiary fractionations exploited
differences in selectivity across a range of reversed-phase chemistries,
achieving the purification of metabolites of interest yielding an
amount of material suitable for chemical characterization. To exemplify
the application of the systematic workflow in a diverse set of cases,
four metabolites with a range of physicochemical properties were selected
and purified from urine and subjected to chemical formula and structure
elucidation by respective magnetic resonance mass spectrometry (MRMS)
and NMR analyses. Their structures were fully assigned as tetrahydropentoxyline,
indole-3-acetic-acid-O-glucuronide, p-cresol glucuronide, and pregnanediol-3-glucuronide. Unused effluent
was collected, dried, and returned to the fraction bank, demonstrating
the viability of the system for repeat use in metabolite annotation
with a high degree of efficiency.
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Affiliation(s)
- Luke Whiley
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom.,UK Dementia Research Institute , Imperial College London, Hammersmith Hospital , Burlington Danes Building , London , W12 0NN , United Kingdom
| | - Elena Chekmeneva
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - David J Berry
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Beatriz Jiménez
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Ada H Y Yuen
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Ash Salam
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Humma Hussain
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Matthias Witt
- Bruker Daltonik GmbH , MRMS Solutions , 28359 Bremen , Germany
| | - Zoltan Takats
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Jeremy Nicholson
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
| | - Matthew R Lewis
- The MRC-NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre , Imperial College London , London , W12 0NN , United Kingdom
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Gafson AR, Savva C, Thorne T, David M, Gomez-Romero M, Lewis MR, Nicholas R, Heslegrave A, Zetterberg H, Matthews PM. Breaking the cycle: Reversal of flux in the tricarboxylic acid cycle by dimethyl fumarate. Neurol Neuroimmunol Neuroinflamm 2019; 6:e562. [PMID: 31086805 PMCID: PMC6481230 DOI: 10.1212/nxi.0000000000000562] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/08/2019] [Accepted: 02/27/2019] [Indexed: 12/17/2022]
Abstract
Objective To infer molecular effectors of therapeutic effects and adverse events for dimethyl fumarate (DMF) in patients with relapsing-remitting MS (RRMS) using untargeted plasma metabolomics. Methods Plasma from 27 patients with RRMS was collected at baseline and 6 weeks after initiating DMF. Patients were separated into discovery (n = 15) and validation cohorts (n = 12). Ten healthy controls were also recruited. Metabolomic profiling using ultra-high-performance liquid chromatography mass spectrometry (UPLC-MS) was performed on the discovery cohort and healthy controls at Metabolon Inc (Durham, NC). UPLC-MS was performed on the validation cohort at the National Phenome Centre (London, UK). Plasma neurofilament concentration (pNfL) was assayed using the Simoa platform (Quanterix, Lexington, MA). Time course and cross-sectional analyses were performed to identify pharmacodynamic changes in the metabolome secondary to DMF and relate these to adverse events. Results In the discovery cohort, tricarboxylic acid (TCA) cycle intermediates fumarate and succinate, and TCA cycle metabolites succinyl-carnitine and methyl succinyl-carnitine increased 6 weeks following treatment (q < 0.05). Methyl succinyl-carnitine increased in the validation cohort (q < 0.05). These changes were not observed in the control population. Increased succinyl-carnitine and methyl succinyl-carnitine were associated with adverse events from DMF (flushing and abdominal symptoms). pNfL concentration was higher in patients with RRMS than in controls and reduced over 15 months of treatment. Conclusion TCA cycle intermediates and metabolites are increased in patients with RRMS treated with DMF. The results suggest reversal of flux through the succinate dehydrogenase complex. The contribution of succinyl-carnitine ester agonism at hydroxycarboxylic acid receptor 2 to both therapeutic effects and adverse events requires investigation.
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Affiliation(s)
- Arie R Gafson
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Constantinos Savva
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Tom Thorne
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Mark David
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Maria Gomez-Romero
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Matthew R Lewis
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Richard Nicholas
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Amanda Heslegrave
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Henrik Zetterberg
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
| | - Paul M Matthews
- Division of Brain Sciences (T.T., R.N., P.M.M.), Department of Medicine, Imperial College, London; St Edmund Hall (C.S., P.M.M.), Oxford University, Oxford, UK; MRC-NIHR National Phenome Centre (M.D., M.G.-R., M.R.L.), Department of Surgery and Cancer, Imperial College; University College London Queen Square Institute of Neurology (A.H., H.Z.); UK Dementia Research Institute, University College London (A.H., H.Z.), London, UK; Department of Psychiatry and Neurochemistry (H.Z.), Institute of Neuroscience and Physiology, the Sahlgrenska Academy, the University of Gothenburg; Clinical Neurochemistry Laboratory (H.Z.), Sahlgrenska University Hospital, Mölndal, Sweden; and UK Dementia Research Institute at Imperial College (P.M.M.), London
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Whiley L, Nye LC, Grant I, Andreas N, Chappell KE, Sarafian MH, Misra R, Plumb RS, Lewis MR, Nicholson JK, Holmes E, Swann JR, Wilson ID. Ultrahigh-Performance Liquid Chromatography Tandem Mass Spectrometry with Electrospray Ionization Quantification of Tryptophan Metabolites and Markers of Gut Health in Serum and Plasma-Application to Clinical and Epidemiology Cohorts. Anal Chem 2019; 91:5207-5216. [PMID: 30848589 PMCID: PMC6503468 DOI: 10.1021/acs.analchem.8b05884] [Citation(s) in RCA: 67] [Impact Index Per Article: 13.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
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A targeted
ultrahigh-performance liquid chromatography tandem mass
spectrometry with electrospray ionization (UHPLC-ESI-MS/MS) method
has been developed for the quantification of tryptophan and its downstream
metabolites from the kynurenine and serotonin pathways. The assay
coverage also includes markers of gut health and inflammation, including
citrulline and neopterin. The method was designed in 96-well plate
format for application in multiday, multiplate clinical and epidemiology
population studies. A chromatographic cycle time of 7 min enables
the analysis of two 96-well plates in 24 h. To protect chromatographic
column lifespan, samples underwent a two-step extraction, using solvent
protein precipitation followed by delipidation via solid-phase extraction
(SPE). Analytical validation reported accuracy of each analyte <20%
for the lowest limit of quantification and <15% for all other quality
control (QC) levels. The analytical precision for each analyte was
2.1–12.9%. To test the applicability of the method to multiplate
and multiday preparations, a serum pool underwent periodic repeat
analysis during a run consisting of 18 plates. The % CV (coefficient
of variation) values obtained for each analyte were <15%. Additional
biological testing applied the assay to samples collected from healthy
control participants and two groups diagnosed with inflammatory bowel
disease (IBD) (one group treated with the anti-inflammatory 5-aminosalicylic
acid (5-ASA) and one group untreated), with results showing significant
differences in the concentrations of picolinic acid, kynurenine, and
xanthurenic acid. The short analysis time and 96-well plate format
of the assay makes it suitable for high-throughput targeted UHPLC-ESI-MS/MS
metabolomic analysis in large-scale clinical and epidemiological population
studies.
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Affiliation(s)
- Luke Whiley
- UK Dementia Research Institute, Burlington Danes Building , Imperial College London , Hammersmith Hospital, London W12 0NN , United Kingdom.,MRC-NIHR National Phenome Centre, IRDB Building , Imperial College London , Hammersmith Hospital, London W12 0NN , United Kingdom
| | - Leanne C Nye
- Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom
| | - Isobelle Grant
- Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom.,Waters Corporation , Milford , Massachusetts 01757 , United States
| | - Nick Andreas
- Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom
| | - Katie E Chappell
- MRC-NIHR National Phenome Centre, IRDB Building , Imperial College London , Hammersmith Hospital, London W12 0NN , United Kingdom
| | - Magali H Sarafian
- Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom
| | - Ravi Misra
- St. Marks Hospital and Academic Institute , Watford Road , Middlesex, London HA1 3UJ , United Kingdom
| | - Robert S Plumb
- Waters Corporation , Milford , Massachusetts 01757 , United States
| | - Matthew R Lewis
- MRC-NIHR National Phenome Centre, IRDB Building , Imperial College London , Hammersmith Hospital, London W12 0NN , United Kingdom
| | - Jeremy K Nicholson
- Australian National Phenome Centre , Murdoch University , Harry Perkins Building , Perth , Western Australia 6150 , Australia
| | - Elaine Holmes
- UK Dementia Research Institute, Burlington Danes Building , Imperial College London , Hammersmith Hospital, London W12 0NN , United Kingdom.,MRC-NIHR National Phenome Centre, IRDB Building , Imperial College London , Hammersmith Hospital, London W12 0NN , United Kingdom.,Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom.,Australian National Phenome Centre , Murdoch University , Harry Perkins Building , Perth , Western Australia 6150 , Australia
| | - Jonathan R Swann
- Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom
| | - Ian D Wilson
- Division of Integrative Systems and Digestive Medicine, Department of Surgery and Cancer , Imperial College London , Sir Alexander Fleming Building, South Kensington Campus , London SW7 2AZ , United Kingdom
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Izzi‐Engbeaya C, Comninos AN, Clarke SA, Jomard A, Yang L, Jones S, Abbara A, Narayanaswamy S, Eng PC, Papadopoulou D, Prague JK, Bech P, Godsland IF, Bassett P, Sands C, Camuzeaux S, Gomez‐Romero M, Pearce JTM, Lewis MR, Holmes E, Nicholson JK, Tan T, Ratnasabapathy R, Hu M, Carrat G, Piemonti L, Bugliani M, Marchetti P, Johnson PR, Hughes SJ, James Shapiro AM, Rutter GA, Dhillo WS. The effects of kisspeptin on β-cell function, serum metabolites and appetite in humans. Diabetes Obes Metab 2018; 20:2800-2810. [PMID: 29974637 PMCID: PMC6282711 DOI: 10.1111/dom.13460] [Citation(s) in RCA: 65] [Impact Index Per Article: 10.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Revised: 06/22/2018] [Accepted: 06/29/2018] [Indexed: 02/06/2023]
Abstract
AIMS To investigate the effect of kisspeptin on glucose-stimulated insulin secretion and appetite in humans. MATERIALS AND METHODS In 15 healthy men (age: 25.2 ± 1.1 years; BMI: 22.3 ± 0.5 kg m-2 ), we compared the effects of 1 nmol kg-1 h-1 kisspeptin versus vehicle administration on glucose-stimulated insulin secretion, metabolites, gut hormones, appetite and food intake. In addition, we assessed the effect of kisspeptin on glucose-stimulated insulin secretion in vitro in human pancreatic islets and a human β-cell line (EndoC-βH1 cells). RESULTS Kisspeptin administration to healthy men enhanced insulin secretion following an intravenous glucose load, and modulated serum metabolites. In keeping with this, kisspeptin increased glucose-stimulated insulin secretion from human islets and a human pancreatic cell line in vitro. In addition, kisspeptin administration did not alter gut hormones, appetite or food intake in healthy men. CONCLUSIONS Collectively, these data demonstrate for the first time a beneficial role for kisspeptin in insulin secretion in humans in vivo. This has important implications for our understanding of the links between reproduction and metabolism in humans, as well as for the ongoing translational development of kisspeptin-based therapies for reproductive and potentially metabolic conditions.
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Affiliation(s)
- Chioma Izzi‐Engbeaya
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Alexander N. Comninos
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
- Department of EndocrinologyImperial College Healthcare NHS TrustLondonUK
| | - Sophie A. Clarke
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Anne Jomard
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Lisa Yang
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Sophie Jones
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Ali Abbara
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Shakunthala Narayanaswamy
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Pei Chia Eng
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Deborah Papadopoulou
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Julia K. Prague
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Paul Bech
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Ian F. Godsland
- Section of Metabolic Medicine, Department of Medicine, Imperial College LondonSt Mary's HospitalLondonUK
| | | | - Caroline Sands
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Stephane Camuzeaux
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Maria Gomez‐Romero
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Jake T. M. Pearce
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Matthew R. Lewis
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Elaine Holmes
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Jeremy K. Nicholson
- The MRC‐NIHR National Phenome Centre and Imperial BRC Clinical Phenotyping Centre, Division of Computational, Systems and Digestive Medicine, Department of Surgery and CancerLondonUK
| | - Tricia Tan
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Risheka Ratnasabapathy
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
| | - Ming Hu
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
- Imperial Pancreatic Islet Biology and Diabetes ConsortiumHammersmith Hospital, Imperial College LondonLondonUK
| | - Gaelle Carrat
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
- Imperial Pancreatic Islet Biology and Diabetes ConsortiumHammersmith Hospital, Imperial College LondonLondonUK
| | - Lorenzo Piemonti
- Diabetes Research Institute (SR‐DRI), IRCCS San Raffaele Scientific InstituteMilanItaly
- Faculty of MedicineVita‐Salute San Raffaele UniversityMilanItaly
| | - Marco Bugliani
- Department of Clinical and Experimental Medicine, Islet Cell LaboratoryUniversity of PisaPisaItaly
| | - Piero Marchetti
- Department of Clinical and Experimental Medicine, Islet Cell LaboratoryUniversity of PisaPisaItaly
| | - Paul R. Johnson
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- Oxford Centre for Diabetes, Endocrinology, and MetabolismUniversity of OxfordOxfordUK
- National Institute of Health Research Oxford Biomedical Research Centre, Churchill HospitalOxfordUK
| | - Stephen J. Hughes
- Nuffield Department of Surgical SciencesUniversity of OxfordOxfordUK
- Oxford Centre for Diabetes, Endocrinology, and MetabolismUniversity of OxfordOxfordUK
- National Institute of Health Research Oxford Biomedical Research Centre, Churchill HospitalOxfordUK
| | - A. M. James Shapiro
- Clinical Islet Laboratory and Clinical Islet Transplant ProgramUniversity of AlbertaEdmontonCanada
| | - Guy A. Rutter
- Section of Cell Biology and Functional Genomics, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
- Imperial Pancreatic Islet Biology and Diabetes ConsortiumHammersmith Hospital, Imperial College LondonLondonUK
| | - Waljit S. Dhillo
- Section of Endocrinology and Investigative Medicine, Division of Diabetes, Endocrinology and Metabolism, Department of MedicineImperial College LondonLondonUK
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Jiménez B, Holmes E, Heude C, Tolson RF, Harvey N, Lodge SL, Chetwynd AJ, Cannet C, Fang F, Pearce JTM, Lewis MR, Viant MR, Lindon JC, Spraul M, Schäfer H, Nicholson JK. Quantitative Lipoprotein Subclass and Low Molecular Weight Metabolite Analysis in Human Serum and Plasma by 1H NMR Spectroscopy in a Multilaboratory Trial. Anal Chem 2018; 90:11962-11971. [PMID: 30211542 DOI: 10.1021/acs.analchem.8b02412] [Citation(s) in RCA: 143] [Impact Index Per Article: 23.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
We report an extensive 600 MHz NMR trial of quantitative lipoprotein and small-molecule measurements in human blood serum and plasma. Five centers with eleven 600 MHz NMR spectrometers were used to analyze 98 samples including 20 quality controls (QCs), 37 commercially sourced, paired serum and plasma samples, and two National Institute of Science and Technology (NIST) reference material 1951c replicates. Samples were analyzed using rigorous protocols for sample preparation and experimental acquisition. A commercial lipoprotein subclass analysis was used to quantify 105 lipoprotein subclasses and 24 low molecular weight metabolites from the NMR spectra. For all spectrometers, the instrument specific variance in measuring internal QCs was lower than the percentage described by the National Cholesterol Education Program (NCEP) criteria for lipid testing [triglycerides <2.7%; cholesterol <2.8%; low-density lipoprotein (LDL) cholesterol <2.8%; high-density lipoprotein (HDL) cholesterol <2.3%], showing exceptional reproducibility for direct quantitation of lipoproteins in both matrixes. The average relative standard deviations (RSDs) for the 105 lipoprotein parameters in the 11 instruments were 4.6% and 3.9% for the two NIST samples, whereas they were 38% and 40% for the 37 commercially sourced plasmas and sera, respectively, showing negligible analytical compared to biological variation. The coefficient of variance (CV) obtained for the quantification of the small molecules across the 11 spectrometers was below 15% for 20 out of the 24 metabolites analyzed. This study provides further evidence of the suitability of NMR for high-throughput lipoprotein subcomponent analysis and small-molecule quantitation with the exceptional required reproducibility for clinical and other regulatory settings.
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Affiliation(s)
- Beatriz Jiménez
- The Imperial Clinical Phenotyping Centre, Division of Integrative Systems Medicine and Digestive Disease, Department of Surgery and Cancer , QEQM Building, Saint Mary's Hospital , London W2 1NY , United Kingdom
| | | | - Clement Heude
- Phenome Centre Birmingham , University of Birmingham , Edgbaston, Birmingham B15 2TT , United Kingdom
| | | | | | - Samantha L Lodge
- The Imperial Clinical Phenotyping Centre, Division of Integrative Systems Medicine and Digestive Disease, Department of Surgery and Cancer , QEQM Building, Saint Mary's Hospital , London W2 1NY , United Kingdom
| | - Andrew J Chetwynd
- Phenome Centre Birmingham , University of Birmingham , Edgbaston, Birmingham B15 2TT , United Kingdom
| | - Claire Cannet
- Bruker Biospin GmbH , Silberstreifen, 76287 Rheinstetten , Germany
| | - Fang Fang
- Bruker Biospin GmbH , Silberstreifen, 76287 Rheinstetten , Germany
| | - Jake T M Pearce
- The Imperial Clinical Phenotyping Centre, Division of Integrative Systems Medicine and Digestive Disease, Department of Surgery and Cancer , QEQM Building, Saint Mary's Hospital , London W2 1NY , United Kingdom
| | - Matthew R Lewis
- The Imperial Clinical Phenotyping Centre, Division of Integrative Systems Medicine and Digestive Disease, Department of Surgery and Cancer , QEQM Building, Saint Mary's Hospital , London W2 1NY , United Kingdom
| | - Mark R Viant
- Phenome Centre Birmingham , University of Birmingham , Edgbaston, Birmingham B15 2TT , United Kingdom
| | | | - Manfred Spraul
- Bruker Biospin GmbH , Silberstreifen, 76287 Rheinstetten , Germany
| | - Hartmut Schäfer
- Bruker Biospin GmbH , Silberstreifen, 76287 Rheinstetten , Germany
| | - Jeremy K Nicholson
- The Imperial Clinical Phenotyping Centre, Division of Integrative Systems Medicine and Digestive Disease, Department of Surgery and Cancer , QEQM Building, Saint Mary's Hospital , London W2 1NY , United Kingdom
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47
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Broadhurst D, Goodacre R, Reinke SN, Kuligowski J, Wilson ID, Lewis MR, Dunn WB. Guidelines and considerations for the use of system suitability and quality control samples in mass spectrometry assays applied in untargeted clinical metabolomic studies. Metabolomics 2018; 14:72. [PMID: 29805336 PMCID: PMC5960010 DOI: 10.1007/s11306-018-1367-3] [Citation(s) in RCA: 437] [Impact Index Per Article: 72.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2018] [Accepted: 05/03/2018] [Indexed: 12/25/2022]
Abstract
BACKGROUND Quality assurance (QA) and quality control (QC) are two quality management processes that are integral to the success of metabolomics including their application for the acquisition of high quality data in any high-throughput analytical chemistry laboratory. QA defines all the planned and systematic activities implemented before samples are collected, to provide confidence that a subsequent analytical process will fulfil predetermined requirements for quality. QC can be defined as the operational techniques and activities used to measure and report these quality requirements after data acquisition. AIM OF REVIEW This tutorial review will guide the reader through the use of system suitability and QC samples, why these samples should be applied and how the quality of data can be reported. KEY SCIENTIFIC CONCEPTS OF REVIEW System suitability samples are applied to assess the operation and lack of contamination of the analytical platform prior to sample analysis. Isotopically-labelled internal standards are applied to assess system stability for each sample analysed. Pooled QC samples are applied to condition the analytical platform, perform intra-study reproducibility measurements (QC) and to correct mathematically for systematic errors. Standard reference materials and long-term reference QC samples are applied for inter-study and inter-laboratory assessment of data.
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Affiliation(s)
- David Broadhurst
- School of Science, Centre for Integrative Metabolomics and Computational Biology, Edith Cowan University, Joondalup, Perth, Australia
| | - Royston Goodacre
- School of Chemistry, Manchester Institute of Biotechnology, University of Manchester, Manchester, M1 7DN, UK
| | - Stacey N Reinke
- School of Science, Centre for Integrative Metabolomics and Computational Biology, Edith Cowan University, Joondalup, Perth, Australia
- Separation Sciences and Metabolomics Laboratory, Murdoch University, Perth, WA, Australia
| | - Julia Kuligowski
- Neonatal Research Unit, Health Research Institute La Fe, Avda. Fernando Abril Martorell 106, 46026, Valencia, Spain
| | - Ian D Wilson
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2AZ, UK
| | - Matthew R Lewis
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2AZ, UK
| | - Warwick B Dunn
- School of Biosciences, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
- Phenome Centre Birmingham, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
- Institute of Metabolism and Systems Research, University of Birmingham, Edgbaston, Birmingham, B15 2TT, UK.
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48
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van Golen RF, Olthof PB, de Haan LR, Coelen RJ, Pechlivanis A, de Keijzer MJ, Weijer R, de Waart DR, van Kuilenburg ABP, Roelofsen J, Gilijamse PW, Maas MA, Lewis MR, Nicholson JK, Verheij J, Heger M. The pathophysiology of human obstructive cholestasis is mimicked in cholestatic Gold Syrian hamsters. Biochim Biophys Acta Mol Basis Dis 2017; 1864:942-951. [PMID: 29196240 DOI: 10.1016/j.bbadis.2017.11.022] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2017] [Revised: 11/25/2017] [Accepted: 11/27/2017] [Indexed: 12/12/2022]
Abstract
Obstructive cholestasis causes liver injury via accumulation of toxic bile acids (BAs). Therapeutic options for cholestatic liver disease are limited, partially because the available murine disease models lack translational value. Profiling of time-related changes following bile duct ligation (BDL) in Gold Syrian hamsters revealed a biochemical response similar to cholestatic patients in terms of BA pool composition, alterations in hepatocyte BA transport and signaling, suppression of BA production, and adapted BA metabolism. Hamsters tolerated cholestasis well for up to 28days and progressed relatively slowly to fibrotic liver injury. Hepatocellular necrosis was absent, which coincided with preserved intrahepatic energy levels and only mild oxidative stress. The histological response to cholestasis in hamsters was similar to the changes seen in 17 patients with prolonged obstructive cholestasis caused by cholangiocarcinoma. Hamsters moreover upregulated hepatic fibroblast growth factor 15 (Fgf15) expression in response to BDL, which is a cytoprotective adaptation to cholestasis that hitherto had only been documented in cholestatic human livers. Hamster models should therefore be added to the repertoire of animal models used to study the pathophysiology of cholestatic liver disease.
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Affiliation(s)
- Rowan F van Golen
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Pim B Olthof
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Lianne R de Haan
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Robert J Coelen
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Alexandros Pechlivanis
- Division of Computational, Systems and Digestive Medicine, Department of Surgery and Cancer, South Kensington Campus, London, SW7 2AZ, UK
| | - Mark J de Keijzer
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Ruud Weijer
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Dirk R de Waart
- Tytgat Institute for Liver and Intestinal Research, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - André B P van Kuilenburg
- Laboratory Genetic Metabolic Disorders, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Jeroen Roelofsen
- Laboratory Genetic Metabolic Disorders, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Pim W Gilijamse
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Martinus A Maas
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Matthew R Lewis
- Division of Computational, Systems and Digestive Medicine, Department of Surgery and Cancer, South Kensington Campus, London, SW7 2AZ, UK; MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
| | - Jeremy K Nicholson
- Division of Computational, Systems and Digestive Medicine, Department of Surgery and Cancer, South Kensington Campus, London, SW7 2AZ, UK; MRC-NIHR National Phenome Centre, Department of Surgery and Cancer, Imperial College London, Hammersmith Hospital, London, W12 0NN, UK
| | - Joanne Verheij
- Department of Pathology, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands
| | - Michal Heger
- Department of Experimental Surgery, Academic Medical Center, University of Amsterdam, Amsterdam, The Netherlands; Membrane Biochemistry and Biophysics, Bijvoet Center for Biomolecular Research, Institute of Biomembranes, Utrecht University, Utrecht, The Netherlands.
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49
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Castagné R, Boulangé CL, Karaman I, Campanella G, Santos Ferreira DL, Kaluarachchi MR, Lehne B, Moayyeri A, Lewis MR, Spagou K, Dona AC, Evangelos V, Tracy R, Greenland P, Lindon JC, Herrington D, Ebbels TMD, Elliott P, Tzoulaki I, Chadeau-Hyam M. Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling. J Proteome Res 2017; 16:3623-3633. [PMID: 28823158 PMCID: PMC5633829 DOI: 10.1021/acs.jproteome.7b00344] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
1H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.
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Affiliation(s)
| | - Claire Laurence Boulangé
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K
| | | | | | | | - Manuja R Kaluarachchi
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K
| | | | - Alireza Moayyeri
- Farr Institute of Health Informatics Research, University College London Institute of Health Informatics , 222 Euston Road, NW1 2DA London, United Kingdom
| | - Matthew R Lewis
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K
| | - Konstantina Spagou
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K
| | - Anthony C Dona
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K
| | - Vangelis Evangelos
- Department of Hygiene and Epidemiology, University of Ioannina Medical School , Ioannina 45110, Greece
| | - Russell Tracy
- Department of Pathology and Laboratory Medicine, University of Vermont Larner College of Medicine , Burlington, Vermont 05405, United States
| | - Philip Greenland
- Department of Preventive Medicine and the Institute for Public Health and Medicine, Northwestern University , Chicago, Illinois 60611, United States
| | - John C Lindon
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K.,Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, South Kensington, SW7 2AZ London, United Kingdom
| | - David Herrington
- Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine , Medical Center Boulevard, Winston-Salem, North Carolina 27157, United States
| | - Timothy M D Ebbels
- Bioincubator Unit, Metabometrix Ltd , Bessemer Building, Prince Consort Road, South Kensington, London SW7 2BP U.K.,Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, South Kensington, SW7 2AZ London, United Kingdom
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50
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Hill-Burns EM, Debelius JW, Morton JT, Wissemann WT, Lewis MR, Wallen ZD, Peddada SD, Factor SA, Molho E, Zabetian CP, Knight R, Payami H. Parkinson's disease and Parkinson's disease medications have distinct signatures of the gut microbiome. Mov Disord 2017; 32:739-749. [PMID: 28195358 DOI: 10.1002/mds.26942] [Citation(s) in RCA: 538] [Impact Index Per Article: 76.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2016] [Revised: 01/06/2017] [Accepted: 01/11/2017] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND There is mounting evidence for a connection between the gut and Parkinson's disease (PD). Dysbiosis of gut microbiota could explain several features of PD. OBJECTIVE The objective of this study was to determine if PD involves dysbiosis of gut microbiome, disentangle effects of confounders, and identify candidate taxa and functional pathways to guide research. METHODS A total of 197 PD cases and 130 controls were studied. Microbial composition was determined by 16S rRNA gene sequencing of DNA extracted from stool. Metadata were collected on 39 potential confounders including medications, diet, gastrointestinal symptoms, and demographics. Statistical analyses were conducted while controlling for potential confounders and correcting for multiple testing. We tested differences in the overall microbial composition, taxa abundance, and functional pathways. RESULTS Independent microbial signatures were detected for PD (P = 4E-5), participants' region of residence within the United States (P = 3E-3), age (P = 0.03), sex (P = 1E-3), and dietary fruits/vegetables (P = 0.01). Among patients, independent signals were detected for catechol-O-methyltransferase-inhibitors (P = 4E-4), anticholinergics (P = 5E-3), and possibly carbidopa/levodopa (P = 0.05). We found significantly altered abundances of the Bifidobacteriaceae, Christensenellaceae, [Tissierellaceae], Lachnospiraceae, Lactobacillaceae, Pasteurellaceae, and Verrucomicrobiaceae families. Functional predictions revealed changes in numerous pathways, including the metabolism of plant-derived compounds and xenobiotics degradation. CONCLUSION PD is accompanied by dysbiosis of gut microbiome. Results coalesce divergent findings of prior studies, reveal altered abundance of several taxa, nominate functional pathways, and demonstrate independent effects of PD medications on the microbiome. The findings provide new leads and testable hypotheses on the pathophysiology and treatment of PD. © 2017 International Parkinson and Movement Disorder Society.
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Affiliation(s)
- Erin M Hill-Burns
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Justine W Debelius
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA
| | - James T Morton
- Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA
| | - William T Wissemann
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Matthew R Lewis
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Zachary D Wallen
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA
| | - Shyamal D Peddada
- Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Stewart A Factor
- Department of Neurology, Emory University School of Medicine, Atlanta, Georgia, USA
| | - Eric Molho
- Department of Neurology, Albany Medical College, Albany, New York, USA
| | - Cyrus P Zabetian
- Veterans Affairs Puget Sound Health Care System and Department of Neurology, University of Washington, Seattle, Washington, USA
| | - Rob Knight
- Department of Pediatrics, University of California San Diego, La Jolla, California, USA.,Department of Computer Science and Engineering, University of California San Diego, La Jolla, California, USA.,Center for Microbiome Innovation, University of California San Diego, La Jolla, California, USA
| | - Haydeh Payami
- Department of Neurology, University of Alabama at Birmingham, Birmingham, Alabama, USA.,Center for Genomic Medicine, HudsonAlpha Institute for Biotechnology, Huntsville, Alabama, USA
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