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Capeding MRZ, Phee LCM, Ming C, Noti M, Vidal K, Le Carrou G, Frézal A, Moll JM, Vogt JK, Myers PN, Nielsen BH, Boulangé CL, Samuel TM, Berger B, Cercamondi CI. Safety, efficacy, and impact on gut microbial ecology of a Bifidobacterium longum subspecies infantis LMG11588 supplementation in healthy term infants: a randomized, double-blind, controlled trial in the Philippines. Front Nutr 2023; 10:1319873. [PMID: 38162520 PMCID: PMC10755859 DOI: 10.3389/fnut.2023.1319873] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 11/16/2023] [Indexed: 01/03/2024] Open
Abstract
Introduction Bifidobacterium longum subspecies infantis (B. infantis) may play a key role in infant gut development. This trial evaluated safety, tolerability, and efficacy of B. infantis LMG11588 supplementation. Methods This randomized, placebo-controlled, double-blind study conducted in the Philippines included healthy breastfed and/or formula-fed infants (14-21 days old) randomized for 8 weeks to a control group (CG; n = 77), or any of two B. infantis experimental groups (EGs): low (Lo-EG; 1*108 CFU/day; n = 75) or high dose (Hi-EG; 1.8*1010 CFU/day; n = 76). Primary endpoint was weight gain; secondary endpoints included stooling patterns, gastrointestinal symptoms, adverse events, fecal microbiome, biomarkers, pH, and organic acids. Results Non-inferiority in weight gain was demonstrated for Hi-EG and Lo-EG vs. CG. Overall, probiotic supplementation promoted mushy-soft stools, fewer regurgitation episodes, and increased fecal acetate production, which was more pronounced in the exclusively breastfed infants (EBF) and positively correlated with B. infantis abundance. In EBF, fecal pro-inflammatory cytokines (IL-1 beta, IL-8) were reduced. Strain-level metagenomic analysis allowed attributing the increased abundance of B. infantis in EGs versus CG, to LMG11588 probiotic colonization. Colonization by autochthonous B. infantis strains was similar between groups. Discussion B. infantis LMG11588 supplementation was associated with normal infant growth, was safe and well-tolerated and promoted a Bifidobacterium-rich microbiota driven by B. infantis LMG11588 colonization without disturbing the natural dispersal of autochthonous B. infantis strains. In EBF, supplementation stimulated microbial metabolic activity and beneficially modulated enteric inflammation.
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Affiliation(s)
| | | | - Chang Ming
- Biostatistics & Data, Nestlé Research, Lausanne, Switzerland
| | - Mario Noti
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., Lausanne, Switzerland
| | - Karine Vidal
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., Lausanne, Switzerland
| | - Gilles Le Carrou
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., Lausanne, Switzerland
| | - A. Frézal
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., Lausanne, Switzerland
| | | | | | | | | | - Claire L. Boulangé
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., Lausanne, Switzerland
| | - Tinu Mary Samuel
- Nestlé Product Technology Center – Nutrition, Société des Produits Nestlé S.A., Vevey, Switzerland
| | - Bernard Berger
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., Lausanne, Switzerland
| | - Colin Ivano Cercamondi
- Nestlé Product Technology Center – Nutrition, Société des Produits Nestlé S.A., Vevey, Switzerland
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Boulangé CL, Pedersen HK, Martin FP, Siegwald L, Pallejà Caro A, Eklund AC, Jia W, Zhang H, Berger B, Sprenger N, Heine RG, Cinnamon Study Investigator Group. An Extensively Hydrolyzed Formula Supplemented with Two Human Milk Oligosaccharides Modifies the Fecal Microbiome and Metabolome in Infants with Cow's Milk Protein Allergy. Int J Mol Sci 2023; 24:11422. [PMID: 37511184 PMCID: PMC10379726 DOI: 10.3390/ijms241411422] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2023] [Revised: 06/27/2023] [Accepted: 06/29/2023] [Indexed: 07/30/2023] Open
Abstract
Cow's milk protein allergy (CMPA) is a prevalent food allergy among infants and young children. We conducted a randomized, multicenter intervention study involving 194 non-breastfed infants with CMPA until 12 months of age (clinical trial registration: NCT03085134). One exploratory objective was to assess the effects of a whey-based extensively hydrolyzed formula (EHF) supplemented with 2'-fucosyllactose (2'-FL) and lacto-N-neotetraose (LNnT) on the fecal microbiome and metabolome in this population. Thus, fecal samples were collected at baseline, 1 and 3 months from enrollment, as well as at 12 months of age. Human milk oligosaccharides (HMO) supplementation led to the enrichment of bifidobacteria in the gut microbiome and delayed the shift of the microbiome composition toward an adult-like pattern. We identified specific HMO-mediated changes in fecal amino acid degradation and bile acid conjugation, particularly in infants commencing the HMO-supplemented formula before the age of three months. Thus, HMO supplementation partially corrected the dysbiosis commonly observed in infants with CMPA. Further investigation is necessary to determine the clinical significance of these findings in terms of a reduced incidence of respiratory infections and other potential health benefits.
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Affiliation(s)
- Claire L Boulangé
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., 1000 Lausanne, Switzerland
| | | | - Francois-Pierre Martin
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., 1000 Lausanne, Switzerland
| | - Léa Siegwald
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., 1000 Lausanne, Switzerland
| | | | | | - Wei Jia
- University of Hawaii Cancer Center, Honolulu, HI 96813, USA
- School of Chinese Medicine, Hong Kong Baptist University, Kowloon Tong, Hong Kong 999077, China
| | - Huizhen Zhang
- University of Hawaii Cancer Center, Honolulu, HI 96813, USA
| | - Bernard Berger
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., 1000 Lausanne, Switzerland
| | - Norbert Sprenger
- Nestlé Institute of Health Sciences, Nestlé Research, Société des Produits Nestlé S.A., 1000 Lausanne, Switzerland
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Jaggard MKJ, Boulangé CL, Graça G, Akhbari P, Vaghela U, Bhattacharya R, Williams HRT, Lindon JC, Gupte CM. The effect of liquid-liquid extraction on metabolite detection and analysis using NMR spectroscopy in human synovial fluid. J Pharm Biomed Anal 2023; 226:115254. [PMID: 36701879 DOI: 10.1016/j.jpba.2023.115254] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/09/2023] [Accepted: 01/13/2023] [Indexed: 01/15/2023]
Abstract
The evaluation of joint disease using synovial fluid is an emerging field of metabolic profiling. The analysis is challenged by multiple macromolecules which can obscure the small molecule chemistry. The use of protein precipitation and extraction has been evaluated previously, but not in synovial fluid. We systematically review the published NMR spectroscopy methods of synovial fluid analysis and investigated the efficacy of three different protein precipitation techniques: methanol, acetonitrile and trichloroacetic acid. The trichloroacetic wash removed the most protein. However, metabolite recoveries were universally very poor. Acetonitrile liquid/liquid extraction gave metabolite gains from four unknown compounds with spectral peaks at δ = 1.91 ppm, 3.64 ppm, 3.95 ppm & 4.05 ppm. The metabolite recoveries for acetonitrile were between 1.5 and 7 times higher than the methanol method, across all classes of metabolite. The methanol method was more effective in removing protein as reported by the free GAG undefined peak (44 % vs 125 %). However, qualitative evaluation showed that acetonitrile and methanol provided good restoration of the spectra to baseline. The methanol extraction has issues of a gelatinous substrate in the samples. All metabolite recoveries had a CV of > 15 %. A recommendation of acetonitrile liquid/liquid extraction was made for human synovial fluid (HSF) analysis. This is due to consistency, effective protein precipitation, recovery of metabolites and additional compounds not previously visible.
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Affiliation(s)
- Matthew K J Jaggard
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, Mary's Hospital, Praed Street, Paddington, London W2 1NY, UK; Department of Surgery and Cancer, Imperial College London, South Kensington, London SW7 2AZ, UK.
| | - Claire L Boulangé
- Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington, London SW7 2AZ, UK; Department of Surgery and Cancer, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Gonçalo Graça
- Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Pouya Akhbari
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, Mary's Hospital, Praed Street, Paddington, London W2 1NY, UK; Department of Surgery and Cancer, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Uddhav Vaghela
- School of Medicine, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Rajarshi Bhattacharya
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, Mary's Hospital, Praed Street, Paddington, London W2 1NY, UK
| | - Horace R T Williams
- Department of Metabolism, Digestion and Reproduction, Imperial College London, South Kensington, London SW7 2AZ, UK; Department of Gastroenterology, Imperial College NHS Trust, Mary's Hospital, Praed Street, Paddington, London W2 1NY, UK
| | - John C Lindon
- Department of Surgery and Cancer, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Chinmay M Gupte
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, Mary's Hospital, Praed Street, Paddington, London W2 1NY, UK; Department of Surgery and Cancer, Imperial College London, South Kensington, London SW7 2AZ, UK
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Calatayud M, Börner RA, Ghyselinck J, Verstrepen L, Medts JD, den Abbeele PV, Boulangé CL, Priour S, Marzorati M, Damak S. Water Kefir and Derived Pasteurized Beverages Modulate Gut Microbiota, Intestinal Permeability and Cytokine Production In Vitro. Nutrients 2021; 13:nu13113897. [PMID: 34836151 PMCID: PMC8625349 DOI: 10.3390/nu13113897] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [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] [Subscribe] [Scholar Register] [Received: 09/21/2021] [Revised: 10/27/2021] [Accepted: 10/27/2021] [Indexed: 01/08/2023] Open
Abstract
Fermentation is an ancient food preservation process, and fermented products have been traditionally consumed in different cultures worldwide over the years. The interplay between human gut microbiota, diet and host health is widely recognized. Diet is one of the main factors modulating gut microbiota potentially with beneficial effects on human health. Fermented dairy products have received much attention, but other sources of probiotic delivery through food received far less attention. In this research, a combination of in vitro tools mimicking colonic fermentation and the intestinal epithelium have been applied to study the effect of different pasteurized and non-pasteurized water kefir products on gut microbiota, epithelial barrier function and immunomodulation. Water kefir increased beneficial short-chain fatty acid production at the microbial level, reduced detrimental proteolytic fermentation compounds and increased Bifidobacterium genus abundance. The observed benefits are enhanced by pasteurization. Pasteurized products also had a significant effect at the host level, improving inflammation-induced intestinal epithelial barrier disruption and increasing IL-10 and IL-1β compared to the control condition. Our data support the potential health benefits of water kefir and demonstrate that pasteurization, performed to prolong shelf life and stability of the product, also enhanced these benefits.
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Affiliation(s)
- Marta Calatayud
- ProDigest, Technologiepark 82, 9052 Zwijnaarde, Belgium; (M.C.); (J.G.); (L.V.); (J.D.M.); (P.V.d.A.)
- Center for Microbial Ecology and Technology (CMET), Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
| | - Rosa Aragao Börner
- Nestlé Institute of Health Sciences, and Nestlé Institute of Material Sciences, Nestlé Research, Société des Produits Nestlé S.A., Vers-chez-les-Blanc, 1000 Lausanne, Switzerland; (C.L.B.); (S.P.); (S.D.)
- Correspondence: (R.A.B.); (M.M.)
| | - Jonas Ghyselinck
- ProDigest, Technologiepark 82, 9052 Zwijnaarde, Belgium; (M.C.); (J.G.); (L.V.); (J.D.M.); (P.V.d.A.)
| | - Lynn Verstrepen
- ProDigest, Technologiepark 82, 9052 Zwijnaarde, Belgium; (M.C.); (J.G.); (L.V.); (J.D.M.); (P.V.d.A.)
| | - Jelle De Medts
- ProDigest, Technologiepark 82, 9052 Zwijnaarde, Belgium; (M.C.); (J.G.); (L.V.); (J.D.M.); (P.V.d.A.)
| | - Pieter Van den Abbeele
- ProDigest, Technologiepark 82, 9052 Zwijnaarde, Belgium; (M.C.); (J.G.); (L.V.); (J.D.M.); (P.V.d.A.)
| | - Claire L. Boulangé
- Nestlé Institute of Health Sciences, and Nestlé Institute of Material Sciences, Nestlé Research, Société des Produits Nestlé S.A., Vers-chez-les-Blanc, 1000 Lausanne, Switzerland; (C.L.B.); (S.P.); (S.D.)
| | - Sarah Priour
- Nestlé Institute of Health Sciences, and Nestlé Institute of Material Sciences, Nestlé Research, Société des Produits Nestlé S.A., Vers-chez-les-Blanc, 1000 Lausanne, Switzerland; (C.L.B.); (S.P.); (S.D.)
| | - Massimo Marzorati
- ProDigest, Technologiepark 82, 9052 Zwijnaarde, Belgium; (M.C.); (J.G.); (L.V.); (J.D.M.); (P.V.d.A.)
- Center for Microbial Ecology and Technology (CMET), Faculty of Bioscience Engineering, Ghent University, Coupure Links 653, 9000 Ghent, Belgium
- Correspondence: (R.A.B.); (M.M.)
| | - Sami Damak
- Nestlé Institute of Health Sciences, and Nestlé Institute of Material Sciences, Nestlé Research, Société des Produits Nestlé S.A., Vers-chez-les-Blanc, 1000 Lausanne, Switzerland; (C.L.B.); (S.P.); (S.D.)
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Abstract
AIMS The diagnosis of joint infections is an inexact science using combinations of blood inflammatory markers and microscopy, culture, and sensitivity of synovial fluid (SF). There is potential for small molecule metabolites in infected SF to act as infection markers that could improve accuracy and speed of detection. The objective of this study was to use nuclear magnetic resonance (NMR) spectroscopy to identify small molecule differences between infected and noninfected human SF. METHODS In all, 16 SF samples (eight infected native and prosthetic joints plus eight noninfected joints requiring arthroplasty for end-stage osteoarthritis) were collected from patients. NMR spectroscopy was used to analyze the metabolites present in each sample. Principal component analysis and univariate statistical analysis were undertaken to investigate metabolic differences between the two groups. RESULTS A total of 16 metabolites were found in significantly different concentrations between the groups. Three were in higher relative concentrations (lipids, cholesterol, and N-acetylated molecules) and 13 in lower relative concentrations in the infected group (citrate, glycine, glycosaminoglycans, creatinine, histidine, lysine, formate, glucose, proline, valine, dimethylsulfone, mannose, and glutamine). CONCLUSION Metabolites found in significantly greater concentrations in the infected cohort are markers of inflammation and infection. They play a role in lipid metabolism and the inflammatory response. Those found in significantly reduced concentrations were involved in carbohydrate metabolism, nucleoside metabolism, the glutamate metabolic pathway, increased oxidative stress in the diseased state, and reduced articular cartilage breakdown. This is the first study to demonstrate differences in the metabolic profile of infected and noninfected human SF, using a noninfected matched cohort, and may represent putative biomarkers that form the basis of new diagnostic tests for infected SF. Cite this article: Bone Joint Res 2021;10(1):85-95.
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Affiliation(s)
- Pouya Akhbari
- Department of Trauma and Orthopaedics, Imperial College Healthcare NHS Trust, London, UK
| | - Matthew K Jaggard
- Department of Trauma and Orthopaedics, Imperial College Healthcare NHS Trust, London, UK
| | - Claire L Boulangé
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Uddhav Vaghela
- Department of Surgery and Cancer, Imperial College London, London, UK
| | - Gonçalo Graça
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - Rajarshi Bhattacharya
- Department of Trauma and Orthopaedics, Imperial College Healthcare NHS Trust, London, UK
| | - John C Lindon
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Chinmay M Gupte
- Department of Trauma and Orthopaedics, Imperial College Healthcare NHS Trust, London, UK.,Department of Surgery and Cancer, Imperial College London, London, UK
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Jaggard MKJ, Boulangé CL, Graça G, Vaghela U, Akhbari P, Bhattacharya R, Williams HRT, Lindon JC, Gupte CM. Can metabolic profiling provide a new description of osteoarthritis and enable a personalised medicine approach? Clin Rheumatol 2020; 39:3875-3882. [PMID: 32488772 PMCID: PMC7648745 DOI: 10.1007/s10067-020-05106-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [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] [Received: 02/18/2020] [Revised: 03/30/2020] [Accepted: 04/16/2020] [Indexed: 12/20/2022]
Abstract
Osteoarthritis (OA) is a multifactorial disease contributing to significant disability and economic burden in Western populations. The aetiology of OA remains poorly understood, but is thought to involve genetic, mechanical and environmental factors. Currently, the diagnosis of OA relies predominantly on clinical assessment and plain radiographic changes long after the disease has been initiated. Recent advances suggest that there are changes in joint fluid metabolites that are associated with OA development. If this is the case, biochemical and metabolic biomarkers of OA could help determine prognosis, monitor disease progression and identify potential therapeutic targets. Moreover, for focussed management and personalised medicine, novel biomarkers could sub-stratify patients into OA phenotypes, differentiating metabolic OA from post-traumatic, age-related and genetic OA. To date, OA biomarkers have concentrated on cytokine action and protein signalling with some progress. However, these remain to be adopted into routine clinical practice. In this review, we outline the emerging metabolic links to OA pathogenesis and how an elucidation of the metabolic changes in this condition may provide future, more descriptive biomarkers to differentiate OA subtypes.
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Affiliation(s)
- M K J Jaggard
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, UK.,Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - C L Boulangé
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.,Nestle Research Centre, Lausanne, Switzerland
| | - G Graça
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - U Vaghela
- School of Medicine, Imperial College London, South Kensington, London, SW7 2AZ, UK.
| | - P Akhbari
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, UK.,Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - R Bhattacharya
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, UK
| | - H R T Williams
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK.,Department of Gastroenterology, Imperial College Healthcare NHS Trust, London, UK.,NIHR Imperial Biomedical Research Centre, Imperial College Healthcare NHS Trust, London, UK
| | - J C Lindon
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | - C M Gupte
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, UK.,NIHR Imperial Biomedical Research Centre, Imperial College Healthcare NHS Trust, London, UK.,Department of Surgery and Cancer, Imperial College London, London, UK
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Akhbari P, Jaggard MK, Boulangé CL, Vaghela U, Graça G, Bhattacharya R, Lindon JC, Williams HRT, Gupte CM. Differences in the composition of hip and knee synovial fluid in osteoarthritis: a nuclear magnetic resonance (NMR) spectroscopy study of metabolic profiles. Osteoarthritis Cartilage 2019; 27:1768-1777. [PMID: 31491490 DOI: 10.1016/j.joca.2019.07.017] [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] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/03/2018] [Revised: 06/04/2019] [Accepted: 07/03/2019] [Indexed: 02/02/2023]
Abstract
OBJECTIVE The hip and knee joints differ biomechanically in terms of contact stresses, fluid lubrication and wear patterns. These differences may be reflected in the synovial fluid (SF) composition of the two joints, but the nature of these differences remains unknown. The objective was to identify differences in osteoarthritic hip and knee SF metabolites using metabolic profiling with Nuclear Magnetic Resonance (NMR) spectroscopy. DESIGN Twenty-four SF samples (12 hip, 12 knee) were collected from patients with end-stage osteoarthritis (ESOA) undergoing hip/knee arthroplasty. Samples were matched for age, gender, ethnicity and had similar medical comorbidities. NMR spectroscopy was used to analyse the metabolites present in each sample. Principal Component Analysis and Orthogonal Partial Least Squares Discriminant Analysis were undertaken to investigate metabolic differences between the groups. Metabolites were identified using 2D NMR spectra, statistical spectroscopy and by comparison to entries in published databases. RESULTS There were significant differences in the metabolic profile between the groups. Four metabolites were found in significantly greater quantities in the knee group compared to the hip group (N-acetylated molecules, glycosaminoglycans, citrate and glutamine). CONCLUSIONS This is the first study to indicate differences in the metabolic profile of hip and knee SF in ESOA. The identified metabolites can broadly be grouped into those involved in collagen degradation, the tricarboxylic acid cycle and oxidative metabolism in diseased joints. These findings may represent a combination of intra and extra-articular factors.
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Affiliation(s)
- P Akhbari
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, United Kingdom.
| | - M K Jaggard
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, United Kingdom.
| | - C L Boulangé
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
| | - U Vaghela
- School of Medicine, Imperial College London, London, United Kingdom.
| | - G Graça
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
| | - R Bhattacharya
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, United Kingdom.
| | - J C Lindon
- Department of Metabolism, Digestion and Reproduction, Imperial College London, London, United Kingdom.
| | - H R T Williams
- Department of Digestive Diseases, Imperial College Healthcare NHS Trust, London, United Kingdom.
| | - C M Gupte
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, London, United Kingdom.
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Tzoulaki I, Castagné R, Boulangé CL, Karaman I, Chekmeneva E, Evangelou E, Ebbels TMD, Kaluarachchi MR, Chadeau-Hyam M, Mosen D, Dehghan A, Moayyeri A, Ferreira DLS, Guo X, Rotter JI, Taylor KD, Kavousi M, de Vries PS, Lehne B, Loh M, Hofman A, Nicholson JK, Chambers J, Gieger C, Holmes E, Tracy R, Kooner J, Greenland P, Franco OH, Herrington D, Lindon JC, Elliott P. Serum metabolic signatures of coronary and carotid atherosclerosis and subsequent cardiovascular disease. Eur Heart J 2019; 40:2883-2896. [PMID: 31102408 PMCID: PMC7963131 DOI: 10.1093/eurheartj/ehz235] [Citation(s) in RCA: 96] [Impact Index Per Article: 19.2] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2018] [Revised: 11/21/2018] [Accepted: 05/13/2019] [Indexed: 12/31/2022] Open
Abstract
AIMS To characterize serum metabolic signatures associated with atherosclerosis in the coronary or carotid arteries and subsequently their association with incident cardiovascular disease (CVD). METHODS AND RESULTS We used untargeted one-dimensional (1D) serum metabolic profiling by proton nuclear magnetic resonance spectroscopy (1H NMR) among 3867 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), with replication among 3569 participants from the Rotterdam and LOLIPOP studies. Atherosclerosis was assessed by coronary artery calcium (CAC) and carotid intima-media thickness (IMT). We used multivariable linear regression to evaluate associations between NMR features and atherosclerosis accounting for multiplicity of comparisons. We then examined associations between metabolites associated with atherosclerosis and incident CVD available in MESA and Rotterdam and explored molecular networks through bioinformatics analyses. Overall, 30 1H NMR measured metabolites were associated with CAC and/or IMT, P = 1.3 × 10-14 to 1.0 × 10-6 (discovery) and P = 5.6 × 10-10 to 1.1 × 10-2 (replication). These associations were substantially attenuated after adjustment for conventional cardiovascular risk factors. Metabolites associated with atherosclerosis revealed disturbances in lipid and carbohydrate metabolism, branched chain, and aromatic amino acid metabolism, as well as oxidative stress and inflammatory pathways. Analyses of incident CVD events showed inverse associations with creatine, creatinine, and phenylalanine, and direct associations with mannose, acetaminophen-glucuronide, and lactate as well as apolipoprotein B (P < 0.05). CONCLUSION Metabolites associated with atherosclerosis were largely consistent between the two vascular beds (coronary and carotid arteries) and predominantly tag pathways that overlap with the known cardiovascular risk factors. We present an integrated systems network that highlights a series of inter-connected pathways underlying atherosclerosis.
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Affiliation(s)
- Ioanna Tzoulaki
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, University Campus Road 455 00, Ioannina, Greece
- Dementia Research Institute, Imperial College London, Norfolk Place, London, UK
| | - Raphaële Castagné
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- LEASP, UMR 1027, Inserm-Université Toulousse III Paul Sabatier, Toulousse, France
| | - Claire L Boulangé
- Metabometrix Ltd, Imperial Incubator, Bessemer Building, Prince Consort Road, London, UK
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - Ibrahim Karaman
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
- Dementia Research Institute, Imperial College London, Norfolk Place, London, UK
| | - Elena Chekmeneva
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - Evangelos Evangelou
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
- Department of Hygiene and Epidemiology, University of Ioannina Medical School, University Campus Road 455 00, Ioannina, Greece
| | - Timothy M D Ebbels
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - Manuja R Kaluarachchi
- Metabometrix Ltd, Imperial Incubator, Bessemer Building, Prince Consort Road, London, UK
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - Marc Chadeau-Hyam
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - David Mosen
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - Abbas Dehghan
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
- Dementia Research Institute, Imperial College London, Norfolk Place, London, UK
| | - Alireza Moayyeri
- Farr Institute of Health Informatics Research, University College London Institute of Health Informatics, 222 Euston Road, London, UK
| | - Diana L Santos Ferreira
- MRC Integrative Epidemiology Unit, School of Social and Community Medicine, University of Bristol, Oakfield House, Oakfiled Grove, Bristol, UK
| | - Xiuqing Guo
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
- Department of Medicine, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
| | - Jerome I Rotter
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
- Department of Medicine, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
| | - Kent D Taylor
- Department of Pediatrics, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
- Department of Medicine, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
| | - Maryam Kavousi
- Department of Epidemiology, Erasmus University Medical Center, University Medical Center Rotterdam, CA Rotterdam, the Netherlands
| | - Paul S de Vries
- Department of Epidemiology, Erasmus University Medical Center, University Medical Center Rotterdam, CA Rotterdam, the Netherlands
- Department of Epidemiology, Human Genetics, and Environmental Sciences, Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, 1200 Pressler Street, Houston, TX, USA
| | - Benjamin Lehne
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - Marie Loh
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
| | - Albert Hofman
- Department of Epidemiology, Erasmus University Medical Center, University Medical Center Rotterdam, CA Rotterdam, the Netherlands
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, USA
| | - Jeremy K Nicholson
- Metabometrix Ltd, Imperial Incubator, Bessemer Building, Prince Consort Road, London, UK
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - John Chambers
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- London North West Healthcare NHS Trust, Northwick Park Hospital, Watford Rd, Harrow, UK
| | - Christian Gieger
- German Research Centre for Environmental Health, Helmholtz Zentrum München, Ingolstädter Landstraße 1, D Neuherberg, Germany
| | - Elaine Holmes
- Metabometrix Ltd, Imperial Incubator, Bessemer Building, Prince Consort Road, London, UK
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - Russell Tracy
- M.D. College of Medicine University of Vermont, The Robert Larner, Given Medical Bldg, E-126, 89 Beaumont Ave, Burlington, VT, USA
| | - Jaspal Kooner
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, 677 Huntington Avenue, Boston, MA, USA
- National Heart & Lung Institute, Faculty of Medicine, Imperial College London, Guy Scadding Building, Dovehouse St, Chelsea, London, UK
| | - Philip Greenland
- Department of Preventive Medicine, Northwestern University, Feinberg School of Medicine, 680 North Lake Shore Drive, Suite, 1400, Chicago, IL, USA
| | - Oscar H Franco
- Department of Medicine, Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, 1000 W Carson St, Torrance, CA, USA
- Institute of Social and Preventive Medicine (ISPM), University of Bern, Mittelstrasse 43, Bern, Switzerland
| | - David Herrington
- Section on Cardiovascular Medicine, Department of Internal Medicine, Wake Forest University School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA
| | - John C Lindon
- Metabometrix Ltd, Imperial Incubator, Bessemer Building, Prince Consort Road, London, UK
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, South Kensington Campus, London, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, Norfolk Place, London, UK
- MRC-PHE Centre for Environment and Health, School of Public Health, Imperial College London, Norfolk Place, London, UK
- Dementia Research Institute, Imperial College London, Norfolk Place, London, UK
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9
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Seow WJ, Shu XO, Nicholson JK, Holmes E, Walker DI, Hu W, Cai Q, Gao YT, Xiang YB, Moore SC, Bassig BA, Wong JYY, Zhang J, Ji BT, Boulangé CL, Kaluarachchi M, Wijeyesekera A, Zheng W, Elliott P, Rothman N, Lan Q. Association of Untargeted Urinary Metabolomics and Lung Cancer Risk Among Never-Smoking Women in China. JAMA Netw Open 2019; 2:e1911970. [PMID: 31539079 PMCID: PMC6755532 DOI: 10.1001/jamanetworkopen.2019.11970] [Citation(s) in RCA: 24] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
IMPORTANCE Chinese women have the highest rate of lung cancer among female never-smokers in the world, and the etiology is poorly understood. OBJECTIVE To assess the association between metabolomics and lung cancer risk among never-smoking women. DESIGN, SETTING, AND PARTICIPANTS This nested case-control study included 275 never-smoking female patients with lung cancer and 289 never-smoking cancer-free control participants from the prospective Shanghai Women's Health Study recruited from December 28, 1996, to May 23, 2000. Validated food frequency questionnaires were used for the collection of dietary information. Metabolomic analysis was conducted from November 13, 2015, to January 6, 2016. Data analysis was conducted from January 6, 2016, to November 29, 2018. EXPOSURES Untargeted ultra-high-performance liquid chromatography-tandem mass spectrometry and nuclear magnetic resonance metabolomic profiles were characterized using prediagnosis urine samples. A total of 39 416 metabolites were measured. MAIN OUTCOMES AND MEASURES Incident lung cancer. RESULTS Among the 564 women, those who developed lung cancer (275 participants; median [interquartile range] age, 61.0 [52-65] years) and those who did not develop lung cancer (289 participants; median [interquartile range] age, 62.0 [53-66] years) at follow-up (median [interquartile range] follow-up, 10.9 [9.0-11.7] years) were similar in terms of their secondhand smoke exposure, history of respiratory diseases, and body mass index. A peak metabolite, identified as 5-methyl-2-furoic acid, was significantly associated with lower lung cancer risk (odds ratio, 0.57 [95% CI, 0.46-0.72]; P < .001; false discovery rate = 0.039). Furthermore, this peak was weakly correlated with self-reported dietary soy intake (ρ = 0.21; P < .001). Increasing tertiles of this metabolite were associated with lower lung cancer risk (in comparison with first tertile, odds ratio for second tertile, 0.52 [95% CI, 0.34-0.80]; and odds ratio for third tertile, 0.46 [95% CI, 0.30-0.70]), and the association was consistent across different histological subtypes and follow-up times. Additionally, metabolic pathway analysis found several systemic biological alterations that were associated with lung cancer risk, including 1-carbon metabolism, nucleotide metabolism, oxidative stress, and inflammation. CONCLUSIONS AND RELEVANCE This prospective study of the untargeted urinary metabolome and lung cancer among never-smoking women in China provides support for the hypothesis that soy-based metabolites are associated with lower lung cancer risk in never-smoking women and suggests that biological processes linked to air pollution may be associated with higher lung cancer risk in this population.
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Affiliation(s)
- Wei Jie Seow
- Saw Swee Hock School of Public Health, National University of Singapore and National University Health System, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore and National University Health System, Singapore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Jeremy K. Nicholson
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
- Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Elaine Holmes
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
- Health Futures Institute, Murdoch University, Murdoch, Western Australia, Australia
| | - Douglas I. Walker
- Department of Environmental Medicine and Public Health, Icahn School of Medicine at Mount Sinai, New York, New York
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
| | - Yong-Bing Xiang
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai, China
- State Key Laboratory of Oncogene and Related Genes, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Steven C. Moore
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Bryan A. Bassig
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Jason Y. Y. Wong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Jinming Zhang
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Claire L. Boulangé
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Manuja Kaluarachchi
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Anisha Wijeyesekera
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Paul Elliott
- Biomolecular Medicine, Division of Computational and Systems Medicine, Medical Research Council–National Institute for Health Research National Phenome Centre, Imperial College London, United Kingdom
- Medical Research Council–PHE Centre for Environment and Health, Department of Surgery and Cancer, Imperial College London, United Kingdom
- MRC-PHE Centre for Environment and Health, School of Public Health, Department of Epidemiology and Biostatistics, Imperial College London, United Kingdom
- National Institute for Health Research, Imperial College Biomedical Research Centre, London, United Kingdom
- Health Data Research UK London at Imperial College London, United Kingdom
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, Maryland
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10
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Jaggard MKJ, Boulangé CL, Akhbari P, Vaghela U, Bhattacharya R, Williams HRT, Lindon JC, Gupte CM. A systematic review of the small molecule studies of osteoarthritis using nuclear magnetic resonance and mass spectroscopy. Osteoarthritis Cartilage 2019; 27:560-570. [PMID: 30287397 DOI: 10.1016/j.joca.2018.08.024] [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] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/04/2018] [Revised: 07/23/2018] [Accepted: 08/28/2018] [Indexed: 02/02/2023]
Abstract
OBJECTIVE To perform a systematic review of the small molecule metabolism studies of osteoarthritis utilising nuclear magnetic resonance (NMR) or mass spectroscopy (MS) analysis (viz., metabolomics or metabonomics), thereby providing coherent conclusions and reference material for future study. METHOD We applied PRISMA guidelines (PROSPERO 95068) with the following MESH terms: 1. "osteoarthritis" AND ("metabolic" OR "metabonomic" OR "metabolomic" OR "metabolism") 2. ("synovial fluid" OR "cartilage" OR "synovium" OR "serum" OR "plasma" OR "urine") AND ("NMR" or "Mass Spectroscopy"). Databases searched were "Medline" and "Embase". Studies were searched in English and excluded review articles not containing original research. Study outcomes were significant or notable metabolites, species (human or animal) and the Newcastle-Ottawa Score. RESULTS In the 27 studies meeting the inclusion criteria, there was a shift towards anaerobic and fatty acid metabolism in OA disease, although whether this represents the inflammatory state remains unclear. Lipid structure and composition was altered within disease subclasses including phosphatidyl choline (PC) and the sphingomyelins. Macromolecular proteoglycan destruction was described, but the correlation to disease factors was not demonstrated. Collated results suggested arachidonate signalling pathways and androgen sex hormones as future metabolic pathways for investigation. CONCLUSION Our meta-analysis demonstrates significant small molecule differences between sample types, between species (such as human and bovine), with potential OA biomarkers and targets for local or systemic therapies. Studies were limited by numbers and a lack of disease correlation. Future studies should use NMR and MS analysis to further investigate large population subgroups including inflammatory arthropathy, OA subclasses, age and joint differences.
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Affiliation(s)
- M K J Jaggard
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, United Kingdom.
| | - C L Boulangé
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - P Akhbari
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, United Kingdom
| | - U Vaghela
- School of Medicine, Imperial College London, United Kingdom
| | - R Bhattacharya
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, United Kingdom
| | - H R T Williams
- Division of Digestive Diseases, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - J C Lindon
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, United Kingdom
| | - C M Gupte
- Department of Orthopaedics & Trauma, Imperial College Healthcare NHS Trust, United Kingdom
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11
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Boulangé CL, Rood IM, Posma JM, Lindon JC, Holmes E, Wetzels JFM, Deegens JKJ, Kaluarachchi MR. NMR and MS urinary metabolic phenotyping in kidney diseases is fit-for-purpose in the presence of a protease inhibitor. Mol Omics 2019; 15:39-49. [DOI: 10.1039/c8mo00190a] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
When using an appropriate data analysis pipeline, protease inhibitor (PI)-containing urine samples are fit-for-purpose for metabolic phenotyping of patients with nephrotic syndrome and proteinuria.
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Affiliation(s)
| | - Ilse M. Rood
- Department of Nephrology
- Radboud University Medical Center
- Nijmegen
- The Netherlands
| | - Joram M. Posma
- Imperial College London
- Division of Computational and Systems Medicine
- Department of Surgery and Cancer
- Faculty of Medicine
- London SW7 2AZ
| | - John C. Lindon
- Metabometrix Ltd
- London SW7 2AZ
- UK
- Imperial College London
- Division of Computational and Systems Medicine
| | - Elaine Holmes
- Metabometrix Ltd
- London SW7 2AZ
- UK
- Imperial College London
- Division of Computational and Systems Medicine
| | - Jack F. M. Wetzels
- Department of Nephrology
- Radboud University Medical Center
- Nijmegen
- The Netherlands
| | - Jeroen K. J. Deegens
- Department of Nephrology
- Radboud University Medical Center
- Nijmegen
- The Netherlands
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12
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Dumas ME, Rothwell AR, Hoyles L, Aranias T, Chilloux J, Calderari S, Noll EM, Péan N, Boulangé CL, Blancher C, Barton RH, Gu Q, Fearnside JF, Deshayes C, Hue C, Scott J, Nicholson JK, Gauguier D. Microbial-Host Co-metabolites Are Prodromal Markers Predicting Phenotypic Heterogeneity in Behavior, Obesity, and Impaired Glucose Tolerance. Cell Rep 2018; 20:136-148. [PMID: 28683308 PMCID: PMC5507771 DOI: 10.1016/j.celrep.2017.06.039] [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] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2015] [Revised: 07/21/2016] [Accepted: 06/12/2017] [Indexed: 02/07/2023] Open
Abstract
The influence of the gut microbiome on metabolic and behavioral traits is widely accepted, though the microbiome-derived metabolites involved remain unclear. We carried out untargeted urine 1H-NMR spectroscopy-based metabolic phenotyping in an isogenic C57BL/6J mouse population (n = 50) and show that microbial-host co-metabolites are prodromal (i.e., early) markers predicting future divergence in metabolic (obesity and glucose homeostasis) and behavioral (anxiety and activity) outcomes with 94%–100% accuracy. Some of these metabolites also modulate disease phenotypes, best illustrated by trimethylamine-N-oxide (TMAO), a product of microbial-host co-metabolism predicting future obesity, impaired glucose tolerance (IGT), and behavior while reducing endoplasmic reticulum stress and lipogenesis in 3T3-L1 adipocytes. Chronic in vivo TMAO treatment limits IGT in HFD-fed mice and isolated pancreatic islets by increasing insulin secretion. We highlight the prodromal potential of microbial metabolites to predict disease outcomes and their potential in shaping mammalian phenotypic heterogeneity. High-fat diet drives phenotypic heterogeneity in metabolism and behavior Microbial metabolites, including methylamines, predict phenotypic heterogeneity TMAO attenuates ER stress and reduces lipogenesis in adipocytes TMAO improves insulin secretion and restores glucose tolerance in vivo
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Affiliation(s)
- Marc-Emmanuel Dumas
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK.
| | - Alice R Rothwell
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Lesley Hoyles
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Thomas Aranias
- Cordeliers Research Centre, INSERM UMR_S 1138, University Pierre & Marie Curie and University Paris Descartes, Sorbonne Paris Cité, Sorbonne Universities, 15 Rue de l'École de Médecine, 75006 Paris, France
| | - Julien Chilloux
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Sophie Calderari
- Cordeliers Research Centre, INSERM UMR_S 1138, University Pierre & Marie Curie and University Paris Descartes, Sorbonne Paris Cité, Sorbonne Universities, 15 Rue de l'École de Médecine, 75006 Paris, France
| | - Elisa M Noll
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Noémie Péan
- Cordeliers Research Centre, INSERM UMR_S 1138, University Pierre & Marie Curie and University Paris Descartes, Sorbonne Paris Cité, Sorbonne Universities, 15 Rue de l'École de Médecine, 75006 Paris, France
| | - Claire L Boulangé
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Christine Blancher
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Richard H Barton
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Quan Gu
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Jane F Fearnside
- Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK
| | - Chloé Deshayes
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Christophe Hue
- Cordeliers Research Centre, INSERM UMR_S 1138, University Pierre & Marie Curie and University Paris Descartes, Sorbonne Paris Cité, Sorbonne Universities, 15 Rue de l'École de Médecine, 75006 Paris, France
| | - James Scott
- Department of Medicine, Imperial College London, Du Cane Road, London W12 0NN, UK
| | - Jeremy K Nicholson
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK
| | - Dominique Gauguier
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London SW7 2AZ, UK; Wellcome Trust Centre for Human Genetics, University of Oxford, Roosevelt Drive, Oxford OX3 7BN, UK; Cordeliers Research Centre, INSERM UMR_S 1138, University Pierre & Marie Curie and University Paris Descartes, Sorbonne Paris Cité, Sorbonne Universities, 15 Rue de l'École de Médecine, 75006 Paris, France.
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13
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Kaluarachchi M, Boulangé CL, Karaman I, Lindon JC, Ebbels TMD, Elliott P, Tracy RP, Olson NC. A comparison of human serum and plasma metabolites using untargeted 1H NMR spectroscopy and UPLC-MS. Metabolomics 2018; 14:32. [PMID: 30830335 PMCID: PMC7122646 DOI: 10.1007/s11306-018-1332-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [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: 10/26/2017] [Accepted: 01/30/2018] [Indexed: 12/21/2022]
Abstract
INTRODUCTION Differences in the metabolite profiles between serum and plasma are incompletely understood. OBJECTIVES To evaluate metabolic profile differences between serum and plasma and among plasma sample subtypes. METHODS We analyzed serum, platelet rich plasma (PRP), platelet poor plasma (PPP), and platelet free plasma (PFP), collected from 8 non-fasting apparently healthy women, using untargeted standard 1D and CPMG 1H NMR and reverse phase and hydrophilic (HILIC) UPLC-MS. Differences between metabolic profiles were evaluated using validated principal component and orthogonal partial least squares discriminant analysis. RESULTS Explorative analysis showed the main source of variation among samples was due to inter-individual differences with no grouping by sample type. After correcting for inter-individual differences, lipoproteins, lipids in VLDL/LDL, lactate, glutamine, and glucose were found to discriminate serum from plasma in NMR analyses. In UPLC-MS analyses, lysophosphatidylethanolamine (lysoPE)(18:0) and lysophosphatidic acid(20:0) were higher in serum, and phosphatidylcholines (PC)(16:1/18:2, 20:3/18:0, O-20:0/22:4), lysoPC(16:0), PE(O-18:2/20:4), sphingomyelin(18:0/22:0), and linoleic acid were lower. In plasma subtype analyses, isoleucine, leucine, valine, phenylalanine, glutamate, and pyruvate were higher among PRP samples compared with PPP and PFP by NMR while lipids in VLDL/LDL, citrate, and glutamine were lower. By UPLC-MS, PE(18:0/18:2) and PC(P-16:0/20:4) were higher in PRP compared with PFP samples. CONCLUSIONS Correction for inter-individual variation was required to detect metabolite differences between serum and plasma. Our results suggest the potential importance of inter-individual effects and sample type on the results from serum and plasma metabolic phenotyping studies.
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Affiliation(s)
- Manuja Kaluarachchi
- Metabometrix Ltd, Sir Alexander Fleming Building, Prince Consort Road, London, SW7 1BP, UK
| | - Claire L Boulangé
- Metabometrix Ltd, Sir Alexander Fleming Building, Prince Consort Road, London, SW7 1BP, UK
| | - Ibrahim Karaman
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
| | - John C Lindon
- Metabometrix Ltd, Sir Alexander Fleming Building, Prince Consort Road, London, SW7 1BP, UK
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Timothy M D Ebbels
- Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, London, SW7 2AZ, UK
| | - Paul Elliott
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, W2 1PG, UK
- MRC-PHE Centre for Environment and Health, Imperial College London, London, W2 1PG, UK
| | - Russell P Tracy
- Department of Biochemistry, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, 05446, USA
- Department of Pathology and Laboratory Medicine, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, 05446, USA
| | - Nels C Olson
- Department of Pathology and Laboratory Medicine, The Robert Larner, M.D. College of Medicine at The University of Vermont, Burlington, VT, 05446, USA.
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14
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Karaman I, Ferreira DLS, Boulangé CL, Kaluarachchi MR, Herrington D, Dona AC, Castagné R, Moayyeri A, Lehne B, Loh M, de Vries PS, Dehghan A, Franco OH, Hofman A, Evangelou E, Tzoulaki I, Elliott P, Lindon JC, Ebbels TMD. Workflow for Integrated Processing of Multicohort Untargeted 1H NMR Metabolomics Data in Large-Scale Metabolic Epidemiology. J Proteome Res 2016; 15:4188-4194. [DOI: 10.1021/acs.jproteome.6b00125] [Citation(s) in RCA: 26] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ibrahim Karaman
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Diana L. S. Ferreira
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Claire L. Boulangé
- Metabometrix, Ltd., Bioincubator Unit, Bessemer Building, Prince Consort Road, SW7 2BP South Kensington, London, United Kingdom
| | - Manuja R. Kaluarachchi
- Metabometrix, Ltd., Bioincubator Unit, Bessemer Building, Prince Consort Road, SW7 2BP South Kensington, London, United Kingdom
| | - David Herrington
- Department
of Internal Medicine, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, North Carolina 27157, United States
| | - Anthony C. Dona
- Metabometrix, Ltd., Bioincubator Unit, Bessemer Building, Prince Consort Road, SW7 2BP South Kensington, London, United Kingdom
- 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
| | - Raphaële Castagné
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Alireza Moayyeri
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Benjamin Lehne
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Marie Loh
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - Paul S. de Vries
- Department
of Epidemiology, Erasmus University, Erasmus Medical Center, Dr Molewaterplein
50, 3015 GE Rotterdam, Netherlands
| | - Abbas Dehghan
- Department
of Epidemiology, Erasmus University, Erasmus Medical Center, Dr Molewaterplein
50, 3015 GE Rotterdam, Netherlands
| | - Oscar H. Franco
- Department
of Epidemiology, Erasmus University, Erasmus Medical Center, Dr Molewaterplein
50, 3015 GE Rotterdam, Netherlands
| | - Albert Hofman
- Department
of Epidemiology, Erasmus University, Erasmus Medical Center, Dr Molewaterplein
50, 3015 GE Rotterdam, Netherlands
| | - Evangelos Evangelou
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
- Department
of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, P.O. Box 1186, 45110 Ioannina, Greece
| | - Ioanna Tzoulaki
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
- Department
of Hygiene and Epidemiology, University of Ioannina School of Medicine, University Campus, P.O. Box 1186, 45110 Ioannina, Greece
| | - Paul Elliott
- Medical
Research Council − Public Health England (MRC−PHE) Centre
for Environment and Health, Department of Epidemiology and Biostatistics,
School of Public Health, Imperial College London, St. Mary’s
Campus, Norfolk Place, W2 1PG, London, United Kingdom
| | - John C. Lindon
- Metabometrix, Ltd., Bioincubator Unit, Bessemer Building, Prince Consort Road, SW7 2BP South Kensington, London, United Kingdom
- 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
| | - Timothy M. D. Ebbels
- Metabometrix, Ltd., Bioincubator Unit, Bessemer Building, Prince Consort Road, SW7 2BP South Kensington, London, United Kingdom
- 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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15
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Montoliu I, Cominetti O, Boulangé CL, Berger B, Siddharth J, Nicholson J, Martin FPJ. Modeling Longitudinal Metabonomics and Microbiota Interactions in C57BL/6 Mice Fed a High Fat Diet. Anal Chem 2016; 88:7617-26. [PMID: 27396289 DOI: 10.1021/acs.analchem.6b01343] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/21/2022]
Abstract
Longitudinal studies aim typically at following populations of subjects over time and are important to understand the global evolution of biological processes. When it comes to longitudinal omics data, it will often depend on the overall objective of the study, and constraints imposed by the data, to define the appropriate modeling tools. Here, we report the use of multilevel simultaneous component analysis (MSCA), orthogonal projection on latent structures (OPLS), and regularized canonical correlation analysis (rCCA) to study associations between specific longitudinal urine metabonomics data and microbiome data in a diet-induced obesity model using C57BL/6 mice. (1)H NMR urine metabolic profiling was performed on samples collected weekly over a period of 13 weeks, and stool microbial composition was assessed using 16S rRNA gene sequencing at three specific time periods (baseline, first week response, end of study). MSCA and OPLS allowed us to explore longitudinal urine metabonomics data in relation to the dietary groups, as well as dietary effects on body weight. In addition, we report a data integration strategy based on regularized CCA and correlation analyses of urine metabonomics data and 16S rRNA gene sequencing data to investigate the functional relationships between metabolites and gut microbial composition. Thanks to this workflow enabling the breakdown of this data set complexity, the most relevant patterns could be extracted to further explore physiological processes at an anthropometric, cellular, and molecular level.
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Affiliation(s)
- Ivan Montoliu
- Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Building H, 1015 Lausanne, Switzerland.,Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Ornella Cominetti
- Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Building H, 1015 Lausanne, Switzerland
| | - Claire L Boulangé
- Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - Bernard Berger
- Nestlé Research Center , Vers-chez-les-Blanc, 1000 Lausanne 26, Switzerland
| | - Jay Siddharth
- Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Building H, 1015 Lausanne, Switzerland
| | - Jeremy Nicholson
- Department of Biomolecular Medicine, Division of Surgery, Oncology, Reproductive Biology and Anaesthetics, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, South Kensington Campus, London SW7 2AZ, United Kingdom
| | - François-Pierre J Martin
- Nestlé Institute of Health Sciences SA , EPFL Innovation Park, Building H, 1015 Lausanne, Switzerland
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16
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Abstract
PURPOSE OF REVIEW The microbial-mammalian symbiosis plays a critical role in metabolic health. Microbial metabolites emerge as key messengers in the complex communication between the gut microbiota and their host. These chemical signals are mainly derived from nutritional precursors, which in turn are also able to modify gut microbiota population. Recent advances in the characterization of the gut microbiome and the mechanisms involved in this symbiosis allow the development of nutritional interventions. This review covers the latest findings on the microbial-mammalian metabolic axis as a critical symbiotic relationship particularly relevant to clinical nutrition. RECENT FINDINGS The modulation of host metabolism by metabolites derived from the gut microbiota highlights the importance of gut microbiota in disease prevention and causation. The composition of microbial populations in our gut ecosystem is a critical pathophysiological factor, mainly regulated by diet, but also by the host's characteristics (e.g. genetics, circadian clock, immune system, age). Tailored interventions, including dietary changes, the use of antibiotics, prebiotic and probiotic supplementation and faecal transplantation are promising strategies to manipulate microbial ecology. SUMMARY The microbiome is now considered as an easily reachable target to prevent and treat related diseases. Recent findings in both mechanisms of its interactions with host metabolism and in strategies to modify gut microbiota will allow us to develop more effective treatments especially in metabolic diseases.
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Affiliation(s)
- Julien Chilloux
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Ana Luisa Neves
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Claire L Boulangé
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
| | - Marc-Emmanuel Dumas
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, United Kingdom
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17
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Abstract
The human gut harbors more than 100 trillion microbial cells, which have an essential role in human metabolic regulation via their symbiotic interactions with the host. Altered gut microbial ecosystems have been associated with increased metabolic and immune disorders in animals and humans. Molecular interactions linking the gut microbiota with host energy metabolism, lipid accumulation, and immunity have also been identified. However, the exact mechanisms that link specific variations in the composition of the gut microbiota with the development of obesity and metabolic diseases in humans remain obscure owing to the complex etiology of these pathologies. In this review, we discuss current knowledge about the mechanistic interactions between the gut microbiota, host energy metabolism, and the host immune system in the context of obesity and metabolic disease, with a focus on the importance of the axis that links gut microbes and host metabolic inflammation. Finally, we discuss therapeutic approaches aimed at reshaping the gut microbial ecosystem to regulate obesity and related pathologies, as well as the challenges that remain in this area.
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Affiliation(s)
- Claire L Boulangé
- Metabometrix Ltd, Bio-incubator, Prince Consort Road, South Kensington, London, SW7 2BP, UK
| | - Ana Luisa Neves
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2PH, UK
| | - Julien Chilloux
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2PH, UK
| | - Jeremy K Nicholson
- Metabometrix Ltd, Bio-incubator, Prince Consort Road, South Kensington, London, SW7 2BP, UK. .,Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2PH, UK.
| | - Marc-Emmanuel Dumas
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Faculty of Medicine, Imperial College London, Sir Alexander Fleming Building, Exhibition Road, South Kensington, London, SW7 2PH, UK.
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18
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Neves AL, Chilloux J, Sarafian MH, Rahim MBA, Boulangé CL, Dumas ME. The microbiome and its pharmacological targets: therapeutic avenues in cardiometabolic diseases. Curr Opin Pharmacol 2015; 25:36-44. [PMID: 26531326 DOI: 10.1016/j.coph.2015.09.013] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [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: 07/28/2015] [Revised: 09/15/2015] [Accepted: 09/29/2015] [Indexed: 02/06/2023]
Abstract
Consisting of trillions of non-pathogenic bacteria living in a symbiotic relationship with their mammalian host, the gut microbiota has emerged in the past decades as one of the key drivers for cardiometabolic diseases (CMD). By degrading dietary substrates, the gut microbiota produces several metabolites that bind human pharmacological targets, impact subsequent signalling networks and in fine modulate host's metabolism. In this review, we revisit the pharmacological relevance of four classes of gut microbial metabolites in CMD: short-chain fatty acids (SCFA), bile acids, methylamines and indoles. Unravelling the signalling mechanisms of the microbial-mammalian metabolic axis adds one more layer of complexity to the physiopathology of CMD and opens new avenues for the development of microbiota-based pharmacological therapies.
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Affiliation(s)
- Ana Luisa Neves
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, UK
| | - Julien Chilloux
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, UK
| | - Magali H Sarafian
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, UK
| | - Mohd Badrin Abdul Rahim
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, UK
| | - Claire L Boulangé
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, UK
| | - Marc-Emmanuel Dumas
- Division of Computational and Systems Medicine, Department of Surgery and Cancer, Imperial College London, Exhibition Road, London SW7 2AZ, UK.
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19
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Boulangé CL, Claus SP, Chou CJ, Collino S, Montoliu I, Kochhar S, Holmes E, Rezzi S, Nicholson JK, Dumas ME, Martin FPJ. Early metabolic adaptation in C57BL/6 mice resistant to high fat diet induced weight gain involves an activation of mitochondrial oxidative pathways. J Proteome Res 2013; 12:1956-68. [PMID: 23473242 DOI: 10.1021/pr400051s] [Citation(s) in RCA: 51] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/20/2022]
Abstract
We investigated the short-term (7 days) and long-term (60 days) metabolic effect of high fat diet induced obesity (DIO) and weight gain in isogenic C57BL/6 mice and examined the specific metabolic differentiation between mice that were either strong-responders (SR), or non-responders (NR) to weight gain. Mice (n = 80) were fed a standard chow diet for 7 days prior to randomization into a high-fat (HF) (n = 56) or a low-fat (LF) (n = 24) diet group. The (1)H NMR urinary metabolic profiles of LF and HF mice were recorded 7 and 60 days after the diet switch. On the basis of the body weight gain (BWG) distribution of HF group, we identified NR mice (n = 10) and SR mice (n = 14) to DIO. Compared with LF, HF feeding increased urinary excretion of glycine conjugates of β-oxidation intermediate (hexanoylglycine), branched chain amino acid (BCAA) catabolism intermediates (isovalerylglycine, α-keto-β-methylvalerate and α-ketoisovalerate) and end-products of nicotinamide adenine dinucleotide (NAD) metabolism (N1-methyl-2-pyridone-5-carboxamide, N1-methyl-4-pyridone-3-carboxamide) suggesting up-regulation of mitochondrial oxidative pathways. In the HF group, NR mice excreted relatively more hexanoylglycine, isovalerylglycine, and fewer tricarboxylic acid (TCA) cycle intermediate (succinate) in comparison to SR mice. Thus, subtle regulation of ketogenic pathways in DIO may alleviate the saturation of the TCA cycle and mitochondrial oxidative metabolism.
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Affiliation(s)
- Claire L Boulangé
- Section of Biomolecular medicine, Division of Surgery and Cancer, Faculty of Medicine, Imperial College London , Sir Alexander Fleming Building, London SW7 2AZ, United Kingdom
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