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Ferreira H, Duarte D, Carneiro TJ, Costa C, Barbosa JC, Rodrigues JE, Alves P, Vasconcelos M, Pinto E, Gomes A, Gil AM. Impact of a legumes diet on the human gut microbiome articulated with fecal and plasma metabolomes: A pilot study. Clin Nutr ESPEN 2024; 63:332-345. [PMID: 38964655 DOI: 10.1016/j.clnesp.2024.06.051] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2024] [Revised: 06/12/2024] [Accepted: 06/27/2024] [Indexed: 07/06/2024]
Abstract
BACKGROUND & AIMS Legumes intake is known to be associated with several health benefits the origins of which is still a matter of debate. This paper addresses a pilot small cohort to probe for metabolic aspects of the interplay between legumes intake, human metabolism and gut microbiota. METHODS Untargeted nuclear magnetic resonance (NMR) metabolomics of blood plasma and fecal extracts was carried out, in tandem with qPCR analysis of feces, to assess the impact of an 8-week pilot legumes diet intervention on the fecal and plasma metabolomes and gut microbiota of 19 subjects. RESULTS While the high inter-individual variability hindered the detection of statistically significant changes in the gut microbiome, increased fecal glucose and decreased threonine levels were noted. Correlation analysis between the microbiome and fecal metabolome lead to putative hypotheses regarding the metabolic activities of prevalent bacteria groups (Clostridium leptum subgroup, Roseburia spp., and Faecalibacterium prausnitzii). These included elevated fecal glucose as a preferential energy source, the involvement of valerate/isovalerate and reduced protein degradation in gut microbiota. Plasma metabolomics advanced mannose and betaine as potential markers of legume intake and unveiled a decrease in formate and ketone bodies, the latter suggesting improved energy utilization through legume carbohydrates. Amino acid metabolism was also apparently affected, as suggested by lowered urea, histidine and threonine levels. CONCLUSIONS Despite the high inter-individual gut microbiome variability characterizing the small cohort addressed, combination of microbiological measurements and untargeted metabolomics unveiled several metabolic effects putatively related to legumes intake. If confirmed in larger cohorts, our findings will support the inclusion of legumes in diets and contribute valuable new insight into the origins of associated health benefits.
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Affiliation(s)
- Helena Ferreira
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal; Department of Chemistry and CICECO-Aveiro Institute of Materials, University of Aveiro, Aveiro, Portugal
| | - Daniela Duarte
- Department of Chemistry and CICECO-Aveiro Institute of Materials, University of Aveiro, Aveiro, Portugal
| | - Tatiana J Carneiro
- Department of Chemistry and CICECO-Aveiro Institute of Materials, University of Aveiro, Aveiro, Portugal
| | - Célia Costa
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal
| | - Joana C Barbosa
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal
| | - João E Rodrigues
- Department of Chemistry and CICECO-Aveiro Institute of Materials, University of Aveiro, Aveiro, Portugal
| | - Paulo Alves
- Universidade Católica Portuguesa, CIIS - Centro de Investigação Interdisciplinar em Saúde, Escola Enfermagem (Porto), Portugal
| | - Marta Vasconcelos
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal
| | - Elisabete Pinto
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal; EPIUnit - Instituto de Saúde Pública, Universidade do Porto, Porto, Portugal
| | - Ana Gomes
- Universidade Católica Portuguesa, CBQF - Centro de Biotecnologia e Química Fina - Laboratório Associado, Escola Superior de Biotecnologia, Porto, Portugal
| | - Ana M Gil
- Department of Chemistry and CICECO-Aveiro Institute of Materials, University of Aveiro, Aveiro, Portugal.
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Dasanayake GS, Hamadani CM, Singh G, Kumar Misra S, Vashisth P, Sharp JS, Adhikari L, Baker GA, Tanner EEL. Imidazolium-based zwitterionic liquid-modified PEG-PLGA nanoparticles as a potential intravenous drug delivery carrier. NANOSCALE 2024; 16:5584-5600. [PMID: 38410026 DOI: 10.1039/d3nr06349f] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Zwitterionic-based systems offer promise as next-generation drug delivery biomaterials capable of enhancing nanoparticle (NP) stimuli-responsiveness, biorecognition, and biocompatibility. Further, imidazole-functionalized amphiphilic zwitterions are able to readily bind to various biological macromolecules, enabling antifouling properties for enhanced drug delivery efficacy and bio-targeting. Herein, we describe structurally tuned zwitterionic imidazole-based ionic liquid (ZIL)-coated PEG-PLGA nanoparticles made with sonicated nanoprecipitation. Upon ZIL surface modification, the hydrodynamic radius increased by nearly 20 nm, and the surface charge significantly shifted closer to neutral. 1H NMR spectra suggests that the amount of ZIL on the nanoparticle surface is controlled by the structure of the ZIL and that the assembly occurs as a result of non-covalent interactions of ZIL-coated nanoparticle with the polymer surface. These nanoparticle-zwitterionic liquid (ZIL) constructs demonstrate selective affinity towards red blood cells in whole mouse blood and show relatively low human hemolysis at ∼5%. Additionally, we observe higher nanoparticle accumulation of ZIL-NPs compared with unmodified NP controls in human triple-negative breast cancer cells (MDA-MB-231). Furthermore, although the ZIL shows similar protein adsorption by SDS-PAGE, LC-MS/MS protein analysis data demonstrate a difference in the relative abundance and depletion of proteins in mouse and human serum. Hence, we show that ZIL-coated nanoparticles provide a new potential platform to enhance RBC-based drug delivery systems for cancer treatments.
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Affiliation(s)
- Gaya S Dasanayake
- Department of Chemistry and Biochemistry, University of Mississippi, University, MS 38677, USA.
| | - Christine M Hamadani
- Department of Chemistry and Biochemistry, University of Mississippi, University, MS 38677, USA.
| | - Gagandeep Singh
- Department of Chemistry and Biochemistry, University of Mississippi, University, MS 38677, USA.
| | - Sandeep Kumar Misra
- Department of BioMolecular Sciences, University of Mississippi, University, MS 38677, USA
| | - Priyavrat Vashisth
- Department of Chemistry and Biochemistry, University of Mississippi, University, MS 38677, USA.
| | - Joshua S Sharp
- Department of Chemistry and Biochemistry, University of Mississippi, University, MS 38677, USA.
- Department of BioMolecular Sciences, University of Mississippi, University, MS 38677, USA
| | - Laxmi Adhikari
- Department of Chemistry, University of Missouri, Columbia, MO, 65211, USA
| | - Gary A Baker
- Department of Chemistry, University of Missouri, Columbia, MO, 65211, USA
| | - Eden E L Tanner
- Department of Chemistry and Biochemistry, University of Mississippi, University, MS 38677, USA.
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Tipton M, Baxter BA, Pfluger BA, Sayre-Chavez B, Muñoz-Amatriaín M, Broeckling CD, Shani I, Steiner-Asiedu M, Manary M, Ryan EP. Urine and Dried Blood Spots From Children and Pregnant Women Reveal Phytochemicals, Amino Acids, and Carnitine Metabolites as Cowpea Consumption Biomarkers. Mol Nutr Food Res 2024; 68:e2300222. [PMID: 38233141 DOI: 10.1002/mnfr.202300222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 10/23/2023] [Indexed: 01/19/2024]
Abstract
SCOPE Legumes consumption has been proven to promote health across the lifespan; cowpeas have demonstrated efficacy in combating childhood malnutrition and growth faltering, with an estimated malnutrition prevalence of 35.6% of children in Ghana. This cowpea feeding study aimed to identify a suite of metabolic consumption biomarkers in children and adults. METHODS AND RESULTS Urine and dried blood spots (DBS) from 24 children (9-21 months) and 21 pregnant women (>18 years) in Northern Ghana are collected before and after dose-escalated consumption of four cowpea varieties for 15 days. Untargeted metabolomics identified significant increases in amino acids, phytochemicals, and lipids. The carnitine metabolism pathway is represented by 137 urine and 43 DBS metabolites, with significant changes to tiglylcarnitine and acetylcarnitine. Additional noteworthy candidate biomarkers are mansouramycin C, N-acetylalliin, proline betaine, N2, N5-diacetylornithine, S-methylcysteine, S-methylcysteine sulfoxide, and cis-urocanate. S-methylcysteine and S-methylcysteine sulfoxide are targeted and quantified in urine. CONCLUSION This feeding study for cowpea biomarkers supports the utility of a suite of key metabolites classified as amino acids, lipids, and phytochemicals for dietary legume and cowpea-specific food exposures of global health importance.
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Affiliation(s)
- Madison Tipton
- Department of Environmental and Radiological Health Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, 80523, USA
| | - Bridget A Baxter
- Department of Environmental and Radiological Health Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, 80523, USA
| | - Brigitte A Pfluger
- Nutrition and Health Sciences, Laney Graduate School, Emory University, Atlanta, Georgia, 30322, USA
| | - Brooke Sayre-Chavez
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, 80521, USA
| | - María Muñoz-Amatriaín
- Department of Soil and Crop Sciences, Colorado State University, Fort Collins, Colorado, 80521, USA
- Departamento de Biología Molecular - Área de Genética, Universidad de León, León, 24071, Spain
| | - Corey D Broeckling
- Analytical Resources Core: Bioanalysis and Omics Center, Colorado State University, Fort Collins, Colorado, 80523, USA
| | - Issah Shani
- Department of Nutrition and Food Science, College of Basic and Applied Science, University of Ghana, Legon, Accra, P.O. Box LG 134 Legon, Ghana
| | - Matilda Steiner-Asiedu
- Department of Nutrition and Food Science, College of Basic and Applied Science, University of Ghana, Legon, Accra, P.O. Box LG 134 Legon, Ghana
| | - Mark Manary
- Department of Pediatrics, Washington University School of Medicine in St. Louis, St. Louis, Missouri, 63110, USA
| | - Elizabeth P Ryan
- Department of Environmental and Radiological Health Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, Colorado, 80523, USA
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Margara-Escudero HJ, Paz-Graniel I, García-Gavilán J, Ruiz-Canela M, Sun Q, Clish CB, Toledo E, Corella D, Estruch R, Ros E, Castañer O, Arós F, Fiol M, Guasch-Ferré M, Lapetra J, Razquin C, Dennis C, Deik A, Li J, Gómez-Gracia E, Babio N, Martínez-González MA, Hu FB, Salas-Salvadó J. Plasma metabolite profile of legume consumption and future risk of type 2 diabetes and cardiovascular disease. Cardiovasc Diabetol 2024; 23:38. [PMID: 38245716 PMCID: PMC10800064 DOI: 10.1186/s12933-023-02111-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 12/29/2023] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Legume consumption has been linked to a reduced risk of type 2 diabetes (T2D) and cardiovascular disease (CVD), while the potential association between plasma metabolites associated with legume consumption and the risk of cardiometabolic diseases has never been explored. Therefore, we aimed to identify a metabolite signature of legume consumption, and subsequently investigate its potential association with the incidence of T2D and CVD. METHODS The current cross-sectional and longitudinal analysis was conducted in 1833 PREDIMED study participants (mean age 67 years, 57.6% women) with available baseline metabolomic data. A subset of these participants with 1-year follow-up metabolomics data (n = 1522) was used for internal validation. Plasma metabolites were assessed through liquid chromatography-tandem mass spectrometry. Cross-sectional associations between 382 different known metabolites and legume consumption were performed using elastic net regression. Associations between the identified metabolite profile and incident T2D and CVD were estimated using multivariable Cox regression models. RESULTS Specific metabolic signatures of legume consumption were identified, these included amino acids, cortisol, and various classes of lipid metabolites including diacylglycerols, triacylglycerols, plasmalogens, sphingomyelins and other metabolites. Among these identified metabolites, 22 were negatively and 18 were positively associated with legume consumption. After adjustment for recognized risk factors and legume consumption, the identified legume metabolite profile was inversely associated with T2D incidence (hazard ratio (HR) per 1 SD: 0.75, 95% CI 0.61-0.94; p = 0.017), but not with CVD incidence risk (1.01, 95% CI 0.86-1.19; p = 0.817) over the follow-up period. CONCLUSIONS This study identified a set of 40 metabolites associated with legume consumption and with a reduced risk of T2D development in a Mediterranean population at high risk of cardiovascular disease. TRIAL REGISTRATION ISRCTN35739639.
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Affiliation(s)
- Hernando J Margara-Escudero
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
| | - Jesús García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Miguel Ruiz-Canela
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
| | - Qi Sun
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clary B Clish
- The Broad Institute of Harvard and MIT, Boston, MA, 02142, USA
| | - Estefania Toledo
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
- Navarra Institute for Health Research, IdiSNA, Pamplona, Navarre, Spain
| | - Dolores Corella
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clinic, University of Barcelona, Barcelona, Spain
| | - Emilio Ros
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Lipid Clinic, Hospital Clínic, Barcelona, Spain
| | - Olga Castañer
- Centro de Investigación Biomédica en Red (CIBERESP) de Epidemiología y Salud Pública, Instituto de Salud Carlos III, Madrid, Spain
- Cardiovascular Risk and Nutrition Research Group, Hospital del Mar Research Institute, Barcelona, Spain
| | - Fernando Arós
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Cardiology, University Hospital of Alava, Vitoria, Spain
| | - Miquel Fiol
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Illes Balears Health Research Institute (IdISBa), Hospital Son Espases, Palma, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Public Health, Section of Epidemiology, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, University of Copenhagen, Copenhagen, Denmark
| | - José Lapetra
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Family Medicine, Research Unit, Distrito Sanitario Atención Primaria Sevilla, Seville, Spain
| | - Cristina Razquin
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
| | - Courtney Dennis
- The Broad Institute of Harvard and MIT, Boston, MA, 02142, USA
| | - Amy Deik
- The Broad Institute of Harvard and MIT, Boston, MA, 02142, USA
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Enrique Gómez-Gracia
- Preventive Medicine and Public Health Department, School of Medicine, University of Málaga, 29010, Malaga, Spain
- Biomedical Research Institute of Malaga-IBIMA Plataforma BIONAND, 29010, Malaga, Spain
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain.
| | - Miguel A Martínez-González
- Department of Preventive Medicine and Public Health, University of Navarra, Instituto de Investigación Sanitario de Navarra (IdiSNA), Pamplona, Spain
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentació, Nutrició, Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- Alimentació, Nutrició, Desenvolupament i Salut Mental, Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
- Centro de Investigación Biomédica en Red Fisiopatología de La Obesidad y La Nutrición (CIBEROBN), Instituto de Salud Carlos III, Madrid, Spain
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Rowley CE, Lodge S, Egan S, Itsiopoulos C, Christophersen CT, Silva D, Kicic-Starcevich E, O’Sullivan TA, Wist J, Nicholson J, Frost G, Holmes E, D’Vaz N. Altered dietary behaviour during pregnancy impacts systemic metabolic phenotypes. Front Nutr 2023; 10:1230480. [PMID: 38111603 PMCID: PMC10725961 DOI: 10.3389/fnut.2023.1230480] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 10/25/2023] [Indexed: 12/20/2023] Open
Abstract
Rationale Evidence suggests consumption of a Mediterranean diet (MD) can positively impact both maternal and offspring health, potentially mediated by a beneficial effect on inflammatory pathways. We aimed to apply metabolic profiling of serum and urine samples to assess differences between women who were stratified into high and low alignment to a MD throughout pregnancy and investigate the relationship of the diet to inflammatory markers. Methods From the ORIGINS cohort, 51 pregnant women were stratified for persistent high and low alignment to a MD, based on validated MD questionnaires. 1H Nuclear Magnetic Resonance (NMR) spectroscopy was used to investigate the urine and serum metabolite profiles of these women at 36 weeks of pregnancy. The relationship between diet, metabolite profile and inflammatory status was investigated. Results There were clear differences in both the food choice and metabolic profiles of women who self-reported concordance to a high (HMDA) and low (LMDA) Mediterranean diet, indicating that alignment with the MD was associated with a specific metabolic phenotype during pregnancy. Reduced meat intake and higher vegetable intake in the HMDA group was supported by increased levels of urinary hippurate (p = 0.044) and lower creatine (p = 0.047) levels. Serum concentrations of the NMR spectroscopic inflammatory biomarkers GlycA (p = 0.020) and GlycB (p = 0.016) were significantly lower in the HDMA group and were negatively associated with serum acetate, histidine and isoleucine (p < 0.05) suggesting a greater level of plant-based nutrients in the diet. Serum branched chain and aromatic amino acids were positively associated with the HMDA group while both urinary and serum creatine, urine creatinine and dimethylamine were positively associated with the LMDA group. Conclusion Metabolic phenotypes of pregnant women who had a high alignment with the MD were significantly different from pregnant women who had a poor alignment with the MD. The metabolite profiles aligned with reported food intake. Differences were most significant biomarkers of systemic inflammation and selected gut-microbial metabolites. This research expands our understanding of the mechanisms driving health outcomes during the perinatal period and provides additional biomarkers for investigation in pregnant women to assess potential health risks.
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Affiliation(s)
- Charlotte E. Rowley
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
| | - Samantha Lodge
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
| | - Siobhon Egan
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
| | | | - Claus T. Christophersen
- WA Human Microbiome Collaboration Centre, Curtin University, Bentley, WA, Australia
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Desiree Silva
- Telethon Kids Institute, Perth Children’s Hospital, Nedlands, WA, Australia
- Joondalup Health Campus, Joondalup, WA, Australia
| | | | - Therese A. O’Sullivan
- School of Medical and Health Sciences, Edith Cowan University, Joondalup, WA, Australia
| | - Julien Wist
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Chemistry Department, Universidad del Valle, Cali, Colombia
| | - Jeremy Nicholson
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Faculty of Medicine, Imperial College London, Institute of Global Health Innovation, London, United Kingdom
- Section of Nutrition Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Gary Frost
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Section of Nutrition Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Elaine Holmes
- Australian National Phenome Centre, and Centre for Computational and Systems Medicine, Health Futures Institute, Murdoch University, Perth, WA, Australia
- Faculty of Medicine, Imperial College London, Institute of Global Health Innovation, London, United Kingdom
- Section of Nutrition Department of Metabolism, Digestion and Reproduction, Faculty of Medicine, Imperial College London, London, United Kingdom
| | - Nina D’Vaz
- Telethon Kids Institute, Perth Children’s Hospital, Nedlands, WA, Australia
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6
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Zhang X, Irajizad E, Hoffman KL, Fahrmann JF, Li F, Seo YD, Browman GJ, Dennison JB, Vykoukal J, Luna PN, Siu W, Wu R, Murage E, Ajami NJ, McQuade JL, Wargo JA, Long JP, Do KA, Lampe JW, Basen-Engquist KM, Okhuysen PC, Kopetz S, Hanash SM, Petrosino JF, Scheet P, Daniel CR. Modulating a prebiotic food source influences inflammation and immune-regulating gut microbes and metabolites: insights from the BE GONE trial. EBioMedicine 2023; 98:104873. [PMID: 38040541 PMCID: PMC10755114 DOI: 10.1016/j.ebiom.2023.104873] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2023] [Revised: 10/06/2023] [Accepted: 10/31/2023] [Indexed: 12/03/2023] Open
Abstract
BACKGROUND Accessible prebiotic foods hold strong potential to jointly target gut health and metabolic health in high-risk patients. The BE GONE trial targeted the gut microbiota of obese surveillance patients with a history of colorectal neoplasia through a straightforward bean intervention. METHODS This low-risk, non-invasive dietary intervention trial was conducted at MD Anderson Cancer Center (Houston, TX, USA). Following a 4-week equilibration, patients were randomized to continue their usual diet without beans (control) or to add a daily cup of study beans to their usual diet (intervention) with immediate crossover at 8-weeks. Stool and fasting blood were collected every 4 weeks to assess the primary outcome of intra and inter-individual changes in the gut microbiome and in circulating markers and metabolites within 8 weeks. This study was registered on ClinicalTrials.gov as NCT02843425, recruitment is complete and long-term follow-up continues. FINDINGS Of the 55 patients randomized by intervention sequence, 87% completed the 16-week trial, demonstrating an increase on-intervention in diversity [n = 48; linear mixed effect and 95% CI for inverse Simpson index: 0.16 (0.02, 0.30); p = 0.02] and shifts in multiple bacteria indicative of prebiotic efficacy, including increased Faecalibacterium, Eubacterium and Bifidobacterium (all p < 0.05). The circulating metabolome showed parallel shifts in nutrient and microbiome-derived metabolites, including increased pipecolic acid and decreased indole (all p < 0.002) that regressed upon returning to the usual diet. No significant changes were observed in circulating lipoproteins within 8 weeks; however, proteomic biomarkers of intestinal and systemic inflammatory response, fibroblast-growth factor-19 increased, and interleukin-10 receptor-α decreased (p = 0.01). INTERPRETATION These findings underscore the prebiotic and potential therapeutic role of beans to enhance the gut microbiome and to regulate host markers associated with metabolic obesity and colorectal cancer, while further emphasizing the need for consistent and sustainable dietary adjustments in high-risk patients. FUNDING This study was funded by the American Cancer Society.
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Affiliation(s)
- Xiaotao Zhang
- Division of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Institute for Translational Epidemiology & Division of Liver Diseases, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ehsan Irajizad
- Division of Basic Sciences, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kristi L Hoffman
- Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Johannes F Fahrmann
- Red & Charline McCombs Institute for the Early Detection and Treatment of Cancer, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Division of Cancer Prevention and Population Sciences, Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Fangyu Li
- Division of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Yongwoo David Seo
- Division of Surgery, Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Gladys J Browman
- Division of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer B Dennison
- Red & Charline McCombs Institute for the Early Detection and Treatment of Cancer, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jody Vykoukal
- Red & Charline McCombs Institute for the Early Detection and Treatment of Cancer, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Pamela N Luna
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, TX, USA
| | - Wesley Siu
- Division of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ranran Wu
- Red & Charline McCombs Institute for the Early Detection and Treatment of Cancer, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Eunice Murage
- Red & Charline McCombs Institute for the Early Detection and Treatment of Cancer, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Nadim J Ajami
- Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer L McQuade
- Division of Cancer Medicine, Department of Melanoma Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Jennifer A Wargo
- Division of Surgery, Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Platform for Innovative Microbiome and Translational Research, Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - James P Long
- Division of Basic Sciences, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Kim-Anh Do
- Division of Basic Sciences, Department of Biostatistics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Johanna W Lampe
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Karen M Basen-Engquist
- Division of Cancer Prevention and Population Sciences, Department of Heath Disparities Research, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Pablo C Okhuysen
- Department of Infectious Diseases, Infection Control, and Employee Health, Division of Internal Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Scott Kopetz
- Department of Gastrointestinal Medical Oncology, Division of Cancer Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Samir M Hanash
- Red & Charline McCombs Institute for the Early Detection and Treatment of Cancer, The University of Texas MD Anderson Cancer Center, Houston, TX, USA; Division of Cancer Prevention and Population Sciences, Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Joseph F Petrosino
- Alkek Center for Metagenomics and Microbiome Research, Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Paul Scheet
- Division of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Carrie R Daniel
- Division of Cancer Prevention and Population Sciences, Department of Epidemiology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
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7
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Lanng SK, Oxfeldt M, Johansen FT, Risikesan J, Hansen M, Bertram HC. Acute changes in the metabolome following resistance exercise combined with intake of different protein sources (cricket, pea, whey). Metabolomics 2023; 19:98. [PMID: 37999866 DOI: 10.1007/s11306-023-02064-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 11/08/2023] [Indexed: 11/25/2023]
Abstract
INTRODUCTION Separately, both exercise and protein ingestion have been shown to alter the blood and urine metabolome. This study goes a step further and examines changes in the metabolome derived from blood, urine and muscle tissue extracts in response to resistance exercise combined with ingestion of three different protein sources. METHODS In an acute parallel study, 52 young males performed one-legged resistance exercise (leg extension, 4 × 10 repetitions at 10 repetition maximum) followed by ingestion of either cricket (insect), pea or whey protein (0.25 g protein/kg fat free mass). Blood and muscle tissue were collected at baseline and three hours after protein ingestion. Urine was collected at baseline and four hours after protein ingestion. Mixed-effects analyses were applied to examine the effect of the time (baseline vs. post), protein (cricket, pea, whey), and time x protein interaction. RESULTS Nuclear magnetic resonance (NMR)-based metabolomics resulted in the annotation and quantification of 25 metabolites in blood, 35 in urine and 21 in muscle tissue. Changes in the muscle metabolome after combined exercise and protein intake indicated effects related to the protein source ingested. Muscle concentrations of leucine, methionine, glutamate and myo-inositol were higher after intake of whey protein compared to both cricket and pea protein. The blood metabolome revealed changes in a more ketogenic direction three hours after exercise reflecting that the trial was conducted after overnight fasting. Urinary concentration of trimethylamine N-oxide was significantly higher after ingestion of cricket than pea and whey protein. CONCLUSION The blood, urine and muscle metabolome showed different and supplementary responses to exercise and ingestion of the different protein sources, and in synergy the summarized results provided a more complete picture of the metabolic state of the body.
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Affiliation(s)
- Sofie Kaas Lanng
- Department of Food Science, Aarhus University, Aarhus N, 8200, Denmark
- CiFOOD, Centre for Innovative Food Research, Aarhus University, Aarhus N, 8200, Denmark
| | - Mikkel Oxfeldt
- Department of Public Health, Aarhus University, Aarhus C, 8000, Denmark
| | | | - Jeyanthini Risikesan
- Department of Child and Adolescent Medicine, Regional Hospital Gødstrup, Aarhus C, Denmark
| | - Mette Hansen
- Department of Public Health, Aarhus University, Aarhus C, 8000, Denmark
| | - Hanne Christine Bertram
- Department of Food Science, Aarhus University, Aarhus N, 8200, Denmark.
- CiFOOD, Centre for Innovative Food Research, Aarhus University, Aarhus N, 8200, Denmark.
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8
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Wang F, Baden MY, Guasch-Ferré M, Wittenbecher C, Li J, Li Y, Wan Y, Bhupathiraju SN, Tobias DK, Clish CB, Mucci LA, Eliassen AH, Costenbader KH, Karlson EW, Ascherio A, Rimm EB, Manson JE, Liang L, Hu FB. Plasma metabolite profiles related to plant-based diets and the risk of type 2 diabetes. Diabetologia 2022; 65:1119-1132. [PMID: 35391539 PMCID: PMC9810389 DOI: 10.1007/s00125-022-05692-8] [Citation(s) in RCA: 38] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 01/24/2022] [Indexed: 01/07/2023]
Abstract
AIMS/HYPOTHESIS Plant-based diets, especially when rich in healthy plant foods, have been associated with a lower risk of type 2 diabetes. However, whether plasma metabolite profiles related to plant-based diets reflect this association was unknown. The aim of this study was to identify the plasma metabolite profiles related to plant-based diets, and to evaluate the associations between the identified metabolite profiles and the risk of type 2 diabetes. METHODS Within three prospective cohorts (Nurses' Health Study, Nurses' Health Study II and Health Professionals Follow-up Study), we measured plasma metabolites from 10,684 participants using high-throughput LC MS. Adherence to plant-based diets was assessed by three indices derived from the food frequency questionnaire: an overall Plant-based Diet Index (PDI), a Healthy Plant-based Diet Index (hPDI), and an Unhealthy Plant-based Diet Index (uPDI). Multi-metabolite profiles related to plant-based diet were identified using elastic net regression with a training/testing approach. The prospective associations between metabolite profiles and incident type 2 diabetes were evaluated using multivariable Cox proportional hazards regression. Metabolites potentially mediating the association between plant-based diets and type 2 diabetes risk were further identified. RESULTS We identified multi-metabolite profiles comprising 55 metabolites for PDI, 93 metabolites for hPDI and 75 metabolites for uPDI. Metabolite profile scores based on the identified metabolite profiles were correlated with the corresponding diet index (Pearson r = 0.33-0.35 for PDI, 0.41-0.45 for hPDI, and 0.37-0.38 for uPDI, all p<0.001). Metabolite profile scores of PDI (HR per 1 SD higher = 0.81 [95% CI 0.75, 0.88]) and hPDI (HR per 1 SD higher = 0.77 [95% CI 0.71, 0.84]) showed an inverse association with incident type 2 diabetes, whereas the metabolite profile score for uPDI was not associated with the risk. Mutual adjustment for metabolites selected in the metabolite profiles, including trigonelline, hippurate, isoleucine and a subset of triacylglycerols, attenuated the associations of diet indices PDI and hPDI with lower type 2 diabetes risk. The explainable proportion of PDI/hPDI-related diabetes risk by these metabolites ranged between 8.5% and 37.2% (all p<0.05). CONCLUSIONS/INTERPRETATION Plasma metabolite profiles related to plant-based diets, especially a healthy plant-based diet, were associated with a lower risk of type 2 diabetes among a generally healthy population. Our findings support the beneficial role of healthy plant-based diets in diabetes prevention and provide new insights for future investigation.
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Affiliation(s)
- Fenglei Wang
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Megu Y Baden
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clemens Wittenbecher
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jun Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yanping Li
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Yi Wan
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Shilpa N Bhupathiraju
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Deirdre K Tobias
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Clary B Clish
- Metabolomics Platform, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - A Heather Eliassen
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Karen H Costenbader
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth W Karlson
- Division of Rheumatology, Inflammation and Immunity, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Alberto Ascherio
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Eric B Rimm
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - JoAnn E Manson
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Preventive Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Mary Horrigan Connors Center for Women's Health and Gender Biology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Liming Liang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA.
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
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9
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Picone G, Mengucci C, Capozzi F. The NMR added value to the green foodomics perspective: Advances by machine learning to the holistic view on food and nutrition. MAGNETIC RESONANCE IN CHEMISTRY : MRC 2022; 60:590-596. [PMID: 35174523 DOI: 10.1002/mrc.5257] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Revised: 02/08/2022] [Accepted: 02/11/2022] [Indexed: 06/14/2023]
Abstract
Food is a complex matter, literally. From production to functionalization, from nutritional quality engineering to predicting effects on health, the interest in finding an efficient physicochemical characterization of food has boomed in recent years. The sheer complexity of characterizing food and its interaction with the human organism has however made the use of data driven approaches in modeling a necessity. High-throughput techniques, such as nuclear magnetic resonance (NMR) spectroscopy, are well suited for omics data production and, coupled with machine learning, are paving a promising way of modeling food-human interaction. The foodomics approach sets the framework for omic data integration in food studies, in which NMR experiments play a key role. NMR data can be used to assess nutritional qualities of food, helping the design of functional and sustainable sources of nutrients; detect biomarkers of intake and study how they impact the metabolism of different individuals; study the kinetics of compounds in foods or their by-products to detect pathological conditions; and improve the efficiency of in silico models of the metabolic network.
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Affiliation(s)
- Gianfranco Picone
- Department of Agricultural and Food Sciences DISTAL, Alma Mater Studiorum University of Bologna, Cesena, Italy
| | - Carlo Mengucci
- Department of Agricultural and Food Sciences DISTAL, Alma Mater Studiorum University of Bologna, Cesena, Italy
| | - Francesco Capozzi
- Department of Agricultural and Food Sciences DISTAL, Alma Mater Studiorum University of Bologna, Cesena, Italy
- Interdepartmental Centre for Industrial Agrofood Research - CIRI Agrofood, Alma Mater Studiorum University of Bologna, Cesena, Italy
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10
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Hafiz MS, Campbell MD, Orsi NM, Mappa G, Orfila C, Boesch C. Impact of food processing on postprandial glycaemic and appetite responses in healthy adults: a randomized, controlled trial. Food Funct 2022; 13:1280-1290. [PMID: 35024710 DOI: 10.1039/d1fo02304g] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Chickpeas are among the lowest glycaemic index carbohydrate foods eliciting protracted digestion and enhanced satiety responses. In vitro studies suggest that mechanical processing of chickpeas significantly increases starch digestion. However, there is little evidence regarding the impact of processing on postprandial glycaemic response in response to chickpea intake in vivo. Therefore, the aim of this study was to determine the effect of mechanical processing on postprandial interstitial glycaemic and satiety responses in humans. In a randomised crossover design, thirteen normoglycaemic adults attended 4 separate laboratory visits following an overnight fast. On each occasion, one of four test meals, matched for available carbohydrate content and consisting of different physical forms of chickpeas (whole, puree, and pasta) or control (mashed potato), was administered followed by a subsequent standardised lunch meal. Continuous glucose monitoring captured interstitial glucose responses, accompanied by periodic venous blood samples for retrospective analysis of C-peptide, glucagon like peptide-1 (GLP-1), ghrelin, leptin, resistin, and cortisol. Subjective appetite responses were measured by Visual Analogue Scale (VAS). Postprandial glycaemic responses were comparable between chickpea treatments albeit significantly lower than the control (p < 0.001). Similarly, all chickpea treatments elicited significantly lower C-peptide and GLP-1 responses compared to the control (p < 0.05), accompanied by enhanced subjective satiety responses (p < 0.05), whilst no significant differences in satiety hormones were detected among different intervention groups (p > 0.05). Chickpea consumption elicits low postprandial glycaemic responses and enhanced subjective satiety responses irrespective of processing methods.
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Affiliation(s)
- Maryam S Hafiz
- School of Food Science and Nutrition, University of Leeds, Leeds, UK. .,Faculty of Applied Medical Sciences, Department of Clinical Nutrition, King Abdul-Aziz University, Jeddah, Saudi Arabia
| | - Matthew D Campbell
- School of Nursing and Health Sciences, Faculty of Health Sciences and Wellbeing, University of Sunderland, UK.,Wellcome-MRC Institute of Metabolic Science, University of Cambridge, UK.,Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, UK
| | - Nicolas M Orsi
- Leeds Institute of Cancer & Pathology, St James's University Hospital, Leeds, UK
| | - Georgia Mappa
- Leeds Institute of Cancer & Pathology, St James's University Hospital, Leeds, UK
| | - Caroline Orfila
- School of Food Science and Nutrition, University of Leeds, Leeds, UK.
| | - Christine Boesch
- School of Food Science and Nutrition, University of Leeds, Leeds, UK.
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11
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Rafiq T, Azab SM, Teo KK, Thabane L, Anand SS, Morrison KM, de Souza RJ, Britz-McKibbin P. Nutritional Metabolomics and the Classification of Dietary Biomarker Candidates: A Critical Review. Adv Nutr 2021; 12:2333-2357. [PMID: 34015815 PMCID: PMC8634495 DOI: 10.1093/advances/nmab054] [Citation(s) in RCA: 35] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2020] [Revised: 01/20/2021] [Accepted: 04/06/2021] [Indexed: 02/06/2023] Open
Abstract
Recent advances in metabolomics allow for more objective assessment of contemporary food exposures, which have been proposed as an alternative or complement to self-reporting of food intake. However, the quality of evidence supporting the utility of dietary biomarkers as valid measures of habitual intake of foods or complex dietary patterns in diverse populations has not been systematically evaluated. We reviewed nutritional metabolomics studies reporting metabolites associated with specific foods or food groups; evaluated the interstudy repeatability of dietary biomarker candidates; and reported study design, metabolomic approach, analytical technique(s), and type of biofluid analyzed. A comprehensive literature search of 5 databases (PubMed, EMBASE, Web of Science, BIOSIS, and CINAHL) was conducted from inception through December 2020. This review included 244 studies, 169 (69%) of which were interventional studies (9 of these were replicated in free-living participants) and 151 (62%) of which measured the metabolomic profile of serum and/or plasma. Food-based metabolites identified in ≥1 study and/or biofluid were associated with 11 food-specific categories or dietary patterns: 1) fruits; 2) vegetables; 3) high-fiber foods (grain-rich); 4) meats; 5) seafood; 6) pulses, legumes, and nuts; 7) alcohol; 8) caffeinated beverages, teas, and cocoas; 9) dairy and soya; 10) sweet and sugary foods; and 11) complex dietary patterns and other foods. We conclude that 69 metabolites represent good candidate biomarkers of food intake. Quantitative measurement of these metabolites will advance our understanding of the relation between diet and chronic disease risk and support evidence-based dietary guidelines for global health.
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Affiliation(s)
- Talha Rafiq
- Medical Sciences Graduate Program, Faculty of Health Sciences, McMaster University, Hamilton, Canada
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Canada
| | - Sandi M Azab
- Department of Chemistry and Chemical Biology, McMaster University, Hamilton, Canada
- Department of Pharmacognosy, Alexandria University, Alexandria, Egypt
| | - Koon K Teo
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Canada
- Department of Health Research Methods, Evidence & Impact, McMaster University, Hamilton, Canada
- Department of Medicine, McMaster University, Hamilton, Canada
| | - Lehana Thabane
- Department of Health Research Methods, Evidence & Impact, McMaster University, Hamilton, Canada
| | - Sonia S Anand
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Canada
- Department of Health Research Methods, Evidence & Impact, McMaster University, Hamilton, Canada
- Department of Medicine, McMaster University, Hamilton, Canada
| | | | - Russell J de Souza
- Population Health Research Institute, Hamilton Health Sciences, McMaster University, Hamilton, Canada
- Department of Health Research Methods, Evidence & Impact, McMaster University, Hamilton, Canada
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12
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Folz JS, Shalon D, Fiehn O. Metabolomics analysis of time-series human small intestine lumen samples collected in vivo. Food Funct 2021; 12:9405-9415. [PMID: 34606553 DOI: 10.1039/d1fo01574e] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
The human small intestine remains an elusive organ to study due to the difficulty of retrieving samples in a non-invasive manner. Stool samples as a surrogate do not reflect events in the upper gut intestinal tract. As proof of concept, this study investigates time-series samples collected from the upper gastrointestinal tract of a single healthy subject. Samples were retrieved using a small diameter tube that collected samples in the stomach and duodenum as the tube progressed to the jejunum, and then remained positioned in the jejunum during the final 8.5 hours of the testing period. Lipidomics and metabolomics liquid chromatography tandem mass spectrometry (LC-MS/MS) assays were employed to annotate 828 unique metabolites using accurate mass with retention time and/or tandem MS library matches. Annotated metabolites were clustered based on correlation to reveal sets of biologically related metabolites. Typical clusters included bile metabolites, food metabolites, protein breakdown products, and endogenous lipids. Acylcarnitines and phospholipids were clustered with known human bile components supporting their presence in human bile, in addition to novel human bile compounds 4-hydroxyhippuric acid, N-acetylglucosaminoasparagine and 3-methoxy-4-hydroxyphenylglycol sulfate. Food metabolites were observed passing through the small intestine after meals. Acetaminophen and its human phase II metabolism products appeared for hours after the initial drug treatment, due to excretion back into the gastrointestinal tract after initial absorption. This exploratory study revealed novel trends in timing and chemical composition of the human jejunum under standard living conditions.
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Affiliation(s)
- Jacob S Folz
- West Coast Metabolomics Center and Department of Food Science and Technology, University of California Davis, Davis, CA, USA.
| | | | - Oliver Fiehn
- West Coast Metabolomics Center and Department of Food Science and Technology, University of California Davis, Davis, CA, USA.
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13
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Smith CE, Parnell LD, Lai CQ, Rush JE, Freeman LM. Investigation of diets associated with dilated cardiomyopathy in dogs using foodomics analysis. Sci Rep 2021; 11:15881. [PMID: 34354102 PMCID: PMC8342479 DOI: 10.1038/s41598-021-94464-2] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 07/08/2021] [Indexed: 02/07/2023] Open
Abstract
Dilated cardiomyopathy (DCM) is a disease of the heart muscle that affects both humans and dogs. Certain canine diets have been associated with DCM, but the diet-disease link is unexplained, and novel methods are needed to elucidate mechanisms. We conducted metabolomic profiling of 9 diets associated with canine DCM, containing ≥ 3 pulses, potatoes, or sweet potatoes as main ingredients, and in the top 16 dog diet brands most frequently associated with canine DCM cases reported to the FDA (3P/FDA diets), and 9 non-3P/FDA diets. We identified 88 named biochemical compounds that were higher in 3P/FDA diets and 23 named compounds that were lower in 3P/FDA diets. Amino acids, amino acid-derived compounds, and xenobiotics/plant compounds were the largest categories of biochemicals that were higher in 3P/FDA diets. Random forest analyses identified the top 30 compounds that distinguished the two diet groups with 100% predictive accuracy. Four diet ingredients distinguished the two diet groups (peas, lentils, chicken/turkey, and rice). Of these ingredients, peas showed the greatest association with higher concentrations of compounds in 3P/FDA diets. Moreover, the current foodomics analyses highlight relationships between diet and DCM in dogs that can identify possible etiologies for understanding diet-disease relationships in dogs and humans.
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Affiliation(s)
- Caren E Smith
- Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Laurence D Parnell
- USDA Agricultural Research Service, Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - Chao-Qiang Lai
- USDA Agricultural Research Service, Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Boston, MA, USA
| | - John E Rush
- Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA, USA
| | - Lisa M Freeman
- Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA, USA.
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14
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Garcia-Aloy M, Ulaszewska M, Franceschi P, Estruel-Amades S, Weinert CH, Tor-Roca A, Urpi-Sarda M, Mattivi F, Andres-Lacueva C. Discovery of Intake Biomarkers of Lentils, Chickpeas, and White Beans by Untargeted LC-MS Metabolomics in Serum and Urine. Mol Nutr Food Res 2020; 64:e1901137. [PMID: 32420683 DOI: 10.1002/mnfr.201901137] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2019] [Revised: 05/05/2020] [Indexed: 11/12/2022]
Abstract
SCOPE To identify reliable biomarkers of food intake (BFIs) of pulses. METHODS AND RESULTS A randomized crossover postprandial intervention study is conducted on 11 volunteers who consumed lentils, chickpeas, and white beans. Urine and serum samples are collected at distinct postprandial time points up to 48 h, and analyzed by LC-HR-MS untargeted metabolomics. Hypaphorine, trigonelline, several small peptides, and polyphenol-derived metabolites prove to be the most discriminating urinary metabolites. Two arginine-related compounds, dopamine sulfate and epicatechin metabolites, with their microbial derivatives, are identified only after intake of lentils, whereas protocatechuic acid is identified only after consumption of chickpeas. Urinary hydroxyjasmonic and hydroxydihydrojasmonic acids, as well as serum pipecolic acid and methylcysteine, are found after white bean consumption. Most of the metabolites identified in the postprandial study are replicated as discriminants in 24 h urine samples, demonstrating that in this case the use of a single, noninvasive sample is suitable for revealing the consumption of pulses. CONCLUSIONS The results of the present untargeted metabolomics work reveals a broad list of metabolites that are candidates for use as biomarkers of pulse intake. Further studies are needed to validate these BFIs and to find the best combinations of them to boost their specificity.
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Affiliation(s)
- Mar Garcia-Aloy
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, 08028, Spain.,Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), San Michele all'Adige, 38010, Italy
| | - Marynka Ulaszewska
- IRCCS San Raffaele Scientific Institute, Center for Omics Sciences, Proteomics and Metabolomics Facility - ProMeFa, Milan, 20132, Italy.,Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), San Michele all'Adige, 38010, Italy
| | - Pietro Franceschi
- Computational Biology Unit, Research and Innovation Center, Fondazione Edmund Mach, San Michele all'Adige, 38010, Italy
| | - Sheila Estruel-Amades
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain
| | - Christoph H Weinert
- Department of Safety and Quality of Fruit and Vegetables, Max Rubner-Institut, Federal Research Institute of Nutrition and Food, Karlsruhe, 76131, Germany
| | - Alba Tor-Roca
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, 08028, Spain
| | - Mireia Urpi-Sarda
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, 08028, Spain
| | - Fulvio Mattivi
- Department of Food Quality and Nutrition, Research and Innovation Center, Fondazione Edmund Mach (FEM), San Michele all'Adige, 38010, Italy.,Department of Cellular, Computational and Integrative Biology (CIBIO), University of Trento, Povo, 38123, Italy
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Sciences and Gastronomy, XaRTA, INSA, Faculty of Pharmacy and Food Sciences, University of Barcelona, Barcelona, 08028, Spain.,CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, Barcelona, 08028, Spain
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15
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Human urine 1H NMR metabolomics reveals alterations of protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet. Nutrition 2020; 79-80:110867. [PMID: 32619792 DOI: 10.1016/j.nut.2020.110867] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2019] [Revised: 04/16/2020] [Accepted: 05/02/2020] [Indexed: 12/13/2022]
Abstract
OBJECTIVES The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and chefs, based on local and sustainable foods, including fish, shellfish, vegetables, roots, fruit, and berries. The NND has been proven to lower blood pressure, reduce glycemia, and lead to weight loss. METHODS The human urine metabolome was measured by untargeted proton nuclear magnetic resonance spectroscopy in samples from 142 centrally obese Danes (20-66 years old), randomized to consume the ADD or the NND. The resulting metabolomics data was processed and analyzed using advanced multivariate data analysis methods to reveal effects related to the design factors, including diet, season, sex, and changes in body weight. RESULTS Exploration of the nuclear magnetic resonance profiles revealed unique metabolite markers reflecting changes in protein and carbohydrate metabolism between the two diets. Glycine betaine, glucose, trimethylamine N-oxide and creatinine were increased in urine of the individuals following the NND compared with the ADD population, whereas relative concentrations of tartrate, dimethyl sulfone, and propylene glycol were decreased. Propylene glycol had a strong association with the homeostatic model assessment for insulin resistance in the NND group. The food intake biomarkers found in this study confirm the importance of these as tools for nutritional research. CONCLUSIONS Findings from this study provided new insights into the effects of a healthy diet on glycemia, reduction of inflammation, and weight loss among obese individuals, and alteration of the gut microbiota metabolism.
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Wang X, Rezeng C, Wang Y, Li J, Zhang L, Chen J, Li Z. Toxicological Risks of Renqingchangjue in Rats Evaluated by 1H NMR-Based Serum and Urine Metabolomics Analysis. ACS OMEGA 2020; 5:2169-2179. [PMID: 32064377 PMCID: PMC7016918 DOI: 10.1021/acsomega.9b03084] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/19/2019] [Accepted: 01/17/2020] [Indexed: 05/09/2023]
Abstract
Renqingchangjue (RQCJ), a kind of Traditional Tibetan Medicine, has been widely utilized to treat various gastroenteritis diseases. However, the biosafety and toxicity of RQCJ was still indefinite because of toxic components in RQCJ, which included a variety of heavy metals. Thus, this study was aimed to evaluate the toxicity and expound the toxicological mechanism of RQCJ. In this study, rats were intragastrically administered with different doses of RQCJ for 15 days, and then, the restorative observation period lasted for 15 days. Liver and kidney tissues were collected for histopathological examination, and simultaneously serum and urine samples were collected for 1H nuclear magnetic resonance (1H NMR) spectroscopy analysis and biochemical analysis combined with inductively coupled plasma mass spectrometry (ICP-MS) measurement. The 1H NMR-based metabolomics analysis revealed that the administration of RQCJ significantly altered the concentrations of 14 serum metabolites and 14 urine metabolites, which implied disturbances in energy metabolism, amino acid metabolism, intestinal flora environment, and membrane damage. Besides, the biochemical analysis of serum samples was consistent with the histopathological results, which indicated slight hepatotoxicity and nephrotoxicity. The quantification of As and Hg in urine and serum samples by ICP-MS provided more evidence about the toxicity of RQCJ. This work provided an effective method to systematically and dynamically evaluate the toxicity of RQCJ and suggested that precautions should be taken in the clinic to monitor the potential toxicity of RQCJ.
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Affiliation(s)
- Xia Wang
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
| | - Caidan Rezeng
- College
of Pharmacy, Qinghai Nationalities University, No. 3 Bayizhong Road, Xining 810000, PR China
| | - Yingfeng Wang
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
| | - Jian Li
- Beijing
University of Chinese Medicine, No. 11 Beisanhuandonglu, Chaoyang District, Beijing 100029, PR China
| | - Lan Zhang
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
| | - Jianxin Chen
- Beijing
University of Chinese Medicine, No. 11 Beisanhuandonglu, Chaoyang District, Beijing 100029, PR China
| | - Zhongfeng Li
- Department
of Chemistry, Capital Normal University, No. 105, Xisanhuanbeilu, Haidian District, Beijing 100048, PR China
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17
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Ocvirk S, Wilson AS, Posma JM, Li JV, Koller KR, Day GM, Flanagan CA, Otto JE, Sacco PE, Sacco FD, Sapp FR, Wilson AS, Newton K, Brouard F, DeLany JP, Behnning M, Appolonia CN, Soni D, Bhatti F, Methé B, Fitch A, Morris A, Gaskins HR, Kinross J, Nicholson JK, Thomas TK, O'Keefe SJD. A prospective cohort analysis of gut microbial co-metabolism in Alaska Native and rural African people at high and low risk of colorectal cancer. Am J Clin Nutr 2020; 111:406-419. [PMID: 31851298 PMCID: PMC6997097 DOI: 10.1093/ajcn/nqz301] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/16/2019] [Accepted: 11/14/2019] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Alaska Native (AN) people have the world's highest recorded incidence of sporadic colorectal cancer (CRC) (∼91:100,000), whereas rural African (RA) people have the lowest risk (<5:100,000). Previous data supported the hypothesis that diet affected CRC risk through its effects on the colonic microbiota that produce tumor-suppressive or -promoting metabolites. OBJECTIVES We investigated whether differences in these metabolites may contribute to the high risk of CRC in AN people. METHODS A cross-sectional observational study assessed dietary intake from 32 AN and 21 RA healthy middle-aged volunteers before screening colonoscopy. Analysis of fecal microbiota composition by 16S ribosomal RNA gene sequencing and fecal/urinary metabolites by 1H-NMR spectroscopy was complemented with targeted quantification of fecal SCFAs, bile acids, and functional microbial genes. RESULTS Adenomatous polyps were detected in 16 of 32 AN participants, but not found in RA participants. The AN diet contained higher proportions of fat and animal protein and less fiber. AN fecal microbiota showed a compositional predominance of Blautia and Lachnoclostridium, higher microbial capacity for bile acid conversion, and low abundance of some species involved in saccharolytic fermentation (e.g., Prevotellaceae, Ruminococcaceae), but no significant lack of butyrogenic bacteria. Significantly lower concentrations of tumor-suppressive butyrate (22.5 ± 3.1 compared with 47.2 ± 7.3 SEM µmol/g) coincided with significantly higher concentrations of tumor-promoting deoxycholic acid (26.7 ± 4.2 compared with 11 ± 1.9 µmol/g) in AN fecal samples. AN participants had lower quantities of fecal/urinary metabolites than RA participants and metabolite profiles correlated with the abundance of distinct microbial genera in feces. The main microbial and metabolic CRC-associated markers were not significantly altered in AN participants with adenomatous polyps. CONCLUSIONS The low-fiber, high-fat diet of AN people and exposure to carcinogens derived from diet or environment are associated with a tumor-promoting colonic milieu as reflected by the high rates of adenomatous polyps in AN participants.
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Affiliation(s)
- Soeren Ocvirk
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Department of Gastrointestinal Microbiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
| | - Annette S Wilson
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Joram M Posma
- Section of Bioinformatics, Division of Systems Medicine, Department of Metabolism, Digestion and Reproduction, Imperial College, London, United Kingdom
| | - Jia V Li
- Section of Nutritional Research, Division of Digestive Diseases, Department of Metabolism, Digestion, and Reproduction, Imperial College, London, United Kingdom
- Centre for Digestive and Gut Health, Institution of Global Health Innovation, Imperial College, London, United Kingdom
| | - Kathryn R Koller
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Gretchen M Day
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Christie A Flanagan
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Jill Evon Otto
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Pam E Sacco
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Frank D Sacco
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Flora R Sapp
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Amy S Wilson
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Keith Newton
- Division of Gastroenterology, University of KwaZulu-Natal, Durban, South Africa
| | - Faye Brouard
- Manguzi Hospital, Manguzi, KwaZulu-Natal, South Africa
| | - James P DeLany
- Division of Endocrinology, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
- Translational Research Institute for Metabolism and Diabetes, Advent Health, Orlando, FL, USA
| | - Marissa Behnning
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Corynn N Appolonia
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Devavrata Soni
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Faheem Bhatti
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Barbara Methé
- Center for Medicine and the Microbiome, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Adam Fitch
- Center for Medicine and the Microbiome, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - Alison Morris
- Center for Medicine and the Microbiome, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
| | - H Rex Gaskins
- Division of Nutritional Sciences, University of Illinois at Urbana-Champaign, Urbana, IL, USA
| | - James Kinross
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Jeremy K Nicholson
- Centre for Digestive and Gut Health, Institution of Global Health Innovation, Imperial College, London, United Kingdom
- Department of Surgery and Cancer, Faculty of Medicine, Imperial College, London, United Kingdom
| | - Timothy K Thomas
- Clinical & Research Services, Community Health Services, Alaska Native Tribal Health Consortium, Anchorage, AK, USA
| | - Stephen J D O'Keefe
- Division of Gastroenterology, Hepatology and Nutrition, Department of Medicine, University of Pittsburgh, Pittsburgh, PA, USA
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18
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Zhang Q, Nong Y, Liu Z, Gong L. Proteinase K Combining Two-Step Liquid–Liquid Extraction for Plasma Untargeted Liquid Chromatography–Mass Spectrometry-Based Metabolomics To Discover the Potential Mechanism of Colorectal Adenoma. Anal Chem 2019; 91:14458-14466. [DOI: 10.1021/acs.analchem.9b03121] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Affiliation(s)
- Qisong Zhang
- International Institute for Translational Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, People’s Republic of China
- Guangdong Key Laboratory for Translational Cancer Research of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, People’s Republic of China
| | - Yanying Nong
- Guangdong Key Laboratory of Gastroenterology, Department of Gastroenterology, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong 510515, People’s Republic of China
| | - Zhongqiu Liu
- International Institute for Translational Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, People’s Republic of China
- Guangdong Key Laboratory for Translational Cancer Research of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, People’s Republic of China
| | - Lingzhi Gong
- International Institute for Translational Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, People’s Republic of China
- Guangdong Key Laboratory for Translational Cancer Research of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong 510006, People’s Republic of China
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19
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Llorach R, Favari C, Alonso D, Garcia-Aloy M, Andres-Lacueva C, Urpi-Sarda M. Comparative metabolite fingerprinting of legumes using LC-MS-based untargeted metabolomics. Food Res Int 2019; 126:108666. [PMID: 31732019 DOI: 10.1016/j.foodres.2019.108666] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Revised: 04/14/2019] [Accepted: 09/09/2019] [Indexed: 01/08/2023]
Abstract
Legumes are a well-known source of phytochemicals and are commonly believed to have similar composition between different genera. To date, there are no studies evaluating changes in legumes to discover those compounds that help to discriminate for food quality and authenticity. The aim of this work was to characterize and make a comparative analysis of the composition of bioactive compounds between Cicer arietinum L. (chickpea), Lens culinaris L. (lentil) and Phaseolus vulgaris L. (white bean) through an LC-MS-Orbitrap metabolomic approach to establish which compounds discriminate between the three studied legumes. Untargeted metabolomic analysis was carried out by LC-MS-Orbitrap from extracts of freeze-dried legumes prepared from pre-cooked canned legumes. The metabolomic data treatment and statistical analysis were realized by using MAIT R's package, and final identification and characterization was done using MSn experiments. Fold-change evaluation was made through Metaboanalyst 4.0. Results showed 43 identified and characterized compounds displaying differences between the three legumes. Polyphenols, mainly flavonol and flavanol compounds, were the main group with 30 identified compounds, followed by α-galactosides (n = 5). Fatty acyls, prenol lipids, a nucleoside and organic compounds were also characterized. The fold-change analysis showed flavanols as the wider class of discriminative compounds of lentils compared to the other legumes; prenol lipids and eucomic acids were the most discriminative compounds of beans versus other legumes and several phenolic acids (such as primeveroside salycilic), kaempferol derivatives, coumesterol and α-galactosides were the most discriminative compounds of chickpeas. This study highlights the applicability of metabolomics for evaluating which are the characteristic compounds of the different legumes. In addition, it describes the future application of metabolomics as tool for the quality control of foods and authentication of different kinds of legumes.
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Affiliation(s)
- Rafael Llorach
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), Faculty of Pharmacy and Food Science, Campus Torribera, University of Barcelona, 08028 Barcelona, Spain; CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 08028 Barcelona, Spain
| | - Claudia Favari
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), Faculty of Pharmacy and Food Science, Campus Torribera, University of Barcelona, 08028 Barcelona, Spain
| | - David Alonso
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), Faculty of Pharmacy and Food Science, Campus Torribera, University of Barcelona, 08028 Barcelona, Spain
| | - Mar Garcia-Aloy
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), Faculty of Pharmacy and Food Science, Campus Torribera, University of Barcelona, 08028 Barcelona, Spain; CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 08028 Barcelona, Spain
| | - Cristina Andres-Lacueva
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), Faculty of Pharmacy and Food Science, Campus Torribera, University of Barcelona, 08028 Barcelona, Spain; CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 08028 Barcelona, Spain
| | - Mireia Urpi-Sarda
- Biomarkers and Nutrimetabolomics Laboratory, Department of Nutrition, Food Science and Gastronomy, Food Technology Reference Net (XaRTA), Nutrition and Food Safety Research Institute (INSA), Faculty of Pharmacy and Food Science, Campus Torribera, University of Barcelona, 08028 Barcelona, Spain; CIBER Fragilidad y Envejecimiento Saludable (CIBERFES), Instituto de Salud Carlos III, 08028 Barcelona, Spain.
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20
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Low DY, Lefèvre‐Arbogast S, González‐Domínguez R, Urpi‐Sarda M, Micheau P, Petera M, Centeno D, Durand S, Pujos‐Guillot E, Korosi A, Lucassen PJ, Aigner L, Proust‐Lima C, Hejblum BP, Helmer C, Andres‐Lacueva C, Thuret S, Samieri C, Manach C. Diet-Related Metabolites Associated with Cognitive Decline Revealed by Untargeted Metabolomics in a Prospective Cohort. Mol Nutr Food Res 2019; 63:e1900177. [PMID: 31218777 PMCID: PMC6790579 DOI: 10.1002/mnfr.201900177] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 05/24/2019] [Indexed: 12/21/2022]
Abstract
SCOPE Untargeted metabolomics may reveal preventive targets in cognitive aging, including within the food metabolome. METHODS AND RESULTS A case-control study nested in the prospective Three-City study includes participants aged ≥65 years and initially free of dementia. A total of 209 cases of cognitive decline and 209 controls (matched for age, gender, education) with slower cognitive decline over up to 12 years are contrasted. Using untargeted metabolomics and bootstrap-enhanced penalized regression, a baseline serum signature of 22 metabolites associated with subsequent cognitive decline is identified. The signature includes three coffee metabolites, a biomarker of citrus intake, a cocoa metabolite, two metabolites putatively derived from fish and wine, three medium-chain acylcarnitines, glycodeoxycholic acid, lysoPC(18:3), trimethyllysine, glucose, cortisol, creatinine, and arginine. Adding the 22 metabolites to a reference predictive model for cognitive decline (conditioned on age, gender, education and including ApoE-ε4, diabetes, BMI, and number of medications) substantially increases the predictive performance: cross-validated Area Under the Receiver Operating Curve = 75% [95% CI 70-80%] compared to 62% [95% CI 56-67%]. CONCLUSIONS The untargeted metabolomics study supports a protective role of specific foods (e.g., coffee, cocoa, fish) and various alterations in the endogenous metabolism responsive to diet in cognitive aging.
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Affiliation(s)
- Dorrain Yanwen Low
- Human Nutrition UnitINRA, Université Clermont AuvergneF‐63000Clermont‐FerrandFrance
| | - Sophie Lefèvre‐Arbogast
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | - Raúl González‐Domínguez
- Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)Instituto de Salud Carlos IIIUniversity of BarcelonaAv Joan XXIII 27–3108028BarcelonaSpain
| | - Mireia Urpi‐Sarda
- Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)Instituto de Salud Carlos IIIUniversity of BarcelonaAv Joan XXIII 27–3108028BarcelonaSpain
| | - Pierre Micheau
- Human Nutrition UnitINRA, Université Clermont AuvergneF‐63000Clermont‐FerrandFrance
| | - Melanie Petera
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Delphine Centeno
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Stephanie Durand
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Estelle Pujos‐Guillot
- Université Clermont AuvergneINRA, UNH, Plateforme d'Exploration du MétabolismeMetaboHUB ClermontF‐63000Clermont‐FerrandFrance
| | - Aniko Korosi
- Brain Plasticity Group, SILS‐CNSUniversity of AmsterdamScience Park 9041098 XHAmsterdamThe Netherlands
| | - Paul J Lucassen
- Brain Plasticity Group, SILS‐CNSUniversity of AmsterdamScience Park 9041098 XHAmsterdamThe Netherlands
| | - Ludwig Aigner
- Institute of Molecular Regenerative Medicine, Spinal Cord Injury and Tissue Regeneration Center Salzburg, Paracelsus Medical UniversitySalzburg5020Austria
| | - Cécile Proust‐Lima
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | | | - Catherine Helmer
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | - Cristina Andres‐Lacueva
- Nutrition, Food Science and Gastronomy Department, Faculty of Pharmacy and Food Science, CIBER Fragilidad y Envejecimiento Saludable (CIBERFES)Instituto de Salud Carlos IIIUniversity of BarcelonaAv Joan XXIII 27–3108028BarcelonaSpain
| | - Sandrine Thuret
- Department of Basic and Clinical NeuroscienceMaurice Wohl Neuroscience InstituteInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 9NUUK
| | - Cécilia Samieri
- Bordeaux Population Health Research CenterInserm, University of BordeauxUMR 1219F‐33000BordeauxFrance
| | - Claudine Manach
- Human Nutrition UnitINRA, Université Clermont AuvergneF‐63000Clermont‐FerrandFrance
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21
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NMR Based Metabolomic Analysis of Health Promoting Phytochemicals in Lentils. Metabolites 2019; 9:metabo9080168. [PMID: 31412621 PMCID: PMC6724105 DOI: 10.3390/metabo9080168] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2019] [Revised: 08/05/2019] [Accepted: 08/05/2019] [Indexed: 01/17/2023] Open
Abstract
Lentils are a high-protein plant food and a valuable source of human nutrition, particularly in the Indian subcontinent. However, beyond sustenance, there is evidence that the consumption of lentils (and legumes in general) is associated with decreased risk of diseases, such as diabetes and cardiovascular disease. Lentils contain health-promoting phytochemicals, such as trigonelline and various polyphenolics. Fourteen lentil genotypes were grown at three locations to explore the variation in phytochemical composition in hulls and cotyledons. Significant differences were measured between genotypes and environments, with some genotypes more affected by environment than others. However, there was a strong genetic effect which indicated that future breeding programs could breed for lentils that product more of these health-promoting phytochemicals.
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22
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Rådjursöga M, Lindqvist HM, Pedersen A, Karlsson GB, Malmodin D, Brunius C, Ellegård L, Winkvist A. The 1H NMR serum metabolomics response to a two meal challenge: a cross-over dietary intervention study in healthy human volunteers. Nutr J 2019; 18:25. [PMID: 30961592 PMCID: PMC6454665 DOI: 10.1186/s12937-019-0446-2] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2018] [Accepted: 03/21/2019] [Indexed: 12/25/2022] Open
Abstract
BACKGROUND Metabolomics represents a powerful tool for exploring modulation of the human metabolome in response to food intake. However, the choice of multivariate statistical approach is not always evident, especially for complex experimental designs with repeated measurements per individual. Here we have investigated the serum metabolic responses to two breakfast meals: an egg and ham based breakfast and a cereal based breakfast using three different multivariate approaches based on the Projections to Latent Structures framework. METHODS In a cross over design, 24 healthy volunteers ate the egg and ham breakfast and cereal breakfast on four occasions each. Postprandial serum samples were subjected to metabolite profiling using 1H nuclear magnetic resonance spectroscopy and metabolites were identified using 2D nuclear magnetic resonance spectroscopy. Metabolic profiles were analyzed using Orthogonal Projections to Latent Structures with Discriminant Analysis and Effect Projections and ANOVA-decomposed Projections to Latent Structures. RESULTS The Orthogonal Projections to Latent Structures with Discriminant Analysis model correctly classified 92 and 90% of the samples from the cereal breakfast and egg and ham breakfast, respectively, but confounded dietary effects with inter-personal variability. Orthogonal Projections to Latent Structures with Effect Projections removed inter-personal variability and performed perfect classification between breakfasts, however at the expense of comparing means of respective breakfasts instead of all samples. ANOVA-decomposed Projections to Latent Structures managed to remove inter-personal variability and predicted 99% of all individual samples correctly. Proline, tyrosine, and N-acetylated amino acids were found in higher concentration after consumption of the cereal breakfast while creatine, methanol, and isoleucine were found in higher concentration after the egg and ham breakfast. CONCLUSIONS Our results demonstrate that the choice of statistical method will influence the results and adequate methods need to be employed to manage sample dependency and repeated measurements in cross-over studies. In addition, 1H nuclear magnetic resonance serum metabolomics could reproducibly characterize postprandial metabolic profiles and identify discriminatory metabolites largely reflecting dietary composition. TRIAL REGISTRATION Registered with ClinicalTrials.gov, identifier: NCT02039596 . Date of registration: January 17, 2014.
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Affiliation(s)
| | - Helen M Lindqvist
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anders Pedersen
- Swedish NMR Centre, University of Gothenburg, Gothenburg, Sweden
| | - Göran B Karlsson
- Swedish NMR Centre, University of Gothenburg, Gothenburg, Sweden
| | - Daniel Malmodin
- Swedish NMR Centre, University of Gothenburg, Gothenburg, Sweden
| | - Carl Brunius
- Department of Biology and Biological Engineering Food and Nutrition Science Chalmers University of Technology, Gothenburg, Sweden
| | - Lars Ellegård
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
| | - Anna Winkvist
- Department of Internal Medicine and Clinical Nutrition, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden
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