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Membrez M, Migliavacca E, Christen S, Yaku K, Trieu J, Lee AK, Morandini F, Giner MP, Stiner J, Makarov MV, Garratt ES, Vasiloglou MF, Chanvillard L, Dalbram E, Ehrlich AM, Sanchez-Garcia JL, Canto C, Karagounis LG, Treebak JT, Migaud ME, Heshmat R, Razi F, Karnani N, Ostovar A, Farzadfar F, Tay SKH, Sanders MJ, Lillycrop KA, Godfrey KM, Nakagawa T, Moco S, Koopman R, Lynch GS, Sorrentino V, Feige JN. Trigonelline is an NAD + precursor that improves muscle function during ageing and is reduced in human sarcopenia. Nat Metab 2024; 6:433-447. [PMID: 38504132 DOI: 10.1038/s42255-024-00997-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/14/2022] [Accepted: 01/26/2024] [Indexed: 03/21/2024]
Abstract
Mitochondrial dysfunction and low nicotinamide adenine dinucleotide (NAD+) levels are hallmarks of skeletal muscle ageing and sarcopenia1-3, but it is unclear whether these defects result from local changes or can be mediated by systemic or dietary cues. Here we report a functional link between circulating levels of the natural alkaloid trigonelline, which is structurally related to nicotinic acid4, NAD+ levels and muscle health in multiple species. In humans, serum trigonelline levels are reduced with sarcopenia and correlate positively with muscle strength and mitochondrial oxidative phosphorylation in skeletal muscle. Using naturally occurring and isotopically labelled trigonelline, we demonstrate that trigonelline incorporates into the NAD+ pool and increases NAD+ levels in Caenorhabditis elegans, mice and primary myotubes from healthy individuals and individuals with sarcopenia. Mechanistically, trigonelline does not activate GPR109A but is metabolized via the nicotinate phosphoribosyltransferase/Preiss-Handler pathway5,6 across models. In C. elegans, trigonelline improves mitochondrial respiration and biogenesis, reduces age-related muscle wasting and increases lifespan and mobility through an NAD+-dependent mechanism requiring sirtuin. Dietary trigonelline supplementation in male mice enhances muscle strength and prevents fatigue during ageing. Collectively, we identify nutritional supplementation of trigonelline as an NAD+-boosting strategy with therapeutic potential for age-associated muscle decline.
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Affiliation(s)
- Mathieu Membrez
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
| | | | - Stefan Christen
- Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland
| | - Keisuke Yaku
- Department of Molecular and Medical Pharmacology, Faculty of Medicine, University of Toyama, Toyama, Japan
| | - Jennifer Trieu
- Centre for Muscle Research, Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Alaina K Lee
- Centre for Muscle Research, Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Francesco Morandini
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Maria Pilar Giner
- Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland
| | - Jade Stiner
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Mikhail V Makarov
- Mitchell Cancer Institute, Department of Pharmacology, F. P. Whiddon College of Medicine, University of South Alabama, Mobile, AL, USA
| | - Emma S Garratt
- Institute of Developmental Sciences, Human Developmental and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- National Institute for Health and Care Research, Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
| | - Maria F Vasiloglou
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
| | - Lucie Chanvillard
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Emilie Dalbram
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Amy M Ehrlich
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Carles Canto
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Leonidas G Karagounis
- Nestlé Health Science, Translation Research, Lausanne, Switzerland
- Mary MacKillop Institute for Health Research, Australian Catholic University, Melbourne, Victoria, Australia
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Jonas T Treebak
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Marie E Migaud
- Mitchell Cancer Institute, Department of Pharmacology, F. P. Whiddon College of Medicine, University of South Alabama, Mobile, AL, USA
| | - Ramin Heshmat
- Chronic Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Science Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Neerja Karnani
- Singapore Institute for Clinical Sciences (A*STAR), Singapore, Singapore
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Bioinformatics Institute, Agency for Science, Technology and Research (A*STAR), Singapore, Singapore
| | - Afshin Ostovar
- Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farshad Farzadfar
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Stacey K H Tay
- KTP-National University Children's Medical Institute, National University Hospital, Singapore, Singapore
| | - Matthew J Sanders
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland
| | - Karen A Lillycrop
- Institute of Developmental Sciences, Human Developmental and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- National Institute for Health and Care Research, Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Biological Sciences, Faculty of Environmental and Life Sciences, University of Southampton, Southampton, UK
| | - Keith M Godfrey
- Institute of Developmental Sciences, Human Developmental and Health, Faculty of Medicine, University of Southampton, Southampton, UK
- National Institute for Health and Care Research, Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK
- Medical Research Council Lifecourse Epidemiology Centre, University of Southampton, Southampton, UK
| | - Takashi Nakagawa
- Department of Molecular and Medical Pharmacology, Faculty of Medicine, University of Toyama, Toyama, Japan
| | - Sofia Moco
- Nestlé Institute of Food Safety and Analytical Sciences, Nestlé Research, Lausanne, Switzerland
- Division of Molecular and Computational Toxicology, Department of Chemistry and Pharmaceutical Sciences, Amsterdam Institute for Molecular and Life Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
| | - René Koopman
- Centre for Muscle Research, Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Gordon S Lynch
- Centre for Muscle Research, Department of Anatomy and Physiology, University of Melbourne, Melbourne, Victoria, Australia
| | - Vincenzo Sorrentino
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland.
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
- Healthy Longevity Translational Research Programme, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore.
| | - Jerome N Feige
- Nestlé Institute of Health Sciences, Nestlé Research, Lausanne, Switzerland.
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
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Rovayo A, Toledo E, Razquin C. Lipidome and inflammation interplay: the role of diet in this relationship. Curr Opin Lipidol 2024; 35:20-24. [PMID: 37938937 DOI: 10.1097/mol.0000000000000909] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
PURPOSE OF REVIEW The aim of this review was to provide an overview of the role of novel lipid biomarkers from the circulating lipidome in inflammatory processes and the impact that dietary patterns may have on the lipidome. RECENT FINDINGS Inflammation is a process that underlies many acute and chronic diseases, contributing to their development and severity. Finding novel molecules which serve as biomarkers and which are involved in inflammation is very useful, since they offer us both preventive or therapeutic targets and reveal mechanisms of action. Recently, several studies have found circulating lipid molecules that are implicated in inflammatory processes of different diseases, such as cardiovascular diseases, type 2 diabetes, COVID-19 or other respiratory infectious diseases. As such, ceramides, triacylglicerides or lysophosphatidylcholines have been associated with inflammation in a different manner depending on the stage of inflammation. The study of dietary patterns, especially healthy ones as the Mediterranean or the Nordic diets, has shown the impact that dietary habits may have on the lipidomic profile of individuals. CONCLUSIONS Healthy dietary patterns have been suggested to exert beneficial effects in the circulating lipid profile. Studying the circulating lipidome could help to find new biomarkers of underlying inflammation, especially in cases of chronic low-grade inflammatory diseases in which it is more difficult to detect.
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Affiliation(s)
- Anacristina Rovayo
- IdiSNA, Pamplona
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona
| | - Estefanía Toledo
- IdiSNA, Pamplona
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
| | - Cristina Razquin
- IdiSNA, Pamplona
- Department of Preventive Medicine and Public Health, University of Navarra, Pamplona
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
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Kanaya AM. Diabetes in South Asians: Uncovering Novel Risk Factors With Longitudinal Epidemiologic Data: Kelly West Award Lecture 2023. Diabetes Care 2024; 47:7-16. [PMID: 38117990 PMCID: PMC10733655 DOI: 10.2337/dci23-0068] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/07/2023] [Accepted: 10/03/2023] [Indexed: 12/22/2023]
Abstract
South Asian populations have a higher prevalence and earlier age of onset of type 2 diabetes and atherosclerotic cardiovascular diseases than other race and ethnic groups. To better understand the pathophysiology and multilevel risk factors for diabetes and cardiovascular disease, we established the Mediators of Atherosclerosis in South Asians Living in America (MASALA) study in 2010. The original MASALA study cohort (n = 1,164) included 83% Asian Indian immigrants, with an ongoing expansion of the study to include individuals of Bangladeshi and Pakistani origin. We have found that South Asian Americans in the MASALA study had higher type 2 diabetes prevalence, lower insulin secretion, more insulin resistance, and an adverse body composition with higher liver and intermuscular fat and lower lean muscle mass compared with four other U.S. race and ethnic groups. MASALA study participants with diabetes were more likely to have the severe hyperglycemia subtype, characterized by β-cell dysfunction and lower body weight, and this subtype was associated with a higher incidence of subclinical atherosclerosis. We have found several modifiable factors for cardiometabolic disease among South Asians including diet and physical activity that can be influenced using specific social network members and with cultural adaptations to the U.S. context. Longitudinal data with repeat cardiometabolic measures that are supplemented with qualitative and mixed-method approaches enable a deeper understanding of disease risk and resilience factors. Studying and contrasting Asian American subgroups can uncover the causes for cardiometabolic disease heterogeneity and reveal novel methods for prevention and treatment.
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Affiliation(s)
- Alka M. Kanaya
- Division of General Internal Medicine, Departments of Medicine, Epidemiology, and Biostatistics, University of California, San Francisco, San Francisco, CA
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Rios S, García-Gavilán JF, Babio N, Paz-Graniel I, Ruiz-Canela M, Liang L, Clish CB, Toledo E, Corella D, Estruch R, Ros E, Fitó M, Arós F, Fiol M, Guasch-Ferré M, Santos-Lozano JM, Li J, Razquin C, Martínez-González MÁ, Hu FB, Salas-Salvadó J. Plasma metabolite profiles associated with the World Cancer Research Fund/American Institute for Cancer Research lifestyle score and future risk of cardiovascular disease and type 2 diabetes. Cardiovasc Diabetol 2023; 22:252. [PMID: 37716984 PMCID: PMC10505328 DOI: 10.1186/s12933-023-01912-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/24/2023] [Accepted: 07/01/2023] [Indexed: 09/18/2023] Open
Abstract
BACKGROUND A healthy lifestyle (HL) has been inversely related to type 2 diabetes (T2D) and cardiovascular disease (CVD). However, few studies have identified a metabolite profile associated with HL. The present study aims to identify a metabolite profile of a HL score and assess its association with the incidence of T2D and CVD in individuals at high cardiovascular risk. METHODS In a subset of 1833 participants (age 55-80y) of the PREDIMED study, we estimated adherence to a HL using a composite score based on the 2018 Word Cancer Research Fund/American Institute for Cancer Research recommendations. Plasma metabolites were analyzed using LC-MS/MS methods at baseline (discovery sample) and 1-year of follow-up (validation sample). Cross-sectional associations between 385 known metabolites and the HL score were assessed using elastic net regression. A 10-cross-validation procedure was used, and correlation coefficients or AUC were assessed between the identified metabolite profiles and the self-reported HL score. We estimated the associations between the identified metabolite profiles and T2D and CVD using multivariable Cox regression models. RESULTS The metabolite profiles that identified HL as a dichotomous or continuous variable included 24 and 58 metabolites, respectively. These are amino acids or derivatives, lipids, and energy intermediates or xenobiotic compounds. After adjustment for potential confounders, baseline metabolite profiles were associated with a lower risk of T2D (hazard ratio [HR] and 95% confidence interval (CI): 0.54, 0.38-0.77 for dichotomous HL, and 0.22, 0.11-0.43 for continuous HL). Similar results were observed with CVD (HR, 95% CI: 0.59, 0.42-0.83 for dichotomous HF and HR, 95%CI: 0.58, 0.31-1.07 for continuous HL). The reduction in the risk of T2D and CVD was maintained or attenuated, respectively, for the 1-year metabolomic profile. CONCLUSIONS In an elderly population at high risk of CVD, a set of metabolites was selected as potential metabolites associated with the HL pattern predicting the risk of T2D and, to a lesser extent, CVD. These results support previous findings that some of these metabolites are inversely associated with the risk of T2D and CVD. TRIAL REGISTRATION The PREDIMED trial was registered at ISRCTN ( http://www.isrctn.com/ , ISRCTN35739639).
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Affiliation(s)
- Santiago Rios
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Jesús F García-Gavilán
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
| | - Nancy Babio
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Indira Paz-Graniel
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain
| | - Miguel Ruiz-Canela
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - 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
| | - Clary B Clish
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Estefania Toledo
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Dolores Corella
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine, University of Valencia, Valencia, Spain
| | - Ramón Estruch
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Internal Medicine, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Emilio Ros
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Endocrinology and Nutrition, Lipid Clinic, Institut d'Investigacions Biomèdiques August Pi Sunyer (IDIBAPS), Hospital Clínic, Barcelona, Spain
| | - Montserrat Fitó
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Unit of Cardiovascular Risk and Nutrition, Institut Hospital del Mar de Investigaciones Médicas Municipal d'Investigació Médica (IMIM), Barcelona, Spain
| | - Fernando Arós
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Cardiology, Hospital Universitario de Álava, Vitoria, Spain
| | - Miquel Fiol
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Hospital Son Espases, Palma de Mallorca, Spain
| | - Marta Guasch-Ferré
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Public Health and Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - José M Santos-Lozano
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Research Unit, Department of Family Medicine, Distrito Sanitario Atención Primaria Sevilla, Sevilla, Spain
| | - Jun Li
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Health Research Institute of the Balearic Islands (IdISBa), Hospital Son Espases, Palma de Mallorca, Spain
| | - Cristina Razquin
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
| | - Miguel Ángel Martínez-González
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Navarra, IdiSNA, Pamplona, Spain
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Frank B Hu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jordi Salas-Salvadó
- Universitat Rovira i Virgili, Departament de Bioquímica i Biotecnologia, Alimentaciò, Nutrició Desenvolupament i Salut Mental ANUT-DSM, Reus, Spain.
- CIBER de Fisiopatología de la Obesidad y Nutrición, Instituto de Salud Carlos III, Madrid, Spain.
- Institut d'Investigació Sanitària Pere Virgili (IISPV), Reus, Spain.
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Bernard L, Chen J, Kim H, Wong KE, Steffen LM, Yu B, Boerwinkle E, Rebholz CM. Metabolomics of Dietary Intake of Total, Animal, and Plant Protein: Results from the Atherosclerosis Risk in Communities (ARIC) Study. Curr Dev Nutr 2023; 7:100067. [PMID: 37304852 PMCID: PMC10257224 DOI: 10.1016/j.cdnut.2023.100067] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/16/2023] [Accepted: 03/17/2023] [Indexed: 06/13/2023] Open
Abstract
Background Dietary consumption has traditionally been studied through food intake questionnaires. Metabolomics can be used to identify blood markers of dietary protein that may complement existing dietary assessment tools. Objectives We aimed to identify associations between 3 dietary protein sources (total protein, animal protein, and plant protein) and serum metabolites using data from the Atherosclerosis Risk in Communities Study. Methods Participants' dietary protein intake was derived from a food frequency questionnaire administered by an interviewer, and fasting serum samples were collected at study visit 1 (1987-1989). Untargeted metabolomic profiling was performed in 2 subgroups (subgroup 1: n = 1842; subgroup 2: n = 2072). Multivariable linear regression models were used to assess associations between 3 dietary protein sources and 360 metabolites, adjusting for demographic factors and other participant characteristics. Analyses were performed separately within each subgroup and meta-analyzed with fixed-effects models. Results In this study of 3914 middle-aged adults, the mean (SD) age was 54 (6) y, 60% were women, and 61% were Black. We identified 41 metabolites significantly associated with dietary protein intake. Twenty-six metabolite associations overlapped between total protein and animal protein, such as pyroglutamine, creatine, 3-methylhistidine, and 3-carboxy-4-methyl-5-propyl-2-furanpropanoic acid. Plant protein was uniquely associated with 11 metabolites, such as tryptophan betaine, 4-vinylphenol sulfate, N-δ-acetylornithine, and pipecolate. Conclusions The results of 17 of the 41 metabolites (41%) were consistent with those of previous nutritional metabolomic studies and specific protein-rich food items. We discovered 24 metabolites that had not been previously associated with dietary protein intake. These results enhance the validity of candidate markers of dietary protein intake and introduce novel metabolomic markers of dietary protein intake.
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Affiliation(s)
- Lauren Bernard
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Jingsha Chen
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Hyunju Kim
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Kari E. Wong
- Metabolon, Research Triangle Park, Morrisville, NC, USA
| | - Lyn M. Steffen
- Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - Eric Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
- Human Genome Sequencing Center, Baylor Colleague of Medicine, Houston, TX, USA
| | - Casey M. Rebholz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
- Division of Nephrology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
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