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Yu M, Song X, Guo J, Feng Q, Tian J. Exploring potential predictors of Henoch-Schönlein purpura nephritis: a pilot investigation on urinary metabolites. Eur J Pediatr 2024; 183:3117-3128. [PMID: 38668796 DOI: 10.1007/s00431-024-05573-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/09/2024] [Revised: 03/29/2024] [Accepted: 04/14/2024] [Indexed: 06/22/2024]
Abstract
Henoch-Schönlein purpura nephritis (HSPN) is the most severe manifestation of Henoch-Schönlein purpura (HSP). This study aimed to determine the role of urine metabolomics in predicting HSPN and explore the potential mechanisms of HSP. A liquid chromatography-tandem mass spectrometry-based untargeted metabolomics analysis was performed to investigate the urinary metabolic profiles of 90 participants, comprising 30 healthy children (group CON) and 60 patients with HSP, including 30 HSP patients without renal involvement (group H) and 30 HSPN patients (group HSPN). The differentially expressed metabolites (DEMs) were identified using orthogonal partial least squares discriminant analysis (OPLS-DA), and subsequent bioinformatics analysis was conducted to elucidate the perturbed metabolic pathways. A total of 43 DEMs between H and HSPN groups were analyzed by the Kyoto Encyclopedia of Gene and Genome (KEGG) database, and the result indicates that glycine, serine and threonine metabolism, and cysteine and methionine metabolism were significantly disturbed. A composite model incorporating propionylcarnitine and indophenol sulfate was developed to assess the risk of renal involvement in pediatric patients with HSP. Conclusion: This study reveals the metabolic alterations in healthy children, HSPN patients, and HSP patients without renal involvement. Furthermore, propionylcarnitine and indophenol sulfate may be potential predictive biomarkers of the occurrence of HSPN. What is Known: • HSP is the predominant type of vasculitis observed in children. The long-term prognosis of HSP is contingent upon the extent of renal impairment. In severe nephritis, a delay in appropriate treatment may lead to fibrosis progression and subsequent development of chronic kidney disease (CKD), even leading to renal failure. • The application of metabolomics in investigating diverse renal disorders has been documented. Urine is a robust and sensitive medium for metabolomics detection. What is New: • The metabolic profiles were identified in urine samples of healthy children and those with HSP at the early stage of the disease. Different metabolites were identified between HSP patients without nephritis and those who developed HSPN. • These different metabolites may affect oxidative stress in the progression of HSPN.
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Affiliation(s)
- Minyi Yu
- Department of Rheumatology, Children's Hospital of Soochow University, Suzhou, 215000, China
| | - Xiaoxiang Song
- Department of Rheumatology, Children's Hospital of Soochow University, Suzhou, 215000, China
| | - Jie Guo
- Department of Rheumatology, Children's Hospital of Soochow University, Suzhou, 215000, China
| | - Qihua Feng
- Department of Rheumatology, Children's Hospital of Soochow University, Suzhou, 215000, China
| | - Jianmei Tian
- Department of Infectious Diseases, Children's Hospital of Soochow University, Suzhou, 215000, China.
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Yagin FH, Al-Hashem F, Ahmad I, Ahmad F, Alkhateeb A. Pilot-Study to Explore Metabolic Signature of Type 2 Diabetes: A Pipeline of Tree-Based Machine Learning and Bioinformatics Techniques for Biomarkers Discovery. Nutrients 2024; 16:1537. [PMID: 38794775 PMCID: PMC11124278 DOI: 10.3390/nu16101537] [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: 03/24/2024] [Revised: 05/13/2024] [Accepted: 05/13/2024] [Indexed: 05/26/2024] Open
Abstract
BACKGROUND This study aims to identify unique metabolomics biomarkers associated with Type 2 Diabetes (T2D) and develop an accurate diagnostics model using tree-based machine learning (ML) algorithms integrated with bioinformatics techniques. METHODS Univariate and multivariate analyses such as fold change, a receiver operating characteristic curve (ROC), and Partial Least-Squares Discriminant Analysis (PLS-DA) were used to identify biomarker metabolites that showed significant concentration in T2D patients. Three tree-based algorithms [eXtreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Adaptive Boosting (AdaBoost)] that demonstrated robustness in high-dimensional data analysis were used to create a diagnostic model for T2D. RESULTS As a result of the biomarker discovery process validated with three different approaches, Pyruvate, D-Rhamnose, AMP, pipecolate, Tetradecenoic acid, Tetradecanoic acid, Dodecanediothioic acid, Prostaglandin E3/D3 (isobars), ADP and Hexadecenoic acid were determined as potential biomarkers for T2D. Our results showed that the XGBoost model [accuracy = 0.831, F1-score = 0.845, sensitivity = 0.882, specificity = 0.774, positive predictive value (PPV) = 0.811, negative-PV (NPV) = 0.857 and Area under the ROC curve (AUC) = 0.887] had the slight highest performance measures. CONCLUSIONS ML integrated with bioinformatics techniques offers accurate and positive T2D candidate biomarker discovery. The XGBoost model can successfully distinguish T2D based on metabolites.
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Affiliation(s)
- Fatma Hilal Yagin
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya 44280, Turkey
| | - Fahaid Al-Hashem
- Department of Physiology, College of Medicine, King Khalid University, Abha 61421, Saudi Arabia
| | - Irshad Ahmad
- Department of Medical Rehabilitation Sciences, College of Applied Medical Sciences, King Khalid University, Abha 61421, Saudi Arabia
| | - Fuzail Ahmad
- Department of Respiratory Care, College of Applied Sciences, Almaarefa University, Diriya, Riyadh 13713, Saudi Arabia
| | - Abedalrhman Alkhateeb
- Department of Computer Science, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
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Güil-Oumrait N, Stratakis N, Maitre L, Anguita-Ruiz A, Urquiza J, Fabbri L, Basagaña X, Heude B, Haug LS, Sakhi AK, Iszatt N, Keun HC, Wright J, Chatzi L, Vafeiadi M, Bustamante M, Grazuleviciene R, Andrušaitytė S, Slama R, McEachan R, Casas M, Vrijheid M. Prenatal Exposure to Chemical Mixtures and Metabolic Syndrome Risk in Children. JAMA Netw Open 2024; 7:e2412040. [PMID: 38780942 PMCID: PMC11117089 DOI: 10.1001/jamanetworkopen.2024.12040] [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] [Received: 11/13/2023] [Accepted: 02/21/2024] [Indexed: 05/25/2024] Open
Abstract
Importance Prenatal exposure to ubiquitous endocrine-disrupting chemicals (EDCs) may increase the risk of metabolic syndrome (MetS) in children, but few studies have studied chemical mixtures or explored underlying protein and metabolic signatures. Objective To investigate associations of prenatal exposure to EDC mixtures with MetS risk score in children and identify associated proteins and metabolites. Design, Setting, and Participants This population-based, birth cohort study used data collected between April 1, 2003, and February 26, 2016, from the Human Early Life Exposome cohort based in France, Greece, Lithuania, Norway, Spain, and the UK. Eligible participants included mother-child pairs with measured prenatal EDC exposures and complete data on childhood MetS risk factors, proteins, and metabolites. Data were analyzed between October 2022 and July 2023. Exposures Nine metals, 3 organochlorine pesticides, 5 polychlorinated biphenyls, 2 polybrominated diphenyl ethers (PBDEs), 5 perfluoroalkyl substances (PFAS), 10 phthalate metabolites, 3 phenols, 4 parabens, and 4 organophosphate pesticide metabolites measured in urine and blood samples collected during pregnancy. Main Outcomes and Measures At 6 to 11 years of age, a composite MetS risk score was constructed using z scores of waist circumference, systolic and diastolic blood pressures, triglycerides, high-density lipoprotein cholesterol, and insulin levels. Childhood levels of 44 urinary metabolites, 177 serum metabolites, and 35 plasma proteins were quantified using targeted methods. Associations were assessed using bayesian weighted quantile sum regressions applied to mixtures for each chemical group. Results The study included 1134 mothers (mean [SD] age at birth, 30.7 [4.9] years) and their children (mean [SD] age, 7.8 [1.5] years; 617 male children [54.4%] and 517 female children [45.6%]; mean [SD] MetS risk score, -0.1 [2.3]). MetS score increased per 1-quartile increase of the mixture for metals (β = 0.44; 95% credible interval [CrI], 0.30 to 0.59), organochlorine pesticides (β = 0.22; 95% CrI, 0.15 to 0.29), PBDEs (β = 0.17; 95% CrI, 0.06 to 0.27), and PFAS (β = 0.19; 95% CrI, 0.14 to 0.24). High-molecular weight phthalate mixtures (β = -0.07; 95% CrI, -0.10 to -0.04) and low-molecular weight phthalate mixtures (β = -0.13; 95% CrI, -0.18 to -0.08) were associated with a decreased MetS score. Most EDC mixtures were associated with elevated proinflammatory proteins, amino acids, and altered glycerophospholipids, which in turn were associated with increased MetS score. Conclusions and Relevance This cohort study suggests that prenatal exposure to EDC mixtures may be associated with adverse metabolic health in children. Given the pervasive nature of EDCs and the increase in MetS, these findings hold substantial public health implications.
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Affiliation(s)
- Nuria Güil-Oumrait
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Nikos Stratakis
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Léa Maitre
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Augusto Anguita-Ruiz
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Jose Urquiza
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Lorenzo Fabbri
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Xavier Basagaña
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Barbara Heude
- Université Paris Cité and Université Sorbonne Paris Nord, National Institute of Health and Medical Research (INSERM), National Institute for Agriculture, Food and the Environment (INRAE), Center for Research in Epidemiology and StatisticS (CRESS), Paris, France
| | - Line Småstuen Haug
- Department of Food Safety, Norwegian Institute of Public Health, Oslo, Norway
| | - Amrit Kaur Sakhi
- Department of Food Safety, Norwegian Institute of Public Health, Oslo, Norway
| | - Nina Iszatt
- Division of Climate and Environmental Health, Norwegian Institute of Public Health, Oslo, Norway
| | - Hector C. Keun
- Cancer Metabolism & Systems Toxicology Group, Imperial College London, Hammersmith Hospital Campus, London, United Kingdom
| | - John Wright
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service Foundation Trust, Bradford, United Kingdom
| | - Leda Chatzi
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles
| | - Marina Vafeiadi
- Department of Social Medicine, University of Crete, Heraklion, Crete, Greece
| | - Mariona Bustamante
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | | | - Sandra Andrušaitytė
- Department of Environmental Sciences, Vytautas Magnus University, Kaunas, Lithuania
| | - Rémy Slama
- Department of Prevention and Treatment of Chronic Diseases, Institute for Advanced Biosciences (IAB; INSERM U1209, CNRS UMR 5309), Université Grenoble Alpes, Grenoble, France
| | - Rosemary McEachan
- Bradford Institute for Health Research, Bradford Teaching Hospitals National Health Service Foundation Trust, Bradford, United Kingdom
| | - Maribel Casas
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Martine Vrijheid
- Barcelona Institute for Global Health (ISGlobal), Barcelona, Spain
- Pompeu Fabra University, Barcelona, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
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Menaker Y, van den Munckhof I, Scarpa A, Placek K, Brandes-Leibovitz R, Glantzspiegel Y, Joosten LAB, Rutten JHW, Netea MG, Gat-Viks I, Riksen NP. Stratification of Atherosclerosis based on Plasma Metabolic States. J Clin Endocrinol Metab 2024; 109:1250-1262. [PMID: 38044551 DOI: 10.1210/clinem/dgad672] [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: 06/29/2023] [Indexed: 12/05/2023]
Abstract
CONTEXT Atherosclerosis is a dominant cause of cardiovascular disease (CVD), including myocardial infarction and stroke. OBJECTIVE To investigate metabolic states that are associated with the development of atherosclerosis. METHODS Cross-sectional cohort study at a university hospital in the Netherlands. A total of 302 adult subjects with a body mass index (BMI) ≥ 27 kg/m2 were included. We integrated plasma metabolomics with clinical metadata to quantify the "atherogenic state" of each individual, providing a continuous spectrum of atherogenic states that ranges between nonatherogenic states to highly atherogenic states. RESULTS Analysis of groups of individuals with different clinical conditions-such as metabolically healthy individuals with obesity, and individuals with metabolic syndrome-confirmed the generalizability of this spectrum; revealed a wide variation of atherogenic states within each condition; and allowed identification of metabolites that are associated with the atherogenic state regardless of the particular condition, such as gamma-glutamyl-glutamic acid and homovanillic acid sulfate. The analysis further highlighted metabolic pathways such as catabolism of phenylalanine and tyrosine and biosynthesis of estrogens and phenylpropanoids. Using validation cohorts, we confirmed variation in atherogenic states in healthy subjects (before atherosclerosis plaques become visible), and showed that metabolites associated with the atherogenic state were also associated with future CVD. CONCLUSION Our results provide a global view of atherosclerosis risk states using plasma metabolomics.
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Affiliation(s)
- Yuval Menaker
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Inge van den Munckhof
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Alice Scarpa
- Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Katarzyna Placek
- Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Rachel Brandes-Leibovitz
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Yossef Glantzspiegel
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Leo A B Joosten
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Department of Medical Genetics, Iuliu Hatieganu University of Medicine and Pharmacy, 400000 Cluj-Napoca, Romania
| | - Joost H W Rutten
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
| | - Mihai G Netea
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
- Department of Immunology and Metabolism, Life and Medical Sciences Institute, University of Bonn, 53115 Bonn, Germany
| | - Irit Gat-Viks
- The Shmunis School of Biomedicine and Cancer Research, George S. Wise Faculty of Life Sciences, Tel Aviv University, Tel Aviv 6997801, Israel
| | - Niels P Riksen
- Department of Internal Medicine, Radboud University Medical Center, 6525 GA Nijmegen, The Netherlands
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Chen J, Qin Y, Li Z, Shan A, Ma Q. Aromatic Amino Acids Promote Lipid Metabolism Disorders by Increasing Hepatic Bile Acid Synthesis. J Nutr 2024; 154:1321-1332. [PMID: 38582699 DOI: 10.1016/j.tjnut.2023.12.047] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2023] [Revised: 12/11/2023] [Accepted: 12/27/2023] [Indexed: 04/08/2024] Open
Abstract
BACKGROUND Obesity is a progressive metabolic disease that begins with lipid metabolism disorders. Aromatic amino acids (AAAs), including tryptophan, phenylalanine, and tyrosine, have diverse biological activities as nutrients. However, the underlying mechanisms by which AAAs affect lipid metabolism are unclear. OBJECTIVES This study was designed to investigate the possible roles and underlying molecular mechanisms of AAA in the pathogenesis of lipid metabolism disorders. METHODS We added an AAA mixture to the high-fat diet (HFD) of mice. Glucose tolerance test was recorded. Protein expression of hepatic bile acid (BA) synthase and mRNA expression of BA metabolism-related genes were determined. Hepatic BA profiles and gut microbial were also determined in mice. RESULTS The results showed that AAA significantly increased body weight and white adipose tissue, aggravated liver injury, impaired glucose tolerance and intestinal integrity, and significantly increased hepatic BA synthesis by inhibiting intestinal farnesoid X receptor (FXR). Moreover, AAA increased the content of total BA in the liver and altered the hepatic BA profile, with elevated levels of lithocholic acid, glycochenodeoxycholic acid, and glycoursodeoxycholic acid. AAA markedly increased the levels of proteins involved in BA synthesis (cholesterol 7α-hydroxylase and oxysterol 7α-hydroxylase) and inhibited the intestinal FXR. Gut microbial composition also changed, reducing the abundance of some beneficial bacteria, such as Parvibacter and Lactobacillus. CONCLUSIONS Under HFD conditions, AAAs stimulate BA synthesis in both the classical and alternative pathways, leading to aggravation of liver injury and fat deposition. Excessive intake of AAA disrupts BA metabolism and contributes to the development of lipid metabolism disorders, suggesting that AAA may be a causative agent of lipid metabolism disorders.
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Affiliation(s)
- Jiayi Chen
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Yingjie Qin
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Zhongyu Li
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Anshan Shan
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China
| | - Qingquan Ma
- College of Animal Science and Technology, Northeast Agricultural University, Harbin, China.
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Burton MA, Antoun E, Garratt ES, Westbury L, Dennison EM, Harvey NC, Cooper C, Patel HP, Godfrey KM, Lillycrop KA. The serum small non-coding RNA (SncRNA) landscape as a molecular biomarker of age associated muscle dysregulation and insulin resistance in older adults. FASEB J 2024; 38:e23423. [PMID: 38294260 PMCID: PMC10952661 DOI: 10.1096/fj.202301089rr] [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: 06/01/2023] [Revised: 12/08/2023] [Accepted: 12/29/2023] [Indexed: 02/01/2024]
Abstract
Small noncoding RNAs (sncRNAs) are implicated in age-associated pathologies, including sarcopenia and insulin resistance (IR). As potential circulating biomarkers, most studies have focussed on microRNAs (miRNAs), one class of sncRNA. This study characterized the wider circulating sncRNA transcriptome of older individuals and associations with sarcopenia and IR. sncRNA expression including miRNAs, transfer RNAs (tRNAs), tRNA-associated fragments (tRFs), and piwi-interacting RNAs (piRNAs) was measured in serum from 21 healthy and 21 sarcopenic Hertfordshire Sarcopenia Study extension women matched for age (mean 78.9 years) and HOMA2-IR. Associations with age, sarcopenia and HOMA2-IR were examined and predicted gene targets and biological pathways characterized. Of the total sncRNA among healthy controls, piRNAs were most abundant (85.3%), followed by tRNAs (4.1%), miRNAs (2.7%), and tRFs (0.5%). Age was associated (FDR < 0.05) with 2 miRNAs, 58 tRNAs, and 14 tRFs, with chromatin organization, WNT signaling, and response to stress enriched among gene targets. Sarcopenia was nominally associated (p < .05) with 12 tRNAs, 3 tRFs, and 6 piRNAs, with target genes linked to cell proliferation and differentiation such as Notch Receptor 1 (NOTCH1), DISC1 scaffold protein (DISC1), and GLI family zinc finger-2 (GLI2). HOMA2-IR was nominally associated (p<0.05) with 6 miRNAs, 9 tRNAs, 1 tRF, and 19 piRNAs, linked with lysine degradation, circadian rhythm, and fatty acid biosynthesis pathways. These findings identify changes in circulating sncRNA expression in human serum associated with chronological age, sarcopenia, and IR. These may have clinical utility as circulating biomarkers of ageing and age-associated pathologies and provide novel targets for therapeutic intervention.
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Affiliation(s)
- Mark A. Burton
- Human Development and Health Academic Unit, Faculty of MedicineUniversity of SouthamptonSouthamptonUK
| | - Elie Antoun
- Human Development and Health Academic Unit, Faculty of MedicineUniversity of SouthamptonSouthamptonUK
| | - Emma S. Garratt
- Human Development and Health Academic Unit, Faculty of MedicineUniversity of SouthamptonSouthamptonUK
- NIHR Southampton Biomedical Research CentreUniversity of Southampton and University Hospital Southampton NHS Foundation TrustSouthamptonUK
| | - Leo Westbury
- MRC Lifecourse Epidemiology CentreUniversity of SouthamptonSouthamptonUK
| | - Elaine M. Dennison
- MRC Lifecourse Epidemiology CentreUniversity of SouthamptonSouthamptonUK
- Victoria University of WellingtonWellingtonNew Zealand
| | - Nicholas C. Harvey
- NIHR Southampton Biomedical Research CentreUniversity of Southampton and University Hospital Southampton NHS Foundation TrustSouthamptonUK
- MRC Lifecourse Epidemiology CentreUniversity of SouthamptonSouthamptonUK
| | - Cyrus Cooper
- NIHR Southampton Biomedical Research CentreUniversity of Southampton and University Hospital Southampton NHS Foundation TrustSouthamptonUK
- MRC Lifecourse Epidemiology CentreUniversity of SouthamptonSouthamptonUK
| | - Harnish P. Patel
- NIHR Southampton Biomedical Research CentreUniversity of Southampton and University Hospital Southampton NHS Foundation TrustSouthamptonUK
- MRC Lifecourse Epidemiology CentreUniversity of SouthamptonSouthamptonUK
- Academic Geriatric Medicine, Faculty of MedicineUniversity of SouthamptonSouthamptonUK
| | - Keith M. Godfrey
- Human Development and Health Academic Unit, Faculty of MedicineUniversity of SouthamptonSouthamptonUK
- NIHR Southampton Biomedical Research CentreUniversity of Southampton and University Hospital Southampton NHS Foundation TrustSouthamptonUK
- MRC Lifecourse Epidemiology CentreUniversity of SouthamptonSouthamptonUK
| | - Karen A. Lillycrop
- Human Development and Health Academic Unit, Faculty of MedicineUniversity of SouthamptonSouthamptonUK
- NIHR Southampton Biomedical Research CentreUniversity of Southampton and University Hospital Southampton NHS Foundation TrustSouthamptonUK
- Biological SciencesUniversity of SouthamptonSouthamptonUK
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Gordon S, Lee JS, Scott TM, Bhupathiraju S, Ordovas J, Kelly RS, Bhadelia R, Koo BB, Bigornia S, Tucker KL, Palacios N. Metabolites and MRI-Derived Markers of AD/ADRD Risk in a Puerto Rican Cohort. RESEARCH SQUARE 2024:rs.3.rs-3941791. [PMID: 38410484 PMCID: PMC10896402 DOI: 10.21203/rs.3.rs-3941791/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/28/2024]
Abstract
Objective Several studies have examined metabolomic profiles in relation to Alzheimer's disease and related dementia (AD/ADRD) risk; however, few studies have focused on minorities, such as Latinos, or examined Magnetic-Resonance Imaging (MRI)-based outcomes. Methods We used multiple linear regression, adjusted for covariates, to examine the association between metabolite concentration and MRI-derived brain age deviation. Metabolites were measured at baseline with untargeted metabolomic profiling (Metabolon, Inc). Brain age deviation (BAD) was calculated at wave 4 (~ 9 years from Boston Puerto Rican Health Study (BPRHS) baseline) as chronologic age, minus MRI-estimated brain age, representing the rate of biological brain aging relative to chronologic age. We also examined if metabolites associated with BAD were similarly associated with hippocampal volume and global cognitive function at wave 4 in the BPRHS. Results Several metabolites, including isobutyrylcarnitine, propionylcarnitine, phenylacetylglutamine, phenylacetylcarnitine (acetylated peptides), p-cresol-glucuronide, phenylacetylglutamate, and trimethylamine N-oxide (TMAO) were inversely associated with brain age deviation. Taurocholate sulfate, a bile salt, was marginally associated with better brain aging. Most metabolites with negative associations with brain age deviation scores also were inversely associations with hippocampal volumes and wave 4 cognitive function. Conclusion The metabolites identifiedin this study are generally consistent with prior literature and highlight the role of BCAA, TMAO and microbially derived metabolites in cognitive decline.
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Aggarwal H, Gautam J, Kumari D, Gupta SK, Bajpai S, Chaturvedi K, Kumar Y, Dikshit M. Comparative profiling of gut microbiota and metabolome in diet-induced obese and insulin-resistant C57BL/6J mice. BIOCHIMICA ET BIOPHYSICA ACTA. MOLECULAR CELL RESEARCH 2024; 1871:119643. [PMID: 37996062 DOI: 10.1016/j.bbamcr.2023.119643] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/19/2023] [Revised: 10/28/2023] [Accepted: 11/10/2023] [Indexed: 11/25/2023]
Abstract
Diet-based models are commonly used to investigate obesity and related disorders. We conducted a comparative profiling of three obesogenic diets HFD, high fat diet; HFHF, high fat high fructose diet; and HFCD, high fat choline deficient diet to assess their impact on the gut microbiome and metabolome. After 20 weeks, we analyzed the gut microbiota and metabolomes of liver, plasma, cecal, and fecal samples. Fecal and plasma bile acids (BAs) and fecal short-chain fatty acids (SCFAs) were also examined. Significant changes were observed in fecal and cecal metabolites, with increased Firmicutes and decreased Bacteroidetes in the HFD, HFHF, and HFCD-fed mice compared to chow and LFD (low fat diet)-fed mice. Most BAs were reduced in plasma and fecal samples of obese groups, except taurocholic acid, which increased in HFCD mice's plasma. SCFAs like acetate and butyrate significantly decreased in obesogenic diet groups, while propionic acid specifically decreased in the HFCD group. Pathway analysis revealed significant alterations in amino acid, carbohydrate metabolism, and nucleic acid biosynthesis pathways in obese mice. Surprisingly, even LFD-fed mice showed distinct changes in microbiome and metabolite profiles compared to the chow group. This study provides insights into gut microbiome dysbiosis and metabolite alterations induced by obesogenic and LFD diets in various tissues. These findings aid in selecting suitable diet models to study the role of the gut microbiome and metabolites in obesity and associated disorders, with potential implications for understanding similar pathologies in humans.
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Affiliation(s)
- Hobby Aggarwal
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Jyoti Gautam
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Deepika Kumari
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Sonu Kumar Gupta
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Sneh Bajpai
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Kartikey Chaturvedi
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India
| | - Yashwant Kumar
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India.
| | - Madhu Dikshit
- Non-communicable Disease Centre, Translational Health Science and Technology Institute (THSTI), NCR Biotech Science Cluster, 3rd Milestone, Faridabad 121001, Haryana, India.
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Xiang X, You S, Zeng Z, Xu J, Lin Y, Liu Y, Zhang L, Huang R, Song C, Jin S. Exploration of the hypoglycemic mechanism of Fuzhuan brick tea based on integrating global metabolomics and network pharmacology analysis. Front Mol Biosci 2024; 10:1266156. [PMID: 38304230 PMCID: PMC10830801 DOI: 10.3389/fmolb.2023.1266156] [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: 07/24/2023] [Accepted: 12/26/2023] [Indexed: 02/03/2024] Open
Abstract
Introduction: Fuzhuan brick tea (FBT) is a worldwide popular beverage which has the appreciable potential in regulating glycometabolism. However, the reports on the hypoglycemic mechanism of FBT remain limited. Methods: In this study, the hypoglycemic effect of FBT was evaluated in a pharmacological experiment based on Kunming mice. Global metabolomics and network pharmacology were combined to discover the potential target metabolites and genes. In addition, the real-time quantitative polymerase chain reaction (RT-qPCR) analysis was performed for verification. Results: Seven potential target metabolites and six potential target genes were screened using the integrated approach. After RT-qPCR analysis, it was found that the mRNA expression of VEGFA, KDR, MAPK14, and PPARA showed significant differences between normal and diabetes mellitus mice, with a retracement after FBT treatment. Conclusion: These results indicated that the hypoglycemic effect of FBT was associated with its anti-inflammatory activities and regulation of lipid metabolism disorders. The exploration of the hypoglycemic mechanism of FBT would be meaningful for its further application and development.
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Affiliation(s)
- Xingliang Xiang
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
- School of Life and Health Sciences, Hainan University, Haikou, Hainan, China
| | - Shanqin You
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Zhaoxiang Zeng
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Jinlin Xu
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
- Department of Pharmacy, Ezhou Central Hospital, Ezhou, Hubei, China
| | - Yuqi Lin
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Yukun Liu
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Lijun Zhang
- School of Basic Medical Sciences, Hubei University of Chinese Medicine, Wuhan, Hubei, China
| | - Rongzeng Huang
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
- Hubei Shizhen Laboratory, Wuhan, Hubei, China
| | - Chengwu Song
- School of Pharmacy, Hubei University of Chinese Medicine, Wuhan, Hubei, China
- Hubei Shizhen Laboratory, Wuhan, Hubei, China
| | - Shuna Jin
- School of Basic Medical Sciences, Hubei University of Chinese Medicine, Wuhan, Hubei, China
- Hubei Shizhen Laboratory, Wuhan, Hubei, China
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10
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Jiang H, Han TL, Yang J, Yang Y, Wang F, Chen Y, Huang N, Mansell T, Craig JM, Scurrah KJ, Novakovic B, Baker PN, Zhang H, Wei Y, Wang L, Saffery R. Evidence for ethnicity and location as regulators of the newborn blood metabolome: a monozygous twin study. Front Nutr 2024; 10:1259777. [PMID: 38239842 PMCID: PMC10794553 DOI: 10.3389/fnut.2023.1259777] [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: 07/16/2023] [Accepted: 12/07/2023] [Indexed: 01/22/2024] Open
Abstract
Introduction Monochorionic, diamniotic (MCDA) monozygotic twins share nearly all genetic variation and a common placenta in utero. Despite this, MCDA twins are often discordant for a range of common phenotypes, including early growth and birth weight. As such, MCDA twins represent a unique model to explore variation in early growth attributable primarily to in utero environmental factors. Methods MCDA twins with a range of within-pair birth weight discordance were sampled from the peri/postnatal epigenetic twin study (PETS, Melbourne; n = 26 pairs), Beijing twin study (BTS, Beijing; n = 25), and the Chongqing longitudinal twin study (LoTiS, Chongqing; n = 22). All PETS participants were of European-Australian ancestry, while all Chinese participants had Han ancestry. The average of the birth weight difference between the larger and smaller co-twins for all twin pairs was determined and metabolomic profiles of amino acids, TCA cycle intermediates, fatty acids, organic acids, and their derivatives generated from cord blood plasma by gas chromatograph mass spectrometry. Within and between co-twin pair analyses were performed to identify metabolites specifically associated with discordance in birth weight. Multivariable regression and pathway enrichment analyses between different regions were performed to evaluate the geographical effects on the metabolism of MCDA twin pairs. Results PETS twins showed a markedly different metabolic profile at birth compared to the two Chinese samples. Within-pair analysis revealed an association of glutathione, creatinine, and levulinic acid with birth weight discordance. Caffeine, phenylalanine, and several saturated fatty acid levels were uniquely elevated in PETS twins and were associated with maternal BMI and average within pair birth weight, in addition to birth weight discordance. LoTiS twins had higher levels of glutathione, tyrosine, and gamma-linolenic acid relative to PETS and BTS twins, potentially associated with eating habits. Conclusion This study highlights the potential role of underlying genetic variation (shared by MZ twins), in utero (non-shared by MZ twins) and location-specific (shared by MZ twins) environmental factors, in regulating the cord blood metabolome of uncomplicated MCDA twins. Future research is needed to unravel these complex relationships that may play a key role in phenotypic metabolic alterations of twins independent of genetic diversity.
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Affiliation(s)
- Huimin Jiang
- Department of Reproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Ting-Li Han
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Jing Yang
- Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
| | - Yang Yang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
- Mass Spectrometry Centre of Maternal-Fetal Medicine, Life Science Institution, Chongqing Medical University, Chongqing, China
| | - Fengdi Wang
- Department of Reproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yuelu Chen
- Department of Reproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Nana Huang
- Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
| | - Toby Mansell
- Murdoch Children’s Research Institute, and Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Jeffrey M. Craig
- Murdoch Children’s Research Institute, and Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
- The Institute for Mental and Physical Health and Clinical Translation (IMPACT), School of Medicine, Deakin University, Melbourne, VIC, Australia
| | - Katrina J. Scurrah
- Twins Research Australia and Centre for Mental Health, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Boris Novakovic
- Murdoch Children’s Research Institute, and Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
| | - Philip N. Baker
- College of Life Sciences, University of Leicester, Leicester, United Kingdom
| | - Hua Zhang
- Department of Obstetrics and Gynecology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
- Chongqing Key Laboratory of Maternal and Fetal Medicine, Chongqing Medical University, Chongqing, China
| | - Yuan Wei
- Department of Obstetrics and Gynecology, Peking University Third Hospital, Beijing, China
| | - Lianlian Wang
- Department of Reproductive Medicine Center, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Richard Saffery
- Murdoch Children’s Research Institute, and Department of Paediatrics, University of Melbourne, Parkville, VIC, Australia
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11
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Singh S, Sarma DK, Verma V, Nagpal R, Kumar M. Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders. Biochem Biophys Res Commun 2023; 682:1-20. [PMID: 37788525 DOI: 10.1016/j.bbrc.2023.09.064] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/13/2023] [Accepted: 09/21/2023] [Indexed: 10/05/2023]
Abstract
Metabolic disorders are increasingly prevalent worldwide, leading to high rates of morbidity and mortality. The variety of metabolic illnesses can be addressed through personalized medicine. The goal of personalized medicine is to give doctors the ability to anticipate the best course of treatment for patients with metabolic problems. By analyzing a patient's metabolomic, proteomic, genetic profile, and clinical data, physicians can identify relevant diagnostic, and predictive biomarkers and develop treatment plans and therapy for acute and chronic metabolic diseases. To achieve this goal, real-time modeling of clinical data and multiple omics is essential to pinpoint underlying biological mechanisms, risk factors, and possibly useful data to promote early diagnosis and prevention of complex diseases. Incorporating cutting-edge technologies like artificial intelligence and machine learning is crucial for consolidating diverse forms of data, examining multiple variables, establishing databases of clinical indicators to aid decision-making, and formulating ethical protocols to address concerns. This review article aims to explore the potential of personalized medicine utilizing omics approaches for the treatment of metabolic disorders. It focuses on the recent advancements in genomics, epigenomics, proteomics, metabolomics, and nutrigenomics, emphasizing their role in revolutionizing personalized medicine.
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Affiliation(s)
- Samradhi Singh
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India
| | - Devojit Kumar Sarma
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India
| | - Vinod Verma
- Stem Cell Research Centre, Department of Hematology, Sanjay Gandhi Post-Graduate Institute of Medical Sciences, Lucknow, 226014, Uttar Pradesh, India
| | - Ravinder Nagpal
- Department of Nutrition and Integrative Physiology, College of Health and Human Sciences, Florida State University, Tallahassee, FL, 32306, USA
| | - Manoj Kumar
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India.
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12
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Li J, Xiong M, Fu XH, Fan Y, Dong C, Sun X, Zheng F, Wang SW, Liu L, Xu M, Wang C, Ping J, Che S, Wang Q, Yang K, Zuo Y, Lu X, Zheng Z, Lan T, Wang S, Ma S, Sun S, Zhang B, Chen CS, Cheng KY, Ye J, Qu J, Xue Y, Yang YG, Zhang F, Zhang W, Liu GH. Determining a multimodal aging clock in a cohort of Chinese women. MED 2023; 4:825-848.e13. [PMID: 37516104 DOI: 10.1016/j.medj.2023.06.010] [Citation(s) in RCA: 10] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/25/2023] [Accepted: 06/30/2023] [Indexed: 07/31/2023]
Abstract
BACKGROUND Translating aging rejuvenation strategies into clinical practice has the potential to address the unmet needs of the global aging population. However, to successfully do so requires precise quantification of aging and its reversal in a way that encompasses the complexity and variation of aging. METHODS Here, in a cohort of 113 healthy women, tiled in age from young to old, we identified a repertoire of known and previously unknown markers associated with age based on multimodal measurements, including transcripts, proteins, metabolites, microbes, and clinical laboratory values, based on which an integrative aging clock and a suite of customized aging clocks were developed. FINDINGS A unified analysis of aging-associated traits defined four aging modalities with distinct biological functions (chronic inflammation, lipid metabolism, hormone regulation, and tissue fitness), and depicted waves of changes in distinct biological pathways peak around the third and fifth decades of life. We also demonstrated that the developed aging clocks could measure biological age and assess partial aging deceleration by hormone replacement therapy, a prevalent treatment designed to correct hormonal imbalances. CONCLUSIONS We established aging metrics that capture systemic physiological dysregulation, a valuable framework for monitoring the aging process and informing clinical development of aging rejuvenation strategies. FUNDING This work was supported by the National Natural Science Foundation of China (32121001), the National Key Research and Development Program of China (2022YFA1103700 and 2020YFA0804000), the National Natural Science Foundation of China (81502304), and the Quzhou Technology Projects (2022K46).
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Affiliation(s)
- Jiaming Li
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Muzhao Xiong
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Xiang-Hong Fu
- Center for Reproductive Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China; Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Yanling Fan
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Chen Dong
- State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Xiaoyan Sun
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Fang Zheng
- Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Si-Wei Wang
- Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Lixiao Liu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Ming Xu
- State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China
| | - Cui Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Jiale Ping
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Shanshan Che
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Qiaoran Wang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Kuan Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Yuesheng Zuo
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Xiaoyong Lu
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Zikai Zheng
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Tian Lan
- Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Si Wang
- Aging Biomarker Consortium, Beijing 100101, China; Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China
| | - Shuai Ma
- Aging Biomarker Consortium, Beijing 100101, China; State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Shuhui Sun
- State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Bin Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Chen-Shui Chen
- Department of Respiratory and Critical Care Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China; Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Ke-Yun Cheng
- Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Jinlin Ye
- Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China
| | - Jing Qu
- Aging Biomarker Consortium, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China; State Key Laboratory of Stem Cell and Reproductive Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China
| | - Yongbiao Xue
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China
| | - Yun-Gui Yang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China.
| | - Feng Zhang
- Center for Reproductive Medicine, Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China; The Joint Innovation Center for Engineering in Medicine, Quzhou People's Hospital, Quzhou 324000, China; Quzhou Affiliated Hospital of Wenzhou Medical University, Quzhou People's Hospital, Quzhou 324000, China.
| | - Weiqi Zhang
- CAS Key Laboratory of Genomic and Precision Medicine, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China; Aging Biomarker Consortium, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China.
| | - Guang-Hui Liu
- Aging Biomarker Consortium, Beijing 100101, China; State Key Laboratory of Membrane Biology, Institute of Zoology, Chinese Academy of Sciences, Beijing 100101, China; University of the Chinese Academy of Sciences, Beijing 100049, China; Institute for Stem Cell and Regeneration, CAS, Beijing 100101, China; Beijing Institute for Stem Cell and Regenerative Medicine, Beijing 100101, China; Advanced Innovation Center for Human Brain Protection and National Clinical Research Center for Geriatric Disorders, Xuanwu Hospital, Capital Medical University, Beijing 100053, China; Aging Translational Medicine Center, International Center for Aging and Cancer, Beijing Municipal Geriatric Medical Research Center, Xuanwu Hospital, Capital Medical University, Beijing 100053, China.
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13
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Jeziorny K, Pietrowska K, Sieminska J, Zmyslowska-Polakowska E, Kretowski A, Ciborowski M, Zmyslowska A. Serum metabolomics identified specific lipid compounds which may serve as markers of disease progression in patients with Alström and Bardet-Biedl syndromes. Front Mol Biosci 2023; 10:1251905. [PMID: 38028552 PMCID: PMC10657895 DOI: 10.3389/fmolb.2023.1251905] [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: 07/02/2023] [Accepted: 10/20/2023] [Indexed: 12/01/2023] Open
Abstract
Objectives: Alström syndrome (ALMS) and Bardet-Biedl syndrome (BBS) are among the so-called ciliopathies and are associated with the development of multiple systemic abnormalities, including early childhood obesity and progressive neurodegeneration. Given the progressive deterioration of patients' quality of life, in the absence of defined causal treatment, it seems reasonable to identify the metabolic background of these diseases and search for their progression markers. The aim of this study was to find metabolites characteristic to ALMS and BBS, correlating with clinical course parameters, and related to the diseases progression. Methods: Untargeted metabolomics of serum samples obtained from ALMS and BBS patients (study group; n = 21) and obese/healthy participants (control group; each of 35 participants; n = 70) was performed using LC-QTOF-MS method at the study onset and after 4 years of follow-up. Results: Significant differences in such metabolites as valine, acylcarnitines, sphingomyelins, phosphatidylethanolamines, phosphatidylcholines, as well as lysophosphatidylethanolamines and lysophosphatidylcholines were observed when the study group was compared to both control groups. After a follow-up of the study group, mainly changes in the levels of lysophospholipids and phospholipids (including oxidized phospholipids) were noted. In addition, in case of ALMS/BBS patients, correlations were observed between selected phospholipids and glucose metabolism parameters. We also found correlations of several LPEs with patients' age (p < 0.05), but the level of only one of them (hexacosanoic acid) correlated negatively with age in the ALMS/BBS group, but positively in the other groups. Conclusion: Patients with ALMS/BBS have altered lipid metabolism compared to controls or obese subjects. As the disease progresses, they show elevated levels of lipid oxidation products, which may suggest increased oxidative stress. Selected lipid metabolites may be considered as potential markers of progression of ALMS and BBS syndromes.
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Affiliation(s)
- Krzysztof Jeziorny
- Department of Endocrinology and Metabolic Diseases, Polish Mother’s Memorial Hospital–Research Institute, Lodz, Poland
- Department of Paediatric Endocrinology, Medical University of Lodz, Lodz, Poland
| | - Karolina Pietrowska
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Julia Sieminska
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | | | - Adam Kretowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
| | - Michal Ciborowski
- Clinical Research Centre, Medical University of Bialystok, Bialystok, Poland
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14
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Lee YH, Park S. Genetic and Lifestyle-Related Factors Influencing Serum Hyper-Propionylcarnitine Concentrations and Their Association with Metabolic Syndrome and Cardiovascular Disease Risk. Int J Mol Sci 2023; 24:15810. [PMID: 37958793 PMCID: PMC10647558 DOI: 10.3390/ijms242115810] [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: 09/27/2023] [Revised: 10/27/2023] [Accepted: 10/27/2023] [Indexed: 11/15/2023] Open
Abstract
The genetic and environmental determinants of serum propionylcarnitine concentrations (PC) remain largely unexplored. This study investigated the impact of genetic and environmental factors on serum propionylcarnitine levels in middle-aged and elderly participants from the Ansan/Ansung cohort of the Korean Genome and Epidemiology Study. Our goal was to understand the role of PC on the risk of metabolic syndrome (MetS) leading to cardiovascular disease, particularly concerning branched-chain amino acid (BCAA) metabolism. We analyzed participants' demographic, lifestyle, and biochemical data with and without MetS. Serum metabolite concentrations, including carnitine, acylcarnitine, and amino acid concentrations, were measured, and the components of MetS were evaluated. Genetic variants associated with low and high PC were selected using genome-wide association studies after adjusting for MetS-related parameters. Further, genetic variants and lifestyle factors that interacted with the polygenic risk score (PRS) were analyzed. Participants with MetS were older and less educated, and their alcohol intake was higher than non-MetS participants. PC was significantly associated with the MetS risk and increased the serum levels of BCAAs and other amino acids. Higher PC positively correlated with MetS components, insulin resistance, and cardiovascular risk factors. Intake of calcium, sodium, and vitamin D were inversely associated with PC, but coffee consumption was positively linked to PC. Multiple C2 And Transmembrane Domain Containing-1 (MCTP1)_rs4290997, Kinesin Family Member-7 (KIF7)_rs2350480, Coagulation Factor-II (F2)_rs2070850, Peroxisomal Biogenesis Factor-3 (PEX3)_rs223231, TBC1 Domain Family Member-22A (TBC1D22A)_rs910543, and Phospholipase A2 Group-IV-C (PLA2G4C)_rs7252136 interact with each other to have a threefold influence on PC. The PRS for the six-genetic variant model also interacted with age; the diet rich in beans, potato, and kimchi; and smoking status, influencing PC. In conclusion, elevated PC was associated with MetS and cardiovascular disease risk, suggesting their potential as disease biomarkers.
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Affiliation(s)
- Yong-Hwa Lee
- Department of Cosmetic Biotechnology, Hoseo University, Asan 31499, Republic of Korea;
| | - Sunmin Park
- Department of Food and Nutrition, Institute of Basic Science, Obesity/Diabetes Research Center, Hoseo University, Asan 31499, Republic of Korea
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15
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Bishehsari F, Drees M, Adnan D, Sharma D, Green S, Koshy J, Giron LB, Goldman A, Abdel-Mohsen M, Rasmussen HE, Miller GE, Keshavarzian A. Multi-omics approach to socioeconomic disparity in metabolic syndrome reveals roles of diet and microbiome. Proteomics 2023; 23:e2300023. [PMID: 37525324 DOI: 10.1002/pmic.202300023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 06/23/2023] [Accepted: 07/10/2023] [Indexed: 08/02/2023]
Abstract
The epidemy of metabolic syndrome (MetS) is typically preceded by adoption of a "risky" lifestyle (e.g., dietary habit) among populations. Evidence shows that those with low socioeconomic status (SES) are at an increased risk for MetS. To investigate this, we recruited 123 obese subjects (body mass index [BMI] ≥ 30) from Chicago. Multi-omic data were collected to interrogate fecal microbiota, systemic markers of inflammation and immune activation, plasma metabolites, and plasma glycans. Intestinal permeability was measured using the sugar permeability testing. Our results suggest a heterogenous metabolic dysregulation among obese populations who are at risk of MetS. Systemic inflammation, linked to poor diet, intestinal microbiome dysbiosis, and gut barrier dysfunction may explain the development of MetS in these individuals. Our analysis revealed 37 key features associated with increased numbers of MetS features. These features were used to construct a composite metabolic-inflammatory (MI) score that was able to predict progression of MetS among at-risk individuals. The MI score was correlated with several markers of poor diet quality as well as lower levels of gut microbial diversity and abnormalities in several species of bacteria. This study reveals novel targets to reduce the burden of MetS and suggests access to healthy food options as a practical intervention.
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Affiliation(s)
- Faraz Bishehsari
- Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, Illinois, USA
| | - Michael Drees
- Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, Illinois, USA
| | - Darbaz Adnan
- Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, Illinois, USA
| | - Deepak Sharma
- Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, Illinois, USA
| | - Stefan Green
- Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, Illinois, USA
| | - Jane Koshy
- The Wistar Institute, Philadelphia, Pennsylvania, USA
| | - Leila B Giron
- The Wistar Institute, Philadelphia, Pennsylvania, USA
| | - Aaron Goldman
- The Wistar Institute, Philadelphia, Pennsylvania, USA
| | | | | | - Gregory E Miller
- Institute for Policy Research and Dept of Psychology, Northwestern Univ, Evanston, Illinois, USA
| | - Ali Keshavarzian
- Rush Center for Integrated Microbiome and Chronobiology Research, Rush University Medical Center, Chicago, Illinois, USA
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Hou Y, Bai L, Wang X, Zhang S, Liu S, Hu J, Gao J, Guo S, Ho CT, Bai N. Gut Microbiota Combined with Serum Metabolomics to Investigate the Hypoglycemic Effect of Actinidia arguta Leaves. Nutrients 2023; 15:4115. [PMID: 37836402 PMCID: PMC10574697 DOI: 10.3390/nu15194115] [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: 08/31/2023] [Revised: 09/20/2023] [Accepted: 09/21/2023] [Indexed: 10/15/2023] Open
Abstract
Actinidia arguta leaves (AAL) are an excellent source of bioactive components for the food industry and possess many functional properties. However, the hypoglycemic effect and mechanism of AAL remain unclear. The aim of this work was to investigate the potential hypoglycemic effect of AAL and explore its possible mechanism using 16S rRNA sequencing and serum metabolomics in diabetic mice induced by high-fat feeding in combination with streptozotocin injection. A total of 25 flavonoids from AAL were isolated and characterized, and the contents of the extract from the AAL ranged from 0.14 mg/g DW to 8.97 mg/g DW. The compound quercetin (2) had the highest content of 8.97 ± 0.09 mg/g DW, and the compound kaempferol-3-O-(2'-O-D-glucopyl)-β-D-rutinoside (12) had the lowest content of 0.14 ± 0.01 mg/g DW. In vivo experimental studies showed that AAL reduced blood glucose and cholesterol levels, improved insulin sensitivity, and ameliorated oxidative stress and liver and kidney pathological damage. In addition, gut microbiota analysis found that AAL significantly reduced the F/B ratio, enriched the beneficial bacteria Bacteroides and Bifidobacterium, and inhibited the harmful bacteria Lactobacillus and Desulfovibrio, thereby playing an active role in intestinal imbalance. In addition, metabolomics analysis showed that AAL could improve amino acid metabolism and arachidonic acid metabolism, thereby exerting a hypoglycemic effect. This study confirmed that AAL can alleviate type 2 diabetes mellitus (T2DM) by regulating intestinal flora and interfering with related metabolic pathways, providing a scientific basis for its use as a dietary supplement and for further exploration of the mechanism of AAL against T2DM.
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Affiliation(s)
- Yufei Hou
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
| | - Lu Bai
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
- Instrument Analysis Center, Xi’an Jiaotong University, 28 Xianning West Road, Xi’an 710048, China
| | - Xin Wang
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
| | - Shanshan Zhang
- Department of Pharmaceutical Engineering, College of Chemical Engineering, Northwest University, 229 Taibai North Road, Xi’an 710069, China
| | - Shaojing Liu
- Department of Pharmaceutical Engineering, College of Chemical Engineering, Northwest University, 229 Taibai North Road, Xi’an 710069, China
- College of Pharmacy, Xi’an Medical University, 1 Xinwang Road, Xi’an 710021, China
| | - Jiabing Hu
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
| | - Jing Gao
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
| | - Sen Guo
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
| | - Chi-Tang Ho
- Department of Food Science, Rutgers University, 65 Dudley Road, New Brunswick, NJ 08901, USA
| | - Naisheng Bai
- College of Food Science and Technology, Northwest University, 229 Taibai North Road, Xi’an 710069, China; (Y.H.); (S.G.)
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Desine S, Gabriel CL, Smith HM, Antonetti OR, Wang C, Calcutt MW, Doran AC, Silver HJ, Nair S, Terry JG, Carr JJ, Linton MF, Brown JD, Koethe JR, Ferguson JF. Association of alpha-aminoadipic acid with cardiometabolic risk factors in healthy and high-risk individuals. Front Endocrinol (Lausanne) 2023; 14:1122391. [PMID: 37745703 PMCID: PMC10513411 DOI: 10.3389/fendo.2023.1122391] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 07/17/2023] [Indexed: 09/26/2023] Open
Abstract
Introduction Plasma levels of the metabolite alpha-aminoadipic acid (2-AAA) have been associated with risk of type 2 diabetes (T2D) and atherosclerosis. However, little is known about the relationship of 2-AAA to other cardiometabolic risk markers in pre-disease states, or in the setting of comorbid disease. Methods We measured circulating 2-AAA using two methods in 1) a sample of 261 healthy individuals (2-AAA Study), and 2) in a sample of 134 persons comprising 110 individuals with treated HIV, with or without T2D, a population at high risk of metabolic disease and cardiovascular events despite suppression of circulating virus, and 24 individuals with T2D without HIV (HATIM Study). We examined associations between plasma 2-AAA and markers of cardiometabolic health within each cohort. Results and discussion We observed differences in 2-AAA by sex and race in both cohorts, with higher levels observed in men compared with women, and in Asian compared with Black or white individuals (P<0.05). There was no significant difference in 2-AAA by HIV status within individuals with T2D in the HATIM Study. We confirmed associations between 2-AAA and dyslipidemia in both cohorts, where high 2-AAA associated with low HDL cholesterol (P<0.001) and high triglycerides (P<0.05). As expected, within the cohort of people with HIV, 2-AAA was higher in the setting of T2D compared to pre-diabetes or normoglycemia (P<0.001). 2-AAA was positively associated with body mass index (BMI) in the 2-AAA Study, and with waist circumference and measures of visceral fat volume in HATIM (all P<0.05). Further, 2-AAA associated with increased liver fat in persons with HIV (P<0.001). Our study confirms 2-AAA as a marker of cardiometabolic risk in both healthy individuals and those at high cardiometabolic risk, reveals relationships with adiposity and hepatic steatosis, and highlights important differences by sex and race. Further studies are warranted to establish molecular mechanisms linking 2-AAA to disease in other high-risk populations.
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Affiliation(s)
- Stacy Desine
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Curtis L. Gabriel
- Division of Gastroenterology, Hepatology and Nutrition, Vanderbilt University Medical Center, Nashville, TN, United States
- Tennessee Center for AIDS Research, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Holly M. Smith
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Olivia R. Antonetti
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Chuan Wang
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - M. Wade Calcutt
- Department of Biochemistry, Mass Spectrometry Research Center, Vanderbilt University, Nashville, TN, United States
| | - Amanda C. Doran
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Heidi J. Silver
- Division of Gastroenterology, Hepatology and Nutrition, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Sangeeta Nair
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - James G. Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - John Jeffrey Carr
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center, Nashville, TN, United States
| | - MacRae F. Linton
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jonathan D. Brown
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
| | - John R. Koethe
- Division of Infectious Diseases, Vanderbilt University Medical Center, Nashville, TN, United States
| | - Jane F. Ferguson
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center, Nashville, TN, United States
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Tian C, Li J, Bao Y, Gao L, Song L, Li K, Sun M. Ursolic acid ameliorates obesity of mice fed with high-fat diet via alteration of gut microbiota and amino acid metabolism. Front Microbiol 2023; 14:1183598. [PMID: 37485499 PMCID: PMC10359042 DOI: 10.3389/fmicb.2023.1183598] [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: 03/14/2023] [Accepted: 06/12/2023] [Indexed: 07/25/2023] Open
Abstract
Obesity has been regarded as one of the major health problems worldwide. Studies demonstrated that ursolic acid (UA) can significantly ameliorate the progress of obesity. However, whether the effect of UA on obesity depends on the regulation of gut microbiota and metabolism is uncertain. To investigate the regulatory role of UA in obese mice from the perspective of intestinal microbiome and metabolomics analyses, an obese mice model was established with a high-fat diet, and the effect of UA on obesity was evaluated. The alterations of gut microbiota and metabolism related to obesity were evaluated by bioinformatic analysis. The results of the gut microbiota analysis showed that UA intervention could shift the Firmicutes to Bacteroidetes ratio at the phylum level and increase in the genera of Lactobacillus, Bacteroides, and Akkermansia. Additionally, metabolomics analysis showed that the beneficial influence of UA on obesity partly depended on amino acid metabolism. The current study demonstrated the roles of UA in the anti-obesity process, which depends in part on alterations in the gut microbiota and metabolism. Therefore, our findings highlight the potential therapeutic effect of UA on the improvement of diet-induced obesity in humans.
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Affiliation(s)
- Chunfeng Tian
- School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
| | - Jie Li
- School of Public Health, Jiamusi University, Jiamusi, China
| | - Yan Bao
- School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
- Institute of Nutrition and Food Health, Baotou Medical College, Baotou, China
| | - Long Gao
- School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
| | - Lixin Song
- Baotou Disease Prevention Control Center, Baotou, China
| | - Kai Li
- School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
| | - Ming Sun
- School of Public Health, Baotou Medical College, Inner Mongolia University of Science and Technology, Baotou, China
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Shi M, Han S, Klier K, Fobo G, Montrone C, Yu S, Harada M, Henning AK, Friedrich N, Bahls M, Dörr M, Nauck M, Völzke H, Homuth G, Grabe HJ, Prehn C, Adamski J, Suhre K, Rathmann W, Ruepp A, Hertel J, Peters A, Wang-Sattler R. Identification of candidate metabolite biomarkers for metabolic syndrome and its five components in population-based human cohorts. Cardiovasc Diabetol 2023; 22:141. [PMID: 37328862 PMCID: PMC10276453 DOI: 10.1186/s12933-023-01862-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/03/2023] [Accepted: 05/20/2023] [Indexed: 06/18/2023] Open
Abstract
BACKGROUND Metabolic Syndrome (MetS) is characterized by risk factors such as abdominal obesity, hypertriglyceridemia, low high-density lipoprotein cholesterol (HDL-C), hypertension, and hyperglycemia, which contribute to the development of cardiovascular disease and type 2 diabetes. Here, we aim to identify candidate metabolite biomarkers of MetS and its associated risk factors to better understand the complex interplay of underlying signaling pathways. METHODS We quantified serum samples of the KORA F4 study participants (N = 2815) and analyzed 121 metabolites. Multiple regression models adjusted for clinical and lifestyle covariates were used to identify metabolites that were Bonferroni significantly associated with MetS. These findings were replicated in the SHIP-TREND-0 study (N = 988) and further analyzed for the association of replicated metabolites with the five components of MetS. Database-driven networks of the identified metabolites and their interacting enzymes were also constructed. RESULTS We identified and replicated 56 MetS-specific metabolites: 13 were positively associated (e.g., Val, Leu/Ile, Phe, and Tyr), and 43 were negatively associated (e.g., Gly, Ser, and 40 lipids). Moreover, the majority (89%) and minority (23%) of MetS-specific metabolites were associated with low HDL-C and hypertension, respectively. One lipid, lysoPC a C18:2, was negatively associated with MetS and all of its five components, indicating that individuals with MetS and each of the risk factors had lower concentrations of lysoPC a C18:2 compared to corresponding controls. Our metabolic networks elucidated these observations by revealing impaired catabolism of branched-chain and aromatic amino acids, as well as accelerated Gly catabolism. CONCLUSION Our identified candidate metabolite biomarkers are associated with the pathophysiology of MetS and its risk factors. They could facilitate the development of therapeutic strategies to prevent type 2 diabetes and cardiovascular disease. For instance, elevated levels of lysoPC a C18:2 may protect MetS and its five risk components. More in-depth studies are necessary to determine the mechanism of key metabolites in the MetS pathophysiology.
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Affiliation(s)
- Mengya Shi
- TUM School of Medicine, Technical University of Munich (TUM), Munich, Germany
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany
| | - Siyu Han
- TUM School of Medicine, Technical University of Munich (TUM), Munich, Germany
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany
| | - Kristin Klier
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
| | - Gisela Fobo
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Corinna Montrone
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Shixiang Yu
- TUM School of Medicine, Technical University of Munich (TUM), Munich, Germany
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Makoto Harada
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany
| | - Ann-Kristin Henning
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
| | - Nele Friedrich
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Martin Bahls
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Marcus Dörr
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - Matthias Nauck
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Henry Völzke
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
- Institute for Community Medicine, University Medicine Greifswald, Greifswald, Germany
- German Centre for Diabetes Research (DZD), Partner Greifswald, Neuherberg, Germany
| | - Georg Homuth
- Interfaculty Institute for Genetics and Functional Genomics, University Medicine Greifswald, Greifswald, Germany
| | - Hans J. Grabe
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Center for Neurodegenerative Diseases (DZNE), Greifswald, Germany
| | - Cornelia Prehn
- Metabolomics and Proteomics Core, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Ljubljana, Slovenia
| | - Karsten Suhre
- Department of Physiology and Biophysics, Weill Cornell Medicine—Qatar, Education City—Qatar Foundation, Doha, Qatar
| | - Wolfgang Rathmann
- German Center for Diabetes Research (DZD), Partner Düsseldorf, Neuherberg, Germany
- Institute of Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research at Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Andreas Ruepp
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Johannes Hertel
- Department of Psychiatry and Psychotherapy, University Medicine Greifswald, Greifswald, Germany
- German Centre for Cardiovascular Research (DZHK), Partner Site Greifswald, Greifswald, Germany
| | - Annette Peters
- German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, Ludwig Maximilian University of Munich (LMU), Munich, Germany
- Munich Heart Alliance, German Center for Cardiovascular Health (DZHK E.V., Partner-Site Munich), Munich, Germany
| | - Rui Wang-Sattler
- Institute of Translational Genomics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD), Partner Neuherberg, Munich-Neuherberg, Germany
- Institute for Medical Information Processing, Biometry, and Epidemiology, Pettenkofer School of Public Health, Ludwig Maximilian University of Munich (LMU), Munich, Germany
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20
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Desine S, Gabriel CL, Smith HM, Antonetti OR, Wang C, Calcutt MW, Doran AC, Silver HJ, Nair S, Terry JG, Carr JJ, Linton MF, Brown JD, Koethe JR, Ferguson JF. Association of alpha-aminoadipic acid (2-AAA) with cardiometabolic risk factors in healthy and high-risk individuals. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.06.05.23290990. [PMID: 37333170 PMCID: PMC10274998 DOI: 10.1101/2023.06.05.23290990] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/20/2023]
Abstract
Plasma levels of the metabolite alpha-aminoadipic acid (2-AAA) have been associated with risk of type 2 diabetes (T2D) and atherosclerosis. However, little is known about the relationship of 2-AAA to other cardiometabolic risk markers in pre-disease states, or in the setting of comorbid disease. We measured circulating 2-AAA using two methods in 1) a sample of 261 healthy individuals (2-AAA Study), and 2) in a sample of 134 persons comprising 110 individuals with treated HIV, with or without T2D, a population at high risk of metabolic disease and cardiovascular events despite suppression of circulating virus, and 24 individuals with T2D without HIV (HATIM Study). We examined associations between plasma 2-AAA and markers of cardiometabolic health within each cohort. We observed differences in 2-AAA by sex and race in both cohorts, with higher levels observed in men compared with women, and in Asian compared with Black or white individuals (P<0.05). There was no significant difference in 2-AAA by HIV status within individuals with T2D in the HATIM Study. We confirmed associations between 2-AAA and dyslipidemia in both cohorts where high 2-AAA associated with low HDL cholesterol (P<0.001) and high triglycerides (P<0.05). As expected, within the cohort of people with HIV, 2-AAA was higher in the setting of T2D compared to pre-diabetes or normoglycemia (P<0.001). 2-AAA was positively associated with body mass index (BMI) in the 2-AAA Study, and with waist circumference and measures of visceral fat volume in HATIM (all P<0.05). Further, 2-AAA associated with increased liver fat in persons with HIV (P<0.001). Our study confirms 2-AAA as a marker of cardiometabolic risk in both healthy individuals and those at high cardiometabolic risk, reveals relationships with adiposity and hepatic steatosis, and highlights important differences by sex and race. Further studies are warranted to establish molecular mechanisms linking 2-AAA to disease in other high-risk populations.
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Affiliation(s)
- Stacy Desine
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | - Curtis L. Gabriel
- Division of Gastroenterology, Hepatology and Nutrition, Vanderbilt University Medical Center
- Tennessee Center for AIDS Research, Vanderbilt University Medical Center
| | - Holly M. Smith
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | | | - Chuan Wang
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | - M. Wade Calcutt
- Department of Biochemistry, Mass Spectrometry Research Center, Vanderbilt University
| | - Amanda C. Doran
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | - Heidi J. Silver
- Division of Gastroenterology, Hepatology and Nutrition, Vanderbilt University Medical Center
| | - Sangeeta Nair
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
| | - James G. Terry
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
| | - J. Jeffrey Carr
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
| | - MacRae F. Linton
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | - Jonathan D. Brown
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
| | - John R. Koethe
- Department of Radiology and Radiological Sciences, Vanderbilt University Medical Center
| | - Jane F. Ferguson
- Division of Cardiovascular Medicine, Vanderbilt University Medical Center
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Moin N, Thakur RS, Singh S, Patel DK, Satish A. β-triketone herbicide exposure cause tyrosine and fat accumulation in Caenorhabditis elegans. CHEMOSPHERE 2023; 326:138353. [PMID: 36914009 DOI: 10.1016/j.chemosphere.2023.138353] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Revised: 03/07/2023] [Accepted: 03/07/2023] [Indexed: 06/18/2023]
Abstract
β-triketone herbicides have been efficiently employed as an alternate to atrazine. Triketones are 4-hydroxyphenylpyruvate dioxygenase (HPPD) enzyme inhibitors and exposure is reported to cause significant increase in plasma tyrosine levels. In this study, we have employed a non-target organism Caenorhabditis elegans to determine the impact of β-triketone exposures at recommended field doses (RfD). Our results indicate sulcotrione and mesotrione, negatively influence the survival, behavior, and reproduction of the organism at RfD. Additionally, we have traced the parallels regarding the impact of triketones on the tyrosine metabolism pathway, in C. elegans to those in mammalian models, wherein the expression of the tyrosine metabolism pathway genes are altered, directly influencing tyrosine catabolism leading to significant tyrosine accumulation in exposed organism. Further, we investigated the impact of sulcotrione and mesotrione exposure on fat deposition (triglyceride levels, Oil-Red-O staining and lipidomics) and the fatty acid metabolism pathway. In the exposed worms, the expression of enlongases and fatty acid desaturases were up-regulated along with an increase in the levels of triglycerides. Thus, the data indicates a positive association of β-triketone exposure to mis-regulation of the fatty acid metabolism pathway genes leading to fat accumulation in worms. Therefore, β-triketone might be a potential obesogen.
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Affiliation(s)
- Nida Moin
- Ecotoxicology Laboratory, Environmental Toxicology Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India; Department of Biochemistry, Babu Banarasi Das University, Lucknow, 227015, India
| | - Ravindra Singh Thakur
- Analytical Chemistry Laboratory, Regulatory Toxicology Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, India
| | - Swati Singh
- Ecotoxicology Laboratory, Environmental Toxicology Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India
| | - Devendra Kumar Patel
- Analytical Chemistry Laboratory, Regulatory Toxicology Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, India
| | - Aruna Satish
- Ecotoxicology Laboratory, Environmental Toxicology Group, CSIR-Indian Institute of Toxicology Research (CSIR-IITR), Vishvigyan Bhavan, 31, Mahatma Gandhi Marg, Lucknow, 226001, Uttar Pradesh, India.
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22
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Xiang W, Yang Y, Weng L, Ye Z, Ding P, Li H, Sun J, Zeng C. Hyperhomocysteinemia activates NLRP3 inflammasome to cause hepatic steatosis and insulin resistance via MDM2-mediated ubiquitination of HSF1. Int Immunopharmacol 2023; 118:110085. [PMID: 37018978 DOI: 10.1016/j.intimp.2023.110085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2022] [Revised: 03/14/2023] [Accepted: 03/21/2023] [Indexed: 04/05/2023]
Abstract
Hyperhomocysteinemia (HHcy) is associated with nonalcoholic fatty liver disease (NAFLD) and insulin resistance (IR). However, the underlying mechanism is still unknown. Recent studies have demonstrated that NLRP3 inflammasome activation plays a vital role in NAFLD and IR. Our study aimed to explore whether NLRP3 inflammasome contributed to HHcy-induced NAFLD and IR as well as dissected the underlying mechanism. C57BL/6 mice were fed a high-methionine diet (HMD) for 8 weeks to establish the HHcy mouse model. Compared with a chow diet, HMD induced hepatic steatosis (HS) and IR as well as activation of hepatic NLRP3 inflammasome. Moreover, HHcy-induced NAFLD and IR characterization disclosed that NLRP3 inflammasome activation occurred in liver tissue of HMD-fed mice, but was very marginal in either NLRP3-/- or Caspase-1-/- mice. Mechanistically, high levels of homocysteine (Hcy) up-regulated the expression of mouse double minute 2 homolog (MDM2), which directly ubiquitinates heat shock transcription factor 1 (HSF1) and consequently activated hepatic NLRP3 inflammasome in vivo and in vitro. In addition, in vitro experiments showed P300-mediated HSF1 acetylation at K298 hindered MDM2-mediated ubiquitination of HSF1 at K372, which plays important role in determining the HSF1 level. Importantly, either inhibition of MDM2 by JNJ-165 or activation of HSF1 by HSF1A reversed HMD-induced hepatic NLRP3 inflammasome, and consequently alleviated HS and IR in mice. This study demonstrates that NLRP3 inflammasome activation contributes to HHcy-induced NAFLD and IR, and further identified that HSF1 as a new substrate of MDM2 and its decrease on MDM2-mediated ubiquitination at K372 modulates NLRP3 inflammasome activation. These findings may provide novel therapeutic strategies aimed at halting HS or IR.
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Affiliation(s)
- Wenjing Xiang
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Yang Yang
- Department of Pharmacy, Zhuhai People's Hospital (Zhuhai Hospital Affiliated with Jinan University), Zhuhai, 519000, China
| | - Liangkun Weng
- Center for Drug Research and Development, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Zhiming Ye
- Center for Drug Research and Development, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Ping Ding
- Center for Drug Research and Development, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Huayu Li
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Jia Sun
- School of Pharmacy, Guangdong Pharmaceutical University, Guangzhou 510006, China
| | - Cheng Zeng
- Center for Drug Research and Development, Guangdong Pharmaceutical University, Guangzhou 510006, China; Key Specialty of Clinical Pharmacy, The First Affiliated Hospital of Guangdong Pharmaceutical University, 510699, China; Guangdong Key Laboratory of Pharmaceutical Bioactive Substances, Guangdong Pharmaceutical University, Guangzhou, 510006, China.
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Auguet T, Bertran L, Capellades J, Abelló S, Aguilar C, Sabench F, del Castillo D, Correig X, Yanes O, Richart C. LC/MS-Based Untargeted Metabolomics Analysis in Women with Morbid Obesity and Associated Type 2 Diabetes Mellitus. Int J Mol Sci 2023; 24:7761. [PMID: 37175468 PMCID: PMC10177925 DOI: 10.3390/ijms24097761] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 04/17/2023] [Accepted: 04/18/2023] [Indexed: 05/15/2023] Open
Abstract
Obesity is a chronic and complex disease, with an increasing incidence worldwide that is associated with metabolic disorders such as type 2 diabetes mellitus (T2DM). Thus, it is important to determine the differences between metabolically healthy obese individuals and those with metabolic disorders. The aim of this study was to perform an untargeted metabolomics assay in women with morbid obesity (MO) compared to a normal weight group, and to differentiate the metabolome of these women with MO who present with T2DM. We carried out a liquid chromatography-mass spectrometry-based untargeted metabolomics assay using serum samples of 209 Caucasian women: 73 with normal weight and 136 with MO, of which 71 had T2DM. First, we found increased levels of choline and acylglycerols and lower levels of bile acids, steroids, ceramides, glycosphingolipids, lysophosphatidylcholines, and lysophosphatidylethanolamines in MO women than in the control group. Then, in MO women with T2DM, we found increased levels of glutamate, propionyl-carnitine, bile acids, ceramides, lysophosphatidylcholine 14:0, phosphatidylinositols and phosphoethanolamines, and lower levels of Phe-Ile/Leu. Thus, we found metabolites with opposite trends of concentration in the two metabolomic analyses. These metabolites could be considered possible new factors of study in the pathogenesis of MO and associated T2DM in women.
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Affiliation(s)
- Teresa Auguet
- Grup de Recerca GEMMAIR (AGAUR)-Medicina Aplicada, Departament de Medicina i Cirurgia, Universitat Rovira i Virgili (URV), IISPV, 43005 Tarragona, Spain; (T.A.); (L.B.); (C.A.); (F.S.); (D.d.C.)
| | - Laia Bertran
- Grup de Recerca GEMMAIR (AGAUR)-Medicina Aplicada, Departament de Medicina i Cirurgia, Universitat Rovira i Virgili (URV), IISPV, 43005 Tarragona, Spain; (T.A.); (L.B.); (C.A.); (F.S.); (D.d.C.)
| | - Jordi Capellades
- Department of Electronic Engineering, Universitat Rovira i Virgili (URV), IISPV, 43007 Tarragona, Spain; (J.C.); (X.C.); (O.Y.)
| | - Sonia Abelló
- Servei de Recursos Científics i Tècnics, Universitat Rovira i Virgili (URV), 43007 Tarragona, Spain;
| | - Carmen Aguilar
- Grup de Recerca GEMMAIR (AGAUR)-Medicina Aplicada, Departament de Medicina i Cirurgia, Universitat Rovira i Virgili (URV), IISPV, 43005 Tarragona, Spain; (T.A.); (L.B.); (C.A.); (F.S.); (D.d.C.)
| | - Fàtima Sabench
- Grup de Recerca GEMMAIR (AGAUR)-Medicina Aplicada, Departament de Medicina i Cirurgia, Universitat Rovira i Virgili (URV), IISPV, 43005 Tarragona, Spain; (T.A.); (L.B.); (C.A.); (F.S.); (D.d.C.)
- Unitat de Cirurgia, Facultad de Medicina i Ciències de la Salut, Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili (URV), IISPV, 43204 Reus, Spain
| | - Daniel del Castillo
- Grup de Recerca GEMMAIR (AGAUR)-Medicina Aplicada, Departament de Medicina i Cirurgia, Universitat Rovira i Virgili (URV), IISPV, 43005 Tarragona, Spain; (T.A.); (L.B.); (C.A.); (F.S.); (D.d.C.)
- Unitat de Cirurgia, Facultad de Medicina i Ciències de la Salut, Hospital Universitari Sant Joan de Reus, Universitat Rovira i Virgili (URV), IISPV, 43204 Reus, Spain
| | - Xavier Correig
- Department of Electronic Engineering, Universitat Rovira i Virgili (URV), IISPV, 43007 Tarragona, Spain; (J.C.); (X.C.); (O.Y.)
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, 43204 Madrid, Spain
| | - Oscar Yanes
- Department of Electronic Engineering, Universitat Rovira i Virgili (URV), IISPV, 43007 Tarragona, Spain; (J.C.); (X.C.); (O.Y.)
- CIBER de Diabetes y Enfermedades Metabólicas Asociadas, Instituto de Salud Carlos III, 43204 Madrid, Spain
| | - Cristóbal Richart
- Grup de Recerca GEMMAIR (AGAUR)-Medicina Aplicada, Departament de Medicina i Cirurgia, Universitat Rovira i Virgili (URV), IISPV, 43005 Tarragona, Spain; (T.A.); (L.B.); (C.A.); (F.S.); (D.d.C.)
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Nutrients, Physical Activity, and Mitochondrial Dysfunction in the Setting of Metabolic Syndrome. Nutrients 2023; 15:nu15051217. [PMID: 36904216 PMCID: PMC10004804 DOI: 10.3390/nu15051217] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/04/2023] Open
Abstract
Metabolic syndrome (MetS) is a cluster of metabolic risk factors for diabetes, coronary heart disease, non-alcoholic fatty liver disease, and some tumors. It includes insulin resistance, visceral adiposity, hypertension, and dyslipidemia. MetS is primarily linked to lipotoxicity, with ectopic fat deposition from fat storage exhaustion, more than obesity per se. Excessive intake of long-chain saturated fatty acid and sugar closely relates to lipotoxicity and MetS through several pathways, including toll-like receptor 4 activation, peroxisome proliferator-activated receptor-gamma regulation (PPARγ), sphingolipids remodeling, and protein kinase C activation. These mechanisms prompt mitochondrial dysfunction, which plays a key role in disrupting the metabolism of fatty acids and proteins and in developing insulin resistance. By contrast, the intake of monounsaturated, polyunsaturated, and medium-chain saturated (low-dose) fatty acids, as well as plant-based proteins and whey protein, favors an improvement in sphingolipid composition and metabolic profile. Along with dietary modification, regular exercises including aerobic, resistance, or combined training can target sphingolipid metabolism and improve mitochondrial function and MetS components. This review aimed to summarize the main dietary and biochemical aspects related to the physiopathology of MetS and its implications for mitochondrial machinery while discussing the potential role of diet and exercise in counteracting this complex clustering of metabolic dysfunctions.
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Teruya T, Sunagawa S, Mori A, Masuzaki H, Yanagida M. Markers for obese and non-obese Type 2 diabetes identified using whole blood metabolomics. Sci Rep 2023; 13:2460. [PMID: 36774491 PMCID: PMC9922320 DOI: 10.1038/s41598-023-29619-4] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Accepted: 02/07/2023] [Indexed: 02/13/2023] Open
Abstract
Definitive differences in blood metabolite profiles between obese and non-obese Type 2 diabetes (T2D) have not been established. We performed an LC-MS-based non-targeted metabolomic analysis of whole blood samples collected from subjects classified into 4 types, based on the presence or absence of obesity and T2D. Of the 125 compounds identified, 20, comprising mainly nucleobases and glucose metabolites, showed significant increases or decreases in the T2D group. These included cytidine, UDP-glucuronate, UMP, 6-phosphogluconate, and pentose-phosphate. Among those 20 compounds, 11 enriched in red blood cells (RBCs) have rarely been studied in the context of diabetes, indicating that RBC metabolism is more extensively disrupted than previously known. Correlation analysis revealed that these T2D markers include 15 HbA1c-associated and 5 irrelevant compounds that may reflect diabetic conditions by a different mechanism than that of HbA1c. In the obese group, enhanced protein and fatty acid catabolism causes increases in 13 compounds, including methylated or acetylated amino acids and short-chain carnitines. Our study, which may be considered a pilot investigation, suggests that changes in blood metabolism due to obesity and diabetes are large, but essentially independent.
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Affiliation(s)
- Takayuki Teruya
- G0 Cell Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
- R&D Cluster Programs Section, Technology Development and Innovation Center, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
| | - Sumito Sunagawa
- Division of Endocrinology, Diabetes and Metabolism, Hematology, Rheumatology (Second Department of Internal Medicine), Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Ayaka Mori
- G0 Cell Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
- Cell Division Dynamics Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan
| | - Hiroaki Masuzaki
- Division of Endocrinology, Diabetes and Metabolism, Hematology, Rheumatology (Second Department of Internal Medicine), Graduate School of Medicine, University of the Ryukyus, Okinawa, Japan
| | - Mitsuhiro Yanagida
- G0 Cell Unit, Okinawa Institute of Science and Technology Graduate University (OIST), Okinawa, Japan.
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26
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Dong Q, Sidra S, Gieger C, Wang-Sattler R, Rathmann W, Prehn C, Adamski J, Koenig W, Peters A, Grallert H, Sharma S. Metabolic Signatures Elucidate the Effect of Body Mass Index on Type 2 Diabetes. Metabolites 2023; 13:metabo13020227. [PMID: 36837846 PMCID: PMC9965667 DOI: 10.3390/metabo13020227] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2022] [Revised: 01/26/2023] [Accepted: 01/31/2023] [Indexed: 02/09/2023] Open
Abstract
Obesity plays an important role in the development of insulin resistance and diabetes, but the molecular mechanism that links obesity and diabetes is still not completely understood. Here, we used 146 targeted metabolomic profiles from the German KORA FF4 cohort consisting of 1715 participants and associated them with obesity and type 2 diabetes. In the basic model, 83 and 51 metabolites were significantly associated with body mass index (BMI) and T2D, respectively. Those metabolites are branched-chain amino acids, acylcarnitines, lysophospholipids, or phosphatidylcholines. In the full model, 42 and 3 metabolites were significantly associated with BMI and T2D, respectively, and replicate findings in the previous studies. Sobel mediation testing suggests that the effect of BMI on T2D might be mediated via lipids such as sphingomyelin (SM) C16:1, SM C18:1 and diacylphosphatidylcholine (PC aa) C38:3. Moreover, mendelian randomization suggests a causal relationship that BMI causes the change of SM C16:1 and PC aa C38:3, and the change of SM C16:1, SM C18:1, and PC aa C38:3 contribute to T2D incident. Biological pathway analysis in combination with genetics and mice experiments indicate that downregulation of sphingolipid or upregulation of phosphatidylcholine metabolism is a causal factor in early-stage T2D pathophysiology. Our findings indicate that metabolites like SM C16:1, SM C18:1, and PC aa C38:3 mediate the effect of BMI on T2D and elucidate their role in obesity related T2D pathologies.
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Affiliation(s)
- Qiuling Dong
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Faculty of Medicine, Ludwig-Maximilians-University München, 81377 Munich, Germany
| | - Sidra Sidra
- Institute for Medical Information Processing, Biometry and Epidemiology (IBE), Ludwig-Maximilians-Universität München, 81377 Munich, Germany
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany
| | - Rui Wang-Sattler
- Institute of Translational Genomics, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Wolfgang Rathmann
- Institute for Biometrics and Epidemiology, German Diabetes Center, Leibniz Center for Diabetes Research, Heinrich Heine University Düsseldorf, 40225 Düsseldorf, Germany
| | - Cornelia Prehn
- Metabolomics and Proteomics Core Facility, Helmholtz Zentrum München, 85764 Neuherberg, Germany
| | - Jerzy Adamski
- Institute of Experimental Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Ingolstädter Landstraße 1, 85764 Neuherberg, Germany
- Department of Biochemistry, Yong Loo Lin School of Medicine, National University of Singapore, 8 Medical Drive, Singapore 117597, Singapore
- Institute of Biochemistry, Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1000 Ljubljana, Slovenia
| | - Wolfgang Koenig
- German Research Center for Cardiovascular Disease (DZHK), Partner site Munich Heart Alliance, 81377 Munich, Germany
- Deutsches Herzzentrum München, Technische Universität München, 81377 Munich, Germany
- Institute of Epidemiology and Medical Biometry, University of Ulm, 89069 Ulm, Germany
| | - Annette Peters
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany
- Chair of Epidemiology, Faculty of Medicine, Ludwig-Maximilians-University München, 81377 Munich, Germany
| | - Harald Grallert
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- German Center for Diabetes Research (DZD), 85764 München-Neuherberg, Germany
- Correspondence: (H.G.); (S.S.)
| | - Sapna Sharma
- Research Unit of Molecular Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Institute of Epidemiology, Helmholtz Zentrum München, 85764 Neuherberg, Germany
- Chair of Food Chemistry and Molecular Sensory Science, Technical University of Munich, 85354 Freising-Weihenstephan, Germany
- Correspondence: (H.G.); (S.S.)
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27
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Luo S, Zhao Y, Zhu S, Liu L, Cheng K, Ye B, Han Y, Fan J, Xia M. Flavonifractor plautii Protects Against Elevated Arterial Stiffness. Circ Res 2023; 132:167-181. [PMID: 36575982 DOI: 10.1161/circresaha.122.321975] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/29/2022]
Abstract
BACKGROUND Dysbiosis of gut microbiota plays a pivotal role in vascular dysfunction and microbial diversity was reported to be inversely correlated with arterial stiffness. However, the causal role of gut microbiota in the progression of arterial stiffness and the specific species along with the molecular mechanisms underlying this change remain largely unknown. METHODS Participants with elevated arterial stiffness and normal controls free of medication were matched for age and sex. The microbial composition and metabolic capacities between the 2 groups were compared with the integration of metagenomics and metabolomics. Subsequently, Ang II (angiotensin II)-induced and humanized mouse model were employed to evaluate the protective effect of Flavonifractor plautii (F plautii) and its main effector cis-aconitic acid. RESULTS Human fecal metagenomic sequencing revealed a significantly high abundance and centrality of F plautii in normal controls, which was absent in the microbial community of subjects with elevated arterial stiffness. Moreover, blood pressure only mediated part of the effect of F plautii on lower arterial stiffness. The microbiome of normal controls exhibited an enhanced capacity for glycolysis and polysaccharide degradation, whereas, those of subjects with increased arterial stiffness were characterized by increased biosynthesis of fatty acids and aromatic amino acids. Integrative analysis with metabolomics profiling further suggested that increased cis-aconitic acid served as the main effector for the protective effect of F plautii against arterial stiffness. Replenishment with F plautii and cis-aconitic acid improved elastic fiber network and reversed increased pulse wave velocity through the suppression of MMP-2 (matrix metalloproteinase-2) and inhibition of MCP-1 (monocyte chemoattractant protein-1) and NF-κB (nuclear factor kappa-B) activation in both Ang II-induced and humanized model of arterial stiffness. CONCLUSIONS Our translational study identifies a novel link between F plautii and arterial function and raises the possibility of sustaining vascular health by targeting gut microbiota.
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Affiliation(s)
- Shiyun Luo
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
| | - Yawen Zhao
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
| | - Shanshan Zhu
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
| | - Ludi Liu
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China.,Department of Statistics and Epidemiology (L.L., B.Y.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
| | - Ken Cheng
- XJTLU Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, China (K.C., Y.H.)
| | - Bingqi Ye
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China.,Department of Statistics and Epidemiology (L.L., B.Y.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
| | - Yueyuan Han
- XJTLU Wisdom Lake Academy of Pharmacy, Xi'an Jiaotong-Liverpool University, Suzhou, China (K.C., Y.H.)
| | - Jiahua Fan
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
| | - Min Xia
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, and Department of Nutrition (S.L., Y.Z., S.Z., L.L., B.Y., J.F., M.X.), School of Public Health, Sun Yat-sen University (Northern Campus), Guangzhou, Guangdong Province, China
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A Metabolomics-Based Investigation of the Effects of a Short-Term Body Weight Reduction Program in a Cohort of Adolescents with Obesity: A Prospective Interventional Clinical Study. Nutrients 2023; 15:nu15030529. [PMID: 36771236 PMCID: PMC9921209 DOI: 10.3390/nu15030529] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2022] [Revised: 01/10/2023] [Accepted: 01/14/2023] [Indexed: 01/20/2023] Open
Abstract
Metabolomics applied to assess the response to a body weight reduction program (BWRP) may generate valuable information concerning the biochemical mechanisms/pathways underlying the BWRP-induced cardiometabolic benefits. The aim of the present study was to establish the BWRP-induced changes in the metabolomic profile that characterizes the obese condition. In particular, a validated liquid chromatography-tandem mass spectrometry (LC-MS/MS) targeted metabolomic approach was used to determine a total of 188 endogenous metabolites in the plasma samples of a cohort of 42 adolescents with obesity (female/male = 32/10; age = 15.94 ± 1.33 year; body mass index standard deviation score (BMI SDS) = 2.96 ± 0.46) who underwent a 3-week BWRP, including hypocaloric diet, physical exercise, nutritional education, and psychological support. The BWRP was capable of significantly improving body composition (e.g., BMI SDS, p < 0.0001), glucometabolic homeostasis (e.g., glucose, p < 0.0001), and cardiovascular function (e.g., diastolic blood pressure, p = 0.016). A total of 64 metabolites were significantly reduced after the intervention (at least p < 0.05), including 53 glycerophospholipids (23 PCs ae, 21 PCs aa, and 9 lysoPCs), 7 amino acids (tyrosine, phenylalanine, arginine, citrulline, tryptophan, glutamic acid, and leucine), the biogenic amine kynurenine, 2 sphingomyelins, and (free) carnitine (C0). On the contrary, three metabolites were significantly increased after the intervention (at least p < 0.05)-in particular, glutamine, trans-4-hydroxyproline, and the octadecenoyl-carnitine (C18:1). In conclusion, when administered to adolescents with obesity, a short-term BWRP is capable of changing the metabolomic profile in the plasma.
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Taghizadeh H, Emamgholipour S, Hosseinkhani S, Arjmand B, Rezaei N, Dilmaghani-Marand A, Ghasemi E, Panahi N, Dehghanbanadaki H, Ghodssi-Ghassemabadi R, Najjar N, Asadi M, khoshniat M, Larijani B, Razi F. The association between acylcarnitine and amino acids profile and metabolic syndrome and its components in Iranian adults: Data from STEPs 2016. Front Endocrinol (Lausanne) 2023; 14:1058952. [PMID: 36923214 PMCID: PMC10008865 DOI: 10.3389/fendo.2023.1058952] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/30/2022] [Accepted: 02/06/2023] [Indexed: 03/03/2023] Open
Abstract
BACKGROUND Evidence, albeit with conflicting results, has suggested that cardiometabolic risk factors, including obesity, type 2 diabetes (T2D), dyslipidemia, and hypertension, are highly associated with changes in metabolic signature, especially plasma amino acids and acylcarnitines levels. Here, we aimed to evaluate the association of circulating levels of amino acids and acylcarnitines with metabolic syndrome (MetS) and its components in Iranian adults. METHODS This cross-sectional study was performed on 1192 participants from the large-scale cross-sectional study of Surveillance of Risk Factors of non-communicable diseases (NCDs) in Iran (STEP 2016). The circulating levels of amino acids and acylcarnitines were measured using liquid chromatography-tandem mass spectrometry (LC-MS/MS) in individuals with MetS (n=529) and without MetS (n=663). RESULTS The higher plasma levels of branched-chain amino acids (Val, Leu), aromatic amino acids (Phe, Tyr), Pro, Ala, Glu, and the ratio of Asp to Asn were significantly associated with MetS, whereas lower circulating levels of Gly, Ser, His, Asn, and citrulline were significantly associated with MetS. As for plasma levels of free carnitine and acylcarnitines, higher levels of short-chain acylcarnitines (C2, C3, C4DC), free carnitine (C0), and long-chain acylcarnitines (C16, C18OH) were significantly associated with MetS. Principal component analysis (PCA) showed that factor 3 (Tyr, Leu, Val, Met, Trp, Phe, Thr) [OR:1.165, 95% CI: 1.121-1.210, P<0.001], factor 7 (C0, C3, C4) [OR:1.257, 95% CI: 1.150-1.374, P<0.001], factor 8 (Gly, Ser) [OR:0.718, 95% CI: 0.651-0.793, P< 0.001], factor 9 (Ala, Pro, C4DC) [OR:1.883, 95% CI: 1.669-2.124, P<0.001], factor 10 (Glu, Asp, C18:2OH) [OR:1.132, 95% CI: 1.032-1.242, P= 0.009], factor 11 (citrulline, ornithine) [OR:0.862, 95% CI: 0.778-0.955, P= 0.004] and 13 (C18OH, C18:1 OH) [OR: 1.242, 95% CI: 1.042-1.480, P= 0.016] were independently correlated with metabolic syndrome. CONCLUSION Change in amino acid, and acylcarnitines profiles were seen in patients with MetS. Moreover, the alteration in the circulating levels of amino acids and acylcarnitines is along with an increase in MetS component number. It also seems that amino acid and acylcarnitines profiles can provide valuable information on evaluating and monitoring MetS risk. However, further studies are needed to establish this concept.
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Affiliation(s)
- Hananeh Taghizadeh
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Solaleh Emamgholipour
- Department of Clinical Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Shaghayegh Hosseinkhani
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran, Iran
| | - Negar Rezaei
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Arezou Dilmaghani-Marand
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Erfan Ghasemi
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Nekoo Panahi
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hojat Dehghanbanadaki
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Niloufar Najjar
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mojgan Asadi
- Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen khoshniat
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- *Correspondence: Farideh Razi,
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30
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Zhang W, Wan Z, Li X, Li R, Luo L, Song Z, Miao Y, Li Z, Wang S, Shan Y, Li Y, Chen B, Zhen H, Sun Y, Fang M, Ding J, Yan Y, Zong Y, Wang Z, Zhang W, Yang H, Yang S, Wang J, Jin X, Wang R, Chen P, Min J, Zeng Y, Li T, Xu X, Nie C. A population-based study of precision health assessments using multi-omics network-derived biological functional modules. Cell Rep Med 2022; 3:100847. [PMID: 36493776 PMCID: PMC9798030 DOI: 10.1016/j.xcrm.2022.100847] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Revised: 10/05/2022] [Accepted: 11/11/2022] [Indexed: 12/13/2022]
Abstract
Recent technological advances in multi-omics and bioinformatics provide an opportunity to develop precision health assessments, which require big data and relevant bioinformatic methods. Here we collect multi-omics data from 4,277 individuals. We calculate the correlations between pairwise features from cross-sectional data and then generate 11 biological functional modules (BFMs) in males and 12 BFMs in females using a community detection algorithm. Using the features in the BFM associated with cardiometabolic health, carotid plaques can be predicted accurately in an independent dataset. We developed a model by comparing individual data with the health baseline in BFMs to assess health status (BFM-ash). Then we apply the model to chronic patients and modify the BFM-ash model to assess the effects of consuming grape seed extract as a dietary supplement. Finally, anomalous BFMs are identified for each subject. Our BFMs and BFM-ash model have huge prospects for application in precision health assessment.
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Affiliation(s)
- Wei Zhang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Ziyun Wan
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Xiaoyu Li
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China
| | - Rui Li
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Lihua Luo
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China
| | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yu Miao
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China
| | - Zhiming Li
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Shiyu Wang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,BGI Education Center, University of the Chinese Academy of Sciences, Shenzhen 518083, China
| | - Ying Shan
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Yan Li
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Bangwei Chen
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Hefu Zhen
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Yuzhe Sun
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Mingyan Fang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Jiahong Ding
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Yizhen Yan
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Yang Zong
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Zhen Wang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Wenwei Zhang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Huanming Yang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,James D. Watson Institute of Genome Sciences, Hangzhou 310058, China
| | - Shuang Yang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Jian Wang
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,James D. Watson Institute of Genome Sciences, Hangzhou 310058, China
| | - Xin Jin
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Ru Wang
- School of Exercise and Health, Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, Shanghai University of Sport, Shanghai, China
| | - Peijie Chen
- School of Exercise and Health, Shanghai Frontiers Science Research Base of Exercise and Metabolic Health, Shanghai University of Sport, Shanghai, China
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China
| | - Tao Li
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Xun Xu
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China
| | - Chao Nie
- BGI-Shenzhen, Shenzhen 518083, China,China National GeneBank, Shenzhen 518120, China,Corresponding author
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Circulating direct infusion MS and NMR metabolomic profiles of post-gonadectomy kittens with or without additional dietary choline supplementation. Br J Nutr 2022:1-20. [DOI: 10.1017/s0007114522003385] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022]
Abstract
Abstract
Choline is beneficial for energy metabolism and growth in various species. Choline may work similarly in kittens at risk of obesity. Direct infusion MS (Di-MS) and NMR spectroscopy were used to investigate the metabolomic signatures of kittens supplemented with or without additional dietary choline for 12 weeks. Fifteen intact male kittens consumed a base diet (3310 mg choline/kg DM) to their daily metabolisable energy requirement (DER) over an 11-week acclimation. Kittens were gonadectomised and assigned, based on body weight, to the base diet (CONTROL, n 7) or the base diet with 300 mg/kgBW0·75 additional choline as choline chloride (CHOLINE, n 8) and offered three times their individual energy requirement divided into three meals. At weeks −1 and 12, fasted blood was sampled and serum analysed for 130 metabolites via Di-MS and fifty-one metabolites via NMR spectroscopy. Changes in fasted metabolites were assessed using a repeated-measures GLIMMIX procedure with time and group as fixed effects, and time as a repeated measure. Metabolites of one-carbon metabolism and lipids increased, and medium-chain acyl carnitines decreased from week −1 to 12 for CHOLINE (P < 0·05), but not CONTROL (P > 0·05). Increases in amino acid, biogenic amine and organic compound concentrations were observed in both groups (P < 0·05). The results suggest impacts of dietary choline at greater intakes than currently recommended on one-carbon metabolism and fatty acid oxidation, and these may promote healthy growth in post-gonadectomy kittens.
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Hameed A, Adamska-Patruno E, Godzien J, Czajkowski P, Miksza U, Pietrowska K, Fiedorczuk J, Moroz M, Bauer W, Sieminska J, Górska M, Krętowski AJ, Ciborowski M. The Beneficial Effect of Cinnamon and Red Capsicum Intake on Postprandial Changes in Plasma Metabolites Evoked by a High-Carbohydrate Meal in Men with Overweight/Obesity. Nutrients 2022; 14:nu14204305. [PMID: 36296989 PMCID: PMC9610620 DOI: 10.3390/nu14204305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2022] [Revised: 10/05/2022] [Accepted: 10/10/2022] [Indexed: 01/24/2023] Open
Abstract
The relationship of high-carbohydrate (HC) meal intake to metabolic syndrome is still not fully explained. Metabolomics has the potential to indicate metabolic pathways altered by HC meals, which may improve our knowledge regarding the mechanisms by which HC meals may contribute to metabolic syndrome development. The fasting and postprandial metabolic response to HC or normo-carbohydrate (NC) meals with/without cinnamon + capsicum intake was evaluated using untargeted metabolomics and compared between normal-weight (NW) and overweight/obese (OW/OB) healthy men. Healthy male participants (age-matched) were divided into two groups (12 subjects per group). One was composed of men with normal weight (NW) and the other of men with overweight/obesity (OW/OB). On separate visits (with 2-3 week intervals), the participants received standardized HC or NC meals (89% or 45% carbohydrates, respectively). Fasting (0 min) and postprandial (30, 60, 120, 180 min) blood were collected for untargeted plasma metabolomics. Based on each metabolic feature's intensity change in time, the area under the curve (AUC) was calculated. Obtained AUCs were analyzed using multivariate statistics. Several metabolic pathways were found dysregulated after an HC meal in people from the OW/OB group but not the NW group. The consumption of HC meals by people with overweight/obesity led to a substantial increase in AUC, mainly for metabolites belonging to phospholipids and fatty acid amides. The opposite was observed for selected sphingolipids. The intake of cinnamon and capsicum normalized the concentration of selected altered metabolites induced by the intake of HC meals. A HC meal may induce an unfavourable postprandial metabolic response in individuals with overweight/obesity, and such persons should avoid HC meals.
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Affiliation(s)
- Ahsan Hameed
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Edyta Adamska-Patruno
- Department of Nutriomics, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Support Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Joanna Godzien
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Przemyslaw Czajkowski
- Department of Nutriomics, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Support Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Urszula Miksza
- Department of Nutriomics, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Support Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Karolina Pietrowska
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Joanna Fiedorczuk
- Department of Nutriomics, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Support Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Monika Moroz
- Department of Nutriomics, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Support Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Witold Bauer
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Julia Sieminska
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
| | - Maria Górska
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, ul. M. Sklodowskiej-Curie 24 A, 15-276 Bialystok, Poland
| | - Adam Jacek Krętowski
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Department of Nutriomics, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Support Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Department of Endocrinology, Diabetology and Internal Medicine, Medical University of Bialystok, ul. M. Sklodowskiej-Curie 24 A, 15-276 Bialystok, Poland
| | - Michal Ciborowski
- Metabolomics Laboratory, Clinical Research Centre, Medical University of Bialystok, M. Sklodowskiej-Curie 24a, 15-276 Bialystok, Poland
- Correspondence:
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Multi-omic phenotyping reveals host-microbe responses to bariatric surgery, glycaemic control and obesity. COMMUNICATIONS MEDICINE 2022; 2:127. [PMID: 36217535 PMCID: PMC9546886 DOI: 10.1038/s43856-022-00185-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 09/12/2022] [Indexed: 11/05/2022] Open
Abstract
Background Resolution of type 2 diabetes (T2D) is common following bariatric surgery, particularly Roux-en-Y gastric bypass. However, the underlying mechanisms have not been fully elucidated. Methods To address this we compare the integrated serum, urine and faecal metabolic profiles of participants with obesity ± T2D (n = 80, T2D = 42) with participants who underwent Roux-en-Y gastric bypass or sleeve gastrectomy (pre and 3-months post-surgery; n = 27), taking diet into account. We co-model these data with shotgun metagenomic profiles of the gut microbiota to provide a comprehensive atlas of host-gut microbe responses to bariatric surgery, weight-loss and glycaemic control at the systems level. Results Here we show that bariatric surgery reverses several disrupted pathways characteristic of T2D. The differential metabolite set representative of bariatric surgery overlaps with both diabetes (19.3% commonality) and body mass index (18.6% commonality). However, the percentage overlap between diabetes and body mass index is minimal (4.0% commonality), consistent with weight-independent mechanisms of T2D resolution. The gut microbiota is more strongly correlated to body mass index than T2D, although we identify some pathways such as amino acid metabolism that correlate with changes to the gut microbiota and which influence glycaemic control. Conclusion We identify multi-omic signatures associated with responses to surgery, body mass index, and glycaemic control. Improved understanding of gut microbiota - host co-metabolism may lead to novel therapies for weight-loss or diabetes. However, further experiments are required to provide mechanistic insight into the role of the gut microbiota in host metabolism and establish proof of causality. Weight-loss surgery is a highly effective treatment of type 2 diabetes in people with obesity. Interestingly, the improvement in diabetes after weight-loss surgery occurs before any significant weight-loss. Through better understanding of this metabolic improvement, weight-loss surgery provides a unique avenue to identify novel ways of treating diabetes and obesity. Here we combine measurements of metabolism, gut bacteria and diet in people with obesity, with or without type 2 diabetes and in patients before and after weight-loss surgery. We have used these data to identify changes associated with weight-loss surgery, obesity and diabetes. Improved understanding of the mechanisms behind these changes, including how changes to gut bacteria influence metabolism, may lead to new treatments for weight-loss or diabetes. Penney et al. conduct microbial and metabolic profiling in people with obesity, with or without type 2 diabetes, undergoing two types of bariatric surgery. Integrative analysis identifies multi-omic signatures associated with response to surgery, body mass index, and glycaemic control.
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Li HY, Huang SY, Xiong RG, Wu SX, Zhou DD, Saimaiti A, Luo M, Zhu HL, Li HB. Anti-Obesity Effect of Theabrownin from Dark Tea in C57BL/6J Mice Fed a High-Fat Diet by Metabolic Profiles through Gut Microbiota Using Untargeted Metabolomics. Foods 2022; 11:foods11193000. [PMID: 36230076 PMCID: PMC9564053 DOI: 10.3390/foods11193000] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2022] [Revised: 09/21/2022] [Accepted: 09/22/2022] [Indexed: 11/25/2022] Open
Abstract
The epidemic of obesity is a serious public health problem. In this study, the effect of theabrownin from dark tea on obesity was evaluated by biochemical tests and nuclear magnetic resonance in C57BL/6J mice fed a high-fat diet. A mixture of antibiotics was used to deplete gut microbiota and then fecal microbiota transplant was used to restore gut microbiota. Untargeted metabolomics was used to reveal the effects of theabrownin on metabolic profiles through gut microbiota. The results showed that theabrownin significantly reduced body weight gain (83.0%) and body fat accumulation (30.29%) without affecting appetite. Also, theabrownin promoted lipid clearance with a hepatoprotective effect. The extra antibiotics disrupted the regulation of theabrownin on weight control while fecal microbiota transplant restored the beneficial regulation. That is, gut microbiota was important for theabrownin to reduce body weight gain. The untargeted metabolomics indicated that 18 metabolites were related to the anti-obesity effect of theabrownin mediated by gut microbiota. Furthermore, phenylalanine metabolism, histidine metabolism, as well as protein digestion and absorption pathway played a role in the anti-obesity of theabrownin. Our findings suggested that theabrownin significantly alleviated obesity via gut microbiota-related metabolic pathways, and theabrownin could be used for the prevention and treatment of obesity.
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35
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Evidence of a genetically driven metabolomic signature in actively inflamed Crohn's disease. Sci Rep 2022; 12:14101. [PMID: 35982195 PMCID: PMC9388636 DOI: 10.1038/s41598-022-18178-9] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 08/08/2022] [Indexed: 11/09/2022] Open
Abstract
Crohn's disease (CD) is characterised by chronic inflammation. We aimed to identify a relationship between plasma inflammatory metabolomic signature and genomic data in CD using blood plasma metabolic profiles. Proton NMR spectroscopy were achieved for 228 paediatric CD patients. Regression (OPLS) modelling and machine learning (ML) approaches were independently applied to establish the metabolic inflammatory signature, which was correlated against gene-level pathogenicity scores generated for all patients and functional enrichment was analysed. OPLS modelling of metabolomic spectra from unfasted patients revealed distinctive shifts in plasma metabolites corresponding to regions of the spectrum assigned to N-acetyl glycoprotein, glycerol and phenylalanine that were highly correlated (R2 = 0.62) with C-reactive protein levels. The same metabolomic signature was independently identified using ML to predict patient inflammation status. Correlation of the individual peaks comprising this metabolomic signature of inflammation with pathogenic burden across 15,854 unselected genes identified significant enrichment for genes functioning within 'intrinsic component of membrane' (p = 0.003) and 'inflammatory bowel disease (IBD)' (p = 0.003). The seven genes contributing IBD enrichment are critical regulators of pro-inflammatory signaling. Overall, a metabolomic signature of inflammation can be detected from blood plasma in CD. This signal is correlated with pathogenic mutation in pro-inflammatory immune response genes.
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Hosseinkhani S, Salari P, Bandarian F, Asadi M, Shirani S, Najjar N, Dehghanbanadaki H, Pasalar P, Razi F. Circulating amino acids and acylcarnitines correlated with different CAC score ranges in diabetic postmenopausal women using LC-MS/MS based metabolomics approach. BMC Endocr Disord 2022; 22:186. [PMID: 35864499 PMCID: PMC9306187 DOI: 10.1186/s12902-022-01073-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 06/06/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Diabetes mellitus (DM) and its cardiovascular disease (CVD) complication are among the most frequent causes of death worldwide. However, the metabolites linking up diabetes and CVD are less understood. In this study, we aimed to evaluate serum acylcarnitines and amino acids in postmenopausal women suffering from diabetes with different severity of CVD and compared them with healthy controls. METHODS Through a cross-sectional study, samples were collected from postmenopausal women without diabetes and CVD as controls (n = 20), patients with diabetes and without CVD (n = 16), diabetes with low risk of CVD (n = 11), and diabetes with a high risk of CVD (n = 21) referred for CT angiography for any reason. Metabolites were detected by a targeted approach using LC-MS/MS and metabolic -alterations were assessed by applying multivariate statistical analysis. The diagnostic ability of discovered metabolites based on multivariate statistical analysis was evaluated by ROC curve analysis. RESULTS The study included women aged from 50-80 years with 5-30 years of menopause. The relative concentration of C14:1, C14:2, C16:1, C18:1, and C18:2OH acylcarnitines decreased and C18 acylcarnitine and serine increased in diabetic patients compared to control. Besides, C16:1 and C18:2OH acylcarnitines increased in high-risk CVD diabetic patients compared to no CVD risk diabetic patients. CONCLUSION Dysregulation of serum acylcarnitines and amino acids profile correlated with different CAC score ranges in diabetic postmenopausal women. (Ethic approval No: IR.TUMS.EMRI.REC.1399.062).
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Affiliation(s)
- Shaghayegh Hosseinkhani
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Clinical Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Pooneh Salari
- Medical Ethics and History of Medicine Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Bandarian
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mojgan Asadi
- Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shapour Shirani
- Imaging Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Niloufar Najjar
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hojat Dehghanbanadaki
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Parvin Pasalar
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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Chen J, Qian D, Wang Z, Sun Y, Sun B, Zhou X, Hu L, Shan A, Ma Q. Threonine supplementation prevents the development of fat deposition in mice fed a high-fat diet. Food Funct 2022; 13:7772-7780. [PMID: 35766226 DOI: 10.1039/d2fo01201d] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Obesity is the main factor involved in the onset of many diseases. Threonine supplementation has been demonstrated to reduce fat mass and serum triglycerides in already obese mice. However, it is unclear whether threonine could inhibit the development of obesity in mice without previous high-fat diet induction. In the present study, mice were fed a chow diet (CD) or a high-fat diet (HFD), supplemented or not with threonine (3.0% in drinking water) for 15 weeks. Results showed that mice subjected to chronic threonine supplementation showed decreased body weight, epididymal white adipose tissue weight, serum low-density lipoprotein cholesterol, and total cholesterol in comparison with HFD-fed mice. In the epididymal adipose tissue, gene expressions of sterol regulatory element-binding protein 1c and fatty acid synthase were up-regulated, while hormone sensitive lipase, adiponectin and fibroblast growth factor 21 were down-regulated. In the liver tissue, gene expressions of sirtuin1, adenosine monophosphate-activated protein kinase and peroxisome proliferator activated receptor γ co-activator 1α were up-regulated by threonine supplementation in HFD-fed mice. These results suggest that long-term threonine supplementation inhibited fat mass and improved lipid metabolism, making it a potential agent to prevent the development of diet-induced obesity.
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Affiliation(s)
- Jiayi Chen
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Dali Qian
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Zhishen Wang
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Yutong Sun
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Bo Sun
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Xinbo Zhou
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Linlin Hu
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Anshan Shan
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
| | - Qingquan Ma
- Institute of Animal Nutrition, Northeast Agricultural University, Harbin, 150030, China.
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Dambrova M, Makrecka-Kuka M, Kuka J, Vilskersts R, Nordberg D, Attwood MM, Smesny S, Sen ZD, Guo AC, Oler E, Tian S, Zheng J, Wishart DS, Liepinsh E, Schiöth HB. Acylcarnitines: Nomenclature, Biomarkers, Therapeutic Potential, Drug Targets, and Clinical Trials. Pharmacol Rev 2022; 74:506-551. [PMID: 35710135 DOI: 10.1124/pharmrev.121.000408] [Citation(s) in RCA: 118] [Impact Index Per Article: 59.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Acylcarnitines are fatty acid metabolites that play important roles in many cellular energy metabolism pathways. They have historically been used as important diagnostic markers for inborn errors of fatty acid oxidation and are being intensively studied as markers of energy metabolism, deficits in mitochondrial and peroxisomal β -oxidation activity, insulin resistance, and physical activity. Acylcarnitines are increasingly being identified as important indicators in metabolic studies of many diseases, including metabolic disorders, cardiovascular diseases, diabetes, depression, neurologic disorders, and certain cancers. The US Food and Drug Administration-approved drug L-carnitine, along with short-chain acylcarnitines (acetylcarnitine and propionylcarnitine), is now widely used as a dietary supplement. In light of their growing importance, we have undertaken an extensive review of acylcarnitines and provided a detailed description of their identity, nomenclature, classification, biochemistry, pathophysiology, supplementary use, potential drug targets, and clinical trials. We also summarize these updates in the Human Metabolome Database, which now includes information on the structures, chemical formulae, chemical/spectral properties, descriptions, and pathways for 1240 acylcarnitines. This work lays a solid foundation for identifying, characterizing, and understanding acylcarnitines in human biosamples. We also discuss the emerging opportunities for using acylcarnitines as biomarkers and as dietary interventions or supplements for many wide-ranging indications. The opportunity to identify new drug targets involved in controlling acylcarnitine levels is also discussed. SIGNIFICANCE STATEMENT: This review provides a comprehensive overview of acylcarnitines, including their nomenclature, structure and biochemistry, and use as disease biomarkers and pharmaceutical agents. We present updated information contained in the Human Metabolome Database website as well as substantial mapping of the known biochemical pathways associated with acylcarnitines, thereby providing a strong foundation for further clarification of their physiological roles.
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Affiliation(s)
- Maija Dambrova
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Marina Makrecka-Kuka
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Janis Kuka
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Reinis Vilskersts
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Didi Nordberg
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Misty M Attwood
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Stefan Smesny
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Zumrut Duygu Sen
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - An Chi Guo
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Eponine Oler
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Siyang Tian
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Jiamin Zheng
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - David S Wishart
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Edgars Liepinsh
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Helgi B Schiöth
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
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Hosseinkhani S, Arjmand B, Dilmaghani-Marand A, Mohammadi Fateh S, Dehghanbanadaki H, Najjar N, Alavi-Moghadam S, Ghodssi-Ghassemabadi R, Nasli-Esfahani E, Farzadfar F, Larijani B, Razi F. Targeted metabolomics analysis of amino acids and acylcarnitines as risk markers for diabetes by LC-MS/MS technique. Sci Rep 2022; 12:8418. [PMID: 35589736 PMCID: PMC9119932 DOI: 10.1038/s41598-022-11970-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 04/27/2022] [Indexed: 11/29/2022] Open
Abstract
Diabetes is a common chronic disease affecting millions of people worldwide. It underlies various complications and imposes many costs on individuals and society. Discovering early diagnostic biomarkers takes excellent insight into preventive plans and the best use of interventions. Therefore, in the present study, we aimed to evaluate the association between the level of amino acids and acylcarnitines and diabetes to develop diabetes predictive models. Using the targeted LC-MS/MS technique, we analyzed fasting plasma samples of 206 cases and 206 controls that were matched by age, sex, and BMI. The association between metabolites and diabetes was evaluated using univariate and multivariate regression analysis with adjustment for systolic and diastolic blood pressure and lipid profile. To deal with multiple comparisons, factor analysis was used. Participants' average age and BMI were 61.6 years, 28.9 kg/m2, and 55% were female. After adjustment, Factor 3 (tyrosine, valine, leucine, methionine, tryptophan, phenylalanine), 5 (C3DC, C5, C5OH, C5:1), 6 (C14OH, C16OH, C18OH, C18:1OH), 8 (C2, C4OH, C8:1), 10 (alanine, proline) and 11 (glutamic acid, C18:2OH) were positively associated with diabetes. Inline, factor 9 (C4DC, serine, glycine, threonine) and 12 (citrulline, ornithine) showed a reverse trend. Some amino acids and acylcarnitines were found as potential risk markers for diabetes incidents that reflected the disturbances in the several metabolic pathways among the diabetic population and could be targeted to prevent, diagnose, and treat diabetes.
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Affiliation(s)
- Shaghayegh Hosseinkhani
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Clinical Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran, Iran
| | - Arezou Dilmaghani-Marand
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sahar Mohammadi Fateh
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hojat Dehghanbanadaki
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Niloufar Najjar
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sepideh Alavi-Moghadam
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Ensieh Nasli-Esfahani
- Diabetes 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
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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40
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Saben JL, Sims CR, Pack L, Lan R, Børsheim E, Andres A. Infant intakes of human milk branched chain amino acids are negatively associated with infant growth and influenced by maternal body mass index. Pediatr Obes 2022; 17:e12876. [PMID: 34913264 PMCID: PMC9269030 DOI: 10.1111/ijpo.12876] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2021] [Revised: 10/28/2021] [Accepted: 11/15/2021] [Indexed: 11/28/2022]
Abstract
BACKGROUND Branched-chain amino acids (BCAAs: isoleucine, leucine, and valine) and aromatic amino acids (AAAs: phenylalanine and tyrosine) are hypothesized to influence early-life obesity risk. OBJECTIVE To assess HM free amino acid (AA) concentrations and infant intakes of HM AAs from women with obesity (OB) compared to those with normal weight (NW) and determine the relationships between HM AA consumption and infant growth. METHODS HM samples were collected at 0.5 (n = 151), 2 (n = 129), and 6 (n = 93) months postpartum from mothers with NW (body mass index [BMI] = 18.5-24.9 kg/m2 ) and OB (BMI > 30 kg/m2 ). HM AAs were quantified via mass spectrometry. Infant HM intake, anthropometrics and body composition were assessed. Linear mixed-effects models (LMEM) examined the relationships between maternal BMI and HM AA intakes, and HM AA intake and infant growth over the first 6 months postpartum after adjusting for maternal and infant characteristics. RESULTS Maternal BMI was positively associated with infant intakes of isoleucine, leucine, and AAAs across timepoints. HM AA intakes were positively associated with weight-for-length z-score, fat mass index, and fat-free mass index in infants (p < 0.05). CONCLUSIONS Maternal BMI led to differences in HM AA composition, which was associated with infant body composition.
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Affiliation(s)
- Jessica L. Saben
- Arkansas Children’s Nutrition Center, Little Rock, AR,Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR
| | - Clark R. Sims
- Arkansas Children’s Nutrition Center, Little Rock, AR,Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR
| | - Lindsay Pack
- Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR
| | - Renny Lan
- Arkansas Children’s Nutrition Center, Little Rock, AR,Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR
| | - Elisabet Børsheim
- Arkansas Children’s Nutrition Center, Little Rock, AR,Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR
| | - Aline Andres
- Arkansas Children’s Nutrition Center, Little Rock, AR,Department of Pediatrics, University of Arkansas for Medical Sciences, Little Rock, AR
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41
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Depommier C, Everard A, Druart C, Maiter D, Thissen JP, Loumaye A, Hermans MP, Delzenne NM, de Vos WM, Cani PD. Serum metabolite profiling yields insights into health promoting effect of A. muciniphila in human volunteers with a metabolic syndrome. Gut Microbes 2022; 13:1994270. [PMID: 34812127 PMCID: PMC8632301 DOI: 10.1080/19490976.2021.1994270] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/04/2023] Open
Abstract
Reduction of A. muciniphila relative abundance in the gut microbiota is a widely accepted signature associated with obesity-related metabolic disorders. Using untargeted metabolomics profiling of fasting plasma, our study aimed at identifying metabolic signatures associated with beneficial properties of alive and pasteurized A. muciniphila when administrated to a cohort of insulin-resistant individuals with metabolic syndrome. Our data highlighted either shared or specific alterations in the metabolome according to the form of A. muciniphila administered with respect to a control group. Common responses encompassed modulation of amino acid metabolism, characterized by reduced levels of arginine and alanine, alongside several intermediates of tyrosine, phenylalanine, tryptophan, and glutathione metabolism. The global increase in levels of acylcarnitines together with specific modulation of acetoacetate also suggested induction of ketogenesis through enhanced β-oxidation. Moreover, our data pinpointed some metabolites of interest considering their emergence as substantial compounds pertaining to health and diseases in the more recent literature.
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Affiliation(s)
- Clara Depommier
- Metabolism and Nutrition Research Group, Louvain Drug Research Institute, Walloon Excellence in Life Sciences and BIOtechnology (Welbio), UCLouvain, Université Catholique De Louvain, Brussels, Belgium
| | - Amandine Everard
- Metabolism and Nutrition Research Group, Louvain Drug Research Institute, Walloon Excellence in Life Sciences and BIOtechnology (Welbio), UCLouvain, Université Catholique De Louvain, Brussels, Belgium
| | - Céline Druart
- Metabolism and Nutrition Research Group, Louvain Drug Research Institute, Walloon Excellence in Life Sciences and BIOtechnology (Welbio), UCLouvain, Université Catholique De Louvain, Brussels, Belgium
| | - Dominique Maiter
- Pôle Edin, Institut De Recherches Expérimentales Et Cliniques, UCLouvain, Université Catholique De Louvain, Brussels, Belgium,Division of Endocrinology and Nutrition, Cliniques Universitaires St-Luc, Brussels, Belgium
| | - Jean-Paul Thissen
- Pôle Edin, Institut De Recherches Expérimentales Et Cliniques, UCLouvain, Université Catholique De Louvain, Brussels, Belgium,Division of Endocrinology and Nutrition, Cliniques Universitaires St-Luc, Brussels, Belgium
| | - Audrey Loumaye
- Pôle Edin, Institut De Recherches Expérimentales Et Cliniques, UCLouvain, Université Catholique De Louvain, Brussels, Belgium,Division of Endocrinology and Nutrition, Cliniques Universitaires St-Luc, Brussels, Belgium
| | - Michel P. Hermans
- Pôle Edin, Institut De Recherches Expérimentales Et Cliniques, UCLouvain, Université Catholique De Louvain, Brussels, Belgium,Division of Endocrinology and Nutrition, Cliniques Universitaires St-Luc, Brussels, Belgium
| | - Nathalie M. Delzenne
- Metabolism and Nutrition Research Group, Louvain Drug Research Institute, Walloon Excellence in Life Sciences and BIOtechnology (Welbio), UCLouvain, Université Catholique De Louvain, Brussels, Belgium
| | - Willem M. de Vos
- Laboratory of Microbiology, Wageningen University, Wageningen, The Netherland,Human Microbiome Research Program, Faculty of Medicine, University of Helsinki, Helsinki, Finland
| | - Patrice D. Cani
- Metabolism and Nutrition Research Group, Louvain Drug Research Institute, Walloon Excellence in Life Sciences and BIOtechnology (Welbio), UCLouvain, Université Catholique De Louvain, Brussels, Belgium,CONTACT Patrice D. Cani UCLouvain, Université Catholique De Louvain, Ldri, Metabolism and Nutrition Research Group, Av. E. Mounier, 73 Box B1.73.11, B-1200Brussels, Belgium
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Ortiz-Martínez M, González-González M, Martagón AJ, Hlavinka V, Willson RC, Rito-Palomares M. Recent Developments in Biomarkers for Diagnosis and Screening of Type 2 Diabetes Mellitus. Curr Diab Rep 2022; 22:95-115. [PMID: 35267140 PMCID: PMC8907395 DOI: 10.1007/s11892-022-01453-4] [Citation(s) in RCA: 41] [Impact Index Per Article: 20.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 01/27/2022] [Indexed: 11/03/2022]
Abstract
PURPOSE OF REVIEW Diabetes mellitus is a complex, chronic illness characterized by elevated blood glucose levels that occurs when there is cellular resistance to insulin action, pancreatic β-cells do not produce sufficient insulin, or both. Diabetes prevalence has greatly increased in recent decades; consequently, it is considered one of the fastest-growing public health emergencies globally. Poor blood glucose control can result in long-term micro- and macrovascular complications such as nephropathy, retinopathy, neuropathy, and cardiovascular disease. Individuals with diabetes require continuous medical care, including pharmacological intervention as well as lifestyle and dietary changes. RECENT FINDINGS The most common form of diabetes mellitus, type 2 diabetes (T2DM), represents approximately 90% of all cases worldwide. T2DM occurs more often in middle-aged and elderly adults, and its cause is multifactorial. However, its incidence has increased in children and young adults due to obesity, sedentary lifestyle, and inadequate nutrition. This high incidence is also accompanied by an estimated underdiagnosis prevalence of more than 50% worldwide. Implementing successful and cost-effective strategies for systematic screening of diabetes mellitus is imperative to ensure early detection, lowering patients' risk of developing life-threatening disease complications. Therefore, identifying new biomarkers and assay methods for diabetes mellitus to develop robust, non-invasive, painless, highly-sensitive, and precise screening techniques is essential. This review focuses on the recent development of new clinically validated and novel biomarkers as well as the methods for their determination that represent cost-effective alternatives for screening and early diagnosis of T2DM.
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Affiliation(s)
- Margarita Ortiz-Martínez
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
| | - Mirna González-González
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México.
- Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, Nuevo León, México.
| | - Alexandro J Martagón
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
- Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, Nuevo León, México
- Unidad de Investigación de Enfermedades Metabólicas, Instituto Nacional de Ciencias Médicas y Nutrición Salvador Zubirán, México City, México
| | - Victoria Hlavinka
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA
| | - Richard C Willson
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
- Department of Chemical and Biomolecular Engineering, University of Houston, Houston, TX, USA
| | - Marco Rito-Palomares
- Tecnologico de Monterrey, Escuela de Medicina y Ciencias de la Salud, Monterrey, Nuevo León, México
- Tecnologico de Monterrey, The Institute for Obesity Research, Monterrey, Nuevo León, México
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43
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Metabolic Status of Lean and Obese Zucker Rats Based on Untargeted and Targeted Metabolomics Analysis of Serum. Biomedicines 2022; 10:biomedicines10010153. [PMID: 35052832 PMCID: PMC8773868 DOI: 10.3390/biomedicines10010153] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2021] [Revised: 01/04/2022] [Accepted: 01/10/2022] [Indexed: 01/02/2023] Open
Abstract
Obesity is growing worldwide epidemic. Animal models can provide some clues about the etiology, development, prevention, and treatment of obesity. We examined and compared serum metabolites between seven lean (L) and seven obese (O) female Zucker rats to investigate the individual serum metabolic profile. A combination of HPLC-UV, HPLC-ECD, and LC-MS revealed more than 400 peaks. The 50 highest quality peaks were selected as the focus of our study. Untargeted metabolomics analysis showed significantly higher mean peak heights for 20 peaks in L rats, generally distributed randomly, except for a cluster (peaks 44–50) where L showed stable dominancy over O. Only eight peaks were significantly higher in O rats. Peak height ratios between pairs of L and O rats were significantly higher at 199 positions in L rats and at 123 positions in O rats. Targeted metabolomics analysis showed significantly higher levels of methionine, cysteine, tryptophan, kynurenic acid, and cysteine/cystine ratio in L rats and significantly higher levels of cystine and tyrosine in O rats. These results contribute to a better understanding of systemic metabolic perturbations in the obese Zucker rat model, emphasizing the value of both whole metabolome and individual metabolic profiles in the design and interpretation of studies using animal models.
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McMurdie PJ, Stoeva MK, Justice N, Nemchek M, Sieber CMK, Tyagi S, Gines J, Skennerton CT, Souza M, Kolterman O, Eid J. Increased circulating butyrate and ursodeoxycholate during probiotic intervention in humans with type 2 diabetes. BMC Microbiol 2022; 22:19. [PMID: 34996347 PMCID: PMC8742391 DOI: 10.1186/s12866-021-02415-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2021] [Accepted: 12/07/2021] [Indexed: 02/07/2023] Open
Abstract
Background An increasing body of evidence implicates the resident gut microbiota as playing a critical role in type 2 diabetes (T2D) pathogenesis. We previously reported significant improvement in postprandial glucose control in human participants with T2D following 12-week administration of a 5-strain novel probiotic formulation (‘WBF-011’) in a double-blind, randomized, placebo controlled setting (NCT03893422). While the clinical endpoints were encouraging, additional exploratory measurements were needed in order to link the motivating mechanistic hypothesis - increased short-chain fatty acids - with markers of disease. Results Here we report targeted and untargeted metabolomic measurements on fasting plasma (n = 104) collected at baseline and end of intervention. Butyrate and ursodeoxycholate increased among participants randomized to WBF-011, along with compelling trends between butyrate and glycated haemoglobin (HbA1c). In vitro monoculture experiments demonstrated that the formulation’s C. butyricum strain efficiently synthesizes ursodeoxycholate from the primary bile acid chenodeoxycholate during butyrogenic growth. Untargeted metabolomics also revealed coordinated decreases in intermediates of fatty acid oxidation and bilirubin, potential secondary signatures for metabolic improvement. Finally, improvement in HbA1c was limited almost entirely to participants not using sulfonylurea drugs. We show that these drugs can inhibit growth of formulation strains in vitro. Conclusion To our knowledge, this is the first description of an increase in circulating butyrate or ursodeoxycholate following a probiotic intervention in humans with T2D, adding support for the possibility of a targeted microbiome-based approach to assist in the management of T2D. The efficient synthesis of UDCA by C. butyricum is also likely of interest to investigators of its use as a probiotic in other disease settings. The potential for inhibitory interaction between sulfonylurea drugs and gut microbiota should be considered carefully in the design of future studies. Supplementary Information The online version contains supplementary material available at 10.1186/s12866-021-02415-8.
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Affiliation(s)
- Paul J McMurdie
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA.
| | - Magdalena K Stoeva
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | - Nicholas Justice
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | - Madeleine Nemchek
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | | | - Surabhi Tyagi
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | - Jessica Gines
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | | | - Michael Souza
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | - Orville Kolterman
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
| | - John Eid
- Pendulum Therapeutics, Inc, 933 20th Street, San Francisco, CA, 94107, USA
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An Z, Zheng D, Wei D, Jiang D, Xing X, Liu C. Correlation between Acylcarnitine and Peripheral Neuropathy in Type 2 Diabetes Mellitus. J Diabetes Res 2022; 2022:8115173. [PMID: 35224109 PMCID: PMC8872664 DOI: 10.1155/2022/8115173] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/07/2021] [Revised: 01/14/2022] [Accepted: 02/08/2022] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVE In patients with type 2 diabetes mellitus (T2DM), it is unknown whether acylcarnitine changes in the patient's plasma as diabetic peripheral neuropathy (DPN) occurs. The purpose of the present study was to investigate the correlation between acylcarnitines and DPN in Chinese patients with T2DM. METHODS A total of 508 patients admitted to the First Affiliated Hospital of Jinzhou Medical University were included in this study, and all of whom were hospitalized for T2DM from January 2018 to December 2020. The diagnostic criteria for DPN were based on the 2017 Chinese Guidelines for the Prevention of Type 2 Diabetes. The contents of 25 acylcarnitine metabolites in fasting blood were determined by mass spectrometry. The measured acylcarnitines were classified by factor analysis, and the factors were extracted. To determine the correlation between acylcarnitines and DPN, binary logistic regression analysis was applied. RESULTS Among the 508 T2DM patients, 270 had DPN. Six factors were extracted from 25 acylcarnitines, and the cumulative contribution rate of variance was 61.02%. After the adjustment for other potential confounding factors, such as other carnitines and conventional risk factors, Factor 2 was positively associated with an increased risk of DPN (OR: 1.38, 95% CI: 1.13-1.69). Factor 2 contained acetylcarnitine (C2), propionylcarnitine (C3), butylcarnitine (C4), and isovalerylcarnitine (C5). CONCLUSIONS Plasma levels of short-chain acylcarnitines (C2, C3, C4, and C5) were positively associated with DPN risk.
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Affiliation(s)
- Zhenni An
- Department of Endocrinology, First Affiliated Hospital of Jinzhou Medical University, 121001, China
| | - Danmeng Zheng
- Department of Endocrinology, First Affiliated Hospital of Jinzhou Medical University, 121001, China
| | - Dongzhuo Wei
- Department of Clinical Discipline of Chinese and Western Integrative Medicine, Liaoning University of Traditional Chinese Medicine, 110847, China
| | - Dingwen Jiang
- Department of Endocrinology, First Affiliated Hospital of Jinzhou Medical University, 121001, China
| | - Xuejiao Xing
- Department of Endocrinology, First Affiliated Hospital of Jinzhou Medical University, 121001, China
| | - Chang Liu
- Department of Endocrinology, First Affiliated Hospital of Jinzhou Medical University, 121001, China
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His M, Viallon V, Dossus L, Schmidt JA, Travis RC, Gunter MJ, Overvad K, Kyrø C, Tjønneland A, Lécuyer L, Rothwell JA, Severi G, Johnson T, Katzke V, Schulze MB, Masala G, Sieri S, Panico S, Tumino R, Macciotta A, Boer JMA, Monninkhof EM, Olsen KS, Nøst TH, Sandanger TM, Agudo A, Sánchez MJ, Amiano P, Colorado-Yohar SM, Ardanaz E, Vidman L, Winkvist A, Heath AK, Weiderpass E, Huybrechts I, Rinaldi S. Lifestyle correlates of eight breast cancer-related metabolites: a cross-sectional study within the EPIC cohort. BMC Med 2021; 19:312. [PMID: 34886862 PMCID: PMC8662901 DOI: 10.1186/s12916-021-02183-2] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 11/09/2021] [Indexed: 12/29/2022] Open
Abstract
BACKGROUND Metabolomics is a promising molecular tool for identifying novel etiological pathways leading to cancer. In an earlier prospective study among pre- and postmenopausal women not using exogenous hormones, we observed a higher risk of breast cancer associated with higher blood concentrations of one metabolite (acetylcarnitine) and a lower risk associated with higher blood concentrations of seven others (arginine, asparagine, phosphatidylcholines (PCs) aa C36:3, ae C34:2, ae C36:2, ae C36:3, and ae C38:2). METHODS To identify determinants of these breast cancer-related metabolites, we conducted a cross-sectional analysis to identify their lifestyle and anthropometric correlates in 2358 women, who were previously included as controls in case-control studies nested within the European Prospective Investigation into Cancer and Nutrition cohort and not using exogenous hormones at blood collection. Associations of each metabolite concentration with 42 variables were assessed using linear regression models in a discovery set of 1572 participants. Significant associations were evaluated in a validation set (n = 786). RESULTS For the metabolites previously associated with a lower risk of breast cancer, concentrations of PCs ae C34:2, C36:2, C36:3, and C38:2 were negatively associated with adiposity and positively associated with total and saturated fat intakes. PC ae C36:2 was also negatively associated with alcohol consumption and positively associated with two scores reflecting adherence to a healthy lifestyle. Asparagine concentration was negatively associated with adiposity. Arginine and PC aa C36:3 concentrations were not associated to any of the factors examined. For the metabolite previously associated with a higher risk of breast cancer, acetylcarnitine, a positive association with age was observed. CONCLUSIONS These associations may indicate possible mechanisms underlying associations between lifestyle and anthropometric factors, and risk of breast cancer. Further research is needed to identify potential non-lifestyle correlates of the metabolites investigated.
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Affiliation(s)
- Mathilde His
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Vivian Viallon
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Laure Dossus
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Julie A Schmidt
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Marc J Gunter
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Kim Overvad
- Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Cecilie Kyrø
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Anne Tjønneland
- Danish Cancer Society Research Center, Copenhagen, Denmark
- Department of Public Health, Section of Environmental Health, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lucie Lécuyer
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
| | - Joseph A Rothwell
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
| | - Gianluca Severi
- Université Paris-Saclay, UVSQ, Inserm, CESP U1018, "Exposome and Heredity" team, Gustave Roussy, Villejuif, France
- Department of Statistics, Computer Science, Applications "G. Parenti", University of Florence, Florence, Italy
| | - Theron Johnson
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Verena Katzke
- Department of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Potsdam, Germany
| | - Giovanna Masala
- Institute for Cancer Research, Prevention and Clinical Network (ISPRO), Florence, Italy
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Instituto Nazionale dei Tumori di Milano, Milan, Italy
| | - Salvatore Panico
- Dipartimento Di Medicina Clinica E Chirurgia, Federico Ii University, Naples, Italy
| | - Rosario Tumino
- Cancer Registry and Histopathology Department, Provincial Health Authority (ASP 7) Ragusa, Ragusa, Italy
| | - Alessandra Macciotta
- Department of Clinical and Biological Sciences, University of Turin, Turin, Italy
| | - Jolanda M A Boer
- Center for Nutrition, Prevention, and Health Services, National Institute for Public Health and the Environment (RIVM), Bilthoven, 3720, BA, the Netherlands
| | - Evelyn M Monninkhof
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, the Netherlands
| | - Karina Standahl Olsen
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Therese H Nøst
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Torkjel M Sandanger
- Department of Community Medicine, Faculty of Health Sciences, UiT The Arctic University of Norway, NO-9037, Tromsø, Norway
| | - Antonio Agudo
- Unit of Nutrition and Cancer, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Nutrition and Cancer Group; Epidemiology, Public Health, Cancer Prevention and Palliative Care Program; Bellvitge Biomedical Research Institute - IDIBELL, L'Hospitalet de Llobregat, Spain
| | - Maria-Jose Sánchez
- Escuela Andaluza de Salud Pública (EASP), Granada, Spain
- Instituto de Investigación Biosanitaria ibs.GRANADA, Granada, Spain
- Centro de Investigación Biomédica en Red de Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Preventive Medicine and Public Health, University of Granada, Granada, Spain
| | - Pilar Amiano
- Ministry of Health of the Basque Government, Sub-Directorate for Public Health and Addictions of Gipuzkoa, San Sebastián, Spain
- Biodonostia Health Research Institute, Group of Epidemiology of Chronic and Communicable Diseases, San Sebastián, Spain
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
| | - Sandra M Colorado-Yohar
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, IMIB-Arrixaca, Murcia, Spain
- Research Group on Demography and Health, National Faculty of Public Health, University of Antioquia, Medellín, Colombia
| | - Eva Ardanaz
- CIBER Epidemiology and Public Health (CIBERESP), Instituto de Salud Carlos III (ISCIII), Madrid, Spain
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
| | - Linda Vidman
- Department of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden
| | - Anna Winkvist
- Sustainable Health, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Alicia K Heath
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - Elisabete Weiderpass
- International Agency for Research on Cancer (IARC/WHO), Office of the Director, Lyon, France
| | - Inge Huybrechts
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France
| | - Sabina Rinaldi
- International Agency for Research on Cancer (IARC/WHO), Nutrition and Metabolism Branch, 150 cours Albert Thomas, 69372, CEDEX 08, Lyon, France.
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Liu KH, Owens JA, Saeedi B, Cohen CE, Bellissimo MP, Naudin C, Darby T, Druzak S, Maner-Smith K, Orr M, Hu X, Fernandes J, Camacho MC, Hunter-Chang S, VanInsberghe D, Ma C, Ganesh T, Yeligar SM, Uppal K, Go YM, Alvarez JA, Vos MB, Ziegler TR, Woodworth MH, Kraft CS, Jones RM, Ortlund E, Neish AS, Jones DP. Microbial metabolite delta-valerobetaine is a diet-dependent obesogen. Nat Metab 2021; 3:1694-1705. [PMID: 34931082 PMCID: PMC8711632 DOI: 10.1038/s42255-021-00502-8] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/24/2020] [Accepted: 11/04/2021] [Indexed: 12/17/2022]
Abstract
Obesity and obesity-related metabolic disorders are linked to the intestinal microbiome. However, the causality of changes in the microbiome-host interaction affecting energy metabolism remains controversial. Here, we show the microbiome-derived metabolite δ-valerobetaine (VB) is a diet-dependent obesogen that is increased with phenotypic obesity and is correlated with visceral adipose tissue mass in humans. VB is absent in germ-free mice and their mitochondria but present in ex-germ-free conventionalized mice and their mitochondria. Mechanistic studies in vivo and in vitro show VB is produced by diverse bacterial species and inhibits mitochondrial fatty acid oxidation through decreasing cellular carnitine and mitochondrial long-chain acyl-coenzyme As. VB administration to germ-free and conventional mice increases visceral fat mass and exacerbates hepatic steatosis with a western diet but not control diet. Thus, VB provides a molecular target to understand and potentially manage microbiome-host symbiosis or dysbiosis in diet-dependent obesity.
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Affiliation(s)
- Ken H Liu
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Joshua A Owens
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Bejan Saeedi
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Catherine E Cohen
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Moriah P Bellissimo
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Crystal Naudin
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Trevor Darby
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Samuel Druzak
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Kristal Maner-Smith
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Michael Orr
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Xin Hu
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Jolyn Fernandes
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Mary Catherine Camacho
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Sarah Hunter-Chang
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - David VanInsberghe
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Chunyu Ma
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Thota Ganesh
- Department of Pharmacology and Chemical Biology, Emory University School of Medicine, Atlanta, GA, USA
| | - Samantha M Yeligar
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Atlanta Veterans Affairs Health Care System, Decatur, GA, USA
| | - Karan Uppal
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Young-Mi Go
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Jessica A Alvarez
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Miriam B Vos
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Thomas R Ziegler
- Division of Endocrinology, Metabolism, and Lipids, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Michael H Woodworth
- Division of Infectious Disease, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Colleen S Kraft
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
- Division of Infectious Disease, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Rheinallt M Jones
- Department of Pediatrics, Emory University School of Medicine, Atlanta, GA, USA
| | - Eric Ortlund
- Department of Biochemistry, Emory University School of Medicine, Atlanta, GA, USA
| | - Andrew S Neish
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA.
| | - Dean P Jones
- Division of Pulmonary, Allergy, Critical Care and Sleep Medicine, Department of Medicine, Emory University School of Medicine, Atlanta, GA, USA.
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Adnan khalaf M, Ghassan Zainal I. Investigation of Antioxidant Markers in Diabetic Patients. ARCHIVES OF RAZI INSTITUTE 2021; 76:1453-1460. [PMID: 35355751 PMCID: PMC8934072 DOI: 10.22092/ari.2021.355755.1717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 09/02/2021] [Indexed: 01/24/2023]
Abstract
Hyperglycemia is a characteristic of diabetes mellitus, one of the most common metabolic illnesses in the world, and is caused by either reduced insulin secretion or insulin resistance. Diabetes mellitus in adults has been on the rise in recent decades, and it is now the world's fifth-biggest cause of mortality. Diabetes mellitus will affect 592 million people worldwide by 2035, according to the International Diabetes Mellitus Federation, and diabetic complications are divided into two groups of acute and chronic types. Diabetic ketoacidosis, nonketotic hyperosmolar coma, and hypoglycemia are some examples of acute problems, whereas chronic complications include injuries to the small vessels (microvascular issues) and large blood arteries (macrovascular complications). Diabetic neuropathy, retinopathy, and nephropathy all have microvascular consequences, and on the other hand, macrovascular problems have a role in the etiology of cardiovascular disorders such as coronary, cerebrovascular, and peripheral artery diseases. This study aimed to estimate some antioxidant markers, including total protein, albumin, globulin, albumin/globulin ratio (AGR), free amino, free amino/total protein, thiol, thiol/total protein, carbonyl, as well as carbonyl/total protein levels in the plasma of diabetic complications compared to healthy subjects, and investigate the correlations between them. The present study included 120 plasma samples divided into 80 samples as patients with diabetic complications; 26, 26, and 28 samples had diabetic kidney disease, diabetic retinopathy, and diabetic neuropathy, respectively, with the age range between 20-60. Moreover, a total of 40 healthy subjects were included in the study as the control group with the same age ranges. The results showed that there was not any significant difference in carbonyl; however, significant differences were recorded in the total protein, albumin, globulin, AGR, free amino, free amino/total protein, thiol and thiol/total protein, as well as carbonyl/total protein levels in all studied groups. The correlation outcomes indicated that there were significant positive relationships between total protein-globulin, AGR-albumin, and free amine-albumin. In contrast, significant negative correlations were recorded between total protein-AGR and AGR-globulin in diabetic complications. Finally, it was concluded that oxidation markers might play a role in monitoring diabetic complications.
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Affiliation(s)
- M Adnan khalaf
- Chemistry Department, College of Science, University of Kirkuk, Kirkuk, Iraq
| | - I Ghassan Zainal
- Chemistry Department, College of Science, University of Kirkuk, Kirkuk, Iraq
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Multi-stage metabolomics and genetic analyses identified metabolite biomarkers of metabolic syndrome and their genetic determinants. EBioMedicine 2021; 74:103707. [PMID: 34801968 PMCID: PMC8605407 DOI: 10.1016/j.ebiom.2021.103707] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Revised: 10/07/2021] [Accepted: 11/05/2021] [Indexed: 12/18/2022] Open
Abstract
Background Metabolic syndrome (MetS) is a cluster of multiple cardiometabolic risk factors that increase the risk of type 2 diabetes and cardiovascular diseases. Identifying novel biomarkers of MetS and their genetic associations could provide insights into the mechanisms of cardiometabolic diseases. Methods Potential MetS-associated metabolites were screened and internally validated by untargeted metabolomics analyses among 693 patients with MetS and 705 controls. External validation was conducted using two well-established targeted metabolomic methods among 149 patients with MetS and 253 controls. The genetic associations of metabolites were determined by linear regression using our previous genome-wide SNP data. Causal relationships were assessed using a one-sample Mendelian Randomization (MR) approach. Findings Nine metabolites were ultimately found to be associated with MetS or its components. Five metabolites, including LysoPC(14:0), LysoPC(15:0), propionyl carnitine, phenylalanine, and docosapentaenoic acid (DPA) were selected to construct a metabolite risk score (MRS), which was found to have a dose-response relationship with MetS and metabolic abnormalities. Moreover, MRS displayed a good ability to differentiate MetS and metabolic abnormalities. Three SNPs (rs11635491, rs7067822, and rs1952458) were associated with LysoPC(15:0). Two SNPs, rs1952458 and rs11635491 were found to be marginally correlated with several MetS components. MR analyses showed that a higher LysoPC(15:0) level was causally associated with the risk of overweight/obesity, dyslipidaemia, high uric acid, high insulin and high HOMA-IR. Interpretation We identified five metabolite biomarkers of MetS and three SNPs associated with LysoPC(15:0). MR analyses revealed that abnormal LysoPC metabolism may be causally linked the metabolic risk. Funding This work was supported by grants from the National Key Research and Development Program of China (2017YFC0907004).
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50
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Liu ZC, Wng Q, Zheng Q, Zhao WL, Chen C, Ruan LY, Xu H, Meng HH, Zhao WL, Liu WY, Zhong JG, Luo BZX, Norbu K, Zhou F, Wang JS, Feng X. Acute hepatotoxicity and nephrotoxicity risk assessment of the Tibetan medicine 25 flavors of the turquoise pill based on 1H-NMR metabonomics. JOURNAL OF ETHNOPHARMACOLOGY 2021; 279:113916. [PMID: 33571615 DOI: 10.1016/j.jep.2021.113916] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/04/2020] [Revised: 02/04/2021] [Accepted: 02/05/2021] [Indexed: 06/12/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE 25 flavors of the turquoise pill, a traditional Tibetan medicine for the treatment of various types of hepatitis, has not been investigated on its safety, especially the component mineral turquoise, which is believed to be essential but worried for its potential toxicity. AIM OF THE STUDY To explore the potential acute toxicity and function of 25 flavors of the turquoise pill and turquoise, the possible mechanism of the effects of turquoise and 25 flavors of the turquoise pill were systematically studied based on 1H NMR metabolomics. MATERIALS AND METHODS The rats were administered with turquoise and 25 flavors of the turquoise pill by gavage for 7 days, and samples of serum, liver, and kidney were collected. The potential toxicity and function of turquoise and 25 flavors of the turquoise pill on the liver and kidney of SD rats were evaluated by 1H NMR metabonomics, histopathology, and biochemical indexes. RESULTS The results demonstrated that 25 flavors of the turquoise pill could scavenge free oxygen radicals, strengthen aerobic respiration and inhibit glycolysis in the liver. It did not cause oxidative stress in the kidney with no obvious damage. By modulation of branched-chain amino acids (BCAAs), 25 flavors of the turquoise pill can improve the utilization of glucose and promote aerobic respiration of the kidney. CONCLUSION Considering the high dosage and short duration used in this study relative to their typical clinical usage, administration of 25 flavors of the turquoise pill and its component mineral turquoise are safe to livers and kidneys.
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Affiliation(s)
- Zhi-Chao Liu
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Qian Wng
- Beijing Hospital of Tibetan Medicine, China Tibetology Research Center, Beijing, 100029, China
| | - Qi Zheng
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Wen-Li Zhao
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Cheng Chen
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Ling-Yu Ruan
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Han Xu
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Hui-Hui Meng
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Wen-Long Zhao
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Wen-Ya Liu
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China
| | - Jia-Ge Zhong
- Beijing Hospital of Tibetan Medicine, China Tibetology Research Center, Beijing, 100029, China
| | - Bu-Zha-Xi Luo
- Beijing Hospital of Tibetan Medicine, China Tibetology Research Center, Beijing, 100029, China
| | - Kelsang Norbu
- Tibet Ganlu Tibetan Medicine Co., Ltd, Lhasa, 851400, China
| | - Feng Zhou
- Tibet Ganlu Tibetan Medicine Co., Ltd, Lhasa, 851400, China
| | - Jun-Song Wang
- Center of Molecular Metabolism, Nanjing University of Science and Technology, 200 Xiaolingwei Street, Nanjing, 210094, China.
| | - Xin Feng
- Beijing Hospital of Tibetan Medicine, China Tibetology Research Center, Beijing, 100029, China.
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