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Wang T, Zhang Y, Jia L, Li Y, Wang L, Zhu Y, Jiang Y, Zhao F, Wang S, Song D. LC-MS/MS-based bioanalysis of branched-chain and aromatic amino acids in human serum. Bioanalysis 2024:1-12. [PMID: 39157863 DOI: 10.1080/17576180.2024.2387467] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2024] [Accepted: 07/30/2024] [Indexed: 08/20/2024] Open
Abstract
Aim: Branched-chain amino acids (BCAAs) and aromatic amino acids (AAAs) were suggested as potential biomarkers in liver disease. This study aimed to develop and validate a simple and rapid LC-MS/MS method to simultaneously measure serum BCAAs and AAAs levels in patients with liver injury, and further establish reference intervals of Chinese healthy adult populations.Patients & methods: Samples were prepared by a one-step protein precipitation and analysis time was 4 min per run.Results: The validation results showed good linearity (r2 >0.9969), satisfactory accuracy (94.44% - 107.75%) and precision (0.10% - 5.90%).Conclusion: This method proved to be suitable for high-throughput routine clinical use and could be a valuable adjunct diagnosis tool for liver injury and other clinical applications.
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Affiliation(s)
- Tianyi Wang
- Department of GCP, The First Affiliated Hospital of Jinzhou Medical University, Jinzhou, P.R. China
| | - Yalian Zhang
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
| | - Luan Jia
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
| | - Ying Li
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
| | - Lu Wang
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
| | - Yanru Zhu
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
| | - Yuxin Jiang
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
- Dalian Runsheng Kangtai Medical Lab Co. Ltd, Dalian, P.R. China
| | - Furong Zhao
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
- Dalian Runsheng Kangtai Medical Lab Co. Ltd, Dalian, P.R. China
- Liaoning Provincial Key Laboratory of Clinical Oncology Metabonomics, Jinzhou Medical University, Jinzhou, P.R. China
| | - Shuang Wang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics, NHC Key Lab of Reproduction Regulation, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, P.R. China
| | - Dan Song
- Dalian Boyuan Medical Technology Co. Ltd, Dalian, P.R. China
- Liaoning Provincial Key Laboratory of Clinical Oncology Metabonomics, Jinzhou Medical University, Jinzhou, P.R. China
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Khoramipour K, Rajizadeh MA, Akbari Z, Arjmand M. The effect of high-intensity interval training on type 2 diabetic muscle: A metabolomics-based study. Heliyon 2024; 10:e34917. [PMID: 39170342 PMCID: PMC11336285 DOI: 10.1016/j.heliyon.2024.e34917] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2024] [Revised: 07/17/2024] [Accepted: 07/18/2024] [Indexed: 08/23/2024] Open
Abstract
Background This study aimed to investigate the effect of eight weeks of high-intensity interval training (HIIT) on muscle metabolism in rats with type 2 diabetes (T2D) using metabolomics approaches. Methods 20 male Wistar rats at the age of 8 weeks-were assigned to four groups of five, each in the group randomly: control (CTL), type 2 diabetes (DB), HIIT (EX), and type 2 diabetes + HIIT (DBX). T2D was induced by two months of a high-fat diet plus a single dose of streptozotocin (35 mg/kg). Rats in the EX and DBX groups performed eight weeks of HIIT (running at 80-100 % of Vmax, 4-10 intervals). NMR spectroscopy was used to determine the changes in the muscle metabolome profile after training. Results Changes in metabolite abundance following exercise revealed distinct clustering in multivariate analysis. The essential metabolite changes between the DB and CTL groups were arginine metabolism, purine metabolism, phosphate pathway, amino sugar metabolism, glutathione metabolism, and aminoacyl-tRNA biosynthesis. However, Arginine biosynthesis, pyrimidine metabolism, aminoacyl-tRNA biosynthesis, and alanine, aspartate, and glutamate metabolism were altered between the DBX and DB groups. Conclusion These results suggest that eight weeks of HIIT could reverse metabolic changes induced by T2D in rat muscles, contributing to reduced FBG and HOMA-IR levels.
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Affiliation(s)
- Kayvan Khoramipour
- Endocrinology and Metabolism Research Center, Kerman University of Medical Sciences Kerman, Iran
- i+HeALTH Strategic Research Group, Department of Health Sciences, Miguel de Cervantes European University (UEMC), 47012 Valladolid, Spain
| | - Mohammad Amin Rajizadeh
- Physiology Research Center, Institute of Neuropharmacology, Kerman University of Medical Sciences, Kerman, Iran
| | - Ziba Akbari
- Metabolomics Lab, Department of Biochemistry, Pasteur Institute of Iran, Tehran, Iran
| | - Mohammad Arjmand
- Metabolomics Lab, Department of Biochemistry, Pasteur Institute of Iran, Tehran, Iran
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3
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Diniz TG, Severo de Assis C, de Sousa BRV, Batista KS, Silva AS, Wanderley de Queiroga Evangelista I, Monteiro Viturino MG, do Nascimento YM, da Silva EF, Tavares JF, Cavalcanti Alves Monteiro MG, Novaes Dos Santos Fechine CP, Lima E Silva A, Persuhn DC. Metabolomic analysis of retinopathy stages and amputation in type 2 diabetes. Clin Nutr ESPEN 2024; 61:158-167. [PMID: 38777429 DOI: 10.1016/j.clnesp.2024.03.013] [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: 10/25/2023] [Revised: 03/05/2024] [Accepted: 03/10/2024] [Indexed: 05/25/2024]
Abstract
BACKGROUND Diabetic retinopathy (DR) and limb amputation are frequent complications of diabetes that cannot always be explained by blood glucose control. Metabolomics is a science that is currently being explored in the search for biomarkers or profiles that identify clinical conditions of interest. OBJECTIVE This study aimed to analyze, using a metabolomic approach, peripheral blood samples from type 2 diabetes mellitus (DM2) individuals, compared with those with diabetic retinopathy and limb amputation. METHODS The sample consisted of 128 participants, divided into groups: control, DM2 without DR (DM2), non-proliferative DR (DRNP), proliferative DR (DRP), and DM2 amputated (AMP). Metabolites from blood plasma were classified by spectra using nuclear magnetic resonance (NMR), and the metabolic routes of each group using metaboanalyst. RESULTS We identified that the metabolism of phenylalanine, tyrosine, and tryptophan was discriminant for the DRP group. Histidine biosynthesis, on the other hand, was statistically associated with the AMP group. The results of this work consolidate metabolites such as glutamine and citrulline as discriminating for DRP, and the branched-chain amino acids as important for DR. CONCLUSIONS The results demonstrate the relationship between the metabolism of ketone bodies, with acetoacetate metabolite being discriminating for the DRP group and histidine being a significant metabolite in the AMP group, when compared to the DM2 group.
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Affiliation(s)
- Tainá Gomes Diniz
- Post-Graduate Program in Nutrition Science, Federal University of Paraiba, Joao Pessoa, Brazil
| | | | | | | | - Alexandre Sérgio Silva
- Department of Physical Education, Federal University of Paraiba (UFPB), Joao Pessoa, PB, Brazil
| | | | - Marina Gonçalves Monteiro Viturino
- Ophthalmology, Otolaryngology and Oral and Maxillofacial Surgery Unit, Lauro Wanderley University Hospital, Federal University of Paraiba, Joao Pessoa, Brazil
| | - Yuri Mangueira do Nascimento
- Post-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraiba, Joao Pessoa, Brazil
| | - Evandro Ferreira da Silva
- Institute for Research in Drugs and Medicines - IPeFarM, Federal University of Paraíba, João Pessoa, PB, 58051-900, Brazil
| | - Josean Fechine Tavares
- Institute for Research in Drugs and Medicines - IPeFarM, Federal University of Paraíba, João Pessoa, PB, 58051-900, Brazil
| | | | | | - Anauara Lima E Silva
- Post-Graduate Program in Natural and Synthetic Bioactive Products, Federal University of Paraiba, Joao Pessoa, Brazil
| | - Darlene Camati Persuhn
- Post-Graduate Program in Nutrition Science, Federal University of Paraiba, Joao Pessoa, Brazil.
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4
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Lin C, Tian Q, Guo S, Xie D, Cai Y, Wang Z, Chu H, Qiu S, Tang S, Zhang A. Metabolomics for Clinical Biomarker Discovery and Therapeutic Target Identification. Molecules 2024; 29:2198. [PMID: 38792060 PMCID: PMC11124072 DOI: 10.3390/molecules29102198] [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: 03/13/2024] [Revised: 04/10/2024] [Accepted: 04/25/2024] [Indexed: 05/26/2024] Open
Abstract
As links between genotype and phenotype, small-molecule metabolites are attractive biomarkers for disease diagnosis, prognosis, classification, drug screening and treatment, insight into understanding disease pathology and identifying potential targets. Metabolomics technology is crucial for discovering targets of small-molecule metabolites involved in disease phenotype. Mass spectrometry-based metabolomics has implemented in applications in various fields including target discovery, explanation of disease mechanisms and compound screening. It is used to analyze the physiological or pathological states of the organism by investigating the changes in endogenous small-molecule metabolites and associated metabolism from complex metabolic pathways in biological samples. The present review provides a critical update of high-throughput functional metabolomics techniques and diverse applications, and recommends the use of mass spectrometry-based metabolomics for discovering small-molecule metabolite signatures that provide valuable insights into metabolic targets. We also recommend using mass spectrometry-based metabolomics as a powerful tool for identifying and understanding metabolic patterns, metabolic targets and for efficacy evaluation of herbal medicine.
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Affiliation(s)
- Chunsheng Lin
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
| | - Qianqian Tian
- Faculty of Social Sciences, The University of Hong Kong, Hong Kong 999077, China;
| | - Sifan Guo
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Dandan Xie
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Ying Cai
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Zhibo Wang
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Hang Chu
- Department of Biomedical Sciences, Beijing City University, Beijing 100193, China;
| | - Shi Qiu
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Songqi Tang
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
| | - Aihua Zhang
- Graduate School and Second Affiliated Hospital, Heilongjiang University of Chinese Medicine, Harbin 150040, China; (C.L.); (S.G.); (Y.C.); (Z.W.)
- International Advanced Functional Omics Platform, Scientific Experiment Center, International Joint Research Center on Traditional Chinese and Modern Medicine, Hainan Engineering Research Center for Biological Sample Resources of Major Diseases (First Affiliated Hospital of Hainan Medical University), Key Laboratory of Tropical Cardiovascular Diseases Research of Hainan Province, Hainan Medical University, Xueyuan Road 3, Haikou 571199, China; (D.X.); (S.Q.); (S.T.)
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Jabbar Al‐Rikabi S, Etemadi A, Morad M, Nowrouzi A, Panahi G, Mondeali M, Toorani‐ghazvini M, Nasli‐Esfahani E, Razi F, Bandarian F. Metabolomics Signature in Prediabetes and Diabetes: Insights From Tandem Mass Spectrometry Analysis. Endocrinol Diabetes Metab 2024; 7:e00484. [PMID: 38739122 PMCID: PMC11090150 DOI: 10.1002/edm2.484] [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: 02/16/2024] [Accepted: 04/01/2024] [Indexed: 05/14/2024] Open
Abstract
OBJECTIVE This study investigates the metabolic differences between normal, prediabetic and diabetic patients with good and poor glycaemic control (GGC and PGC). DESIGN In this study, 1102 individuals were included, and 50 metabolites were analysed using tandem mass spectrometry. The diabetes diagnosis and treatment standards of the American Diabetes Association (ADA) were used to classify patients. METHODS The nearest neighbour method was used to match controls and cases in each group on the basis of age, sex and BMI. Factor analysis was used to reduce the number of variables and find influential underlying factors. Finally, Pearson's correlation coefficient was used to check the correlation between both glucose and HbAc1 as independent factors with binary classes. RESULTS Amino acids such as glycine, serine and proline, and acylcarnitines (AcylCs) such as C16 and C18 showed significant differences between the prediabetes and normal groups. Additionally, several metabolites, including C0, C5, C8 and C16, showed significant differences between the diabetes and normal groups. Moreover, the study found that several metabolites significantly differed between the GGC and PGC diabetes groups, such as C2, C6, C10, C16 and C18. The correlation analysis revealed that glucose and HbA1c levels significantly correlated with several metabolites, including glycine, serine and C16, in both the prediabetes and diabetes groups. Additionally, the correlation analysis showed that HbA1c significantly correlated with several metabolites, such as C2, C5 and C18, in the controlled and uncontrolled diabetes groups. CONCLUSIONS These findings could help identify new biomarkers or underlying markers for the early detection and management of diabetes.
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Affiliation(s)
| | - Ali Etemadi
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences InstituteTehran University of Medical SciencesTehranIran
- Medical Biotechnology Department, School of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
| | - Maher Mohammed Morad
- Department of Clinical Biochemistry, School of MedicineTehran University of Medical SciencesTehranIran
| | - Azin Nowrouzi
- Department of Clinical Biochemistry, School of MedicineTehran University of Medical SciencesTehranIran
| | | | - Mozhgan Mondeali
- Department of Medical Genetics, School of MedicineTehran University of Medical SciencesTehranIran
| | - Mahsa Toorani‐ghazvini
- Medical Biotechnology Department, School of Advanced Technologies in MedicineTehran University of Medical SciencesTehranIran
| | - Ensieh Nasli‐Esfahani
- Diabetes Research CenterEndocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical SciencesTehranIran
| | - Farideh Razi
- Metabolomics and Genomics Research CenterEndocrinology and Metabolism Molecular‐Cellular Sciences Institute, Tehran University of Medical SciencesTehranIran
| | - Fatemeh Bandarian
- Metabolomics and Genomics Research CenterEndocrinology and Metabolism Molecular‐Cellular Sciences Institute, Tehran University of Medical SciencesTehranIran
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Yousf S, Batra HS, Jha RM, Sardesai DM, Ananthamohan K, Chugh J, Sharma S. Identification of potential serum biomarkers associated with HbA1c levels in Indian type 2 diabetic subjects using NMR-based metabolomics. Clin Chim Acta 2024; 557:117857. [PMID: 38484908 DOI: 10.1016/j.cca.2024.117857] [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: 11/30/2023] [Revised: 02/29/2024] [Accepted: 03/02/2024] [Indexed: 03/25/2024]
Abstract
BACKGROUND The prevalence of type 2 diabetes mellitus (T2DM), a progressive metabolic disorder characterized by chronic hyperglycemia and the development of insulin resistance, has increased globally, with worrying statistics coming from children, adolescents, and young adults from developing countries like India. Here, we investigated unique circulating metabolic signatures associated with prediabetes and T2DM in an Indian cohort using NMR-based metabolomics. MATERIALS AND METHODS The study subjects included healthy volunteers (N = 101), prediabetic subjects (N = 75), and T2DM patients (N = 108). Serum metabolic profiling was performed using 1H NMR spectroscopy and major perturbed metabolites were identified by multivariate analysis and receiver operating characteristic (ROC) modules. RESULTS Of the 36 aqueous abundant metabolites, 24 showed a statistically significant difference between healthy volunteers, prediabetics, and established T2DM subjects. On performing multivariate ROC curve analysis with 5 commonly dysregulated metabolites (namely, glucose, pyroglutamate, o-phosphocholine, serine, and methionine) in prediabetes and T2DM, AUC values obtained were 0.96 (95 % confidence interval (CI) = 0.93, 0.98) for T2DM; and 0.88 (95 % CI = 0.81, 0.93) for prediabetic subjects, respectively. CONCLUSION We propose that the identified metabolite panel can be used in the future as a biomarker for clinical diagnosis, patient surveillance, and for predicting individuals at risk for developing diabetes.
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Affiliation(s)
- Saleem Yousf
- Department of Chemistry, Indian Institute of Science Education and Research (IISER), Dr. Homi Bhabha Road, Pashan, Pune 411008, India; Division of Cancer Imaging Research, The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Hitender S Batra
- Department of Biochemistry, Armed Forces Medical College (AFMC), Wanowrie, Pune 411040, India; Department of Biochemistry, Symbiosis Medical College for Women, Pune 412115, India.
| | - Rakesh M Jha
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India
| | - Devika M Sardesai
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India
| | - Kalyani Ananthamohan
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India
| | - Jeetender Chugh
- Department of Chemistry, Indian Institute of Science Education and Research (IISER), Dr. Homi Bhabha Road, Pashan, Pune 411008, India.
| | - Shilpy Sharma
- Department of Biotechnology, Savitribai Phule Pune University, Ganeshkhind Road, Pune 411007, India.
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7
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Das S, Devi Rajeswari V, Venkatraman G, Elumalai R, Dhanasekaran S, Ramanathan G. Current updates on metabolites and its interlinked pathways as biomarkers for diabetic kidney disease: A systematic review. Transl Res 2024; 265:71-87. [PMID: 37952771 DOI: 10.1016/j.trsl.2023.11.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 11/09/2023] [Accepted: 11/09/2023] [Indexed: 11/14/2023]
Abstract
Diabetic kidney disease (DKD) is a major microvascular complication of diabetes mellitus (DM) that poses a serious risk as it can lead to end-stage renal disease (ESRD). DKD is linked to changes in the diversity, composition, and functionality of the microbiota present in the gastrointestinal tract. The interplay between the gut microbiota and the host organism is primarily facilitated by metabolites generated by microbial metabolic processes from both dietary substrates and endogenous host compounds. The production of numerous metabolites by the gut microbiota is a crucial factor in the pathogenesis of DKD. However, a comprehensive understanding of the precise mechanisms by which gut microbiota and its metabolites contribute to the onset and progression of DKD remains incomplete. This review will provide a summary of the current scenario of metabolites in DKD and the impact of these metabolites on DKD progression. We will discuss in detail the primary and gut-derived metabolites in DKD, and the mechanisms of the metabolites involved in DKD progression. Further, we will address the importance of metabolomics in helping identify potential DKD markers. Furthermore, the possible therapeutic interventions and research gaps will be highlighted.
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Affiliation(s)
- Soumik Das
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - V Devi Rajeswari
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - Ganesh Venkatraman
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - Ramprasad Elumalai
- Department of Nephrology, Sri Ramachandra Institute of Higher Education and Research, Porur, Chennai, Tamil Nadu 600116, India
| | - Sivaraman Dhanasekaran
- School of Energy Technology, Pandit Deendayal Energy University, Knowledge Corridor, Raisan Village, PDPU Road, Gandhinagar, Gujarat 382426, India
| | - Gnanasambandan Ramanathan
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India.
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Duong QH, Kwahk EJ, Kim J, Park H, Cho H, Kim H. Bioinspired Fluorine Labeling for 19F NMR-Based Plasma Amine Profiling. Anal Chem 2024; 96:1614-1621. [PMID: 38244044 DOI: 10.1021/acs.analchem.3c04485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2024]
Abstract
Metabolite profiling serves as a powerful tool that advances our understanding of biological systems, disease mechanisms, and environmental interactions. In this study, we present an approach employing 19F-nuclear magnetic resonance (19F NMR) spectroscopy for plasma amine profiling. This method utilizes a highly efficient and reliable fluorine-labeling reagent, 3,5-difluorosalicylaldehyde, which effectively emulates pyridoxal phosphate, facilitating the formation of Schiff base compounds with primary amines. The fluorine labeling allows for distinct resolution of 19F NMR signals from amine mixtures, leading to precise identification and quantification of amine metabolites in human plasma. This advancement offers valuable tools for furthering metabolomics research.
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Affiliation(s)
- Quynh Huong Duong
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Eun-Jeong Kwahk
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Jumi Kim
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Hahyoun Park
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Heyjin Cho
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
| | - Hyunwoo Kim
- Department of Chemistry, Korea Advanced Institute of Science and Technology (KAIST), Daejeon 34141, Korea
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9
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Arjmand B, Alavi-Moghadam S, Kokabi-Hamidpour S, Arjmand R, Rezaei-Tavirani M, Larijani B, Goodarzi P, Mehrdad N, Rajaeinejad M. Development and Validation of Type 2 Diabetic Zebrafish Model for Cell-Based Treatments. Methods Mol Biol 2024; 2736:127-137. [PMID: 36773274 DOI: 10.1007/7651_2022_475] [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] [Indexed: 02/12/2023]
Abstract
Diabetes mellitus can be categorized as one of the prolonged metabolic disorders that are associated with inappropriately elevated blood glucose levels. Among the subgroups of this disease, type 2 diabetes accounts for the most patients. Although pharmaceutical and non-pharmaceutical treatments have been employed to control the progression of the disease, as with any treatment approach, both therapeutic approaches are associated with side effects and challenges. Nowadays, the emergence of treatment methods based on stem cells has attracted the attention of researchers in order to treat diabetes fundamentally and provide a long-term solution. Since there are still blind spots regarding the positive and negative effects of these types of treatments, animal studies can give researchers a detailed insight into the effects of stem cell-based treatments. Recently, zebrafish has been proposed as a valuable animal model due to its outstanding genetic and physiological characteristics in biomedical studies including diabetes. Hereupon, in this protocol, the development and validation of type 2 diabetic zebrafish model for cell-based treatments have been explained.
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Affiliation(s)
- Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
- Iranian Cancer Control Center (MACSA), Tehran, Iran.
| | - Sepideh Alavi-Moghadam
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shayesteh Kokabi-Hamidpour
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Rasta Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular 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
| | - Parisa Goodarzi
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Neda Mehrdad
- Elderly Health Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mohsen Rajaeinejad
- AJA Cancer Epidemiology Research and Treatment Center (AJA-CERTC), AJA University of Medical Sciences, Tehran, Iran
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Mujammami M, Aleidi SM, Buzatto AZ, Alshahrani A, AlMalki RH, Benabdelkamel H, Al Dubayee M, Li L, Aljada A, Abdel Rahman AM. Lipidomics Profiling of Metformin-Induced Changes in Obesity and Type 2 Diabetes Mellitus: Insights and Biomarker Potential. Pharmaceuticals (Basel) 2023; 16:1717. [PMID: 38139843 PMCID: PMC10747765 DOI: 10.3390/ph16121717] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2023] [Revised: 12/06/2023] [Accepted: 12/08/2023] [Indexed: 12/24/2023] Open
Abstract
Metformin is the first-line oral medication for treating type 2 diabetes mellitus (T2DM). In the current study, an untargeted lipidomic analytical approach was used to investigate the alterations in the serum lipidome of a cohort of 89 participants, including healthy lean controls and obese diabetic patients, and to examine the alterations associated with metformin administration. A total of 115 lipid molecules were significantly dysregulated (64 up-regulated and 51 down-regulated) in the obese compared to lean controls. However, the levels of 224 lipid molecules were significantly dysregulated (125 up-regulated and 99 down-regulated) in obese diabetic patients compared to the obese group. Metformin administration in obese diabetic patients was associated with significant dysregulation of 54 lipid molecule levels (20 up-regulated and 34 down-regulated). Levels of six molecules belonging to five lipid subclasses were simultaneously dysregulated by the effects of obesity, T2DM, and metformin. These include two putatively annotated triacylglycerols (TGs), one plasmenyl phosphatidylcholine (PC), one phosphatidylglycerol (PGs), one sterol lipid (ST), and one Mannosyl-phosphoinositol ceramide (MIPC). This study provides new insights into our understanding of the lipidomics alterations associated with obesity, T2DM, and metformin and offers a new platform for potential biomarkers for the progression of diabetes and treatment response in obese patients.
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Affiliation(s)
- Muhammad Mujammami
- University Diabetes Center, Medical City, King Saud University, Riyadh 11472, Saudi Arabia;
- Endocrinology and Diabetes Unit, Department of Medicine, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia
| | - Shereen M. Aleidi
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman 11942, Jordan;
| | | | - Awad Alshahrani
- College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh 11426, Saudi Arabia; (A.A.); (M.A.D.)
| | - Reem H. AlMalki
- Metabolomics Section, Department of Clinical Genomics, Center for Genomics Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia;
| | - Hicham Benabdelkamel
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh 11461, Saudi Arabia;
| | - Mohammed Al Dubayee
- College of Medicine, King Saud Bin Abdulaziz University for Health Sciences, Ministry of National Guard Health Affairs, Riyadh 11426, Saudi Arabia; (A.A.); (M.A.D.)
| | - Liang Li
- The Metabolomics Innovation Center (TMIC), Edmonton, AB T6G 1C9, Canada; (A.Z.B.); (L.L.)
- Department of Chemistry, University of Alberta, Edmonton, AB T6G 2G2, Canada
| | - Ahmad Aljada
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh 11461, Saudi Arabia
| | - Anas M. Abdel Rahman
- Metabolomics Section, Department of Clinical Genomics, Center for Genomics Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh 11211, Saudi Arabia;
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh 11461, Saudi Arabia
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11
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Hassan MH, Galal O, Sakhr HM, Kamaleldeen EB, Zekry NF, Fateen E, Toghan R. Profile of plasma free amino acids, carnitine and acylcarnitines, and JAK2 v617f mutation as potential metabolic markers in children with type 1 diabetic nephropathy. Biomed Chromatogr 2023; 37:e5747. [PMID: 37728037 DOI: 10.1002/bmc.5747] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2023] [Revised: 08/28/2023] [Accepted: 08/29/2023] [Indexed: 09/21/2023]
Abstract
Fifty diabetic nephropathy (DN) children with type 1 diabetes mellitus (T1DM) and 50 healthy matched controls were included. Chromatographic assays of 14 amino acids, free carnitine and 27 carnitine esters using high-performance liquid chromatography/electrospray ionization-mass spectroscopy, and genetic testing for JAK2v617f mutation using real-time PCR were performed. Patients had significantly lower levels of tyrosine, branched-chain amino acids (BCAAs), and BCAA/AAA (aromatic chain amino acids) ratios, glycine, arginine, ornithine, free carnitine and some carnitine esters (C5, 6, 12 and 16) and higher phenylalanine, phenylalanine/tyrosine ratio and C18 compared with the controls and in the macro-albuminuria vs. the microalbuminuria group (p < 0.05 for all) except for free carnitine. Plasma carnitine was negatively correlated with eGFR (r = -0.488, p = 0.000). There were significant positive correlations between tyrosine with UACR ratio (r = 0.296, p = 0.037). The plasma BCAA/AAA ratio showed significant negative correlations with UACR (r = -0.484, p = 0.000). There was a significantly higher frequency of the JAK2V617F gene mutation in diabetic nephropathy patients compared with the control group and in macro-albuminuria than the microalbuminuria group (p = 0.000) for both. When monitoring children with T1DM, plasma free amino acids and acylcarnitine profiles should be considered, especially if they have tested positive for JAK2V617F for the early diagnosis of DN.
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Affiliation(s)
- Mohammed H Hassan
- Department of Medical Biochemistry, Faculty of Medicine, South Valley University, Qena, Egypt
| | - Omyma Galal
- Medical Physiology Department, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Hala M Sakhr
- Department of Pediatrics, Faculty of Medicine, South Valley University, Qena, Egypt
| | - Eman B Kamaleldeen
- Department of Pediatrics, Faculty of Medicine, Assiut University, Assiut, Egypt
| | - Nadia Farouk Zekry
- Medical Physiology Department, Faculty of Medicine, South Valley University, Qena, Egypt
| | - Ekram Fateen
- Department of Biochemical Genetics, National Research Center, Cairo, Egypt
| | - Rana Toghan
- Medical Physiology Department, Faculty of Medicine, South Valley University, Qena, Egypt
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12
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Hillesheim E, Brennan L. Distinct patterns of personalised dietary advice delivered by a metabotype framework similarly improve dietary quality and metabolic health parameters: secondary analysis of a randomised controlled trial. Front Nutr 2023; 10:1282741. [PMID: 38035361 PMCID: PMC10684740 DOI: 10.3389/fnut.2023.1282741] [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: 08/24/2023] [Accepted: 10/31/2023] [Indexed: 12/02/2023] Open
Abstract
Background In a 12-week randomised controlled trial, personalised nutrition delivered using a metabotype framework improved dietary intake, metabolic health parameters and the metabolomic profile compared to population-level dietary advice. The objective of the present work was to investigate the patterns of dietary advice delivered during the intervention and the alterations in dietary intake and metabolic and metabolomic profiles to obtain further insights into the effectiveness of the metabotype framework. Methods Forty-nine individuals were randomised into the intervention group and subsequently classified into metabotypes using four biomarkers (triacylglycerol, HDL-C, total cholesterol, glucose). These individuals received personalised dietary advice from decision tree algorithms containing metabotypes and individual characteristics. In a secondary analysis of the data, patterns of dietary advice were identified by clustering individuals according to the dietary messages received and clusters were compared for changes in dietary intake and metabolic health parameters. Correlations between changes in blood clinical chemistry and changes in metabolite levels were investigated. Results Two clusters of individuals with distinct patterns of dietary advice were identified. Cluster 1 had the highest percentage of messages delivered to increase the intake of beans and pulses and milk and dairy products. Cluster 2 had the highest percentage of messages delivered to limit the intake of foods high in added sugar, high-fat foods and alcohol. Following the intervention, both patterns improved dietary quality assessed by the Alternate Mediterranean Diet Score and the Alternative Healthy Eating Index, nutrient intakes, blood pressure, triacylglycerol and LDL-C (p ≤ 0.05). Several correlations were identified between changes in total cholesterol, LDL-C, triacylglycerol, insulin and HOMA-IR and changes in metabolites levels, including mostly lipids (sphingomyelins, lysophosphatidylcholines, glycerophosphocholines and fatty acid carnitines). Conclusion The findings indicate that the metabotype framework effectively personalises and delivers dietary advice to improve dietary quality and metabolic health. Clinical trial registration isrctn.com, identifier ISRCTN15305840.
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Affiliation(s)
- Elaine Hillesheim
- UCD School of Agriculture and Food Science, Institute of Food and Health, University College Dublin, Dublin, Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
| | - Lorraine Brennan
- UCD School of Agriculture and Food Science, Institute of Food and Health, University College Dublin, Dublin, Ireland
- UCD Conway Institute of Biomolecular and Biomedical Research, University College Dublin, Dublin, Ireland
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Yuan Z, Tian Y, Zhang C, Wang M, Xie J, Wang C, Huang J. Integration of systematic review, lipidomics with experiment verification reveals abnormal sphingolipids facilitate diabetic retinopathy by inducing oxidative stress on RMECs. Biochim Biophys Acta Mol Cell Biol Lipids 2023; 1868:159382. [PMID: 37659619 DOI: 10.1016/j.bbalip.2023.159382] [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: 05/05/2023] [Revised: 08/21/2023] [Accepted: 08/28/2023] [Indexed: 09/04/2023]
Abstract
OBJECTIVE This study aims to explore the potential biomarkers in the development of diabetes mellitus (DM) into diabetic retinopathy (DR). METHODS Systematic review of diabetic metabolomics was used to screen the differential metabolites and related pathways during the development of DM. Non-targeted lipidomics of rat plasma was performed to explore the differential metabolites in the development of DM into DR in vivo. To verify the effects of differential metabolites in inducing retinal microvascular endothelial cells (RMECs) injury by increasing oxidative stress, high glucose medium containing differential metabolites was used to induce rat RMECs injury and cell viability, malondialdehyde (MDA) contents, superoxide dismutase (SOD) activities, reactive oxygen species (ROS) levels and mitochondrial membrane potential (MMP) were evaluated in vitro. Network pharmacology was performed to explore the potential mechanism of differential metabolites in inducing DR. RESULTS Through the systematic review, 148 differential metabolites were obtained and the sphingolipid metabolic pathway attracted our attention. Plasma non-targeted lipidomics found that sphingolipids were accompanied by the development of DM into DR. In vitro experiments showed sphinganine and sphingosine-1-phosphate aggravated rat RMECs injury induced by high glucose, further increased MDA and ROS levels, and further decreased SOD activities and MMP. Network pharmacology revealed sphinganine and sphingosine-1-phosphate may induce DR by regulating the AGE-RAGE and HIF-1 signaling pathways. CONCLUSIONS Integrated systematic review, lipidomics and experiment verification reveal that abnormal sphingolipid metabolism facilitates DR by inducing oxidative stress on RMECs. Our study could provide the experimental basis for finding potential biomarkers for the diagnosis and treatment of DR.
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Affiliation(s)
- Zhenshuang Yuan
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Yue Tian
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Cong Zhang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Mingshuang Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Jiaqi Xie
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China
| | - Can Wang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China.
| | - Jianmei Huang
- School of Chinese Materia Medica, Beijing University of Chinese Medicine, Beijing 100029, China.
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Liu J, Xie Z, Fu J, Yu M, Wang T, Qi C, Liu P, Hui X, Wang D, Ding L, Zhang Q, Xie T, Xiao X. Quantitative profiling and diagnostic potential of one-carbon and central metabolism pools in MODY2 and T1DM. Diabetol Metab Syndr 2023; 15:206. [PMID: 37875989 PMCID: PMC10594937 DOI: 10.1186/s13098-023-01175-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 09/27/2023] [Indexed: 10/26/2023] Open
Abstract
BACKGROUND Maturity-onset diabetes of the young type 2 (MODY2) is a rare genetic disorder characterized as mild fasting hyperglycemia with low risk of vascular complications caused by glucokinase gene mutation. This study aims to investigate metabolites alteration associated with MODY2, exploring possible mechanism underlying characteristic clinical manifestations and low cardiovascular risks of MODY2 and providing serum metabolite biomarkers to facilitating MODY2 diagnosis. METHODS Fasting serum samples from MODY2, type 1 diabetes (T1DM) and healthy individuals were collected. By using targeted metabolomics via liquid chromatography-tandem mass spectrometry platform, we quantified the metabolites involved in tricarboxylic acid (TCA) cycle and one-carbon metabolism. RESULTS Metabolomic profiling revealed significant difference of intermediates from central metabolism cycle, methionine cycle and several amino acids between MODY2 and T1DM groups. Among these, serum citrate, α-ketoglutaric acid, serine, glycine, glutamine and homocysteine were significantly elevated in MODY2 patients compared with T1DM patients; and compared with healthy subjects, malate and methionine levels were significantly increased in the two groups of diabetic patients. The correlation analysis with clinical indexes showed that α- ketoglutarate, serine, glycine, and glutamine were negatively correlated with blood glucose indicators including fasting blood glucose, HbA1c, and GA, while citrate was positively correlated with C-peptide. And homocysteine displayed positive correlation with HDL and negative with C-reactive protein, which shed light on the mechanism of mild symptoms and low risk of cardiovascular complications in MODY2 patients. A panel of 4 metabolites differentiated MODY2 from T1DM with AUC of 0.924, and a combination of clinical indices and metabolite also gained good diagnostic value with AUC 0.948. CONCLUSION In this research, we characterized the metabolite profiles of TCA cycle and one-carbon metabolism in MODY2 and T1DM and identified promising diagnostic biomarkers for MODY2. This study may provide novel insights into the pathogenesis and clinical manifestations of MODY2.
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Affiliation(s)
- Jieying Liu
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Ziyan Xie
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
| | - Junling Fu
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
- Department of Endocrinology, Beijing Institute of Geriatrics, Xuanwu Hospital, Capital Medical University, Beijing, 100053, China
| | - Miao Yu
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
| | - Tong Wang
- Department of Endocrinology, The 305 Hospital of People's Liberation Army of China, Beijing, 100017, China
| | - Cuijuan Qi
- Department of Endocrinology, Hebei General Hospital, Hebei, 050051, China
| | - Peng Liu
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xiangyi Hui
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Dongmei Wang
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
| | - Lu Ding
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
| | - Qian Zhang
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
| | - Ting Xie
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xinhua Xiao
- China Key Laboratory of Endocrinology of National Health Commission, Diabetes Research Center of Chinese Academy of Medical Sciences, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, No. 1 Shuaifuyuan, Wangfujing Street, Dongcheng District, Beijing, 100730, P. R. China.
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Ding Y, Wang S, Lu J. Unlocking the Potential: Amino Acids' Role in Predicting and Exploring Therapeutic Avenues for Type 2 Diabetes Mellitus. Metabolites 2023; 13:1017. [PMID: 37755297 PMCID: PMC10535527 DOI: 10.3390/metabo13091017] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 09/08/2023] [Accepted: 09/13/2023] [Indexed: 09/28/2023] Open
Abstract
Diabetes mellitus, particularly type 2 diabetes mellitus (T2DM), imposes a significant global burden with adverse clinical outcomes and escalating healthcare expenditures. Early identification of biomarkers can facilitate better screening, earlier diagnosis, and the prevention of diabetes. However, current clinical predictors often fail to detect abnormalities during the prediabetic state. Emerging studies have identified specific amino acids as potential biomarkers for predicting the onset and progression of diabetes. Understanding the underlying pathophysiological mechanisms can offer valuable insights into disease prevention and therapeutic interventions. This review provides a comprehensive summary of evidence supporting the use of amino acids and metabolites as clinical biomarkers for insulin resistance and diabetes. We discuss promising combinations of amino acids, including branched-chain amino acids, aromatic amino acids, glycine, asparagine and aspartate, in the prediction of T2DM. Furthermore, we delve into the mechanisms involving various signaling pathways and the metabolism underlying the role of amino acids in disease development. Finally, we highlight the potential of targeting predictive amino acids for preventive and therapeutic interventions, aiming to inspire further clinical investigations and mitigate the progression of T2DM, particularly in the prediabetic stage.
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Affiliation(s)
- Yilan Ding
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.D.); (S.W.)
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Shuangyuan Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.D.); (S.W.)
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
| | - Jieli Lu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China; (Y.D.); (S.W.)
- Shanghai National Clinical Research Center for Endocrine and Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai National Center for Translational Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200025, China
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Artymowicz M, Struck-Lewicka W, Wiczling P, Markuszewski M, Markuszewski MJ, Siluk D. Targeted quantitative metabolomics with a linear mixed-effect model for analysis of urinary nucleosides and deoxynucleosides from bladder cancer patients before and after tumor resection. Anal Bioanal Chem 2023; 415:5511-5528. [PMID: 37460824 PMCID: PMC10444683 DOI: 10.1007/s00216-023-04826-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Revised: 06/07/2023] [Accepted: 06/26/2023] [Indexed: 08/23/2023]
Abstract
In the present study, we developed and validated a fast, simple, and sensitive quantitative method for the simultaneous determination of eleven nucleosides and deoxynucleosides from urine samples. The analyses were performed with the use of liquid chromatography coupled with triple quadrupole mass spectrometry. The sample pretreatment procedure was limited to centrifugation, vortex mixing of urine samples with a methanol/water solution (1:1, v/v), evaporation and dissolution steps. The analysis lasted 20 min and was performed in dynamic multiple reaction monitoring mode (dMRM) in positive polarity. Process validation was conducted to determine the linearity, precision, accuracy, limit of quantification, stability, recovery and matrix effect. All validation procedures were carried out in accordance with current FDA and EMA regulations. The validated method was applied for the analysis of 133 urine samples derived from bladder cancer patients before tumor resection and 24 h, 2 weeks, and 3, 6, 9, and 12 months after the surgery. The obtained data sets were analyzed using a linear mixed-effect model. The analysis revealed that concentration level of 2-methylthioadenosine was decreased, while for inosine, it was increased 24 h after tumor resection in comparison to the preoperative state. The presented quantitative longitudinal study of urine nucleosides and deoxynucleosides before and up to 12 months after bladder tumor resection brings additional prospective insight into the metabolite excretion pattern in bladder cancer disease. Moreover, incurred sample reanalysis was performed proving the robustness and repeatability of the developed targeted method.
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Affiliation(s)
- Małgorzata Artymowicz
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Aleja Gen. J. Hallera 107, 80-416, Gdańsk, Poland
| | - Wiktoria Struck-Lewicka
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Aleja Gen. J. Hallera 107, 80-416, Gdańsk, Poland
| | - Paweł Wiczling
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Aleja Gen. J. Hallera 107, 80-416, Gdańsk, Poland
| | - Marcin Markuszewski
- Department of Urology, Medical University of Gdańsk, Mariana Smoluchowskiego 17, 80-214, Gdańsk, Poland
| | - Michał J Markuszewski
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Aleja Gen. J. Hallera 107, 80-416, Gdańsk, Poland
| | - Danuta Siluk
- Department of Biopharmaceutics and Pharmacodynamics, Medical University of Gdańsk, Aleja Gen. J. Hallera 107, 80-416, Gdańsk, Poland.
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Liu Y, Wang H, Liang Y, Guo Z, Qu L, Wang Y, Zhang C, Sun G, Li Y. Dietary intakes of methionine, threonine, lysine, arginine and histidine increased risk of type 2 diabetes in Chinese population: does the mediation effect of obesity exist? BMC Public Health 2023; 23:1551. [PMID: 37582714 PMCID: PMC10428589 DOI: 10.1186/s12889-023-16468-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2023] [Accepted: 08/07/2023] [Indexed: 08/17/2023] Open
Abstract
BACKGROUND Published studies have shown positive associations of branched chain and aromatic amino acids with type 2 diabetes mellitus (T2DM), and the findings remain consistent. However, the associations of other essential and semi-essential amino acids, i.e., methionine (Met), threonine (Thr), lysine (Lys), arginine (Arg) and histidine (His), with T2DM remain unknown. Obesity is an important independent risk factor for T2DM, and excessive amino acids can convert into glucose and lipids, which might underlie the associations of amino acids with obesity. Therefore, we aimed to estimate the associations between dietary intakes of these 5 amino acids and T2DM risk, as well as the mediation effects of obesity on these associations, in a Chinese population. METHODS A total of 10,920 participants (57,293 person-years) were included, and dietary intakes of 5 amino acids were investigated using 24-h dietary recalls. Anthropometric obesity indices were measured at both baseline and the follow-up endpoints. Associations of amino acids with T2DM were estimated using COX regression models, hazard ratios (HRs) and 95% confidence intervals (95% CIs) were shown. The mediation effects of obesity indices were analyzed, and the proportion of the mediation effect was estimated. RESULTS Higher intakes of the 5 amino acids were associated with increasing T2DM risk, while significant HRs were only shown in men after adjustments. No interaction by gender was found. Regression analyses using quintiles of amino acids intakes showed that T2DM risk was positively associated with amino acids intakes only when comparing participants with the highest intake levels of amino acids to those with the lowest intake levels. Adjusted correlation coefficients between amino acid intakes and obesity indices measured at follow-up endpoints were significantly positive. Mediation analyses showed that mediation effects of obesity indices existed on associations between amino acids intakes and T2DM risk, and the mediation effect of waist circumference remained strongest for each amino acid. CONCLUSIONS We found positive associations of dietary intakes of Met, Thr, Lys, Arg and His with increasing T2DM risk in general Chinese residents, on which the mediation effect of obesity existed. These findings could be helpful for developing more constructive guidance in the primary prevention of T2DM based on dietary interventions.
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Affiliation(s)
- Yuyan Liu
- Department of Clinical Epidemiology, The Fourth Affiliated Hospital of China Medical University, Shenyang, Liaoning, China
| | - Huan Wang
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Yuanhong Liang
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Zijun Guo
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Litong Qu
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Ying Wang
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Chengwen Zhang
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Guifan Sun
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China
- School of Public Health, China Medical University, Shenyang, Liaoning, China
| | - Yongfang Li
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention (China Medical University), Ministry of Education, Shenyang, China.
- School of Public Health, China Medical University, Shenyang, Liaoning, China.
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Cheng Y, Azad MAK, Ding S, Liu Y, Blachier F, Ye T, Kong X. Metabolomics Analysis Reveals the Potential Relationship Between Sow Colostrum and Neonatal Serum Metabolites in Different Pig Breeds. Mol Nutr Food Res 2023; 67:e2200677. [PMID: 37436085 DOI: 10.1002/mnfr.202200677] [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: 10/07/2022] [Revised: 04/18/2023] [Indexed: 07/13/2023]
Abstract
SCOPE Colostrum composition is an important indicator of newborn piglet survival and growth. However, limited information is available on the association between colostrum metabolites in sows and serum metabolites in neonates. Therefore, the present study aims to determine the metabolites in the colostrum of sows, in the serum of their offspring piglets, and mother-offspring metabolite correlations in different pig breeds. METHODS AND RESULTS Colostrum and serum samples are collected from 30 sows and their piglets from three pig breeds (Taoyuan black, TB; Xiangcun black, XB; and Duroc) to analyze the targeted metabolomics. This study identifies 191 metabolites in the colostrum of sows, including fatty acids, amino acids, bile acids, carnitines, carbohydrates, and organic acids, and the concentrations of these metabolites are highest in the TB pigs. Metabolite profiles in sow colostrum and piglet serum differ among Duroc, TB, and XB pigs, and the matching metabolites are mainly enriched in the digestive system and transportation pathways. Furthermore, identification of the associations between metabolites in the colostrum of sows and their neonate sera suggests that metabolite compounds from colostrum are transported to suckling piglets. CONCLUSION The present study findings deepen the understanding of the composition of sow colostrum metabolites and the transportation of metabolites from sow colostrum to piglets. The findings also provide insight regarding the development of dietary formulas that resemble the sow colostrum for newborn animals to maintain health and improve the early growth of offspring.
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Affiliation(s)
- Yating Cheng
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Md Abul Kalam Azad
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Sujuan Ding
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
| | - Yating Liu
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
| | | | - Ting Ye
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
| | - Xiangfeng Kong
- Key Laboratory of Agro-ecological Processes in Subtropical Region, Hunan Provincial Key Laboratory of Animal Nutritional Physiology and Metabolic Process, National Engineering Laboratory for Pollution Control and Waste Utilization in Livestock and Poultry Production, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
- College of Advanced Agricultural Sciences, University of Chinese Academy of Sciences, Beijing, China
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Oliveira NCD, Balikian Júnior P, Júnior ATDC, Bento EDS, Tonholo J, Aquino T, Sousa FADB, Araujo GGD, Ferreira ML. Environmental Planning and Non-Communicable Diseases: A Systematic Review on the Role of the Metabolomic Profile. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:6433. [PMID: 37510665 PMCID: PMC10380082 DOI: 10.3390/ijerph20146433] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Revised: 07/17/2023] [Accepted: 07/21/2023] [Indexed: 07/30/2023]
Abstract
Non-communicable diseases (NCDs) are the major cause of death worldwide and have economic, psychological, and social impacts. Air pollution is the second, contributing to NCDs-related deaths. Metabolomics are a useful diagnostic and prognostic tool for NCDs, as they allow the identification of biomarkers linked to emerging pathologic processes. The aim of the present study was to review the scientific literature on the application of metabolomics profiling in NCDs and to discuss environmental planning actions to assist healthcare systems and public managers based on early metabolic diagnosis. The search was conducted following PRISMA guidelines using Web of Science, Scopus, and PubMed databases with the following MeSH terms: "metabolomics" AND "noncommunicable diseases" AND "air pollution". Twenty-nine studies were eligible. Eleven involved NCDs prevention, eight addressed diabetes mellitus, insulin resistance, systemic arterial hypertension, or metabolic syndrome. Six studies focused on obesity, two evaluated nonalcoholic fatty liver disease, two studied cancer, and none addressed chronic respiratory diseases. The studies provided insights into the biological pathways associated with NCDs. Understanding the cost of delivering care where there will be a critical increase in NCDs prevalence is crucial to achieving universal health coverage and improving population health by allocating environmental planning and treatment resources.
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Affiliation(s)
| | - Pedro Balikian Júnior
- Institute of Physical Education and Sport (IEFE), Federal University of Alagoas, Campus AC Simões, Maceió 57072-900, AL, Brazil
| | - Arnaldo Tenório da Cunha Júnior
- Kineanthropometry, Physical Activity and Health Promotion Laboratory (LACAPS), Physical Education Department, Federal University of Alagoas, Campus Arapiraca, Arapiraca 57309-005, AL, Brazil
| | - Edson de Souza Bento
- Institute of Chemistry and Biotechnology (IQB), Federal University of Alagoas, Campus AC Simões, Maceió 57072-900, AL, Brazil
| | - Josealdo Tonholo
- Institute of Chemistry and Biotechnology (IQB), Federal University of Alagoas, Campus AC Simões, Maceió 57072-900, AL, Brazil
| | - Thiago Aquino
- Institute of Chemistry and Biotechnology (IQB), Federal University of Alagoas, Campus AC Simões, Maceió 57072-900, AL, Brazil
| | - Filipe Antonio de Barros Sousa
- Institute of Physical Education and Sport (IEFE), Federal University of Alagoas, Campus AC Simões, Maceió 57072-900, AL, Brazil
| | - Gustavo Gomes de Araujo
- Institute of Physical Education and Sport (IEFE), Federal University of Alagoas, Campus AC Simões, Maceió 57072-900, AL, Brazil
| | - Maurício Lamano Ferreira
- Department of Geoenvironmental Analysis, Guarulhos University, Central Campus, Guarulhos 07023-070, SP, Brazil
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20
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Aleidi SM, Al Fahmawi H, Masoud A, Rahman AA. Metabolomics in diabetes mellitus: clinical insight. Expert Rev Proteomics 2023; 20:451-467. [PMID: 38108261 DOI: 10.1080/14789450.2023.2295866] [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: 08/02/2023] [Accepted: 12/13/2023] [Indexed: 12/19/2023]
Abstract
INTRODUCTION Diabetes Mellitus (DM) is a chronic heterogeneous metabolic disorder characterized by hyperglycemia due to the destruction of insulin-producing pancreatic β cells and/or insulin resistance. It is now considered a global epidemic disease associated with serious threats to a patient's life. Understanding the metabolic pathways involved in disease pathogenesis and progression is important and would improve prevention and management strategies. Metabolomics is an emerging field of research that offers valuable insights into the metabolic perturbation associated with metabolic diseases, including DM. AREA COVERED Herein, we discussed the metabolomics in type 1 and 2 DM research, including its contribution to understanding disease pathogenesis and identifying potential novel biomarkers clinically useful for disease screening, monitoring, and prognosis. In addition, we highlighted the metabolic changes associated with treatment effects, including insulin and different anti-diabetic medications. EXPERT OPINION By analyzing the metabolome, the metabolic disturbances involved in T1DM and T2DM can be explored, enhancing our understanding of the disease progression and potentially leading to novel clinical diagnostic and effective new therapeutic approaches. In addition, identifying specific metabolites would be potential clinical biomarkers for predicting the disease and thus preventing and managing hyperglycemia and its complications.
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Affiliation(s)
- Shereen M Aleidi
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Hiba Al Fahmawi
- Department of Biopharmaceutics and Clinical Pharmacy, School of Pharmacy, The University of Jordan, Amman, Jordan
| | - Afshan Masoud
- Proteomics Resource Unit, Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Anas Abdel Rahman
- Department of Biochemistry and Molecular Medicine, College of Medicine, Al Faisal University, Riyadh, Saudi Arabia
- Metabolomics Section, Department of Clinical Genomics, Center for Genomics Medicine, King Faisal Specialist Hospital and Research Centre, Riyadh, Saudi Arabia
- Department of Chemistry, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada
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21
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Cai D, Hou B, Xie SL. Amino acid analysis as a method of discovering biomarkers for diagnosis of diabetes and its complications. Amino Acids 2023:10.1007/s00726-023-03255-8. [PMID: 37067568 DOI: 10.1007/s00726-023-03255-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2022] [Accepted: 02/21/2023] [Indexed: 04/18/2023]
Abstract
Diabetes mellitus (DM) is a severe chronic diseases with a global prevalence of 9%, leading to poor health and high health care costs, and is a direct cause of millions of deaths each year. The rising epidemic of diabetes and its complications, such as retinal and peripheral nerve disease, is a huge burden globally. A better understanding of the molecular pathways involved in the development and progression of diabetes and its complications can facilitate individualized prevention and treatment. High diabetes mellitus incidence rate is caused mainly by lack of non-invasive and reliable methods for early diagnosis, such as plasma biomarkers. The incidence of diabetes and its complications in the world still grows so it is crucial to develop a new, faster, high specificity and more sensitive diagnostic technologies. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner, and effective biomarkers can greatly improve the efficiency of diabetes and its complications. By providing information on potential metabolic pathways, metabolomics can further define the mechanisms underlying the progression of diabetes and its complications, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The application of amino acid metabolomics in epidemiological studies has identified new biomarkers of diabetes mellitus (DM) and its complications, such as branched-chain amino acids, phenylalanine and arginine metabolites. This study focused on the analysis of metabolic amino acid profiling as a method for identifying biomarkers for the detection and screening of diabetes and its complications. The results presented are all from recent studies, and in all cases analyzed, there were significant changes in the amino acid profile of patients in the experimental group compared to the control group. This study demonstrates the potential of amino acid profiles as a detection method for diabetes and its complications.
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Affiliation(s)
- Dan Cai
- The Affiliated Nanhua Hospital, Department of Hand and Foot Surgery, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China
| | - Biao Hou
- The Affiliated Nanhua Hospital, Department of Hand and Foot Surgery, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China
| | - Song Lin Xie
- The Affiliated Nanhua Hospital, Department of Hand and Foot Surgery, Hengyang Medical School, University of South China, Hengyang, 421001, Hunan, China.
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22
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Calvani R, Picca A, Rodriguez-Mañas L, Tosato M, Coelho-Júnior HJ, Biancolillo A, Laosa O, Gervasoni J, Primiano A, Santucci L, Giampaoli O, Bourdel-Marchasson I, Regueme SC, Sinclair AJ, Urbani A, Landi F, Gambassi G, Marini F, Marzetti E. Amino Acid Profiles in Older Adults with Frailty: Secondary Analysis from MetaboFrail and BIOSPHERE Studies. Metabolites 2023; 13:metabo13040542. [PMID: 37110200 PMCID: PMC10147014 DOI: 10.3390/metabo13040542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/03/2023] [Revised: 04/07/2023] [Accepted: 04/09/2023] [Indexed: 04/29/2023] Open
Abstract
An altered amino acid metabolism has been described in frail older adults which may contribute to muscle loss and functional decline associated with frailty. In the present investigation, we compared circulating amino acid profiles of older adults with physical frailty and sarcopenia (PF&S, n = 94), frail/pre-frail older adults with type 2 diabetes mellitus (F-T2DM, n = 66), and robust non-diabetic controls (n = 40). Partial least squares discriminant analysis (PLS-DA) models were built to define the amino acid signatures associated with the different frailty phenotypes. PLS-DA allowed correct classification of participants with 78.2 ± 1.9% accuracy. Older adults with F-T2DM showed an amino acid profile characterized by higher levels of 3-methylhistidine, alanine, arginine, ethanolamine, and glutamic acid. PF&S and control participants were discriminated based on serum concentrations of aminoadipic acid, aspartate, citrulline, cystine, taurine, and tryptophan. These findings suggest that different types of frailty may be characterized by distinct metabolic perturbations. Amino acid profiling may therefore serve as a valuable tool for frailty biomarker discovery.
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Affiliation(s)
- Riccardo Calvani
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
- Department of Geriatrics and Orthopedics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Anna Picca
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
- Department of Medicine and Surgery, LUM University, 70010 Casamassima, Italy
| | - Leocadio Rodriguez-Mañas
- Servicio de Geriatría, Hospital Universitario de Getafe, 28905 Getafe, Spain
- Centro de Investigación Biomédica en Red "Fragilidad y Envejecimiento Saludable" (CIBERFES), Instituto de Salud Carlos III, 28029 Madrid, Spain
| | - Matteo Tosato
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
| | - Hélio José Coelho-Júnior
- Department of Geriatrics and Orthopedics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Alessandra Biancolillo
- Department of Physical and Chemical Sciences, Università degli Studi dell'Aquila, 67100 L'Aquila, Italy
| | - Olga Laosa
- Department of Medicine and Surgery, LUM University, 70010 Casamassima, Italy
- Geriatric Research Group, Biomedical Research Foundation at Getafe University Hospital, 28905 Getafe, Spain
| | - Jacopo Gervasoni
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
| | - Aniello Primiano
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
| | - Lavinia Santucci
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
| | - Ottavia Giampaoli
- Department of Chemistry, Sapienza Università di Roma, 00185 Rome, Italy
| | - Isabelle Bourdel-Marchasson
- Clinical Gerontology Department, Bordeaux University Hospital, 33000 Bordeaux, France
- CRMSB, CNRS UMR 5536, Université de Bordeaux, 33000 Bordeaux, France
| | - Sophie C Regueme
- CHU Bordeaux, Pole Gérontologie Clinique, 33000 Bordeaux, France
| | - Alan J Sinclair
- Foundation for Diabetes Research in Older People (fDROP), King's College, London WC2R 2LS, UK
| | - Andrea Urbani
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
- Department of Geriatrics and Orthopedics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Francesco Landi
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
- Department of Geriatrics and Orthopedics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Giovanni Gambassi
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
- Department of Geriatrics and Orthopedics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
| | - Federico Marini
- Department of Chemistry, Sapienza Università di Roma, 00185 Rome, Italy
| | - Emanuele Marzetti
- Fondazione Policlinico Universitario "Agostino Gemelli" IRCCS, 00168 Rome, Italy
- Department of Geriatrics and Orthopedics, Università Cattolica del Sacro Cuore, 00168 Rome, Italy
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23
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Mir FA, Mall R, Ullah E, Iskandarani A, Cyprian F, Samra TA, Alkasem M, Abdalhakam I, Farooq F, Taheri S, Abou-Samra AB. An integrated multi-omic approach demonstrates distinct molecular signatures between human obesity with and without metabolic complications: a case-control study. J Transl Med 2023; 21:229. [PMID: 36991398 PMCID: PMC10053148 DOI: 10.1186/s12967-023-04074-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 03/22/2023] [Indexed: 03/31/2023] Open
Abstract
OBJECTIVES To examine the hypothesis that obesity complicated by the metabolic syndrome, compared to uncomplicated obesity, has distinct molecular signatures and metabolic pathways. METHODS We analyzed a cohort of 39 participants with obesity that included 21 with metabolic syndrome, age-matched to 18 without metabolic complications. We measured in whole blood samples 754 human microRNAs (miRNAs), 704 metabolites using unbiased mass spectrometry metabolomics, and 25,682 transcripts, which include both protein coding genes (PCGs) as well as non-coding transcripts. We then identified differentially expressed miRNAs, PCGs, and metabolites and integrated them using databases such as mirDIP (mapping between miRNA-PCG network), Human Metabolome Database (mapping between metabolite-PCG network) and tools like MetaboAnalyst (mapping between metabolite-metabolic pathway network) to determine dysregulated metabolic pathways in obesity with metabolic complications. RESULTS We identified 8 significantly enriched metabolic pathways comprising 8 metabolites, 25 protein coding genes and 9 microRNAs which are each differentially expressed between the subjects with obesity and those with obesity and metabolic syndrome. By performing unsupervised hierarchical clustering on the enrichment matrix of the 8 metabolic pathways, we could approximately segregate the uncomplicated obesity strata from that of obesity with metabolic syndrome. CONCLUSIONS The data suggest that at least 8 metabolic pathways, along with their various dysregulated elements, identified via our integrative bioinformatics pipeline, can potentially differentiate those with obesity from those with obesity and metabolic complications.
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Affiliation(s)
- Fayaz Ahmad Mir
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar.
| | - Raghvendra Mall
- Department of Immunology, St. Jude Children's Research Hospital, Memphis, USA.
- Biotechnology Research Center, Technology Innovation Institute, P.O. Box 9639, Abu Dhabi, United Arab Emirates.
| | - Ehsan Ullah
- Qatar Computational Research Institute (QCRI), Hamad Bin Khalifa University, Doha, Qatar.
| | - Ahmad Iskandarani
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar
| | - Farhan Cyprian
- College of Medicine, QU Health, Qatar University, Doha, Qatar
| | - Tareq A Samra
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar
| | - Meis Alkasem
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar
| | - Ibrahem Abdalhakam
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar
| | - Faisal Farooq
- Qatar Computational Research Institute (QCRI), Hamad Bin Khalifa University, Doha, Qatar
| | - Shahrad Taheri
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar
- National Obesity Treatment Center, Hamad Medical Corporation, Doha, Qatar
- Weil Cornell Medicine - Qatar, Doha, Qatar
| | - Abdul-Badi Abou-Samra
- Qatar Metabolic Institute, Academic Health System, Hamad Medical Corporation, PO Box 3050, Doha, Qatar
- National Obesity Treatment Center, Hamad Medical Corporation, Doha, Qatar
- Weil Cornell Medicine - Qatar, Doha, Qatar
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24
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Role of Impaired Glycolysis in Perturbations of Amino Acid Metabolism in Diabetes Mellitus. Int J Mol Sci 2023; 24:ijms24021724. [PMID: 36675238 PMCID: PMC9863464 DOI: 10.3390/ijms24021724] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 01/10/2023] [Accepted: 01/13/2023] [Indexed: 01/18/2023] Open
Abstract
The most frequent alterations in plasma amino acid concentrations in type 1 and type 2 diabetes are decreased L-serine and increased branched-chain amino acid (BCAA; valine, leucine, and isoleucine) levels. The likely cause of L-serine deficiency is decreased synthesis of 3-phosphoglycerate, the main endogenous precursor of L-serine, due to impaired glycolysis. The BCAA levels increase due to decreased supply of pyruvate and oxaloacetate from glycolysis, enhanced supply of NADH + H+ from beta-oxidation, and subsequent decrease in the flux through the citric acid cycle in muscles. These alterations decrease the supply of α-ketoglutarate for BCAA transamination and the activity of branched-chain keto acid dehydrogenase, the rate-limiting enzyme in BCAA catabolism. L-serine deficiency contributes to decreased synthesis of phospholipids and increased synthesis of deoxysphinganines, which play a role in diabetic neuropathy, impaired homocysteine disposal, and glycine deficiency. Enhanced BCAA levels contribute to increased levels of aromatic amino acids (phenylalanine, tyrosine, and tryptophan), insulin resistance, and accumulation of various metabolites, whose influence on diabetes progression is not clear. It is concluded that amino acid concentrations should be monitored in patients with diabetes, and systematic investigation is needed to examine the effects of L-serine and glycine supplementation on diabetes progression when these amino acids are decreased.
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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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26
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Postmortem Metabolomics of Insulin Intoxications and the Potential Application to Find Hypoglycemia-Related Deaths. Metabolites 2022; 13:metabo13010005. [PMID: 36676928 PMCID: PMC9912265 DOI: 10.3390/metabo13010005] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2022] [Revised: 12/13/2022] [Accepted: 12/16/2022] [Indexed: 12/24/2022] Open
Abstract
Postmortem metabolomics can assist death investigations by characterizing metabolic fingerprints differentiating causes of death. Hypoglycemia-related deaths, including insulin intoxications, are difficult to identify and, thus, presumably underdiagnosed. This investigation aims to differentiate insulin intoxication deaths by metabolomics, and identify a metabolic fingerprint to screen for unknown hypoglycemia-related deaths. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry data were obtained from 19 insulin intoxications (hypo), 19 diabetic comas (hyper), and 38 hangings (control). Screening for potentially unknown hypoglycemia-related deaths was performed using 776 random postmortem cases. Data were processed using XCMS and SIMCA. Multivariate modeling revealed group separations between hypo, hyper, and control groups. A metabolic fingerprint for the hypo group was identified, and analyses revealed significant decreases in 12 acylcarnitines, including nine hydroxylated-acylcarnitines. Screening of random postmortem cases identified 46 cases (5.9%) as potentially hypoglycemia-related, including six with unknown causes of death. Autopsy report review revealed plausible hypoglycemia-cause for five unknown cases. Additionally, two diabetic cases were found, with a metformin intoxication and a suspicious but unverified insulin intoxication, respectively. Further studies are required to expand on the potential of postmortem metabolomics as a tool in hypoglycemia-related death investigations, and the future application of screening for potential insulin intoxications.
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Arjmand B, Ebrahimi Fana S, Ghasemi E, Kazemi A, Ghodssi-Ghassemabadi R, Dehghanbanadaki H, Najjar N, Kakaii A, Forouzanfar K, Nasli-Esfahani E, Farzadfar F, Larijani B, Razi F. Metabolic signatures of insulin resistance in non-diabetic individuals. BMC Endocr Disord 2022; 22:212. [PMID: 36002887 PMCID: PMC9404631 DOI: 10.1186/s12902-022-01130-3] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Accepted: 08/18/2022] [Indexed: 12/15/2022] Open
Abstract
BACKGROUND Insulin resistance (IR) evolved from excessive energy intake and poor energy expenditure, affecting the patient's quality of life. Amino acid and acylcarnitine metabolomic profiles have identified consistent patterns associated with metabolic disease and insulin sensitivity. Here, we have measured a wide array of metabolites (30 acylcarnitines and 20 amino acids) with the MS/MS and investigated the association of metabolic profile with insulin resistance. METHODS The study population (n = 403) was randomly chosen from non-diabetic participants of the Surveillance of Risk Factors of NCDs in Iran Study (STEPS 2016). STEPS 2016 is a population-based cross-sectional study conducted periodically on adults aged 18-75 years in 30 provinces of Iran. Participants were divided into two groups according to the optimal cut-off point determined by the Youden index of HOMA-IR for the diagnosis of metabolic syndrome. Associations were investigated using regression models adjusted for age, sex, and body mass index (BMI). RESULTS People with high IR were significantly younger, and had higher education level, BMI, waist circumference, FPG, HbA1c, ALT, triglyceride, cholesterol, non-HDL cholesterol, uric acid, and a lower HDL-C level. We observed a strong positive association of serum BCAA (valine and leucine), AAA (tyrosine, tryptophan, and phenylalanine), alanine, and C0 (free carnitine) with IR (HOMA-IR); while C18:1 (oleoyl L-carnitine) was inversely correlated with IR. CONCLUSIONS In the present study, we identified specific metabolites linked to HOMA-IR that improved IR prediction. In summary, our study adds more evidence that a particular metabolomic profile perturbation is associated with metabolic disease and reemphasizes the significance of understanding the biochemistry and physiology which lead to these associations.
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Affiliation(s)
- Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran, Iran
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Saeed Ebrahimi Fana
- Department of Clinical Biochemistry, School of Medicine, 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
| | - Ameneh Kazemi
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Hojat Dehghanbanadaki
- Diabetes Research Center, Endocrinology and Metabolism Clinical 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
| | - Ardeshir Kakaii
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular -Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Katayoon Forouzanfar
- 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
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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