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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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Gradisteanu Pircalabioru G, Musat M, Elian V, Iliescu C. Liquid Biopsy: A Game Changer for Type 2 Diabetes. Int J Mol Sci 2024; 25:2661. [PMID: 38473908 DOI: 10.3390/ijms25052661] [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: 12/22/2023] [Revised: 02/19/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024] Open
Abstract
As the burden of type 2 diabetes (T2D) continues to escalate globally, there is a growing need for novel, less-invasive biomarkers capable of early diabetes detection and monitoring of disease progression. Liquid biopsy, recognized for its minimally invasive nature, is increasingly being applied beyond oncology, and nevertheless shows its potential when the collection of the tissue biopsy is not possible. This diagnostic approach involves utilizing liquid biopsy markers such as cell-free nucleic acids, extracellular vesicles, and diverse metabolites for the molecular diagnosis of T2D and its related complications. In this context, we thoroughly examine recent developments in T2D liquid biopsy research. Additionally, we discuss the primary challenges and future prospects of employing liquid biopsy in the management of T2D. Prognosis, diagnosis and monitoring of T2D through liquid biopsy could be a game-changing technique for personalized diabetes management.
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Affiliation(s)
- Gratiela Gradisteanu Pircalabioru
- eBio-Hub Research-Center, National University of Science and Technology "Politehnica" Bucharest, 6 Iuliu Maniu Bulevard, Campus Building, 061344 Bucharest, Romania
- Research Institute of University of Bucharest, University of Bucharest, 050095 Bucharest, Romania
- Academy of Romanian Scientists, 3 Ilfov Str., 050094 Bucharest, Romania
| | - Madalina Musat
- eBio-Hub Research-Center, National University of Science and Technology "Politehnica" Bucharest, 6 Iuliu Maniu Bulevard, Campus Building, 061344 Bucharest, Romania
- Department of Endocrinology, Carol Davila University of Medicine and Pharmacy, 030167 Bucharest, Romania
- Department of Endocrinology, C.I. Parhon National Institute of Endocrinology, 011683 Bucharest, Romania
| | - Viviana Elian
- Department of Diabetes, Nutrition and Metabolic Diseases, Carol Davila University of Medicine and Pharmacy, 5-7 Ion Movila Street, 030167 Bucharest, Romania
- Department of Diabetes, Nutrition and Metabolic Diseases, Prof. Dr. N. C. Paulescu National Institute of Diabetes, Nutrition and Metabolic Diseases, 030167 Bucharest, Romania
| | - Ciprian Iliescu
- eBio-Hub Research-Center, National University of Science and Technology "Politehnica" Bucharest, 6 Iuliu Maniu Bulevard, Campus Building, 061344 Bucharest, Romania
- Academy of Romanian Scientists, 3 Ilfov Str., 050094 Bucharest, Romania
- National Research and Development Institute in Microtechnologies-IMT Bucharest, 126A Erou Iancu Nicolae Street, 077190 Voluntari, Romania
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Xu K, Zhang L, Wang T, Ren Z, Yu T, Zhang Y, Zhao X. Untargeted metabolomics reveals dynamic changes in metabolic profiles of rat supraspinatus tendon at three different time points after diabetes induction. Front Endocrinol (Lausanne) 2023; 14:1292103. [PMID: 38053726 PMCID: PMC10694349 DOI: 10.3389/fendo.2023.1292103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/11/2023] [Accepted: 11/01/2023] [Indexed: 12/07/2023] Open
Abstract
Objective To investigate the dynamic changes of metabolite composition in rat supraspinatus tendons at different stages of diabetes by untargeted metabolomics analysis. Methods A total of 80 Sprague-Dawley rats were randomly divided into normal (NG, n = 20) and type 2 diabetes mellitus groups (T2DM, n = 60) and subdivided into three groups according to the duration of diabetes: T2DM-4w, T2DM-12w, and T2DM-24w groups; the duration was calculated from the time point of T2DM rat model establishment. The three comparison groups were set up in this study, T2DM-4w group vs. NG, T2DM-12w group vs. T2DM-4w group, and T2DM-24w group vs. T2DM-12w group. The metabolite profiles of supraspinatus tendon were obtained using tandem mass spectrometry. Metabolomics multivariate statistics were used for metabolic data analysis and differential metabolite (DEM) determination. The intersection of the three comparison groups' DEMs was defined as key metabolites that changed consistently in the supraspinatus tendon after diabetes induction; then, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed. Results T2DM-4w group vs. NG, T2DM-12w group vs. T2DM-4w group, and T2DM-24w group vs. T2DM-12w group detected 94 (86 up-regulated and 8 down-regulated), 36 (13 up-regulated and 23 down-regulated) and 86 (24 up-regulated and 62 down-regulated) DEMs, respectively. Seven key metabolites of sustained changes in the supraspinatus tendon following induction of diabetes include D-Lactic acid, xanthine, O-acetyl-L-carnitine, isoleucylproline, propoxycarbazone, uric acid, and cytidine, which are the first identified biomarkers of the supraspinatus tendon as it progresses through the course of diabetes. The results of KEGG pathway enrichment analysis showed that the main pathway of supraspinatus metabolism affected by diabetes (p < 0.05) was purine metabolism. The results of the KEGG metabolic pathway vs. DEMs correlation network graph revealed that uric acid and xanthine play a role in more metabolic pathways. Conclusion Untargeted metabolomics revealed the dynamic changes of metabolite composition in rat supraspinatus tendons at different stages of diabetes, and the newly discovered seven metabolites, especially uric acid and xanthine, may provide novel research to elucidate the mechanism of diabetes-induced tendinopathy.
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Affiliation(s)
- Kuishuai Xu
- Department of Sports Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Liang Zhang
- Department of Sports Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tianrui Wang
- Department of Sports Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Zhongkai Ren
- Department of Sports Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Tengbo Yu
- Department of Sports Medicine, Qingdao Municipal Hospital, Qingdao, Shandong, China
| | - Yingze Zhang
- Department of Sports Medicine, Affiliated Hospital of Qingdao University, Qingdao, China
| | - Xia Zhao
- Department of Sports Medicine, Affiliated Hospital of Qingdao University, Qingdao, 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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Balint L, Socaciu C, Socaciu AI, Vlad A, Gadalean F, Bob F, Milas O, Cretu OM, Suteanu-Simulescu A, Glavan M, Ienciu S, Mogos M, Jianu DC, Petrica L. Quantitative, Targeted Analysis of Gut Microbiota Derived Metabolites Provides Novel Biomarkers of Early Diabetic Kidney Disease in Type 2 Diabetes Mellitus Patients. Biomolecules 2023; 13:1086. [PMID: 37509122 PMCID: PMC10377254 DOI: 10.3390/biom13071086] [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: 05/08/2023] [Revised: 06/29/2023] [Accepted: 07/04/2023] [Indexed: 07/30/2023] Open
Abstract
Diabetic kidney disease (DKD) is one of the most debilitating complications of type 2 diabetes mellitus (T2DM), as it progresses silently to end-stage renal disease (ESRD). The discovery of novel biomarkers of early DKD becomes acute, as its incidence is reaching catastrophic proportions. Our study aimed to quantify previously identified metabolites from serum and urine through untargeted ultra-high-performance liquid chromatography coupled with electrospray ionization-quadrupole-time of flight-mass spectrometry (UHPLC-QTOF-ESI+-MS) techniques, such as the following: arginine, dimethylarginine, hippuric acid, indoxyl sulfate, p-cresyl sulfate, L-acetylcarnitine, butenoylcarnitine and sorbitol. The study concept was based on the targeted analysis of selected metabolites, using the serum and urine of 20 healthy subjects and 90 T2DM patients with DKD in different stages (normoalbuminuria-uACR < 30 mg/g; microalbuminuria-uACR 30-300 mg/g; macroalbuminuria-uACR > 300 mg/g). The quantitative evaluation of metabolites was performed with pure standards, followed by the validation methods such as the limit of detection (LOD) and the limit of quantification (LOQ). The following metabolites from this study resulted as possible biomarkers of early DKD: in serum-arginine, dimethylarginine, hippuric acid, indoxyl sulfate, butenoylcarnitine and sorbitol and in urine-p-cresyl sulfate.
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Affiliation(s)
- Lavinia Balint
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Carmen Socaciu
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
- Research Center for Applied Biotechnology and Molecular Therapy Biodiatech, SC Proplanta, Trifoiului 12G, 400478 Cluj-Napoca, Romania
| | - Andreea Iulia Socaciu
- Department of Occupational Health, University of Medicine and Pharmacy "Iuliu Haţieganu", Victor Babes 8, 400347 Cluj-Napoca, Romania
| | - Adrian Vlad
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
- Department of Internal Medicine II-Division of Diabetes and Metabolic Diseases, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
| | - Florica Gadalean
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Flaviu Bob
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Oana Milas
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Octavian Marius Cretu
- Department of Surgery I-Division of Surgical Semiology I, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, Emergency Clinical Municipal Hospital, 300041 Timisoara, Romania
| | - Anca Suteanu-Simulescu
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Mihaela Glavan
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Silvia Ienciu
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Maria Mogos
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Dragos Catalin Jianu
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
- Department of Neurosciences-Division of Neurology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Cognitive Research in Neuropsychiatric Pathology (Neuropsy-Cog), Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
| | - Ligia Petrica
- Department of Internal Medicine II-Division of Nephrology, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, County Emergency Hospital, 300041 Timisoara, Romania
- Center for Molecular Research in Nephrology and Vascular Disease, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
- Center for Cognitive Research in Neuropsychiatric Pathology (Neuropsy-Cog), Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie Murgu Sq. No. 2, 300041 Timisoara, Romania
- Center for Translational Research and Systems Medicine, Faculty of Medicine, "Victor Babes" University of Medicine and Pharmacy, Eftimie, Murgu Sq. No. 2, 300041 Timisoara, Romania
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Identification of FGF13 as a Potential Biomarker and Target for Diagnosis of Impaired Glucose Tolerance. Int J Mol Sci 2023; 24:ijms24021807. [PMID: 36675322 PMCID: PMC9867186 DOI: 10.3390/ijms24021807] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2022] [Revised: 01/08/2023] [Accepted: 01/11/2023] [Indexed: 01/19/2023] Open
Abstract
Early identification of pre-diabetes provides an opportunity for intervention and treatment to delay its progression to type 2 diabetes mellitus (T2DM). We aimed to identify the biomarkers of impaired glucose tolerance (IGT) through bioinformatics analysis. The GSE76896 dataset, including non-diabetic (ND), IGT, and T2DM clinical samples, was deeply analyzed to identify 309 Co-DEGs for IGT and T2DM. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses indicated that inflammatory responses and the PI3K-AKT signaling pathway are important patho-physiological features of IGT and T2DM. Protein-protein interaction (PPI) network analysis and cytoHubba technolgy identified seven hub genes: namely, CCL2, CXCL1, CXCL8, EDN1, FGF13, MMP1, and NGF. The expression and ROC curves of these hub genes were validated using the GSE38642 dataset. Through an immunofluorescence assay, we found that the expression of FGF13 in islets of mice in the HFD and T2DM groups was significantly lower than in the control group. Similarly, the level of FGF13 in the sera of IGT and T2DM patients was lower than that in the healthy group. Together, these results suggest that FGF13 can be treated as a novel biomarker of IGT, which may provide new targets for the diagnosis and treatment of pre-diabetes and T2DM.
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Moura AV, de Oliveira DC, Silva AAR, da Rosa JR, Garcia PHD, Sanches PHG, Garza KY, Mendes FMM, Lambert M, Gutierrez JM, Granado NM, dos Santos AC, de Lima IL, Negrini LDDO, Antonio MA, Eberlin MN, Eberlin LS, Porcari AM. Urine Metabolites Enable Fast Detection of COVID-19 Using Mass Spectrometry. Metabolites 2022; 12:1056. [PMID: 36355139 PMCID: PMC9697918 DOI: 10.3390/metabo12111056] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2022] [Revised: 10/19/2022] [Accepted: 10/27/2022] [Indexed: 08/27/2023] Open
Abstract
The COVID-19 pandemic boosted the development of diagnostic tests to meet patient needs and provide accurate, sensitive, and fast disease detection. Despite rapid advancements, limitations related to turnaround time, varying performance metrics due to different sampling sites, illness duration, co-infections, and the need for particular reagents still exist. As an alternative diagnostic test, we present urine analysis through flow-injection-tandem mass spectrometry (FIA-MS/MS) as a powerful approach for COVID-19 diagnosis, targeting the detection of amino acids and acylcarnitines. We adapted a method that is widely used for newborn screening tests on dried blood for urine samples in order to detect metabolites related to COVID-19 infection. We analyzed samples from 246 volunteers with diagnostic confirmation via PCR. Urine samples were self-collected, diluted, and analyzed with a run time of 4 min. A Lasso statistical classifier was built using 75/25% data for training/validation sets and achieved high diagnostic performances: 97/90% sensitivity, 95/100% specificity, and 95/97.2% accuracy. Additionally, we predicted on two withheld sets composed of suspected hospitalized/symptomatic COVID-19-PCR negative patients and patients out of the optimal time-frame collection for PCR diagnosis, with promising results. Altogether, we show that the benchmarked FIA-MS/MS method is promising for COVID-19 screening and diagnosis, and is also potentially useful after the peak viral load has passed.
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Affiliation(s)
- Alexandre Varao Moura
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Danilo Cardoso de Oliveira
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Alex Ap. R. Silva
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Jonas Ribeiro da Rosa
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Pedro Henrique Dias Garcia
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Pedro Henrique Godoy Sanches
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Kyana Y. Garza
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA
| | - Flavio Marcio Macedo Mendes
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Mayara Lambert
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Junier Marrero Gutierrez
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Nicole Marino Granado
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
| | - Alicia Camacho dos Santos
- Department of Material Engineering and Nanotechnology, Mackenzie Presbyterian University, São Paulo 01302-907, SP, Brazil
| | - Iasmim Lopes de Lima
- Department of Material Engineering and Nanotechnology, Mackenzie Presbyterian University, São Paulo 01302-907, SP, Brazil
| | | | - Marcia Aparecida Antonio
- Integrated Unit of Pharmacology and Gastroenterology, UNIFAG, Bragança Paulista 12916-900, SP, Brazil
| | - Marcos N. Eberlin
- Department of Material Engineering and Nanotechnology, Mackenzie Presbyterian University, São Paulo 01302-907, SP, Brazil
| | - Livia S. Eberlin
- Department of Chemistry, The University of Texas at Austin, Austin, TX 78712, USA
- Department of Surgery, Baylor College of Medicine, Houston, TX 77030, USA
| | - Andreia M. Porcari
- MSLife Laboratory of Mass Spectrometry, Health Sciences Postgraduate Program, São Francisco University, Bragança Paulista 12916-900, SP, Brazil
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9
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Hosseinkhani S, Salari P, Bandarian F, Asadi M, Shirani S, Najjar N, Dehghanbanadaki H, Pasalar P, Razi F. Circulating amino acids and acylcarnitines correlated with different CAC score ranges in diabetic postmenopausal women using LC-MS/MS based metabolomics approach. BMC Endocr Disord 2022; 22:186. [PMID: 35864499 PMCID: PMC9306187 DOI: 10.1186/s12902-022-01073-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Accepted: 06/06/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Diabetes mellitus (DM) and its cardiovascular disease (CVD) complication are among the most frequent causes of death worldwide. However, the metabolites linking up diabetes and CVD are less understood. In this study, we aimed to evaluate serum acylcarnitines and amino acids in postmenopausal women suffering from diabetes with different severity of CVD and compared them with healthy controls. METHODS Through a cross-sectional study, samples were collected from postmenopausal women without diabetes and CVD as controls (n = 20), patients with diabetes and without CVD (n = 16), diabetes with low risk of CVD (n = 11), and diabetes with a high risk of CVD (n = 21) referred for CT angiography for any reason. Metabolites were detected by a targeted approach using LC-MS/MS and metabolic -alterations were assessed by applying multivariate statistical analysis. The diagnostic ability of discovered metabolites based on multivariate statistical analysis was evaluated by ROC curve analysis. RESULTS The study included women aged from 50-80 years with 5-30 years of menopause. The relative concentration of C14:1, C14:2, C16:1, C18:1, and C18:2OH acylcarnitines decreased and C18 acylcarnitine and serine increased in diabetic patients compared to control. Besides, C16:1 and C18:2OH acylcarnitines increased in high-risk CVD diabetic patients compared to no CVD risk diabetic patients. CONCLUSION Dysregulation of serum acylcarnitines and amino acids profile correlated with different CAC score ranges in diabetic postmenopausal women. (Ethic approval No: IR.TUMS.EMRI.REC.1399.062).
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Affiliation(s)
- Shaghayegh Hosseinkhani
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Clinical Biochemistry, Faculty of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Pooneh Salari
- Medical Ethics and History of Medicine Research Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Fatemeh Bandarian
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Mojgan Asadi
- Osteoporosis Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Shapour Shirani
- Imaging Department, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Niloufar Najjar
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hojat Dehghanbanadaki
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Parvin Pasalar
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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10
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Wang Z, Tang J, Jin E, Zhong Y, Zhang L, Han X, Liu J, Cheng Y, Hou J, Shi X, Qi H, Qian T, Yuan L, Hou X, Yin H, Liang J, Zhao M, Huang L, Qu J. Serum Untargeted Metabolomics Reveal Potential Biomarkers of Progression of Diabetic Retinopathy in Asians. Front Mol Biosci 2022; 9:871291. [PMID: 35755823 PMCID: PMC9224596 DOI: 10.3389/fmolb.2022.871291] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Accepted: 04/25/2022] [Indexed: 12/16/2022] Open
Abstract
Purpose: To reveal molecular mechanisms of diabetic retinopathy (DR) in Asians and facilitate the identification of new therapeutic targets through untargeted metabolomics. To determine the differences in serum metabolites and metabolic pathways between different stages of diabetic retinopathy in patients with type 2 diabetic mellitus (T2DM) and proliferative DR (PDR) and non-proliferative DR (NPDR) and identify differential metabolites between T2DM and DR (NPDR and PDR) patients. Methods: This prospective observational registration study described the differential metabolites between 45 T2DM patients and 15 control cases with no significant differences in clinical characteristics. Their biospecimens and clinical information were collected and recorded in their medical reports. DR phenotypes of the subjects were verified by retina specialists. Serum metabolites were analyzed using high-resolution mass spectrometry with liquid chromatography. Untargeted metabolomics was performed on serum samples from 15 T2DM patients, 15 non-proliferative diabetic retinopathy patients, 15 proliferative diabetic retinopathy patients, and 15 diabetic controls. Discriminatory metabolic features were identified through partial least squares discriminant analysis (PLS-DA), hierarchical clustering analysis (HCA), and generalized linear regression models. Result: Through untargeted metabolomics, 931 features (523 in positive and 408 in negative modes) with 102 common metabolites highly relevant to the presence of DR were detected. In the adjusted analysis, 67 metabolic features differed significantly between T2DM and NPDR patients. Pathway analysis revealed alterations in metabolisms of amino acids and fatty acids. Glutamate, phosphatidylcholine, and 13-hydroperoxyoctadeca-9,11-dienoic acid (13-PHODE) were key contributors to these pathway differences. A total of 171 features distinguished PDR patients from T2DM patients, and pathway analysis revealed alterations in amino acid metabolism, fatty acid metabolism, nitrogen metabolism, and tricarboxylic acid cycle. Aspartate, glutamate, glutamine, ornithine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, citrate, succinate, N-(L-arginino)succinate, 2-oxoglutarate, 13-hydroperoxyoctadeca-9,11-dienoic acid, methionine, lysine, threonine, phenylalanine, N(pi)-methyl-l-histidine, phosphatidylcholine, and linoleate were major contributors to the pathway differences. Between NPDR patients and PDR patients, there were 79 significant differential metabolites. Enrichment pathway analysis showed changes in amino acid metabolism, fatty acid metabolism, pantothenate, and CoA biosynthesis. Aspartate, glutamine, N-acetyl-l-glutamate, N-acetyl-l-aspartate, pantothenate, dihomo-gamma-linolenate, docosahexaenoic acid, and icosapentaenoic acid were key factors for the differences of these pathways. Conclusion: This study demonstrated that the pathways of arginine biosynthesis metabolism, linoleic acid metabolism, alanine, aspartate, and glutamate metabolism, as well as d-glutamine and d-glutamate metabolism, were dysregulated in DR patients of the Asian population. Increased levels of glutamate, aspartate, glutamine, N-acetyl-l-glutamate, and N-acetyl-l-aspartate and decreased levels of dihomo-gamma-linolenate, docosahexaenoic, and icosapentaenoic were considered as the metabolic profile that could distinguish PDR from NPDR in Asians. Phosphatidylcholine and 13-PHODE were identified as two major novel metabolite markers in advanced stages of DR in our study.
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Affiliation(s)
- Zongyi Wang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jiyang Tang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Enzhong Jin
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yusheng Zhong
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Linqi Zhang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Xinyao Han
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jia Liu
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yong Cheng
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jing Hou
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Xuan Shi
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Huijun Qi
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Tong Qian
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Li Yuan
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Xianru Hou
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Hong Yin
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jianhong Liang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Mingwei Zhao
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Lvzhen Huang
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jinfeng Qu
- Department of Ophthalmology, Peking University People's Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
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11
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Alsoud LO, Soares NC, Al-Hroub HM, Mousa M, Kasabri V, Bulatova N, Suyagh M, Alzoubi KH, El-Huneidi W, Abu-Irmaileh B, Bustanji Y, Semreen MH. Identification of Insulin Resistance Biomarkers in Metabolic Syndrome Detected by UHPLC-ESI-QTOF-MS. Metabolites 2022; 12:metabo12060508. [PMID: 35736441 PMCID: PMC9227428 DOI: 10.3390/metabo12060508] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 05/28/2022] [Accepted: 05/29/2022] [Indexed: 02/04/2023] Open
Abstract
Metabolic syndrome (MetS) is a disorder characterized by a group of factors that can increase the risk of chronic diseases, including cardiovascular diseases and type 2 diabetes mellitus (T2D). Metabolomics has provided new insight into disease diagnosis and biomarker identification. This cross-sectional investigation used an untargeted metabolomics-based technique to uncover metabolomic alterations and their relationship to pathways in normoglycemic and prediabetic MetS participants to improve disease diagnosis. Plasma samples were collected from drug-naive prediabetic MetS patients (n = 26), normoglycemic MetS patients (n = 30), and healthy (normoglycemic lean) subjects (n = 30) who met the inclusion criteria for the study. The plasma samples were analyzed using highly sensitive ultra-high-performance liquid chromatography electrospray ionization quadrupole time-of-flight mass spectrometry (UHPLC-ESI-QTOF-MS). One-way ANOVA analysis revealed that 59 metabolites differed significantly among the three groups (p < 0.05). Glutamine, 5-hydroxy-L-tryptophan, L-sorbose, and hippurate were highly associated with MetS. However, 9-methyluric acid, sphinganine, and threonic acid were highly associated with prediabetes/MetS. Metabolic pathway analysis showed that arginine biosynthesis and glutathione metabolism were associated with MetS/prediabetes, while phenylalanine, D-glutamine and D-glutamate, and lysine degradation were highly impacted in MetS. The current study sheds light on the potential diagnostic value of some metabolites in metabolic syndrome and the role of their alteration on some of the metabolic pathways. More studies are needed in larger cohorts in order to verify the implication of the above metabolites on MetS and their diagnostic value.
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Affiliation(s)
- Leen Oyoun Alsoud
- College of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (L.O.A.); (N.C.S.); (K.H.A.)
| | - Nelson C. Soares
- College of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (L.O.A.); (N.C.S.); (K.H.A.)
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (H.M.A.-H.); (W.E.-H.)
| | - Hamza M. Al-Hroub
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (H.M.A.-H.); (W.E.-H.)
| | - Muath Mousa
- Research Institute of Science and Engineering, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates;
| | - Violet Kasabri
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan; (V.K.); (N.B.); (M.S.)
| | - Nailya Bulatova
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan; (V.K.); (N.B.); (M.S.)
| | - Maysa Suyagh
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan; (V.K.); (N.B.); (M.S.)
| | - Karem H. Alzoubi
- College of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (L.O.A.); (N.C.S.); (K.H.A.)
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (H.M.A.-H.); (W.E.-H.)
| | - Waseem El-Huneidi
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (H.M.A.-H.); (W.E.-H.)
- College of Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
| | - Bashaer Abu-Irmaileh
- Hamdi Mango Center for Scientific Research, The University of Jordan, Amman 11942, Jordan;
| | - Yasser Bustanji
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (H.M.A.-H.); (W.E.-H.)
- School of Pharmacy, The University of Jordan, Amman 11942, Jordan; (V.K.); (N.B.); (M.S.)
- College of Medicine, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates
- Correspondence: (Y.B.); (M.H.S.)
| | - Mohammad H. Semreen
- College of Pharmacy, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (L.O.A.); (N.C.S.); (K.H.A.)
- Sharjah Institute for Medical Research, University of Sharjah, Sharjah P.O. Box 27272, United Arab Emirates; (H.M.A.-H.); (W.E.-H.)
- Correspondence: (Y.B.); (M.H.S.)
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12
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Hosseinkhani S, Arjmand B, Dilmaghani-Marand A, Mohammadi Fateh S, Dehghanbanadaki H, Najjar N, Alavi-Moghadam S, Ghodssi-Ghassemabadi R, Nasli-Esfahani E, Farzadfar F, Larijani B, Razi F. Targeted metabolomics analysis of amino acids and acylcarnitines as risk markers for diabetes by LC-MS/MS technique. Sci Rep 2022; 12:8418. [PMID: 35589736 PMCID: PMC9119932 DOI: 10.1038/s41598-022-11970-7] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 04/27/2022] [Indexed: 11/29/2022] Open
Abstract
Diabetes is a common chronic disease affecting millions of people worldwide. It underlies various complications and imposes many costs on individuals and society. Discovering early diagnostic biomarkers takes excellent insight into preventive plans and the best use of interventions. Therefore, in the present study, we aimed to evaluate the association between the level of amino acids and acylcarnitines and diabetes to develop diabetes predictive models. Using the targeted LC-MS/MS technique, we analyzed fasting plasma samples of 206 cases and 206 controls that were matched by age, sex, and BMI. The association between metabolites and diabetes was evaluated using univariate and multivariate regression analysis with adjustment for systolic and diastolic blood pressure and lipid profile. To deal with multiple comparisons, factor analysis was used. Participants' average age and BMI were 61.6 years, 28.9 kg/m2, and 55% were female. After adjustment, Factor 3 (tyrosine, valine, leucine, methionine, tryptophan, phenylalanine), 5 (C3DC, C5, C5OH, C5:1), 6 (C14OH, C16OH, C18OH, C18:1OH), 8 (C2, C4OH, C8:1), 10 (alanine, proline) and 11 (glutamic acid, C18:2OH) were positively associated with diabetes. Inline, factor 9 (C4DC, serine, glycine, threonine) and 12 (citrulline, ornithine) showed a reverse trend. Some amino acids and acylcarnitines were found as potential risk markers for diabetes incidents that reflected the disturbances in the several metabolic pathways among the diabetic population and could be targeted to prevent, diagnose, and treat diabetes.
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Affiliation(s)
- Shaghayegh Hosseinkhani
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Department of Clinical Biochemistry, School of Medicine, Tehran University of Medical Sciences, Tehran, Iran
| | - Babak Arjmand
- Cell Therapy and Regenerative Medicine Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran, Iran
| | - Arezou Dilmaghani-Marand
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sahar Mohammadi Fateh
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Hojat Dehghanbanadaki
- Metabolic Disorders Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Niloufar Najjar
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Sepideh Alavi-Moghadam
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Ensieh Nasli-Esfahani
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farshad Farzadfar
- Non-Communicable Diseases Research Center, Endocrinology and Metabolism Population Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Bagher Larijani
- Endocrinology and Metabolism Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran
| | - Farideh Razi
- Diabetes Research Center, Endocrinology and Metabolism Clinical Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
- Metabolomics and Genomics Research Center, Endocrinology and Metabolism Molecular-Cellular Sciences Institute, Tehran University of Medical Sciences, Tehran, Iran.
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13
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Wang Z, Tang J, Jin E, Ren C, Li S, Zhang L, Zhong Y, Cao Y, Wang J, Zhou W, Zhao M, Huang L, Qu J. Metabolomic comparison followed by cross-validation of enzyme-linked immunosorbent assay to reveal potential biomarkers of diabetic retinopathy in Chinese with type 2 diabetes. Front Endocrinol (Lausanne) 2022; 13:986303. [PMID: 36157454 PMCID: PMC9492931 DOI: 10.3389/fendo.2022.986303] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 08/23/2022] [Indexed: 11/13/2022] Open
Abstract
PURPOSE To identify the biomarkers in the critical period of development in diabetic retinopathy (DR) in Chinese with type 2 diabetes using targeted and untargeted metabolomics, and to explore the feasibility of their clinical application. METHODS This case-control study described the differential metabolites between 83 Chinese type 2 diabetes mellitus (T2DM) samples with disease duration ≥ 10 years and 27 controls matched cases. Targeted metabolomics using high-resolution mass spectrometry with liquid chromatography was performed on plasma samples of subjects. The results were compared to our previous untargeted metabolomics study and ELISA was performed to validate the mutual differential metabolites of targeted and untargeted metabolomics on plasma. Multiple linear regression analyses were performed to adjust for the significance of different metabolites between groups. RESULT Mean age of the subjects was 66.3 years and mean T2DM duration was 16.5 years. By cross-validating with results from previous untargeted metabolomic assays, we found that L-Citrulline (Cit), indoleacetic acid (IAA), 1-methylhistidine (1-MH), phosphatidylcholines (PCs), hexanoylcarnitine, chenodeoxycholic acid (CDCA) and eicosapentaenoic acid (EPA) were the most distinctive metabolites biomarkers to distinguish the severity of DR for two different metabolomic approaches in our study. We mainly found that samples in the DR stage showed lower serum level of Cit and higher serum level of IAA compared with samples in the T2DM stage, while during the progression of diabetic retinopathy, the serum levels of CDCA and EPA in PDR stage were significantly lower than NPDR stage. Among them, 4 differential key metabolites including Cit, IAA, CDCA and EPA were confirmed with ELISA. CONCLUSION This is the first study to compare the results of targeted and untargeted metabolomics via liquid chromatography-mass spectrometry to find the serum biomarkers which could reflect the metabolic variations among different stages of DR in Chinese. The progression of DR in Chinese at different critical stages was related to the serum levels of specific differential metabolites, of which there is a significant correlation between DR progression and increased IAA and decreased Cit, hexanoylcarnitine, CDCA, and EPA. However, larger studies are needed to confirm our results. Based on this study, it could be inferred that the accuracy of targeted metabolomics for metabolite expression in serum is to some extent higher than that of untargeted metabolomics.
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Affiliation(s)
- Zongyi Wang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jiyang Tang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Enzhong Jin
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Chi Ren
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Siying Li
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Linqi Zhang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yusheng Zhong
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Yu Cao
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Jianmin Wang
- Department of Ophthalmology, The Second Hospital of Hebei Medical University, Shijiazhuang, China
| | - Wei Zhou
- Department of Ophthalmology, Tianjin Medical University General Hospital, Tianjin, China
| | - Mingwei Zhao
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
| | - Lvzhen Huang
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
- *Correspondence: Jinfeng Qu, ; Lvzhen Huang,
| | - Jinfeng Qu
- Department of Ophthalmology, Peking University People’s Hospital, Eye Diseases and Optometry Institute, Beijing Key Laboratory of Diagnosis and Therapy of Retinal and Choroid Diseases, College of Optometry, Peking University Health Science Center, Beijing, China
- *Correspondence: Jinfeng Qu, ; Lvzhen Huang,
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14
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Mu X, Yang M, Ling P, Wu A, Zhou H, Jiang J. Acylcarnitines: Can They Be Biomarkers of Diabetic Nephropathy? Diabetes Metab Syndr Obes 2022; 15:247-256. [PMID: 35125878 PMCID: PMC8811266 DOI: 10.2147/dmso.s350233] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2021] [Accepted: 01/13/2022] [Indexed: 12/22/2022] Open
Abstract
Diabetic nephropathy (DN), one of the most serious microvascular complications of diabetes mellitus (DM), may progress to end-stage renal disease (ESRD). Current biochemical biomarkers, such as urinary albumin excretion rate (UAER), have limitations for early screening and monitoring of DN. Recent studies have identified some metabolites as candidate biomarkers for early detection of DN. In this review, we summarize the role of dysregulated acylcarnitines (AcylCNs) in DN pathophysiology. Lower abundance of short- and medium-chain AcylCNs and higher long-chain AcylCNs often occurred in DM with normal albuminuria and microalbuminuria, compared with advanced stages of DN. The increase of long-chain AcylCNs was supposed to be an adaptive compensation in fat acids (FAs) oxidation in the early stage of DN. Conversely, the decrease of long-chain AcylCNs was due to incomplete oxidation of FAs in advanced stage of DN. Thus, AcylCNs may serve as sensitive biomarkers in predicting the risk of DN.
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Affiliation(s)
- Xiaodie Mu
- Department of Nephrology, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China
| | - Min Yang
- Department of Nephrology, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China
| | - Peiyao Ling
- Department of Nephrology, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China
| | - Aihua Wu
- Department of Nephrology, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China
| | - Hua Zhou
- Department of Nephrology, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China
- Correspondence: Hua Zhou; Jingting Jiang, Department of Nephrology, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China, Tel +86 0519 68872082, Email ;
| | - Jingting Jiang
- Department of Tumor Biological Treatment, The Third Affiliated Hospital of Soochow University, Changzhou, 213003, People’s Republic of China
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