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Chai J, Sun Z, Xu J. A Contemporary Insight of Metabolomics Approach for Type 1 Diabetes: Potential for Novel Diagnostic Targets. Diabetes Metab Syndr Obes 2022; 15:1605-1625. [PMID: 35642181 PMCID: PMC9148614 DOI: 10.2147/dmso.s357007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2022] [Accepted: 04/08/2022] [Indexed: 11/23/2022] Open
Abstract
High-throughput omics has been widely applied in metabolic disease, type 1 diabetes (T1D) was one of the most typical diseases. Effective prevention and early diagnosis are very important because of infancy and persistent characteristics of T1D. The occurrence and development of T1D is a chronic and continuous process, in which the production of autoantibodies (ie serum transformation) occupies the central position. Metabolomics can evaluate the metabolic characteristics of serum before seroconversion, the changes with age and T1D complications. And the addition of natural drug metabolomics is more conducive to the systematic and comprehensive diagnosis and treatment of T1D. This paper reviewed the metabolic changes and main pathogenesis from pre-diagnosis to treatment in T1D. The metabolic spectrum of significant abnormal energy and glucose-related metabolic pathway, down-regulation of lipid metabolism and up-regulation of some antioxidant pathways has appeared before seroconversion, indicating that the body has been in the dual state of disease progression and disease resistance before T1D onset. Some metabolites (such as methionine) are closely related to age, and the types of autoantibodies produced are age-specific. Some metabolites may jointly predict DN with eGFR, and metabolomics can further contribute to the pathogenesis based on the correlation between DN and DR. Many natural drug components have been proved to act on abnormal metabolic pathways of T1D and have a positive impact on some metabolic levels, which is very important for further finding therapeutic targets and developing new drugs with small side effects. Metabolomics can provide auxiliary value for the diagnosis of T1D and provide a new direction to reveal the pathogenesis of T1D and find new therapeutic targets. The development of T1D metabolomics shows that high-throughput research methods are expected to be introduced into clinical practice.
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Affiliation(s)
- Jiatong Chai
- Department of Laboratory Medicine, The First Hospital of Jilin University, Changchun, People’s Republic of China
| | - Zeyu Sun
- Department of Laboratory Medicine, The First Hospital of Jilin University, Changchun, People’s Republic of China
| | - Jiancheng Xu
- Department of Laboratory Medicine, The First Hospital of Jilin University, Changchun, People’s Republic of China
- Correspondence: Jiancheng Xu, Department of Laboratory Medicine, The First Bethune Hospital of Jilin University, 71 Xinmin Street, Changchun, 130021, People’s Republic of China, Tel +86-431-8878-2595, Fax +86-431-8878-6169, Email
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Samanta T, Sharma P, Kukri D, Kar S. Decoding the regulatory mechanism of glucose and insulin induced phosphatidylinositol 3,4,5-trisphosphate dynamics in β-cells. MOLECULAR BIOSYSTEMS 2018. [PMID: 28636047 DOI: 10.1039/c7mb00227k] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
In MIN6 pancreatic β-cells, glucose and insulin act in a synergistic manner to regulate the dynamics of Phosphatidylinositol (3,4,5)-trisphosphate (PIP3). However, the precise regulatory mechanism behind such an experimentally observed synergy is poorly understood. In this article, we propose a phenomenological mathematical model for studying the glucose and insulin driven PIP3 activation dynamics under various stimulatory conditions to unfold the mechanism responsible for the observed synergy. The modeling study reveals that the experimentally observed oscillation in PIP3 dynamics with disparate time scales for different external glucose doses is mainly orchestrated by the complex dynamic regulation of cytosolic Ca2+ in β-cells. The model accounts for the dose-dependent activation of PIP3 as a function of externally added insulin, and further shows that even in the absence of Ca2+ signaling, externally added glucose can still maintain a basal level of endogenous insulin secretion via the fatty acid metabolism pathway. Importantly, the model analysis suggests that the glucose mediated ROS (reactive oxygen species) activation often contributes considerably to the synergistic activation of PIP3 by glucose and insulin in a context dependent manner. Under the physiological conditions that keep β-cells in an insulin responsive state, the effect of glucose induced ROS signaling plays a moderate role in PIP3 activation. As β-cells approach an insulin resistant state, the glucose induced ROS signaling significantly affects the PIP3 dynamics. Our findings provide a plausible mechanistic insight into the experimentally observed synergy, and can lead to novel therapeutic strategies.
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Affiliation(s)
- Tagari Samanta
- Department of Chemistry, IIT Bombay, Powai, Mumbai - 400076, India.
| | - Peeyush Sharma
- Department of Chemistry, IIT Bombay, Powai, Mumbai - 400076, India.
| | - Dwijendra Kukri
- Department of Chemistry, IIT Bombay, Powai, Mumbai - 400076, India.
| | - Sandip Kar
- Department of Chemistry, IIT Bombay, Powai, Mumbai - 400076, India.
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Abstract
Metabolomics is the snapshot of all detectable metabolites and lipids in biological materials and has potential in reflecting genetic and environmental factors contributing to the development of complex diseases, such as type 1 diabetes. The progression to seroconversion to development of type 1 diabetes has been studied using this technique, although in relatively small cohorts and at limited time points. Overall, three observations have been consistently reported; phospholipids at birth are lower in children developing type 1 diabetes early in childhood, methionine levels are lower in children at seroconversion, and triglycerides are increased at seroconversion and associated to microbiome diversity, indicating an association between the metabolome and microbiome in type 1 diabetes progression.
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Affiliation(s)
- Anne Julie Overgaard
- Department of Pediatrics, Herlev University Hospital, Herlev Ringvej 75, DK-2730, Herlev, Denmark.
| | - Simranjeet Kaur
- Department of Pediatrics, Herlev University Hospital, Herlev Ringvej 75, DK-2730, Herlev, Denmark
| | - Flemming Pociot
- Department of Pediatrics, Herlev University Hospital, Herlev Ringvej 75, DK-2730, Herlev, Denmark
- Institute of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, DK-2200, Copenhagen N, Denmark
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Modeling strategies to study metabolic pathways in progression to type 1 diabetes – Challenges and opportunities. Arch Biochem Biophys 2016; 589:131-7. [DOI: 10.1016/j.abb.2015.08.011] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2015] [Revised: 07/29/2015] [Accepted: 08/20/2015] [Indexed: 11/23/2022]
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Jaberi-Douraki M, Liu SW(S, Pietropaolo M, Khadra A. Autoimmune responses in T1DM: quantitative methods to understand onset, progression, and prevention of disease. Pediatr Diabetes 2014; 15:162-74. [PMID: 24827702 PMCID: PMC4050373 DOI: 10.1111/pedi.12148] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/11/2014] [Revised: 03/12/2014] [Accepted: 04/01/2014] [Indexed: 02/06/2023] Open
Abstract
Understanding the physiological processes that underlie autoimmune disorders and identifying biomarkers to predict their onset are two pressing issues that need to be thoroughly sorted out by careful thought when analyzing these diseases. Type 1 diabetes (T1D) is a typical example of such diseases. It is mediated by autoreactive cytotoxic CD4⁺ and CD8⁺ T-cells that infiltrate the pancreatic islets of Langerhans and destroy insulin-secreting β-cells, leading to abnormal levels of glucose in affected individuals. The disease is also associated with a series of islet-specific autoantibodies that appear in high-risk subjects (HRS) several years prior to the onset of diabetes-related symptoms. It has been suggested that T1D is relapsing-remitting in nature and that islet-specific autoantibodies released by lymphocytic B-cells are detectable at different stages of the disease, depending on their binding affinity (the higher, the earlier they appear). The multifaceted nature of this disease and its intrinsic complexity make this disease very difficult to analyze experimentally as a whole. The use of quantitative methods, in the form of mathematical models and computational tools, to examine the disease has been a very powerful tool in providing predictions and insights about the underlying mechanism(s) regulating its onset and development. Furthermore, the models developed may have prognostic implications by aiding in the enrollment of HRS into trials for T1D prevention. In this review, we summarize recent advances made in determining T- and B-cell involvement in T1D using these quantitative approaches and delineate areas where mathematical modeling can make further contributions in unraveling certain aspect of this disease.
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Affiliation(s)
- Majid Jaberi-Douraki
- Department of Physiology, McGill University, McIntyre Medical Building, 3655 Promenade Sir William Osler, Montreal, Quebec, Canada H3G 1Y6
| | - Shang Wan (Shalon) Liu
- Department of Physiology, McGill University, McIntyre Medical Building, 3655 Promenade Sir William Osler, Montreal, Quebec, Canada H3G 1Y6
| | - Massimo Pietropaolo
- Laboratory of Immunogenetics, University of Michigan, Ann Arbor, MI, USA 48105-5714
| | - Anmar Khadra
- Department of Physiology, McGill University, McIntyre Medical Building, 3655 Promenade Sir William Osler, Montreal, Quebec, Canada H3G 1Y6
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Saki N, Jalalifar MA, Soleimani M, Hajizamani S, Rahim F. Adverse effect of high glucose concentration on stem cell therapy. Int J Hematol Oncol Stem Cell Res 2013; 7:34-40. [PMID: 24505533 PMCID: PMC3913149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2013] [Accepted: 06/02/2013] [Indexed: 11/22/2022] Open
Abstract
Stem cell therapy could have great potential for the treatment of a wide variety of diseases. Stem cells might have the ability to differentiate into a widespread cell types, and to repopulate and revitalize the damaged cells with healthy tissue, and improve its performance. We provide here the evidence supporting the critical use of stem cell as a treatment in disease conditions existing with high glucose complaint such as diabetes. The reduction of glucose stimulated cell proliferation and high glucose enhanced apoptosis in rat model, which may be a problem in therapeutic strategies based on ex vivo expansion of stem cell, and may also propagate the development of osteoporosis in high glucose complaint such as diabetes. This leads to the hypothesis that, high glucose could be more deleterious to stem cell therapy that may be due to the aggravation of oxidative stress triggered by high glucose. These findings may help to understand the possible reasons associated with high glucose induced detrimental effects on stem cells as well as provide novel therapeutic strategies for preventing the adverse effects of glucose on the development and progression of stem cells in patients with diabetes.
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Affiliation(s)
- Najmaldin Saki
- Research Center of Thalassemia & Hemoglobinopathy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Mohammad Ali Jalalifar
- Research Center of Thalassemia & Hemoglobinopathy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Masoud Soleimani
- Department of Hematology and Blood Banking, School of Medical Sciences, Tarbiat Modares University, Tehran, Iran
| | - Saeideh Hajizamani
- Research Center of Thalassemia & Hemoglobinopathy, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran
| | - Fakher Rahim
- Toxicology Research Center, Ahvaz University of Medical Sciences, Ahvaz, Iran,Corresponding Author: Fakher Rahim, Ph.D. in Molecular Medicine, Toxicology Research Center, Ahvaz University of medical Sciences (AJUMS), Ahvaz, Iran. Tel/Fax: +986113367562. E-mail:
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Abstract
The metabolome is sensitive to genetic and environmental factors contributing to complex diseases such as type 1 diabetes (T1D). Metabolomics is the study of biochemical and physiological processes involving metabolites. It is therefore one of the key platforms for the discovery and study of pathophysiological phenomena leading to T1D and the development of T1D-associated complications. Although the application of metabolomics in T1D research is still rare, metabolomic research has already advanced across the full spectrum, from disease progression to the development of diabetic complications. Metabolomic studies in T1D have contributed to an improved etiopathogenic understanding and demonstrated their potential in the clinic. For example, metabolomic data from recent T1D studies suggest that a specific metabolic profile, or metabotype, precedes islet autoimmunity and the development of overt T1D. These early metabolic changes are attributed to many biochemical pathways, thus suggesting a systemic change in metabolism which may be inborn. Based on this evidence, the role of the metabolome in the progression to T1D is therefore to facilitate specific biochemical processes associated with T1D, and to contribute to the development of a vulnerable state in which disease is more likely to be triggered. This may have important implications for the understanding of T1D pathophysiology and early disease detection and prevention.
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Affiliation(s)
- Matej Oresic
- VTT Technical Research Centre of Finland, Tietotie 2, Espoo, FIN-02044 VTT, Finland.
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