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Luo Y, Zhang W, Qin G. Metabolomics in diabetic nephropathy: Unveiling novel biomarkers for diagnosis (Review). Mol Med Rep 2024; 30:156. [PMID: 38963028 PMCID: PMC11258608 DOI: 10.3892/mmr.2024.13280] [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: 03/22/2024] [Accepted: 06/21/2024] [Indexed: 07/05/2024] Open
Abstract
Diabetic nephropathy (DN) also known as diabetic kidney disease, is a major microvascular complication of diabetes and a leading cause of end‑stage renal disease (ESRD), which affects the morbidity and mortality of patients with diabetes. Despite advancements in diabetes care, current diagnostic methods, such as the determination of albuminuria and the estimated glomerular filtration rate, are limited in sensitivity and specificity, often only identifying kidney damage after considerable morphological changes. The present review discusses the potential of metabolomics as an approach for the early detection and management of DN. Metabolomics is the study of metabolites, the small molecules produced by cellular processes, and may provide a more sensitive and specific diagnostic tool compared with traditional methods. For the purposes of this review, a systematic search was conducted on PubMed and Google Scholar for recent human studies published between 2011 and 2023 that used metabolomics in the diagnosis of DN. Metabolomics has demonstrated potential in identifying metabolic biomarkers specific to DN. The ability to detect a broad spectrum of metabolites with high sensitivity and specificity may allow for earlier diagnosis and better management of patients with DN, potentially reducing the progression to ESRD. Furthermore, metabolomics pathway analysis assesses the pathophysiological mechanisms underlying DN. On the whole, metabolomics is a potential tool in the diagnosis and management of DN. By providing a more in‑depth understanding of metabolic alterations associated with DN, metabolomics could significantly improve early detection, enable timely interventions and reduce the healthcare burdens associated with this condition.
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Affiliation(s)
- Yuanyuan Luo
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan 450052, P.R. China
| | - Wei Zhang
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan 450052, P.R. China
| | - Guijun Qin
- Department of Endocrinology and Metabolism, The First Affiliated Hospital of Zhengzhou University, Zhengzhou University, Zhengzhou, Henan 450052, P.R. China
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Yagin FH, Colak C, Algarni A, Gormez Y, Guldogan E, Ardigò LP. Hybrid Explainable Artificial Intelligence Models for Targeted Metabolomics Analysis of Diabetic Retinopathy. Diagnostics (Basel) 2024; 14:1364. [PMID: 39001254 PMCID: PMC11241009 DOI: 10.3390/diagnostics14131364] [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: 05/21/2024] [Revised: 06/24/2024] [Accepted: 06/25/2024] [Indexed: 07/16/2024] Open
Abstract
BACKGROUND Diabetic retinopathy (DR) is a prevalent microvascular complication of diabetes mellitus, and early detection is crucial for effective management. Metabolomics profiling has emerged as a promising approach for identifying potential biomarkers associated with DR progression. This study aimed to develop a hybrid explainable artificial intelligence (XAI) model for targeted metabolomics analysis of patients with DR, utilizing a focused approach to identify specific metabolites exhibiting varying concentrations among individuals without DR (NDR), those with non-proliferative DR (NPDR), and individuals with proliferative DR (PDR) who have type 2 diabetes mellitus (T2DM). METHODS A total of 317 T2DM patients, including 143 NDR, 123 NPDR, and 51 PDR cases, were included in the study. Serum samples underwent targeted metabolomics analysis using liquid chromatography and mass spectrometry. Several machine learning models, including Support Vector Machines (SVC), Random Forest (RF), Decision Tree (DT), Logistic Regression (LR), and Multilayer Perceptrons (MLP), were implemented as solo models and in a two-stage ensemble hybrid approach. The models were trained and validated using 10-fold cross-validation. SHapley Additive exPlanations (SHAP) were employed to interpret the contributions of each feature to the model predictions. Statistical analyses were conducted using the Shapiro-Wilk test for normality, the Kruskal-Wallis H test for group differences, and the Mann-Whitney U test with Bonferroni correction for post-hoc comparisons. RESULTS The hybrid SVC + MLP model achieved the highest performance, with an accuracy of 89.58%, a precision of 87.18%, an F1-score of 88.20%, and an F-beta score of 87.55%. SHAP analysis revealed that glucose, glycine, and age were consistently important features across all DR classes, while creatinine and various phosphatidylcholines exhibited higher importance in the PDR class, suggesting their potential as biomarkers for severe DR. CONCLUSION The hybrid XAI models, particularly the SVC + MLP ensemble, demonstrated superior performance in predicting DR progression compared to solo models. The application of SHAP facilitates the interpretation of feature importance, providing valuable insights into the metabolic and physiological markers associated with different stages of DR. These findings highlight the potential of hybrid XAI models combined with explainable techniques for early detection, targeted interventions, and personalized treatment strategies in DR management.
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Affiliation(s)
- Fatma Hilal Yagin
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya 44280, Turkey
| | - Cemil Colak
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya 44280, Turkey
| | - Abdulmohsen Algarni
- Department of Computer Science, King Khalid University, Abha 61421, Saudi Arabia
| | - Yasin Gormez
- Department of Management Information Systems, Faculty of Economics and Administrative Sciences, Sivas Cumhuriyet University, Sivas 58140, Turkey
| | - Emek Guldogan
- Department of Biostatistics and Medical Informatics, Faculty of Medicine, Inonu University, Malatya 44280, Turkey
| | - Luca Paolo Ardigò
- Department of Teacher Education, NLA University College, 0166 Oslo, Norway
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Yazdanpanah M, Yazdanpanah N, Gamache I, Ong K, Perry JRB, Manousaki D. Metabolome-wide Mendelian randomization for age at menarche and age at natural menopause. Genome Med 2024; 16:69. [PMID: 38802955 PMCID: PMC11131236 DOI: 10.1186/s13073-024-01322-7] [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: 10/31/2023] [Accepted: 03/22/2024] [Indexed: 05/29/2024] Open
Abstract
BACKGROUND The role of metabolism in the variation of age at menarche (AAM) and age at natural menopause (ANM) in the female population is not entirely known. We aimed to investigate the causal role of circulating metabolites in AAM and ANM using Mendelian randomization (MR). METHODS We combined MR with genetic colocalization to investigate potential causal associations between 658 metabolites and AAM and between 684 metabolites and ANM. We extracted genetic instruments for our exposures from four genome-wide association studies (GWAS) on circulating metabolites and queried the effects of these variants on the outcomes in two large GWAS from the ReproGen consortium. Additionally, we assessed the mediating role of the body mass index (BMI) in these associations, identified metabolic pathways implicated in AAM and ANM, and sought validation for selected metabolites in the Avon Longitudinal Study of Parents and Children (ALSPAC). RESULTS Our analysis identified 10 candidate metabolites for AAM, but none of them colocalized with AAM. For ANM, 76 metabolites were prioritized (FDR-adjusted MR P-value ≤ 0.05), with 17 colocalizing, primarily in the glycerophosphocholines class, including the omega-3 fatty acid and phosphatidylcholine (PC) categories. Pathway analyses and validation in ALSPAC mothers also highlighted the role of omega and polyunsaturated fatty acids levels in delaying age at menopause. CONCLUSIONS Our study suggests that metabolites from the glycerophosphocholine and fatty acid families play a causal role in the timing of both menarche and menopause. This underscores the significance of specific metabolic pathways in the biology of female reproductive longevity.
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Affiliation(s)
- Mojgan Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada
| | - Nahid Yazdanpanah
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada
| | - Isabel Gamache
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada
| | - Ken Ong
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - John R B Perry
- MRC Epidemiology Unit, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
- Metabolic Research Laboratory, School of Clinical Medicine, Wellcome-MRC Institute of Metabolic Science, University of Cambridge, Cambridge, CB2 0QQ, UK
| | - Despoina Manousaki
- Research Center of the Sainte-Justine University Hospital, Université de Montréal, 3175 Côte-Sainte-Catherine, Montréal, Québec, H3T 1C5, Canada.
- Departments of Pediatrics, Biochemistry and Molecular Medicine, Université de Montréal, Montreal, Canada.
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Pausova Z, Sliz E. Large-Scale Population-Based Studies of Blood Metabolome and Brain Health. Curr Top Behav Neurosci 2024. [PMID: 38509405 DOI: 10.1007/7854_2024_463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/22/2024]
Abstract
Metabolomics technologies enable the quantification of multiple metabolomic measures simultaneously, which provides novel insights into molecular aspects of human health and disease. In large-scale, population-based studies, blood is often the preferred biospecimen. Circulating metabolome may relate to brain health either by affecting or reflecting brain metabolism. Peripheral metabolites may act at or cross the blood-brain barrier and, subsequently, influence brain metabolism, or they may reflect brain metabolism if similar pathways are engaged. Peripheral metabolites may also include those penetrating the circulation from the brain, indicating, for example, brain damage. Most brain health-related metabolomics studies have been conducted in the context of neurodegenerative disorders and cognition, but some studies have also focused on neuroimaging markers of these disorders. Moreover, several metabolomics studies of neurodevelopmental disorders have been performed. Here, we provide a brief background on the types of blood metabolites commonly assessed, and we review the literature describing the relationships between human blood metabolome (n > 50 metabolites) and brain health reported in large-scale studies (n > 500 individuals).
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Affiliation(s)
- Zdenka Pausova
- The Hospital for Sick Children, Toronto, ON, Canada
- Departments of Physiology and Nutritional Sciences, University of Toronto, Toronto, ON, Canada
| | - Eeva Sliz
- Research Unit of Population Health, Faculty of Medicine, University of Oulu, Oulu, Finland.
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Gong K, Chen J, Yin X, Wu M, Zheng H, Jiang L. Untargeted metabolomics analysis reveals spatial metabolic heterogeneity in different intestinal segments of type 1 diabetic mice. Mol Omics 2024; 20:128-137. [PMID: 37997452 DOI: 10.1039/d3mo00163f] [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: 11/25/2023]
Abstract
Type 1 diabetes (T1D) has been reported to cause systematic metabolic disorders, but metabolic changes in different intestinal segments of T1D remain unclear. In this study, we analyzed metabolic profiles in the jejunum, ileum, cecum and colon of streptozocin-induced T1D and age-matched control (CON) mice by an LC-MS-based metabolomics method. The results show that segment-specific metabolic disorders occurred in the gut of T1D mice. In the jejunum, we found that T1D mainly led to disordered amino acid metabolism and most amino acids were significantly lower relative to CON mice. Moreover, fatty acid metabolism was disrupted mainly in the ileum, cecum and colon of T1D mice, such as arachidonic acid, alpha-linolenic acid and linoleic acid metabolism. Thus, our study reveals spatial metabolic heterogeneity in the gut of T1D mice and provides a metabolic view on diabetes-associated intestinal diseases.
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Affiliation(s)
- Kaiyan Gong
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
| | - Junli Chen
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
| | - Xiaoli Yin
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
| | - Mengjun Wu
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
| | - Hong Zheng
- School of Pharmaceutical Sciences, Wenzhou Medical University, Wenzhou 325035, China.
| | - Lingling Jiang
- College of Science and Technology, Wenzhou-Kean University, Wenzhou 325060, China.
- Wenzhou Municipal Key Laboratory for Applied Biomedical and Biopharmaceutical Informatics, Wenzhou-Kean University, Wenzhou 325060, China
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Jung S, Silva S, Dallal CM, LeBlanc E, Paris K, Shepherd J, Snetselaar LG, Van Horn L, Zhang Y, Dorgan JF. Untargeted serum metabolomic profiles and breast density in young women. Cancer Causes Control 2024; 35:323-334. [PMID: 37737303 DOI: 10.1007/s10552-023-01793-w] [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: 01/21/2023] [Accepted: 09/06/2023] [Indexed: 09/23/2023]
Abstract
PURPOSE OF THE STUDY Breast density is an established risk factor for breast cancer. However, little is known about metabolic influences on breast density phenotypes. We conducted untargeted serum metabolomics analyses to identify metabolic signatures associated with breast density phenotypes among young women. METHODS In a cross-sectional study of 173 young women aged 25-29 who participated in the Dietary Intervention Study in Children 2006 Follow-up Study, 449 metabolites were measured in fasting serum samples using ultra-high-performance liquid chromatography-tandem mass spectrometry. Multivariable-adjusted mixed-effects linear regression identified metabolites associated with magnetic resonance imaging measured breast density phenotypes: percent dense breast volume (%DBV), absolute dense breast volume (ADBV), and absolute non-dense breast volume (ANDBV). Metabolite results were corrected for multiple comparisons using a false discovery rate adjusted p-value (q). RESULTS The amino acids valine and leucine were significantly inversely associated with %DBV. For each 1 SD increase in valine and leucine, %DBV decreased by 20.9% (q = 0.02) and 18.4% (q = 0.04), respectively. ANDBV was significantly positively associated with 16 lipid and one amino acid metabolites, whereas no metabolites were associated with ADBV. Metabolite set enrichment analysis also revealed associations of distinct metabolic signatures with %DBV, ADBV, and ANDBV; branched chain amino acids had the strongest inverse association with %DBV (p = 0.002); whereas, diacylglycerols and phospholipids were positively associated with ANDBV (p ≤ 0.002), no significant associations were observed for ADBV. CONCLUSION Our results suggest an inverse association of branched chain amino acids with %DBV. Larger studies in diverse populations are needed.
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Affiliation(s)
- Seungyoun Jung
- Department of Nutritional Science and Food Management, Ewha Womans University, Seoul, South Korea
- Graduate Program in System Health Science and Engineering, Ewha Womans University, Seoul, South Korea
| | - Sarah Silva
- University of Maryland School of Medicine, Baltimore, MD, USA
| | - Cher M Dallal
- Department of Epidemiology and Biostatistics, School of Public Health, University of Maryland, College Park, MD, USA
| | - Erin LeBlanc
- Kaiser Permanente Center for Health Research, Portland, OR, USA
| | - Kenneth Paris
- Department of Pediatrics, Louisiana State University School of Medicine, New Orleans, LA, USA
| | - John Shepherd
- University of Hawaii Cancer Center, Honolulu, HI, USA
| | | | - Linda Van Horn
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
| | - Yuji Zhang
- Division of Cancer Epidemiology, Department of Epidemiology and Public Health, University of Maryland School of Medicine, 660 West Redwood St., Howard Hall, Room 102E, Baltimore, MD, 21201, USA
| | - Joanne F Dorgan
- Division of Cancer Epidemiology, Department of Epidemiology and Public Health, University of Maryland School of Medicine, 660 West Redwood St., Howard Hall, Room 102E, Baltimore, MD, 21201, USA.
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Ma L, Liu J, Deng M, Zhou L, Zhang Q, Xiao X. Metabolomics analysis of serum and urine in type 1 diabetes patients with different time in range derived from continuous glucose monitoring. Diabetol Metab Syndr 2024; 16:21. [PMID: 38238828 PMCID: PMC10797982 DOI: 10.1186/s13098-024-01257-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 01/03/2024] [Indexed: 01/22/2024] Open
Abstract
BACKGROUND Time in range (TIR), as an important glycemic variability (GV) index, is clearly associated with disease complications in type 1 diabetes (T1D). Metabolic dysregulation is also involved in the risks of T1D complications. However, the relationship between metabolites and TIR remains poorly understood. We used metabolomics to investigate metabolic profile changes in T1D patients with different TIR. METHODS This study included 85 T1D patients and 81 healthy controls. GV indices, including TIR, were collected from continuous glucose monitoring system. The patients were compared within two subgroups: TIR-L (TIR < 50%, n = 21) and TIR-H (TIR > 70%, n = 14). To screen for differentially abundant metabolites and metabolic pathways, serum and urine samples were obtained for untargeted metabolomics by ultra-performance liquid chromatography‒mass spectrometry. Correlation analysis was conducted with GV metrics and screened biomarkers. RESULTS Metabolites were significantly altered in T1D and subgroups. Compared with healthy controls, T1D patients had higher serum levels of 5-hydroxy-L-tryptophan, 5-methoxyindoleacetate, 4-(2-aminophenyl)-2,4-dioxobutanoate, and 4-pyridoxic acid and higher urine levels of thromboxane B3 but lower urine levels of hypoxanthine. Compared with TIR-H group, The TIR-L subgroup had lower serum levels of 5-hydroxy-L-tryptophan and mevalonolactone and lower urine levels of thromboxane B3 and phenylbutyrylglutamine. Dysregulation of pathways, such as tryptophan, vitamin B6 and purine metabolism, may be involved in the mechanism of diabetic complications related to glycemic homeostasis. Mevalonolactone, hypoxanthine and phenylbutyrylglutamine showed close correlation with TIR. CONCLUSIONS We identified altered metabolic profiles in T1D individuals with different TIR. These findings provide new insights and merit further exploration of the underlying molecular pathways relating to diabetic complications.
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Affiliation(s)
- Liyuan Ma
- Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Jieying Liu
- Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
- Department of Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Mingqun Deng
- Department of Endocrinology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China
| | - Liyuan Zhou
- Department of Endocrinology, Beijing Chao-Yang Hospital, Capital Medical University, Beijing, 100020, China
| | - Qian Zhang
- Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China
| | - Xinhua Xiao
- Department of Endocrinology, Key Laboratory of Endocrinology, Ministry of Health, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, 100730, China.
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Li J, Zhu N, Wang Y, Bao Y, Xu F, Liu F, Zhou X. Application of Metabolomics and Traditional Chinese Medicine for Type 2 Diabetes Mellitus Treatment. Diabetes Metab Syndr Obes 2023; 16:4269-4282. [PMID: 38164418 PMCID: PMC10758184 DOI: 10.2147/dmso.s441399] [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: 09/21/2023] [Accepted: 11/21/2023] [Indexed: 01/03/2024] Open
Abstract
Diabetes is a major global public health problem with high incidence and case fatality rates. Traditional Chinese medicine (TCM) is used to help manage Type 2 Diabetes Mellitus (T2DM) and has steadily gained international acceptance. Despite being generally accepted in daily practice, the TCM methods and hypotheses for understanding diseases lack applicability in the current scientific characterization systems. To date, there is no systematic evaluation system for TCM in preventing and treating T2DM. Metabonomics is a powerful tool to predict the level of metabolites in vivo, reveal the potential mechanism, and diagnose the physiological state of patients in time to guide the follow-up intervention of T2DM. Notably, metabolomics is also effective in promoting TCM modernization and advancement in personalized medicine. This review provides updated knowledge on applying metabolomics to TCM syndrome differentiation, diagnosis, biomarker discovery, and treatment of T2DM by TCM. Its application in diabetic complications is discussed. The combination of multi-omics and microbiome to fully elucidate the use of TCM to treat T2DM is further envisioned.
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Affiliation(s)
- Jing Li
- Jilin Ginseng Academy, Changchun University of Chinese Medicine, Changchun, People’s Republic of China
| | - Na Zhu
- Clinical Trial Research Center, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Central Hospital, Qingdao, People’s Republic of China
| | - Yaqiong Wang
- Clinical Trial Research Center, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Central Hospital, Qingdao, People’s Republic of China
| | - Yanlei Bao
- Department of Pharmacy, Liaoyuan People’s Hospital, Liaoyuan, People’s Republic of China
| | - Feng Xu
- Clinical Trial Research Center, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Central Hospital, Qingdao, People’s Republic of China
| | - Fengjuan Liu
- Clinical Trial Research Center, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Central Hospital, Qingdao, People’s Republic of China
| | - Xuefeng Zhou
- Clinical Trial Research Center, Affiliated Qingdao Central Hospital of Qingdao University, Qingdao Central Hospital, Qingdao, People’s Republic of China
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Hu C, Wang J, Qi F, Liu Y, Zhao F, Wang J, Sun B. Untargeted metabolite profiling of serum in rats exposed to pyrraline. Food Sci Biotechnol 2023; 32:1541-1549. [PMID: 37637845 PMCID: PMC10449741 DOI: 10.1007/s10068-023-01256-7] [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: 01/28/2022] [Revised: 12/27/2022] [Accepted: 01/10/2023] [Indexed: 01/27/2023] Open
Abstract
Pyrraline, one of advanced glycation end-products, is formed in advanced Maillard reactions. It was reported that the presence of pyrraline was tested to be associated with nephropathy and diabetes. Pyrraline might result in potential health risks because many modern diets are heat processed. In the study, an integrated metabolomics by ultra-high-performance liquid chromatography with mass spectrometry was used to evaluate the effects of pyrraline on metabolism in rats. Thirty-two metabolites were identified as differential metabolites. Linolenic acid metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, arachidonic acid metabolism, tyrosine metabolism and glycerophospholipid metabolism were the main perturbed networks in this pathological process. Differential metabolites and metabolic pathways we found give new insights into studying the toxic molecular mechanisms of pyrraline. Supplementary Information The online version contains supplementary material available at 10.1007/s10068-023-01256-7.
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Affiliation(s)
- Chuanqin Hu
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Jiahui Wang
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Fangyuan Qi
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Yingli Liu
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Fen Zhao
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Jing Wang
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
| | - Baoguo Sun
- China-Canada Joint Lab of Food Nutrition and Health (Beijing), Beijing Advanced Innovation Center for Food Nutrition and Human Health, Beijing Engineering and Technology Research Center of Food Additives, Beijing Laboratory for Food Quality and Safety, Key Laboratory of Cleaner Production and Integrated Resource Utilization of China National Light Industry, Beijing Technology and Business University (BTBU), 11 Fucheng Road, Beijing, 100048 China
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Martín-Masot R, Jiménez-Muñoz M, Herrador-López M, Navas-López VM, Obis E, Jové M, Pamplona R, Nestares T. Metabolomic Profiling in Children with Celiac Disease: Beyond the Gluten-Free Diet. Nutrients 2023; 15:2871. [PMID: 37447198 DOI: 10.3390/nu15132871] [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: 05/24/2023] [Revised: 06/20/2023] [Accepted: 06/22/2023] [Indexed: 07/15/2023] Open
Abstract
Celiac disease (CD) is included in the group of complex or multifactorial diseases, i.e., those caused by the interaction of genetic and environmental factors. Despite a growing understanding of the pathophysiological mechanisms of the disease, diagnosis is still often delayed and there are no effective biomarkers for early diagnosis. The only current treatment, a gluten-free diet (GFD), can alleviate symptoms and restore intestinal villi, but its cellular effects remain poorly understood. To gain a comprehensive understanding of CD's progression, it is crucial to advance knowledge across various scientific disciplines and explore what transpires after disease onset. Metabolomics studies hold particular significance in unravelling the complexities of multifactorial and multisystemic disorders, where environmental factors play a significant role in disease manifestation and progression. By analyzing metabolites, we can gain insights into the reasons behind CD's occurrence, as well as better comprehend the impact of treatment initiation on patients. In this review, we present a collection of articles that showcase the latest breakthroughs in the field of metabolomics in pediatric CD, with the aim of trying to identify CD biomarkers for both early diagnosis and treatment monitoring. These advancements shed light on the potential of metabolomic analysis in enhancing our understanding of the disease and improving diagnostic and therapeutic strategies. More studies need to be designed to cover metabolic profiles in subjects at risk of developing the disease, as well as those analyzing biomarkers for follow-up treatment with a GFD.
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Affiliation(s)
- Rafael Martín-Masot
- Pediatric Gastroenterology and Nutrition Unit, Hospital Regional Universitario de Malaga, 29010 Málaga, Spain
- Institute of Nutrition and Food Technology "José MataixVerdú" (INYTA), Biomedical Research Centre (CIBM), University of Granada, 18071 Granada, Spain
| | - María Jiménez-Muñoz
- Pediatric Gastroenterology and Nutrition Unit, Hospital Regional Universitario de Malaga, 29010 Málaga, Spain
| | - Marta Herrador-López
- Pediatric Gastroenterology and Nutrition Unit, Hospital Regional Universitario de Malaga, 29010 Málaga, Spain
| | - Víctor Manuel Navas-López
- Pediatric Gastroenterology and Nutrition Unit, Hospital Regional Universitario de Malaga, 29010 Málaga, Spain
| | - Elia Obis
- Department of Experimental Medicine, Lleida Biomedical Research Institute (IRBLleida), University of Lleida (UdL), 25198 Lleida, Spain
| | - Mariona Jové
- Department of Experimental Medicine, Lleida Biomedical Research Institute (IRBLleida), University of Lleida (UdL), 25198 Lleida, Spain
| | - Reinald Pamplona
- Department of Experimental Medicine, Lleida Biomedical Research Institute (IRBLleida), University of Lleida (UdL), 25198 Lleida, Spain
| | - Teresa Nestares
- Institute of Nutrition and Food Technology "José MataixVerdú" (INYTA), Biomedical Research Centre (CIBM), University of Granada, 18071 Granada, Spain
- Department of Physiology, Faculty of Pharmacy, University of Granada, 18071 Granada, Spain
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11
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Mu C, Zhao Q, Zhao Q, Yang L, Pang X, Liu T, Li X, Wang B, Fung SY, Cao H. Multi-omics in Crohn's disease: New insights from inside. Comput Struct Biotechnol J 2023; 21:3054-3072. [PMID: 37273853 PMCID: PMC10238466 DOI: 10.1016/j.csbj.2023.05.010] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2022] [Revised: 05/10/2023] [Accepted: 05/11/2023] [Indexed: 06/06/2023] Open
Abstract
Crohn's disease (CD) is an inflammatory bowel disease (IBD) with complex clinical manifestations such as chronic diarrhea, weight loss and hematochezia. Despite the increasing incidence worldwide, cure of CD remains extremely difficult. The rapid development of high-throughput sequencing technology with integrated-omics analyses in recent years has provided a new means for exploring the pathogenesis, mining the biomarkers and designing targeted personalized therapeutics of CD. Host genomics and epigenomics unveil heredity-related mechanisms of susceptible individuals, while microbiome and metabolomics map host-microbe interactions in CD patients. Proteomics shows great potential in searching for promising biomarkers. Nonetheless, single omics technology cannot holistically connect the mechanisms with heterogeneity of pathological behavior in CD. The rise of multi-omics analysis integrates genetic/epigenetic profiles with protein/microbial metabolite functionality, providing new hope for comprehensive and in-depth exploration of CD. Herein, we emphasized the different omics features and applications of CD and discussed the current research and limitations of multi-omics in CD. This review will update and deepen our understanding of CD from integration of broad omics spectra and will provide new evidence for targeted individualized therapeutics.
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Affiliation(s)
- Chenlu Mu
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Qianjing Zhao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Qing Zhao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Lijiao Yang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Xiaoqi Pang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Tianyu Liu
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Xiaomeng Li
- Department of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Science, Tianjin Medical University, Tianjin, China
| | - Bangmao Wang
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
| | - Shan-Yu Fung
- Department of Immunology, Key Laboratory of Immune Microenvironment and Disease (Ministry of Education), The Province and Ministry Co-Sponsored Collaborative Innovation Center for Medical Epigenetics, School of Basic Medical Science, Tianjin Medical University, Tianjin, China
| | - Hailong Cao
- Department of Gastroenterology and Hepatology, General Hospital, Tianjin Medical University, Tianjin Institute of Digestive Diseases, Tianjin Key Laboratory of Digestive Diseases, Tianjin, China
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12
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Das S, Gnanasambandan R. Intestinal microbiome diversity of diabetic and non-diabetic kidney disease: Current status and future perspective. Life Sci 2023; 316:121414. [PMID: 36682521 DOI: 10.1016/j.lfs.2023.121414] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2022] [Revised: 01/09/2023] [Accepted: 01/17/2023] [Indexed: 01/21/2023]
Abstract
A significant portion of the health burden of diabetic kidney disease (DKD) is caused by both type 1 and type 2 diabetes which leads to morbidity and mortality globally. It is one of the most common diabetic complications characterized by loss of renal function with high prevalence, often leading to acute kidney disease (AKD). Inflammation triggered by gut microbiota is commonly associated with the development of DKD. Interactions between the gut microbiota and the host are correlated in maintaining metabolic and inflammatory homeostasis. However, the fundamental processes through which the gut microbiota affects the onset and progression of DKD are mainly unknown. In this narrative review, we summarised the potential role of the gut microbiome, their pathogenicity between diabetic and non-diabetic kidney disease (NDKD), and their impact on host immunity. A well-established association has already been seen between gut microbiota, diabetes and kidney disease. The gut-kidney interrelationship is confirmed by mounting evidence linking gut dysbiosis to DKD, however, it is still unclear what is the real cause of gut dysbiosis, the development of DKD, and its progression. In addition, we also try to distinguish novel biomarkers for early detection of DKD and the possible therapies that can be used to regulate the gut microbiota and improve the host immune response. This early detection and new therapies will help clinicians for better management of the disease and help improve patient outcomes.
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Affiliation(s)
- Soumik Das
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India
| | - Ramanathan Gnanasambandan
- School of Biosciences and Technology, Vellore Institute of Technology (VIT), Vellore, Tamil Nadu 632014, India.
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13
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Dorgan JF, Ryan AS, LeBlanc ES, Van Horn L, Magder LS, Snetselaar LG, Zhang Y, Dallal CM, Jung S, Shepherd JA. A comparison of associations of body mass index and dual-energy x-ray absorptiometry measured percentage fat and total fat with global serum metabolites in young women. Obesity (Silver Spring) 2023; 31:525-536. [PMID: 36642094 PMCID: PMC9937438 DOI: 10.1002/oby.23619] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/20/2022] [Revised: 09/21/2022] [Accepted: 09/23/2022] [Indexed: 01/17/2023]
Abstract
OBJECTIVE Body mass index (BMI) does not directly measure adiposity, whereas dual-energy x-ray absorptiometry (DXA) provides valid direct estimates of adiposity. Therefore, this study evaluated usefulness of BMI as a measure of adiposity in serum metabolomics studies. METHODS A cross-sectional analysis was conducted of 202 women aged 25 to 29 years in the Dietary Intervention Study in Children Follow-Up Study. Heights and weights were measured, and body composition was quantified using clinical DXA protocols. Serum metabolomic profiling was performed by liquid chromatography-tandem mass spectrometry. Partial correlations of BMI, percentage fat (%FAT), and total fat (TOTFAT) with log transformed serum metabolites were calculated. RESULTS There was significant overlap in the 93 metabolites that correlated with BMI, %FAT, and/or TOTFAT; 9 differently correlated with BMI and %FAT, whereas 15 differently correlated with BMI and TOTFAT. Even for these metabolites, absolute differences were modest. Metabolite set enrichment analysis identified diacylglycerol and sphingolipid metabolism as overrepresented among metabolites significantly correlated with all three measures of adiposity. CONCLUSIONS BMI can be a good proxy for DXA measured %FAT and TOTFAT in descriptive metabolomic studies of healthy, young White women. Larger studies in more diverse populations are needed to endorse more generalized conclusions.
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Affiliation(s)
- Joanne F Dorgan
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Alice S Ryan
- Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Erin S LeBlanc
- Kaiser Permanente Center for Health Research, Portland, Oregon, USA
| | - Linda Van Horn
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA
| | - Laurence S Magder
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Linda G Snetselaar
- Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USA
| | - Yuji Zhang
- Department of Epidemiology and Public Health, University of Maryland School of Medicine, Baltimore, Maryland, USA
| | - Cher M Dallal
- Department of Epidemiology and Biostatistics, University of Maryland School of Public Health, College Park, Maryland, USA
| | - Seungyoun Jung
- Department of Nutritional Science & Food Management, Ewha Womans University, Seoul, South Korea
- Graduate Program in System Health Science & Engineering, Ewha Womans University, Seoul, South Korea
| | - John A Shepherd
- Department of Nutritional Sciences, University of Hawaii at Manoa, Honolulu, Hawaii, USA
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14
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Si Q, Guo J, Yang X, Guo Y, Wu L, Xie D, Jiang P. Systematic assessment of streptozotocin-induced diabetic metabolic alterations in rats using metabolomics. Front Endocrinol (Lausanne) 2023; 14:1107162. [PMID: 36761194 PMCID: PMC9902650 DOI: 10.3389/fendo.2023.1107162] [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: 11/24/2022] [Accepted: 01/09/2023] [Indexed: 01/25/2023] Open
Abstract
PURPOSE Type 1 diabetes is characterized by elevated blood glucose levels, which negatively impacts multiple organs and tissues throughout the body, and its prevalence is on the rise. Prior reports primarily investigated the serum and urine specimen from diabetic patients. However, only a few studies examined the overall metabolic profile of diabetic animals or patients. The current systemic investigation will benefit the knowledge of STZ-based type 1 diabetes pathogenesis. METHODS Male SD rats were arbitrarily separated into control and streptozotocin (STZ)-treated diabetic rats (n = 7). The experimental rats received 50mg/kg STZ intraperitoneal injection daily for 2 consecutive days. Following 6 weeks, metabolites were assessed via gas chromatography-mass spectrometry (GC-MS), and multivariate analysis was employed to screen for differentially expressed (DE) metabolites between the induced diabetic and normal rats. RESULTS We identified 18, 30, 6, 24, 34, 27, 27 and 12 DE metabolites in the serum, heart, liver, kidney, cortex, renal lipid, hippocampus, and brown fat tissues of STZ-treated diabetic rats, compared to control rats. Based on our analysis, the largest differences were observed in the amino acids (AAs), B-group vitamin, and purine profiles. Using the metabolic pathway analysis, we screened 13 metabolic pathways related to the STZ-exposed diabetes pathogenesis. These pathways were primarily AA metabolism, followed by organic acids, sugars, and lipid metabolism. CONCLUSION Based on our GC-MS analysis, we identified potential metabolic alterations within the STZ-exposed diabetic rats, which may aid in the understanding of diabetes pathogenesis.
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Affiliation(s)
- Qingying Si
- Department of Endocrinology, Tengzhou Central People’s Hospital, Tengzhou, China
| | - Jinxiu Guo
- Translational Pharmaceutical Laboratory, Jining First People’s Hospital, Shandong First Medical University, Jining, China
| | - Xiumei Yang
- Department of Endocrinology, Tengzhou Central People’s Hospital, Tengzhou, China
| | - Yujin Guo
- Translational Pharmaceutical Laboratory, Jining First People’s Hospital, Shandong First Medical University, Jining, China
- *Correspondence: Yujin Guo, ; Pei Jiang,
| | - Linlin Wu
- Office of Scientific Research Management, Tengzhou Central People’s Hospital, Tengzhou, China
| | - Dadi Xie
- Department of Endocrinology, Tengzhou Central People’s Hospital, Tengzhou, China
| | - Pei Jiang
- Translational Pharmaceutical Laboratory, Jining First People’s Hospital, Shandong First Medical University, Jining, China
- Institute of Translational Pharmacy, Jining Medical Research Academy, Jining, China
- *Correspondence: Yujin Guo, ; Pei Jiang,
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15
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Limonte CP, Kretzler M, Pennathur S, Pop-Busui R, de Boer IH. Present and future directions in diabetic kidney disease. J Diabetes Complications 2022; 36:108357. [PMID: 36403478 PMCID: PMC9764992 DOI: 10.1016/j.jdiacomp.2022.108357] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 10/28/2022] [Accepted: 11/05/2022] [Indexed: 11/16/2022]
Abstract
Diabetic kidney disease (DKD) is the leading cause of kidney failure and is associated with substantial risk of cardiovascular disease, morbidity, and mortality. Traditionally, DKD prevention and management have focused on addressing hyperglycemia, hypertension, obesity, and renin-angiotensin system activation as important risk factors for disease. Over the last decade, sodium-glucose cotransporter-2 inhibitors and glucagon-like peptide-1 receptor agonists have been shown to meaningfully reduce risk of diabetes-related kidney and cardiovascular complications. Additional agents demonstrating benefit in DKD such as non-steroidal mineralocorticoid receptor antagonists and endothelin A receptor antagonists are further contributing to the growing arsenal of DKD therapies. With the availability of greater therapeutic options comes the opportunity to individually optimize DKD prevention and management. Novel applications of transcriptomic, proteomic, and metabolomic/lipidomic technologies, as well as use of artificial intelligence and reinforced learning methods through consortia such as the Kidney Precision Medicine Project and focused studies in established cohorts hold tremendous promise for advancing our understanding and treatment of DKD. Specifically, enhanced understanding of the molecular mechanisms underlying DKD pathophysiology may allow for the identification of new mechanism-based DKD subtypes and the development and implementation of targeted therapies. Implementation of personalized care approaches has the potential to revolutionize DKD care.
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Affiliation(s)
- Christine P Limonte
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, USA; Kidney Research Institute, University of Washington, Seattle, WA, USA.
| | - Matthias Kretzler
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA; Department of Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, MI, USA
| | - Subramaniam Pennathur
- Division of Nephrology, University of Michigan, Ann Arbor, MI, USA; Michigan Regional Comprehensive Metabolomics Resource Core, Ann Arbor, MI, USA; Department of Molecular and Integrative Physiology, University of Michigan, Ann Arbor, MI, USA
| | - Rodica Pop-Busui
- Department of Internal Medicine, Division of Metabolism, Endocrinology and Diabetes, University of Michigan, Ann Arbor, MI, USA
| | - Ian H de Boer
- Division of Nephrology, Department of Medicine, University of Washington, Seattle, WA, USA; Kidney Research Institute, University of Washington, Seattle, WA, USA
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16
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Banimfreg BH, Shamayleh A, Alshraideh H, Semreen MH, Soares NC. Untargeted approach to investigating the metabolomics profile of type 2 diabetes emiratis. J Proteomics 2022; 269:104718. [PMID: 36100153 DOI: 10.1016/j.jprot.2022.104718] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2022] [Revised: 07/28/2022] [Accepted: 08/20/2022] [Indexed: 12/12/2022]
Abstract
Type 2 Diabetes (T2D) is expected to be the seventh most significant cause of death worldwide by 2030. Although research into its mechanism has received the attention it deserves, our understanding of T2D is still limited. This case-control study employs untargeted metabolomics to explore novel T2D plasma biomarkers in the Emirati population. Ninety-two UAE nationals were included in the cohort, with fifty T2D and forty-two non-T2D profiles. Participants were then stratified into three groups based on metabolic profiles, clinically verified diabetic status, and current HbA1c values: namely controlled diabetics, uncontrolled diabetics and prediabetics, and non-diabetics. The study identified fifteen significant differentially abundant metabolites between the uncontrolled diabetics group and the prediabetics or controlled diabetics group. Interestingly, some metabolites essential for the corticosteroid and thyroid signaling pathways were found to be significantly elevated in poorly controlled T2D, including cortisol, glycocholic acid, bile acids, thyroxine, and the tryptophan metabolite, 5-hydroxyindoleacetic acid. These findings align with those from prior western cohorts and suggest an intriguing linkage between T2D glycemic control and thyroid and adrenal signaling that may provide new diagnostic and prognostic indicators. RESEARCH SIGNIFICANCE: This study investigates the underlooked metabolomic role and correlation with T2D in the UAE population. The report indicates fifteen significant differentially abundant metabolites between on diabetics, uncontrolled diabetics and or controlled diabetics or prediabetics. This panel of metabolites such as thyroxine and corticosteroids should be considered further as potential diagnostic or prognostic biomarkers for T2D in the region.
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Affiliation(s)
- Bayan Hassan Banimfreg
- College of Engineering, Department of Industrial Engineering, American University of Sharjah, United Arab Emirates
| | - Abdulrahim Shamayleh
- College of Engineering, Department of Industrial Engineering, American University of Sharjah, United Arab Emirates
| | - Hussam Alshraideh
- College of Engineering, Department of Industrial Engineering, American University of Sharjah, United Arab Emirates
| | - Mohammad Harb Semreen
- College of Pharmacy, Department of Medicinal Chemistry, University of Sharjah, United Arab Emirates; Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates
| | - Nelson C Soares
- College of Pharmacy, Department of Medicinal Chemistry, University of Sharjah, United Arab Emirates; Sharjah Institute for Medical Research, University of Sharjah, Sharjah, United Arab Emirates.
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17
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Ferreira-Divino LF, Suvitaival T, Rotbain Curovic V, Tofte N, Trošt K, Mattila IM, Theilade S, Winther SA, Hansen TW, Frimodt-Møller M, Legido-Quigley C, Rossing P. Circulating metabolites and molecular lipid species are associated with future cardiovascular morbidity and mortality in type 1 diabetes. Cardiovasc Diabetol 2022; 21:135. [PMID: 35850688 PMCID: PMC9295441 DOI: 10.1186/s12933-022-01568-8] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 07/05/2022] [Indexed: 11/10/2022] Open
Abstract
Background Cardiovascular disease remains the leading cause of mortality in individuals with diabetes and improved understanding of its pathophysiology is needed. We investigated the association of a large panel of metabolites and molecular lipid species with future cardiovascular events in type 1 diabetes. Methods The study included 669 individuals with type 1 diabetes. Non-targeted serum metabolomics and lipidomics analyses were performed using mass spectrometry. Data on cardiovascular events (cardiovascular mortality, coronary artery disease, stroke, and peripheral arterial interventions) were obtained from Danish Health registries and analyzed by Cox hazards models. Metabolites and molecular lipid species were analyzed in univariate models adjusted for false discovery rate (FDR). Metabolites and molecular lipid species fulfilling a pFDR < 0.05 were subsequently analyzed in adjusted models including age, sex, hemoglobin A1c, mean arterial pressure, smoking, body mass index, low-density lipoprotein cholesterol, estimated glomerular filtration rate, urinary albumin excretion rate and previous cardiovascular disease. Analyses of molecular lipid species were further adjusted for triglycerides and statin use. Results Of the included participants, 55% were male and mean age was 55 ± 13 years. Higher 4-hydroxyphenylacetic acid (HR 1.35, CI [1.01–1.80], p = 0.04) and lower threonine (HR 0.81, CI [0.67–0.98] p = 0.03) were associated with development of cardiovascular events (n = 95). In lipidomics analysis, higher levels of three different species, diacyl-phosphatidylcholines (PC)(36:2) (HR 0.82, CI [0.70–0.98], p = 0.02), alkyl-acyl-phosphatidylcholines (PC-O)(34:2) (HR 0.76, CI [0.59–0.98], p = 0.03) and (PC-O)(34:3) (HR 0.75, CI [0.58–0.97], p = 0.03), correlated with lower risk of cardiovascular events, whereas higher sphingomyelin (SM)(34:1) (HR 1.32, CI [1.04–1.68], p = 0.02), was associated with an increased risk. Conclusions Circulating metabolites and molecular lipid species were associated with future cardiovascular events in type 1 diabetes. While the causal effect of these biomolecules on the cardiovascular system remains unknown, our findings support that omics-based technologies, although still in an early phase, may have the potential to unravel new pathways and biomarkers in the field of cardiovascular disease in type 1 diabetes. Supplementary Information The online version contains supplementary material available at 10.1186/s12933-022-01568-8.
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Affiliation(s)
| | - Tommi Suvitaival
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | | | - Nete Tofte
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Kajetan Trošt
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,University of Copenhagen, Copenhagen, Denmark
| | - Ismo M Mattila
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Simone Theilade
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,University of Copenhagen, Copenhagen, Denmark.,The Department of Medicine, Herlev-Gentofte Hospital, Copenhagen, Denmark
| | - Signe A Winther
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Tine W Hansen
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | - Marie Frimodt-Møller
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark
| | | | - Peter Rossing
- Steno Diabetes Center Copenhagen, Borgmester Ib Juuls Vej 83, 2730, Herlev, Denmark.,University of Copenhagen, Copenhagen, Denmark
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18
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Ban Q, Sun X, Jiang Y, Cheng J, Guo M. Effect of synbiotic yogurt fortified with monk fruit extract on hepatic lipid biomarkers and metabolism in rats with type 2 diabetes. J Dairy Sci 2022; 105:3758-3769. [PMID: 35248379 DOI: 10.3168/jds.2021-21204] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/25/2021] [Accepted: 01/14/2022] [Indexed: 01/03/2024]
Abstract
Monk fruit extract (MFE) is widely used as a sweetener in foods. In this study, the effects of the consumption of MFE-sweetened synbiotic yogurt on the lipid biomarkers and metabolism in the livers of type 2 diabetic rats were evaluated. The results revealed that the MFE-sweetened symbiotic yogurt affected the phosphatidylcholines, phosphatidylethanolamines, phosphatidylglycerol, lysophosphatidic acids, lysophosphatidylcholines, lysophosphatidylethanolamines, lysophosphatidylglycerols, lysophosphatidylinositols, lysophosphatidylserines, and fatty acid-hydroxy fatty acids biomarkers in the livers of type 2 diabetic rats. In addition, the consumption of the MFE-sweetened synbiotic yogurt significantly altered 12 hepatic metabolites, which are involved in phenylalanine metabolism, sphingolipid metabolism, bile secretion, and glyoxylate and dicarboxylate metabolism in the liver. Furthermore, a multiomics (metabolomic and transcriptomic) association study revealed that there was a significant correlation between the MFE-sweetened synbiotic yogurt and the metabolites and genes involved in fatty acid biosynthesis, bile secretion, and glyoxylate and dicarboxylate metabolism. The findings of this study will provide new insights on exploring the function of sweeteners for improving type 2 diabetes mellitus liver lipid biomarkers.
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Affiliation(s)
- Qingfeng Ban
- College of Food Science, Northeast Agricultural University, Harbin, 150030, China; Key Laboratory of Dairy Science of Ministry of Education, Northeast Agricultural University, Harbin 150030, China
| | - Xiaomeng Sun
- College of Food Science, Northeast Agricultural University, Harbin, 150030, China
| | - Yunqing Jiang
- College of Food Science, Northeast Agricultural University, Harbin, 150030, China
| | - Jianjun Cheng
- College of Food Science, Northeast Agricultural University, Harbin, 150030, China.
| | - Mingruo Guo
- Department of Nutrition and Food Sciences, College of Agriculture and Life Sciences, University of Vermont, Burlington 05405.
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19
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Chen Y, Jia H, Qian X, Wang J, Yu M, Gong Q, An Y, Li H, Li S, Shi N, Zou Z, Li G. Circulating Palmitoyl Sphingomyelin Is Associated With Cardiovascular Disease in Individuals With Type 2 Diabetes: Findings From the China Da Qing Diabetes Study. Diabetes Care 2022; 45:666-673. [PMID: 35165706 PMCID: PMC8918230 DOI: 10.2337/dc21-1520] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 12/05/2021] [Indexed: 02/03/2023]
Abstract
OBJECTIVE To investigate the association of potential cardiovascular disease (CVD) biomarkers in patients with type 2 diabetes. RESEARCH DESIGN AND METHODS We enrolled 120 participants (aged 61.5-69.5 years) with type 2 diabetes and 60 (aged 62.5-73.5 years) with normal glucose tolerance in the discovery group from the original Da Qing Diabetes Study. Their diabetes status was confirmed in 1986; then, the participants were followed over 23 years to collect CVD outcome data. Untargeted and targeted metabolomics analyses based on ultra-high-performance liquid chromatography-tandem mass spectrometry were used to identify potential markers. Multivariable regression analysis was used to evaluate the association between metabolites and CVD outcomes. An independent group of 335 patients (aged 67.0-77.0 years) with diabetes was used for biomarker validation. RESULTS In the discovery group, untargeted metabolomics analysis found 16 lipids and fatty acids metabolites associated with CVD risk in patients with diabetes, with palmitoyl sphingomyelin (PSM) having the strongest association. Plasma PSM concentrations were significantly higher in cases of diabetes with CVD than without (41.68 ± 10.47 vs. 9.69 ± 1.47 μg/mL; P < 0.0001). The odds ratio (OR) of CVD for 1 µg/mL PSM change was 1.19 (95% CI 1.13-1.25) after adjustment of clinical confounders. The validation study confirmed that PSM was significantly associated with increased CVD risk in diabetes (OR 1.22 [95% CI 1.16-1.30]). CONCLUSIONS Changes in lipid and fatty acid content were significantly associated with CVD risk in the Chinese population with diabetes. PSM is a potential biomarker of increased CVD risk in diabetes.
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Affiliation(s)
- Yanyan Chen
- Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Department of Endocrinology, Fuwai Hospital, Chinese Academy of Medical Sciences, Shenzhen, Shenzhen, Guangdong, China
| | - Hongmei Jia
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xin Qian
- Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jinping Wang
- Department of Cardiology, Da Qing First Hospital, Da Qing, China
| | - Meng Yu
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Qiuhong Gong
- Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yali An
- Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Hui Li
- Department of Cardiology, Da Qing First Hospital, Da Qing, China
| | - Sidong Li
- Medical Research and Biometrics Center, Fuwai Hospital, National Center for Cardiovascular Diseases, Peking Union Medical College and Chinese Academy of Medical Sciences, Beijing, China
| | - Na Shi
- Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Zhongmei Zou
- Institute of Medicinal Plant Development, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Guangwei Li
- Endocrinology Centre, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.,Department of Endocrinology, China-Japan Friendship Hospital, Beijing
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20
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Ren M, Lin DZ, Liu ZP, Sun K, Wang C, Lao GJ, Fan YQ, Wang XY, Liu J, Du J, Zhu GB, Wang JH, Yan L. Potential Novel Serum Metabolic Markers Associated With Progression of Prediabetes to Overt Diabetes in a Chinese Population. Front Endocrinol (Lausanne) 2022; 12:745214. [PMID: 35069433 PMCID: PMC8766640 DOI: 10.3389/fendo.2021.745214] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/21/2021] [Accepted: 12/13/2021] [Indexed: 11/20/2022] Open
Abstract
Background Identifying the metabolite profile of individuals with prediabetes who turned to type 2 diabetes (T2D) may give novel insights into early T2D interception. The purpose of this study was to identify metabolic markers that predict the development of T2D from prediabetes in a Chinese population. Methods We used an untargeted metabolomics approach to investigate the associations between serum metabolites and risk of prediabetes who turned to overt T2D (n=153, mean follow up 5 years) in a Chinese population (REACTION study). Results were compared with matched controls who had prediabetes at baseline [age: 56 ± 7 years old, body mass index (BMI): 24.2 ± 2.8 kg/m2] and at a 5-year follow-up [age: 61 ± 7 years old, BMI: 24.5 ± 3.1 kg/m2]. Confounding factors were adjusted and the associations between metabolites and diabetes risk were evaluated with multivariate logistic regression analysis. A 10-fold cross-validation random forest classification (RFC) model was used to select the optimal metabolites panels for predicting the development of diabetes, and to internally validate the discriminatory capability of the selected metabolites beyond conventional clinical risk factors. Findings Metabolic alterations, including those associated with amino acid and lipid metabolism, were associated with an increased risk of prediabetes progressing to diabetes. The most important metabolites were inosine [odds ratio (OR) = 19.00; 95% confidence interval (CI): 4.23-85.37] and carvacrol (OR = 17.63; 95% CI: 4.98-62.34). Thirteen metabolites were found to improve T2D risk prediction beyond eight conventional T2D risk factors [area under the curve (AUC) was 0.98 for risk factors + metabolites vs 0.72 for risk factors, P < 0.05]. Interpretations Use of the metabolites identified in this study may help determine patients with prediabetes who are at highest risk of progressing to diabetes.
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Affiliation(s)
- Meng Ren
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Diao zhu Lin
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Zhi Peng Liu
- Biotree-Shanghai, Focus Dream Park, Shanghai, China
| | - Kan Sun
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Chuan Wang
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Guo juan Lao
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Yan qun Fan
- Biotree-Shanghai, Focus Dream Park, Shanghai, China
| | - Xiao yi Wang
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jing Liu
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Jie Du
- Biotree-Shanghai, Focus Dream Park, Shanghai, China
| | - Guo bin Zhu
- Biotree-Shanghai, Focus Dream Park, Shanghai, China
| | - Jia huan Wang
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
| | - Li Yan
- Department of Endocrinology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, Guangzhou, China
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21
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Xuan Q, Hu C, Zhang Y, Wang Q, Zhao X, Liu X, Wang C, Jia W, Xu G. Serum lipidomics profiles reveal potential lipid markers for prediabetes and type 2 diabetes in patients from multiple communities. Front Endocrinol (Lausanne) 2022; 13:966823. [PMID: 36060983 PMCID: PMC9434798 DOI: 10.3389/fendo.2022.966823] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/11/2022] [Accepted: 07/21/2022] [Indexed: 12/02/2022] Open
Abstract
OBJECTIVE Dyslipidemia is a hallmark of diabetes mellitus (DM). However, specific lipid molecules closely associated with the initiation and progression of diabetes remain unclear. We used a pseudotargeted lipidomics approach to evaluate the complex lipid changes that occurred long before the diagnosis of type 2 diabetes mellitus (T2DM) and to identify novel lipid markers for screening prediabetes mellitus (PreDM) and T2DM in patients from multiple communities. METHODS Four hundred and eighty-one subjects consisting of T2DM, three subtypes of PreDM, and normal controls (NC) were enrolled as discovery cohort. Serum lipidomic profiles of 481 subjects were analyzed using an ultrahigh performance liquid chromatography-triple quadrupole mass spectrometry (UHPLC-QqQ-MS)-based pseudotargeted lipidomics method. The differential lipid molecules were further validated in an independent case-control study consisting of 150 PreDM, 234 T2DM and 94 NC. RESULTS Multivariate discriminative analyses show that lipidomics data have considerable potential for identifying lipidome differences among T2DM, subtypes of PreDM and NC. Statistical associations of lipid (sub)species display significant variations in 11 lipid (sub)species levels for T2DM and distinctive differences in 8 lipid (sub)species levels between prediabetic and normoglycemic individuals, with further differences in 8 lipid (sub)species levels among subtypes of PreDM. Adjusted for sex, age and BMI, only two lipid (sub)species of fatty acid (FA) and phosphatidylcholine (PC) were associated at p< 0.05 for PreDM (all) and subtypes of PreDM. The defined lipid markers not only significantly improve the diagnostic accuracy of PreDM and T2DM but also effectively evaluating the risk of developing into each subtype of PreDM and T2DM when addition of age, sex, BMI, and FPG, respectively. CONCLUSIONS Our findings improve insights into the lipid metabolic complexity and interindividual variations among subtypes of PreDM and T2DM, beyond the well-known differences in dyslipidemia in clinic.
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Affiliation(s)
- Qiuhui Xuan
- Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- Department of Endocrinology, Shandong Provincial Hospital, Shandong University, Jinan, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chunxiu Hu
- Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Yinan Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
| | - Qingqing Wang
- Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xinjie Zhao
- Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Xinyu Liu
- Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Congrong Wang
- Department of Endocrinology and Metabolism, Shanghai Fourth People’s Hospital, Tongji University School of Medicine, Shanghai, China
- *Correspondence: Guowang Xu, ; Weiping Jia, ; Congrong Wang,
| | - Weiping Jia
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, Shanghai, China
- *Correspondence: Guowang Xu, ; Weiping Jia, ; Congrong Wang,
| | - Guowang Xu
- Chinese Academy of Sciences (CAS) Key Laboratory of Separation Sciences for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, China
- University of Chinese Academy of Sciences, Beijing, China
- *Correspondence: Guowang Xu, ; Weiping Jia, ; Congrong Wang,
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Trevisan França de Lima L, Müller Bark J, Rasheduzzaman M, Ekanayake Weeramange C, Punyadeera C. Saliva as a matrix for measurement of cancer biomarkers. Cancer Biomark 2022. [DOI: 10.1016/b978-0-12-824302-2.00008-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
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23
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Xing WL, Liu HX, Niu Q, Wang YT, Zhu Y. Danhong injection improves elective percutaneous coronary intervention in ua patients with blood stasis syndrome revealed by perioperative metabolomics. WORLD JOURNAL OF TRADITIONAL CHINESE MEDICINE 2022. [DOI: 10.4103/wjtcm.wjtcm_63_21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/04/2022] Open
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24
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Taya N, Katakami N, Omori K, Arakawa S, Hosoe S, Watanabe H, Takahara M, Miyashita K, Nishizawa H, Matsuoka T, Furuno M, Bamba T, Iida J, Fukusaki E, Shimomura I. Evaluation of change in metabolome caused by comprehensive diabetes treatment: A prospective observational study of diabetes inpatients with gas chromatography/mass spectrometry-based non-target metabolomic analysis. J Diabetes Investig 2021; 12:2232-2241. [PMID: 34032389 PMCID: PMC8668060 DOI: 10.1111/jdi.13600] [Citation(s) in RCA: 6] [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: 11/09/2020] [Revised: 04/17/2021] [Accepted: 05/20/2021] [Indexed: 11/28/2022] Open
Abstract
AIMS/INTRODUCTION Diabetes patients develop a variety of metabolic abnormalities in addition to hyperglycemia. However, details regarding change in various metabolites after comprehensive diabetes treatment remain unknown. This study aimed to identify the short-term change in metabolome in inpatients who were subject to comprehensive diabetes treatment, using gas chromatography/mass spectrometry-based non-target metabolomics techniques. MATERIALS AND METHODS Participants of the present study were randomly recruited from the patients with type 2 diabetes hospitalized due to problems with glycemic control (n = 31) and volunteers without diabetes (n = 30), both of whom were aged between 20 and 75 years. A metabolomic analysis of fasting plasma samples on the 2nd (pre-treatment) and 16th hospital (post-treatment) day with gas chromatography/mass spectrometry using a multiple reaction monitoring mode was carried out. RESULTS A principal component analysis showed that metabolome of fasting plasma was different between individuals with and without diabetes. The metabolome of fasting plasma in diabetes patients after treatment was different from that of pre-treatment, as well as individuals without diabetes. Many amino acids (proline, glycine, serine, threonine, methionine, pyroglutamic acid, glutamine and lysine) were significantly increased by >10% after administering the inpatient diabetes treatment. A hierarchical clustering analysis showed that in the case of patients with markedly decreased monosaccharide levels and increased 1,5-anhydroglucitol, the levels of amino acids increased more significantly. CONCLUSIONS After a 2-week comprehensive treatment, the plasma levels of various amino acids increased in conjunction with the reduction in monosaccharide levels in poorly controlled type 2 diabetes patients.
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Affiliation(s)
- Naohiro Taya
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Naoto Katakami
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
- Department of Metabolism and AtherosclerosisOsaka University Graduate School of MedicineOsakaJapan
| | - Kazuo Omori
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Shoya Arakawa
- Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Shigero Hosoe
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Hirotaka Watanabe
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Mitsuyoshi Takahara
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
- Department of Diabetes Care MedicineGraduate School of MedicineOsaka UniversityOsakaJapan
| | - Kazuyuki Miyashita
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Hitoshi Nishizawa
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Taka‐Aki Matsuoka
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
| | - Masahiro Furuno
- Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Takeshi Bamba
- Division of MetabolomicsResearch Center for Transomics MedicineMedical Institute of BioregulationKyushu UniversityFukuokaJapan
| | - Junko Iida
- Shimadzu CorporationKyotoJapan
- Osaka University Shimadzu Omics Innovation Research LaboratoriesGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Eiichiro Fukusaki
- Laboratory of Bioresource EngineeringDepartment of BiotechnologyGraduate School of EngineeringOsaka UniversityOsakaJapan
| | - Iichiro Shimomura
- Department of Metabolic MedicineOsaka University Graduate School of MedicineOsakaJapan
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25
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Fu Y, Zhang F, Liu Z, Zhao Q, Xue Y, Shen Q. Improvement of diabetes-induced metabolic syndrome by millet prolamin is associated with changes in serum metabolomics. FOOD BIOSCI 2021. [DOI: 10.1016/j.fbio.2021.101434] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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26
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Progress and Challenges in Quantifying Carbonyl-Metabolomic Phenomes with LC-MS/MS. Molecules 2021; 26:molecules26206147. [PMID: 34684729 PMCID: PMC8541004 DOI: 10.3390/molecules26206147] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2021] [Revised: 09/30/2021] [Accepted: 10/01/2021] [Indexed: 12/17/2022] Open
Abstract
Carbonyl-containing metabolites widely exist in biological samples and have important physiological functions. Thus, accurate and sensitive quantitative analysis of carbonyl-containing metabolites is crucial to provide insight into metabolic pathways as well as disease mechanisms. Although reversed phase liquid chromatography electrospray ionization mass spectrometry (RPLC-ESI-MS) is widely used due to the powerful separation capability of RPLC and high specificity and sensitivity of MS, but it is often challenging to directly analyze carbonyl-containing metabolites using RPLC-ESI-MS due to the poor ionization efficiency of neutral carbonyl groups in ESI. Modification of carbonyl-containing metabolites by a chemical derivatization strategy can overcome the obstacle of sensitivity; however, it is insufficient to achieve accurate quantification due to instrument drift and matrix effects. The emergence of stable isotope-coded derivatization (ICD) provides a good solution to the problems encountered above. Thus, LC-MS methods that utilize ICD have been applied in metabolomics including quantitative targeted analysis and untargeted profiling analysis. In addition, ICD makes multiplex or multichannel submetabolome analysis possible, which not only reduces instrument running time but also avoids the variation of MS response. In this review, representative derivatization reagents and typical applications in absolute quantification and submetabolome profiling are discussed to highlight the superiority of the ICD strategy for detection of carbonyl-containing metabolites.
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27
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Zhang Y, Yang Y, Ding L, Wang Z, Xiao Y, Xiao W. Emerging Applications of Metabolomics to Assess the Efficacy of Traditional Chinese Medicines for Treating Type 2 Diabetes Mellitus. Front Pharmacol 2021; 12:735410. [PMID: 34603052 PMCID: PMC8486080 DOI: 10.3389/fphar.2021.735410] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Accepted: 09/08/2021] [Indexed: 12/14/2022] Open
Abstract
Diabetes is a common and complex disease that can exacerbate the complications related to cardiovascular disease, and this is especially true for type 2 diabetes mellitus (T2DM). In addition to the standard pharmacological therapies, T2DM has also been treated with nonconventional regimens such as traditional Chinese medicine (TCM), e.g., herbal medicines and TCM prescriptions, although the mechanisms underlying the therapeutic benefits remain unclear. In this regard, many studies have used metabolomics technology to elucidate the basis for the efficacy of TCM for T2DM. Metabolomics has recently attracted much attention with regard to drug discovery and pharmacologically relevant natural products. In this review, we summarize the application of metabolomics to the assessment of TCM efficacy for treating T2DM. Increasing evidence suggests that the metabolic profile of an individual patient may reflect a specific type of T2DM syndrome, which may provide a new perspective for disease diagnosis. In addition, TCM has proved effective for countering the metabolic disorders related to T2DM, and this may constitute the basis for TCM efficacy. Therefore, further determining how TCM contributes to the reversal of metabolic disorders, such as using network pharmacology or by assessing the contribution of host–gut microbiota interactions, will also provide researchers with new potential targets for pharmacologic-based therapies.
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Affiliation(s)
- Yumeng Zhang
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Yingbo Yang
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Jiangsu Kanion Pharmaceutical Co., Ltd., Lianyungang, China
| | - Lili Ding
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Zhengtao Wang
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Ying Xiao
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China
| | - Wei Xiao
- The Ministry of Education (MOE) Key Laboratory for Standardization of Chinese Medicines, Institute of Chinese Materia Medica, Shanghai University of Traditional Chinese Medicine, Shanghai, China.,Jiangsu Kanion Pharmaceutical Co., Ltd., Lianyungang, China
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28
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Chowdhury S, Faheem SM, Nawaz SS, Siddiqui K. The role of metabolomics in personalized medicine for diabetes. Per Med 2021; 18:501-508. [PMID: 34406076 DOI: 10.2217/pme-2021-0083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Metabolomics is rapidly evolving omics technology in personalized medicine, it offers a new avenue for identification of multiple novel metabolic mediators of impaired glucose tolerance and dysglycemia. Liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry and nuclear magnetic resonance spectroscopy are most commonly used analytical methods in the field of metabolomics. Recent evidences showed that metabolomic profiles are link to the incidence of diabetes. In this review, an overview of metabolomics studies in diabetes revealed several diabetes-associated metabolites including 1,5-anhydroglycitol, branch chain amino acids, glucose, α-hydroxybutyric acid, 3-hydroundecanoyl-carnitine and phosphatidylcholine that could be potential biomarkers associated with diabetes. These identified metabolites can be used to develop personalized prognostics and diagnostic, and help in diabetes management.
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Affiliation(s)
- Shamiha Chowdhury
- School of Life Sciences, Manipal Academy of Higher Education Dubai Campus, Academic City, Dubai, UAE
| | - Sultan Mohammed Faheem
- School of Life Sciences, Manipal Academy of Higher Education Dubai Campus, Academic City, Dubai, UAE
| | - Shaik Sarfaraz Nawaz
- Strategic Center for Diabetes Research, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Khalid Siddiqui
- Strategic Center for Diabetes Research, College of Medicine, King Saud University, Riyadh, Saudi Arabia
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Akinci B, Subauste A, Ajluni N, Esfandiari NH, Meral R, Neidert AH, Eraslan A, Hench R, Rus D, Mckenna B, Hussain HK, Chenevert TL, Tayeh MK, Rupani AR, Innis JW, Mantzoros CS, Conjeevaram HS, Burant CL, Oral EA. Metreleptin therapy for nonalcoholic steatohepatitis: Open-label therapy interventions in two different clinical settings. MED 2021; 2:814-835. [DOI: 10.1016/j.medj.2021.04.001] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
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30
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Abdullah MA, Hussein HA. Integrated algal and oil palm biorefinery as a model system for bioenergy co-generation with bioproducts and biopharmaceuticals. BIORESOUR BIOPROCESS 2021; 8:40. [PMID: 38650258 PMCID: PMC10992906 DOI: 10.1186/s40643-021-00396-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Accepted: 05/11/2021] [Indexed: 01/03/2023] Open
Abstract
BACKGROUND There has been a greater call for greener and eco-friendly processes and bioproducts to meet the 2030's core agenda on 17 global sustainable development goals. The challenge lies in incorporating systems thinking with a comprehensive worldview as a guiding principle to develop the economy, whilst taking cognisance of the need to safeguard the environment, and to embrace the socio-cultural diversity dimension as an equal component. Any discussion on climate change, destruction of eco-system and habitat for wildlife, poverty and starvation, and the spread of infectious diseases, must be addressed together with the emphasis on the development of cleaner energy, air and water, better management of resources and biodiversity, improved agro-practices for food production and distribution, and affordable health care, as the outcomes and key performance indicators to be evaluated. Strict regulation, monitoring and enforcement to minimize emission, pollution and wastage must also be put in place. CONCLUSION This review article focuses on the research and development efforts to achieve sustainable bioenergy production, environmental remediation, and transformation of agro-materials into value-added bioproducts through the integrated algal and oil palm biorefinery. Recent development in microalgal research with nanotechnology as anti-cancer and antimicrobial agents and for biopharmaceutical applications are discussed. The life-cycle analysis in the context of palm oil mill processes is evaluated. The way forward from this integrated biorefinery concept is to strive for inclusive development strategies, and to address the immediate and pressing problems facing the Planet and the People, whilst still reaping the Profit.
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Affiliation(s)
- Mohd Azmuddin Abdullah
- Institute of Marine Biotechnology, Universiti Malaysia Terengganu, 21030, Kuala Nerus, Terengganu, Malaysia.
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A metabolomics approach to investigate the proceedings of mitochondrial dysfunction in rats from prediabetes to diabetes. Saudi J Biol Sci 2021; 28:4762-4769. [PMID: 34354464 PMCID: PMC8324946 DOI: 10.1016/j.sjbs.2021.04.091] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2021] [Revised: 04/27/2021] [Accepted: 04/28/2021] [Indexed: 01/12/2023] Open
Abstract
Diabetes mellitus (DM) is a leading cause of preventable cardiovascular disease, but the metabolic changes from prediabetes to diabetes have not been fully clarified. This study implemented a metabolomics profiling platform to investigate the variations of metabolites and to elucidate their global profiling from metabolic syndrome to DM. Methods: Male Sprague-Dawley rats (n = 44) were divided into four groups. Three groups were separately fed with a normal diet, a high-fructose diet (HF), or a high-fat (HL) diet while one group was treated with streptozotocin. The HF and HL diet were meant to induce insulin resistance, obesity, and dyslipidemia, which known to induce DM. Results: The most significant metabolic variations in the DM group’s urine samples were the reduced release of citric acid cycle intermediates, the increase in acylcarnitines, and the decrease in urea excretion, all of which indicated energy metabolism abnormalities and mitochondrial dysfunction. Overall, the metabolic analysis revealed tryptophan metabolic pathway variations in the prediabetic phase, even though the mitochondrial function remains unaffected. Conclusion: This study show that widespread methylations and impaired tryptophan metabolism occur in metabolic syndrome and are then followed by a decline in citric acid cycle intermediates, indicating mitochondrial dysfunction in diabetes.
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Key Words
- CAN, acetonitrile
- DM, diabetes mellitus
- Diabetes
- GOT, glutamate oxaloacetate transaminase
- GPT, glutamate pyruvate transaminase
- HF, high-fructose
- HL, high-fat
- HMDB, human metabolome database
- KEGG, kyoto encyclopedia of genes and genomes
- LC-MS, liquid chromatography–mass spectrometry
- Metabolic syndrome
- Metabolomics
- Methylation
- Mitochondrial dysfunction
- PCA, principal component analysis
- Prediabetes
- STZ, streptozotocin
- TC, total cholesterol
- TG, triacylglycerol
- Tryptophan
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Jafari A, Babajani A, Rezaei-Tavirani M. Multiple Sclerosis Biomarker Discoveries by Proteomics and Metabolomics Approaches. Biomark Insights 2021; 16:11772719211013352. [PMID: 34017167 PMCID: PMC8114757 DOI: 10.1177/11772719211013352] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 04/05/2021] [Indexed: 12/22/2022] Open
Abstract
Multiple sclerosis (MS) is an autoimmune inflammatory disorder of the central nervous system (CNS) resulting in demyelination and axonal loss in the brain and spinal cord. The precise pathogenesis and etiology of this complex disease are still a mystery. Despite many studies that have been aimed to identify biomarkers, no protein marker has yet been approved for MS. There is urgently needed for biomarkers, which could clarify pathology, monitor disease progression, response to treatment, and prognosis in MS. Proteomics and metabolomics analysis are powerful tools to identify putative and novel candidate biomarkers. Different human compartments analysis using proteomics, metabolomics, and bioinformatics approaches has generated new information for further clarification of MS pathology, elucidating the mechanisms of the disease, finding new targets, and monitoring treatment response. Overall, omics approaches can develop different therapeutic and diagnostic aspects of complex disorders such as multiple sclerosis, from biomarker discovery to personalized medicine.
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Affiliation(s)
- Ameneh Jafari
- Student Research Committee, Shahid Beheshti University of Medical Sciences, Tehran, Iran
- Proteomics Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Amirhesam Babajani
- Department of Pharmacology, School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Abstract
Metabolomics is a technology that generates large amounts of data and contributes to obtaining wide and integral explanations of the biochemical state of a living organism. Plants are continuously affected by abiotic stresses such as water scarcity, high temperatures and high salinity, and metabolomics has the potential for elucidating the response-to-stress mechanisms and develop resistance strategies in affected cultivars. This review describes the characteristics of each of the stages of metabolomic studies in plants and the role of metabolomics in the characterization of the response of various plant species to abiotic stresses.
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Moon S, Tsay JJ, Lampert H, Md Dom ZI, Kostic AD, Smiles A, Niewczas MA. Circulating short and medium chain fatty acids are associated with normoalbuminuria in type 1 diabetes of long duration. Sci Rep 2021; 11:8592. [PMID: 33883567 PMCID: PMC8060327 DOI: 10.1038/s41598-021-87585-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Accepted: 03/30/2021] [Indexed: 11/08/2022] Open
Abstract
A substantial number of subjects with Type 1 Diabetes (T1D) of long duration never develop albuminuria or renal function impairment, yet the underlying protective mechanisms remain unknown. Therefore, our study included 308 Joslin Kidney Study subjects who had T1D of long duration (median: 24 years), maintained normal renal function and had either normoalbuminuria or a broad range of albuminuria within the 2 years preceding the metabolomic determinations. Serum samples were subjected to global metabolomic profiling. 352 metabolites were detected in at least 80% of the study population. In the logistic analyses adjusted for multiple testing (Bonferroni corrected α = 0.000028), we identified 38 metabolites associated with persistent normoalbuminuria independently from clinical covariates. Protective metabolites were enriched in Medium Chain Fatty Acids (MCFAs) and in Short Chain Fatty Acids (SCFAs) and particularly involved odd-numbered and dicarboxylate Fatty Acids. One quartile change of nonanoate, the top protective MCFA, was associated with high odds of having persistent normoalbuminuria (OR (95% CI) 0.14 (0.09, 0.23); p < 10-12). Multivariable Random Forest analysis concordantly indicated to MCFAs as effective classifiers. Associations of the relevant Fatty Acids with albuminuria seemed to parallel associations with tubular biomarkers. Our findings suggest that MCFAs and SCFAs contribute to the metabolic processes underlying protection against albuminuria development in T1D that are independent from mechanisms associated with changes in renal function.
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Affiliation(s)
- Salina Moon
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
| | - John J Tsay
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Medicine, Veterans Affairs Boston Healthcare System, Boston, MA, USA
| | - Heather Lampert
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Family Medicine, Brown University, Providence, RI, USA
| | - Zaipul I Md Dom
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Aleksandar D Kostic
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Microbiology, Harvard Medical School, Boston, MA, USA
| | - Adam Smiles
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA
| | - Monika A Niewczas
- Research Division, Joslin Diabetes Center, One Joslin Place, Boston, MA, 02215, USA.
- Department of Medicine, Harvard Medical School, Boston, MA, USA.
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Al‐Sari N, Schmidt S, Suvitaival T, Kim M, Trošt K, Ranjan AG, Christensen MB, Overgaard AJ, Pociot F, Nørgaard K, Legido‐Quigley C. Changes in the lipidome in type 1 diabetes following low carbohydrate diet: Post-hoc analysis of a randomized crossover trial. Endocrinol Diabetes Metab 2021; 4:e00213. [PMID: 33855215 PMCID: PMC8029500 DOI: 10.1002/edm2.213] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2020] [Accepted: 11/14/2020] [Indexed: 01/14/2023] Open
Abstract
Aims Lipid metabolism might be compromised in type 1 diabetes, and the understanding of lipid physiology is critically important. This study aimed to compare the change in plasma lipid concentrations during carbohydrate dietary changes in individuals with type 1 diabetes and identify links to early-stage dyslipidaemia. We hypothesized that (1) the lipidomic profiles after ingesting low or high carbohydrate diet for 12 weeks would be different; and (2) specific annotated lipid species could have significant associations with metabolic outcomes. Methods Ten adults with type 1 diabetes (mean ± SD: age 43.6 ± 13.8 years, diabetes duration 24.5 ± 13.4 years, BMI 24.9 ± 2.1 kg/m2, HbA1c 57.6 ± 2.6 mmol/mol) using insulin pumps participated in a randomized 2-period crossover study with a 12-week intervention period of low carbohydrate diet (< 100 g carbohydrates/day) or high carbohydrate diet (> 250 g carbohydrates/day), respectively, separated by a 12-week washout period. A large-scale non-targeted lipidomics was performed with mass spectrometry in fasting plasma samples obtained before and after each diet intervention. Longitudinal lipid levels were analysed using linear mixed-effects models. Results In total, 289 lipid species were identified from 14 major lipid classes. Comparing the two diets, 11 lipid species belonging to sphingomyelins, phosphatidylcholines and LPC(O-16:0) were changed. All the 11 lipid species were significantly elevated during low carbohydrate diet. Two lipid species were most differentiated between diets, namely SM(d36:1) (β ± SE: 1.44 ± 0.28, FDR = 0.010) and PC(P-36:4)/PC(O-36:5) (β ± SE: 1.34 ± 0.25, FDR = 0.009) species. Polyunsaturated PC(35:4) was inversely associated with BMI and positively associated with HDL cholesterol (p < .001). Conclusion Lipidome-wide outcome analysis of a randomized crossover trial of individuals with type 1 diabetes following a low carbohydrate diet showed an increase in sphingomyelins and phosphatidylcholines which are thought to reduce dyslipidaemia. The polyunsaturated phosphatidylcholine 35:4 was inversely associated with BMI and positively associated with HDL cholesterol (p < .001). Results from this study warrant for more investigation on the long-term effect of single lipid species in type 1 diabetes.
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Affiliation(s)
| | - Signe Schmidt
- Steno Diabetes Center CopenhagenGentofteDenmark
- Danish Diabetes AcademyOdenseDenmark
- Department of EndocrinologyCopenhagen University Hospital HvidovreHvidovreDenmark
| | | | - Min Kim
- Steno Diabetes Center CopenhagenGentofteDenmark
| | - Kajetan Trošt
- Steno Diabetes Center CopenhagenGentofteDenmark
- Present address:
Novo Nordisk foundation Center for Basic Metabolic ResearchKøbenhavn NDenmark
| | - Ajenthen G. Ranjan
- Steno Diabetes Center CopenhagenGentofteDenmark
- Danish Diabetes AcademyOdenseDenmark
- Department of EndocrinologyCopenhagen University Hospital HvidovreHvidovreDenmark
| | - Merete B. Christensen
- Steno Diabetes Center CopenhagenGentofteDenmark
- Department of EndocrinologyCopenhagen University Hospital HvidovreHvidovreDenmark
| | | | - Flemming Pociot
- Steno Diabetes Center CopenhagenGentofteDenmark
- Department of Clinical MedicineUniversity of CopenhagenKøbenhavnDenmark
| | - Kirsten Nørgaard
- Steno Diabetes Center CopenhagenGentofteDenmark
- Department of EndocrinologyCopenhagen University Hospital HvidovreHvidovreDenmark
| | - Cristina Legido‐Quigley
- Steno Diabetes Center CopenhagenGentofteDenmark
- Institute of Pharmaceutical ScienceKing’s College LondonLondonUK
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36
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Dysbiosis in the Development of Type I Diabetes and Associated Complications: From Mechanisms to Targeted Gut Microbes Manipulation Therapies. Int J Mol Sci 2021; 22:ijms22052763. [PMID: 33803255 PMCID: PMC7967220 DOI: 10.3390/ijms22052763] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 03/06/2021] [Accepted: 03/08/2021] [Indexed: 12/12/2022] Open
Abstract
Globally, we are facing a worrying increase in type 1 diabetes mellitus (T1DM) incidence, with onset at younger age shedding light on the need to better understand the mechanisms of disease and step-up prevention. Given its implication in immune system development and regulation of metabolism, there is no surprise that the gut microbiota is a possible culprit behind T1DM pathogenesis. Additionally, microbiota manipulation by probiotics, prebiotics, dietary factors and microbiota transplantation can all modulate early host-microbiota interactions by enabling beneficial microbes with protective potential for individuals with T1DM or at high risk of developing T1DM. In this review, we discuss the challenges and perspectives of translating microbiome data into clinical practice. Nevertheless, this progress will only be possible if we focus our interest on developing numerous longitudinal, multicenter, interventional and double-blind randomized clinical trials to confirm their efficacy and safety of these therapeutic approaches.
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Mass Spectrometry-based Metabolomics in Translational Research. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1310:509-531. [PMID: 33834448 DOI: 10.1007/978-981-33-6064-8_19] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Metabolomics is the systematic study of metabolite profiles of complex biological systems, and involves the systematic identification and quantification of metabolites. Metabolism is integrated with all biochemical reactions in biological systems; thus metabolite profiles provide collective information on biochemical processes induced by genetic or environmental perturbations. Transcriptomes or proteomes may not be functionally active and not always reflect phenotypic variations. The metabolome, however, consists of the biomolecules closest to the phenotype of living organisms, and is often called the molecular phenotype of biological systems. Thus, metabolome alterations can easily result in disease states, providing important clues to understand pathophysiological mechanisms contributing to various biomedical symptoms. The metabolome and metabolomics have been emphasized in translational research related to biomarker discovery, drug target discovery, drug responses, and disease mechanisms. This review describes the basic concepts, workflows, and applications of mass spectrometry-based metabolomics in translational research.
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38
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Wang L, Zhang Y, Liu X, Zhao X, Ouyang Y, Qiu G, Lv W, Zheng F, Wang Q, Lu X, Peng X, Wu T, Lehmann R, Wang C, Jia W, Xu G. Metabolite Triplet in Serum Improves the Diagnostic Accuracy of Prediabetes and Diabetes Screening. J Proteome Res 2020; 20:1005-1014. [PMID: 33347754 DOI: 10.1021/acs.jproteome.0c00786] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Large-scale population screenings are not feasible by applying laborious oral glucose tolerance tests, but using fasting blood glucose (FPG) and glycated hemoglobin (HbA1c), a considerable number of diagnoses are missed. A novel marker is urgently needed to improve the diagnostic accuracy of broad-scale diabetes screening in easy-to-collect blood samples. In this study, by applying a novel knowledge-based, multistage discovery and validation strategy, we scaled down from 108 diabetes-associated metabolites to a diagnostic metabolite triplet (Met-T), namely hexose, 2-hydroxybutyric/2-hydroxyisobutyric acid, and phenylalanine. Met-T showed in two independent cohorts, each comprising healthy controls, prediabetic, and diabetic individuals, distinctly higher diagnostic sensitivities for diabetes screening than FPG alone (>79.6 vs <68%). Missed diagnoses decreased from >32% using fasting plasma glucose down to <20.4%. Combining Met-T and fasting plasma glucose further improved the diagnostic accuracy. Additionally, a positive association of Met-T with future diabetes risk was found (odds ratio: 1.41; p = 1.03 × 10-6). The results reveal that missed prediabetes and diabetes diagnoses can be markedly reduced by applying Met-T alone or in combination with FPG and it opens perspectives for higher diagnostic accuracy in broad-scale diabetes-screening approaches using easy to collect sample materials.
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Affiliation(s)
- Lichao Wang
- State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China.,CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yinan Zhang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Xinyu Liu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
| | - Xinjie Zhao
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
| | - Yang Ouyang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Gaokun Qiu
- MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Wangjie Lv
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Fujian Zheng
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - QingQing Wang
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China.,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Xin Lu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
| | - Xiaojun Peng
- State Key Laboratory of Fine Chemicals, Dalian University of Technology, Dalian 116024, China
| | - Tangchun Wu
- MOE Key Laboratory of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science & Technology, Wuhan 430030, Hubei, China
| | - Rainer Lehmann
- Institute for Clinical Chemistry and Pathobiochemistry, University Hospital Tuebingen, Hoppe-Seyler-Strasse 3, Tuebingen 72076, Germany.,Institute for Diabetes Research and Metabolic Diseases of the Helmholtz Zentrum Muenchen at the University of Tuebingen, Tuebingen 72076, Germany.,German Center for Diabetes Research (DZD), Tübingen 72076, Germany
| | - Congrong Wang
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China.,Department of Endocrinology, Shanghai Fourth People's Hospital Affiliated to Tongji University, Shanghai 200434, China
| | - Weiping Jia
- Shanghai Diabetes Institute, Shanghai Key Laboratory of Diabetes Mellitus, Shanghai Clinical Center for Endocrine and Metabolic Diseases, Metabolic Diseases Biobank, Shanghai Jiao Tong University Affiliated Sixth People's Hospital, Shanghai 200233, China
| | - Guowang Xu
- CAS Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China
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Gu X, Al Dubayee M, Alshahrani A, Masood A, Benabdelkamel H, Zahra M, Li L, Abdel Rahman AM, Aljada A. Distinctive Metabolomics Patterns Associated With Insulin Resistance and Type 2 Diabetes Mellitus. Front Mol Biosci 2020; 7:609806. [PMID: 33381523 PMCID: PMC7768025 DOI: 10.3389/fmolb.2020.609806] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 11/23/2020] [Indexed: 01/17/2023] Open
Abstract
Obesity is associated with an increased risk of insulin resistance (IR) and type 2 diabetes mellitus (T2DM) which is a multi-factorial disease associated with a dysregulated metabolism and can be prevented in pre-diabetic individuals with impaired glucose tolerance. A metabolomic approach emphasizing metabolic pathways is critical to our understanding of this heterogeneous disease. This study aimed to characterize the serum metabolomic fingerprint and multi-metabolite signatures associated with IR and T2DM. Here, we have used untargeted high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) to identify candidate biomarkers of IR and T2DM in sera from 30 adults of normal weight, 26 obese adults, and 16 adults newly diagnosed with T2DM. Among the 3633 peak pairs detected, 62% were either identified or matched. A group of 78 metabolites were up-regulated and 111 metabolites were down-regulated comparing obese to lean group while 459 metabolites were up-regulated and 166 metabolites were down-regulated comparing T2DM to obese groups. Several metabolites were identified as IR potential biomarkers, including amino acids (Asn, Gln, and His), methionine (Met) sulfoxide, 2-methyl-3-hydroxy-5-formylpyridine-4-carboxylate, serotonin, L-2-amino-3-oxobutanoic acid, and 4,6-dihydroxyquinoline. T2DM was associated with dysregulation of 42 metabolites, including amino acids, amino acids metabolites, and dipeptides. In conclusion, these pilot data have identified IR and T2DM metabolomics panels as potential novel biomarkers of IR and identified metabolites associated with T2DM, with possible diagnostic and therapeutic applications. Further studies to confirm these associations in prospective cohorts are warranted.
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Affiliation(s)
- Xinyun Gu
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Mohammed Al Dubayee
- Department of Medicine, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Awad Alshahrani
- Department of Medicine, College of Medicine, King Saud bin Abdulaziz University for Health Sciences, King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia
| | - Afshan Masood
- Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Hicham Benabdelkamel
- Obesity Research Center, College of Medicine, King Saud University, Riyadh, Saudi Arabia
| | - Mahmoud Zahra
- Department of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
| | - Liang Li
- Department of Chemistry, University of Alberta, Edmonton, AB, Canada
| | - Anas M Abdel Rahman
- Department of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia.,Department of Genetics, King Faisal Specialist Hospital and Research Center, Riyadh, Saudi Arabia.,Department of Chemistry, Memorial University of Newfoundland, St. John's, NL, Canada
| | - Ahmad Aljada
- Department of Biochemistry and Molecular Medicine, College of Medicine, Alfaisal University, Riyadh, Saudi Arabia
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40
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Fu Y, Yin R, Liu Z, Niu Y, Guo E, Cheng R, Diao X, Xue Y, Shen Q. Hypoglycemic Effect of Prolamin from Cooked Foxtail Millet ( Setaria italic) on Streptozotocin-Induced Diabetic Mice. Nutrients 2020; 12:E3452. [PMID: 33187155 PMCID: PMC7696583 DOI: 10.3390/nu12113452] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2020] [Revised: 11/06/2020] [Accepted: 11/09/2020] [Indexed: 12/12/2022] Open
Abstract
Millet proteins have been demonstrated to possess glucose-lowering and lipid metabolic disorder modulation functions against diabetes; however, the molecular mechanisms underlying their anti-diabetic effects remain unclear. The present study aimed to investigate the hypoglycemic effect of prolamin from cooked foxtail millet (PCFM) on type 2 diabetic mice, and explore the gut microbiota and serum metabolic profile changes that are associated with diabetes attenuation by PCFM. Our diabetes model was established using a high-fat diet combined with streptozotocin before PCFM or saline was daily administrated by gavage for 5 weeks. The results showed that PCFM ameliorated glucose metabolism disorders associated with type 2 diabetes. Furthermore, the effects of PCFM administration on gut microbiota and serum metabolome were investigated. 16S rRNA gene sequencing analysis indicated that PCFM alleviated diabetes-related gut microbiota dysbiosis in mice. Additionally, the serum metabolomics analysis revealed that the metabolite levels disturbed by diabetes were partly altered by PCFM. Notably, the decreased D-Glucose level caused by PCFM suggested that its anti-diabetic potential can be associated with the activation of glycolysis and the inhibition of gluconeogenesis, starch and sucrose metabolism and galactose metabolism. In addition, the increased serotonin level caused by PCFM may stimulate insulin secretion by pancreatic β-cells, which contributed to its hypoglycemic effect. Taken together, our research demonstrated that the modulation of gut microbiota composition and the serum metabolomics profile was associated with the anti-diabetic effect of PCFM.
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Affiliation(s)
- Yongxia Fu
- Key Laboratory of Plant Protein and Grain Processing, National Engineering Research Center for Fruits and Vegetables Processing, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (Y.F.); (R.Y.); (Z.L.); (Y.X.)
| | - Ruiyang Yin
- Key Laboratory of Plant Protein and Grain Processing, National Engineering Research Center for Fruits and Vegetables Processing, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (Y.F.); (R.Y.); (Z.L.); (Y.X.)
| | - Zhenyu Liu
- Key Laboratory of Plant Protein and Grain Processing, National Engineering Research Center for Fruits and Vegetables Processing, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (Y.F.); (R.Y.); (Z.L.); (Y.X.)
| | - Yan Niu
- Shan Xi Dongfang Wuhua Agricultural Technology Co. Ltd., Datong 037000, China;
| | - Erhu Guo
- Research Institute of Millet, Shanxi Academy of Agricultural Sciences, Taiyuan 030031, China;
| | - Ruhong Cheng
- Research Institute of Millet, Hebei Academy of Agriculture and Forestry Sciences, Shijiazhuang 050035, China;
| | - Xianmin Diao
- Institute of Crop Science, Chinese Academy of Agricultural Sciences, Beijing 100081, China;
| | - Yong Xue
- Key Laboratory of Plant Protein and Grain Processing, National Engineering Research Center for Fruits and Vegetables Processing, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (Y.F.); (R.Y.); (Z.L.); (Y.X.)
| | - Qun Shen
- Key Laboratory of Plant Protein and Grain Processing, National Engineering Research Center for Fruits and Vegetables Processing, College of Food Science and Nutritional Engineering, China Agricultural University, Beijing 100083, China; (Y.F.); (R.Y.); (Z.L.); (Y.X.)
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41
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Lin L, Zhang S, Lin Y, Liu W, Zou B, Cai Y, Liu D, Sun Y, Zhong Y, Xiao D, Liao Q, Xie Z. Untargeted metabolomics analysis on Cicer arietinium L.-Induced Amelioration in T2D rats by UPLC-Q-TOF-MS/MS. JOURNAL OF ETHNOPHARMACOLOGY 2020; 261:113013. [PMID: 32526338 DOI: 10.1016/j.jep.2020.113013] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2019] [Revised: 04/24/2020] [Accepted: 05/22/2020] [Indexed: 06/11/2023]
Abstract
ETHNOPHARMACOLOGICAL RELEVANCE Cicer arietinium L., which belongs to Cicer genus, was not only a kind of traditional Chinese medicines (TCM) recorded in Pharmacopoeia of the People's Republic of China (version 2015), but also a kind of Uighur antidiabetic medicines. It has been used as an adjuvant drug or functional food for thousand years in Xinjiang province, China. However, the mechanisms of C. arietinium treatment in T2D have not been fully understood especially on the perspective of metabolomics. AIM OF THE STUDY To clarify the potential mechanisms of C. arietinium treatment in T2D from the perspective of metabolomics since T2D is indeed a kind of metabolic syndromes. MATERIALS AND METHODS T2D rat model was built by HFD for 4 weeks, combining with STZ administration. T2D rats were administrated C. arietinium extraction or metformin (positive control) for 4 weeks. UPLC-Q-TOF-MS was applied to screen and identify differential metabolites among groups. RESULTS After 4 weeks of treatments, IR and inflammation were greatly ameliorated in C. arietinium group. And the therapeutic efficiency of C. arietinium treatment was comparable to metformin treatment. Differential metabolites related to C. arietinium treatment, including acylcarnitines, amino acid related metabolites and organic acids, were further used to indicate relevant pathways in T2D rats, including glyoxylate and dicarboxylate metabolism, tricarboxylic acid cycle, vitamin B6 metabolism and energy metabolism. CONCLUSIONS In summary, C. arietinium treatment could effectively alleviate diabetic symptoms and regulate metabolic disorders in T2D rats.
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MESH Headings
- Animals
- Biomarkers/blood
- Blood Glucose/drug effects
- Blood Glucose/metabolism
- Chromatography, High Pressure Liquid
- Cicer/chemistry
- Diabetes Mellitus, Experimental/blood
- Diabetes Mellitus, Experimental/chemically induced
- Diabetes Mellitus, Experimental/drug therapy
- Diabetes Mellitus, Type 2/blood
- Diabetes Mellitus, Type 2/chemically induced
- Diabetes Mellitus, Type 2/drug therapy
- Energy Metabolism/drug effects
- Hypoglycemic Agents/isolation & purification
- Hypoglycemic Agents/pharmacology
- Male
- Metabolomics
- Metformin/pharmacology
- Plant Extracts/isolation & purification
- Plant Extracts/pharmacology
- Rats, Sprague-Dawley
- Spectrometry, Mass, Electrospray Ionization
- Streptozocin
- Tandem Mass Spectrometry
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Affiliation(s)
- Lei Lin
- School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China
| | - Shaobao Zhang
- School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China
| | - Yixuan Lin
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Wen Liu
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China
| | - Baorong Zou
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China
| | - Ying Cai
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China
| | - Deliang Liu
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China
| | - Yangwen Sun
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China
| | - Yuping Zhong
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Dan Xiao
- School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China
| | - Qiongfeng Liao
- School of Pharmaceutical Sciences, Guangzhou University of Chinese Medicine, Guangzhou, 510006, China
| | - Zhiyong Xie
- School of Pharmaceutical Sciences, Sun Yat-sen University, Guangzhou, 510006, China; School of Pharmaceutical Sciences (Shenzhen), Sun Yat-sen University, Guangzhou, 510006, China; Guangdong Provincial Key Laboratory of New Drug Design and Evaluation, Guangzhou, 510006, China.
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42
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Zhu Y, Wancewicz B, Schaid M, Tiambeng TN, Wenger K, Jin Y, Heyman H, Thompson CJ, Barsch A, Cox ED, Davis DB, Brasier AR, Kimple ME, Ge Y. Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research. J Proteome Res 2020; 20:463-473. [PMID: 33054244 DOI: 10.1021/acs.jproteome.0c00510] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.
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Affiliation(s)
- Yanlong Zhu
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Benjamin Wancewicz
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Michael Schaid
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Research Service, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 53705, United States
| | - Timothy N Tiambeng
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Kent Wenger
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Yutong Jin
- Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
| | - Heino Heyman
- Bruker Daltonics Inc., Billerica, Massachusetts 01821, United States
| | | | | | - Elizabeth D Cox
- Department of Pediatrics, University of Wisconsin-Madison, Madison, Wisconsin 53792, United States
| | - Dawn B Davis
- Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Research Service, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 53705, United States
| | - Allan R Brasier
- Institute for Clinical and Translational Research, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States
| | - Michelle E Kimple
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Medicine, Division of Endocrinology, Diabetes, and Metabolism, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Research Service, William S. Middleton Memorial Veterans Hospital, Madison, Wisconsin 53705, United States
| | - Ying Ge
- Department of Cell and Regenerative Biology, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Human Proteomics Program, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, Wisconsin 53705, United States.,Department of Chemistry, University of Wisconsin-Madison, Madison, Wisconsin 53706, United States
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43
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Liu W, Li S, Wu YK, Yan X, Zhu YM, Jiang FY, Jiang Y, Zou LH, Wang TT. Metabolic profiling of rats poisoned with paraquat and treated with Xuebijing using a UPLC-QTOF-MS/MS metabolomics approach. ANALYTICAL METHODS : ADVANCING METHODS AND APPLICATIONS 2020; 12:4562-4571. [PMID: 33001064 DOI: 10.1039/d0ay00968g] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Xuebijing (XBJ) is a compound Chinese medicine that contains Paeoniae Radix Rubra, ChuanXiong Rhizoma, Salvia Miltiorrhiza Radix et Rhizoma, Carthami Flos, and Angelicae Sinensis Radix. It is widely used in China to treat sepsis. Previous studies have demonstrated that XBJ can decrease mortality in patients with moderate paraquat poisoning. However, the mechanism by which it exerts this effect is not completely clear. In this study, an ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC-QTOF-MS/MS)-based metabolomics approach was used to perform a metabolic profiling analysis. Principal component analysis (PCA), random forest (RF), and partial least squares discriminant analysis (PLS-DA) were used to identify metabolites to clarify the mechanism of XBJ's activity. XBJ clearly alleviated lung injury in a Sprague Dawley (SD) rat model of paraquat (PQ) poisoning. Seven metabolites related to four pathways, including those involved in sphingolipid and phospholipid metabolism, amino acid metabolism, unsaturated fatty acid metabolism, and pantothenic acid and CoA biosynthesis, were present at different levels in PQ-poisoned rats treated with XBJ compared with untreated rats. XBJ can ameliorate the effects of PQ poisoning in SD rats. Using a metabolomics approach enabled us to gain new insight into the mechanism underlying this effect.
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Affiliation(s)
- Wen Liu
- Department of Pharmacy, Hunan Provincial People's Hospital/The First Affiliated Hospital of Hunan Normal University, Changsha, 410005, China.
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44
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Malinowski RM, Ghiasi SM, Mandrup-Poulsen T, Meier S, Lerche MH, Ardenkjær-Larsen JH, Jensen PR. Pancreatic β-cells respond to fuel pressure with an early metabolic switch. Sci Rep 2020; 10:15413. [PMID: 32963286 PMCID: PMC7508987 DOI: 10.1038/s41598-020-72348-1] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2019] [Accepted: 06/03/2020] [Indexed: 11/23/2022] Open
Abstract
Pancreatic β-cells become irreversibly damaged by long-term exposure to excessive glucose concentrations and lose their ability to carry out glucose stimulated insulin secretion (GSIS) upon damage. The β-cells are not able to control glucose uptake and they are therefore left vulnerable for endogenous toxicity from metabolites produced in excess amounts upon increased glucose availability. In order to handle excess fuel, the β-cells possess specific metabolic pathways, but little is known about these pathways. We present a study of β-cell metabolism under increased fuel pressure using a stable isotope resolved NMR approach to investigate early metabolic events leading up to β-cell dysfunction. The approach is based on a recently described combination of 13C metabolomics combined with signal enhanced NMR via dissolution dynamic nuclear polarization (dDNP). Glucose-responsive INS-1 β-cells were incubated with increasing concentrations of [U-13C] glucose under conditions where GSIS was not affected (2–8 h). We find that pyruvate and DHAP were the metabolites that responded most strongly to increasing fuel pressure. The two major divergence pathways for fuel excess, the glycerolipid/fatty acid metabolism and the polyol pathway, were found not only to operate at unchanged rate but also with similar quantity.
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Affiliation(s)
- Ronja M Malinowski
- Department of Health Technology, Technical University of Denmark, Oersteds Pl. Bldg. 349, Room 120, 2800, Kgs. Lyngby, Denmark
| | - Seyed M Ghiasi
- Department of Biomedical Sciences, University of Copenhagen, Copenhagen, Denmark.,Department of Metabolism, Digestion and Reproduction, Imperial College London, London, UK
| | | | - Sebastian Meier
- Department of Chemistry, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Mathilde H Lerche
- Department of Health Technology, Technical University of Denmark, Oersteds Pl. Bldg. 349, Room 120, 2800, Kgs. Lyngby, Denmark
| | - Jan H Ardenkjær-Larsen
- Department of Health Technology, Technical University of Denmark, Oersteds Pl. Bldg. 349, Room 120, 2800, Kgs. Lyngby, Denmark
| | - Pernille R Jensen
- Department of Health Technology, Technical University of Denmark, Oersteds Pl. Bldg. 349, Room 120, 2800, Kgs. Lyngby, Denmark.
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45
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Mass spectrometry-based metabolomics for an in-depth questioning of human health. Adv Clin Chem 2020; 99:147-191. [PMID: 32951636 DOI: 10.1016/bs.acc.2020.02.009] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Abstract
Today, metabolomics is becoming an indispensable tool to get a more comprehensive analysis of complex living systems, providing insights on multiple aspects of physiology. Although its application in large scale population-based studies is very challenging due to the processing of large sample sets as well as the complexity of data information, its potential to characterize human health is well recognized. Technological advances in metabolomics pave the way for the efficient biomarker discovery of disease etiology, diagnosis and prognosis. Here, different steps of the metabolomics workflow, particularly mass spectrometry-based approaches, are discussed to demonstrate the potential of metabolomics to address biological questioning in human health. First an overview of metabolomics is provided with its interest in human health studies. Analytical development and advances in mass spectrometry instrumentation and computational tools are discussed regarding their application limits. Advancing metabolomics for applicability in human health and large-scale studies is presented and discussed in conclusion.
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46
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Lee YF, Sim XY, Teh YH, Ismail MN, Greimel P, Murugaiyah V, Ibrahim B, Gam LH. The effects of high-fat diet and metformin on urinary metabolites in diabetes and prediabetes rat models. Biotechnol Appl Biochem 2020; 68:1014-1026. [PMID: 32931602 DOI: 10.1002/bab.2021] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2020] [Accepted: 08/31/2020] [Indexed: 12/17/2022]
Abstract
High-fat diet (HFD) interferes with the dietary plan of patients with type 2 diabetes mellitus (T2DM). However, many diabetes patients consume food with higher fat content for a better taste bud experience. In this study, we examined the effect of HFD on rats at the early onset of diabetes and prediabetes by supplementing their feed with palm olein oil to provide a fat content representing 39% of total calorie intake. Urinary profile generated from liquid chromatography-mass spectrometry analysis was used to construct the orthogonal partial least squares discriminant analysis (OPLS-DA) score plots. The data provide insights into the physiological state of an organism. Healthy rats fed with normal chow (NC) and HFD cannot be distinguished by their urinary metabolite profiles, whereas diabetic and prediabetic rats showed a clear separation in OPLS-DA profile between the two diets, indicating a change in their physiological state. Metformin treatment altered the metabolomics profiles of diabetic rats and lowered their blood sugar levels. For prediabetic rats, metformin treatment on both NC- and HFD-fed rats not only reduced their blood sugar levels to normal but also altered the urinary metabolite profile to be more like healthy rats. The use of metformin is therefore beneficial at the prediabetes stage.
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Affiliation(s)
- Yan-Fen Lee
- USM-RIKEN International Centre of Aging Science, USM, Minden, Penang, Malaysia.,School of Pharmaceutical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
| | - Xuan-Yi Sim
- USM-RIKEN International Centre of Aging Science, USM, Minden, Penang, Malaysia.,School of Pharmaceutical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
| | - Ying-Hui Teh
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
| | - Mohd Nazri Ismail
- Analytical Biochemistry Research Centre (ABrC), USM, Minden, Penang, Malaysia
| | - Peter Greimel
- Laboratory for Cell Function Dynamics, RIKEN Centre for Brain Sciences, Wako, Saitama, Japan
| | | | - Baharudin Ibrahim
- School of Pharmaceutical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
| | - Lay-Harn Gam
- USM-RIKEN International Centre of Aging Science, USM, Minden, Penang, Malaysia.,School of Pharmaceutical Sciences, Universiti Sains Malaysia, Minden, Penang, Malaysia
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47
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Tran H, McConville M, Loukopoulos P. Metabolomics in the study of spontaneous animal diseases. J Vet Diagn Invest 2020; 32:635-647. [PMID: 32807042 PMCID: PMC7488963 DOI: 10.1177/1040638720948505] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
Using analytical chemistry techniques such as nuclear magnetic resonance (NMR) spectroscopy and liquid or gas chromatography-mass spectrometry (LC/GC-MS), metabolomics allows detection of most endogenous and exogenous metabolites in a biological sample. Metabolomics has a wide range of applications, and has been employed in nutrition science, toxicology, environmental studies, and systems biology. Metabolomics is particularly useful in biomedical science, and has been used for diagnostic laboratory testing, identifying targets for drug development, and monitoring drug metabolism, mode of action, and toxicity. Despite its immense potential, metabolomics remains underutilized in the study of spontaneous animal diseases. Our aim was to comprehensively review the existing literature on the use of metabolomics in spontaneous veterinary diseases. Three databases were used to find journal articles that applied metabolomics in veterinary medicine. A screening process was then conducted to eliminate references that did not meet the eligibility criteria; only primary research studies investigating spontaneous animal disease were included; 38 studies met the inclusion criteria. The main techniques used were NMR and MS. All studies detected metabolite alterations in diseased animals compared with non-diseased animals. Metabolomics was mainly used to study diseases of the digestive, reproductive, and musculoskeletal systems. Inflammatory conditions made up the largest proportion of studies when articles were categorized by disease process. Following a comprehensive analysis of the literature on metabolomics in spontaneous veterinary diseases, we concluded that metabolomics, although in its early stages in veterinary research, is a promising tool regarding diagnosis, biomarker discovery, and in uncovering new insights into disease pathophysiology.
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Affiliation(s)
- Helena Tran
- Melbourne Veterinary School, Faculty of
Veterinary and Agricultural Sciences, University of Melbourne, Melbourne,
Victoria, Australia
| | - Malcolm McConville
- Bio21 Institute, Metabolomics Australia,
University of Melbourne, Melbourne, Victoria, Australia
| | - Panayiotis Loukopoulos
- Melbourne Veterinary School, Faculty of
Veterinary and Agricultural Sciences, University of Melbourne, Melbourne,
Victoria, Australia
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48
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Méndez-Rodríguez KB, Figueroa-Vega N, Ilizaliturri-Hernandez CA, Cardona-Alvarado M, Borjas-García JA, Kornhauser C, Malacara JM, Flores-Ramírez R, Pérez-Vázquez FJ. Identification of metabolic markers in patients with type 2 Diabetes by Ultrafast gas chromatography coupled to electronic nose. A pilot study. Biomed Chromatogr 2020; 34:e4956. [PMID: 32706910 DOI: 10.1002/bmc.4956] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/22/2020] [Revised: 07/19/2020] [Accepted: 07/22/2020] [Indexed: 12/27/2022]
Abstract
Metabolomics is a potential tool for the discovery of new biomarkers in the early diagnosis of diseases. An ultra-fast gas chromatography system equipped to an electronic nose detector (FGC eNose) was used to identify the metabolomic profile of Volatile Organic Compounds (VOCs) in type 2 diabetes (T2D) urine from Mexican population. A cross-sectional, comparative, and clinical study with translational approach was performed. We recruited twenty T2D patients and twenty-one healthy subjects. Urine samples were taken and analyzed by FGC eNose. Eighty-eight compounds were identified through Kovats's indexes. A natural variation of 30% between the metabolites, expressed by study groups, was observed in Principal Component 1 and 2 with a significant difference (p < 0.001). The model, performed through a Canonical Analysis of Principal coordinated (CAP), allowed a correct classification of 84.6% between healthy and T2D patients, with a 15.4% error. The metabolites 2-propenal, 2-propanol, butane- 2,3-dione and 2-methylpropanal, were increased in patients with T2D, and they were strongly correlated with discrimination between clinically healthy people and T2D patients. This study identified metabolites in urine through FGC eNose that can be used as biomarkers in the identification of T2D patients. However, more studies are needed for its implementation in clinical practice.
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Affiliation(s)
- Karen Beatriz Méndez-Rodríguez
- Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACyT), Universidad Autónoma de San Luis Potosí, San Luis Potosí, S.L.P., Mexico
| | - Nicté Figueroa-Vega
- Department of Medical Sciences, University of Guanajuato, León, Gto., Mexico
| | - César Arturo Ilizaliturri-Hernandez
- Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACyT), Universidad Autónoma de San Luis Potosí, San Luis Potosí, S.L.P., Mexico
| | | | | | - Carlos Kornhauser
- Department of Medical Sciences, University of Guanajuato, León, Gto., Mexico
| | | | - Rogelio Flores-Ramírez
- Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACyT), Universidad Autónoma de San Luis Potosí, San Luis Potosí, S.L.P., Mexico.,CONACYT Research Fellow, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACYT), Universidad Autónoma de San Luis Potosí, San Luis Potosí, S.L.P., Mexico
| | - Francisco Javier Pérez-Vázquez
- Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACyT), Universidad Autónoma de San Luis Potosí, San Luis Potosí, S.L.P., Mexico.,CONACYT Research Fellow, Coordinación para la Innovación y Aplicación de la Ciencia y la Tecnología (CIACYT), Universidad Autónoma de San Luis Potosí, San Luis Potosí, S.L.P., Mexico
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49
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Shah AM, Wondisford FE. Tracking the carbons supplying gluconeogenesis. J Biol Chem 2020; 295:14419-14429. [PMID: 32817317 DOI: 10.1074/jbc.rev120.012758] [Citation(s) in RCA: 24] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2020] [Revised: 08/12/2020] [Indexed: 11/06/2022] Open
Abstract
As the burden of type 2 diabetes mellitus (T2DM) grows in the 21st century, the need to understand glucose metabolism heightens. Increased gluconeogenesis is a major contributor to the hyperglycemia seen in T2DM. Isotope tracer experiments in humans and animals over several decades have offered insights into gluconeogenesis under euglycemic and diabetic conditions. This review focuses on the current understanding of carbon flux in gluconeogenesis, including substrate contribution of various gluconeogenic precursors to glucose production. Alterations of gluconeogenic metabolites and fluxes in T2DM are discussed. We also highlight ongoing knowledge gaps in the literature that require further investigation. A comprehensive analysis of gluconeogenesis may enable a better understanding of T2DM pathophysiology and identification of novel targets for treating hyperglycemia.
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Affiliation(s)
- Ankit M Shah
- Department of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA
| | - Fredric E Wondisford
- Department of Medicine, Robert Wood Johnson Medical School, Rutgers University, New Brunswick, New Jersey, USA
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50
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Lai M, Al Rijjal D, Röst HL, Dai FF, Gunderson EP, Wheeler MB. Underlying dyslipidemia postpartum in women with a recent GDM pregnancy who develop type 2 diabetes. eLife 2020; 9:59153. [PMID: 32748787 PMCID: PMC7417169 DOI: 10.7554/elife.59153] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2020] [Accepted: 07/18/2020] [Indexed: 12/15/2022] Open
Abstract
Approximately, 35% of women with Gestational Diabetes (GDM) progress to Type 2 Diabetes (T2D) within 10 years. However, links between GDM and T2D are not well understood. We used a well-characterised GDM prospective cohort of 1035 women following up to 8 years postpartum. Lipidomics profiling covering >1000 lipids was performed on fasting plasma samples from participants 6–9 week postpartum (171 incident T2D vs. 179 controls). We discovered 311 lipids positively and 70 lipids negatively associated with T2D risk. The upregulation of glycerolipid metabolism involving triacylglycerol and diacylglycerol biosynthesis suggested activated lipid storage before diabetes onset. In contrast, decreased sphingomyelines, hexosylceramide and lactosylceramide indicated impaired sphingolipid metabolism. Additionally, a lipid signature was identified to effectively predict future diabetes risk. These findings demonstrate an underlying dyslipidemia during the early postpartum in those GDM women who progress to T2D and suggest endogenous lipogenesis may be a driving force for future diabetes onset.
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Affiliation(s)
- Mi Lai
- Department of Physiology, Faculty of Medicine, University of Toronto, Ontario, Canada
| | - Dana Al Rijjal
- Department of Physiology, Faculty of Medicine, University of Toronto, Ontario, Canada
| | - Hannes L Röst
- Donnelly Centre for Cellular & Biomolecular Research, University of Toronto, Ontario, Canada
| | - Feihan F Dai
- Department of Physiology, Faculty of Medicine, University of Toronto, Ontario, Canada
| | - Erica P Gunderson
- Kaiser Permanente Northern California, Division of Research, Oakland, United States
| | - Michael B Wheeler
- Department of Physiology, Faculty of Medicine, University of Toronto, Ontario, Canada.,Advanced Diagnostics, Metabolism, Toronto General Research Institute, Ontario, Canada
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