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Ramos-Lopez O. Genotype-based precision nutrition strategies for the prediction and clinical management of type 2 diabetes mellitus. World J Diabetes 2024; 15:142-153. [PMID: 38464367 PMCID: PMC10921165 DOI: 10.4239/wjd.v15.i2.142] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/14/2023] [Revised: 12/07/2023] [Accepted: 01/11/2024] [Indexed: 02/04/2024] Open
Abstract
Globally, type 2 diabetes mellitus (T2DM) is one of the most common metabolic disorders. T2DM physiopathology is influenced by complex interrelationships between genetic, metabolic and lifestyle factors (including diet), which differ between populations and geographic regions. In fact, excessive consumptions of high fat/high sugar foods generally increase the risk of developing T2DM, whereas habitual intakes of plant-based healthy diets usually exert a protective effect. Moreover, genomic studies have allowed the characterization of sequence DNA variants across the human genome, some of which may affect gene expression and protein functions relevant for glucose homeostasis. This comprehensive literature review covers the impact of gene-diet interactions on T2DM susceptibility and disease progression, some of which have demonstrated a value as biomarkers of personal responses to certain nutritional interventions. Also, novel genotype-based dietary strategies have been developed for improving T2DM control in comparison to general lifestyle recommendations. Furthermore, progresses in other omics areas (epigenomics, metagenomics, proteomics, and metabolomics) are improving current understanding of genetic insights in T2DM clinical outcomes. Although more investigation is still needed, the analysis of the genetic make-up may help to decipher new paradigms in the pathophysiology of T2DM as well as offer further opportunities to personalize the screening, prevention, diagnosis, management, and prognosis of T2DM through precision nutrition.
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Affiliation(s)
- Omar Ramos-Lopez
- Medicine and Psychology School, Autonomous University of Baja California, Tijuana 22390, Baja California, Mexico
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Farrim MI, Gomes A, Milenkovic D, Menezes R. Gene expression analysis reveals diabetes-related gene signatures. Hum Genomics 2024; 18:16. [PMID: 38326874 PMCID: PMC10851551 DOI: 10.1186/s40246-024-00582-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 02/01/2024] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND Diabetes is a spectrum of metabolic diseases affecting millions of people worldwide. The loss of pancreatic β-cell mass by either autoimmune destruction or apoptosis, in type 1-diabetes (T1D) and type 2-diabetes (T2D), respectively, represents a pathophysiological process leading to insulin deficiency. Therefore, therapeutic strategies focusing on restoring β-cell mass and β-cell insulin secretory capacity may impact disease management. This study took advantage of powerful integrative bioinformatic tools to scrutinize publicly available diabetes-associated gene expression data to unveil novel potential molecular targets associated with β-cell dysfunction. METHODS A comprehensive literature search for human studies on gene expression alterations in the pancreas associated with T1D and T2D was performed. A total of 6 studies were selected for data extraction and for bioinformatic analysis. Pathway enrichment analyses of differentially expressed genes (DEGs) were conducted, together with protein-protein interaction networks and the identification of potential transcription factors (TFs). For noncoding differentially expressed RNAs, microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), which exert regulatory activities associated with diabetes, identifying target genes and pathways regulated by these RNAs is fundamental for establishing a robust regulatory network. RESULTS Comparisons of DEGs among the 6 studies showed 59 genes in common among 4 or more studies. Besides alterations in mRNA, it was possible to identify differentially expressed miRNA and lncRNA. Among the top transcription factors (TFs), HIPK2, KLF5, STAT1 and STAT3 emerged as potential regulators of the altered gene expression. Integrated analysis of protein-coding genes, miRNAs, and lncRNAs pointed out several pathways involved in metabolism, cell signaling, the immune system, cell adhesion, and interactions. Interestingly, the GABAergic synapse pathway emerged as the only common pathway to all datasets. CONCLUSIONS This study demonstrated the power of bioinformatics tools in scrutinizing publicly available gene expression data, thereby revealing potential therapeutic targets like the GABAergic synapse pathway, which holds promise in modulating α-cells transdifferentiation into β-cells.
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Affiliation(s)
- M I Farrim
- CBIOS, Universidade Lusófona's Research Center for Biosciences & Health Technologies, Universidade Lusófona, Lisbon, Portugal
- Universidad de Alcalá, Escuela de Doctorado, Madrid, Spain
| | - A Gomes
- CBIOS, Universidade Lusófona's Research Center for Biosciences & Health Technologies, Universidade Lusófona, Lisbon, Portugal
| | - D Milenkovic
- Department of Nutrition, University of California Davis, Davis, USA
| | - R Menezes
- CBIOS, Universidade Lusófona's Research Center for Biosciences & Health Technologies, Universidade Lusófona, Lisbon, Portugal.
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Ağagündüz D, Icer MA, Yesildemir O, Koçak T, Kocyigit E, Capasso R. The roles of dietary lipids and lipidomics in gut-brain axis in type 2 diabetes mellitus. J Transl Med 2023; 21:240. [PMID: 37009872 PMCID: PMC10068184 DOI: 10.1186/s12967-023-04088-5] [Citation(s) in RCA: 12] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/20/2023] [Accepted: 03/25/2023] [Indexed: 04/04/2023] Open
Abstract
Type 2 diabetes mellitus (T2DM), one of the main types of Noncommunicable diseases (NCDs), is a systemic inflammatory disease characterized by dysfunctional pancreatic β-cells and/or peripheral insulin resistance, resulting in impaired glucose and lipid metabolism. Genetic, metabolic, multiple lifestyle, and sociodemographic factors are known as related to high T2DM risk. Dietary lipids and lipid metabolism are significant metabolic modulators in T2DM and T2DM-related complications. Besides, accumulated evidence suggests that altered gut microbiota which plays an important role in the metabolic health of the host contributes significantly to T2DM involving impaired or improved glucose and lipid metabolism. At this point, dietary lipids may affect host physiology and health via interaction with the gut microbiota. Besides, increasing evidence in the literature suggests that lipidomics as novel parameters detected with holistic analytical techniques have important roles in the pathogenesis and progression of T2DM, through various mechanisms of action including gut-brain axis modulation. A better understanding of the roles of some nutrients and lipidomics in T2DM through gut microbiota interactions will help develop new strategies for the prevention and treatment of T2DM. However, this issue has not yet been entirely discussed in the literature. The present review provides up-to-date knowledge on the roles of dietary lipids and lipidomics in gut-brain axis in T2DM and some nutritional strategies in T2DM considering lipids- lipidomics and gut microbiota interactions are given.
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Affiliation(s)
- Duygu Ağagündüz
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Gazi University, 06490, Ankara, Turkey.
| | - Mehmet Arif Icer
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Amasya University, 05100, Amasya, Turkey
| | - Ozge Yesildemir
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Bursa Uludag University, 16059, Bursa, Turkey
| | - Tevfik Koçak
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Gazi University, 06490, Ankara, Turkey
| | - Emine Kocyigit
- Department of Nutrition and Dietetics, Faculty of Health Sciences, Ordu University, 52200, Ordu, Turkey
| | - Raffaele Capasso
- Department of Agricultural Sciences, University of Naples Federico II, Portici, 80055, Naples, Italy.
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Ding E, Deng F, Fang J, Li T, Hou M, Liu J, Miao K, Yan W, Fang K, Shi W, Fu Y, Liu Y, Dong H, Dong L, Ding C, Liu X, Pollitt KJG, Ji JS, Shi Y, Cai Y, Tang S, Shi X. Association between Organophosphate Ester Exposure and Insulin Resistance with Glycometabolic Disorders among Older Chinese Adults 60-69 Years of Age: Evidence from the China BAPE Study. Environ Health Perspect 2023; 131:47009. [PMID: 37042841 PMCID: PMC10094192 DOI: 10.1289/ehp11896] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 02/10/2023] [Accepted: 03/16/2023] [Indexed: 06/19/2023]
Abstract
BACKGROUND Organophosphate esters (OPEs) are common endocrine-disrupting chemicals, and OPE exposure may be associated with type 2 diabetes (T2D). However, greater knowledge regarding the biomolecular intermediators underlying the impact of OPEs on T2D in humans are needed to understand biological etiology. OBJECTIVES We explored the associations between OPE exposure and glycometabolic markers among older Chinese adults 60-69 years of age to elucidate the underlying mechanisms using a multi-omics approach. METHODS This was a longitudinal panel study comprising 76 healthy participants 60-69 years of age who lived in Jinan city of northern China. The study was conducted once every month for 5 months, from September 2018 to January 2019. We measured a total of 17 OPEs in the blood, 11 OPE metabolites in urine, and 4 glycometabolic markers (fasting plasma glucose, glycated serum protein, fasting insulin, and homeostatic model assessment for insulin resistance). The blood transcriptome and serum/urine metabolome were also evaluated. The associations between individual OPEs and glycometabolic markers were explored. An adverse outcome pathway (AOP) was established to determine the biomolecules mediating the associations. RESULTS Exposure to five OPEs and OPE metabolites (trimethylolpropane phosphate, triphenyl phosphate, tri-iso-butyl phosphate, dibutyl phosphate, and diphenyl phosphate) was associated with increased levels of glycometabolic markers. The mixture effect analysis further indicated the adverse effect of OPE mixtures. Multi-omics analyses revealed that the endogenous changes in the transcriptional and metabolic levels were associated with OPE exposure. The putative AOPs model suggested that triggers of molecular initiation events (e.g., insulin receptor and glucose transporter type 4) with subsequent key events, including disruptions in signal transduction pathways (e.g., phosphatidylinositol 3-kinase/protein kinase B and insulin secretion signaling) and biological functions (glucose uptake and insulin secretion), may constitute the diabetogenic effects of OPEs. DISCUSSION OPEs are associated with the elevated risk of T2D among older Chinese adults 60-69 years of age. Implementing OPE exposure reduction strategies may help reduce the T2D burden among these individuals, if the relationship is causal. https://doi.org/10.1289/EHP11896.
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Affiliation(s)
- Enmin Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Institute of Occupational Disease Prevention, Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Fuchang Deng
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Jianlong Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tiantian Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Minmin Hou
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
| | - Juan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ke Miao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wenyan Yan
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Ke Fang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wanying Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuanzheng Fu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yuanyuan Liu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Haoran Dong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Li Dong
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Changming Ding
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaohui Liu
- National Protein Science Technology Center and School of Life Sciences, Tsinghua University, Beijing, China
| | - Krystal J. Godri Pollitt
- Department of Environmental Health Sciences, Yale School of Public Health, New Haven, Connecticut, USA
| | - John S. Ji
- Vanke School of Public Health, Tsinghua University, Beijing, China
| | - Yali Shi
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
| | - Yaqi Cai
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
| | - Song Tang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
| | - Xiaoming Shi
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing, China
- Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, China
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Bajinka O, Tan Y, Darboe A, Ighaede-Edwards IG, Abdelhalim KA. The gut microbiota pathway mechanisms of diabetes. AMB Express 2023; 13:16. [PMID: 36754883 DOI: 10.1186/s13568-023-01520-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 01/25/2023] [Indexed: 02/10/2023] Open
Abstract
The contribution of dysbiotic gut microbiota configuration is essential when making reference to the metabolic disorders by increasing energy. It is important to understand that the gut microbiota induced metabolic disease mechanisms and inflammations. Thus it is imperative to have an insight into the state of all chronic subclinical inflammations influencing disease outcomes. However, from the emerging studies, there still exist inconsistencies in the findings of such studies. While making the best out of the reasons for inconsistencies of the findings, this review is designed to make a clear spell out as to the inconsistence of gut microbiota with respect to diabetes. It considered gut-virome alterations and diabetes and gut-bacteriome-gut-virome-alterations and diabetes as confounding factors. The review further explained some study design strategies that will spontaneously eliminate any potential confounding factors to lead to a more evidence based diabetic-gut microbiota medicine. Lipopolysaccharide (LPS) pro-inflammatory, metabolic endotoxemia and diet/gut microbiota insulin-resistance and low-grade systemic inflammation induced by gut microbiota can trigger pro-inflammatory cytokines in insulin-resistance, consequently, leading to the diabetic condition. While diet influences the gut microbiota, the consequences are mainly the constant high levels of pro-inflammatory cytokines in the circulatory system. Of recent, dietary natural products have been shown to be anti-diabetic. The effects of resveratrol on the gut showed an improved lipid profile, anti-inflammatory properties and ameliorated the endotoxemia, tight junction and glucose intolerance.
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Zhang X, Kupczyk E, Schmitt-Kopplin P, Mueller C. Current and future approaches for in vitro hit discovery in diabetes mellitus. Drug Discov Today 2022; 27:103331. [PMID: 35926826 DOI: 10.1016/j.drudis.2022.07.016] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Revised: 06/10/2022] [Accepted: 07/26/2022] [Indexed: 12/15/2022]
Abstract
Type 2 diabetes mellitus (T2DM) is a serious public health problem. In this review, we discuss current and promising future drugs, targets, in vitro assays and emerging omics technologies in T2DM. Importantly, we open the perspective to image-based high-content screening (HCS), with the focus of combining it with metabolomics or lipidomics. HCS has become a strong technology in phenotypic screens because it allows comprehensive screening for the cell-modulatory activity of small molecules. Metabolomics and lipidomics screen for perturbations at the molecular level. The combination of these data-intensive comprehensive technologies is enabled by the rapid development of artificial intelligence. It promises a deep cellular and molecular phenotyping directly linked to chemical information about the applied drug candidates or complex mixtures.
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Affiliation(s)
- Xin Zhang
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany
| | - Erwin Kupczyk
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany; Comprehensive Foodomics Platform, Chair of Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich, Maximus-von-Imhof-Forum 2, 85354 Freising, Germany
| | - Philippe Schmitt-Kopplin
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany; Comprehensive Foodomics Platform, Chair of Analytical Food Chemistry, TUM School of Life Sciences, Technical University of Munich, Maximus-von-Imhof-Forum 2, 85354 Freising, Germany.
| | - Constanze Mueller
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Ingolstaedter Landstr. 1, 85764 Neuherberg, Germany.
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Islam MN, Rabby MG, Hossen MM, Kamal MM, Zahid MA, Syduzzaman M, Hasan MM. In silico functional and pathway analysis of risk genes and SNPs for type 2 diabetes in Asian population. PLoS One 2022; 17:e0268826. [PMID: 36037214 PMCID: PMC9423640 DOI: 10.1371/journal.pone.0268826] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/29/2021] [Accepted: 05/10/2022] [Indexed: 11/19/2022] Open
Abstract
Type 2 diabetes (T2D) has earned widespread recognition as a primary cause of death, disability, and increasing healthcare costs. There is compelling evidence that hereditary factors contribute to the development of T2D. Clinical trials in T2D have mostly focused on genes and single nucleotide polymorphisms (SNPs) in protein-coding areas. Recently, it was revealed that SNPs located in noncoding areas also play a significant impact on disease vulnerability. It is required for cell type-specific gene expression. However, the precise mechanism by which T2D risk genes and SNPs work remains unknown. We integrated risk genes and SNPs from genome-wide association studies (GWASs) and performed comprehensive bioinformatics analyses to further investigate the functional significance of these genes and SNPs. We identified four intriguing transcription factors (TFs) associated with T2D. The analysis revealed that the SNPs are engaged in chromatin interaction regulation and/or may have an effect on TF binding affinity. The Gene Ontology (GO) study revealed high enrichment in a number of well-characterized signaling pathways and regulatory processes, including the STAT3 and JAK signaling pathways, which are both involved in T2D metabolism. Additionally, a detailed KEGG pathway analysis identified two major T2D genes and their prospective therapeutic targets. Our findings underscored the potential functional significance of T2D risk genes and SNPs, which may provide unique insights into the disease’s pathophysiology.
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Affiliation(s)
- Md. Numan Islam
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md. Golam Rabby
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md. Munnaf Hossen
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
- Department of Immunology, Health Science Center, Shenzhen University, Shenzhen, China
| | - Md. Mostafa Kamal
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md. Ashrafuzzaman Zahid
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md. Syduzzaman
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
| | - Md. Mahmudul Hasan
- Department of Nutrition and Food Technology, Jashore University of Science and Technology, Jashore, Bangladesh
- Division of Plant Science, University of Missouri, Columbia, Missouri, United States of America
- * E-mail:
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Xu J, Piao C, Qu Y, Liu T, Peng Y, Li Q, Zhao X, Li P, Wu X, Fan Y, Chen B, Yang J. Efficacy and mechanism of Jiedu Tongluo Tiaogan Formula in treating type 2 diabetes mellitus combined with non-alcoholic fatty liver disease: Study protocol for a parallel-armed, randomized controlled trial. Front Pharmacol 2022; 13:924021. [PMID: 36034810 PMCID: PMC9411737 DOI: 10.3389/fphar.2022.924021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 07/11/2022] [Indexed: 11/29/2022] Open
Abstract
Background: The incidence of Type 2 diabetes mellitus (T2DM) combined with non-alcoholic fatty liver disease (NAFLD) has risen over the years. This comorbid condition significantly increases the probability of cirrhosis, liver cancer, and mortality compared to the disease alone. The multi-targeted, holistic treatment efficacy of traditional Chinese medicine (TCM) plays a vital role in the treatment of T2DM and NAFLD. Jiedu Tongluo Tiaogan Formula (JTTF), based on TCM theory, is widely used in clinical treatment, and its effectiveness in lowering glucose, regulating lipids, improving insulin resistance, and its pathways of action have been demonstrated in previous studies. However, the mechanism of this formula has not been investigated from a metabolomics perspective. Moreover, high-quality clinical studies on T2DM combined with NAFLD are lacking. Therefore, we aim to conduct a clinical trial to investigate the clinical efficacy, safety, and possible pathways of JTTF in the treatment of T2DM combined with NAFLD using metabolomics techniques. Methods: A total of 98 participants will be recruited to this clinical trial and randomly assigned to either a treatment group (JTTF + conventional basic treatment) or control group (conventional basic treatment) in a 1:1 ratio. Both groups will have received the same lifestyle interventions in the preceding 12 weeks. The primary outcome will be change in visceral fat area and total score on the TCM syndromes efficacy score scale. The secondary outcome will include changes in ultrasound steatosis grade, fibrosis 4 score (FIB-4), metabolic parameters, anthropometric parameters, visceral fat area. In addition, serum and urine samples collected at baseline and at the end of 12 weeks of treatment will be sequentially tested for untargeted and targeted metabolomics. Discussion: This study will evaluate the efficacy and safety of JTTF, as well as investigate the differential metabolites and possible mechanisms of JTTF treatment in T2DM combined with NAFLD. We hypothesize that patients will benefit from JTTF, which may provide strong evidence for the clinical use of JTTF in the treatment of T2DM and NAFLD, leading to the possibility of further mechanistic exploration. Clinical Trial Registration: This clinical trial has been registered in China Clinical Trial Registry (ChiCTR 2100051174).
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Affiliation(s)
- Jinghan Xu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Chunli Piao
- Shenzhen Hospital, Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
- *Correspondence: Chunli Piao,
| | - Yue Qu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Tianjiao Liu
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Yuting Peng
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Qi Li
- Shenzhen Hospital, Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Xiaohua Zhao
- Shenzhen Hospital, Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Pei Li
- Shenzhen Hospital, Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Xuemin Wu
- Shenzhen Hospital, Guangzhou University of Chinese Medicine (Futian), Shenzhen, China
| | - Yawen Fan
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Binqin Chen
- Guangzhou University of Chinese Medicine, Guangzhou, China
| | - Jie Yang
- Changchun University of Chinese Medicine, Jilin, China
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Tian X, Gao Y, Zhong M, Kong M, Zhao L, Feng Z, Sun Q, He J, Liu X. The association between serum Sestrin2 and the risk of coronary heart disease in patients with type 2 diabetes mellitus. BMC Cardiovasc Disord 2022; 22:281. [PMID: 35729499 DOI: 10.1186/s12872-022-02727-1] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Accepted: 06/17/2022] [Indexed: 12/15/2022] Open
Abstract
Background Coronary heart disease (CHD) is one of the most common causes of morbidity and mortality in type 2 diabetes mellitus (T2DM). Oxidative stress is one of the important contributors to the pathogenesis of CHD. Sestrin2 is a stress-induced antioxidant protein that plays a important role in T2DM and CHD. However, the relationship between serum Sestrin2 levels and T2DM with CHD remains unclear.
Aim This study aimed to investigate the relationship between serum Sestrin2 levels and CHD in patients with type 2 diabetes. Methods A total of 70 T2DM patients with CHD and 69 T2DM patients were enrolled in this study. Clinical features and metabolic indices were identified. Serum Sestrin2 was measured by ELISA. Results Serum Sestrin2 levels in T2DM-CHD groups were significantly lower compared with the T2DM group (11.17 (9.79, 13.14) ng/mL vs 9.46 (8.34, 10.91) ng/mL). Bivariate correlation analysis revealed that serum Sestrin2 levels were negatively correlated with age (r = − 0.256, P = 0.002), BMI (r = − 0.206, P = 0.015), FBG (r = − 0.261, P = 0.002) and Tyg index (r = − 0.207, P < 0.014). Binary logistic regression suggested that low serum Sestrin2 levels were related to the increased risk of T2DM-CHD (P < 0.05). In addition, the receiver operating characteristic analysis revealed that the area under the curve of Sestrin2 was 0.724 (95% CI 0.641–0.808, P < 0.001) to predict T2DM-CHD patients (P < 0.001). Conclusion The Sestrin2 levels were highly associated with CHD in diabetes patients. Serum Sestrin2 may be involved in the occurrence and development of diabetic with CHD.
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10
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Mahjoob G, Ahmadi Y, Fatima rajani H, khanbabaei N, Abolhasani S. Circulating microRNAs as predictive biomarkers of coronary artery diseases in type 2 diabetes patients. J Clin Lab Anal 2022; 36:e24380. [PMID: 35349731 PMCID: PMC9102494 DOI: 10.1002/jcla.24380] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2022] [Revised: 03/16/2022] [Accepted: 03/17/2022] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) is an increasing metabolic disorder mostly resulting from unhealthy lifestyles. T2DM patients are prone to develop heart conditions such as coronary artery disease (CAD) which is a major cause of death in the world. Most clinical symptoms emerge at the advanced stages of CAD; therefore, establishing new biomarkers detectable in the early stages of the disease is crucial to enhance the efficiency of treatment. Recently, a significant body of evidence has shown alteration in miRNA levels associate with dysregulated gene expression occurring in T2DM and CAD, highlighting significance of circulating miRNAs in early detection of CAD arising from T2DM. Therefore, it seems crucial to establish a link between the miRNAs prognosing value and development of CAD in T2DM. AIM This study provides an overview on the alterations of the circulatory miRNAs in T2DM and various CADs and consider the potentials of miRNAs as biomarkers prognosing CADs in T2DM patients. MATERIALS AND METHODS Literature search was conducted for miRNAs involved in development of T2DM and CAD using the following key words: "miRNAs", "Biomarker", "Diabetes Mellitus Type 2 (T2DM)", "coronary artery diseases (CAD)". Articles written in the English language. RESULT There has been shown a rise in miR-375, miR-9, miR-30a-5p, miR-150, miR-9, miR-29a, miR-30d, miR-34a, miR-124a, miR-146a, miR-27a, and miR-320a in T2DM; whereas, miR-126, miR-21, miR-103, miR-28-3p, miR-15a, miR-145, miR-375, miR-223 have been shown to decrease. In addition to T2DM, some miRNAs such as mirR-1, miR-122, miR-132, and miR-133 play a part in development of subclinical aortic atherosclerosis associated with metabolic syndrome. Some miRNAs increase in both T2DM and CAD such as miR-1, miR-132, miR-133, and miR-373-3-p. More interestingly, some of these miRNAs such as miR-92a elevate years before emerging CAD in T2DM. CONCLUSION dysregulation of miRNAs plays outstanding roles in development of T2DM and CAD. Also, elevation of some miRNAs such as miR-92a in T2DM patients can efficiently prognose development of CAD in these patients, so these miRNAs can be used as biomarkers in this regard.
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Affiliation(s)
- Golnoosh Mahjoob
- Department of Clinical BiochemistrySarab Faculty of Medical Sciences.SarabIran
- Department of Clinical BiochemistryTarbiat Modares UniversityTehranIran
| | - Yasin Ahmadi
- Department of Medical Laboratory SciencesCollege of ScienceKomar University of Science and TechnologySulaimaniIraq
| | - Huda Fatima rajani
- Department of medical biotechnologySchool of advanced sciences in medicineTehran University of medical sciencesTehranIran
| | - Nafiseh khanbabaei
- Department of Clinical BiochemistrySarab Faculty of Medical Sciences.SarabIran
- Department of Clinical BiochemistryTarbiat Modares UniversityTehranIran
| | - Sakhavat Abolhasani
- Department of Clinical BiochemistrySarab Faculty of Medical Sciences.SarabIran
- Department of Clinical BiochemistryTarbiat Modares UniversityTehranIran
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Chrishtop VV, Prilepskii AY, Nikonorova VG, Mironov VA. Nanosafety vs. nanotoxicology: adequate animal models for testing in vivo toxicity of nanoparticles. Toxicology 2021; 462:152952. [PMID: 34543703 DOI: 10.1016/j.tox.2021.152952] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2021] [Revised: 09/10/2021] [Accepted: 09/11/2021] [Indexed: 11/20/2022]
Abstract
Nanotoxicological studies using existing models of normal cells and animals often encounter a paradox: retention of nanoparticles in intracellular compartments for a long time is not accompanied by any significant toxicological effects. Can we expect that the revealed changes will be not harmful after translation to practice, outside of a sterile laboratory and ideally healthy organisms? Age-associated and pathological processes can affect target organs, metabolism, and detoxification in the mononuclear phagocyte system organs and change biodistribution routes, thus making the use of nanomaterial not safe. The potential solution to this issue can be testing the toxic properties of nanoparticles in animal models with chronic diseases. However, current studies of nanotoxicity in animal models with a brain, cardiovascular system, liver, digestive tract, reproductive system, and skin diseases are unsystematic. Even though these studies demonstrate the emergence of new toxic effects that are not present in healthy animals. In this regard, we set the goal of this review as the formulation of the requirements for an animal model capable of assessing the potential toxicity of nanoparticles based on the nanosafety approach.
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