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Gao X, Su Q, Pan H, You Y, Ruan Z, Wu Y, Tang Z, Hu L. Arsenic-Induced Ferroptosis in Chicken Hepatocytes via the Mitochondrial ROS Pathway. Biol Trace Elem Res 2024; 202:4180-4190. [PMID: 38102534 DOI: 10.1007/s12011-023-03968-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/17/2023] [Accepted: 11/16/2023] [Indexed: 12/17/2023]
Abstract
Arsenic has been shown to be highly toxic and can cause liver damage. Previous studies have shown that arsenic causes severe liver damage and induces accumulation of reactive oxygen species (ROS). This study aimed to investigate the effects of ferroptosis on the liver in arsenic trioxide (ATO) and to explore the underlying mechanisms. We confirmed the hepatotoxic effects of arsenic by in vivo and in vitro experiments. After 28 days of administration of arsenic trioxide (4-mg/kg, 8-mg/kg) by gavage, chickens exhibited body weight loss and liver damage in a dose-dependent manner. In addition, in vivo and in vitro western blot and real-time fluorescence quantitative PCR analyses simultaneously indicated that ferroptosis might be the main pathway of arsenic-induced liver injury. Finally, Mito-TEMPO effectively eliminated the ROS accumulation in mitochondria, significantly attenuating the process of cellular ferroptosis. In summary, the hepatotoxic effects of arsenic are related to ferroptosis, and the hepatic ferroptosis process of arsenic is regulated by mitochondrial ROS (MtROS). Our study reveals new mechanisms of arsenic toxicity to the liver, which may deepen our understanding of arsenic toxicology.
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Affiliation(s)
- Xinglin Gao
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China
| | - Qian Su
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China
| | - Hang Pan
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China
| | - Yanli You
- College of Life Science, Yantai University, Yantai City, 264005, Shandong Province, China
| | - Zhiyan Ruan
- School of Pharmacy, Guangdong Food & Drug Vocational College, No. 321, Longdong North Road, Tianhe District, Guangzhou, 510520, Guangdong Province, People's Republic of China
| | - Yuhan Wu
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China
| | - Zhaoxin Tang
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China
| | - Lianmei Hu
- College of Veterinary Medicine, South China Agricultural University, Guangzhou, 510642, China.
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2
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Shokat S, Iqbal R, Riaz S, Yaqub A. Association Between Arsenic Toxicity, AS3MT Gene Polymorphism and Onset of Type 2 Diabetes. Biol Trace Elem Res 2024; 202:1550-1558. [PMID: 37889428 DOI: 10.1007/s12011-023-03919-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 10/13/2023] [Indexed: 10/28/2023]
Abstract
Arsenic (As) exposure in drinking water has become a serious public health issue. AS3MT gene is involved in the metabolism of arsenic, so a single nucleotide polymorphism in this gene may lead to the development of type 2 diabetes in arsenic-exposed areas. This study aimed to evaluate the association of the AS3MT gene with the development of type 2 diabetes in highly arsenic-exposed areas of Punjab, Pakistan. Total 200 samples equal in number from high arsenic exposed-areas of Lahore (Nishtar) and Kasur (Mustafa Abad) were collected. rs11191439 was utilized as an influential variable to evaluate the association between arsenic metabolism and diabetes status to find a single nucleotide polymorphism in the AS3MT gene. We observed the arsenic level in drinking water of the arsenic-exposed selected areas 115.54 ± 1.23 µg/L and 96.88 ± 0.48 µg/L, respectively. The As level in the urine of diabetics (98.54 ± 2.63 µg/L and 56.38 ± 12.66 µg/L) was higher as compared to non-diabetics (77.58 ± 1.8 µg/L and 46.9 ± 8.95 µg/L) of both affected areas, respectively. Correspondingly, the As level in the blood of diabetics (6.48 ± 0.08 µg/L and 5.49 ± 1.43 µg/L) and non-diabetics (6.22 ± 0.12 µg/L and 5.26 ± 0.24 µg/L) in the affected areas. Genotyping showed significant differences in the frequencies of alleles among cases and controls. Nevertheless, notable disparities in genotype distribution were observed in SNPs rs11191439 (T/C) (P < 0.05) and when comparing T2D patients and non-diabetic control subjects. The AS3MT gene and clinical parameters show a significant association with the affected people with diabetes living in arsenic-exposed areas.
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Affiliation(s)
- Saima Shokat
- Department of Zoology, Government College University, Lahore, Pakistan.
| | - Riffat Iqbal
- Department of Zoology, Government College University, Lahore, Pakistan
| | - Samreen Riaz
- Institute of Microbiology and Molecular Genetics, University of the Punjab, Lahore, Pakistan
| | - Atif Yaqub
- Department of Zoology, Government College University, Lahore, Pakistan
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3
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Liu Y, Li W, Zhang J, Yan Y, Zhou Q, Liu Q, Guan Y, Zhao Z, An J, Cheng X, He M. Associations of arsenic exposure and arsenic metabolism with the risk of non-alcoholic fatty liver disease. Int J Hyg Environ Health 2024; 257:114342. [PMID: 38401403 DOI: 10.1016/j.ijheh.2024.114342] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2023] [Revised: 01/29/2024] [Accepted: 02/20/2024] [Indexed: 02/26/2024]
Abstract
Growing evidences supported that arsenic exposure contributes to non-alcoholic fatty liver disease (NAFLD) risk, but findings were still inconsistent. Additionally, once absorbed, arsenic is methylated into monomethyl and dimethyl arsenicals. However, no studies investigated the association of arsenic metabolism with NAFLD. Our objectives were to evaluate the associations of arsenic exposure and arsenic metabolism with NAFLD prevalence. We conducted a case-control study with 1790 participants derived from Dongfeng-Tongji cohort and measured arsenic species (arsenite, arsenate, monomethylarsonate [MMA], dimethylarsinate [DMA], and arsenobetaine) in urine. Arsenic exposure (∑As) was defined as the sum of inorganic arsenic (iAs), MMA, and DMA. Arsenic metabolism was evaluated as the proportions of inorganic-related species (iAs%, MMA%, and DMA%) and methylation efficiency ratios (primary methylation index [PMI], secondary methylation index [SMI]). NAFLD was diagnosed by liver ultrasound. Logistic regression was used to evaluate the associations. The median of ∑As was 13.24 μg/g creatinine. The ∑As showed positive and nonlinear association with moderate/severe NAFLD (OR: per log-SD = 1.33, 95% CI: [1.03,1.71]; Pfor nonlinearity = 0.021). The iAs% (OR: per SD = 1.16, 95% CI: [1.03,1.30]) and SMI (OR: per log-SD = 1.16, 95% CI: [1.03,1.31]) showed positive while MMA% (OR: per SD = 0.80, 95% CI: [0.70,0.91]) and PMI (OR: per log-SD = 0.86, 95% CI: [0.77,0.96]) showed inverse associations with NAFLD. Moreover, the ORs (95% CI) of NAFLD for each 5% increase in iAs% was 1.36 (1.17,1.58) when MMA% decreased and 1.07 (1.01,1.13) when DMA% decreased; and for each 5% increase in MMA%, it was 0.74 (0.63,0.86) and 0.79 (0.69,0.91) when iAs% and DMA% decreased, respectively. The results suggest that inorganic arsenic exposure is positively associated with NAFLD risk and arsenic methylation efficiency plays a role in the NAFLD. The findings provide clues to explore potential interventions for the prevention of NAFLD. Prospective studies are needed to validate our findings.
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Affiliation(s)
- Yuenan Liu
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Weiya Li
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jiazhen Zhang
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Yan Yan
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qihang Zhou
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Qianying Liu
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Youbin Guan
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Zhuoya Zhao
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Jun An
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Xu Cheng
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China
| | - Meian He
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan 430030, China.
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Liu Q, Liu Y, Zhang J, Guan Y, Zhou Q, Yan Y, Li W, An J, He M. Gut microbiota deficiency aggravates arsenic-induced toxicity by affecting bioaccumulation and biotransformation in C57BL/6J mice. Food Chem Toxicol 2024; 186:114564. [PMID: 38438009 DOI: 10.1016/j.fct.2024.114564] [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: 01/15/2024] [Revised: 02/20/2024] [Accepted: 03/01/2024] [Indexed: 03/06/2024]
Abstract
Gut microbiome can influence the arsenic metabolism in mammals. Confusingly, gut microbiome was found to both mitigate and exacerbate arsenic toxicity. In this study, the role of gut microbiota in arsenic bioaccumulation, biotransformation, and organ toxicity in C57BL/6J mice was investigated. Gut microbiota deficiency model was established by antibiotics (Ab) cocktail AVNM. Conventional and gut microbiota deficiency mice were exposed to NaAsO2 for 4 weeks. Comparing with Ab-treated mice, the total arsenic (tAs) in the tissues was significantly reduced in conventional mice, which was opposed to the results of those in feces. Interestingly, dimethyl arsenite (DMA) was the most abundant metabolite in the feces of Ab-treated mice, while arsenic acid (AsV) had the highest proportion in the feces of conventional mice with approximately 16-fold than that in Ab-treated mice, indicating the critical role of gut microbiota in metabolizing arsenious acid (AsIII) to AsV. Additionally, the liver and kidney in Ab-treated mice showed more severe pathological changes and apoptosis. The significant increased level of ionized calcium-binding adapter molecule 1 (IBA-1) was also found in the brains of Ab-treated mice. Our results indicated that gut microbiota protected the host from arsenic-induced toxicity in liver, kidney, and brain by reducing the arsenic accumulation.
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Affiliation(s)
- Qianying Liu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yuenan Liu
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jiazhen Zhang
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Youbing Guan
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Qihang Zhou
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Yan Yan
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Weiya Li
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Jun An
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Meian He
- Department of Occupational and Environmental Health and State Key Laboratory of Environmental Health for Incubating, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China.
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Rosendo GBO, Ferreira RLU, Aquino SLS, Barbosa F, Pedrosa LFC. Glycemic Changes Related to Arsenic Exposure: An Overview of Animal and Human Studies. Nutrients 2024; 16:665. [PMID: 38474793 DOI: 10.3390/nu16050665] [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: 09/03/2023] [Revised: 10/18/2023] [Accepted: 10/26/2023] [Indexed: 03/14/2024] Open
Abstract
BACKGROUND Arsenic (As) is a risk factor associated with glycemic alterations. However, the mechanisms of action and metabolic aspects associated with changes in glycemic profiles have not yet been completely elucidated. Therefore, in this review, we aimed to investigate the metabolic aspects of As and its mechanism of action associated with glycemic changes. METHODS We searched the PubMed (MEDLINE) and Google Scholar databases for relevant articles published in English. A combination of free text and medical subject heading keywords and search terms was used to construct search equations. The search yielded 466 articles; however, only 50 were included in the review. RESULTS We observed that the relationship between As exposure and glycemic alterations in humans may be associated with sex, smoking status, body mass index, age, occupation, and genetic factors. The main mechanisms of action associated with changes induced by exposure to As in the glycemic profile identified in animals are increased oxidative stress, reduced expression of glucose transporter type 4, induction of inflammatory factor expression and dysfunction of pancreatic β cells. CONCLUSIONS Therefore, As exposure may be associated with glycemic alterations according to inter-individual differences.
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Affiliation(s)
| | | | - Séphora Louyse Silva Aquino
- Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Natal 59012-570, RN, Brazil
| | - Fernando Barbosa
- Department of Clinical Analyses, Toxicology and Food Sciences, School of Pharmaceutical Sciences of Ribeirão Preto, University of São Paulo, Ribeirão Preto 14040-903, SP, Brazil
| | - Lucia Fatima Campos Pedrosa
- Postgraduate Program in Health Sciences, Federal University of Rio Grande do Norte, Natal 59012-570, RN, Brazil
- Department of Nutrition, Federal University of Rio Grande do Norte, Natal 59078-970, RN, Brazil
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Ji S, Qu Y, Sun Q, Zhao F, Qiu Y, Li Z, Li Y, Song H, Zhang M, Zhang W, Fu H, Cai J, Zhang Z, Zhu Y, Cao Z, Lv Y, Shi X. Mediating Role of Liver Dysfunction in the Association between Arsenic Exposure and Diabetes in Chinese Adults: A Nationwide Cross-Sectional Study of China National Human Biomonitoring (CNHBM) 2017-2018. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2024; 58:2693-2703. [PMID: 38285630 DOI: 10.1021/acs.est.3c08718] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/31/2024]
Abstract
Inconsistent results have been reported regarding the association between low-to-moderate arsenic (As) exposure and diabetes. The effect of liver dysfunction on As-induced diabetes remains unclear. The cross-sectional study included 10,574 adults from 2017-2018 China National Human Biomonitoring. Urinary total As (TAs) levels were analyzed as markers of As exposure. Generalized linear mixed models and restricted cubic splines models were used to examine the relationships among TAs levels, serum alanine aminotransferase (ALT) and aspartate aminotransferase (AST) concentrations, and diabetes prevalence. Mediating analysis was performed to assess whether liver dysfunction mediated the association between TAs and diabetes. Overall, the OR (95% CI) of diabetes in participants in the second, third, and fourth quartiles of TAs were 1.08 (0.88, 1.33), 1.17 (0.94, 1.45), and 1.52 (1.22, 1.90), respectively, in the fully adjusted models compared with those in the lowest quartile. Serum ALT was positively associated with TAs and diabetes. Additionally, mediation analyses showed that ALT mediated 4.32% of the association between TAs and diabetes in the overall population and 8.86% in the population without alcohol consumption in the past year. This study suggested that alleviating the hepatotoxicity of As could have implications for both diabetes and liver disease.
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Affiliation(s)
- Saisai Ji
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- Department of Occupational and Environmental Health Sciences, School of Public Health, Peking University, Beijing 100191, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yingli Qu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Qi Sun
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Feng Zhao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yidan Qiu
- Department of Big Data in Health Science, School of Public Health, Zhejiang University, Hangzhou 310058, China
| | - Zheng Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yawei Li
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Haocan Song
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Miao Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Wenli Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Hui Fu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Jiayi Cai
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhuona Zhang
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Ying Zhu
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Zhaojin Cao
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
| | - Yuebin Lv
- China CDC Key Laboratory of Environment and Population Health, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, 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 100021, China
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, National Institute of Environmental Health, Chinese Center for Disease Control and Prevention, Beijing 100021, China
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Li W, Li Z, Yan Y, Zhang J, Zhou Q, Wang R, He M. Association of urinary arsenic metabolism with type 2 diabetes and glucose homeostasis: Cross-sectional and longitudinal associations. ENVIRONMENTAL RESEARCH 2023; 239:117410. [PMID: 37858693 DOI: 10.1016/j.envres.2023.117410] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/20/2023] [Revised: 09/20/2023] [Accepted: 10/11/2023] [Indexed: 10/21/2023]
Abstract
BACKGROUND Previous researches have assessed the relationships of urinary arsenic metabolism with type 2 diabetes (T2D) and glucose-insulin homeostasis, but the results were controversial, and potential mechanisms remain largely unclear. OBJECTIVES This study aimed to investigate the cross-sectional and longitudinal associations of urinary arsenic metabolism with T2D prevalence and glucose changes in relatively higher arsenic exposure, and further to evaluate the underlying roles of oxidative damage in these relationships. METHODS We included 796 participants at baseline, among them 509 participants were followed up after 2 years. Logistic regression model and leave-one-out approach were applied to evaluate the associations of arsenic metabolism with T2D prevalence. Linear mixed model was conducted to estimate the relationship of arsenic metabolism with glycemic changes over two years. The associations between arsenic metabolism and indicators of oxidative stress were assessed with a linear regression model. We further performed mediation analysis to investigate the role of oxidative stress in the associations of arsenic metabolism with 2-year change of glucose levels. RESULTS Higher urinary MMA% increased T2D prevalence and baseline glucose levels. MMA% was positively associated with 2-year change of glucose levels. Moreover, we observed significant dose-response relationship between MMA% and 8-hydroxy-2-deoxyguanosine (8-OHdG). However, the mediating role of 8-OHdG in the association of MMA% and 2-year change of glucose levels was not observed in this population. CONCLUSIONS In this population exposure to relatively higher arsenic levels, higher MMA% contributed to increased T2D prevalence and glucose homeostasis disorder. Arsenic metabolism also affected oxidative stress levels, especially 8-OHdG. Further studies are required to investigate the potential mechanisms.
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Affiliation(s)
- Weiya Li
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zhaoyang Li
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yan Yan
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Jiazhen Zhang
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Qihang Zhou
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ruixin Wang
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Meian He
- Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Liu Q, Lei Z. The Role of microRNAs in Arsenic-Induced Human Diseases: A Review. JOURNAL OF AGRICULTURAL AND FOOD CHEMISTRY 2023. [PMID: 37930083 DOI: 10.1021/acs.jafc.3c03721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2023]
Abstract
MicroRNAs (miRNAs) are noncoding RNAs with 20-22 nucleotides, which are encoded by endogenous genes and are capable of targeting the majority of human mRNAs. Arsenic is regarded as a human carcinogen, which can lead to many adverse health effects including diabetes, skin lesions, kidney disease, neurological impairment, male reproductive injury, and cardiovascular disease (CVD) such as cardiac arrhythmias, ischemic heart failure, and endothelial dysfunction. miRNAs can act as tumor suppressors and oncogenes via directly targeting oncogenes or tumor suppressors. Recently, miRNA dysregulation was considered to be an important mechanism of arsenic-induced human diseases and a potential biomarker to predict the diseases caused by arsenic exposure. Endogenic miRNAs such as miR-21, the miR-200 family, miR-155, and the let-7 family are involved in arsenic-induced human disease by inducing translational repression or RNA degradation and influencing multiple pathways, including mTOR/Arg 1, HIF-1α/VEGF, AKT, c-Myc, MAPK, Wnt, and PI3K pathways. Additionally, exogenous miRNAs derived from plants, such as miR-34a, miR-159, miR-2911, miR-159a, miR-156c, miR-168, etc., among others, can be transported from blood to specific tissue/organ systems in vivo. These exogenous miRNAs might be critical players in the treatment of human diseases by regulating host gene expression. This review summarizes the regulatory mechanisms of miRNAs in arsenic-induced human diseases, including cancers, CVD, and other human diseases. These special miRNAs could serve as potential biomarkers in the management and treatment of human diseases linked to arsenic exposure. Finally, the protective action of exogenous miRNAs, including antitumor, anti-inflammatory, anti-CVD, antioxidant stress, and antivirus are described.
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Affiliation(s)
- Qianying Liu
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
| | - Zhiqun Lei
- School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, 430030, China
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Ortiz-Garcia NY, Cipriano Ramírez AI, Juarez K, Brand Galindo J, Briceño G, Calderon Martinez E. Maternal Exposure to Arsenic and Its Impact on Maternal and Fetal Health: A Review. Cureus 2023; 15:e49177. [PMID: 38130554 PMCID: PMC10734558 DOI: 10.7759/cureus.49177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/20/2023] [Indexed: 12/23/2023] Open
Abstract
Arsenic exposure is a significant public health issue, with harmful effects caused by its use in commercial products such as car batteries, pesticides, and herbicides. Arsenic has three main compounds: inorganic, organic, and arsine gas. Inorganic arsenic compounds in water are highly toxic. The daily intake of arsenic from food and beverages is between 20 and 300 mcg/day. Arsenic is known for its carcinogenic properties and is classified as a human carcinogen by different institutions. Exposure can lead to oxidative stress, DNA damage, and epigenetic deregulation, which can cause endocrine disorders, altered signal transduction pathways, and cell proliferation. In addition, arsenic can easily cross the placenta, making it a critical concern for maternal and fetal health. Exposure can lead to complications such as gestational diabetes, anemia, low birth weight, miscarriage, and congenital anomalies. Female babies are particularly vulnerable to the negative impact of arsenic exposure, with a higher risk of low weight for gestational age and congenital cardiac anomalies. Therefore, it is crucial to monitor and regulate the levels of arsenic in drinking water and food sources to prevent these adverse health outcomes. Further research is necessary to fully understand the impact of arsenic exposure on human health, especially during pregnancy and infancy, by implementing preventative measures and monitoring the levels of arsenic in the environment.
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Affiliation(s)
| | | | - Karen Juarez
- Infectious Disease, Universidad Nacional Autónoma de México (UNAM), Mexico City, MEX
| | | | - Gabriela Briceño
- Obstetrics and Gynecology, Universidad de Oriente, Barcelona, VEN
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Eikelboom M, Wang Y, Portlock G, Gourain A, Gardner J, Bullen J, Lewtas P, Carriere M, Alvarez A, Kumar A, O'Prey S, Tölgyes T, Omanović D, Bhowmick S, Weiss D, Salaun P. Voltammetric determination of inorganic arsenic in mildly acidified (pH 4.7) groundwaters from Mexico and India. Anal Chim Acta 2023; 1276:341589. [PMID: 37573093 DOI: 10.1016/j.aca.2023.341589] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 06/19/2023] [Accepted: 07/04/2023] [Indexed: 08/14/2023]
Abstract
Routine monitoring of inorganic arsenic in groundwater using sensitive, reliable, easy-to-use and affordable analytical methods is integral to identifying sources, and delivering appropriate remediation solutions, to the widespread global issue of arsenic pollution. Voltammetry has many advantages over other analytical techniques, but the low electroactivity of arsenic(V) requires the use of either reducing agents or relatively strong acidic conditions, which both complicate the analytical procedures, and require more complex material handling by skilled operators. Here, we present the voltammetric determination of total inorganic arsenic in conditions of near-neutral pH using a new commercially available 25 μm diameter gold microwire (called the Gold Wirebond), which is described here for the first time. The method is based on the addition of low concentrations of permanganate (10 μM MnO4-) which fulfils two roles: (1) to ensure that all inorganic arsenic is present as arsenate by chemically oxidising arsenite to arsenate and, (2) to provide a source of manganese allowing the sensitive detection of arsenate by anodic stripping voltammetry at a gold electrode. Tests were carried out in synthetic solutions of various pH (ranging from 4.7 to 9) in presence/absence of chloride. The best response was obtained in 0.25 M chloride-containing acetate buffer resulting in analytical parameters (limit of detection of 0.28 μg L-1 for 10 s deposition time, linear range up to 20 μg L-1 and a sensitivity of 63.5 nA ppb-1. s-1) better than those obtained in acidic conditions. We used this new method to measure arsenic concentrations in contrasting groundwaters: the reducing, arsenite-rich groundwaters of India (West Bengal and Bihar regions) and the oxidising, arsenate-rich groundwaters of Mexico (Guanajuato region). Very good agreement was obtained in all groundwaters with arsenic concentrations measured by inductively coupled plasma-mass spectrometry (slope = +1.029, R2 = 0.99). The voltammetric method is sensitive, faster than other voltammetric techniques for detection of arsenic (typically 10 min per sample including triplicate measurements and 2 standard additions), easier to implement than previous methods (no acidic conditions, no chemical reduction required, reproducible sensor, can be used by non-voltammetric experts) and could enable cheaper groundwater surveying campaigns with in-the-field analysis for quick data reporting, even in remote communities.
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Affiliation(s)
- Martijn Eikelboom
- School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, L69 3GP, Liverpool, UK.
| | - Yaxuan Wang
- School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, L69 3GP, Liverpool, UK
| | - Gemma Portlock
- School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, L69 3GP, Liverpool, UK
| | - Arthur Gourain
- School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, L69 3GP, Liverpool, UK
| | - Joseph Gardner
- School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, L69 3GP, Liverpool, UK
| | - Jay Bullen
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Paul Lewtas
- School of Science, Edith Cowan University, 270 Joondalup Drive, Joondalup, Western Australia, 6027, Australia
| | - Matthieu Carriere
- Caminos de Agua, José María Correa 23A, Colonia Santa Cecilia, 37727, San Miguel de Allende, Gto, Mexico
| | - Alexandra Alvarez
- Caminos de Agua, José María Correa 23A, Colonia Santa Cecilia, 37727, San Miguel de Allende, Gto, Mexico
| | - Arun Kumar
- Mahavir Cancer Sansthan and Research Centre, Phulwarisharif, Patna, 801505, Bihar, India
| | | | | | - Dario Omanović
- Division for Marine and Environmental Research, Ruđer Bošković Institute, Bijenička 54, 10000, Zagreb, Croatia
| | - Subhamoy Bhowmick
- Kolkata Zonal Center CSIR-National Environmental Engineering Research Institute (NEERI), Kolkata, West Bengal, 700107, India
| | - Dominik Weiss
- Department of Earth Science and Engineering, Imperial College London, South Kensington Campus, London, SW7 2AZ, UK
| | - Pascal Salaun
- School of Environmental Sciences, University of Liverpool, 4 Brownlow Street, L69 3GP, Liverpool, UK.
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Islam J, Islam Z, Haque N, Khatun M, Islam F, Hossain S, Hoque MA, Nikkon F, Hossain K, Saud ZA. Fenugreek seed powder protects mice against arsenic-induced neurobehavioral changes. Curr Res Toxicol 2023; 5:100114. [PMID: 37554151 PMCID: PMC10404539 DOI: 10.1016/j.crtox.2023.100114] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Revised: 07/09/2023] [Accepted: 07/11/2023] [Indexed: 08/10/2023] Open
Abstract
The current study was designed to evaluate the protective effect of fenugreek seed powder against As-induced neurobehavioral and biochemical perturbations using a mouse model. Mice exposed to arsenic at 10 mg/kg body weight showed development of anxiety-like behavior and memory impairment compared to control mice in elevated plus maze and Morris water maze tests, respectively. A significantly decreased acetyl and butyrylcholinesterase, superoxide dismutase and glutathione reductase activities and brain-derived neurotrophic factor levels were found in the brain of arsenic-exposed mice compared to control mice. Interestingly, supplementation of fenugreek seed powder to arsenic-treated mice significantly restored the activity of cholinesterase and antioxidant enzymes (e.g. superoxide dismutase, glutathione reductase) as well as brain-derived neurotrophic factor levels in the brain tissue of arsenic-exposed mice. Consequently, reduced anxiety-like behavior, improved learning and memory were observed in fenugreek supplemented arsenic treated mice compared to only arsenic-exposed mice group. Thus, this study suggests that fenugreek seed powder reduces arsenic-induced neurotoxicity in mice.
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Affiliation(s)
| | | | - Nazmul Haque
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Moriom Khatun
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Farhadul Islam
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Shakhawoat Hossain
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Md Ashraful Hoque
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Farjana Nikkon
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Khaled Hossain
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
| | - Zahangir Alam Saud
- Department of Biochemistry and Molecular Biology, University of Rajshahi, Rajshahi 6205, Bangladesh
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Weiss MC, Shih YH, Bryan MS, Jackson BP, Aguilar D, Brown EL, Jun G, Hanis CL, Argos M, Sargis RM. Arsenic metabolism, diabetes prevalence, and insulin resistance among Mexican Americans: A mendelian randomization approach. ENVIRONMENTAL ADVANCES 2023; 12:100361. [PMID: 37426694 PMCID: PMC10328543 DOI: 10.1016/j.envadv.2023.100361] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 07/11/2023]
Abstract
Background Differences in arsenic metabolism capacity may influence risk for type 2 diabetes, but the mechanistic drivers are unclear. We evaluated the associations between arsenic metabolism with overall diabetes prevalence and with static and dynamic measures of insulin resistance among Mexican Americans living in Starr County, Texas. Methods We utilized data from cross-sectional studies conducted in Starr County, Texas, from 2010-2014. A Mendelian randomization approach was utilized to evaluate the associations between arsenic metabolism and type 2 diabetes prevalence using the intronic variant in the arsenic methylating gene, rs9527, as the instrumental variable for arsenic metabolism. To further assess mechanisms for diabetes pathogenesis, proportions of the urinary arsenic metabolites were employed to assess the association between arsenic metabolism and insulin resistance among participants without diabetes. Urinary biomarkers of arsenic metabolites were modeled as individual proportions of the total. Arsenic metabolism was evaluated both with a static outcome of insulin resistance, homeostatic measure of assessment (HOMA-IR), and a dynamic measure of insulin sensitivity, Matsuda Index. Results Among 475 Mexican American participants from Starr County, higher metabolism capacity for arsenic is associated with higher diabetes prevalence driven by worse insulin resistance. Presence of the minor T allele of rs9527 is independently associated with an increase in the proportion of monomethylated arsenic (MMA%) and is associated with an odds ratio of 0.50 (95% CI: 0.24, 0.90) for type 2 diabetes. This association was conserved after potential covariate adjustment. Furthermore, among participants without type 2 diabetes, the highest quartile of MMA% was associated with 22% (95% CI: -33.5%, -9.07%) lower HOMA-IR and 56% (95% CI: 28.3%, 91.3%) higher Matsuda Index for insulin sensitivity. Conclusions Arsenic metabolism capacity, indicated by a lower proportion of monomethylated arsenic, is associated with increased diabetes prevalence driven by an insulin resistant phenotype among Mexican Americans living in Starr County, Texas.
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Affiliation(s)
- Margaret C. Weiss
- School of Public Health, University of Illinois at Chicago, Chicago, IL, United States of America
- College of Medicine, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Yu-Hsuan Shih
- School of Public Health, University of Illinois at Chicago, Chicago, IL, United States of America
| | - Molly Scannell Bryan
- Institute for Minority Health Research, University of Illinois at Chicago, United States of America
- Center for Infectious Disease, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Brian P. Jackson
- Department of Earth Sciences, Dartmouth College, Hanover, NH, United States of America
| | - David Aguilar
- Division of Cardiovascular Medicine, LSU Health School of Medicine, New Orleans, LA, United States
| | - Eric L. Brown
- Center for Infectious Disease, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Goo Jun
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Craig L. Hanis
- Human Genetics Center, University of Texas Health Science Center at Houston, Houston, TX, United States
| | - Maria Argos
- School of Public Health, University of Illinois at Chicago, Chicago, IL, United States of America
- Chicago Center for Health and Environment, Chicago, IL, United States of America
| | - Robert M. Sargis
- College of Medicine, University of Illinois at Chicago, Chicago, IL, United States of America
- Chicago Center for Health and Environment, Chicago, IL, United States of America
- Section of Endocrinology, Diabetes, and Metabolism, Jesse Brown Veterans Affairs Medical Center, Chicago, IL, United States of America
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Liang X, Guo G, Wang Y, Wang M, Chen X, Zhang J, Li S, Liu L, Huang Q, Cui B, Zhang M, Sun G, Tang N, Zhang X, Zhang Q. Arsenic metabolism, N6AMT1 and AS3MT single nucleotide polymorphisms, and their interaction on gestational diabetes mellitus in Chinese pregnant women. ENVIRONMENTAL RESEARCH 2023; 221:115331. [PMID: 36681142 DOI: 10.1016/j.envres.2023.115331] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/16/2022] [Revised: 01/16/2023] [Accepted: 01/18/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND Single nucleotide polymorphisms (SNPs) in N6AMT1 and AS3MT are associated with arsenic (As) metabolism, and efficient As methylation capacity has been associated with diabetes. However, little is known about the gene-As interaction on gestational diabetes mellitus (GDM). OBJECTIVE This study aimed to explore the individual and combined effects of N6AMT1 and AS3MT SNPs with As metabolism on GDM. METHODS A cross-sectional study was performed among 385 Chinese pregnant women (86 GDM and 299 Non-GDM). Four SNPs in N6AMT1 (rs1997605 and rs1003671) and AS3MT (rs1046778 and rs11191453) were genotyped. Urinary inorganic arsenic (iAs), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) were determined, and the percentages of As species (iAs%, MMA%, and DMA%) were calculated to assess the efficiency of As metabolism. RESULTS Pregnant women with N6AMT1 rs1997605 AA genotype had lower iAs% (B: 2.11; 95% CI: 4.08, -0.13) and MMA% (B: 0.21; 95% CI: 0.39, -0.04) than pregnant women with GG genotype. The AS3MT rs1046778 and rs11191453 C alleles were negatively associated with iAs% and MMA% but positively associated with DMA%. Higher urinary MMA% was significantly associated with a lower risk of GDM (OR: 0.54; 95% CI: 0.30, 0.97). The A allele in N6AMT1 rs1997605 (OR: 0.46; 95% CI: 0.26, 0.79) was associated with a decreased risk of GDM. The additive interactions between N6AMT1 rs1997605 GG genotypes and lower iAs% (AP: 0.50; 95% CI: 0.01, 0.99) or higher DMA% (AP: 0.52; 95% CI: 0.04, 0.99) were statistically significant. Similar additive interactions were also found between N6AMT1 rs1003671 GG genotypes and lower iAs% or higher DMA%. CONCLUSIONS Genetic variants in N6AMT1 and efficient As metabolism (indicated by lower iAs% and higher DMA%) can interact to influence GDM occurrence synergistically in Chinese pregnant women.
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Affiliation(s)
- Xiaoshan Liang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Guanshuai Guo
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Yiyun Wang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Meng Wang
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Xi Chen
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Jingran Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Shuying Li
- Department of Endocrinology, Tianjin Xiqing Hospital, Tianjin, 300380, China
| | - Liangpo Liu
- School of Public Health, Shanxi Medical University, Taiyuan, 030001 China
| | - Qingyu Huang
- Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, 361021, China
| | - Bo Cui
- Institute of Environmental and Operational Medicine, Academy of Military Medical Sciences, Tianjin, 300050, China
| | - Ming Zhang
- Shenzhen Prevention and Treatment Center for Occupational Diseases, Shenzhen, 518020, China
| | - Guifan Sun
- Key Laboratory of Arsenic-related Biological Effects and Prevention and Treatment in Liaoning Province, School of Public Health, China Medical University, Shenyang, 110122, China
| | - Naijun Tang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Xumei Zhang
- Department of Nutrition and Food Science, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China
| | - Qiang Zhang
- Department of Occupational and Environmental Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China; Tianjin Key Laboratory of Environment, Nutrition and Public Health, School of Public Health, Tianjin Medical University, Tianjin, 300070, China.
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14
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Zhang Y, Huang B, Jin J, Xiao Y, Ying H. Recent advances in the application of ionomics in metabolic diseases. Front Nutr 2023; 9:1111933. [PMID: 36726817 PMCID: PMC9884710 DOI: 10.3389/fnut.2022.1111933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 12/30/2022] [Indexed: 01/19/2023] Open
Abstract
Trace elements and minerals play a significant role in human health and diseases. In recent years, ionomics has been rapidly and widely applied to explore the distribution, regulation, and crosstalk of different elements in various physiological and pathological processes. On the basis of multi-elemental analytical techniques and bioinformatics methods, it is possible to elucidate the relationship between the metabolism and homeostasis of diverse elements and common diseases. The current review aims to provide an overview of recent advances in the application of ionomics in metabolic disease research. We mainly focuses on the studies about ionomic or multi-elemental profiling of different biological samples for several major types of metabolic diseases, such as diabetes mellitus, obesity, and metabolic syndrome, which reveal distinct and dynamic patterns of ion contents and their potential benefits in the detection and prognosis of these illnesses. Accumulation of copper, selenium, and environmental toxic metals as well as deficiency of zinc and magnesium appear to be the most significant risk factors for the majority of metabolic diseases, suggesting that imbalance of these elements may be involved in the pathogenesis of these diseases. Moreover, each type of metabolic diseases has shown a relatively unique distribution of ions in biofluids and hair/nails from patients, which might serve as potential indicators for the respective disease. Overall, ionomics not only improves our understanding of the association between elemental dyshomeostasis and the development of metabolic disease but also assists in the identification of new potential diagnostic and prognostic markers in translational medicine.
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Affiliation(s)
- Yan Zhang
- Shenzhen Key Laboratory of Marine Bioresources and Ecology, Brain Disease and Big Data Research Institute, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China,Shenzhen-Hong Kong Institute of Brain Science-Shenzhen Fundamental Research Institutions, Shenzhen, China,*Correspondence: Yan Zhang ✉
| | - Biyan Huang
- Shenzhen Key Laboratory of Marine Bioresources and Ecology, Brain Disease and Big Data Research Institute, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Jiao Jin
- Shenzhen Key Laboratory of Marine Bioresources and Ecology, Brain Disease and Big Data Research Institute, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Yao Xiao
- Shenzhen Key Laboratory of Marine Bioresources and Ecology, Brain Disease and Big Data Research Institute, College of Life Sciences and Oceanography, Shenzhen University, Shenzhen, China
| | - Huimin Ying
- Affiliated Hangzhou Xixi Hospital, Zhejiang University School of Medicine, Hangzhou, China,Huimin Ying ✉
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