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Zhong J, Yang T, Wang Z, Zhang Y, Shen Y, Hu Y, Hong F. Associations between individual and mixed urinary metal exposure and dyslipidemia among Chinese adults: Data from the China Multi-Ethnic Cohort Study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 282:116696. [PMID: 38986334 DOI: 10.1016/j.ecoenv.2024.116696] [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: 04/07/2024] [Revised: 07/03/2024] [Accepted: 07/04/2024] [Indexed: 07/12/2024]
Abstract
The prevalence of dyslipidemia is increasing, and it has become a significant global public health concern. Some studies have demonstrated contradictory relationships between urinary metals and dyslipidemia, and the combined effects of mixed urinary metal exposure on dyslipidemia remain ambiguous. In this study, we examined how individual and combined urinary metal exposure are associated with the occurrence of dyslipidemia. According to the data from the 2018-2019 baseline survey database of the China Multi-Ethnic Cohort (CMEC) Study, a population of 9348 individuals was studied. Inductively coupled plasmamass spectrometry (ICP-MS) was used to measure 21 urinary metal concentrations in the collected adult urinary samples. The associations between urinary metals and dyslipidemia were analyzed by logistic regression, weighted quantile sum regression (WQS), and quantile-based g-computation (qgcomp), controlled for potential confounders to examine single and combined effects. Dyslipidemia was detected in 3231 individuals, which represented approximately 34.6 % of the total population. According to the single-exposure model, Al and Na were inversely associated with the risk of dyslipidemia (OR = 0.95, 95 % CI: 0.93, 0.98; OR = 0.89, 95 % CI: 0.83, 0.95, respectively), whereas Zn, Ca, and P were positively associated (OR = 1.69, 95 % CI: 1.42, 2.01; OR = 1.12, 95 % CI: 1.06, 1.18; OR = 1.21, 95 % CI: 1.09, 1.34, respectively). Moreover, Zn and P were significantly positively associated even after adjusting for these metals, whereas Al and Cr were negatively associated with the risk of dyslipidemia. The results of the WQS and qgcomp analyses showed that urinary metal mixtures were positively associated with the risk of dyslipidemia (OR = 1.26, 95 % CI: 1.15, 1.38; OR = 1.09, 95 % CI: 1.01, 1.19). This positive association was primarily driven by Zn, P, and Ca. In the sensitivity analyses with collinearity diagnosis, interaction, and stratified analysis, the results remained, confirming the reliability of the study findings. In this study, the individual and combined effects of urinary Zn, P, and Ca on dyslipidemia were determined, which provided novel insights into the link between exposure to metals and dyslipidemia.
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Affiliation(s)
- Jianqin Zhong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Tingting Yang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Ziyun Wang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Yuxin Zhang
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Yili Shen
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Yuxin Hu
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China
| | - Feng Hong
- School of Public Health, the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, No.6 Ankang Road, Guian New Area, Guizhou 561113, China.
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Li H, Cheng BJ, Yang PY, Wang C, Meng K, Li TL, Wang J, Liu R. Associations of Urinary Heavy Metal Mixtures with High Remnant Cholesterol among US Adults: Evidence from the National Health and Nutrition Examination Survey (1998-2018). TOXICS 2024; 12:430. [PMID: 38922110 PMCID: PMC11209470 DOI: 10.3390/toxics12060430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/15/2024] [Revised: 06/06/2024] [Accepted: 06/10/2024] [Indexed: 06/27/2024]
Abstract
The main objective of our study is to explore the associations between combined exposure to urinary heavy metals and high remnant cholesterol (HRC), a known cardiovascular risk factor. Utilizing data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2018, we conducted a cross-sectional analysis of 5690 participants, assessing urinary concentrations of ten heavy metals. Ten heavy metals in urine were measured by inductively coupled plasma mass spectrometry (ICP-MS). Fasting residual cholesterol ≥0.8 mmol/L was defined as HRC (using blood samples). Statistical analyses included weighted multivariable logistic regression, weighted quantile sum (WQS) regression, quantile g-computation (qgcomp), and Bayesian kernel machine regression (BKMR) to evaluate the associations of heavy metal exposure with HRC. Stratified analyses based on individual characteristics were also conducted. Multivariable logistic regression found that the four metals (OR Q4 vs. Q1: 1.33, 95% CI: 1.01-1.75 for barium (Ba); OR Q4 vs. Q1: 1.50, 95% CI: 1.16-1.94 for cadmium (Cd); OR Q4 vs. Q1: 1.52, 95% CI: 1.15-2.01 for mercury (Hg); OR Q4 vs. Q1: 1.35, 95% CI: 1.06-1.73 for lead (Pb)) were positively correlated with the elevated risk of HRC after adjusting for covariates. In addition, all three mixed models, including WQS (OR: 1.25; 95% CI: 1.07-1.46), qgcomp (OR: 1.17; 95% CI: 1.03-1.34), and BKMR, consistently showed a significant positive correlation between co-exposure to heavy metal mixtures and HRC, with Ba and Cd being the main contributors within the mixture. These associations were more pronounced in younger adults (20 to 59 years), males, and those with a higher body mass index status (≥25 kg/m2). Our findings reveal a significant relationship between exposure to the mixture of heavy metals and HRC among US adults, with Ba and Cd being the major contributors to the mixture's overall effect. Public health efforts aimed at reducing heavy metal exposure can help prevent HRC and, in turn, cardiovascular disease.
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Affiliation(s)
| | | | | | | | | | | | | | - Ran Liu
- Key Laboratory of Environmental Medicine Engineering, Ministry of Education, School of Public Health, Southeast University, Nanjing 210009, China; (H.L.); (B.-J.C.); (P.-Y.Y.); (C.W.); (K.M.); (T.-L.L.); (J.W.)
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Zhang Y, Gao Y, Liu QS, Zhou Q, Jiang G. Chemical contaminants in blood and their implications in chronic diseases. JOURNAL OF HAZARDOUS MATERIALS 2024; 466:133511. [PMID: 38262316 DOI: 10.1016/j.jhazmat.2024.133511] [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: 09/25/2023] [Revised: 12/27/2023] [Accepted: 01/10/2024] [Indexed: 01/25/2024]
Abstract
Artificial chemical products are widely used and ubiquitous worldwide and pose a threat to the environment and human health. Accumulating epidemiological and toxicological evidence has elucidated the contributions of environmental chemical contaminants to the incidence and development of chronic diseases that have a negative impact on quality of life or may be life-threatening. However, the pathways of exposure to these chemicals and their involvements in chronic diseases remain unclear. We comprehensively reviewed the research progress on the exposure risks of humans to environmental contaminants, their body burden as indicated by blood monitoring, and the correlation of blood chemical contaminants with chronic diseases. After entering the human body through various routes of exposure, environmental contaminants are transported to target organs through blood circulation. The application of the modern analytical techniques based on human plasma or serum specimens is promising for determining the body burden of environmental contaminants, including legacy persistent organic pollutants, emerging pollutants, and inorganic elements. Furthermore, their body burden, as indicated by blood monitoring correlates with the incidence and development of metabolic syndromes, cancers, chronic nervous system diseases, cardiovascular diseases, and reproductive disorders. On this basis, we highlight the urgent need for further research on environmental pollution causing health problems in humans.
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Affiliation(s)
- Yuzhu Zhang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Yurou Gao
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; Sino-Danish College, University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Qian S Liu
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China.
| | - Qunfang Zhou
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, PR China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, PR China
| | - Guibin Jiang
- State Key Laboratory of Environmental Chemistry and Ecotoxicology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, PR China; College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, PR China; School of Environment, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310000, PR China
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Moon SI, Yim DH, Choi K, Eom SY, Choi BS, Park JD, Kim H, Kim YD. Association Between Multiple Heavy Metal Exposures and Cholesterol Levels in Residents Living Near a Smelter Plant in Korea. J Korean Med Sci 2024; 39:e77. [PMID: 38442720 PMCID: PMC10911942 DOI: 10.3346/jkms.2024.39.e77] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 11/28/2023] [Indexed: 03/07/2024] Open
Abstract
BACKGROUND Considering the interactions between heavy metals, a comprehensive evaluation of the effects of exposure to various types of co-interacting heavy metals on health is required. This study assessed the association between dyslipidemia markers and blood mercury, lead, cadmium, iron, zinc, and nickel levels in residents of an abandoned refinery plant. METHODS A total of 972 individuals (exposed group: 567, control group: 405) living near the Janghang refinery plant in the Republic of Korea were included. Blood mercury, lead, cadmium, iron, zinc, nickel, cholesterol, and triglyceride levels were measured. The combined effect of the six heavy metals on dyslipidemia markers was evaluated using a Bayesian kernel machine regression (BKMR) model and compared with the results of a linear regression analysis. The BKMR model results were compared using a stratified analysis of the exposed and control groups. RESULTS In the BKMR model, the combined effect of the six heavy metals was significantly associated with total cholesterol (TC) levels both below the 45th percentile and above the 55th percentile in the total population. The combined effect range between the 25th and 75th percentiles of the six metals on TC levels was larger in the exposed group than that in the total population. In the control group, the combined effects of the changes in concentration of the six heavy metals on the TC concentration were not statistically significant. CONCLUSION These results suggest that the cholesterol levels of residents around the Janghang refinery plant may be elevated owing to exposure to multiple heavy metals.
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Affiliation(s)
- Sun-In Moon
- Chungbuk Environmental Health Center, Chungbuk National University Hospital, Cheongju, Korea
- Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Dong-Hyuk Yim
- Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Kyunghi Choi
- Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea
| | - Sang-Yong Eom
- Chungbuk Environmental Health Center, Chungbuk National University Hospital, Cheongju, Korea
- Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea
- Department of Office of Public Healthcare Service, Chungbuk National University Hospital, Cheongju, Korea
| | - Byung-Sun Choi
- Department of Preventive Medicine, College of Medicine, Chung-Ang University, Seoul, Korea
| | - Jung-Duck Park
- Department of Preventive Medicine, College of Medicine, Chung-Ang University, Seoul, Korea
| | - Heon Kim
- Chungbuk Environmental Health Center, Chungbuk National University Hospital, Cheongju, Korea
- Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea
- Department of Occupational and Environmental Medicine, Chungbuk National University Hospital, Cheongju, Korea
| | - Yong-Dae Kim
- Chungbuk Environmental Health Center, Chungbuk National University Hospital, Cheongju, Korea
- Department of Preventive Medicine, College of Medicine, Chungbuk National University, Cheongju, Korea
- Chungbuk Regional Cancer Center, Chungbuk National University Hospital, Cheongju, Korea.
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Arabnezhad MR, Haghani F, Ghaffarian-Bahraman A, Jafarzadeh E, Mohammadi H, Yadegari JG, Farkhondeh T, Aschner M, Darroudi M, Marouzi S, Samarghandian S. Involvement of Nrf2 Signaling in Lead-induced Toxicity. Curr Med Chem 2024; 31:3529-3549. [PMID: 37221680 DOI: 10.2174/0929867330666230522143341] [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: 12/10/2022] [Revised: 03/19/2023] [Accepted: 03/31/2023] [Indexed: 05/25/2023]
Abstract
Nuclear factor erythroid 2-related factor 2 (Nrf2) is used as one of the main protective factors against various pathological processes, as it regulates cells resistant to oxidation. Several studies have extensively explored the relationship between environmental exposure to heavy metals, particularly lead (Pb), and the development of various human diseases. These metals have been reported to be able to, directly and indirectly, induce the production of reactive oxygen species (ROS) and cause oxidative stress in various organs. Since Nrf2 signaling is important in maintaining redox status, it has a dual role depending on the specific biological context. On the one hand, Nrf2 provides a protective mechanism against metal-induced toxicity; on the other hand, it can induce metalinduced carcinogenesis upon prolonged exposure and activation. Therefore, the aim of this review was to summarize the latest knowledge on the functional interrelation between toxic metals, such as Pb and Nrf2 signaling.
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Affiliation(s)
- Mohammad-Reza Arabnezhad
- Department of Toxicology and Pharmacology, Faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran
| | - Fatemeh Haghani
- Department of Pharmaceutical Biotechnology, Faculty of Pharmacy, Kerman University of Medical Sciences, Kerman, Iran
| | - Ali Ghaffarian-Bahraman
- Occupational Environment Research Center, Rafsanjan University of Medical Sciences, Rafsanjan, Iran
| | - Emad Jafarzadeh
- Department of Toxicology and Pharmacology, Faculty of Pharmacy, Tehran University of Medical Sciences (TUMS), Tehran, Iran
| | - Hamidreza Mohammadi
- Department of Pharmacology and Toxicology, Faculty of Pharmacy, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Javad Ghasemian Yadegari
- Department of Pharmacognosy, Faculty of Pharmacy, Lorestan University of Medical Sciences, Khorramabad, Iran
| | - Tahereh Farkhondeh
- Department of Toxicology and Pharmacology, School of Pharmacy, Birjand University of Medical Sciences, Birjand, Iran
| | - Michael Aschner
- Department of Molecular Pharmacology, Albert Einstein College of Medicine, Bronx, NY 10461, USA
| | - Majid Darroudi
- Nuclear Medicine Research Center, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Somayeh Marouzi
- Department of Basic Medical Sciences, Neyshabur University of Medical Sciences, Neyshabur, Iran
- Department of Medical Biotechnology and Nanotechnology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Saeed Samarghandian
- Healthy Ageing Research Centre, Neyshabur University of Medical Sciences, Neyshabur 9318614139, Iran
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Liang JH, Pu YQ, Liu ML, Hu LX, Bao WW, Zhang YS, Kakaer A, Zhao Y, Chen YC, Pu XY, Huang SY, Jiang N, Huang S, Dong GH, Chen YJ. Joint effect of whole blood metals exposure with dyslipidemia in representative US adults in NHANES 2011-2020. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2023; 30:96604-96616. [PMID: 37578581 DOI: 10.1007/s11356-023-28903-0] [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: 03/07/2023] [Accepted: 07/17/2023] [Indexed: 08/15/2023]
Abstract
With little knowledge on the joint effects of metal exposure on dyslipidemia, we aimed to investigate the relationship between exposure to metal and dyslipidemia among US adults based on the National Health and Nutrition Examination Survey (NHANES). Based on the five NHANES waves (2011-2020), we selected five metals in blood as exposure, namely, cadmium (Cd), lead (Pb), total mercury (Hg), manganese (Mn), and selenium (Se), which were detected by inductively coupled plasma mass spectrometry. Survey-multivariable logistic regression, generalized weighted quantile sum (WQS), and Bayesian kernel machine regression (BKMR) were performed to determine whether dyslipidemia was associated with single metals or mixed metals. Our study included 12,526 participants aged from 20 to 80, representing 577.1 million non-institutionalized US adults. We found a positive association between several metals including Pb [adjusted odds ratio (AOR) = 1.332, 95%CI: 1.165, 1.522], total Hg (AOR = 1.264, 95%CI: 1.120, 1.427), Mn (AOR = 1.181, 95%CI: 1.046, 1.334), and Se (AOR = 1.771, 95%CI: 1.576, 1.992) and dyslipidemia. According to the WQS approach, metal mixtures were positively associated with dyslipidemia (AOR: 1.310, 95%CI: 1.216, 1.411) after a full-model adjustment. As is shown in the BKMR model, mixed metals tended to be positively associated with dyslipidemia ratios in a significant manner. Females, non-Hispanic White populations, people aged over 60, and those who did a little physical activity had a greater risk for dyslipidemia. Our findings suggest metals including Cd, Pb, Hg, Mn, and Se and their combinations may adversely affect dyslipidemia among US adults. Due to the cross-sectional nature of the study, it is possible that reverse causation may exist.
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Affiliation(s)
- Jing-Hong Liang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Ying-Qi Pu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Mei-Ling Liu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Li-Xin Hu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Wen-Wen Bao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Yu-Shan Zhang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Aerziguli Kakaer
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Yu Zhao
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Yi-Can Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Xue-Ya Pu
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Shao-Yi Huang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Nan Jiang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Shan Huang
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080
| | - Guang-Hui Dong
- Guangzhou Key Laboratory of Environmental Pollution and Health Risk Assessment, Guangdong Provincial Engineering Technology Research Center of Environmental and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou, People's Republic of China
| | - Ya-Jun Chen
- Department of Maternal and Child Health, School of Public Health, Sun Yat-sen University, No.74 Zhongshan 2nd Road, Yuexiu District, Guangzhou, People's Republic of China, 510080.
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Zhao M, Yin G, Xu J, Ge X, Li A, Mei Y, Wu J, Liu X, Wei L, Xu Q. Independent, combine and interactive effects of heavy metal exposure on dyslipidemia biomarkers: A cross-sectional study in northeastern China. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2023; 250:114494. [PMID: 36608569 DOI: 10.1016/j.ecoenv.2022.114494] [Citation(s) in RCA: 11] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/16/2022] [Revised: 12/27/2022] [Accepted: 12/29/2022] [Indexed: 06/17/2023]
Abstract
Dyslipidemia is a common disease in the older population and represents a considerable disease burden worldwide. Epidemiological and experimental studies have indicated associations between heavy metal exposure and dyslipidemia; few studies have investigated the effects of heavy metal mixture and interactions between metals on dyslipidemia. We recruited 1121 participants living in heavy metal-contaminated and control areas in northeast China from a cross-sectional survey (2017-2019). Urinary metals including chromium (Cr), cadmium (Cd), lead (Pb), and manganese (Mn) and dyslipidemia biomarkers, namely triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C) levels, were measured. The generalized linear model (GLM) was used to explore the association of a single metal with dyslipidemia biomarkers. Bayesian kernel machine regression (BKMR) and multivariable linear regression were performed to explore the overall effect of metal mixture and the interaction between metals on dyslipidemia. Heavy metal mixture was positively associated with LDL-C, TC, and TG and negatively with HDL-C. In multivariable linear regression, Pb and Cd exhibited a synergistic association with LDL-C in the participants without hyperlipemia. Mn-Cd and Pb-Cr also showed a synergistic association with increasing the level of LDL-C in subjects without hyperlipemia. Cd-Cr showed an antagonistic association with HDL-C, respectively. Cr-Mn exhibited an antagonistic association with decreased HDL-C and TG levels. No significant interaction was noted among the three metals. Our study indicated that exposure to heavy metals is associated with dyslipidemia biomarkers and the presence of potential synergistic or antagonistic interactions between the heavy metals.
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Affiliation(s)
- Meiduo Zhao
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Guohuan Yin
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China
| | - Jing Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Xiaoyu Ge
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Ang Li
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Yayuan Mei
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Jingtao Wu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China
| | - Xiaolin Liu
- Department of Epidemiology and Biostatistics, Jinzhou Medical University, Jinzhou 121001, Liaoning, China
| | - Lanping Wei
- Jinzhou Central Hospital, Jinzhou 121001, Liaoning, China
| | - Qun Xu
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences Chinese Academy of Medical Sciences, School of Basic Medicine Peking Union Medical College, Beijing 100005, China; Center of Environmental and Health Sciences, Chinese Academy of Medical Sciences, Peking Union Medical College, Beijing 100005, China.
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Luo T, Chen S, Cai J, Liu Q, Gou R, Mo X, Tang X, He K, Xiao S, Wei Y, Lin Y, Huang S, Li T, Chen Z, Li R, Li Y, Zhang Z. Association between combined exposure to plasma heavy metals and dyslipidemia in a chinese population. Lipids Health Dis 2022; 21:131. [PMID: 36474262 PMCID: PMC9724421 DOI: 10.1186/s12944-022-01743-6] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 11/18/2022] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Exposure to heavy metals in the environment is widespread, while the relationship between combined exposure to heavy metals and dyslipidemia is unclear. METHODS A cross-sectional study was performed, and 3544 participants aged 30 years or older were included in the analyses. Heavy metal concentrations in plasma were based on inductively coupled plasma‒mass spectrometry. The relationship between heavy metals and dyslipidemia was estimated by logistic regression. BKMR was used to evaluate metal mixtures and their potential interactions. RESULTS In logistic regression analysis, participants in the fourth quartile of Fe and Zn (Fe > 1352.38 µg/L; Zn > 4401.42 µg/L) had a relatively higher risk of dyslipidemia (Fe, OR = 1.13, 95% CI: 0.92,1.38; Zn, OR = 1.30, 95% CI: 1.03,1.64). After sex stratification, females in the third quartile of plasma Zn (1062.05-4401.42 µg/L) had a higher relative risk of dyslipidemia (OR = 1.75, 95% CI: 1.28, 2.38). In BKMR analysis, metal mixtures were negatively associated with dyslipidemia in females when all metal concentrations were above the 50th percentile. In the total population (estimated from 0.030 to 0.031), As was positively associated with dyslipidemia when other metals were controlled at the 25th, 50th, or 75th percentile, respectively, and As was below the 75th percentile. In females (estimated from - 0.037 to -0.031), Zn was negatively associated with dyslipidemia when it was above the 50th percentile. CONCLUSION This study indicated that As was positively associated with dyslipidemia and that Zn may be negatively associated with dyslipidemia in females. Combined metal exposure was negatively associated with dyslipidemia in females. Females with low plasma Zn levels are more likely to develop dyslipidemia and should receive more clinical attention in this population.
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Affiliation(s)
- Tingyu Luo
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Shiyi Chen
- grid.411858.10000 0004 1759 3543School of Public Health and Management, Guangxi University of Chinese Medicine, Guangxi 530200 Nanning, China
| | - Jiansheng Cai
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Qiumei Liu
- grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Ruoyu Gou
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Xiaoting Mo
- grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Xu Tang
- grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Kailian He
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Song Xiao
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Yanfei Wei
- grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Yinxia Lin
- grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Shenxiang Huang
- grid.256607.00000 0004 1798 2653Department of Environmental and Occupational Health, School of Public Health, Guangxi Medical University, 530021 Nanning, Guangxi China
| | - Tingjun Li
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Ziqi Chen
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Ruiying Li
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - You Li
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
| | - Zhiyong Zhang
- grid.443385.d0000 0004 1798 9548Department of Environmental Health and Occupational Medicine, School of Public Health, Guilin Medical University, No.1 Zhiyuan Road, Guangxi 541199 Guilin, China ,grid.443385.d0000 0004 1798 9548Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guangxi 541199 Guilin, China
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9
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Ge X, Ye G, He J, Bao Y, Zheng Y, Cheng H, Feng X, Yang W, Wang F, Zou Y, Yang X. Metal mixtures with longitudinal changes in lipid profiles: findings from the manganese-exposed workers healthy cohort. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:85103-85113. [PMID: 35793018 DOI: 10.1007/s11356-022-21653-5] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 06/20/2022] [Indexed: 06/15/2023]
Abstract
The majority of epidemiological investigations on metal exposures and lipid metabolism employed cross-sectional designs and focused on individual metal. We explored the associations between metal mixture exposures and longitudinal changes in lipid profiles and potential sexual heterogeneity. We recruited 250 men and 73 women, aged 40 years at baseline (2012), and followed them up in 2020, from the manganese-exposed workers healthy cohort. We detected metal concentrations of blood cells at baseline with inductively coupled plasma mass spectrometry. Lipid profiles were repeatedly measured over 8 years of follow-up. We performed sparse partial least squares (sPLS) model to evaluate multi-pollutant associations. Bayesian kernel machine regression was utilized for metal mixtures as well as evaluating their joint impacts on lipid changes. In sPLS models, a positive association was found between manganese and change in total cholesterol (TC) (beta = 0.169), while a negative association was observed between cobalt (beta = - 0.134) and change in low density lipoprotein cholesterol (LDL-C) (beta = - 0.178) among overall participants, which were consistent in men. Interestingly, rubidium was positively associated with change in LDL-C (beta = 0.273) in women, while copper was negatively associated with change in TC (beta = - 0.359) and LDL-C (beta = - 0.267). Magnesium was negatively associated with change in TC (beta = - 0.327). We did not observe the significantly cumulative effect of metal mixtures on lipid changes. In comparison to other metals, manganese had a more significant influence on lipid change [group PIP (0.579) and conditional PIP (0.556) for TC change in men]. Furthermore, male rats exposed to manganese (20 mg/kg) had higher levels of LDL-C in plasma and more apparent inflammatory infiltration, vacuolation of liver cells, nuclear pyknosis, and fatty change than the controls. These findings highlight the potential role of metal mixtures in lipid metabolism with sex-dependent heterogeneity. More researches are needed to explore the underlying mechanisms.
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Affiliation(s)
- Xiaoting Ge
- Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, 545006, China
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Guohong Ye
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Junxiu He
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Yu Bao
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Yuan Zheng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Hong Cheng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Xiuming Feng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Wenjun Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Fei Wang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Yunfeng Zou
- Department of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, China
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, 530021, China
| | - Xiaobo Yang
- Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, 545006, China.
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, 530021, China.
- Guangxi Colleges and Universities Key Laboratory of Prevention and Control of Highly Prevalent Diseases, Guangxi Medical University, Nanning, 530021, China.
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10
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Wei S, Yu X, Wen X, Zhang M, Lang Q, Zhong P, Huang B. Genetic Variations in Metallothionein Genes and Susceptibility to Hypertensive Disorders of Pregnancy: A Case-Control Study. Front Genet 2022; 13:830446. [PMID: 35734434 PMCID: PMC9208279 DOI: 10.3389/fgene.2022.830446] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/19/2022] [Indexed: 01/07/2023] Open
Abstract
Background: The involvement of oxidative stress in the pathological process of hypertensive disorders of pregnancy (HDP) gives rise to the interest in exploring the association of genetic variations in antioxidant metallothionein (MT) genes with HDP susceptibility. Methods: Seventeen single-nucleotide polymorphisms(SNPs) in MT genes were selected to conduct genotyping based on a case-control study consisting of 371 HDP cases (pregnancy with chronic hypertension (66), gestational hypertension (172), and preeclampsia or preeclampsia superimposed on chronic hypertension (133)) and 479 controls. The association between SNPs in MTs and the risk of HDP was estimated with unconditional logistic regression analysis and further tested with the false-positive report probability (FPRP) procedure. The joint effects of SNPs on the HDP risk were assessed by haplotype analysis. Results: After the adjustment for age and pre-pregnancy body mass index (pre-BMI) in the logistic regress analysis and followed by the FPRP test, the genetic variation rs10636 (OR = 0.46, 95% CI: 0.30–0.71 for GG vs. CC, p = 0.000 and OR = 0.48, 95% CI: 0.32–0.73 for GG vs. CG/CC, p = 0.001) in MT2A was associated with gestational hypertension. Other four SNPs, that is, rs11076161 (OR = 1.89, 95% CI: 1.35–2.63 for GG vs. GA/AA, p = 0.000) in MT1A; rs7191779 (OR = 1.54, 95% CI: 1.11–2.13 for CC vs. CG/GG, p = 0.010) in MT1B; rs8044719 (OR = 0.57, 95% CI: 0.40–0.80 for GT vs. GG, p = 0.001) in MT1DP; and rs8052334 (OR = 1.52, 95% CI: 1.10–2.11 for TT vs. TC/CC, p = 0.012) in MT1B were significantly associated with the susceptibility of HDP. The haplotype analysis among 11, 10, 10, and seven SNPs in MT (MT1A, MT2A, MT1M, MT1B, and MT1DP) genes showed that eight (A-C-G-T-C-G-A-G-C-G-C, OR = 4.559; A-C-T-C-C-C-A-G-C-G-C, OR = 5.777; A-C-T-T-C-G-A-G-C-G-C, OR = 4.590; G-A-T-C-C-G-C-G-G-C-C, OR = 4.065; G-A-T-C-G-C-C-G-G-C-C, OR = 4.652; G-A-T-T-C-C-C-G-G-C-C, OR = 0.404; G-C-T-C-C-C-A-G-G-C-C, OR = 1.901; G-C-T-T-C-C-A-G-G-C-C, and OR = 3.810), five (C-G-A-T-C-A-C-C-G-G, OR = 2.032; C-G-A-T-C-G-C-C-G-G, OR = 2.077; G-A-C-T-C-A-C-C-T-G, OR = 0.564; G-G-A-G-C-A-C-C-G-G, OR = 5.466; G-G-A-T-T-A-G-C-G-G, and OR = 0.284), five (A-C-G-T-C-G-A-G-C-C, OR = 2.399; A-C-T-C-C-C-C-T-G-G, OR = 0.259; G-A-T-C-C-C-C-G-G-C, OR = 1.572; G-A-T-C-G-C-C-G-G-C, OR = 0.001; G-C-T-C-G-C-A-G-G-C, and OR = 2.512), and five (A-C-T-C-C-C-G, OR = 0.634; G-A-G-C-C-C-G, OR = 4.047; G-A-T-T-G-C-G, OR = 0.499; G-C-G-T-C-A-G, and OR = 7.299; G-C-T-C-C-A-G, OR = 1.434) haplotypes were significantly associated with pregnancy with chronic hypertension, gestational hypertension, preeclampsia, or preeclampsia superimposed on chronic hypertension and HDP. Conclusion: These variant MT alleles and their combination patterns may be used as genetic markers for predicting HDP susceptibility.
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Affiliation(s)
- Shudan Wei
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Xiangyuan Yu
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Xiaolan Wen
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Min Zhang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Qi Lang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
| | - Ping Zhong
- Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Guilin Medical University, Guilin, China
| | - Bo Huang
- Guangxi Key Laboratory of Environmental Exposomics and Entire Lifecycle Health, Guangxi Health Commission Key Laboratory of Entire Lifecycle Health and Care, Guilin Medical University, Guilin, China
- *Correspondence: Bo Huang,
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11
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Zhou J, Meng X, Deng L, Liu N. Non-linear associations between metabolic syndrome and four typical heavy metals: Data from NHANES 2011-2018. CHEMOSPHERE 2022; 291:132953. [PMID: 34800500 DOI: 10.1016/j.chemosphere.2021.132953] [Citation(s) in RCA: 23] [Impact Index Per Article: 11.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2021] [Revised: 11/14/2021] [Accepted: 11/15/2021] [Indexed: 06/13/2023]
Abstract
Previous studies have found that heavy metals are associated with metabolic syndrome (MetS), although findings are inconsistent. Further, investigations into potential associations that consider age- or gender-specific effects and dose-response associations for metal exposure and MetS are rare. In this study, we explore the associations between blood levels of typical heavy metals [lead (Pb), cadmium (Cd), mercury (Hg) and manganese (Mn)] and MetS among adults using logistic regression analysis and restricted cubic splines (RCS) logistic analysis using data from the US National Health and Nutrition Examination Survey 2011-2018. After adjusting for covariates, higher levels of blood Pb, Cd and Hg were associated with lower risks of MetS in participants overall, and in all subgroup analyses, by logistic regression analysis (all P-values <0.05); in contrast, higher levels of blood Mn had a higher risk of MetS only in the age group of 30-49 years (P-values <0.05). We also found non-linear associations of heavy metal levels in blood with risk of MetS in participants overall, in specific age groups and in both genders, using RCS logistic regressions (all P-values <0.05). In addition, the non-linear associations of Pb and Hg we observed in different subgroups differed. In conclusion, blood levels of four heavy metals were associated with the risk of MetS through a variety of non-linear patterns.
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Affiliation(s)
- Jianli Zhou
- Department of Occupational Health and Occupational Medicine, School of Public Health, Southern Medical University, Guangzhou, 510515, PR China
| | - Xiaojing Meng
- Department of Occupational Health and Occupational Medicine, School of Public Health, Southern Medical University, Guangzhou, 510515, PR China.
| | - Lugang Deng
- Institute of Environment and Health, South China Hospital, Health Science Center, Shenzhen University, Shenzhen, 518116, PR China
| | - Nan Liu
- Department of Occupational Health and Occupational Medicine, School of Public Health, Southern Medical University, Guangzhou, 510515, PR China; Institute of Environment and Health, South China Hospital, Health Science Center, Shenzhen University, Shenzhen, 518116, PR China; Institute of Chronic Disease Risks Assessment, School of Nursing and Health, Henan University, Kaifeng, 475004, PR China; College of Public Health, Zhengzhou University, Zhengzhou, 540001, PR China.
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12
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Single Nucleotide Polymorphism of TWIST2 May Be a Modifier for the Association between High-Density Lipoprotein Cholesterol and Blood Lead (Pb) Level. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19031352. [PMID: 35162374 PMCID: PMC8834775 DOI: 10.3390/ijerph19031352] [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] [Received: 12/02/2021] [Revised: 01/19/2022] [Accepted: 01/24/2022] [Indexed: 12/10/2022]
Abstract
The association between lead (Pb) exposure and lower high-density lipoprotein cholesterol (HDL-C) was reported; however, the mechanism was unclear. Our purpose was to investigate the association of Pb, lipid profile, and to study the associated SNPs using a genome-wide association study (GWAS). A total of 511 participants were recruited to check blood Pb levels, lipid profile, and genotypes with Taiwan Biobank version 2.0 (TWB2). Our main result shows that HDL-C was significantly negatively associated with blood Pb levels, adjusted for gender, body mass index (BMI), and potential confounders. In addition, via the TWB2 GWAS, only two SNPs were found, including rs150813626 (single-nucleotide variation in the TWIST2 gene on chromosome 2), and rs1983079 (unclear SNP on chromosome 3). Compared to the rs150813626 GG carriers, the AA and AG carriers were significantly and negatively associated with HDL-C. We analyzed the interaction of rs150813626 SNP and blood Pb, and the HDL-C was consistently and negatively associated with blood Pb, male, BMI, and the rs150813626 AA and AG carriers. Moreover, the rs150813626 AA and blood Pb interaction was significantly and positively associated with HDL-C. In conclusion, the SNPs rs150813626 and rs1983079 were significantly associated with HDL-C in Pb-exposed workers. Furthermore, the interaction of rs150813626 AA and blood Pb had a positive influence on HDL-C. TWIST may inhibit osteoblast maturation, which might relate to bone Pb deposition and calcium metabolism. The mechanism needs more investigation in the future.
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13
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Jiang Q, Xiao Y, Long P, Li W, Yu Y, Liu Y, Liu K, Zhou L, Wang H, Yang H, Li X, He M, Wu T, Yuan Y. Associations of plasma metal concentrations with incident dyslipidemia: Prospective findings from the Dongfeng-Tongji cohort. CHEMOSPHERE 2021; 285:131497. [PMID: 34273700 DOI: 10.1016/j.chemosphere.2021.131497] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/20/2021] [Accepted: 07/07/2021] [Indexed: 06/13/2023]
Abstract
Metal exposures are ubiquitous around the world, while it is lack of prospective studies to evaluate the associations of exposure to multiple metal/metalloids with incident dyslipidemia. A total of 2947 participants without dyslipidemia at baseline were included in the analyses. We utilized inductively coupled plasma mass spectrometry to measure the baseline plasma metal concentrations. Unconditional logistic regression models were applied to estimate the relations between plasma metals and risk of incident dyslipidemia, and principal component analysis was performed to extract principal components of metals. During 5.01 ± 0.31 years of follow-up, 521 subjects were diagnosed with incident dyslipidemia. After multivariable adjustment, the odds ratios (ORs) of dyslipidemia comparing the highest quartiles to the lowest were 1.58 (95% CI: 1.20, 2.08; Ptrend = 0.001) for aluminum, 1.34 (95% CI: 1.03, 1.75; Ptrend = 0.03) for arsenic, 1.44 (1.09, 1.91; Ptrend = 0.03) for strontium, and 1.47 (95% CI: 1.09, 2.00; Ptrend = 0.005) for vanadium. The four metals also showed significant associations with the subtypes of dyslipidemia, including low HDL-C and high LDL-C. The first principal component, which mainly represented aluminum, arsenic, barium, lead, vanadium, and zinc, was associated with increased risk of incident dyslipidemia, and the adjusted OR was 1.40 (95% CI: 1.07, 1.84; Ptrend = 0.02) comparing extreme quartiles. The study indicated that elevated plasma aluminum, arsenic, strontium, and vanadium concentrations were associated with a higher incidence of dyslipidemia. These findings highlight the importance of controlling metal exposures for dyslipidemia prevention.
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Affiliation(s)
- Qin Jiang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Yang Xiao
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Pinpin Long
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Wending Li
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Yanqiu Yu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Yiyi Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Kang Liu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Lue Zhou
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Hao Wang
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Handong Yang
- Department of Cardiovascular Diseases, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Xiulou Li
- Department of Cardiovascular Diseases, Sinopharm Dongfeng General Hospital, Hubei University of Medicine, Shiyan, China
| | - Meian He
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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
| | - Tangchun Wu
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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.
| | - Yu Yuan
- Department of Occupational and Environmental Health, Key Laboratory of Environment and 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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14
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He ZZ, Guo PY, Xu SL, Zhou Y, Jalaludin B, Leskinen A, Knibbs LD, Heinrich J, Morawska L, Yim SHL, Bui D, Komppula M, Roponen M, Hu L, Chen G, Zeng XW, Yu Y, Yang BY, Dong G. Associations of Particulate Matter Sizes and Chemical Constituents with Blood Lipids: A Panel Study in Guangzhou, China. ENVIRONMENTAL SCIENCE & TECHNOLOGY 2021; 55:5065-5075. [PMID: 33764049 DOI: 10.1021/acs.est.0c06974] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/12/2023]
Abstract
Existing evidence is scarce concerning the various effects of different PM sizes and chemical constituents on blood lipids. A panel study that involved 88 healthy college students with five repeated measurements (440 blood samples in total) was performed. We measured mass concentrations of particulate matter with diameters ≤ 2.5 μm (PM2.5), ≤1.0 μm (PM1.0), and ≤0.5 μm (PM0.5) as well as number concentrations of particulate matter with diameters ≤ 0.2 μm (PN0.2) and ≤0.1 μm (PN0.1). We applied linear mixed-effect models to assess the associations between short-term exposure to different PM size fractions and PM2.5 constituents and seven lipid metrics. We found significant associations of greater concentrations of PM in different size fractions within 5 days before blood collection with lower high-density lipoprotein cholesterol (HDL-C) and apolipoprotein A (ApoA1) levels, higher apolipoprotein B (ApoB) levels, and lower ApoA1/ApoB ratios. Among the PM2.5 constituents, we observed that higher concentrations of tin and lead were significantly associated with decreased HDL-C levels, and higher concentrations of nickel were associated with higher HDL-C levels. Our results suggest that short-term exposure to PM in different sizes was deleteriously associated with blood lipids. Some constituents, especially metals, might be the major contributors to the detrimental effects.
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Affiliation(s)
- Zhi-Zhou He
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Peng-Yue Guo
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Shu-Li Xu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yang Zhou
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Bin Jalaludin
- Centre for Air Quality and Health Research and Evaluation, Glebe, NSW 2037, Australia
- Population Health, South Western Sydney Local Health District, Liverpool, NSW 2170, Australia
- Ingham Institute for Applied Medical Research, Liverpool, NSW 2170, Australia
- School of Public Health and Community Medicine, The University of New South Wales, Kensington, NSW 2052, Australia
| | - Ari Leskinen
- Finnish Meteorological Institute, Kuopio 70211, Finland
- Department of Applied Physics, University of Eastern Finland, Kuopio 70211, Finland
| | - Luke D Knibbs
- School of Public Health, The University of Queensland, Herston, Queensland 4006, Australia
| | - Joachim Heinrich
- Institute and Clinic for Occupational, Social and Environmental Medicine, University Hospital, LMU Munich, Munich 80336, Germany
- Comprehensive Pneumology Center Munich, German Center for Lung Research, Munich 80336, Germany
| | - Lidia Morawska
- International Laboratory for Air Quality and Health, Queensland University of Technology (QUT), GP.O. Box 2434, Brisbane, Queensland 4001, Australia
| | - Steve Hung-Lam Yim
- Department of Geography and Resource Management, Stanley Ho Big Data Decision Analytics Research Centre, Institute of Environment, Energy and Sustainability, The Chinese University of Hong Kong, Shatin, China
| | - Dinh Bui
- Allergy and Lung Health Unit, Centre for Epidemiology and Biostatistics, School of Population & Global Health, The University of Melbourne, Melbourne, VIC 3010, Australia
| | - Mika Komppula
- Finnish Meteorological Institute, Kuopio 70211, Finland
| | - Marjut Roponen
- Department of Environmental and Biological Sciences, University of Eastern Finland, Kuopio, FI 70211, Finland
| | - Liwen Hu
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Gongbo Chen
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xiao-Wen Zeng
- Guangdong Provincial Engineering Technology Research Center of Environmental Pollution and Health Risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yunjiang Yu
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Bo-Yi Yang
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
| | - Guanghui Dong
- State Environmental Protection Key Laboratory of Environmental Pollution Health Risk Assessment, South China Institute of Environmental Sciences, Ministry of Environmental Protection, Guangzhou 510655, China
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15
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Xu P, Liu A, Li F, Tinkov AA, Liu L, Zhou JC. Associations between metabolic syndrome and four heavy metals: A systematic review and meta-analysis. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 273:116480. [PMID: 33486246 DOI: 10.1016/j.envpol.2021.116480] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Revised: 12/19/2020] [Accepted: 01/07/2021] [Indexed: 06/12/2023]
Abstract
Four most concerned heavy metal pollutants, arsenic, cadmium, lead, and mercury may share common mechanisms to induce metabolic syndrome (MetS). However, recent studies exploring the relationships between MetS and metal exposure presented inconsistent findings. We aimed to clarify the relationship between heavy metal exposure biomarkers and MetS using a meta-analysis and systematic review approach. Literature search was conducted in international and the Chinese national databases up to June 2020. Of selected studies, we extracted the relevant data and evaluated the quality of each study's methodology. We then calculated the pooled effect sizes (ESs), standardized mean differences (SMDs), and their 95% confidence intervals (CIs) using a random-effect meta-analysis approach followed by stratification analyses for control of potential confounders. Involving 55,536 participants, the included 22 articles covered 52 observational studies reporting ESs and/or metal concentrations on specific metal and gender. Our results show that participants with MetS had significantly higher levels of heavy metal exposure [pooled ES = 1.16, 95% CI: 1.09, 1.23; n = 42, heterogeneity I2 = 75.6%; and SMD = 0.22, 95% CI: 0.15, 0.29; n = 32, I2 = 94.2%] than those without MetS. Pooled ESs in the subgroups stratified by arsenic, cadmium, lead, and mercury were 1.04 (95% CI: 0.97, 1.10; n = 8, I2 = 61.0%), 1.10 (0.95, 1.27; 11, 45.0%), 1.21 (1.00, 1.48; 12, 82.9%), and 1.26 (1.06, 1.48; 11, 67.7%), respectively. Pooled ESs in the subgroups stratified by blood, urine, and the other specimen were 1.22 (95% CI: 1.08, 1.38; n = 26, I2 = 75.8%), 1.06 (1.00, 1.13; 14, 58.1%), and 2.41 (1.30, 4.43; 2, 0.0%), respectively. In conclusion, heavy metal exposure was positively associated with MetS. Further studies are warranted to examine the effects of individual metals and their interaction on the relationship between MetS and heavy metals.
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Affiliation(s)
- Ping Xu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, 518100, China
| | - Aiping Liu
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, 518100, China
| | - Fengna Li
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, 518100, China
| | - Alexey A Tinkov
- Yaroslavl State University, 150003, Yaroslavl, Russia; IM Sechenov First Moscow State Medical University (Sechenov University), 119146, Moscow, Russia
| | - Longjian Liu
- Department of Epidemiology and Biostatistics, Dornsife School of Public Health, Drexel University, Philadelphia, PA, 19104, USA
| | - Ji-Chang Zhou
- School of Public Health (Shenzhen), Sun Yat-sen University, Shenzhen, 518100, China; Guangdong Province Engineering Laboratory for Nutrition Translation, Guangzhou, 510080, China.
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16
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Amirabadizadeh A, Nakhaee S, Mehrpour O. Risk assessment of elevated blood lead concentrations in the adult population using a decision tree approach. Drug Chem Toxicol 2020; 45:878-885. [DOI: 10.1080/01480545.2020.1783286] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Alireza Amirabadizadeh
- Medical Toxicology and Drug Abuse Research Center (MTDRC), Birjand University of Medical Sciences, Birjand, Iran
| | - Samaneh Nakhaee
- Medical Toxicology and Drug Abuse Research Center (MTDRC), Birjand University of Medical Sciences, Birjand, Iran
| | - Omid Mehrpour
- Medical Toxicology and Drug Abuse Research Center (MTDRC), Birjand University of Medical Sciences, Birjand, Iran
- Rocky Mountain Poison and Drug Safety, Denver Health and Hospital Authority, Denver, CO, USA
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17
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Hussain S, Ali S, Mumtaz S, Shakir HA, Ahmad F, Tahir HM, Ulhaq M, Khan MA, Zahid MT. Dose and duration-dependent toxicological evaluation of lead acetate in chicks. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2020; 27:15149-15164. [PMID: 32072413 DOI: 10.1007/s11356-020-08016-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2019] [Accepted: 02/06/2020] [Indexed: 06/10/2023]
Abstract
Lead is one of the utmost contaminated and dangerous heavy metals. This toxicant ultimately enters into the human body through the food chain and accumulated in the body because the animal/human body has not an appropriate mechanism to excrete it from the body. The main objective of the present research was to assess the toxicological effects of lead on body weights, biochemical, and hematological parameters of chickens and also to measure its bioaccumulation in the brain. Lead acetate was administrated orally at doses of 0, 71, 142, 213, and 284 mg/kg of body weight of chicken for groups A, B, C, D, and E, respectively. Along with determination of biometry of all experimental chicks, hematological [hemoglobin (Hb), packed cell volume (PCV), mean corpuscular hemoglobin concentration (MCHC), total erythrocyte count (TEC), white blood cells (WBCs), leukocyte differential count (LDC)] and biochemical [low density lipoprotein (LDL), total protein, high-density lipoprotein (HDL), and alanine aminotransferase (ALT)] parameters were measured. The present study showed that the bodyweight of chickens was not affected significantly by lead acetate exposure. The levels of MCHC, PCV, TEC, Hb, LDL, HDL, and total protein were found to be significantly decreased while WBC, LDC, and ALT profile were enhanced due to administration of lead acetate. Bioaccumulation of lead acetate was found to be higher in the brain. We conclude that the chronic administration of lead acetate affected the blood and biochemical profile of exposed chicken. These effects might be due to the accumulation of the chemical in certain vital organ(s). However, further studies in the future are suggested to refine such findings.
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Affiliation(s)
- Saeeda Hussain
- Department of Zoology, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan
| | - Shaukat Ali
- Applied Entomology and Medical Toxicology, Department of Zoology, Government College University, Lahore, Pakistan.
| | - Shumaila Mumtaz
- Applied Entomology and Medical Toxicology, Department of Zoology, Government College University, Lahore, Pakistan
| | | | - Farooq Ahmad
- Department of Zoology, The Islamia University of Bahawalpur, Bahawalpur, Punjab, Pakistan
| | - Hafiz Muhammad Tahir
- Applied Entomology and Medical Toxicology, Department of Zoology, Government College University, Lahore, Pakistan
| | - Mazhar Ulhaq
- Department of Veterinary Biomedical Sciences, PMAS Arid Agriculture University, Rawalpindi, 46300, Pakistan
| | - Muhammad Adeeb Khan
- Department of Zoology, The University of Azad Jammu and Kashmir, Muzaffarabad, Pakistan
| | - Muhammad Tariq Zahid
- Applied Entomology and Medical Toxicology, Department of Zoology, Government College University, Lahore, Pakistan
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18
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Sekovanić A, Jurasović J, Piasek M. Metallothionein 2A gene polymorphisms in relation to diseases and trace element levels in humans. Arh Hig Rada Toksikol 2020; 71:27-47. [PMID: 32597135 PMCID: PMC7837243 DOI: 10.2478/aiht-2020-71-3349] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/01/2019] [Revised: 10/01/2019] [Accepted: 03/01/2020] [Indexed: 02/08/2023] Open
Abstract
Human metallothioneins are a superfamily of low molecular weight intracellular proteins, whose synthesis can be induced by essential elements (primarily Zn and Cu), toxic elements and chemical agents, and stress-producing conditions. Of the four known isoforms in the human body MT2 is the most common. The expression of metallothioneins is encoded by a multigene family of linked genes and can be influenced by single nucleotide polymorphisms (SNPs) in these genes. To date, 24 SNPs in the MT2A gene have been identified with the incidence of about 1 % in various population groups, and three of them were shown to affect physiological and pathophysiological processes. This review summarises current knowledge about these three SNPs in the MT2A gene and their associations with element concentrations in the body of healthy and diseased persons. The most investigated SNP is rs28366003 (MT2A -5 A/G). Reports associate it with longevity, cancer (breast, prostate, laryngeal, and in paranasal sinuses), and chronic renal disease. The second most investigated SNP, rs10636 (MT2A +838G/C), is associated with breast cancer, cardiovascular disease, and type 2 diabetes. Both are also associated with several metal/metalloid concentrations in the organism. The third SNP, rs1610216 (MT2A -209A/G), has been studied for association with type 2 diabetes, cardiomyopathy, hyperglycaemia, and Zn concentrations. Metallothionein concentrations and MT2A polymorphisms have a potential to be used as biomarkers of metal exposure and clinical markers of a number of chronic diseases. This potential needs to be studied and verified in a large number of well-defined groups of participants (several hundreds and thousands) with a focus on particular physiological or pathological condition and taking into consideration other contributing factors, such as environmental exposure and individual genetic and epigenetic makeup.
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Affiliation(s)
- Ankica Sekovanić
- Analytical Toxicology and Mineral Metabolism Unit, Institute for Medical Research and Occupational Health,Zagreb, Croatia
| | - Jasna Jurasović
- Analytical Toxicology and Mineral Metabolism Unit, Institute for Medical Research and Occupational Health,Zagreb, Croatia
| | - Martina Piasek
- Analytical Toxicology and Mineral Metabolism Unit, Institute for Medical Research and Occupational Health,Zagreb, Croatia
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19
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Dolan LC, Flannery BM, Hoffman-Pennesi D, Gavelek A, Jones OE, Kanwal R, Wolpert B, Gensheimer K, Dennis S, Fitzpatrick S. A review of the evidence to support interim reference level for dietary lead exposure in adults. Regul Toxicol Pharmacol 2020; 111:104579. [PMID: 31945454 DOI: 10.1016/j.yrtph.2020.104579] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2019] [Revised: 01/09/2020] [Accepted: 01/10/2020] [Indexed: 12/13/2022]
Abstract
FDA developed the interim reference level (IRL) for lead of 3 μg/day in children and 12.5 μg/day in women of childbearing age (WOCBA) to better protect the fetus from lead toxicity. These IRLs correspond to a blood lead level (BLL) of 0.5 μg/dL in both populations. The current investigation was performed to determine if the IRL for WOCBA should apply to the general population of adults. A literature review of epidemiological studies was conducted to determine whether a BLL of 0.5 μg/dL is associated with adverse effects in adults. Some studies reported adverse effects over a wide range of BLLs that included 0.5 μg/dL adding uncertainty to conclusions about effects at 0.5 μg/dL; however, no studies clearly identified this BLL as an adverse effect level. Results also showed that the previously developed PTTDI for adults of 75 μg/day lead may not be health protective, supporting use of a lower reference value for lead toxicity in this population group. Use of the 12.5 μg/day IRL as a benchmark for dietary lead intake is one way FDA will ensure that dietary lead intake in adults is reduced.
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Affiliation(s)
- Laurie C Dolan
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Brenna M Flannery
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA.
| | - Dana Hoffman-Pennesi
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Alexandra Gavelek
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Olivia E Jones
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Richard Kanwal
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Beverly Wolpert
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Kathleen Gensheimer
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Sherri Dennis
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
| | - Suzanne Fitzpatrick
- US Food and Drug Administration, Center for Food Safety and Applied Nutrition, College Park, MD, USA
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20
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Baranowska-Bosiacka I, Olszowski T, Gutowska I, Korbecki J, Rębacz-Maron E, Barczak K, Lubkowska A, Chlubek D. Fatty acid levels alterations in THP-1 macrophages cultured with lead (Pb). J Trace Elem Med Biol 2019; 52:222-231. [PMID: 30732887 DOI: 10.1016/j.jtemb.2019.01.003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/23/2018] [Revised: 12/16/2018] [Accepted: 01/04/2019] [Indexed: 10/27/2022]
Abstract
OBJECTIVE As cardiovascular events are one of the main causes of death in developed countries, each factor potentially increasing the risk of cardiovascular disease deserves special attention. One such factor is the potentially atherogenic effect of lead (Pb) on lipid metabolism, and is significant in view of the still considerable Pb environmental pollution and the non-degradability of Pb compounds. METHODS Analysis of saturated fatty acids (SFA) (caprylic acid (C8:0), decanoic acid (C10:0), lauric acid (C12:0), tridecanoic acid (C13:0), myristic acid (C14:0), pentadecanoic acid (C15:0), palmitic acid (C16:0), heptadecanoic acid (C17:0), stearic acid (C18:0), and behenic acid (C22:0)), monounsaturated fatty acid (MUFA) (palmitoleic acid (C16:1), oleic acid (18:1w9), trans-vaccenic acid (C18:1 trans11)), and polyunsaturated fatty acid (PUFA) (linoleic acid (C18:2n6), gamma-linolenic acid (C18:3n6), arachidonic acid (C20:4n6)), was conducted by gas chromatography. Analysis of stearoyl-CoA desaturase (SCD), fatty acid desaturase 1 (FADS1) and fatty acid desaturase 2 (FADS2) expression was performed using qRT-PCR. Oxidative stress intensity (malondialdehyde - MDA concentration) was measured using spectrophotometric method. Intracellular generation of reactive oxygen species (ROS) in macrophages was visualized by fluorescence microscopy and quantitatively measured by plate reader. RESULTS Pb caused quantitative alterations in FAs profile in macrophages; the effect was Pb-concentration dependent and selective (i.e. concerned only selected FAs). In general, the effect of Pb was biphasic, with Pb levels of 1.25 μg/dL and 2.5 μg/dL being stimulatory, and 10 μg/dL being inhibitory on concentrations of selected FAs. The most potent Pb concentration, resulting in increase in levels of 9 FAs, was 2.5 μg/dL, the Pb-level corresponding to the mean blood Pb concentrations of people living in urban areas not contaminated by Pb. Pb was found to exert similar, biphasic effect on the expression of FADS1. However, Pb decreased, in a concentration-dependent manner, the expression of SCD and FADS2. Pb significantly increased MDA and ROS concentration in macrophages. CONCLUSION Environmental Pb exposure might be a risk factor resulting in alterations in FAs levels, oxidative stress and increased MDA concentration in macrophages, which might lead to the formation of foam cells and to inflammatory reactions.
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Affiliation(s)
- Irena Baranowska-Bosiacka
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University in Szczecin, Powstańców Wlkp. 72 St., 70-111, Szczecin, Poland.
| | - Tomasz Olszowski
- Department of Hygiene and Epidemiology, Pomeranian Medical University in Szczecin, Powstańców Wlkp. 72 St., 70-111, Szczecin, Poland
| | - Izabela Gutowska
- Department of Biochemistry and Human Nutrition, Pomeranian Medical University in Szczecin, Broniewskiego 24 St., 71-460, Szczecin, Poland
| | - Jan Korbecki
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University in Szczecin, Powstańców Wlkp. 72 St., 70-111, Szczecin, Poland
| | - Ewa Rębacz-Maron
- University of Szczecin, Department of Vertebrate Zoology and Anthropology, Institute for Research on Biodiversity, Faculty of Biology, University of Szczecin, Wąska 13 St., 71-415, Szczecin, Poland
| | - Katarzyna Barczak
- Department of Conservative Dentistry and Endodontics, Pomeranian Medical University, Powstańców Wlkp. 72, 70-111, Szczecin, Poland
| | - Anna Lubkowska
- Department of Functional Diagnostics and Physical Medicine, Pomeranian Medical University in Szczecin, 71-210, Szczecin, Poland
| | - Dariusz Chlubek
- Department of Biochemistry and Medical Chemistry, Pomeranian Medical University in Szczecin, Powstańców Wlkp. 72 St., 70-111, Szczecin, Poland
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21
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Bulka CM, Persky VW, Daviglus ML, Durazo-Arvizu RA, Argos M. Multiple metal exposures and metabolic syndrome: A cross-sectional analysis of the National Health and Nutrition Examination Survey 2011-2014. ENVIRONMENTAL RESEARCH 2019; 168:397-405. [PMID: 30388496 PMCID: PMC6274587 DOI: 10.1016/j.envres.2018.10.022] [Citation(s) in RCA: 99] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/21/2018] [Revised: 10/17/2018] [Accepted: 10/19/2018] [Indexed: 05/05/2023]
Abstract
BACKGROUND Epidemiologic studies suggest toxic metals are linked with diabetes and cardiovascular disease, while experimental studies indicate nutritionally essential metals are involved in the metabolism of macronutrients and defense against oxidative stress. OBJECTIVES We sought to evaluate how essential and toxic metals are cross-sectionally related to metabolic syndrome, a clustering of cardiometabolic conditions. METHODS Using data from the 2011-2014 National Health and Nutrition Examination Survey (n = 1088), we characterized metal concentrations as measured in spot urine (arsenic, cadmium, and inorganic/elemental mercury), whole blood (manganese, lead, methylmercury, and selenium), and serum (copper and zinc) samples. Principal component analysis was performed to derive patterns of exposures. Metabolic syndrome was defined according to the 2009 Joint Scientific Statement as the presence of ≥ 3 of the following conditions: high blood pressure, high triglycerides, low HDL cholesterol, high fasting glucose, and abdominal obesity. RESULTS After adjustment for potential confounders, prevalence ratios for metabolic syndrome comparing the highest to the lowest quartiles were 1.41 (95% CI: 1.18-1.67) for the arsenic-inorganic/elemental mercury pattern, 0.95 (0.78-1.16) for the methylmercury-manganese pattern, 0.73 (0.57-0.94) for the cadmium-lead pattern, 0.91 (0.76-1.10) for the copper pattern, and 1.36 (1.13-1.63) for the selenium-zinc pattern. The positive associations observed for the arsenic-inorganic/elemental mercury pattern were due to an elevated prevalence of high blood pressure, low HDL cholesterol, and high triglycerides among those with greater exposures. Associations for the selenium-zinc pattern were driven by a positive relationship with high triglycerides. Greater lead-cadmium co-exposures were related to a lower prevalence of dyslipidemia and abdominal obesity. CONCLUSIONS These cross-sectional findings suggest both toxic and essential metal exposures may contribute to cardiometabolic health, but need to be confirmed with prospective data.
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Affiliation(s)
- Catherine M Bulka
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago School of Public Health, Chicago, IL, USA.
| | - Victoria W Persky
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago School of Public Health, Chicago, IL, USA
| | - Martha L Daviglus
- Institute for Minority Health Research, University of Illinois College of Medicine, Chicago, IL, USA
| | - Ramon A Durazo-Arvizu
- Institute for Minority Health Research, University of Illinois College of Medicine, Chicago, IL, USA
| | - Maria Argos
- Division of Epidemiology and Biostatistics, University of Illinois at Chicago School of Public Health, Chicago, IL, USA
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22
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Obeng-Gyasi E, Armijos RX, Weigel MM, Filippelli GM, Sayegh MA. Cardiovascular-Related Outcomes in U.S. Adults Exposed to Lead. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2018; 15:E759. [PMID: 29662032 PMCID: PMC5923801 DOI: 10.3390/ijerph15040759] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 03/10/2018] [Revised: 04/10/2018] [Accepted: 04/12/2018] [Indexed: 01/15/2023]
Abstract
Cardiovascular-related clinical markers were evaluated in this cross-sectional study of United States adults (aged ≥ 20) exposed to lead via the National Health and Nutrition Examination Survey 2007-2008 and the 2009-2010 datasets. In four quartiles of exposure-0-2 μg/dL, 2-5 μg/dL, 5-10 μg/dL, and 10 μg/dL and over, clinical and anthropometric markers were evaluated-to examine how the markers manifested in the quartiles. Associations were determined via linear regression. Finally, clinical makers, and how they manifested between exposed and less-exposed occupations, were explored in addition to how duration of exposure altered these clinical markers. In regression analysis, Diastolic Blood Pressure (DBP) and high-density lipoprotein (HDL) cholesterol, were significantly associated with blood lead level (BLL). In the occupational analysis, Systolic Blood Pressure (SBP), DBP, C-reactive protein (CRP), triglycerides, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, showed differences between populations in the exposed and less-exposed occupations. Regarding Agriculture, Forestry & Fishing, the duration of exposure altered SBP, CRP, and LDL cholesterol. With mining, the duration of exposure altered SBP, DBP, triglycerides, and HDL cholesterol, whereas in construction, the duration in occupation altered SBP, triglycerides, and CRP. In conclusion, lead exposure has a profound effect on the cardiovascular system, with potentially adverse outcomes existing at all exposure levels.
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Affiliation(s)
- Emmanuel Obeng-Gyasi
- Department of Built Environment, North Carolina Agricultural and Technical State University, Greensboro, NC 27411, USA.
| | - Rodrigo X Armijos
- Department of Environmental and Occupational Health, Indiana University School of Public Health, Bloomington, IN 47405, USA.
| | - M Margaret Weigel
- Department of Environmental and Occupational Health, Indiana University School of Public Health, Bloomington, IN 47405, USA.
| | - Gabriel M Filippelli
- Department of Earth Sciences, Indiana University Purdue University Indianapolis, Indianapolis, IN 46202, USA.
| | - M Aaron Sayegh
- Department of Epidemiology and Biostatistics, Indiana University School of Public Health, Bloomington, IN 47405, USA.
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23
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Mitra P, Sharma S, Purohit P, Sharma P. Clinical and molecular aspects of lead toxicity: An update. Crit Rev Clin Lab Sci 2017; 54:506-528. [DOI: 10.1080/10408363.2017.1408562] [Citation(s) in RCA: 139] [Impact Index Per Article: 19.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Affiliation(s)
- Prasenjit Mitra
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, India
| | - Shailja Sharma
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, India
| | - Purvi Purohit
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, India
| | - Praveen Sharma
- Department of Biochemistry, All India Institute of Medical Sciences, Jodhpur, India
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