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Weng C, Zhao Y, Song M, Shao Z, Pang Y, Yu C, Pei P, Yang L, Millwood IY, Walters RG, Chen Y, Du H, Chen J, Chen Z, Genovese G, Terao C, Lv J, Li L, Sun D. Mosaic loss of chromosome Y, tobacco smoking and risk of age-related lung diseases: insights from two prospective cohorts. Eur Respir J 2024; 64:2400968. [PMID: 39401857 DOI: 10.1183/13993003.00968-2024] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/20/2024] [Accepted: 09/11/2024] [Indexed: 12/31/2024]
Abstract
BACKGROUND Little is known about the underlying relationship between mosaic loss of chromosome Y (mLOY), the most common chromosomal alterations in older men, and the risk of age-related lung diseases. METHODS We included 217 780 participants from the UK Biobank (UKB) and 42 859 participants from the China Kadoorie Biobank. The mLOY events were detected using the Mosaic Chromosomal Alterations (MoChA) pipeline. Outcomes included all lung diseases, COPD, lung cancer and idiopathic pulmonary fibrosis (IPF). Cox proportional hazard models were fitted to estimate the hazard ratios and 95% confidence intervals of mLOY with lung diseases in both cohorts. The combined hazard ratios were derived from meta-analysis. RESULTS Results from the two cohorts showed that expanded mLOY was associated with increased risks of all lung diseases (HR 1.19 (95% CI 1.04-1.36)), COPD (HR 1.20 (95% CI 1.13-1.28)), lung cancer (HR 1.34 (95% CI 1.21-1.48)) and IPF (HR 1.34 (95% CI 1.16-1.56) in the UKB). There was evidence of positive interactions between mLOY and smoking behaviour (relative excess risk due to interaction (97.5% CI) >0). Additionally, we observed that current smokers with expanded mLOY had the highest risk of incident lung diseases in both cohorts. CONCLUSIONS mLOY may be a novel predictor for age-related lung diseases. For current smokers carrying mLOY, adopting quitting smoking behaviour may contribute to substantially reducing their risk of incident lung diseases.
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Affiliation(s)
- Chenghao Weng
- School of Basic Medical Sciences, Peking University Health Science Center, Beijing, China
- These authors contributed equally to this work
| | - Yuxuan Zhao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- These authors contributed equally to this work
| | - Mingyu Song
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Zilun Shao
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Yuanjie Pang
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
| | - Canqing Yu
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Pei Pei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
| | - Ling Yang
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Iona Y Millwood
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Robin G Walters
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Yiping Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Huaidong Du
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Junshi Chen
- China National Center for Food Safety Risk Assessment, Beijing, China
| | - Zhengming Chen
- Clinical Trial Service Unit and Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Giulio Genovese
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
| | - Chikashi Terao
- Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Kanagawa, Japan
- Clinical Research Center, Shizuoka General Hospital, Shizuoka, Japan
- Department of Applied Genetics, School of Pharmaceutical Sciences, University of Shizuoka, Shizuoka, Japan
| | - Jun Lv
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Liming Li
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
| | - Dianjianyi Sun
- Department of Epidemiology and Biostatistics, School of Public Health, Peking University Health Science Center, Beijing, China
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, China
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Wang X, Wu X, Ma W, Wang Q, Chen Y, Zhao X, Lu Y. Antimony exposure affects oocyte quality and early embryo development via excessive mitochondrial oxidation and dysfunction. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 285:117084. [PMID: 39305772 DOI: 10.1016/j.ecoenv.2024.117084] [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: 05/30/2024] [Revised: 09/18/2024] [Accepted: 09/18/2024] [Indexed: 10/17/2024]
Abstract
Antimony (Sb) is a metalloid, widely presents in the environment and associates with human health. In this study, we aimed to decipher whether Sb exposure is harmful to female reproduction and explore the underlying mechanisms. The ICR mice were exposed to 0, 5, 10, and 20 mg/kg acetate potassium Sb tartrate trihydrate by intraperitoneal injection for 10 days, then mouse oocytes were collected for further analysis. We first found a significant decrease in the proportion of MII-stage oocytes obtained from supernumerary ovulation in the fallopian tubes and early embryo development under Sb treatment. Then a series of tests showed Sb affects oocyte maturation by damaging the cytoskeleton of microtubule and actin. Moreover, the abnormal distribution of cortical granules and their component Ovastacin in oocytes, combined with reduced expression levels of Juno, affected sperm-oocyte binding and led to fertilization failure. Based on the sequencing results and experimental validation, it was demonstrated that Sb exposure impairs mitochondrial distribution and membrane potential, elevated levels of mitochondrial superoxide, finally caused energy supply deficits. Mitochondrial damage in oocytes after Sb exposure results in the excessive oxidative stress and early apoptosis. Taken together, these data suggest that Sb exposure decreases oocyte quality and female fertilization ability by impairing mitochondrial function and redox perturbation.
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Affiliation(s)
- Xia Wang
- Center for Reproductive Medicine, Affiliated Hospital of Nantong University, Nantong University, Nantong 226001, China
| | - Xue Wu
- Center for Reproductive Medicine, Affiliated Hospital of Nantong University, Nantong University, Nantong 226001, China; Institute of Reproductive Medicine, Medical School, Nantong University, Nantong 226019, China
| | - Wei Ma
- Center for Reproductive Medicine, Affiliated Hospital of Nantong University, Nantong University, Nantong 226001, China; Institute of Reproductive Medicine, Medical School, Nantong University, Nantong 226019, China
| | - Qingxin Wang
- Center for Reproductive Medicine, Affiliated Hospital of Nantong University, Nantong University, Nantong 226001, China
| | - Yuqi Chen
- Center for Reproductive Medicine, Affiliated Hospital of Nantong University, Nantong University, Nantong 226001, China; Institute of Reproductive Medicine, Medical School, Nantong University, Nantong 226019, China
| | - Xinyuan Zhao
- Department of Occupational Medicine and Environmental Toxicology, Nantong Key Laboratory of Environmental Toxicology, School of Public Health, Nantong University, Nantong 226019, China.
| | - Yajuan Lu
- Institute of Reproductive Medicine, Medical School, Nantong University, Nantong 226019, China.
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Hu Z, Wu N, An S, Deng M, Tao L, Liao D, Yu R, Yang J, Xiao Y, Zheng X, Zeng R, Liu Y, Xiong S, Xie Y, Liu X, Shen X, Shang X, Li Q, Zhou Y. Effect of combined exposure to phthalates and polycyclic aromatic hydrocarbons during early pregnancy on gestational age and neonatal size: A prospective cohort study. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 284:116868. [PMID: 39146592 DOI: 10.1016/j.ecoenv.2024.116868] [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: 04/02/2024] [Revised: 08/07/2024] [Accepted: 08/09/2024] [Indexed: 08/17/2024]
Abstract
Many studies have indicated that individual exposure to phthalates (PAEs) or polycyclic aromatic hydrocarbons (PAHs) affects pregnancy outcomes. However, combined exposure to PAEs and PAHs presents a more realistic situation, and research on the combined effects of PAEs and PAHs on gestational age and newborn size is still limited. This study aimed to assess the effects of combined exposure to PAEs and PAHs on neonatal gestational age and birth size. Levels of 9 PAE and 10 PAH metabolites were measured from the urine samples of 1030 women during early pregnancy from the Zunyi Birth Cohort in China. Various statistical models, including linear regression, restricted cubic spline, Bayesian kernel machine regression, and quantile g-computation, were used to study the individual effects, dose-response relationships, and combined effects, respectively. The results of this prospective study revealed that each ten-fold increase in the concentration of monoethyl phthalate (MEP), 2-hydroxynaphthalene (2-OHNap), 2-hydroxyphenanthrene (2-OHPhe), and 1-hydroxypyrene (1-OHPyr) decreased gestational age by 1.033 days (95 % CI: -1.748, -0.319), 0.647 days (95 % CI: -1.076, -0.219), 0.845 days (95 % CI: -1.430, -0.260), and 0.888 days (95 % CI: -1.398, -0.378), respectively. Moreover, when the concentrations of MEP, 2-OHNap, 2-OHPhe, and 1-OHPyr exceeded 0.528, 0.039, 0.012, and 0.002 µg/g Cr, respectively, gestational age decreased in a dose-response manner. Upon analyzing the selected PAE and PAH metabolites as a mixture, we found that they were significantly negatively associated with gestational age, birth weight, and the ponderal index, with 1-OHPyr being the most important contributor. These findings highlight the adverse effects of single and combined exposure to PAEs and PAHs on gestational age. Therefore, future longitudinal cohort studies with larger sample sizes should be conducted across different geographic regions and ethnic groups to confirm the impact of combined exposure to PAEs and PAHs on birth outcomes.
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Affiliation(s)
- Zhongmei Hu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Department of Obstetrics and Gynecology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China; Department of Reproductive Medicine, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Nian Wu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Songlin An
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Mingyu Deng
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Department of Obstetrics and Gynecology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Lin Tao
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Dengqing Liao
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Rui Yu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Jing Yang
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Yanling Xiao
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Xingting Zheng
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China
| | - Rong Zeng
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Yijun Liu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Shimin Xiong
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Yan Xie
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Xingyan Liu
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Xubo Shen
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China
| | - Xuejun Shang
- Department of Andrology, School of Medicine, Jinling Hospital, Nanjing University, Nanjing 210002, China
| | - Quan Li
- Department of Obstetrics and Gynecology, Affiliated Hospital of Zunyi Medical University, Zunyi, Guizhou 563000, China.
| | - Yuanzhong Zhou
- School of Public Health, Zunyi Medical University, Zunyi, Guizhou 563000, China; Key Laboratory of Maternal & Child Health and Exposure Science of Guizhou Higher Education Institutes, Zunyi, Guizhou 563000, China.
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Wu L, Lu X, Zhang S, Zhong Y, Gao H, Tao FB, Wu X. Co-exposure effects of urinary polycyclic aromatic hydrocarbons and metals on lung function: mediating role of systematic inflammation. BMC Pulm Med 2024; 24:386. [PMID: 39128985 PMCID: PMC11316979 DOI: 10.1186/s12890-024-03173-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 07/15/2024] [Indexed: 08/13/2024] Open
Abstract
BACKGROUND Polycyclic aromatic hydrocarbons (PAHs) and metals were associated with decreased lung function, but co-exposure effects and underlying mechanism remained unknown. METHODS Among 1,123 adults from National Health and Nutrition Examination Survey 2011-2012, 10 urinary PAHs, 11 urinary metals, and peripheral white blood cell (WBC) count were determined, and 5 lung function indices were measured. Least absolute shrinkage and selection operator, Bayesian kernel machine regression, and quantile-based g-computation were used to estimate co-exposure effects on lung function. Mediation analysis was used to explore mediating role of WBC. RESULTS These models demonstrated that PAHs and metals were significantly associated with lung function impairment. Bayesian kernel machine regression models showed that comparing to all chemicals fixed at median level, forced expiratory volume in 1 s (FEV1)/forced vital capacity, peak expiratory flow, and forced expiratory flow between 25 and 75% decreased by 1.31% (95% CI: 0.72%, 1.91%), 231.62 (43.45, 419.78) mL/s, and 131.64 (37.54, 225.74) mL/s respectively, when all chemicals were at 75th percentile. In the quantile-based g-computation, each quartile increase in mixture was associated with 104.35 (95% CI: 40.67, 168.02) mL, 1.16% (2.11%, 22.40%), 294.90 (78.37, 511.43) mL/s, 168.44 (41.66, 295.22) mL/s decrease in the FEV1, FEV1/forced vital capacity, peak expiratory flow, and forced expiratory flow between 25% and 75%, respectively. 2-Hydroxyphenanthrene, 3-Hydroxyfluorene, and cadmium were leading contributors to the above associations. WBC mediated 8.22%-23.90% of association between PAHs and lung function. CONCLUSIONS Co-exposure of PAHs and metals impairs lung function, and WBC could partially mediate this relationship. Our findings elucidate co-exposure effects of environmental mixtures on respiratory health and underlying mechanisms, suggesting that focusing on highly prioritized toxicants would effectively attenuate adverse effects.
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Affiliation(s)
- Lihong Wu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
- Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Key Laboratory of Environment and Population Health Across the Life Course, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xue Lu
- Department of Toxicology, Anhui Medical University, Anhui, China
| | - Siying Zhang
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Yumei Zhong
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Hui Gao
- Department of Pediatrics, The First Affiliated Hospital of Anhui Medical University, No 218 Jixi Road, Hefei, 230022, Anhui, China
| | - Fang-Biao Tao
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
- Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China
- Anhui Provincial Key Laboratory of Environment and Population Health Across the Life Course, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China
| | - Xiulong Wu
- Department of Maternal, Child and Adolescent Health, School of Public Health, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
- Key Laboratory of Population Health Across Life Cycle (Anhui Medical University), Ministry of Education of the People's Republic of China, No 81 Meishan Road, Hefei, 230032, Anhui, China.
- Anhui Provincial Key Laboratory of Environment and Population Health Across the Life Course, Anhui Medical University, No 81 Meishan Road, Hefei, 230032, Anhui, China.
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Guan X, Meng X, Zhong G, Zhang Z, Wang C, Xiao Y, Fu M, Zhao H, Zhou Y, Hong S, Xu X, Bai Y, Kan H, Chen R, Wu T, Guo H. Particulate matter pollution, polygenic risk score and mosaic loss of chromosome Y in middle-aged and older men from the Dongfeng-Tongji cohort study. JOURNAL OF HAZARDOUS MATERIALS 2024; 471:134315. [PMID: 38678703 DOI: 10.1016/j.jhazmat.2024.134315] [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: 12/01/2023] [Revised: 04/04/2024] [Accepted: 04/14/2024] [Indexed: 05/01/2024]
Abstract
Mosaic loss of chromosome Y (mLOY) is the most common somatic alteration as men aging and may reflect genome instability. PM exposure is a major health concern worldwide, but its effects with genetic factors on mLOY has never been investigated. Here we explored the associations of PM2.5 and PM10 exposure with mLOY of 10,158 males measured via signal intensity of 2186 probes in male-specific chromosome-Y region from Illumina array data. The interactive and joint effects of PM2.5 and PM10 with genetic factors and smoking on mLOY were further evaluated. Compared with the lowest tertiles of PM2.5 levels in each exposure window, the highest tertiles in the same day, 7-, 14-, 21-, and 28-day showed a 0.005, 0.006, 0.007, 0.007, and 0.006 decrease in mLRR-Y, respectively (all P < 0.05), with adjustment for age, BMI, smoking pack-years, alcohol drinking status, physical activity, education levels, season of blood draw, and experimental batch. Such adverse effects were also observed in PM10-mLOY associations. Moreover, the unweighted and weighted PRS presented significant negative associations with mLRR-Y (both P < 0.001). Participants with high PRS and high PM2.5 or PM10 exposure in the 28-day separately showed a 0.018 or 0.019 lower mLRR-Y level [β (95 %CI) = -0.018 (-0.023, -0.012) and - 0.019 (-0.025, -0.014), respectively, both P < 0.001], when compared to those with low PRS and low PM2.5 or PM10 exposure. We also observed joint effects of PM with smoking on exacerbated mLOY. This large study is the first to elucidate the impacts of PM2.5 exposure on mLOY, and provides key evidence regarding the interactive and joint effects of PM with genetic factors on mLOY, which may promote understanding of mLOY development, further modifying and increasing healthy aging in males.
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Affiliation(s)
- Xin Guan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Xia Meng
- Department of Environment Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Guorong Zhong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Zirui Zhang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Chenming Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Yang Xiao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Ming Fu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Hui Zhao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Yuhan Zhou
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Shiru Hong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Xuedan Xu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Yansen Bai
- Institute for Chemical Carcinogenesis, School of Public Health, Guangzhou Medical University, Xinzao, Panyu District, Guangzhou 511436, China
| | - Haidong Kan
- Department of Environment Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Renjie Chen
- Department of Environment Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education and National Health Commission Key Lab of Health Technology Assessment, Fudan University, Shanghai, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China
| | - Huan Guo
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Rd, Wuhan, China.
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6
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Wang C, Zhong G, Liu C, Hong S, Guan X, Xiao Y, Fu M, Zhou Y, You Y, Wu T, Zhao H, Wang Y, Chen S, Zhang Y, Wang C, Guo H. DNA methylation aging signatures of multiple metals exposure and their mediation effects in metal-associated mortality: Evidence from the Dongfeng-Tongji cohort study. JOURNAL OF HAZARDOUS MATERIALS 2024; 465:133200. [PMID: 38113735 DOI: 10.1016/j.jhazmat.2023.133200] [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: 09/08/2023] [Revised: 11/28/2023] [Accepted: 12/06/2023] [Indexed: 12/21/2023]
Abstract
Humans were exposed to multiple metals, but the impact of metals on DNA methylation-age (DNAm-age), a well-recognized aging measure, remains inconclusive. This study included 2942 participants from the Dongfeng-Tongji cohort. We detected their plasma concentrations of 23 metals and determined their genome-wide DNA methylation using the Illumina Human-MethylationEPIC BeadChip. Five DNAm-age acceleration indexes (DAIs), including HannumAge-Accel, HorvathAge-Accel, PhenoAge-Accel, GrimAge-Accel (residual from regressing corresponding DNAm-age on chronological age) and DNAm-mortality score (DNAm-MS), were separately calculated. We found that each 1-unit increase in ln-transformed copper (Cu) was associated with a separate 1.02-, 0.83- and 0.07-unit increase in PhenoAge-Accel, GrimAge-Accel, and DNAm-MS (all FDR<0.05). Each 1-unit increase in ln-transformed nickel (Ni) was associated with a 0.34-year increase in PhenoAge-Accel, while each 1-unit increase in ln-transformed strontium (Sr) was associated with a 0.05-unit increase in DNAm-MS. The Cu, Ni and Sr showed joint positive effects on above three DAIs. PhenoAge-Accel, GrimAge-Accel, and DNAm-MS mediated a separate 6.5%, 12.3%, 6.0% of the positive association between Cu and all-cause mortality; GrimAge-Accel mediated 14.3% of the inverse association of selenium with all-cause mortality. Our findings revealed the effects of Cu, Ni, Sr and their co-exposure on accelerated aging and highlighted mediation roles of DNAm-age on metal-associated mortality.
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Affiliation(s)
- Chenming Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Guorong Zhong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Chenliang Liu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shiru Hong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Xin Guan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yang Xiao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Ming Fu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yuhan Zhou
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yingqian You
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Tianhao Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Hui Zhao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yuxi Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Shengli Chen
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Yichi Zhang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Chaolong Wang
- Department of Epidemiology and Biostatistics, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China
| | - Huan Guo
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei 430030, China.
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7
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Chang VC, Zhou W, Berndt SI, Andreotti G, Yeager M, Parks CG, Sandler DP, Rothman N, Beane Freeman LE, Machiela MJ, Hofmann JN. Glyphosate Use and Mosaic Loss of Chromosome Y among Male Farmers in the Agricultural Health Study. ENVIRONMENTAL HEALTH PERSPECTIVES 2023; 131:127006. [PMID: 38055050 PMCID: PMC10699410 DOI: 10.1289/ehp12834] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 11/01/2023] [Accepted: 11/15/2023] [Indexed: 12/07/2023]
Abstract
BACKGROUND Glyphosate is the most commonly used herbicide worldwide and has been implicated in the development of certain hematologic cancers. Although mechanistic studies in human cells and animals support the genotoxic effects of glyphosate, evidence in human populations is scarce. OBJECTIVES We evaluated the association between lifetime occupational glyphosate use and mosaic loss of chromosome Y (mLOY) as a marker of genotoxicity among male farmers. METHODS We analyzed blood-derived DNA from 1,606 farmers ≥ 50 years of age in the Biomarkers of Exposure and Effect in Agriculture study, a subcohort of the Agricultural Health Study. mLOY was detected using genotyping array intensity data in the pseudoautosomal region of the sex chromosomes. Cumulative lifetime glyphosate use was assessed using self-reported pesticide exposure histories. Using multivariable logistic regression, we estimated odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between glyphosate use and any detectable mLOY (overall mLOY) or mLOY affecting ≥ 10 % of cells (expanded mLOY). RESULTS Overall, mLOY was detected in 21.4% of farmers, and 9.8% of all farmers had expanded mLOY. Increasing total lifetime days of glyphosate use was associated with expanded mLOY [highest vs. lowest quartile; OR = 1.75 (95% CI: 1.00, 3.07), p trend = 0.03 ] but not with overall mLOY; the associations with expanded mLOY were most apparent among older (≥ 70 years of age) men [OR = 2.30 (95% CI: 1.13, 4.67), p trend = 0.01 ], never smokers [OR = 2.32 (95% CI: 1.04, 5.21), p trend = 0.04 ], and nonobese men [OR = 2.04 (95% CI: 0.99, 4.19), p trend = 0.03 ]. Similar patterns of associations were observed for intensity-weighted lifetime days of glyphosate use. DISCUSSION High lifetime glyphosate use could be associated with mLOY affecting a larger fraction of cells, suggesting glyphosate could confer genotoxic or selective effects relevant for clonal expansion. As the first study to investigate this association, our findings contribute novel evidence regarding the carcinogenic potential of glyphosate and require replication in future studies. https://doi.org/10.1289/EHP12834.
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Affiliation(s)
- Vicky C. Chang
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
| | - Weiyin Zhou
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, NCI, NIH, DHHS, Bethesda, Maryland, USA
| | - Sonja I. Berndt
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
| | - Gabriella Andreotti
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
| | - Meredith Yeager
- Cancer Genomics Research Laboratory, Division of Cancer Epidemiology and Genetics, NCI, NIH, DHHS, Bethesda, Maryland, USA
| | - Christine G. Parks
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, DHHS, Durham, North Carolina, USA
| | - Dale P. Sandler
- Epidemiology Branch, National Institute of Environmental Health Sciences, NIH, DHHS, Durham, North Carolina, USA
| | - Nathaniel Rothman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
| | - Laura E. Beane Freeman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
| | - Mitchell J. Machiela
- Integrative Tumor Epidemiology Branch, Division of Cancer Epidemiology and Genetics, NCI, NIH, DHHS, Bethesda, Maryland, USA
| | - Jonathan N. Hofmann
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute (NCI), National Institutes of Health (NIH), Department of Health and Human Services (DHHS), Bethesda, Maryland, USA
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8
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Wang C, Hong S, Guan X, Xiao Y, Fu M, Meng H, Feng Y, Zhou Y, Cao Q, Yuan F, Liu C, Zhong G, You Y, Wu T, Yang H, Zhang X, He M, Wu T, Guo H. Associations between multiple metals exposure and biological aging: Evidence from the Dongfeng-Tongji cohort. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 861:160596. [PMID: 36464054 DOI: 10.1016/j.scitotenv.2022.160596] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 11/21/2022] [Accepted: 11/26/2022] [Indexed: 06/17/2023]
Abstract
Aging is related to a progressive decline in physiological functions and is affected by environmental factors. Metal exposures are linked with many health effects, but have poorly understood associations with aging. In this study, a total of 33,916 participants from the Dongfeng-Tongji cohort were included to establish biological age (BA) predictors by using recent advanced algorithms, Klemera and Doubal method (KDM) and Mahalanobis distance. Two biological aging indexes (BAIs), recorded as KDM-accel [the residual from regressing KDM-BA on chronological age] and physiological dysregulation (PD), were separately defined and tested on their associations with mortality by using Cox proportional hazard models. Among 3320 subjects with laboratory determinations of 23 metals in plasma, the individual and overall associations between these metals and BAIs were evaluated by using multiple-linear regression and weighted quantile sum (WQS) models. Both BAIs were prospectively associated with all-cause mortality among the whole participants [KDM-accel: HR(95%CI) = 1.23(1.18, 1.29); PD: HR(95%CI) = 1.37(1.31, 1.42)]. Each 1-unit increment in ln-transformed strontium and molybdenum were cross-sectionally associated with a separate 0.71- and 0.34-year increase in KDM-accel, and each 1 % increment in copper, rubidium, strontium, cobalt was cross-sectionally associated with a separate 0.10 %, 0.10 %, 0.09 %, 0.02 % increase in PD (all FDR < 0.05). The WQS models observed mixture effects of multi-metals on aging, with a 0.20-year increase in KDM-accel and a 0.04 % increase in PD for each quartile increase in ln-transformed concentrations of all metals [KDM-accel: β(95%CI) = 0.20(0.08, 0.32); PD: β(95%CI) = 0.04(0.02, 0.06)]. Our findings revealed that plasma strontium, molybdenum, copper, rubidium and cobalt were associated with accelerated aging. Multi-metals exposure showed mixture effects on the aging process, which highlights potential preventative interventions.
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Affiliation(s)
- Chenming Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Shiru Hong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Xin Guan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yang Xiao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Ming Fu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Hua Meng
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yue Feng
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yuhan Zhou
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Qiang Cao
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Fangfang Yuan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Chenliang Liu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Guorong Zhong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Yingqian You
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tianhao Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Handong Yang
- Department of Cardiovascular Diseases, Dongfeng Central Hospital, Hubei University of Medicine, Shiyan, Hubei, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Meian He
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Tangchun Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China
| | - Huan Guo
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei, China.
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9
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Feng X, Zan G, Wei Y, Ge X, Cai H, Long T, Xie L, Tong L, Liu C, Li L, Huang L, Wang F, Chen X, Zhang H, Zou Y, Zhang Z, Yang X. Relationship of multiple metals mixture and osteoporosis in older Chinese women: An aging and longevity study. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2023; 317:120699. [PMID: 36403877 DOI: 10.1016/j.envpol.2022.120699] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/14/2022] [Revised: 10/21/2022] [Accepted: 11/17/2022] [Indexed: 06/16/2023]
Abstract
Osteoporosis has become a major health problem in older women. Previous studies have linked individual metals exposure with osteoporosis, but combined effects remain inconclusive. We aimed to explore the individual and combined association between multiple metals mixture and osteoporosis risk in older Chinese women. A total of 2297 older women (aged ≥60) from the Hongshuihe region of Guangxi, southern China included. We measured 22 blood metal levels through inductively coupled plasma mass spectrometry. And osteoporosis was defined as a T score ≤ -2.5. The least absolute shrinkage and selection operator (LASSO) penalized regression, and Bayesian kernel machine regression (BKMR) models were performed to explore the association between blood metals and osteoporosis risk. Of 2297 older women, there were 829 osteoporosis and 1468 non-osteoporosis participants. The median age was 71 and 68 years old in the osteoporosis and the non-osteoporosis group, respectively. In the single-metal model, rubidium and vanadium were negatively associated with osteoporosis (P for trend = 0.02 and 0.002, respectively), and lead presented the reverse trend (P for trend = 0.01). The LASSO penalized regression model selected nine metals (calcium, cadmium, cobalt, lead, magnesium, rubidium, strontium, vanadium and zinc), which were included in the subsequent analysis. And the multiple-metal model presented a consistent trend with the single-metal model using the selected metals. Furthermore, we performed BKMR to explore the combined effect, and found an overall negative effect between metals mixture and osteoporosis risk when all the metals were fixed at 50th, and rubidium and vanadium were the main contributors. In addition, blood Rb and V were significantly negatively related to OP risk with other metals at different levels (25th, 50th and 75th percentiles). The study suggests metal mixture exposure and osteoporosis risk in older Chinese women, and further studies need to be conducted.
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Affiliation(s)
- Xiuming Feng
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Gaohui Zan
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Yue Wei
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xiaoting Ge
- Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Haiqing Cai
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Tianzhu Long
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Lianguang Xie
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Department of Public Health, School of Medicine, Guangxi University of Science and Technology, Liuzhou, Guangxi, China
| | - Lei Tong
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Chaoqun Liu
- Department of Nutrition and Food Hygiene, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Longman Li
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Lulu Huang
- Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China
| | - Fei Wang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Xing Chen
- Department of Sanitary Chemistry, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Haiying Zhang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China
| | - Yunfeng Zou
- Department of Toxicology, School of Public Health, Guangxi Medical University, Nanning, 530021, China
| | - Zhiyong Zhang
- School of Public Health, Guilin Medical University, Guilin, Guangxi, China
| | - Xiaobo Yang
- Department of Occupational Health and Environmental Health, School of Public Health, Guangxi Medical University, Nanning, Guangxi, China; Center for Genomic and Personalized Medicine, Guangxi Key Laboratory for Genomic and Personalized Medicine, Guangxi Collaborative Innovation Center for Genomic and Personalized Medicine, Guangxi Medical University, Nanning, Guangxi, China.
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10
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Fu M, Wang C, Hong S, Guan X, Meng H, Feng Y, Xiao Y, Zhou Y, Liu C, Zhong G, You Y, Wu T, Yang H, Zhang X, He M, Guo H. Multiple metals exposure and blood mitochondrial DNA copy number: A cross-sectional study from the Dongfeng-Tongji cohort. ENVIRONMENTAL RESEARCH 2023; 216:114509. [PMID: 36208786 DOI: 10.1016/j.envres.2022.114509] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/14/2022] [Revised: 09/25/2022] [Accepted: 10/02/2022] [Indexed: 06/16/2023]
Abstract
OBJECTIVE Mitochondria are essential organelles that execute fundamental biological processes, while mitochondrial DNA is vulnerable to environmental insults. The aim of this study was to investigate the individual and mixture effect of plasma metals on blood mitochondria DNA copy number (mtDNAcn). METHODS This study involved 1399 randomly selected subcohort participants from the Dongfeng-Tongji cohort. The blood mtDNAcn and plasma levels of 23 metals were determined by using quantitative real-time polymerase chain reaction (qPCR) and inductively coupled plasma mass spectrometer (ICP-MS), respectively. The multiple linear regression was used to explore the association between each metal and mtDNAcn, and the LASSO penalized regression was performed to select the most significant metals. We also used the quantile g-computation analysis to assess the mixture effect of multiple metals. RESULTS Based on multiple linear regression models, each 1% increase in plasma concentration of copper (Cu), rubidium (Rb), and titanium (Ti) was associated with a separate 0.16% [β(95% CI) = 0.158 (0.066, 0.249), P = 0.001], 0.20% [β(95% CI) = 0.196 (0.073, 0.318), P = 0.002], and 0.25% [β(95% CI) = 0.245 (0.081, 0.409), P = 0.003] increase in blood mtDNAcn. The LASSO regression also confirmed Cu, Rb, and Ti as significant predictors for mtDNAcn. There was a significant mixture effect of multiple metals on increasing mtDNAcn among the elder participants (aged ≥65), with an approximately 11% increase in mtDNAcn for each quartile increase in all metal concentrations [β(95% CI) = 0.146 (0.048, 0.243), P = 0.004]. CONCLUSIONS Our results show that plasma Cu, Rb and Ti were associated with increased blood mtDNA, and we further revealed a significant mixture effect of all metals on mtDNAcn among elder population. These findings may provide a novel perspective on the effect of metals on mitochondrial dysfunction.
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Affiliation(s)
- Ming Fu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chenming Wang
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shiru Hong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Xin Guan
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Hua Meng
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yue Feng
- Department of Occupational and Environmental Health, 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, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yuhan Zhou
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Chenliang Liu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Guorong Zhong
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Yingqian You
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Tianhao Wu
- Department of Occupational and Environmental Health, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Handong Yang
- Dongfeng Central Hospital, Dongfeng Motor Corporation and Hubei University of Medicine, Shiyan, China
| | - Xiaomin Zhang
- Department of Occupational and Environmental Health, 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, State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Huan Guo
- Department of Occupational and Environmental Health, 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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11
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Bigambo FM, Zhang M, Zhang J, Yang X, Yu Q, Wu D, Wang X, Xia Y. Exposure to a mixture of personal care product and plasticizing chemicals in relation to reproductive hormones and menarche timing among 12–19 years old girls in NHANES 2013–2016. Food Chem Toxicol 2022; 170:113463. [PMID: 36220617 DOI: 10.1016/j.fct.2022.113463] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2022] [Revised: 08/15/2022] [Accepted: 10/04/2022] [Indexed: 11/05/2022]
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12
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Jiang L, Xiao Q, Zhang J, Zhao Y, Chen L, Lu S. Association between fetal exposure to polycyclic aromatic hydrocarbons and low birth weight: a case-control study in Shenzhen, China. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:88779-88787. [PMID: 35840835 DOI: 10.1007/s11356-022-21965-6] [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: 04/25/2022] [Accepted: 07/07/2022] [Indexed: 06/15/2023]
Abstract
The potential hazards of polycyclic aromatic hydrocarbons (PAHs) on fetus development have raised widespread concerns in recent years, although current epidemiological findings are conflicting. The aim of this case-control study was to investigate the relationship between PAH concentrations in maternal serum and low birth weight (LBW). A questionnaire survey was conducted among 144 (72 pairs) neonates with normal or LBW and their mothers at four different hospitals in Shenzhen, China. Peripheral blood from primiparas and umbilical cord blood from neonates were collected. Concentrations of PAHs were determined by gas chromatography-mass spectrometry. The detection frequencies of PAHs were relatively higher in the peripheral blood samples, while levels of low molecular weight PAHs were greater than high molecular weight PAHs in both peripheral and umbilical cord blood samples. Phenanthrene was frequently detected in blood samples from the case and control groups. Logistic regression analysis showed that acenaphthene in peripheral blood was positively associated with LBW (p < 0.05). This study found a relationship between exposure to certain PAHs and LBW, although future studies are needed to confirm these results.
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Affiliation(s)
- Lei Jiang
- Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China
| | - Qinru Xiao
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, 518107, China
| | - Jianqing Zhang
- Shenzhen Center for Disease Control and Prevention, Shenzhen, 518055, China
| | - Yang Zhao
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, 518107, China
| | - Lihua Chen
- Shenzhen Maternity & Child Healthcare Hospital, Southern Medical University, Shenzhen, 518028, China
| | - Shaoyou Lu
- School of Public Health (Shenzhen), Sun Yat-Sen University, Shenzhen, 518107, China.
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Qin N, Wang C, Chen C, Yang L, Liu S, Xiang J, Xie Y, Liang S, Zhou J, Xu X, Zhao X, Zhu M, Jin G, Ma H, Dai J, Hu Z, Shen H. Association of the interaction between mosaic chromosomal alterations and polygenic risk score with the risk of lung cancer: an array-based case-control association and prospective cohort study. Lancet Oncol 2022; 23:1465-1474. [PMID: 36265503 DOI: 10.1016/s1470-2045(22)00600-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/25/2022] [Revised: 09/13/2022] [Accepted: 09/15/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Mosaic chromosomal alterations (mCAs) detected from blood-derived DNA are large structural alterations of clonal haematopoietic origin and are associated with various diseases, such as haematological malignancies, infections, and solid cancers. We aimed to investigate whether mCAs contribute to the risk of lung cancer and modify the effect of polygenic risk score (PRS) on lung cancer risk prediction. METHODS The blood-derived DNA of patients with lung cancer and cancer-free controls with Chinese ancestry from the Nanjing Lung Cancer Cohort (NJLCC) study were genotyped with a Global Screening Array, and mCAs were detected with the Mosaic Chromosomal Alterations (MoChA) pipeline. mCA call sets of individuals with European ancestry were obtained from the prospective cohort UK Biobank (UKB) study, including documented incident lung cancer. All patients with lung cancer from the NJLCC study (aged 15 years or older at diagnosis) were histopathologically confirmed as new lung cancer cases by at least two pathologists and were free of chemotherapy or radiotherapy before diagnosis. Participants with incident lung cancer (aged 37-73 years at assessment) diagnosed after recruitment to the UKB were identified through linkage to national cancer registries. Logistic regression and Cox proportional hazard models were applied to evaluate associations between mCAs and risk of lung cancer in the NJLCC (logistic regression) and UKB (Cox proportional hazard model) studies. FINDINGS The NJLCC study included 10 248 individuals (6445 [62·89%] men and 3803 [37·11%] women; median age 60·0 years [IQR 53·0-66·0]) with lung cancer and 9298 individuals (5871 [63·14%] men and 3427 [36·86%] women; median age 60·0 years [52·0-65·0]) without lung cancer recruited from three sub-regions (north, central, and south) across China between April 15, 2003, and Aug 18, 2017. The UKB included 450 821 individuals recruited from 22 centres across the UK between March 13, 2006, and Nov 1, 2010, including 2088 individuals with lung cancer (1075 [51·48%] men and 1013 [48·52%] women; median age 63·0 years [IQR 59·0-66·0]), and 448 733 participants were free of lung cancer (204 713 [45·62%] men and 244 020 [54·38%] women; median age 58·0 years [IQR 50·0-63·0]). Compared with non-carriers of mosaic losses, carriers had a significantly increased risk of lung cancer in the NJLCC (odds ratio [OR] 1·81, 95% CI 1·43-2·28; p=6·69 × 10-7) and UKB (hazard ratio [HR] 1·40, 95% CI 1·00-1·95; p=0·048) studies. This increased risk was even higher in patients with expanded cell fractions of mCAs (ie, cell fractions ≥10% vs cell fractions <10%) in the NJLCC (OR 1·61 [95% CI 1·26-2·08] vs 1·03 [0·83-1·26]; p for heterogeneity test=6·41 × 10-3). A significant multiplicative interaction was observed between PRS and mosaic losses on the risk of lung cancer in both the NJLCC (interaction p value=0·030) and UKB (p=0·043). Compared with non-carriers of mosaic loss abnormalities with low genetic risk, participants with expanded mosaic losses (cell fractions ≥10%) and high genetic risk had around a six-times increased risk of lung cancer in the NJLCC study (OR 6·40 [95% CI 3·22-12·69]), and an almost four-times increased risk of lung cancer (HR 3·75 [95% CI 1·86-7·55]) in the UKB study. The additive interaction also contributed a 3·67 (95% CI 0·49-6·85) relative excess risk of developing lung cancer in the NJLCC study, and a 2·15 (0·12-4·19) relative excess risk in the UKB study. INTERPRETATION mCAs act as a new endogenous indicator for the risk of lung cancer and might be jointly used with PRS to optimise personalised risk stratification for lung cancer. FUNDING National Natural Science Foundation of China, Outstanding Youth Foundation of Jiangsu Province, Natural Science Foundation of Jiangsu Province, and Postdoctoral Science Foundation of China. TRANSLATION For the Chinese translation of the abstract see Supplementary Materials section.
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Affiliation(s)
- Na Qin
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Cheng Wang
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Congcong Chen
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Liu Yang
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Su Liu
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jun Xiang
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Yuan Xie
- Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Shuang Liang
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jun Zhou
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xianfeng Xu
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Xiaoyu Zhao
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Meng Zhu
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China
| | - Guangfu Jin
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China
| | - Hongxia Ma
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Juncheng Dai
- Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China
| | - Zhibin Hu
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; State Key Laboratory of Reproductive Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou Municipal Hospital, Gusu School, Nanjing Medical University, Nanjing, China.
| | - Hongbing Shen
- State Key Laboratory of Reproductive Medicine, School of Public Health, Nanjing Medical University, Nanjing, China; Department of Epidemiology, Centre for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Centre for Cancer Medicine, Nanjing Medical University, Nanjing, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China.
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14
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Wang R, Long T, He J, Xu Y, Wei Y, Zhang Y, He X, He M. Associations of multiple plasma metals with chronic kidney disease in patients with diabetes. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 244:114048. [PMID: 36063616 DOI: 10.1016/j.ecoenv.2022.114048] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/01/2022] [Revised: 08/14/2022] [Accepted: 08/30/2022] [Indexed: 06/15/2023]
Abstract
As common contaminants, metals are non-negligible risk factors for diabetes and chronic kidney disease. However, whether there is an association between multiple metals exposure and incident chronic kidney disease (CKD) risk in patients with diabetes is unclear. We conducted a prospective study to evaluate these associations. In total, 3071 diabetics with baseline estimated glomerular filtration rate (eGFR) ≥ 60 mL/min/1.73 m2 from the Dongfeng-Tongji cohort were included. We measured baseline plasma concentrations of 23 metals and investigated the associations between plasma metal concentrations and CKD in diabetics using logistic regression, the least absolute shrinkage and selection operator (LASSO), and the Bayesian Kernel Machine Regression (BKMR) models. During average 4.6 years of follow-up, 457 diabetics developed CKD (14.9 %). The three models consistently found plasma levels of zinc, arsenic, and rubidium had a positive association with incident CKD risk in patients with diabetes, while titanium, cadmium, and lead had an inverse correlation. The results of BKMR showed a significant and positive overall effect of 23 metals on the risk of CKD, when all of the metals were above the 50th percentile as compared to the median value. In addition, potential interactions of zinc and arsenic, zinc and cadmium, zinc and lead, titanium and arsenic, and cadmium and lead on CKD risk were observed. In summary, we found significant associations of plasma titanium, zinc, arsenic, rubidium, cadmium, and lead with CKD in diabetes and interactions between these metals except for rubidium. Co-exposure to multiple metals was associated with increased CKD risk in diabetics.
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Affiliation(s)
- Ruixin Wang
- 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, Hubei, China
| | - Tengfei Long
- 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, Hubei, China
| | - Jia 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, Hubei, China; Department of Public Health, Shihezi University School of Medicine, Shihezi 832000, Xinjiang, China
| | - Yali Xu
- 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, Hubei, China
| | - Yue Wei
- 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, Hubei, China
| | - Ying 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, Hubei, China
| | - Xiangjing 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, Hubei, 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, Hubei, China.
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15
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Turkez H, Yıldırım S, Sahin E, Arslan ME, Emsen B, Tozlu OO, Alak G, Ucar A, Tatar A, Hacimuftuoglu A, Keles MS, Geyikoglu F, Atamanalp M, Saruhan F, Mardinoglu A. Boron Compounds Exhibit Protective Effects against Aluminum-Induced Neurotoxicity and Genotoxicity: In Vitro and In Vivo Study. TOXICS 2022; 10:428. [PMID: 36006107 PMCID: PMC9413983 DOI: 10.3390/toxics10080428] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/01/2022] [Revised: 07/18/2022] [Accepted: 07/26/2022] [Indexed: 02/04/2023]
Abstract
Genetic, neuropathological and biochemical investigations have revealed meaningful relationships between aluminum (Al) exposure and neurotoxic and hematotoxic damage. Hence, intensive efforts are being made to minimize the harmful effects of Al. Moreover, boron compounds are used in a broad mix of industries, from cosmetics and pharmaceuticals to agriculture. They affect critical biological functions in cellular events and enzymatic reactions, as well as endocrinal and mineral metabolisms. There are limited dose-related data about boric acid (BA) and other boron compounds, including colemanite (Col), ulexite (UX) and borax (BX), which have commercial prominence. In this study, we evaluate boron compounds' genetic, cytological, biochemical and pathological effects against aluminum chloride (AlCl3)-induced hematotoxicity and neurotoxicity on different cell and animal model systems. First, we perform genotoxicity studies on in vivo rat bone marrow cells and peripheric human blood cultures. To analyze DNA and chromosome damage, we use single cell gel electrophoresis (SCGE or comet assay) and micronucleus (MN) and chromosome aberration (CA) assays. The nuclear division index (NDI) is used to monitor cytostasis. Second, we examine the biochemical parameters (superoxide dismutase (SOD), catalase (CAT), glutathione peroxidase (GSH-Px), malondialdehyde (MDA), total antioxidant capacity (TAC) and total oxidative status (TOS)) to determine oxidative changes in blood and brain. Next, we assess the histopathological alterations by using light and electron microscopes. Our results show that Al increases oxidative stress and genetic damage in blood and brain in vivo and in vitro studies. Al also led to severe histopathological and ultrastructural alterations in the brain. However, the boron compounds alone did not cause adverse changes based on the above-studied parameters. Moreover, these compounds exhibit different levels of beneficial effects by removing the harmful impact of Al. The antioxidant, antigenotoxic and cytoprotective effects of boron compounds against Al-induced damage indicate that boron may have a high potential for use in medical purposes in humans. In conclusion, our analysis suggests that boron compounds (especially BA, BX and UX) can be administered to subjects to prevent neurodegenerative and hematological disorders at determined doses.
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Affiliation(s)
- Hasan Turkez
- Department of Medical Biology, Faculty of Medicine, Atatürk University, 25240 Erzurum, Turkey;
| | - Serkan Yıldırım
- Department of Pathology, Faculty of Veterinary, Atatürk University, 25240 Erzurum, Turkey;
| | - Elvan Sahin
- Department of Histology and Embryology, Faculty of Medicine, Sakarya University, 54050 Sakarya, Turkey;
| | - Mehmet Enes Arslan
- Department of Molecular Biology and Genetics, Faculty of Science, Erzurum Technical University, 25050 Erzurum, Turkey; (M.E.A.); (O.O.T.)
| | - Bugrahan Emsen
- Department of Biology, Kamil Özdağ Faculty of Science, Karamanoğlu Mehmetbey University, 70200 Karaman, Turkey;
| | - Ozlem Ozdemir Tozlu
- Department of Molecular Biology and Genetics, Faculty of Science, Erzurum Technical University, 25050 Erzurum, Turkey; (M.E.A.); (O.O.T.)
| | - Gonca Alak
- Department of Aquaculture, Faculty of Fisheries, Atatürk University, 25240 Erzurum, Turkey; (G.A.); (A.U.); (M.A.)
| | - Arzu Ucar
- Department of Aquaculture, Faculty of Fisheries, Atatürk University, 25240 Erzurum, Turkey; (G.A.); (A.U.); (M.A.)
| | - Abdulgani Tatar
- Department of Medical Genetics, Medical Faculty, Atatürk University, 25240 Erzurum, Turkey;
| | - Ahmet Hacimuftuoglu
- Department of Medical Pharmacology, Medical Faculty, Atatürk University, 25240 Erzurum, Turkey; (A.H.); (F.S.)
| | - Mevlut Sait Keles
- Department of Biochemistry, Medical Faculty, Uskudar University, 34664 Istanbul, Turkey;
| | - Fatime Geyikoglu
- Department of Biology, Faculty of Arts and Sciences, Atatürk University, 25240 Erzurum, Turkey;
| | - Muhammed Atamanalp
- Department of Aquaculture, Faculty of Fisheries, Atatürk University, 25240 Erzurum, Turkey; (G.A.); (A.U.); (M.A.)
| | - Fatih Saruhan
- Department of Medical Pharmacology, Medical Faculty, Atatürk University, 25240 Erzurum, Turkey; (A.H.); (F.S.)
| | - Adil Mardinoglu
- Science for Life Laboratory, KTH-Royal Institute of Technology, 114 28 Stockholm, Sweden
- Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King’s College London, London WC2R 2LS, UK
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16
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Lai Z, He M, Lin C, Ouyang W, Liu X. Interactions of antimony with biomolecules and its effects on human health. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2022; 233:113317. [PMID: 35182796 DOI: 10.1016/j.ecoenv.2022.113317] [Citation(s) in RCA: 31] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 01/28/2022] [Accepted: 02/14/2022] [Indexed: 06/14/2023]
Abstract
Antimony (Sb) pollution has increased health risks to humans as a result of extensive application in diverse fields. Exposure to different levels of Sb and its compounds will directly or indirectly affect the normal function of the human body, whereas limited human health data and simulation studies delay the understanding of this element. In this review, we summarize current research on the effects of Sb on human health from different perspectives. First, the exposure pathways, concentration and excretion of Sb in humans are briefly introduced, and several studies have revealed that human exposure to high levels of Sb will cause higher concentrations in body tissues. Second, interactions between Sb and biomolecules or other nonbiomolecules affected biochemical processes such as gene expression and hormone secretion, which are vital for causing and understanding health effects and mechanisms. Finally, we discuss the different health effects of Sb at the biological level from small molecules to individual. In conclusion, exposure to high levels of Sb compounds will increase the risk of disease by affecting different cell signaling pathways. In addition, the appropriate form and dose of Sb contribute to inhibit the development of specific diseases. Key challenges and gaps in toxicity or benefit effects and mechanisms that still hinder risk assessment of human health are also identified in this review. Systematic studies on the relationships between the biochemical process of Sb and human health are needed.
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Affiliation(s)
- Ziyang Lai
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Mengchang He
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China.
| | - Chunye Lin
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Wei Ouyang
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
| | - Xitao Liu
- State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, No. 19 Xinjiekouwai Street, Beijing 100875, China
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17
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Dai X, Guo X. Decoding and rejuvenating human ageing genomes: Lessons from mosaic chromosomal alterations. Ageing Res Rev 2021; 68:101342. [PMID: 33866012 DOI: 10.1016/j.arr.2021.101342] [Citation(s) in RCA: 22] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2021] [Revised: 04/05/2021] [Accepted: 04/07/2021] [Indexed: 01/10/2023]
Abstract
One of the most curious findings emerged from genome-wide studies over the last decade was that genetic mosaicism is a dominant feature of human ageing genomes. The clonal dominance of genetic mosaicism occurs preceding the physiological and physical ageing and associates with propensity for diseases including cancer, Alzheimer's disease, cardiovascular disease and diabetes. These findings are revolutionizing the ways biologists thinking about health and disease pathogenesis. Among all mosaic mutations in ageing genomes, mosaic chromosomal alterations (mCAs) have the most significant functional consequences because they can produce intercellular genomic variations simultaneously involving dozens to hundreds or even thousands genes, and therefore have most profound effects in human ageing and disease etiology. Here, we provide a comprehensive picture of the landscapes, causes, consequences and rejuvenation of mCAs at multiple scales, from cell to human population, by reviewing data from cytogenetic, genetic and genomic studies in cells, animal models (fly and mouse) and, more frequently, large-cohort populations. A detailed decoding of ageing genomes with a focus on mCAs may yield important insights into the genomic architecture of human ageing, accelerate the risk stratification of age-related diseases (particularly cancers) and development of novel targets and strategies for delaying or rejuvenating human (genome) ageing.
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Affiliation(s)
- Xueqin Dai
- School of Life Sciences, Yunnan Normal University, Kunming, Yunnan, 650500, China
| | - Xihan Guo
- School of Life Sciences, Yunnan Normal University, Kunming, Yunnan, 650500, China; The Engineering Research Center of Sustainable Development and Utilization of Biomass Energy, Ministry of Education, Kunming, Yunnan, 650500, China; Yunnan Environmental Mutagen Society, Kunming, Yunnan, 650500, China.
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