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Lin CH, Liu WS, Wan C, Wang HH. PPARγ activation ameliorates PM2.5-induced renal tubular injury by inhibiting ferroptosis and epithelial-mesenchymal transition. Curr Res Toxicol 2024; 7:100189. [PMID: 39188272 PMCID: PMC11345305 DOI: 10.1016/j.crtox.2024.100189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2024] [Revised: 07/21/2024] [Accepted: 07/23/2024] [Indexed: 08/28/2024] Open
Abstract
Exposure to fine particulate matter (PM2.5) has been associated with the development and progression of renal disease. Peroxisome proliferator-activated receptor gamma (PPARγ), a key transcription factor involved in inflammation as well as lipid and glucose metabolism, helps maintain the integrity of tubular epithelial cells. However, the precise role of PPARγ in PM2.5-induced tubular injury remains unclear. In this study, we investigated the regulatory effects of PPARγ on PM2.5-induced ferroptotic stress and epithelial-mesenchymal transition (EMT) in tubular (HK-2) cells. We found that downregulation of PPARγ expression was correlated with EMT in PM2.5-exposed cells. Pretreatment with the PPARγ agonist 15d-PGJ2 protected the cells from EMT by reducing ferroptotic stress, whereas that with the PPARγ antagonist GW9662 promoted EMT. Furthermore, pretreatment with ferrostatin-1 (Fer-1) significantly prevented PM2.5-induced EMT and downregulation of PPARγ expression. Notably, overexpression of PPARγ blocked PM2.5-induced downregulation of E-cadherin and GPX4 expression and upregulation of α-SMA expression. This study highlights the complex associations of PPARγ with ferroptosis and EMT in PM2.5-exposed tubular cells. Our findings suggest that PPARγ activation confers protection against PM2.5-induced renal injury.
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Affiliation(s)
- Chien-Hung Lin
- Division of Pediatric Immunology and Nephrology, Department of Pediatrics, Taipei Veterans General Hospital, Taipei 112201, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- College of Science and Engineering, Fu Jen Catholic University, New Taipei 242062, Taiwan
| | - Wen-Sheng Liu
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- College of Science and Engineering, Fu Jen Catholic University, New Taipei 242062, Taiwan
- Division of Nephrology, Department of Medicine, Taipei City Hospital Zhongxing Branch, Taipei 10341, Taiwan
- Institute of Food Safety and Health Risk Assessment, National Yang Ming Chiao Tung University, Hsinchu 300093, Taiwan
- Department of Special Education, University of Taipei, Taipei 100234, Taiwan
| | - Chuan Wan
- Department of Pediatrics, Taipei City Hospital, Zhongxing Branch, Taipei 10341, Taiwan
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
| | - Hsin-Hui Wang
- Division of Pediatric Immunology and Nephrology, Department of Pediatrics, Taipei Veterans General Hospital, Taipei 112201, Taiwan
- School of Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
- Institute of Emergency and Critical Care Medicine, National Yang Ming Chiao Tung University, Taipei 112304, Taiwan
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2
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Zhao J, Mei Y, Li A, Zhou Q, Zhao M, Xu J, Li Y, Li K, Yang M, Xu Q. Association between PM 2.5 constituents and cardiometabolic risk factors: Exploring individual and combined effects, and mediating inflammation. CHEMOSPHERE 2024; 359:142251. [PMID: 38710413 DOI: 10.1016/j.chemosphere.2024.142251] [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: 01/22/2024] [Revised: 04/17/2024] [Accepted: 05/03/2024] [Indexed: 05/08/2024]
Abstract
BACKGROUND The individual and combined effects of PM2.5 constituents on cardiometabolic risk factors are sparsely investigated. Besides, the key cardiometabolic risk factor that PM2.5 constituents targeted and the biological mechanisms remain unclear. METHOD A multistage, stratified cluster sampling survey was conducted in two typically air-polluted Chinese cities. The PM2.5 and its constituents including sulfate, nitrate, ammonium, organic matter, and black carbon were predicted using a machine learning model. Twenty biomarkers in three category were simultaneously adopted as cardiometabolic risk factors. We explored the individual and mixture association of long-term PM2.5 constituents with these markers using generalized additive model and quantile-based g-computation, respectively. To minimize potential confounding effects, we accounted for covariates including demographic, lifestyle, meteorological, temporal trends, and disease-related information. We further used ROC curve and mediation analysis to identify the key subclinical indicators and explore whether inflammatory mediators mediate such association, respectively. RESULT PM2.5 constituents was positively correlated with HOMA-B, TC, TG, LDL-C and LCI, and negatively correlated with PP and RC. Further, PM2.5 constituent mixture was positive associated with DBP, MAP, HbA1c, HOMA-B, AC, CRI-1 and CRI-2, and negative associated with PP and HDL-C. The ROC analysis further reveals that multiple cardiometabolic risk factors can collectively discriminate exposure to PM2.5 constituents (AUC>0.9), among which PP and CRI-2 as individual indicators exhibit better identifiable performance for nitrate and ammonium (AUC>0.75). We also found that multiple blood lipid indicators may be affected by PM2.5 and its constituents, possibly mediated through complement C3 or hsCRP. CONCLUSION Our study suggested associations of individual and combined PM2.5 constituents exposure with cardiometabolic risk factors. PP and CRI-2 were the targeted markers of long-term exposure to nitrate and ammonium. Inflammation may serve as a mediating factor between PM2.5 constituents and dyslipidemia, which enhance current understanding of potential pathways for PM2.5-induced preclinical cardiovascular responses.
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Affiliation(s)
- Jiaxin 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
| | - 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; Big Data Center, Beijing Children's Hospital, Capital Medical University, National Center for Children's Health, Beijing, 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
| | - Quan Zhou
- 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
| | - 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
| | - 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
| | - Yanbing 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
| | - Kai 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
| | - Ming Yang
- 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
| | - 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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3
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Niu Z, Duan Z, He W, Chen T, Tang H, Du S, Sun J, Chen H, Hu Y, Iijima Y, Han S, Li J, Zhao Z. Kidney function decline mediates the adverse effects of per- and poly-fluoroalkyl substances (PFAS) on uric acid levels and hyperuricemia risk. JOURNAL OF HAZARDOUS MATERIALS 2024; 471:134312. [PMID: 38640681 DOI: 10.1016/j.jhazmat.2024.134312] [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: 01/06/2024] [Revised: 03/30/2024] [Accepted: 04/14/2024] [Indexed: 04/21/2024]
Abstract
Previous studies indicated per- and poly-fluoroalkyl substances (PFAS) were related to uric acid and hyperuricemia risk, but evidence for the exposure-response (E-R) curves and combined effect of PFAS mixture is limited. Moreover, the potential mediation effect of kidney function was not assessed. Hence, we conducted a national cross-sectional study involving 13,979 US adults in NHANES 2003-2018 to examine the associations of serum PFAS with uric acid and hyperuricemia risk, and the mediation effects of kidney function. Generalized linear models and E-R curves showed positive associations of individual PFAS with uric acid and hyperuricemia risk, and nearly linear E-R curves indicated no safe threshold for PFAS. Weighted quantile sum regression found positive associations of PFAS mixture with uric acid and hyperuricemia risk, and PFOA was the dominant contributor to the adverse effect of PFAS on uric acid and hyperuricemia risk. Causal mediation analysis indicated significant mediation effects of kidney function decline in the associations of PFAS with uric acid and hyperuricemia risk, with the mediated proportion ranging from 19 % to 57 %. Our findings suggested that PFAS, especially PFOA, may cause increased uric acid and hyperuricemia risk increase even at low levels, and kidney function decline plays a crucial mediation effect.
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Affiliation(s)
- Zhiping Niu
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Zhizhou Duan
- Preventive Health Service, Jiangxi Provincial People's Hospital, The First Affiliated Hospital of Nanchang Medical College, 152 Aiguo Road, Nanchang, Jiangxi, China
| | - Weixiang He
- Department of Urology, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, China
| | - Tianyi Chen
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Hao Tang
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Shuang Du
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Jin Sun
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Han Chen
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yuanzhuo Hu
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China
| | - Yuka Iijima
- Department of Clinical Medicine, Shanghai Medical College, Fudan University, Shanghai 200032, China
| | - Shichao Han
- Department of Urology, Xijing Hospital, The Fourth Military Medical University, 127 West Changle Road, Xi'an 710032, China.
| | - Jiufeng Li
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China.
| | - Zhuohui Zhao
- Department of Environmental Health, School of Public Health, NHC Key Laboratory of Health Technology Assessment, Key Laboratory of Public Health Safety of the Ministry of Education, Fudan University, Shanghai 200032, China; Shanghai Typhoon Institute/CMA, Shanghai Key Laboratory of Meteorology and Health, Shanghai 200030, China; IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai 200438, China; WMO/IGAC MAP-AQ Asian Office Shanghai, Fudan University, Shanghai 200438, China.
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Dai Y, Yin J, Li S, Li J, Han X, Deji Q, Pengcuo C, Liu L, Yu Z, Chen L, Xie L, Guo B, Zhao X. Long-term exposure to fine particulate matter constituents in relation to chronic kidney disease: evidence from a large population-based study in China. ENVIRONMENTAL GEOCHEMISTRY AND HEALTH 2024; 46:174. [PMID: 38592609 DOI: 10.1007/s10653-024-01949-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Accepted: 03/07/2024] [Indexed: 04/10/2024]
Abstract
The effects of long-term exposure to fine particulate matter (PM2.5) constituents on chronic kidney disease (CKD) are not fully known. This study sought to examine the association between long-term exposure to major PM2.5 constituents and CKD and look for potential constituents contributing substantially to CKD. This study included 81,137 adults from the 2018 to 2019 baseline survey of China Multi-Ethnic Cohort. CKD was defined by the estimated glomerular filtration rate. Exposure concentration data of 7 major PM2.5 constituents were assessed by satellite remote sensing. Logistic regression models were used to estimate the effect of each PM2.5 constituent exposure on CKD. The weighted quantile sum regression was used to estimate the effect of mixed exposure to all constituents. PM2.5 constituents had positive correlations with CKD (per standard deviation increase), with ORs (95% CIs) of 1.20 (1.02-1.41) for black carbon, 1.27 (1.07-1.51) for ammonium, 1.29 (1.08-1.55) for nitrate, 1.20 (1.01-1.43) for organic matter, 1.25 (1.06-1.46) for sulfate, 1.30 (1.11-1.54) for soil particles, and 1.63 (1.39-1.91) for sea salt. Mixed exposure to all constituents was positively associated with CKD (1.68, 1.32-2.11). Sea salt was the constituent with the largest weight (0.36), which suggested its importance in the PM2.5-CKD association, followed by nitrate (0.32), organic matter (0.18), soil particles (0.10), ammonium (0.03), BC (0.01). Sulfate had the least weight (< 0.01). Long-term exposure to PM2.5 sea salt and nitrate may contribute more than other constituents in increasing CKD risk, providing new evidence and insights for PM2.5-CKD mechanism research and air pollution control strategy.
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Affiliation(s)
- Yucen Dai
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Jianzhong Yin
- School of Public Health, Kunming Medical University, Kunming, China
- Baoshan College of Traditional Chinese Medicine, Baoshan, China
| | - Sicheng Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Jiawei Li
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | - Xinyu Han
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
| | | | - Ciren Pengcuo
- Tibet Center for Disease Control and Prevention CN, Lhasa, China
| | - Leilei Liu
- School of Public Health the Key Laboratory of Environmental Pollution Monitoring and Disease Control, Ministry of Education, Guizhou Medical University, Guiyang, China
| | - Zhimiao Yu
- Chengdu Center for Disease Control and Prevention, Chengdu, China
| | - Liling Chen
- Chongqing Municipal Center for Disease Control and Prevention, Chongqing, China
| | - Linshen Xie
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China.
| | - Bing Guo
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China.
| | - Xing Zhao
- West China School of Public Health and West China Fourth Hospital, Sichuan University, No.17, Section 3, South Renmin Road, Chengdu, 610041, Sichuan Province, China
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Peng S, Yin X, Chen G, Sun J, Chen B, Zhou Y, Li Z, Liu F, Xiang H. Long-term exposure to varying-sized particulate matters and kidney disease in middle-aged and elder adults: A 8-year nationwide cohort study in China. THE SCIENCE OF THE TOTAL ENVIRONMENT 2024; 911:168621. [PMID: 37977376 DOI: 10.1016/j.scitotenv.2023.168621] [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: 09/14/2023] [Revised: 11/07/2023] [Accepted: 11/14/2023] [Indexed: 11/19/2023]
Abstract
Evidence for the causal relationship of particulate matters (PMs) exposure with kidney disease, especially PM1, PM1-2.5 and PM2.5-10, remained scarce among developing countries with severe pollution. We conducted a longitudinal cohort study involving 13,041 adults with free kidney disease from 150 Chinese counties. PMs concentrations were generated using a well-established satellite-based spatiotemporal model. And the time-varying Cox regression model along with stratified analyses were performed to determine the association and potential modifiers, respectively. We also calculated the population-attributable fraction to evaluate the burden of kidney disease attributable to PMs pollution. Between Jan 2011 and Dec 2018, 985 kidney disease incidents were identified with an incidence rate of 12.69 per 1000 person-years. Significant dose-response relationships were observed for all 5 kinds PMs. Specifically, an increased risk of kidney disease was associated with per 10 μg/m3 increment of PM1 (HR = 1.187, 95%CI: 1.114 to 1.265), PM1-2.5 (1.326, 1.212 to 1.452), PM2.5 (1.197, 1.139 to 1.258), PM2.5-10 (1.297, 1.240 to 1.357), and PM10 (1.137, 1.108 to 1.166). A mixture analysis method of weighted quantile regression model revealed that PM2.5-10 predominated the PMs mixture index (57.1 %), and followed with PM10 (26.4 %). Stratified analyses indicated the elder, overweight persons, smokers, respiratory patients and urban residents were more vulnerable to PMs pollution than their counterparts. Calculated population attributable fractions of kidney disease attributable to PMs pollution was 16.67-39.47 %. Higher PMs pollution was associated with the increased risk of kidney disease development in China. Acceleration of efforts to reduce PMs pollution was therefore urgently needed to alleviate kidney disease burden.
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Affiliation(s)
- Shouxin Peng
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China; Global Health Institute, Wuhan University, Wuhan, Hubei 430071, China
| | - Xiaoyi Yin
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China
| | - Gongbo Chen
- Department of Epidemiology and Preventive Medicine, School of Public Health and Preventive Medicine, Monash University, Melbourne, VIC 3004, Australia
| | - Jinhui Sun
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China; Global Health Institute, Wuhan University, Wuhan, Hubei 430071, China
| | - Bingbing Chen
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China
| | - Yi Zhou
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China
| | - Zhaoyuan Li
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China; Global Health Institute, Wuhan University, Wuhan, Hubei 430071, China
| | - Feifei Liu
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China; Global Health Institute, Wuhan University, Wuhan, Hubei 430071, China
| | - Hao Xiang
- Global Health Department, School of Public Health, Wuhan University, Wuhan, Hubei 430071, China; Global Health Institute, Wuhan University, Wuhan, Hubei 430071, China.
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Wathanavasin W, Banjongjit A, Phannajit J, Eiam-Ong S, Susantitaphong P. Association of fine particulate matter (PM 2.5) exposure and chronic kidney disease outcomes: a systematic review and meta-analysis. Sci Rep 2024; 14:1048. [PMID: 38200164 PMCID: PMC10781728 DOI: 10.1038/s41598-024-51554-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Accepted: 01/06/2024] [Indexed: 01/12/2024] Open
Abstract
Several studies have reported an increased risk of chronic kidney disease (CKD) outcomes after long-term exposure (more than 1 year) to particulate matter with an aerodynamic diameter of ≤ 2.5 µm (PM2.5). However, the conclusions remain inconsistent. Therefore, we conducted this meta-analysis to examine the association between long-term PM2.5 exposure and CKD outcomes. A literature search was conducted in PubMed, Scopus, Cochrane Central Register of Controlled trials, and Embase for relevant studies published until August 10, 2023. The main outcomes were incidence and prevalence of CKD as well as incidence of end-stage kidney disease (ESKD). The random-effect model meta-analyses were used to estimate the risk of each outcome among studies. Twenty two studies were identified, including 14 cohort studies, and 8 cross-sectional studies, with a total of 7,967,388 participants. This meta-analysis revealed that each 10 μg/m3 increment in PM2.5 was significantly associated with increased risks of both incidence and prevalence of CKD [adjusted odds ratio (OR) 1.31 (95% confidence interval (CI) 1.24 to 1.40), adjusted OR 1.31 (95% CI 1.03 to 1.67), respectively]. In addition, the relationship with ESKD incidence is suggestive of increased risk but not conclusive (adjusted OR 1.16; 95% CI 1.00 to 1.36). The incidence and prevalence of CKD outcomes had a consistent association across all subgroups and adjustment variables. Our study observed an association between long-term PM2.5 exposure and the risks of CKD. However, more dedicated studies are required to show causation that warrants urgent action on PM2.5 to mitigate the global burden of CKD.
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Affiliation(s)
- Wannasit Wathanavasin
- Nephrology Unit, Department of Medicine, Charoenkrung Pracharak Hospital, Bangkok Metropolitan Administration, Bangkok, Thailand
| | - Athiphat Banjongjit
- Nephrology Unit, Department of Medicine, Vichaiyut Hospital, Bangkok, Thailand
| | - Jeerath Phannajit
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
- Division of Clinical Epidemiology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
- Center of Excellence for Metabolic Bone Disease in CKD Patients, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand
| | - Somchai Eiam-Ong
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand
| | - Paweena Susantitaphong
- Division of Nephrology, Department of Medicine, Faculty of Medicine, Chulalongkorn University, Bangkok, 10330, Thailand.
- Center of Excellence for Metabolic Bone Disease in CKD Patients, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.
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Peng S, Chen B, Li Z, Sun J, Liu F, Yin X, Zhou Y, Shen H, Xiang H. Ambient ozone pollution impairs glucose homeostasis and contributes to renal function decline: Population-based evidence. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY 2024; 269:115803. [PMID: 38091674 PMCID: PMC10790241 DOI: 10.1016/j.ecoenv.2023.115803] [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: 08/26/2023] [Revised: 12/04/2023] [Accepted: 12/06/2023] [Indexed: 01/12/2024]
Abstract
Particulate matter pollution could increase the risk of kidney disease, while evidence for ozone exposure is less well-established. Here, we aimed to evaluate the effect of ozone pollution on renal function and explore mechanisms. We first conducted a cross-sectional study based on Wuhan Chronic Disease Cohort Study baseline information. We recruited 2699 eligible participants, estimated their residential ozone concentrations, collected fasting peripheral blood samples for biochemical analysis and calculated the estimated glomerular filtration rate (eGFR). The linear regression model was applied to evaluate the long-term association between ozone pollution and eGFR. Then, we recruited another 70 volunteers as a panel with 8 rounds follow-up visits. We calculated the eGFR and measured fasting blood glucose and lipid levels. The linear mixed-effect model along with mediation analysis were performed to confirm the short-term association and explore potential mechanisms, respectively. For the long-term association, a 10.95 μg/m3 increment of 3-year ozone exposure was associated with 2.96 mL/min/1.73 m2 decrease in eGFR (95%CI: -4.85, -1.06). Furthermore, the drinkers exhibited a pronounced declination of eGFR (-7.46 mL/min/1.73 m2, 95%CI: -11.84, -3.08) compared to non-drinkers in relation to ozone exposure. Additionally, a 19.02 μg/m3 increase in 3-day ozone concentrations was related to 2.51 mL/min/1.73 m2 decrease in eGFR (95%CI: -3.78, -1.26). Hyperglycemia and insulin resistance mediated 12.2% and 16.5% of the aforementioned association, respectively. Our findings indicated that higher ozone pollution could affect renal function, and the hyperglycemia and insulin resistance linked to ozone might be the underlying mechanisms.
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Affiliation(s)
- Shouxin Peng
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China; Global Health Institute, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Bingbing Chen
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Zhaoyuan Li
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China; Global Health Institute, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Jinhui Sun
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China; Global Health Institute, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Feifei Liu
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China; Global Health Institute, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Xiaoyi Yin
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Yi Zhou
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China
| | - Huanfeng Shen
- School of Resource and Environmental Sciences, Wuhan University, Wuhan 430079, Hubei, PR China.
| | - Hao Xiang
- Department of Global Health, School of Public Health, Wuhan University, Wuhan 430071, Hubei, PR China; Global Health Institute, Wuhan University, Wuhan 430071, Hubei, PR China.
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