1
|
Pu F, Chen W, Li C, Fu J, Gao W, Ma C, Cao X, Zhang L, Hao M, Zhou J, Huang R, Ma Y, Hu K, Liu Z. Heterogeneous associations of multiplexed environmental factors and multidimensional aging metrics. Nat Commun 2024; 15:4921. [PMID: 38858361 PMCID: PMC11164970 DOI: 10.1038/s41467-024-49283-0] [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: 10/24/2023] [Accepted: 05/31/2024] [Indexed: 06/12/2024] Open
Abstract
Complicated associations between multiplexed environmental factors and aging are poorly understood. We manipulated aging using multidimensional metrics such as phenotypic age, brain age, and brain volumes in the UK Biobank. Weighted quantile sum regression was used to examine the relative individual contributions of multiplexed environmental factors to aging, and self-organizing maps (SOMs) were used to examine joint effects. Air pollution presented a relatively large contribution in most cases. We also found fair heterogeneities in which the same environmental factor contributed inconsistently to different aging metrics. Particulate matter contributed the most to variance in aging, while noise and green space showed considerable contribution to brain volumes. SOM identified five subpopulations with distinct environmental exposure patterns and the air pollution subpopulation had the worst aging status. This study reveals the heterogeneous associations of multiplexed environmental factors with multidimensional aging metrics and serves as a proof of concept when analyzing multifactors and multiple outcomes.
Collapse
Affiliation(s)
- Fan Pu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Weiran Chen
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Chenxi Li
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Jingqiao Fu
- Ocean College, Zhejiang University, Zhoushan, 316021, Zhejiang, China
| | - Weijing Gao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Chao Ma
- School of Economics and Management, Southeast University, Nanjing, 211189, Jiangsu, China
| | - Xingqi Cao
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Lingzhi Zhang
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China
| | - Meng Hao
- State Key Laboratory of Genetic Engineering, Collaborative Innovation Center for Genetics and Development, School of Life Sciences and Human Phenome Institute, Fudan University, Shanghai, 200433, China
| | - Jin Zhou
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University; Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China
| | - Rong Huang
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University; Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China
| | - Yanan Ma
- Key Laboratory of Environmental Stress and Chronic Disease Control & Prevention, Ministry of Education, China Medical University; Department of Biostatistics and Epidemiology, School of Public Health, China Medical University, Shenyang, 110122, Liaoning, China.
| | - Kejia Hu
- Department of Big Data in Health Science School of Public Health, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China.
| | - Zuyun Liu
- Center for Clinical Big Data and Analytics of the Second Affiliated Hospital, and Department of Big Data in Health Science School of Public Health, The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Zhejiang University School of Medicine, Hangzhou, 310058, Zhejiang, China.
| |
Collapse
|
2
|
Geng R, Yu M, Xu J, Wei Y, Wang Q, Chen J, Sun F, Xu K, Xu H, Liu X, Xiao J, Zhang X, Xie B. Amino acids analysis reveals serum methionine contributes to diagnosis of the Kawasaki disease in mice and children. J Pharm Biomed Anal 2024; 239:115873. [PMID: 38008045 DOI: 10.1016/j.jpba.2023.115873] [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: 09/09/2023] [Revised: 11/05/2023] [Accepted: 11/21/2023] [Indexed: 11/28/2023]
Abstract
BACKGROUND Kawasaki disease (KD) patients often lack early and definitive diagnosis due to insufficient clinical criteria, whereas biomarkers might accelerate the diagnostic process and treatment. METHODS The KD mouse models were established and thirteen amino acids were determined. A total of 551 serum samples were collected including KD patients (n = 134), HCs (n = 223) and KD patients after intravascular immunoglobulin therapy (IVIG, n = 194). A paired analysis of pre- and post-IVIG was employed in 10 KD patients. RESULTS The pathological alterations of the aorta, myocardial interstitium and coronary artery vessel were observed in KD mice; the serum levels of methionine in KD mice (n = 40) were markedly altered and negatively correlated with the C-reactive protein levels. Consistent with the mouse model, serum methionine were significantly decreased in KD children, with the relative variation ratio of KD with HCs above 30% and AUROC value of 0.845. Serum methionine were correlated with Z-Score and significantly restored to the normal ranges after KD patient IVIG treatment. Another case-control study with 10 KD patients with IVIG sensitivity and 20 healthy controls validated serum methionine as a biomarker for KD patients with AUROC of 0.86. Elevation of serum DNMT1 activities, but no differences of DNMT3a and DNMT3b, were observed in KD patients when comparing with those in the HCs. CONCLUSIONS Our study validated that serum methionine was a potential biomarker for KD, the alteration of which is associated with the activation of DNMT1 in KD patients.
Collapse
Affiliation(s)
- Ruijin Geng
- Medical College of Jiaxing University, Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province, Jiaxing University, Jiaxing 314001, China; School of Pharmaceutical Science, Nanchang University, Nanchang 330001, China
| | - Mengjie Yu
- School of Pharmaceutical Science, Nanchang University, Nanchang 330001, China
| | - Jinbiao Xu
- Medical College of Jiaxing University, Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province, Jiaxing University, Jiaxing 314001, China
| | - Yuanwang Wei
- Medical College of Jiaxing University, Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province, Jiaxing University, Jiaxing 314001, China
| | - Qiong Wang
- Department of Pediatrics, the Second Affiliated Hospital of Jiaxing University, Jiaxing 314001, China
| | - Junguo Chen
- Department of Pediatrics, the Second Affiliated Hospital of Jiaxing University, Jiaxing 314001, China
| | - Fei Sun
- Department of Pediatrics, the Affiliated Hospital of Jiaxing University, Jiaxing 314001, China
| | - Kun Xu
- Department of General Surgery, Jiangxi Provincial Children's Hospital, Nanchang 330001, China
| | - Han Xu
- Department of General Surgery, Jiangxi Provincial Children's Hospital, Nanchang 330001, China
| | - Xiaohui Liu
- Department of General Surgery, Jiangxi Provincial Children's Hospital, Nanchang 330001, China
| | - Juhua Xiao
- Department of Ultrasound, Jiangxi Provincial Maternal and Child Health Hospital, Nanchang 330001, China.
| | - Xianchao Zhang
- Medical College of Jiaxing University, Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province, Jiaxing University, Jiaxing 314001, China.
| | - Baogang Xie
- Medical College of Jiaxing University, Key Laboratory of Medical Electronics and Digital Health of Zhejiang Province, Jiaxing University, Jiaxing 314001, China; School of Pharmaceutical Science, Nanchang University, Nanchang 330001, China.
| |
Collapse
|
3
|
Casella C, Kiles F, Urquhart C, Michaud DS, Kirwa K, Corlin L. Methylomic, Proteomic, and Metabolomic Correlates of Traffic-Related Air Pollution in the Context of Cardiorespiratory Health: A Systematic Review, Pathway Analysis, and Network Analysis. TOXICS 2023; 11:1014. [PMID: 38133415 PMCID: PMC10748071 DOI: 10.3390/toxics11121014] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/03/2023] [Revised: 11/18/2023] [Accepted: 12/06/2023] [Indexed: 12/23/2023]
Abstract
A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead to cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease and highlight contemporary challenges and opportunities associated with such efforts.
Collapse
Affiliation(s)
- Cameron Casella
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Frances Kiles
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Catherine Urquhart
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
| | - Kipruto Kirwa
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
- Department of Environmental Health, Boston University School of Public Health, Boston, MA 02118, USA
| | - Laura Corlin
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA; (C.C.); (F.K.); (C.U.); (D.S.M.); (K.K.)
- Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA 02155, USA
| |
Collapse
|
4
|
Casella C, Kiles F, Urquhart C, Michaud DS, Kirwa K, Corlin L. Methylomic, proteomic, and metabolomic correlates of traffic-related air pollution: A systematic review, pathway analysis, and network analysis relating traffic-related air pollution to subclinical and clinical cardiorespiratory outcomes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.30.23296386. [PMID: 37873294 PMCID: PMC10592990 DOI: 10.1101/2023.09.30.23296386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
A growing body of literature has attempted to characterize how traffic-related air pollution (TRAP) affects molecular and subclinical biological processes in ways that could lead to cardiorespiratory disease. To provide a streamlined synthesis of what is known about the multiple mechanisms through which TRAP could lead cardiorespiratory pathology, we conducted a systematic review of the epidemiological literature relating TRAP exposure to methylomic, proteomic, and metabolomic biomarkers in adult populations. Using the 139 papers that met our inclusion criteria, we identified the omic biomarkers significantly associated with short- or long-term TRAP and used these biomarkers to conduct pathway and network analyses. We considered the evidence for TRAP-related associations with biological pathways involving lipid metabolism, cellular energy production, amino acid metabolism, inflammation and immunity, coagulation, endothelial function, and oxidative stress. Our analysis suggests that an integrated multi-omics approach may provide critical new insights into the ways TRAP could lead to adverse clinical outcomes. We advocate for efforts to build a more unified approach for characterizing the dynamic and complex biological processes linking TRAP exposure and subclinical and clinical disease, and highlight contemporary challenges and opportunities associated with such efforts.
Collapse
Affiliation(s)
- Cameron Casella
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Frances Kiles
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Catherine Urquhart
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Dominique S. Michaud
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
| | - Kipruto Kirwa
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
- Department of Environmental Health, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Laura Corlin
- Department of Public Health and Community Medicine, Tufts University School of Medicine, Boston, MA 02111, USA
- Department of Civil and Environmental Engineering, Tufts University School of Engineering, Medford, MA 02155, USA
| |
Collapse
|
5
|
Tyan YS, Shen CY, Tantoh DM, Hsu SY, Chou YH, Nfor ON, Liaw YP. Association between ESR1 rs2234693 single nucleotide polymorphism and uterine fibroids in Taiwanese premenopausal and postmenopausal women. JOURNAL OF HEALTH, POPULATION, AND NUTRITION 2023; 42:16. [PMID: 36890612 PMCID: PMC9993586 DOI: 10.1186/s41043-023-00357-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/13/2022] [Accepted: 02/28/2023] [Indexed: 06/18/2023]
Abstract
BACKGROUND Uterine fibroids (UFs) are uterine smooth muscle neoplasms that affect women, especially during the reproductive stage. Both genetic and lifestyle factors affect the onset of the disease. We examined the association between the estrogen receptor 1 (ESR1) rs2234693 variant (whose genotypes are TT, TC, and CC) and UFs in Taiwanese premenopausal and postmenopausal women. METHODS We linked individual-level data of 3588 participants from the Taiwan Biobank to the National Health Insurance Research Database at the Health and Welfare Data Science Center. The association of the ESR1 rs2234693 variant and other variables with UFs was determined by multiple logistic regression, and the results were presented as odds ratios and 95% confidence intervals (CIs). RESULTS The 3588 participants comprised 622 cases and 2966 controls. In all the participants, the ESR1 rs2234693 TC and CC genotypes compared to the reference genotype (TT) were associated with a lower risk of UFs. However, the results were significant only for the CC genotype (OR; 95% CI = 0.70; 0.52-0.93). Noteworthy, the association of TC and CC with UFs was dose-dependent (p-trend = 0.012). Based on menopausal status, both TC and CC were significantly and dose-dependently associated with a lower risk of UFs in premenopausal women (OR; 95% CI = 0.76; 0.59-0.98 for TC and 0.64; 0.43-0.95 for CC: p-trend = 0.010). CONCLUSION The TC and CC genotypes of the ESR1 rs2234693 variant may reduce susceptibility to UFs, especially in premenopausal women.
Collapse
Affiliation(s)
- Yeu-Sheng Tyan
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung City, 40201, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung City, 40201, Taiwan
- School of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung City, 40201, Taiwan
- Medical Imaging and Big Data Center, Chung Shan Medical University Hospital, Taichung City, 40201, Taiwan
| | - Chao-Yu Shen
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung City, 40201, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung City, 40201, Taiwan
- School of Medical Informatics, Chung Shan Medical University, Taichung City, 40201, Taiwan
| | - Disline Manli Tantoh
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung City, 40201, Taiwan
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110, Sec. 1 Jianguo N. Rd., Taichung City, 40201, Taiwan
| | - Shu-Yi Hsu
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110, Sec. 1 Jianguo N. Rd., Taichung City, 40201, Taiwan
| | - Ying-Hsiang Chou
- School of Medical Imaging and Radiological Sciences, Chung Shan Medical University, Taichung City, 40201, Taiwan
- Department of Radiation Oncology, Chung Shan Medical University Hospital, Taichung, 40201, Taiwan
- Institute of Medicine, Chung Shan Medical University, Taichung City, 40201, Taiwan
| | - Oswald Ndi Nfor
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110, Sec. 1 Jianguo N. Rd., Taichung City, 40201, Taiwan
| | - Yung-Po Liaw
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung City, 40201, Taiwan.
- Medical Imaging and Big Data Center, Chung Shan Medical University Hospital, Taichung City, 40201, Taiwan.
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110, Sec. 1 Jianguo N. Rd., Taichung City, 40201, Taiwan.
| |
Collapse
|
6
|
Zhao L, Zhang M, Bai L, Zhao Y, Cai Z, Yung KKL, Dong C, Li R. Real-world PM 2.5 exposure induces pathological injury and DNA damage associated with miRNAs and DNA methylation alteration in rat lungs. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH INTERNATIONAL 2022; 29:28788-28803. [PMID: 34988794 DOI: 10.1007/s11356-021-17779-7] [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: 08/26/2021] [Accepted: 11/23/2021] [Indexed: 06/14/2023]
Abstract
Fine particulate matter (PM2.5) has been demonstrated to threaten public health and increase lung cancer risk. DNA damage is involved in the pathogenesis of lung cancer. However, the mechanisms of epigenetic modification of lung DNA damage are still unclear. This study developed a real-world air PM2.5 inhalation system and exposed rats for 1 and 2 months, respectively, and investigated rat lungs pathological changes, inflammation, oxidative stress, and DNA damage effects. OGG1 and MTH1 expression was measured, along with their DNA methylation status and related miRNAs expression. The results showed that PM2.5 exposure led to pathological injury, influenced levels of inflammatory cytokines and oxidative stress factors in rat lungs. Of note, 2-month PM2.5 exposure aggravated pathological injury. Besides, PM2.5 significantly elevated OGG1 expression and suppressed MTH1 expression, which was correlated to oxidative stress and partially mediated by reducing OGG1 DNA methylation status and increasing miRNAs expression related to MTH1 in DNA damage with increases of γ-H2AX, 8-OHdG and GADD153. PM2.5 also activated c-fos and c-jun levels and inactivated PTEN levels in rat lungs. These suggested that epigenetic modification was probably a potential mechanism by which PM2.5-induced genotoxicity in rat lungs.
Collapse
Affiliation(s)
- Lifang Zhao
- Institute of Environmental Science, Shanxi University, Taiyuan, China
| | - Mei Zhang
- Institute of Environmental Science, Shanxi University, Taiyuan, China
| | - Lirong Bai
- Institute of Environmental Science, Shanxi University, Taiyuan, China
| | - Yufei Zhao
- Institute of Environmental Science, Shanxi University, Taiyuan, China
| | - Zongwei Cai
- State Key Laboratory of Environmental and Biological Analysis, Hong Kong Baptist University, Hong Kong SAR, China
| | - Ken Kin Lam Yung
- Institute of Environmental Science, Shanxi University, Taiyuan, China
- Department of Biology, Hong Kong Baptist University, Hong Kong SAR, China
| | - Chuan Dong
- Institute of Environmental Science, Shanxi University, Taiyuan, China.
| | - Ruijin Li
- Institute of Environmental Science, Shanxi University, Taiyuan, China.
| |
Collapse
|
7
|
Wu Y, Qie R, Cheng M, Zeng Y, Huang S, Guo C, Zhou Q, Li Q, Tian G, Han M, Zhang Y, Wu X, Li Y, Zhao Y, Yang X, Feng Y, Liu D, Qin P, Hu D, Hu F, Xu L, Zhang M. Air pollution and DNA methylation in adults: A systematic review and meta-analysis of observational studies. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2021; 284:117152. [PMID: 33895575 DOI: 10.1016/j.envpol.2021.117152] [Citation(s) in RCA: 26] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Revised: 04/04/2021] [Accepted: 04/05/2021] [Indexed: 05/24/2023]
Abstract
This systematic review and meta-analysis aimed to investigate the association between air pollution and DNA methylation in adults from published observational studies. PubMed, Web of Science and Embase databases were systematically searched for available studies on the association between air pollution and DNA methylation published up to March 9, 2021. Three DNA methylation approaches were considered: global methylation, candidate-gene, and epigenome-wide association studies (EWAS). Meta-analysis was used to summarize the combined estimates for the association between air pollutants and global DNA methylation levels. Heterogeneity was assessed with the Cochran Q test and quantified with the I2 statistic. In total, 38 articles were included in this study: 16 using global methylation, 18 using candidate genes, and 11 using EWAS, with 7 studies using more than one approach. Meta-analysis revealed an imprecise but inverse association between exposure to PM2.5 and global DNA methylation (for each 10-μg/m3 PM2.5, combined estimate: 0.39; 95% confidence interval: 0.97 - 0.19). The candidate-gene results were consistent for the ERCC3 and SOX2 genes, suggesting hypermethylation in ERCC3 associated with benzene and that in SOX2 associated with PM2.5 exposure. EWAS identified 201 CpG sites and 148 differentially methylated regions that showed differential methylation associated with air pollution. Among the 307 genes investigated in 11 EWAS, a locus in nucleoredoxin gene was found to be positively associated with PM2.5 in two studies. Current meta-analysis indicates that PM2.5 is imprecisely and inversely associated with DNA methylation. The candidate-gene results consistently suggest hypermethylation in ERCC3 associated with benzene exposure and that in SOX2 associated with PM2.5 exposure. The Kyoto Encyclopedia of Genes and Genomes (KEGG) network analyses revealed that these genes were associated with African trypanosomiasis, Malaria, Antifolate resistance, Graft-versus-host disease, and so on. More evidence is needed to clarify the association between air pollution and DNA methylation.
Collapse
Affiliation(s)
- Yuying Wu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Ranran Qie
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Min Cheng
- Department of Cardiology, Shenzhen Second People's Hospital, The First Affiliated Hospital of Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yunhong Zeng
- Center for Health Management, The Affiliated Shenzhen Hospital of University of Chinese Academy of Sciences, Shenzhen, Guangdong, People's Republic of China
| | - Shengbing Huang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Chunmei Guo
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Qionggui Zhou
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Quanman Li
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Gang Tian
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Minghui Han
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yanyan Zhang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Xiaoyan Wu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yang Li
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Yang Zhao
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Xingjin Yang
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Yifei Feng
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Dechen Liu
- Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Pei Qin
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Dongsheng Hu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Department of Epidemiology and Biostatistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China
| | - Fulan Hu
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Lidan Xu
- Department of Nutrition, The Second Affiliated Hospital, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China
| | - Ming Zhang
- Department of Biostatistics and Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Regional Immunity and Diseases, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
| |
Collapse
|
8
|
Liu YR, Tantoh DM, Lin CC, Hsiao CH, Liaw YP. Risk of gout among Taiwanese adults with ALDH-2 rs671 polymorphism according to BMI and alcohol intake. Arthritis Res Ther 2021; 23:115. [PMID: 33858492 PMCID: PMC8048165 DOI: 10.1186/s13075-021-02497-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Accepted: 03/29/2021] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND Gout stems from both modifiable and genetic sources. We evaluated the risk of gout among Taiwanese adults with aldehyde dehydrogenase-2 (ALDH2) rs671 single nucleotide polymorphism (SNP) according to body mass index (BMI) and alcohol drinking. METHODS We obtained information of 9253 individuals having no personal history of cancer from the Taiwan Biobank (2008-2016) and estimated the association between gout and independent variables (e.g., rs671, BMI, and alcohol drinking) using multiple logistic regression. RESULTS Alcohol drinking and abnormal BMI were associated with a higher risk of gout whereas the rs671 GA+AA genotype was associated with a lower risk. The odds ratios (ORs) and 95% confidence intervals (CIs) were 1.297 and 1.098-1.532 for alcohol drinking, 1.550 and 1.368-1.755 for abnormal BMI, and 0.887 and 0.800-0.984 for GA+AA. The interaction between BMI and alcohol on gout was significant for GG (p-value = 0.0102) and GA+AA (p-value = 0.0175). When we stratified genotypes by BMI, alcohol drinking was significantly associated with gout only among individuals with a normal BMI (OR; 95% CI = 1.533; 1.036-2.269 for GG and 2.109; 1.202-3.699 for GA+AA). Concerning the combination of BMI and alcohol drinking among participants stratified by genotypes (reference, GG genotype, normal BMI, and no alcohol drinking), the risk of gout was significantly higher in the following categories: GG, normal BMI, and alcohol drinking (OR, 95% CI = 1.929, 1.385-2.688); GG, abnormal BMI, and no alcohol drinking (OR, 95% CI, = 1.721, 1.442-2.052); GG, abnormal BMI, and alcohol drinking (OR, 95% CI = 1.941, 1.501-2.511); GA+AA, normal BMI, and alcohol drinking (OR, 95% CI = 1.971, 1.167-3.327); GA+AA, abnormal BMI, and no alcohol drinking (OR, 95% CI = 1.498, 1.256-1.586); and GA+AA, abnormal BMI, and alcohol drinking (OR, 95% CI = 1.545, 1.088-2.194). CONCLUSIONS Alcohol and abnormal BMI were associated with a higher risk of gout, whereas the rs671 GA+AA genotype was associated with a lower risk. Noteworthy, BMI and alcohol had a significant interaction on gout risk. Stratified analyses revealed that alcohol drinking especially among normal-weight individuals might elevate the risk of gout irrespective of the genotype.
Collapse
Affiliation(s)
- Yu-Ruey Liu
- Department of Emergency Medicine, Chung-Kang Branch, Cheng Ching Hospital, Taichung City, 407, Taiwan
| | - Disline Manli Tantoh
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung City, Taiwan
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110 Sec. 1 Jianguo N. Road, Taichung City, 40201, Taiwan
| | - Chuan-Chao Lin
- Department of Physical Medicine and Rehabilitation, Chung Shan Medical University Hospital, Taichung City, Taiwan
- School of Medicine, Chung Shan Medical University, Taichung City, Taiwan
| | - Chih-Hsuan Hsiao
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110 Sec. 1 Jianguo N. Road, Taichung City, 40201, Taiwan
| | - Yung-Po Liaw
- Department of Medical Imaging, Chung Shan Medical University Hospital, Taichung City, Taiwan.
- Department of Public Health and Institute of Public Health, Chung Shan Medical University, No. 110 Sec. 1 Jianguo N. Road, Taichung City, 40201, Taiwan.
| |
Collapse
|
9
|
Avery-Kiejda KA. Switching off Cancer: Is There a Role for Epigenetics? Cancers (Basel) 2021; 13:cancers13061272. [PMID: 33809396 PMCID: PMC7998574 DOI: 10.3390/cancers13061272] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2021] [Accepted: 03/08/2021] [Indexed: 12/16/2022] Open
Affiliation(s)
- Kelly A. Avery-Kiejda
- School of Biomedical Sciences and Pharmacy, College of Health, Medicine and Wellbeing, University of Newcastle, Callaghan, NSW 2308, Australia;
- Hunter Medical Research Institute, New Lambton Heights, NSW 2305, Australia
| |
Collapse
|