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Orach J, Hemshekhar M, Rider CF, Spicer V, Lee AH, Yuen ACY, Mookherjee N, Carlsten C. Concentration-dependent alterations in the human plasma proteome following controlled exposure to diesel exhaust. ENVIRONMENTAL POLLUTION (BARKING, ESSEX : 1987) 2024; 342:123087. [PMID: 38061431 DOI: 10.1016/j.envpol.2023.123087] [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: 08/03/2023] [Revised: 11/24/2023] [Accepted: 12/01/2023] [Indexed: 12/17/2023]
Abstract
Traffic-related air pollution (TRAP) exposure is associated with systemic health effects, which can be studied using blood-based markers. Although we have previously shown that high TRAP concentrations alter the plasma proteome, the concentration-response relationship between blood proteins and TRAP is unexplored in controlled human exposure studies. We aimed to identify concentration-dependent plasma markers of diesel exhaust (DE), a model of TRAP. Fifteen healthy non-smokers were enrolled into a double-blinded, crossover study where they were exposed to filtered air (FA) and DE at 20, 50 and 150 μg/m3 PM2.5 for 4h, separated by ≥ 4-week washouts. We collected blood at 24h post-exposure and used label-free mass spectrometry to quantify proteins in plasma. Proteins exhibiting a concentration-response, as determined by linear mixed effects models (LMEMs), were assessed for pathway enrichment using WebGestalt. Top candidates, identified by sparse partial least squares discriminant analysis and LMEMs, were confirmed using enzyme-linked immunoassays. Thereafter, we assessed correlations between proteins that showed a DE concentration-response and acute inflammatory endpoints, forced expiratory volume in 1 s (FEV1) and methacholine provocation concentration causing a 20% drop in FEV1 (PC20). DE exposure was associated with concentration-dependent alterations in 45 proteins, which were enriched in complement pathways. Of the 9 proteins selected for confirmatory immunoassays, based on complementary bioinformatic approaches to narrow targets and availability of high-quality assays, complement factor I (CFI) exhibited a significant concentration-dependent decrease (-0.02 μg/mL per μg/m3 of PM2.5, p = 0.04). Comparing to FA at discrete concentrations, CFI trended downward at 50 (-2.14 ± 1.18, p = 0.08) and significantly decreased at 150 μg/m3 PM2.5 (-2.93 ± 1.18, p = 0.02). CFI levels were correlated with FEV1, PC20 and nasal interleukin (IL)-6 and IL-1β. This study details concentration-dependent alterations in the plasma proteome following DE exposure at concentrations relevant to occupational and community settings. CFI shows a robust concentration-response and association with established measures of airway function and inflammation.
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Affiliation(s)
- Juma Orach
- Air Pollution Exposure Laboratory, Division of Respiratory Medicine, Department of Medicine, Vancouver Coastal Health Research Institute, The University of British Columbia, British Columbia, Vancouver, V5Z1W9, Canada
| | - Mahadevappa Hemshekhar
- Manitoba Center for Proteomics and Systems Biology, Department of Internal Medicine, University of Manitoba, Manitoba, Winnipeg, R3E 3P4, Canada
| | - Christopher Francis Rider
- Air Pollution Exposure Laboratory, Division of Respiratory Medicine, Department of Medicine, Vancouver Coastal Health Research Institute, The University of British Columbia, British Columbia, Vancouver, V5Z1W9, Canada
| | - Victor Spicer
- Manitoba Center for Proteomics and Systems Biology, Department of Internal Medicine, University of Manitoba, Manitoba, Winnipeg, R3E 3P4, Canada
| | - Amy H Lee
- Molecular Biology and Biochemistry, Department of Molecular Biology and Biochemistry, Simon Fraser University, British Columbia, Burnaby, V5A 1S6, Canada
| | - Agnes Che Yan Yuen
- Air Pollution Exposure Laboratory, Division of Respiratory Medicine, Department of Medicine, Vancouver Coastal Health Research Institute, The University of British Columbia, British Columbia, Vancouver, V5Z1W9, Canada
| | - Neeloffer Mookherjee
- Manitoba Center for Proteomics and Systems Biology, Department of Internal Medicine, University of Manitoba, Manitoba, Winnipeg, R3E 3P4, Canada; Department of Immunology, University of Manitoba, Manitoba, Winnipeg, R3E 0T5, Canada
| | - Chris Carlsten
- Air Pollution Exposure Laboratory, Division of Respiratory Medicine, Department of Medicine, Vancouver Coastal Health Research Institute, The University of British Columbia, British Columbia, Vancouver, V5Z1W9, Canada.
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Qin S, Zeng H, Wu Q, Li Q, Zeeshan M, Ye L, Jiang Y, Zhang R, Jiang X, Li M, Zhang R, Chen W, Chou WC, Dong GH, Li DC, Zeng XW. An integrative analysis of lipidomics and transcriptomics in various mouse brain regions in response to real-ambient PM 2.5 exposure. THE SCIENCE OF THE TOTAL ENVIRONMENT 2023; 895:165112. [PMID: 37364843 DOI: 10.1016/j.scitotenv.2023.165112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/20/2023] [Revised: 06/13/2023] [Accepted: 06/23/2023] [Indexed: 06/28/2023]
Abstract
Exposure to Fine particulate matter (PM2.5) has been associated with various neurological disorders. However, the underlying mechanisms of PM2.5-induced adverse effects on the brain are still not fully defined. Multi-omics analyses could offer novel insights into the mechanisms of PM2.5-induced brain dysfunction. In this study, a real-ambient PM2.5 exposure system was applied to male C57BL/6 mice for 16 weeks, and lipidomics and transcriptomics analysis were performed in four brain regions. The findings revealed that PM2.5 exposure led to 548, 283, 304, and 174 differentially expressed genes (DEGs), as well as 184, 89, 228, and 49 distinctive lipids in the hippocampus, striatum, cerebellum, and olfactory bulb, respectively. Additionally, in most brain regions, PM2.5-induced DEGs were mainly involved in neuroactive ligand-receptor interaction, cytokine-cytokine receptor interaction, and calcium signaling pathway, while PM2.5-altered lipidomic profile were primarily enriched in retrograde endocannabinoid signaling and biosynthesis of unsaturated fatty acids. Importantly, mRNA-lipid correlation networks revealed that PM2.5-altered lipids and DEGs were obviously enriched in pathways involving in bile acid biosynthesis, De novo fatty acid biosynthesis, and saturated fatty acids beta-oxidation in brain regions. Furthermore, multi-omics analyses revealed that the hippocampus was the most sensitive part to PM2.5 exposure. Specifically, dysregulation of Pla2g1b, Pla2g, Alox12, Alox15, and Gpx4 induced by PM2.5 were closely correlated to the disruption of alpha-linolenic acid, arachidonic acid and linoleic acid metabolism in the hippocampus. In summary, our findings highlight differential lipidomic and transcriptional signatures of various brain regions by real-ambient PM2.5 exposure, which will advance our understanding of potential mechanisms of PM2.5-induecd neurotoxicity.
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Affiliation(s)
- Shuangjian Qin
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Huixian Zeng
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Qizhen Wu
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Qingqing Li
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Mohammed Zeeshan
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Lizhu Ye
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Yue Jiang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Rui Zhang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Xinhang Jiang
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Miao Li
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Rong Zhang
- Department of Toxicology, School of Public Health, Hebei Medical University, Shijiazhuang 050017, China
| | - Wen Chen
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Wei-Chun Chou
- Center for Environmental and Human Toxicology, Department of Environmental and Global Health, College of Public Health and Health Professions, University of Florida, Gainesville, FL 32611, United States
| | - Guang-Hui Dong
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China
| | - Dao-Chuan Li
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Department of Toxicology, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
| | - Xiao-Wen Zeng
- Guangdong Provincial Key Laboratory of Food, Nutrition and Health, Guangdong Provincial Engineering Technology Research Center of Environmental and Health risk Assessment, Department of Occupational and Environmental Health, School of Public Health, Sun Yat-sen University, Guangzhou 510080, China.
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Wong JY, Blechter B, Bassig BA, Dai Y, Vermeulen R, Hu W, Rahman ML, Duan H, Niu Y, Downward GS, Leng S, Ji BT, Fu W, Xu J, Meliefste K, Zhou B, Yang J, Ren D, Ye M, Jia X, Meng T, Bin P, Hosgood HD, Rothman N, Silverman DT, Zheng Y, Lan Q. Alterations to biomarkers related to long-term exposure to diesel exhaust at concentrations below occupational exposure limits in the European Union and the USA. Occup Environ Med 2023; 80:260-267. [PMID: 36972977 PMCID: PMC10337808 DOI: 10.1136/oemed-2022-108719] [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: 10/28/2022] [Accepted: 03/04/2023] [Indexed: 03/29/2023]
Abstract
BACKGROUND We previously found that occupational exposure to diesel engine exhaust (DEE) was associated with alterations to 19 biomarkers that potentially reflect the mechanisms of carcinogenesis. Whether DEE is associated with biological alterations at concentrations under existing or recommended occupational exposure limits (OELs) is unclear. METHODS In a cross-sectional study of 54 factory workers exposed long-term to DEE and 55 unexposed controls, we reanalysed the 19 previously identified biomarkers. Multivariable linear regression was used to compare biomarker levels between DEE-exposed versus unexposed subjects and to assess elemental carbon (EC) exposure-response relationships, adjusted for age and smoking status. We analysed each biomarker at EC concentrations below the US Mine Safety and Health Administration (MSHA) OEL (<106 µg/m3), below the European Union (EU) OEL (<50 µg/m3) and below the American Conference of Governmental Industrial Hygienists (ACGIH) recommendation (<20 µg/m3). RESULTS Below the MSHA OEL, 17 biomarkers were altered between DEE-exposed workers and unexposed controls. Below the EU OEL, DEE-exposed workers had elevated lymphocytes (p=9E-03, false discovery rate (FDR)=0.04), CD4+ count (p=0.02, FDR=0.05), CD8+ count (p=5E-03, FDR=0.03) and miR-92a-3p (p=0.02, FDR=0.05), and nasal turbinate gene expression (first principal component: p=1E-06, FDR=2E-05), as well as decreased C-reactive protein (p=0.02, FDR=0.05), macrophage inflammatory protein-1β (p=0.04, FDR=0.09), miR-423-3p (p=0.04, FDR=0.09) and miR-122-5p (p=2E-03, FDR=0.02). Even at EC concentrations under the ACGIH recommendation, we found some evidence of exposure-response relationships for miR-423-3p (ptrend=0.01, FDR=0.19) and gene expression (ptrend=0.02, FDR=0.19). CONCLUSIONS DEE exposure under existing or recommended OELs may be associated with biomarkers reflective of cancer-related processes, including inflammatory/immune response.
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Affiliation(s)
- Jason Yy Wong
- Epidemiology and Community Health Branch, National Heart Lung and Blood Institute, Bethesda, Maryland, USA
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Batel Blechter
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Bryan A Bassig
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Yufei Dai
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Roel Vermeulen
- The Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Wei Hu
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Mohammad L Rahman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Huawei Duan
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Niu
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - George S Downward
- The Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Shuguang Leng
- Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, University of New Mexico School of Medicine, Albuquerque, New Mexico, USA
- Cancer Control and Population Sciences, University of New Mexico Comprehensive Cancer Center, Albuquerque, New Mexico, USA
| | - Bu-Tian Ji
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Wei Fu
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Lianing, China
| | - Jun Xu
- Division of Community Medicine and Public Health Practice, Hong Kong University, Hong Kong, Hong Kong, China
| | - Kees Meliefste
- The Institute for Risk Assessment Sciences, Utrecht University, Utrecht, The Netherlands
| | - Baosen Zhou
- China Medical University, Liaoning, Shenyang, China
| | - Jufang Yang
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Lianing, China
| | - Dianzhi Ren
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Lianing, China
| | - Meng Ye
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaowei Jia
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tao Meng
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ping Bin
- National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - H Dean Hosgood
- Division of Epidemiology, Yeshiva University Albert Einstein College of Medicine, Bronx, New York, USA
| | - Nathaniel Rothman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Debra T Silverman
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
| | - Yuxin Zheng
- School of Public Health, Qingdao University, Qingdao, China
| | - Qing Lan
- Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA
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4
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Wong JYY, Imani P, Grigoryan H, Bassig BA, Dai Y, Hu W, Blechter B, Rahman ML, Ji BT, Duan H, Niu Y, Ye M, Jia X, Meng T, Bin P, Downward G, Meliefste K, Leng S, Fu W, Yang J, Ren D, Xu J, Zhou B, Hosgood HD, Vermeulen R, Zheng Y, Silverman DT, Rothman N, Rappaport SM, Lan Q. Exposure to diesel engine exhaust and alterations to the Cys34/Lys525 adductome of human serum albumin. ENVIRONMENTAL TOXICOLOGY AND PHARMACOLOGY 2022; 95:103966. [PMID: 36067935 PMCID: PMC9757949 DOI: 10.1016/j.etap.2022.103966] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 08/28/2022] [Accepted: 08/29/2022] [Indexed: 06/15/2023]
Abstract
We investigated whether exposure to carcinogenic diesel engine exhaust (DEE) was associated with altered adduct levels in human serum albumin (HSA) residues. Nano-liquid chromatography-high resolution mass spectrometry (nLC-HRMS) was used to measure adducts of Cys34 and Lys525 residues in plasma samples from 54 diesel engine factory workers and 55 unexposed controls. An untargeted adductomics and bioinformatics pipeline was used to find signatures of Cys34/Lys525 adductome modifications. To identify adducts that were altered between DEE-exposed and unexposed participants, we used an ensemble feature selection approach that ranks and combines findings from linear regression and penalized logistic regression, then aggregates the important findings with those determined by random forest. We detected 40 Cys34 and 9 Lys525 adducts. Among these findings, we found evidence that 6 Cys34 adducts were altered between DEE-exposed and unexposed participants (i.e., 841.75, 851.76, 856.10, 860.77, 870.43, and 913.45). These adducts were biologically related to antioxidant activity.
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Affiliation(s)
- Jason Y Y Wong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA.
| | - Partow Imani
- School of Public Health, University of California, Berkeley, CA, USA
| | - Hasmik Grigoryan
- School of Public Health, University of California, Berkeley, CA, USA
| | - Bryan A Bassig
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Yufei Dai
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Batel Blechter
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Mohammad L Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Huawei Duan
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Yong Niu
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Meng Ye
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Xiaowei Jia
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Tao Meng
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - Ping Bin
- National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
| | - George Downward
- Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Kees Meliefste
- Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Shuguang Leng
- Cancer Control and Population Sciences, University of New Mexico Comprehensive Cancer Center, Albuquerque, NM, USA; Division of Epidemiology, Biostatistics, and Preventive Medicine, Department of Internal Medicine, University of New Mexico School of Medicine, University of New Mexico Comprehensive Cancer Center, Albuquerque, NM, USA
| | - Wei Fu
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Liaoning, China
| | - Jufang Yang
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Liaoning, China
| | - Dianzhi Ren
- Chaoyang Center for Disease Control and Prevention, Chaoyang, Liaoning, China
| | - Jun Xu
- School of Public Health, The University of Hong Kong, Hong Kong Special Administrative Region
| | - Baosen Zhou
- China Medical University, Shenyang, Liaoning, China
| | - H Dean Hosgood
- Division of Epidemiology, Albert Einstein College of Medicine, New York, NY, USA
| | - Roel Vermeulen
- Division of Environmental Epidemiology, Institute for Risk Assessment Sciences, Utrecht University, Utrecht, the Netherlands
| | - Yuxin Zheng
- School of Public Health, Qingdao University, Qingdao, China
| | - Debra T Silverman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | | | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
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