1
|
Rahman ML, Breeze CE, Shu XO, Wong JYY, Blechter B, Cardenas A, Wang X, Ji BT, Hu W, Cai Q, Hosgood HD, Yang G, Shi J, Long J, Gao YT, Bell DA, Zheng W, Rothman N, Lan Q. Epigenome-wide association study of lung cancer among never smokers in two prospective cohorts in Shanghai, China. Thorax 2024:thorax-2023-220352. [PMID: 38702190 DOI: 10.1136/thorax-2023-220352] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/19/2023] [Accepted: 02/17/2024] [Indexed: 05/06/2024]
Abstract
BACKGROUND The aetiology of lung cancer among individuals who never smoked remains elusive, despite 15% of lung cancer cases in men and 53% in women worldwide being unrelated to smoking. Epigenetic alterations, particularly DNA methylation (DNAm) changes, have emerged as potential drivers. Yet, few prospective epigenome-wide association studies (EWAS), primarily focusing on peripheral blood DNAm with limited representation of never smokers, have been conducted. METHODS We conducted a nested case-control study of 80 never-smoking incident lung cancer cases and 83 never-smoking controls within the Shanghai Women's Health Study and Shanghai Men's Health Study. DNAm was measured in prediagnostic oral rinse samples using Illumina MethylationEPIC array. Initially, we conducted an EWAS to identify differentially methylated positions (DMPs) associated with lung cancer in the discovery sample of 101 subjects. The top 50 DMPs were further evaluated in a replication sample of 62 subjects, and results were pooled using fixed-effect meta-analysis. RESULTS Our study identified three DMPs significantly associated with lung cancer at the epigenome-wide significance level of p<8.22×10-8. These DMPs were identified as cg09198866 (MYH9; TXN2), cg01411366 (SLC9A10) and cg12787323. Furthermore, examination of the top 1000 DMPs indicated significant enrichment in epithelial regulatory regions and their involvement in small GTPase-mediated signal transduction pathways. Additionally, GrimAge acceleration was identified as a risk factor for lung cancer (OR=1.19 per year; 95% CI 1.06 to 1.34). CONCLUSIONS While replication in a larger sample size is necessary, our findings suggest that DNAm patterns in prediagnostic oral rinse samples could provide novel insights into the underlying mechanisms of lung cancer in never smokers.
Collapse
Affiliation(s)
- Mohammad L Rahman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Charles E Breeze
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Xiao-Ou Shu
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Jason Y Y Wong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Batel Blechter
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Andres Cardenas
- Department of Epidemiology and Population Health, Stanford University, Stanford, California, USA
| | - Xuting Wang
- Immunity, Inflammation and Diseases Laboratory, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Bu-Tian Ji
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Wei Hu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Qiuyin Cai
- Vanderbilt University, Nashville, Tennessee, USA
| | - H Dean Hosgood
- Albert Einstein College of Medicine, Bronx, New York, USA
| | - Gong Yang
- Department of Medicine, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee, USA
| | - Jianxin Shi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Jirong Long
- Department of Medicine, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee, USA
| | | | - Douglas A Bell
- Immunity, Inflammation and Diseases Laboratory, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USA
| | - Wei Zheng
- Vanderbilt University Medical Center, Nashville, Tennessee, USA
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland, USA
| |
Collapse
|
2
|
Ivic-Pavlicic T, Joshi S, Zegarelli A, Taioli E. Assessing how lung cancer screening guidelines contribute to racial disparities in screening access. Transl Lung Cancer Res 2023; 12:1122-1132. [PMID: 37323180 PMCID: PMC10261853 DOI: 10.21037/tlcr-22-816] [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: 11/17/2022] [Accepted: 04/25/2023] [Indexed: 06/17/2023]
Abstract
Background Lung cancer (LC) is the leading cause of cancer-related deaths in the United States (U.S.), with non-White people who smoke often bearing the burden of the highest rate of LC mortality. This is often due to later stage diagnoses, leading to poor prognosis and outcomes. We assess here how the eligibility criteria for LC screening set by the U.S. Preventive Services Task Force (USPSTF) and the Centers for Medicare and Medicaid Services (CMS) could contribute to racial disparities in screening access. Methods This paper analyzes data from the National Health and Nutrition Examination Survey (NHANES), an annual survey conducted by the Centers for Disease Control and Prevention (CDC) that gathers health and nutrition data from a representative sample of the U.S. population. After excluding those who were ineligible for LC screening, the final cohort of participants was 5,001, which consisted of 2,669 people who formerly smoked and 2,332 people who currently smoke. Results Out of 608 participants who were eligible for LC screening, 77.5% were non-Hispanic White (NHW) and 8.7% were non-Hispanic Black (NHB) participants versus 69.4% and 10.8% among 4,393 ineligible participants. Age, pack-years, and age along with pack-years were the most frequent reasons for ineligibility. LC screening ineligible NHW participants were statistically significantly older and had higher mean pack-years than the other racial and ethnic groups. NHB participants among the ineligible group had higher urinary cotinine levels compared to NHW participants. Conclusions This paper underscores the need for more individualized risk estimates when determining eligibility for LC screening, which could include biomarkers of smoking exposure. The analysis shows that current screening criteria, which rely solely on factors such as age and pack years, contribute to LC racial disparities.
Collapse
Affiliation(s)
- Tara Ivic-Pavlicic
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Shivam Joshi
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Angelo Zegarelli
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Emanuela Taioli
- Institute for Translational Epidemiology, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Thoracic Surgery, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| |
Collapse
|
3
|
Cigan SS, Murphy SE, Stram DO, Hecht SS, Le Marchand L, Stepanov I, Park SL. Association of Urinary Biomarkers of Smoking-Related Toxicants with Lung Cancer Incidence in Smokers: The Multiethnic Cohort Study. Cancer Epidemiol Biomarkers Prev 2023; 32:306-314. [PMID: 36350738 PMCID: PMC9992134 DOI: 10.1158/1055-9965.epi-22-0569] [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: 05/16/2022] [Revised: 08/09/2022] [Accepted: 11/02/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND While cigarette smoking is the leading cause of lung cancer, the majority of smokers do not develop the disease over their lifetime. The inter-individual differences in risk among smokers may in part be due to variations in exposure to smoking-related toxicants. METHODS Using data from a subcohort of 2,309 current smokers at the time of urine collection from the Multiethnic Cohort Study, we prospectively evaluated the association of ten urinary biomarkers of smoking-related toxicants [total nicotine equivalents (TNE), a ratio of total trans-3'-hydroxycotinine (3-HCOT)/cotinine (a phenotypic measure of CYP2A6 enzymatic activity), 4-(methylnitrosamino)-1-3-(pyridyl)-1-butanol (NNAL), S-phenylmercapturic acid (SPMA), 3-hydroxypropyl mercapturic acid (3-HPMA), phenanthrene tetraol (PheT), 3-hydroxyphenanthrene (PheOH), the ratio of PheT/PheOH, cadmium (Cd), and (Z)-7-(1R,2R,3R,5S)-3,5-dihydroxy-2-[(E,3S)-3-hydroxyoct-1-enyl]cyclopenyl]hept-5-enoic acid (8-iso-PGF2α)] with lung cancer risk (n = 140 incident lung cancer cases over an average of 13.4 years of follow-up). Lung cancer risk was estimated using Cox proportional hazards models. RESULTS After adjusting for decade of birth, sex, race/ethnicity, body mass index, self-reported pack-years, creatinine, and urinary TNE (a biomarker of internal smoking dose), a one SD increase in log total 3-HCOT/cotinine (HR, 1.33; 95% CI, 1.06-1.66), 3-HPMA (HR, 1.41; 95% CI, 1.07-1.85), and Cd (HR, 1.45; 95% CI, 1.18-1.79) were each associated with increased lung cancer risk. CONCLUSIONS Our study demonstrates that urinary total 3-HCOT/cotinine, 3-HPMA, and Cd are positively associated with lung cancer risk. These findings warrant replication and consideration as potential biomarkers for smoking-related lung cancer risk. IMPACT These biomarkers may provide additional information on lung cancer risk that is not captured by self-reported smoking history or TNE. See related commentary by Etemadi et al., p. 289.
Collapse
Affiliation(s)
- Shannon S. Cigan
- Department of Pediatrics, Division of Epidemiology and Clinical Research, University of Minnesota, Minneapolis, MN 55455, United States of America
- Division of Environmental Health Sciences, University of Minnesota, Minneapolis MN 55455, United States of America
| | - Sharon E. Murphy
- Masonic Cancer Center, University of Minnesota, Minneapolis MN 55455, United States of America
| | - Daniel O. Stram
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, United States of America
| | - Stephen S. Hecht
- Masonic Cancer Center, University of Minnesota, Minneapolis MN 55455, United States of America
| | - Loïc Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, United States of America
| | - Irina Stepanov
- Division of Environmental Health Sciences, University of Minnesota, Minneapolis MN 55455, United States of America
- Masonic Cancer Center, University of Minnesota, Minneapolis MN 55455, United States of America
| | - Sungshim L. Park
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI 96813, United States of America
| |
Collapse
|
4
|
He H, Zhong R. Reply to Liu and Xiong. Am J Respir Crit Care Med 2023; 207:371-372. [PMID: 36191307 PMCID: PMC9896642 DOI: 10.1164/rccm.202209-1805le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
|
5
|
Liu N, Xiong W. Early Life Exposure to Tobacco Smoke and Lung Cancer in Adulthood. Am J Respir Crit Care Med 2023; 207:370-371. [PMID: 36191304 PMCID: PMC9896639 DOI: 10.1164/rccm.202208-1542le] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
|
6
|
Jochems SHJ, Stattin P, Stocks T. Reply to Paulius Bosas, Gintaras Zaleskis, and Dainius Characiejus's Letter to the Editor re: Sylvia H.J. Jochems, Josef Fritz, Christel Häggström, Bengt Järvholm, Pär Stattin, Tanja Stocks. Smoking and Risk of Prostate Cancer and Prostate Cancer Death: A Pooled Study. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2022.03.033. Therapeutic Monitoring in Prostate Cancer Should Involve a Cotinine Test in Current Smokers: Smoking Cessation Remains a Cornerstone in Preventive Health Care Overall and for Men with Prostate Cancer. Eur Urol 2022; 82:e115. [PMID: 35907663 DOI: 10.1016/j.eururo.2022.07.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Accepted: 07/12/2022] [Indexed: 11/28/2022]
Affiliation(s)
| | - Pär Stattin
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Tanja Stocks
- Department of Clinical Sciences Lund, Lund University, Lund, Sweden
| |
Collapse
|
7
|
Hovanec J, Weiß T, Koch HM, Pesch B, Behrens T, Kendzia B, Arendt M, Dragano N, Moebus S, Schmidt B, Brüning T, Jöckel KH. Smoking intensity and urinary nicotine metabolites by socioeconomic status in the Heinz Nixdorf Recall study. BMC Public Health 2022; 22:302. [PMID: 35164711 PMCID: PMC8842804 DOI: 10.1186/s12889-022-12609-y] [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: 11/02/2020] [Accepted: 01/19/2022] [Indexed: 11/28/2022] Open
Abstract
Background Smoking intensity, which is generally based on self-reported average cigarettes per day (CPD), is a major behavioural risk factor and strongly related to socioeconomic status (SES). To assess the validity of the CPD measure, correlations with objective markers of tobacco smoke exposure – such as urinary nicotine metabolites – were examined. Yet, it remains unclear, whether this correlation is affected by SES, which may indicate imprecise or biased self-reports of smoking intensity.
Methods We investigated the role of SES in the association between CPD and nicotine metabolites in current smokers among the participants of the population-based, prospective Heinz Nixdorf Recall Study. We determined urinary cotinine and additionally trans-3′-hydroxy-cotinine. SES was assessed by the International Socio-Economic Index of occupational status, and education. We calculated correlations (Pearson’s r) between logarithmised CPD and cotinine in subgroups of SES and analysed SES and further predictors of cotinine in multiple linear regression models separately by gender. Results Median reported smoking intensity was 20 CPD in male and 19 CPD in female smokers. Men showed higher cotinine concentrations (median 3652 μg/L, interquartile range (IQR) 2279–5422 μg/L) than women (3127 μg/L, IQR 1692–4920 μg/L). Logarithmised CPD correlated moderately with cotinine in both, men and women (Pearson’s r 0.4), but correlations were weaker in smokers with lower SES: Pearson’s r for low, intermediate, and high occupational SES was 0.35, 0.39, and 0.48 in men, and 0.28, 0.43, and 0.47 in women, respectively. Logarithmised CPD and urinary creatinine were main predictors of cotinine in multiple regression models, whereas SES showed a weak negative association in women. Results were similar for trans-3′-hydroxy-cotinine. Conclusions Decreasing precision of self-reported CPD was indicated for low SES in men and women. We found no strong evidence for biased self-reports of smoking intensity by SES. Supplementary Information The online version contains supplementary material available at 10.1186/s12889-022-12609-y.
Collapse
Affiliation(s)
- Jan Hovanec
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany.
| | - Tobias Weiß
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Holger M Koch
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Beate Pesch
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Thomas Behrens
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Benjamin Kendzia
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Marina Arendt
- Institute for Medical Informatics, Biometry and Epidemiology, Essen University Hospital, Essen, Germany.,Department of Computer Science, University of Applied Sciences and Arts, Dortmund, Germany
| | - Nico Dragano
- Institute of Medical Sociology, Medical Faculty, University of Düsseldorf, Düsseldorf, Germany
| | - Susanne Moebus
- Institute for Urban Public Health, Essen University Hospital, University Duisburg-Essen, Essen, Germany
| | - Börge Schmidt
- Institute for Medical Informatics, Biometry and Epidemiology, Essen University Hospital, Essen, Germany
| | - Thomas Brüning
- Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum (IPA), Bürkle-de-la-Camp-Platz 1, 44789, Bochum, Germany
| | - Karl-Heinz Jöckel
- Institute for Medical Informatics, Biometry and Epidemiology, Essen University Hospital, Essen, Germany
| |
Collapse
|
8
|
Madama D, Martins R, Pires AS, Botelho MF, Alves MG, Abrantes AM, Cordeiro CR. Metabolomic Profiling in Lung Cancer: A Systematic Review. Metabolites 2021; 11:630. [PMID: 34564447 PMCID: PMC8471464 DOI: 10.3390/metabo11090630] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Revised: 09/09/2021] [Accepted: 09/13/2021] [Indexed: 12/25/2022] Open
Abstract
Lung cancer continues to be a significant burden worldwide and remains the leading cause of cancer-associated mortality. Two considerable challenges posed by this disease are the diagnosis of 61% of patients in advanced stages and the reduced five-year survival rate of around 4%. Noninvasively collected samples are gaining significant interest as new areas of knowledge are being sought and opened up. Metabolomics is one of these growing areas. In recent years, the use of metabolomics as a resource for the study of lung cancer has been growing. We conducted a systematic review of the literature from the past 10 years in order to identify some metabolites associated with lung cancer. More than 150 metabolites have been associated with lung cancer-altered metabolism. These were detected in different biological samples by different metabolomic analytical platforms. Some of the published results have been consistent, showing the presence/alteration of specific metabolites. However, there is a clear variability due to lack of a full clinical characterization of patients or standardized patients selection. In addition, few published studies have focused on the added value of the metabolomic profile as a means of predicting treatment response for lung cancer. This review reinforces the need for consistent and systematized studies, which will help make it possible to identify metabolic biomarkers and metabolic pathways responsible for the mechanisms that promote tumor progression, relapse and eventually resistance to therapy.
Collapse
Affiliation(s)
- Daniela Madama
- Clinical Academic Center of Coimbra (CACC), Department of Pulmonology, Faculty of Medicine, University Hospitals of Coimbra, University of Coimbra, 3004-504 Coimbra, Portugal;
| | - Rosana Martins
- Coimbra Institute for Clinical and Biomedical Research (iCBR), Biophysics Institute of Faculty of Medicine of University of Coimbra, Area of Environmental Genetics and Oncobiology (CIMAGO), 3000-548 Coimbra, Portugal;
| | - Ana S. Pires
- Clinical Academic Center of Coimbra (CACC), Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra Institute for Clinical and Biomedical Research (iCBR), Biophysics Institute of Faculty of Medicine of University of Coimbra, Area of Environmental Genetics and Oncobiology (CIMAGO), 3000-548 Coimbra, Portugal; (A.S.P.); (M.F.B.); (A.M.A.)
| | - Maria F. Botelho
- Clinical Academic Center of Coimbra (CACC), Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra Institute for Clinical and Biomedical Research (iCBR), Biophysics Institute of Faculty of Medicine of University of Coimbra, Area of Environmental Genetics and Oncobiology (CIMAGO), 3000-548 Coimbra, Portugal; (A.S.P.); (M.F.B.); (A.M.A.)
| | - Marco G. Alves
- Department of Anatomy, Unit for Multidisciplinary Research in Biomedicine (UMIB), Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, 4099-002 Porto, Portugal;
| | - Ana M. Abrantes
- Clinical Academic Center of Coimbra (CACC), Center for Innovative Biomedicine and Biotechnology (CIBB), Coimbra Institute for Clinical and Biomedical Research (iCBR), Biophysics Institute of Faculty of Medicine of University of Coimbra, Area of Environmental Genetics and Oncobiology (CIMAGO), 3000-548 Coimbra, Portugal; (A.S.P.); (M.F.B.); (A.M.A.)
| | - Carlos R. Cordeiro
- Clinical Academic Center of Coimbra (CACC), Department of Pulmonology, Faculty of Medicine, University Hospitals of Coimbra, University of Coimbra, 3004-504 Coimbra, Portugal;
| |
Collapse
|
9
|
Zahed H, Johansson M, Ueland PM, Midttun Ø, Milne RL, Giles GG, Manjer J, Sandsveden M, Langhammer A, Sørgjerd EP, Grankvist K, Johansson M, Freedman ND, Huang WY, Chen C, Prentice R, Stevens VL, Wang Y, Le Marchand L, Wilkens LR, Weinstein SJ, Albanes D, Cai Q, Blot WJ, Arslan AA, Zeleniuch-Jacquotte A, Shu XO, Zheng W, Yuan JM, Koh WP, Visvanathan K, Sesso HD, Zhang X, Gaziano JM, Fanidi A, Muller D, Brennan P, Guida F, Robbins HA. Epidemiology of 40 blood biomarkers of one-carbon metabolism, vitamin status, inflammation, and renal and endothelial function among cancer-free older adults. Sci Rep 2021; 11:13805. [PMID: 34226613 PMCID: PMC8257595 DOI: 10.1038/s41598-021-93214-8] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Accepted: 05/21/2021] [Indexed: 11/09/2022] Open
Abstract
Imbalances of blood biomarkers are associated with disease, and biomarkers may also vary non-pathologically across population groups. We described variation in concentrations of biomarkers of one-carbon metabolism, vitamin status, inflammation including tryptophan metabolism, and endothelial and renal function among cancer-free older adults. We analyzed 5167 cancer-free controls aged 40-80 years from 20 cohorts in the Lung Cancer Cohort Consortium (LC3). Centralized biochemical analyses of 40 biomarkers in plasma or serum were performed. We fit multivariable linear mixed effects models to quantify variation in standardized biomarker log-concentrations across four factors: age, sex, smoking status, and body mass index (BMI). Differences in most biomarkers across most factors were small, with 93% (186/200) of analyses showing an estimated difference lower than 0.25 standard-deviations, although most were statistically significant due to large sample size. The largest difference was for creatinine by sex, which was - 0.91 standard-deviations lower in women than men (95%CI - 0.98; - 0.84). The largest difference by age was for total cysteine (0.40 standard-deviation increase per 10-year increase, 95%CI 0.36; 0.43), and by BMI was for C-reactive protein (0.38 standard-deviation increase per 5-kg/m2 increase, 95%CI 0.34; 0.41). For 31 of 40 markers, the mean difference between current and never smokers was larger than between former and never smokers. A statistically significant (p < 0.05) association with time since smoking cessation was observed for 8 markers, including C-reactive protein, kynurenine, choline, and total homocysteine. We conclude that most blood biomarkers show small variations across demographic characteristics. Patterns by smoking status point to normalization of multiple physiological processes after smoking cessation.
Collapse
Affiliation(s)
- Hana Zahed
- Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France
| | - Mattias Johansson
- Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France
| | - Per M Ueland
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | | | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia
| | - Jonas Manjer
- Department of Surgery, Skane University Hospital, Malmö, Sweden
- Lund University, Malmö, Sweden
| | - Malte Sandsveden
- Department of Clinical Sciences Malmo, Lund University, Malmö, Sweden
| | - Arnulf Langhammer
- Department of Public Health and Nursing, Hunt Research Centre, Norwegian University of Science and Technology, Levanger, Norway
- Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
| | - Elin Pettersen Sørgjerd
- Department of Public Health and Nursing, NTNU, Hunt Research Centre, Norwegian University of Science and Technology, Levanger, Norway
- Department of Endocrinology, St. Olavs Hospital, Trondheim University Hospital, Levanger, Norway
| | - Kjell Grankvist
- Department of Medical Biosciences, Umea University, Umeå, Sweden
| | - Mikael Johansson
- Department of Radiation Sciences, Oncology, Umea University, Umeå, Sweden
| | - Neal D Freedman
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Wen-Yi Huang
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Chu Chen
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA
| | - Ross Prentice
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, USA
| | | | - Ying Wang
- American Cancer Society, Atlanta, USA
| | - Loic Le Marchand
- University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, USA
| | - Lynne R Wilkens
- University of Hawai'i Cancer Center, University of Hawai'i at Mānoa, Honolulu, USA
| | - Stephanie J Weinstein
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Demetrius Albanes
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD, USA
| | - Qiuyin Cai
- Vanderbilt University Medical Center, Nashville, USA
| | | | - Alan A Arslan
- Department of Obstetrics and Gynecology, NYU Langone Health, New York, NY, USA
- Department of Population Health, NYU Langone Health, New York, NY, USA
- Perlmutter Comprehensive Cancer Center, NYU Langone Health, New York, NY, USA
| | - Anne Zeleniuch-Jacquotte
- Department of Population Health, NYU Langone Health, New York, NY, USA
- Perlmutter Comprehensive Cancer Center, NYU Langone Health, New York, NY, USA
| | - Xiao-Ou Shu
- Vanderbilt University Medical Center, Nashville, USA
| | - Wei Zheng
- Vanderbilt University Medical Center, Nashville, USA
| | - Jian-Min Yuan
- University of Pittsburgh Medical Center, Pittsburgh, USA
| | | | - Kala Visvanathan
- Johns Hopkins Institute for Clinical and Translational Research, Baltimore, USA
| | - Howard D Sesso
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- Harvard T.H. Chan School of Public Health, Boston, USA
| | - Xuehong Zhang
- Brigham and Women's Hospital, Harvard Medical School, Boston, USA
- Harvard T.H. Chan School of Public Health, Boston, USA
| | - J Michael Gaziano
- Harvard T.H. Chan School of Public Health, Boston, USA
- Brigham and Women's Hospital, Boston, USA
| | | | - David Muller
- Imperial College London School of Public Health, London, UK
| | - Paul Brennan
- Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France
| | - Florence Guida
- Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France
| | - Hilary A Robbins
- Genomic Epidemiology Branch, International Agency for Research on Cancer, 150 cours Albert Thomas, 69008, Lyon, France.
| |
Collapse
|
10
|
Zhu J, Smith-Warner SA, Yu D, Zhang X, Blot WJ, Xiang YB, Sinha R, Park Y, Tsugane S, White E, Koh WP, Park SK, Sawada N, Kanemura S, Sugawara Y, Tsuji I, Robien K, Tomata Y, Yoo KY, Kim J, Yuan JM, Gao YT, Rothman N, Lazovich D, Abe SK, Rahman MS, Loftfield E, Takata Y, Li X, Lee JE, Saito E, Freedman ND, Inoue M, Lan Q, Willett WC, Zheng W, Shu XO. Associations of coffee and tea consumption with lung cancer risk. Int J Cancer 2021; 148:2457-2470. [PMID: 33326609 PMCID: PMC8460087 DOI: 10.1002/ijc.33445] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Revised: 11/17/2020] [Accepted: 11/19/2020] [Indexed: 12/17/2022]
Abstract
Associations of coffee and tea consumption with lung cancer risk have been inconsistent, and most lung cancer cases investigated were smokers. Included in this study were over 1.1 million participants from 17 prospective cohorts. Cox regression analyses were conducted to estimate hazard ratios (HRs) and 95% confidence intervals (CIs). Potential effect modifications by sex, smoking, race, cancer subtype and coffee type were assessed. After a median 8.6 years of follow-up, 20 280 incident lung cancer cases were identified. Compared with noncoffee and nontea consumption, HRs (95% CIs) associated with exclusive coffee drinkers (≥2 cups/d) among current, former and never smokers were 1.30 (1.15-1.47), 1.49 (1.27-1.74) and 1.35 (1.15-1.58), respectively. Corresponding HRs for exclusive tea drinkers (≥2 cups/d) were 1.16 (1.02-1.32), 1.10 (0.92-1.32) and 1.37 (1.17-1.61). In general, the coffee and tea associations did not differ significantly by sex, race or histologic subtype. Our findings suggest that higher consumption of coffee or tea is associated with increased lung cancer risk. However, these findings should not be assumed to be causal because of the likelihood of residual confounding by smoking, including passive smoking, and change of coffee and tea consumption after study enrolment.
Collapse
Affiliation(s)
- Jingjing Zhu
- Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | | | - Danxia Yu
- Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Xuehong Zhang
- Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
| | - William J. Blot
- Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Yong-Bing Xiang
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China
| | - Rashmi Sinha
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Yikyung Park
- Division of Public Health Sciences, Department of Surgery, Washington University School of Medicine, St. Louis, MO
| | - Shoichiro Tsugane
- Division of Prevention Center for Public Health Sciences National Cancer Center, Tokyo, Japan
| | - Emily White
- Cancer Prevention Program, Fred Hutchinson Cancer Research Center, Seattle, WA
| | - Woon-Puay Koh
- Health Services and Systems Research, Duke-NUS Medical School, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore
| | - Sue K. Park
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Norie Sawada
- Department of Global Health Policy, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Seiki Kanemura
- Division of Epidemiology, Department of Health Informatics and Public Health, Tohoku University School of Public Health, Graduate School of Medicine, Sendai, Japan
| | - Yumi Sugawara
- Division of Epidemiology, Department of Health Informatics and Public Health, Tohoku University School of Public Health, Graduate School of Medicine, Sendai, Japan
| | - Ichiro Tsuji
- Division of Epidemiology, Department of Health Informatics and Public Health, Tohoku University School of Public Health, Graduate School of Medicine, Sendai, Japan
| | - Kim Robien
- Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, The George Washington University, Washington, DC
| | - Yasutake Tomata
- Division of Epidemiology, Department of Health Informatics and Public Health, Tohoku University School of Public Health, Graduate School of Medicine, Sendai, Japan
| | - Keun-Young Yoo
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul, Korea
| | - Jeongseon Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center of Korea, Goyang, Korea
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, University of Pittsburgh Medical Center (UPMC) Hillman Cancer Center, Pittsburgh, PA
- Department of Epidemiology, University of Pittsburgh Graduate School of Public Health, Pittsburgh, PA
| | - Yu-Tang Gao
- State Key Laboratory of Oncogene and Related Genes & Department of Epidemiology, Shanghai Cancer Institute Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai 200032, China
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - DeAnn Lazovich
- Division of Epidemiology & Community Health, School of Public Health, Masonic Cancer Center, University of Minnesota, Minneapolis, MN, USA
| | - Sarah K. Abe
- Department of Global Health Policy, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Md Shafiur Rahman
- Department of Global Health Policy, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
- Division of Prevention Center for Public Health Sciences National Cancer Center, Tokyo, Japan
| | - Erikka Loftfield
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Yumie Takata
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR
| | - Xin Li
- Richard M. Fairbanks School of Public Health, Indiana University
| | - Jung Eun Lee
- Department of Food and Nutrition, College of Human Ecology, Seoul National University, Seoul
| | - Eiko Saito
- Division of Cancer Statistics Integration Center for Cancer Control & Information Services National Cancer Center, Tokyo, Japan
| | - Neal D. Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Manami Inoue
- Department of Global Health Policy, Graduate School of Medicine, University of Tokyo, Tokyo, Japan
| | - Qing Lan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD
| | - Walter C. Willett
- Departments of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA
- The Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School
| | - Wei Zheng
- Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| | - Xiao-Ou Shu
- Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN
| |
Collapse
|
11
|
Murphy SE. Biochemistry of nicotine metabolism and its relevance to lung cancer. J Biol Chem 2021; 296:100722. [PMID: 33932402 PMCID: PMC8167289 DOI: 10.1016/j.jbc.2021.100722] [Citation(s) in RCA: 29] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2021] [Revised: 04/26/2021] [Accepted: 04/27/2021] [Indexed: 12/27/2022] Open
Abstract
Nicotine is the key addictive constituent of tobacco. It is not a carcinogen, but it drives smoking and the continued exposure to the many carcinogens present in tobacco. The investigation into nicotine biotransformation has been ongoing for more than 60 years. The dominant pathway of nicotine metabolism in humans is the formation of cotinine, which occurs in two steps. The first step is cytochrome P450 (P450, CYP) 2A6–catalyzed 5′-oxidation to an iminium ion, and the second step is oxidation of the iminium ion to cotinine. The half-life of nicotine is longer in individuals with low P450 2A6 activity, and smokers with low activity often decrease either the intensity of their smoking or the number of cigarettes they use compared with those with “normal” activity. The effect of P450 2A6 activity on smoking may influence one's tobacco-related disease risk. This review provides an overview of nicotine metabolism and a summary of the use of nicotine metabolite biomarkers to define smoking dose. Some more recent findings, for example, the identification of uridine 5′-diphosphoglucuronosyltransferase 2B10 as the catalyst of nicotine N-glucuronidation, are discussed. We also describe epidemiology studies that establish the contribution of nicotine metabolism and CYP2A6 genotype to lung cancer risk, particularly with respect to specific racial/ethnic groups, such as those with Japanese, African, or European ancestry. We conclude that a model of nicotine metabolism and smoking dose could be combined with other lung cancer risk variables to more accurately identify former smokers at the highest risk of lung cancer and to intervene accordingly.
Collapse
Affiliation(s)
- Sharon E Murphy
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota, USA.
| |
Collapse
|
12
|
Association between Metabolites and the Risk of Lung Cancer: A Systematic Literature Review and Meta-Analysis of Observational Studies. Metabolites 2020; 10:metabo10090362. [PMID: 32899527 PMCID: PMC7570231 DOI: 10.3390/metabo10090362] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/17/2020] [Accepted: 08/24/2020] [Indexed: 12/12/2022] Open
Abstract
Globally, lung cancer is the most prevalent cancer type. However, screening and early detection is challenging. Previous studies have identified metabolites as promising lung cancer biomarkers. This systematic literature review and meta-analysis aimed to identify metabolites associated with lung cancer risk in observational studies. The literature search was performed in PubMed and EMBASE databases, up to 31 December 2019, for observational studies on the association between metabolites and lung cancer risk. Heterogeneity was assessed using the I2 statistic and Cochran’s Q test. Meta-analyses were performed using either a fixed-effects or random-effects model, depending on study heterogeneity. Fifty-three studies with 297 metabolites were included. Most identified metabolites (252 metabolites) were reported in individual studies. Meta-analyses were conducted on 45 metabolites. Five metabolites (cotinine, creatinine riboside, N-acetylneuraminic acid, proline and r-1,t-2,3,c-4-tetrahydroxy-1,2,3,4-tetrahydrophenanthrene) and five metabolite groups (total 3-hydroxycotinine, total cotinine, total nicotine, total 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol (sum of concentrations of the metabolite and its glucuronides), and total nicotine equivalent (sum of total 3-hydroxycotinine, total cotinine and total nicotine)) were associated with higher lung cancer risk, while three others (folate, methionine and tryptophan) were associated with lower lung cancer risk. Significant heterogeneity was detected across most studies. These significant metabolites should be further evaluated as potential biomarkers for lung cancer.
Collapse
|
13
|
Ambrose JA, Najafi A, Jain V, Muller JE, Ranka S, Barua RS. Reducing Tobacco-Related Disability in Chronic Smokers. Am J Med 2020; 133:908-915. [PMID: 32325048 DOI: 10.1016/j.amjmed.2020.03.025] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/10/2020] [Revised: 03/17/2020] [Accepted: 03/18/2020] [Indexed: 02/02/2023]
Abstract
Tobacco consumption (predominantly cigarettes) is the leading preventable cause of mortality worldwide. Although the major focus of strategies to reduce mortality from tobacco must include prevention of future generations from initially gaining access, some smokers are unwilling or unable to quit. Can the higher risk chronic smoker be identified and can their risk be reduced? The risk of adverse events in cigarette smokers is influenced by the intensity and duration of cigarette smoking or secondhand exposure, associated conventional risk factors, environmental stressors, and certain genetic variants and epigenetic modifiers. Recent data suggest that inflammatory markers such as high-sensitivity C-reactive protein (hs CRP) and targeted imaging can identify some smokers at higher risk. As smoking is prothrombotic, aspirin initiation and expanded statin use might reduce cardiovascular risk in those who do not presently meet criteria for these therapies, but further study is required. Thus, although advocacy for smoking cessation should always be the primary approach, increased efforts are needed to identify and potentially treat those who are unable or unwilling to quit.
Collapse
Affiliation(s)
- John A Ambrose
- University of California, San Francisco, Fresno Medical Education Program, Fresno, Calif.
| | - Amir Najafi
- University of California, San Francisco, Fresno Medical Education Program, Fresno, Calif
| | - Vipul Jain
- University of California, San Francisco, Fresno Medical Education Program, Fresno, Calif
| | | | - Sagar Ranka
- University of Kansas Medical Center, Kansas City Veterans' Administration, Kansas City, Mo
| | - Rajat S Barua
- University of Kansas Medical Center, Kansas City Veterans' Administration, Kansas City, Mo
| |
Collapse
|
14
|
Thomas CE, Wang R, Adams-Haduch J, Murphy SE, Ueland PM, Midttun Ø, Brennan P, Johansson M, Gao YT, Yuan JM. Urinary Cotinine Is as Good a Biomarker as Serum Cotinine for Cigarette Smoking Exposure and Lung Cancer Risk Prediction. Cancer Epidemiol Biomarkers Prev 2020; 29:127-132. [PMID: 31685561 PMCID: PMC7695222 DOI: 10.1158/1055-9965.epi-19-0653] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Revised: 08/01/2019] [Accepted: 10/29/2019] [Indexed: 12/24/2022] Open
Abstract
BACKGROUND Cotinine is a metabolite of nicotine. Serum and urinary cotinine are validated biomarkers for cigarette exposure. Their performance for lung cancer risk prediction has not been simultaneously examined in epidemiologic studies. METHODS A nested case-control study, including 452 incident lung cancer cases and 452 smoking-matched controls in the Shanghai cohort study, was conducted. Mass spectrometry-based methods were used to quantify cotinine in serum and urine samples collected from current smokers at baseline, on average 10 years before cancer diagnosis of cases. Logistic regression was used to estimate ORs, 95% confidence intervals (CI), and AUC ROC for lung cancer associated with higher levels of cotinine. RESULTS Serum and urinary cotinine levels were significantly higher in lung cancer cases than controls. Compared with the lowest quartile serum cotinine (≤0.40 nmol/mL), the OR of lung cancer for smokers in the highest quartiles (>1.39 nmol/mL) was 5.46 (95% CI, 3.38-8.81). Similarly, the OR was 5.49 (95% CI, 3.39-8.87) for highest (>16.38 nmol/mg creatinine) relative to the lowest quartile of urinary total cotinine (≤4.11 nmol/mg creatinine). A risk prediction model yielded an AUC of 0.72 (95% CI, 0.69-0.75) for serum cotinine and 0.72 (95% CI, 0.69-0.75) for urinary total cotinine combined with smoking history. CONCLUSIONS Urinary and serum cotinine have the same performance in prediction of lung cancer risk for current smokers. IMPACT Urinary cotinine is a noninvasive biomarker that can replace serum cotinine in risk prediction of future lung cancer risk for current smokers.
Collapse
Affiliation(s)
- Claire E Thomas
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Renwei Wang
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Jennifer Adams-Haduch
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Sharon E Murphy
- Masonic Cancer Center, University of Minnesota, Minneapolis, Minnesota
- Department of Biochemistry, Molecular Biology and BioPhysics, University of Minnesota, Minneapolis, Minnesota
| | - Per Magne Ueland
- Department of Clinical Sciences, Laboratory of Clinical Biochemistry, University of Bergen, Bergen, Norway
- Laboratory of Clinical Biochemistry, Haukeland University Hospital, Bergen, Norway
| | | | - Paul Brennan
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Mattias Johansson
- Genetic Epidemiology Group, International Agency for Research on Cancer, Lyon, France
| | - Yu-Tang Gao
- Department of Epidemiology, Shanghai Cancer Institute, Shanghai Jiaotong University, Shanghai, China
| | - Jian-Min Yuan
- Division of Cancer Control and Population Sciences, UPMC Hillman Cancer Center, University of Pittsburgh, Pittsburgh, Pennsylvania.
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, Pennsylvania
| |
Collapse
|
15
|
Menon I, Bhat N. Association of passive smoking with dental caries and salivary biomarkers among 5-10 years old children of Muradnagar, Ghaziabad. J Family Med Prim Care 2019; 8:2633-2639. [PMID: 31548946 PMCID: PMC6753823 DOI: 10.4103/jfmpc.jfmpc_369_19] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2019] [Revised: 05/13/2019] [Accepted: 05/22/2019] [Indexed: 11/05/2022] Open
Abstract
Objectives: The purpose of this study is to assess the association of passive smoking (PS) with dental caries and salivary biomarkers among 5–10 years old children of Muradnagar, Ghaziabad. Methods: A case–control study was conducted among 160 children of age group 5–10 years who visited the outdoor patient department of a dental college. Regular smoking households were recognized and children who lived in smoking households were identified as PS subjects. Two categories of children were formed – PS (80 children) and control group (80 children). Parents completed a pretested questionnaire and clinical examination of children was done using dmft index and gingival index. This was followed by collection of stimulated saliva of children which was further subjected to determine salivary buffering capacity and pH. Inoculation on mitis salivarius-bacitracin agar for counting streptococcus colonies and Rogosa SL agar (Difco) for counting lactobacillus colonies was done. Cotinine level was then measured using enzyme-linked immunosorbent assay kit. Student's independent t-test, Mann–Whitney U test, and one-way analysis of variance test were used for analyzing data. Results: The mean streptococcus and lactobacillus colony count was higher in PS case subjects, that is, 348.9 ± 166.509 and 247.3 ± 15.86 in comparison to control group where the mean streptococcus and lactobacillus colony count was 63.03 ± 23.082 and 63.825 ± 12.638, respectively. The mean cotinine level among PS case subjects was 1.08 ± 0.265 which was higher than the control group, that is, 0.00 ± 0.00. The mean cotinine level was directly proportional to streptococcus colonies, lactobacillus colonies, dmft and gingival index (GI) scores, and smoking exposure. Conclusion: PS has deleterious impact on children which was reflected by their increased cotinine levels, streptococcus colonies, lactobacillus colonies, and poor dmft and GI scores in comparison to the control group.
Collapse
Affiliation(s)
- Ipseeta Menon
- Department of Public Health Dentistry, I.T.S College for Dental Sciences and Research, Delhi, India
| | - Nagesh Bhat
- Department of Public Health Dentistry, Pacific Dental College, Udaipur, Rajasthan, India
| |
Collapse
|