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Domingo-Relloso A, Joehanes R, Rodriguez-Hernandez Z, Lahousse L, Haack K, Fallin MD, Herreros-Martinez M, Umans JG, Best LG, Huan T, Liu C, Ma J, Yao C, Jerolon A, Bermudez JD, Cole SA, Rhoades DA, Levy D, Navas-Acien A, Tellez-Plaza M. Smoking, blood DNA methylation sites and lung cancer risk. Environ Pollut 2023; 334:122153. [PMID: 37442331 PMCID: PMC10528956 DOI: 10.1016/j.envpol.2023.122153] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 06/07/2023] [Accepted: 07/04/2023] [Indexed: 07/15/2023]
Abstract
Altered DNA methylation (DNAm) might be a biological intermediary in the pathway from smoking to lung cancer. In this study, we investigated the contribution of differential blood DNAm to explain the association between smoking and lung cancer incidence. Blood DNAm was measured in 2321 Strong Heart Study (SHS) participants. Incident lung cancer was assessed as time to event diagnoses. We conducted mediation analysis, including validation with DNAm and paired gene expression data from the Framingham Heart Study (FHS). In the SHS, current versus never smoking and pack-years single-mediator models showed, respectively, 29 and 21 differentially methylated positions (DMPs) for lung cancer with statistically significant mediated effects (14 of 20 available, and five of 14 available, positions, replicated, respectively, in FHS). In FHS, replicated DMPs showed gene expression downregulation largely in trans, and were related to biological pathways in cancer. The multimediator model identified that DMPs annotated to the genes AHRR and IER3 jointly explained a substantial proportion of lung cancer. Thus, the association of smoking with lung cancer was partly explained by differences in baseline blood DNAm at few relevant sites. Experimental studies are needed to confirm the biological role of identified eQTMs and to evaluate potential implications for early detection and control of lung cancer.
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Affiliation(s)
- Arce Domingo-Relloso
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain; Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Department of Statistics and Operations Research, University of Valencia, Spain.
| | - Roby Joehanes
- Population Sciences Branch, National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, USA; Framingham Heart Study, Framingham, MA, USA
| | - Zulema Rodriguez-Hernandez
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
| | - Lies Lahousse
- Department of Epidemiology, Erasmus MC University Medical Center, Rotterdam, the Netherlands; Department of Bioanalysis, Faculty of Pharmaceutical Sciences, Ghent University, Ghent, Belgium
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - M Daniele Fallin
- Department of Mental Health, Johns Hopkins University, Baltimore, USA; Department of Epidemiology, Johns Hopkins University, Baltimore, USA
| | | | - Jason G Umans
- MedStar Health Research Institute, Washington DC, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA
| | - Lyle G Best
- Missouri Breaks Industries and Research Inc., Eagle Butte, SD, USA
| | - Tianxiao Huan
- Framingham Heart Study, Framingham, MA, USA; University of Massachusetts Medical School, Worcester, MA, USA
| | - Chunyu Liu
- Framingham Heart Study, Framingham, MA, USA; Boston University School of Public Health, Boston, MA, USA
| | - Jiantao Ma
- Framingham Heart Study, Framingham, MA, USA; Tufts University Friedman School of Nutrition Science and Policy, Boston, MA, USA
| | - Chen Yao
- Framingham Heart Study, Framingham, MA, USA; Bristol Myers Squibb, Cambridge, MA, USA
| | - Allan Jerolon
- Université Paris Cité, CNRS, MAP5, F-75006, Paris, France
| | - Jose D Bermudez
- Department of Statistics and Operations Research, University of Valencia, Spain
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Dorothy A Rhoades
- Stephenson Cancer Center, University of Oklahoma Health Sciences Department of Medicine, Oklahoma City, OK, USA
| | - Daniel Levy
- Population Sciences Branch, National Heart, Lung, And Blood Institute, National Institutes of Health, Bethesda, MD, USA; Framingham Heart Study, Framingham, MA, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
| | - Maria Tellez-Plaza
- Integrative Epidemiology Group, Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institute, Madrid, Spain
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Li Z, Lewin M, Ruiz P, Nigra AE, Henderson NB, Jarrett JM, Ward C, Zhu J, Umans JG, O'Leary M, Zhang Y, Ragin-Wilson A, Navas-Acien A. Blood cadmium, lead, manganese, mercury, and selenium levels in American Indian populations: The Strong Heart Study. Environ Res 2022; 215:114101. [PMID: 35977585 PMCID: PMC9644284 DOI: 10.1016/j.envres.2022.114101] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 08/08/2022] [Accepted: 08/09/2022] [Indexed: 05/15/2023]
Abstract
BACKGROUND Many American Indian (AI) communities are in areas affected by environmental contamination, such as toxic metals. However, studies assessing exposures in AI communities are limited. We measured blood metals in AI communities to assess historical exposure and identify participant characteristics associated with these levels in the Strong Heart Study (SHS) cohort. METHOD Archived blood specimens collected from participants (n = 2014, all participants were 50 years of age and older) in Arizona, Oklahoma, and North and South Dakota during SHS Phase-III (1998-1999) were analyzed for cadmium, lead, manganese, mercury, and selenium using inductively coupled plasma triple quadrupole mass spectrometry. We conducted descriptive analyses for the entire cohort and stratified by selected subgroups, including selected demographics, health behaviors, income, waist circumference, and body mass index. Bivariate associations were conducted to examine associations between blood metal levels and selected socio-demographic and behavioral covariates. Finally, multivariate regression models were used to assess the best model fit that predicted blood metal levels. FINDINGS All elements were detected in 100% of study participants, with the exception of mercury (detected in 73% of participants). The SHS population had higher levels of blood cadmium and manganese than the general U.S. population 50 years and older. The median blood mercury in the SHS cohort was at about 30% of the U.S. reference population, potentially due to low fish consumption. Participants in North Dakota and South Dakota had the highest blood cadmium, lead, manganese, and selenium, and the lowest total mercury levels, even after adjusting for covariates. In addition, each of the blood metals was associated with selected demographic, behavioral, income, and/or weight-related factors in multivariate models. These findings will help guide the tribes to develop education, outreach, and strategies to reduce harmful exposures and increase beneficial nutrient intake in these AI communities.
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Affiliation(s)
- Zheng Li
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA.
| | - Michael Lewin
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Patricia Ruiz
- Office of Innovation and Analytics, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Anne E Nigra
- Department of Environmental Health Sciences, School of Public Health, Columbia University, New York City, NY, USA
| | - Noelle B Henderson
- Office of Community Health and Hazard Assessment, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jeffery M Jarrett
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Cynthia Ward
- Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Jianhui Zhu
- MedStar Health Research Institute, Hyattsville, MD, USA
| | - Jason G Umans
- MedStar Health Research Institute, Hyattsville, MD, USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA
| | - Marcia O'Leary
- Missouri Breaks Industries and Research, Inc., Eagle Butte, SD, USA
| | - Ying Zhang
- Center for American Indian Health Research, University of Oklahoma Health Sciences Center, Oklahoma City, OK, USA
| | - Angela Ragin-Wilson
- Office of Associate Director, Agency for Toxic Substances and Disease Registry, Centers for Disease Control and Prevention, Atlanta, GA, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, School of Public Health, Columbia University, New York City, NY, USA
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Nigra AE, Olmedo P, Grau-Perez M, O'Leary R, O'Leary M, Fretts AM, Umans JG, Best LG, Francesconi KA, Goessler W, Cole SA, Navas-Acien A. Dietary determinants of inorganic arsenic exposure in the Strong Heart Family Study. Environ Res 2019; 177:108616. [PMID: 31442790 PMCID: PMC6748659 DOI: 10.1016/j.envres.2019.108616] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/02/2019] [Revised: 07/08/2019] [Accepted: 07/26/2019] [Indexed: 05/19/2023]
Abstract
BACKGROUND Chronic exposure to inorganic arsenic (iAs) in the US occurs mainly through drinking water and diet. Although American Indian (AI) populations have elevated urinary arsenic concentrations compared to the general US population, dietary sources of arsenic exposure in AI populations are not well characterized. METHODS We evaluated food frequency questionnaires to determine the major dietary sources of urinary arsenic concentrations (measured as the sum of arsenite, arsenate, monomethylarsonate, and dimethylarsinate, ΣAs) for 1727 AI participants in the Strong Heart Family Study (SHFS). We compared geometric mean ratios (GMRs) of urinary ΣAs for an interquartile range (IQR) increase in reported food group consumption. Exploratory analyses were stratified by gender and study center. RESULTS In fully adjusted generalized estimating equation models, the percent increase (95% confidence interval) of urinary ΣAs per increase in reported food consumption corresponding to the IQR was 13% (5%, 21%) for organ meat, 8% (4%, 13%) for rice, 7% (2%, 13%) for processed meat, and 4% (1%, 7%) for non-alcoholic drinks. In analyses stratified by study center, the association with organ meat was only observed in North/South Dakota. Consumption of red meat [percent increase -7% (-11%, -3%)] and fries and chips [-6% (-10%, -2%)] was inversely associated with urinary ΣAs. CONCLUSIONS Organ meat, processed meat, rice, and non-alcoholic drinks contribute to ΣAs exposure in the SHFS population. Organ meat is a unique source of ΣAs exposure for North and South Dakota participants and may reflect local food consumption. Further studies should comprehensively evaluate drinking water arsenic in SHFS communities and determine the relative contribution of diet and drinking water to total arsenic exposure.
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Affiliation(s)
- Anne E Nigra
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA.
| | - Pablo Olmedo
- Department of Legal Medicine and Toxicology, School of Medicine, University of Granada, Granada, Spain
| | - Maria Grau-Perez
- Area of Cardiometabolic and Renal Risk, Biomedical Research Institute Hospital Clinic of Valencia, Valencia, Spain
| | - Rae O'Leary
- Missouri Breaks Industries Research Inc, Eagle Butte, SD, USA
| | - Marcia O'Leary
- Missouri Breaks Industries Research Inc, Eagle Butte, SD, USA
| | - Amanda M Fretts
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Jason G Umans
- MedStar Health Research Institute; Washington, DC, USA
| | - Lyle G Best
- Missouri Breaks Industries Research Inc, Eagle Butte, SD, USA
| | | | | | - Shelley A Cole
- Texas Biomedical Research Institute, Hyattsville, MD, USA
| | - Ana Navas-Acien
- Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA
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Ferrara LA, Wang H, Umans JG, Franceschini N, Jolly S, Lee ET, Yeh J, Devereux RB, Howard BV, de Simone G. Serum uric acid does not predict incident metabolic syndrome in a population with high prevalence of obesity. Nutr Metab Cardiovasc Dis 2014; 24:1360-1364. [PMID: 25063537 PMCID: PMC4250289 DOI: 10.1016/j.numecd.2014.06.002] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/27/2014] [Revised: 05/19/2014] [Accepted: 06/09/2014] [Indexed: 01/05/2023]
Abstract
AIM To evaluate whether uric acid (UA) predicts 4-yr incidence of metabolic syndrome (MetS) in non-diabetic participants of the Strong Heart Study (SHS) cohort. METHODS AND RESULTS In this population-based prospective study we analyzed 1499 American Indians (890 women), without diabetes or MetS, controlled during the 4th SHS exam and re-examined 4 years later during the 5th SHS exam. Participants were divided into sex-specific tertiles of UA and the first two tertiles (group N) were compared with the third tertile (group H). Body mass index (BMI = 28.3 ± 7 vs. 31.1 ± 7 kg/m(2)), fat-free mass (FFM = 52.0 ± 14 vs. 54.9 ± 11 kg), waist-to-hip ratio, HOMA-IR (3.66 vs. 4.26), BP and indices of inflammation were significantly higher in group H than in group N (all p < 0.001). Incident MetS at the time of the 5th exam was more frequent in group H than group N (35 vs. 28%, OR 1.44 (95% CI = 1.10-1.91; p < 0.01). This association was still significant (OR = 1.13, p = 0.04) independently of family relatedness, sex, history of hypertension, HOMA-IR, central adiposity and renal function, but disappeared when fat-free mass was included in the model. CONCLUSIONS In the SHS, UA levels are associated to parameters of insulin resistance and to indices of inflammation. UA levels, however, do not predict incident MetS independently of the initial obesity-related increased FFM.
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Affiliation(s)
- L A Ferrara
- Department of Clinical Medicine and Surgery, Federico II University, Via S. Pansini 5, 80131 Naples, Italy.
| | - H Wang
- MedStar Health Research Institute, Washington, D.C., USA
| | - J G Umans
- MedStar Health Research Institute, Washington, D.C., USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, D.C., USA
| | - N Franceschini
- University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - S Jolly
- General Internal Medicine, Cleveland Clinic Medicine Institute, USA
| | - E T Lee
- Center for American Indian Health Research, University of Oklahoma, Oklahoma City, OK, USA
| | - J Yeh
- Center for American Indian Health Research, University of Oklahoma, Oklahoma City, OK, USA
| | - R B Devereux
- Department of Medicine, Weill Cornell Medical College, New York, NY, USA
| | - B V Howard
- MedStar Health Research Institute, Washington, D.C., USA; Georgetown-Howard Universities Center for Clinical and Translational Science, Washington, D.C., USA
| | - G de Simone
- Department of Medicine, Weill Cornell Medical College, New York, NY, USA; Department of Translational Medical Sciences, Federico II University, Naples, Italy
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