Maria Grau-Perez1, Jinying Zhao2, Brandon Pierce3, Kevin A Francesconi4, Walter Goessler4, Yun Zhu5, Qiang An6, Jason Umans7, Lyle Best8, Shelley A Cole9, Ana Navas-Acien10, Maria Tellez-Plaza11. 1. Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Area of Cardiometabolic and Renal Risk, Biomedical Research Institute Hospital Clinic of Valencia (INCLIVA), Valencia, Spain. Electronic address: mgrau@incliva.es. 2. Department of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA; Public Health Research, Division of Community Health Promotion, Florida Department of Health, Tallahassee, FL, USA. 3. Department of Public Health Sciences, University of Chicago, Chicago, IL, USA. 4. Institute of Chemistry, University of Graz, Graz, Austria. 5. Department of Epidemiology, College of Public Health and Health Professions, College of Medicine, University of Florida, Gainesville, FL, USA. 6. Public Health Research, Division of Community Health Promotion, Florida Department of Health, Tallahassee, FL, USA. 7. Georgetown-Howard Universities Center for Clinical and Translational Science, Washington DC, USA; MedStar Health Research Institute, Hyattsville, MD, USA. 8. Department of Epidemiology, Missouri Breaks Industries Research Inc., Timber Lake, SD, USA. 9. Department of Genetics, Texas Biomedical Research Institute, San Antonio, TX, USA. 10. Department of Environmental Health Sciences, Columbia University Mailman School of Public Health, New York, NY, USA; Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA. Electronic address: an2737@cumc.columbia.edu. 11. Area of Cardiometabolic and Renal Risk, Biomedical Research Institute Hospital Clinic of Valencia (INCLIVA), Valencia, Spain; Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD, USA; Department of Chronic Diseases Epidemiology, National Center for Epidemiology, Carlos III Health Institutes, Madrid, Spain.
Abstract
INTRODUCTION: While several mechanisms may explain metal-related health effects, the exact cellular processes are not fully understood. We evaluated the association between leukocyte telomere length (LTL) and urine arsenic (ΣAs), cadmium (Cd) and tungsten (W) exposure in the Strong Heart Study (SHS, N = 1702) and in the Strong Heart Family Study (SHFS, N = 1793). METHODS: Urine metal concentrations were measured using ICP-MS. Arsenic exposure was assessed as the sum of inorganic arsenic, monomethylarsonate and dimethylarsinate levels (ΣAs). LTL was measured by quantitative polymerase chain reaction. RESULTS: In the SHS, median levels were 1.09 for LTL, and 8.8, 1.01 and 0.11 μg/g creatinine for ΣAs, Cd, and W, respectively. In the SHFS, median levels were 1.01 for LTL, and 4.3, 0.44, and 0.10 μg/g creatinine. Among SHS participants, increased urine ΣAs, Cd, and W was associated with shorter LTL. The adjusted geometric mean ratio (95% confidence interval) of LTL per an increase equal to the difference between the percentiles 90th and 10th in metal distributions was 0.85 (0.79, 0.92) for ΣAs, 0.91 (0.84, 1.00) for Cd and 0.93 (0.88, 0.98) for W. We observed no significant associations among SHFS participants. The findings also suggest that the association between arsenic and LTL might be differential depending on the exposure levels or age. CONCLUSIONS: Additional research is needed to confirm the association between metal exposures and telomere length.
INTRODUCTION: While several mechanisms may explain metal-related health effects, the exact cellular processes are not fully understood. We evaluated the association between leukocyte telomere length (LTL) and urine arsenic (ΣAs), cadmium (Cd) and tungsten (W) exposure in the Strong Heart Study (SHS, N = 1702) and in the Strong Heart Family Study (SHFS, N = 1793). METHODS: Urine metal concentrations were measured using ICP-MS. Arsenic exposure was assessed as the sum of inorganic arsenic, monomethylarsonate and dimethylarsinate levels (ΣAs). LTLwas measured by quantitative polymerase chain reaction. RESULTS: In the SHS, median levels were 1.09 for LTL, and 8.8, 1.01 and 0.11 μg/g creatinine for ΣAs, Cd, and W, respectively. In the SHFS, median levels were 1.01 for LTL, and 4.3, 0.44, and 0.10 μg/g creatinine. Among SHS participants, increased urine ΣAs, Cd, and Wwas associated with shorter LTL. The adjusted geometric mean ratio (95% confidence interval) of LTL per an increase equal to the difference between the percentiles 90th and 10th in metal distributions was 0.85 (0.79, 0.92) for ΣAs, 0.91 (0.84, 1.00) for Cd and 0.93 (0.88, 0.98) for W. We observed no significant associations among SHFS participants. The findings also suggest that the association between arsenic and LTL might be differential depending on the exposure levels or age. CONCLUSIONS: Additional research is needed to confirm the association between metal exposures and telomere length.
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