Maria Grau-Perez1, Gernot Pichler2, Inma Galan-Chilet3, Laisa S Briongos-Figuero4, Pilar Rentero-Garrido3, Raul Lopez-Izquierdo4, Ana Navas-Acien5, Virginia Weaver6, Tamara García-Barrera7, Jose L Gomez-Ariza7, Juan C Martín-Escudero4, F Javier Chaves8, Josep Redon9, Maria Tellez-Plaza10. 1. Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, USA; Area of Cardiometabolic and Renal Risk, Institute for Biomedical Research INCLIVA, Valencia, Spain. 2. Area of Cardiometabolic and Renal Risk, Institute for Biomedical Research INCLIVA, Valencia, Spain; Department of Internal Medicine, Hospital Clínico de Valencia, University of Valencia, Spain. 3. Genotyping and Genetic Diagnosis Unit, Institute for Biomedical Research INCLIVA, Valencia, Spain. 4. Department of Internal Medicine, University Hospital Rio Hortega, Valladolid, Spain. 5. Department of Environmental Health Sciences, Mailman School of Public Health, Columbia University, New York, USA; Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA. 6. Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA. 7. Department of Chemistry, Faculty of Experimental Science, University of Huelva, Huelva, Spain; Research Center of Health and Environment (CYSMA), University of Huelva, Huelva, Spain. 8. Genotyping and Genetic Diagnosis Unit, Institute for Biomedical Research INCLIVA, Valencia, Spain; CIBER of Diabetes and Associated Metabolic Diseases (CIBERDEM), Barcelona, Spain. 9. Area of Cardiometabolic and Renal Risk, Institute for Biomedical Research INCLIVA, Valencia, Spain; CIBER Physiopathology of Obesity and Nutrition (CIBEROBN), Institute of Health Carlos III, Minister of Health, Madrid, Spain; Department of Internal Medicine, Hospital Clínico de Valencia, University of Valencia, Spain. 10. Area of Cardiometabolic and Renal Risk, Institute for Biomedical Research INCLIVA, Valencia, Spain; Department of Environmental Health Sciences, Johns Hopkins Bloomberg School of Public Health, Baltimore, USA. Electronic address: maria.tellez@uv.es.
Abstract
BACKGROUND: The interaction of cadmium with genes involved in oxidative stress, cadmium metabolism and transport pathways on albuminuria can provide biological insight on the relationship between cadmium and albuminuria at low exposure levels. OBJECTIVES: We tested the hypothesis that specific genotypes in candidate genes may confer increased susceptibility to cadmium exposure. METHODS: Cadmium exposure was estimated by inductively coupled plasma mass spectrometry (ICPMS) in urine from 1397 men and women aged 18-85years participating in the Hortega Study, a representative sample of a general population from Spain. Urine albumin was measured by automated nephelometric immunochemistry. Abnormal albuminuria was defined as urine albumin greater than or equal to 30mg/g. RESULTS: The weighted prevalence of abnormal albuminuria was 6.3%. The median level of urine cadmium was 0.39 (IQR, 0.23-0.65) μg/g creatinine. Multivariable-adjusted geometric mean ratios of albuminuria comparing the two highest to the lowest tertile of urine cadmium were 1.62 (95% CI, 1.43-1.84) and 2.94 (95% CI, 2.58-3.35), respectively. The corresponding odds ratios of abnormal albuminuria were 1.58 (0.83, 3.02) and 4.54 (2.58, 8.00). The association between urine cadmium and albuminuria was observed across all participant subgroups evaluated including participants without hypertension, diabetes or chronic kidney disease. We observed Bonferroni-corrected statistically significant interactions between urine cadmium levels and polymorphisms in gene SLC30A7 and RAC1. CONCLUSIONS: Increasing urine cadmium concentrations were cross-sectionally associated with increased albuminuria in a representative sample of a general population from Spain. Genetic variation in oxidative stress and cadmium metabolism and transport genes may confer differential susceptibility to potential cadmium effects.
BACKGROUND: The interaction of cadmium with genes involved in oxidative stress, cadmium metabolism and transport pathways on albuminuria can provide biological insight on the relationship between cadmium and albuminuria at low exposure levels. OBJECTIVES: We tested the hypothesis that specific genotypes in candidate genes may confer increased susceptibility to cadmium exposure. METHODS:Cadmium exposure was estimated by inductively coupled plasma mass spectrometry (ICPMS) in urine from 1397 men and women aged 18-85years participating in the Hortega Study, a representative sample of a general population from Spain. Urine albumin was measured by automated nephelometric immunochemistry. Abnormal albuminuria was defined as urine albumin greater than or equal to 30mg/g. RESULTS: The weighted prevalence of abnormal albuminuria was 6.3%. The median level of urine cadmium was 0.39 (IQR, 0.23-0.65) μg/g creatinine. Multivariable-adjusted geometric mean ratios of albuminuria comparing the two highest to the lowest tertile of urine cadmium were 1.62 (95% CI, 1.43-1.84) and 2.94 (95% CI, 2.58-3.35), respectively. The corresponding odds ratios of abnormal albuminuria were 1.58 (0.83, 3.02) and 4.54 (2.58, 8.00). The association between urine cadmium and albuminuria was observed across all participant subgroups evaluated including participants without hypertension, diabetes or chronic kidney disease. We observed Bonferroni-corrected statistically significant interactions between urine cadmium levels and polymorphisms in gene SLC30A7 and RAC1. CONCLUSIONS: Increasing urine cadmium concentrations were cross-sectionally associated with increased albuminuria in a representative sample of a general population from Spain. Genetic variation in oxidative stress and cadmium metabolism and transport genes may confer differential susceptibility to potential cadmium effects.
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