Diddier Prada1, Elena Colicino2, Melinda C Power3, Marc G Weisskopf4, Jia Zhong2, Lifang Hou5, Avron Spiro6, Pantel Vokonas7, Kasey Brenan2, Luis A Herrera8, Joel Schwartz4, Robert Wright, Howard Hu, Andrea A Baccarelli9. 1. Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA; Unidad de Investigación Biomédica en Cáncer, Instituto Nacional de Cancerología - Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City 14080, Mexico. 2. Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA. 3. Department of Epidemiology and Biostatistics, George Washington University Milken Institute of Public Health, 950 New Hampshire Avenue NW, Washington, DC 20052, USA. 4. Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA. 5. Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, 420 East Superior St, Chicago, IL 60611, USA. 6. Veterans Affairs Boston Healthcare System, 150 South Huntington Ave, Boston, MA 02130, USA; Department of Epidemiology, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA; Department of Psychiatry, Boston University School of Medicine, 72 East Concord Street, Boston, MA 02118, USA. 7. Veterans Affairs Boston Healthcare System, 150 South Huntington Ave, Boston, MA 02130, USA; Department of Epidemiology, Boston University School of Public Health, 715 Albany Street, Boston, MA 02118, USA. 8. Unidad de Investigación Biomédica en Cáncer, Instituto Nacional de Cancerología - Instituto de Investigaciones Biomédicas, Universidad Nacional Autónoma de México, Mexico City 14080, Mexico. 9. Department of Environmental Health, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA; Department of Epidemiology, Harvard T.H. Chan School of Public Health, 665 Huntington Ave, Boston, MA 02115, USA. Electronic address: ab4303@cumc.columbia.edu.
Abstract
BACKGROUND: Continuing chronic and sporadic high-level of lead exposure in some regions in the U.S. has directed public attention to the effects of lead on human health. Long-term lead exposure has been associated with faster cognitive decline in older individuals; however, genetic susceptibility to lead-related cognitive decline during aging has been poorly studied. METHODS: We determined the interaction of APOE-epsilon variants and environmental lead exposure in relation to age-related cognitive decline. We measured tibia bone lead by K-shell-x-ray fluorescence, APOE-epsilon variants by multiplex PCR and global cognitive z-scores in 489 men from the VA-Normative Aging Study. To determine global cognitive z-scores we incorporated multiple cognitive assessments, including word list memory task, digit span backwards, verbal fluency test, sum of drawings, and pattern comparison task, which were assessed at multiple visits. We used linear mixed-effect models with random intercepts for individual and for cognitive test. RESULTS: An interquartile range (IQR:14.23μg/g) increase in tibia lead concentration was associated with a 0.06 (95% confidence interval [95%CI]: -0.11 to -0.01) lower global cognition z-score. In the presence of both ε4 alleles, one IQR increase in tibia lead was associated with 0.57 (95%CI: -0.97 to -0.16; p-value for interaction: 0.03) lower total cognition z-score. A borderline association was observed in presence of one ε4 allele (Estimate-effect per 1-IQR increase: -0.11, 95%CI: -0.22, 0.01) as well as lack of association in individuals without APOE ε4 allele. CONCLUSIONS: Our findings suggest that individuals carrying both ε4 alleles are more susceptible to lead impact on global cognitive decline during aging.
BACKGROUND: Continuing chronic and sporadic high-level of lead exposure in some regions in the U.S. has directed public attention to the effects of lead on human health. Long-term lead exposure has been associated with faster cognitive decline in older individuals; however, genetic susceptibility to lead-related cognitive decline during aging has been poorly studied. METHODS: We determined the interaction of APOE-epsilon variants and environmental lead exposure in relation to age-related cognitive decline. We measured tibia bone lead by K-shell-x-ray fluorescence, APOE-epsilon variants by multiplex PCR and global cognitive z-scores in 489 men from the VA-Normative Aging Study. To determine global cognitive z-scores we incorporated multiple cognitive assessments, including word list memory task, digit span backwards, verbal fluency test, sum of drawings, and pattern comparison task, which were assessed at multiple visits. We used linear mixed-effect models with random intercepts for individual and for cognitive test. RESULTS: An interquartile range (IQR:14.23μg/g) increase in tibia lead concentration was associated with a 0.06 (95% confidence interval [95%CI]: -0.11 to -0.01) lower global cognition z-score. In the presence of both ε4 alleles, one IQR increase in tibia lead was associated with 0.57 (95%CI: -0.97 to -0.16; p-value for interaction: 0.03) lower total cognition z-score. A borderline association was observed in presence of one ε4 allele (Estimate-effect per 1-IQR increase: -0.11, 95%CI: -0.22, 0.01) as well as lack of association in individuals without APOE ε4 allele. CONCLUSIONS: Our findings suggest that individuals carrying both ε4 alleles are more susceptible to lead impact on global cognitive decline during aging.
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