| Literature DB >> 15522122 |
Ines A Silva1, Jennifer F Nyland, Andrew Gorman, Andre Perisse, Ana Maria Ventura, Elizabeth C O Santos, Jose M de Souza, C L Burek, Noel R Rose, Ellen K Silbergeld.
Abstract
BACKGROUND: Mercury is an immunotoxic metal that induces autoimmune disease in rodents. Highly susceptible mouse strains such as SJL/N, A.SW, B10.S (H-2s) develop multiple autoimmune manifestations after exposure to inorganic mercury, including lymphoproliferation, elevated levels of autoantibodies, overproduction of IgG and IgE, and circulating immune complexes in kidney and vasculature. A few studies have examined relationships between mercury exposures and adverse immunological reactions in humans, but there is little evidence of mercury-associated autoimmunity in humans.Entities:
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Year: 2004 PMID: 15522122 PMCID: PMC538267 DOI: 10.1186/1476-069X-3-11
Source DB: PubMed Journal: Environ Health ISSN: 1476-069X Impact factor: 5.984
Demographic characterization of the 3 populations
| Current Occupation (%) | Prev. Occupation | |||||||
| Populations | N | Age [Mean] | Sex (%) F/M | Gold Mine | Fisherman | Others | Students | Gold Miner (%) |
| Tabatinga-adults | 98 | 44 | 73/27 | 0 | 1.1 | 98.9 | 0 | 0 |
| Jacareacanga | 140 | 25 | 54/46 | 0 | 2.2 | 72.4 | 25.4 | 9.4 |
| Rio-Rato | 98 | 30 | 35/65 | 54 | 0 | 46 | 0 | N/A |
N/A = data not available from original survey.
Figure 1Distribution of mercury levels Population distributions are shown for (A) Tabatinga and (B) Jacareacanga in μg Hg/g hair and (C) Rio-Rato in μg Hg/L urine.
Malaria and Hg data from the 3 populations Malaria status (prevalent and reported past infections) and mercury exposures in the three populations.
| Malaria | Hg (median) | Hg | |||
| Populations | Prevalent (%) | History (%) | Urine (microgram/L) | Hair (microgram/g) | range values |
| Tabatinga-adults N = 98 | 0 | 10.1 | ND | 6.4 | 1.19–16.96 |
| Jacareacanga N = 140 | 0 | 69.6 | ND | 8 | 0.29–58.47 |
| Rio-Rato N = 98 | 93.9 | N/A | 4 | ND | 0.01–81.37 |
N/A = data not available from original survey.
ND = analysis not completed in original survey.
Percentages of detectable ANA and ANoA in serum from the 3 populations
| ANA (%) | ANoA (%) | ANA + ANoA (%) | |||||||
| Populations | <det | ≥1:10 | ≥1:40 | <det | ≥1:10 | ≥1:40 | <det | ≥1:10 | ≥1:40 |
| Tabatinga-adults N = 98 | 92.9 | 7.1 | 2.0 | 97.9 | 2.1 | 0 | 100 | 0 | 0 |
| Jacareacanga N = 140 | 89.3 | 10.7 | 3.6 | 82.0 | 18.0 | 13.0 | 100 | 0 | 0 |
| Rio-Rato N = 98 | 45.9 | 54.1 | 51.0 | 59.2 | 40.8 | 36.7 | 89.0 | 11.0 | 10.0 |
ANA ≥1:10 or ANoA ≥1:10 percentages include ANA 1 1:40 or ANoA ≥1:40 percentages.
Figure 2Detectable levels of serum autoantibodies Population distributions of (A, C, E) ANA and (B, D, F) ANoA are shown for (A&B) Rio-Rato, (C&D) Jacareacanga and (E&F) Tabatinga, at varying serum dilutions.
Jacareacanga-odds ratio between risk factors and prevalence of ANoA ≥1:10 Logistical model for odds of detectable ANoA (≥1:10) and mercury exposure, gender, age, occupation, and malaria history, p < 0.05*.
| Variable | Odds ratio | 95% Confidence interval | p-value |
| Hg | 3.27 | 1.28 – 8.37 | 0.014* |
| Gender | 1.16 | 0.44 – 3.02 | 0.769 |
| Age | 0.93 | 0.36 – 2.39 | 0.871 |
| Past-malaria | 1.28 | 0.43 – 3.83 | 0.663 |
| N past-malaria infections | 1.18 | 0.39 – 3.55 | 0.772 |
| Other occupations: gold miner | 0.74 | 0.14 – 3.75 | 0.711 |
Serum ANA and ANoA (Jacareacanga) stratified for mercury and past malaria infections P values obtained comparing Hg <8 with >8 μg/g hair (* p < 0.05) and number of malaria infections <4 with ≥4 (§p < 0.05).
| ANA 1:10 | 3.61 | 17.65 § |
| ANA 1:40 | 0 | 11.76 § |
| ANoA 1:10 | 12.05 | 17.65 |
| ANoA 1:40 | 8.43 | 17.65 |
| ANA 1:10 | 14.81 * | 10.00 |
| ANA 1:40 | 11.11 * | 0 |
| ANoA 1:10 | 33.33 * | 30.00 |
| ANoA 1:40 | 22.22 | 20.00 |
Figure 3AFA in Rio-Rato serum samples Photograph of denaturing gel electrophoresis of 3 AFA positive samples from 41 ANoA positive serum samples previously determined by IIF. Fibrillarin = 34 Kda protein.