Human adaptation to arsenic in Bolivians living in the Andes

Genotoxicity in humans exposed to arsenic, lithium, and boron in drinking water in the Bolivian Andes-A cross sectional study

Elevated concentrations of arsenic, lithium and boron in drinking water have already been reported in Bolivia. Arsenic is known to cause genotoxicity but that caused by lithium and boron is less well known. The aim of the present cross-sectional study was to evaluate potential genotoxic effects of exposure to arsenic, while considering exposure to lithium and boron and genetic susceptibility. Women (n = 230) were recruited in villages located around Lake Poopó. Exposure to arsenic was determined as the sum of concentrations of arsenic metabolites inorganic arsenic, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) in urine. Exposure to lithium and boron was determined based on their concentrations in urine. Genetic susceptibility was determined by GSTM1 (glutathione S-transferase-mu-1) and GSTT1 (glutathione S-transferase-theta-1) null genotypes and AS3MT (Arsenite Methyltransferase) rs3740393. Genotoxicity was measured in peripheral blood leukocytes using the comet assay. The geometric means of arsenic, lithium, and boron concentrations were 68, 897, and 3972 μg/L, respectively. GSTM1 and GSTT1 null carriers had more DNA strand breaks than gene carriers (p = .008, p = .005). We found no correlation between urinary arsenic and DNA strand breaks (rS = .03, p = .64), and only a weak non-significant positive association in the adjusted multivariate analysis (β = .09 [-.03; .22], p = .14). Surprisingly, increasing concentrations of lithium in urine were negatively correlated with DNA strand breaks (rS = -.24, p = .0006), and the association persisted in multivariate analysis after adjusting for arsenic (β = -.22 [-.36; -.08], p = .003). We found no association between boron and DNA strand breaks. The apparent protective effect of lithium merits further investigation.

Spatial distribution of arsenic and metals suggest a high ecotoxicological potential in Puno Bay, Lake Titicaca, Peru

Spatial distribution and interpolation methods provide a summarized overview about the pollution dispersion, concerning the environment's quality. A high-altitude lake was taken as a model to assess the metalloid As and metals Cr, Cu, Ni, Pb, Zn distribution in superficial sediment and classify them according to their ecotoxicological potential in the aquatic environment. Surface sediments were collected from 11 sites along Puno Bay located at the western area of Lake Titicaca, Peru, and analyzed for pseudo total-metals. Sediment concentration data and quality were plotted using the Inverse Distance Weighting (IDW) as an interpolation method. High concentrations of As were found especially in the outer bay (81.73 mg.kg^-1). Spatial heterogeneity was evidenced for metal by the coefficient of variation, although no significative differences were observed between the two bays applying a Kruskall Wallis test (p < 0.05, df = 1). Sediment quality classification showed that most metal values were below TEL and toxicity was unlikely to occur, only As exceeded threefold PEL values, which categorized sediment as "Very Bad", indicating a rather high ecotoxicological potential to the aquatic environment. In conclusion, spatial analysis connected to interpolation methods demonstrated the superficial sediment heterogeneity in Puno Bay.

Sequencing-based fine-mapping and in silico functional characterization of the 10q24.32 arsenic metabolism efficiency locus across multiple arsenic-exposed populations

Inorganic arsenic is highly toxic and carcinogenic to humans. Exposed individuals vary in their ability to metabolize arsenic, and variability in arsenic metabolism efficiency (AME) is associated with risks of arsenic-related toxicities. Inherited genetic variation in the 10q24.32 region, near the arsenic methyltransferase (AS3MT) gene, is associated with urine-based measures of AME in multiple arsenic-exposed populations. To identify potential causal variants in this region, we applied fine mapping approaches to targeted sequencing data generated for exposed individuals from Bangladeshi, American Indian, and European American populations (n = 2,357, 557, and 648 respectively). We identified three independent association signals for Bangladeshis, two for American Indians, and one for European Americans. The size of the confidence sets for each signal varied from 4 to 85 variants. There was one signal shared across all three populations, represented by the same SNP in American Indians and European Americans (rs191177668) and in strong linkage disequilibrium (LD) with a lead SNP in Bangladesh (rs145537350). Beyond this shared signal, differences in LD patterns, minor allele frequency (MAF) (e.g., rs12573221 ~13% in Bangladesh ~0.2% among American Indians), and/or heterogeneity in effect sizes across populations likely contributed to the apparent population specificity of the additional identified signals. One of our potential causal variants influences AS3MT expression and nearby DNA methylation in numerous GTEx tissue types (with rs4919690 as a likely causal variant). Several SNPs in our confidence sets overlap transcription factor binding sites and cis-regulatory elements (from ENCODE). Taken together, our analyses reveal multiple potential causal variants in the 10q24.32 region influencing AME, including a variant shared across populations, and elucidate potential biological mechanisms underlying the impact of genetic variation on AME.

Evolutionary Implications of Environmental Toxicant Exposure

Homo sapiens have been exposed to various toxins and harmful compounds that change according to various phases of human evolution. Population genetics studies showed that such exposures lead to adaptive genetic changes; while observing present exposures to different toxicants, the first molecular mechanism that confers plasticity is epigenetic remodeling and, in particular, DNA methylation variation, a molecular mechanism proposed for medium-term adaptation. A large amount of scientific literature from clinical and medical studies revealed the high impact of such exposure on human biology; thus, in this review, we examine and infer the impact that different environmental toxicants may have in shaping human evolution. We first describe how environmental toxicants shape natural human variation in terms of genetic and epigenetic diversity, and then we describe how DNA methylation may influence mutation rate and, thus, genetic variability. We describe the impact of these substances on biological fitness in terms of reproduction and survival, and in conclusion, we focus on their effect on brain evolution and physiology.