Screening for gene-environment (G×E) interaction using omics data from exposed individuals: an application to gene-arsenic interaction

Self Nano-Emulsifying Curcumin (SNEC30) attenuates arsenic-induced cell death in mice

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Sodium arsenite disrupts the histoarchitecture and cell morphology causing cell death in thymus and spleen of Swiss albino mice.

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Activation of apoptotic cell death occurred due to high level of ROS generation and increased promotion of autophagy upon arsenic insult.

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SNEC30 restored cellular architecture, reduced ROS generation and ameliorated autophagy-mediated cell death in the immune organs.

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This study clearly demonstrated anti-oxidative and anti-apoptotic properties of SNEC30 against NaAsO₂-induced in vivo immunotoxicity.

Several precedents have confirmed numerous infirmities caused by arsenic poisoning, including immune suppression and cancer. Exposure to arsenic leads to alterations of the cellular machinery and eventually cell death, depending on the dose and duration of exposure. Oxidative stress induced by arsenic is the major mechanism by which it inflicts cellular toxicity, challenging the survival-support - autophagy and culminating in apoptosis in the thymus and spleen of mice. Curcumin, a potent dietary anti-oxidant with known anti-apoptotic and anti-inflammatory properties, was assessed for therapeutic benefits. However, the major caveat of this polyphenol is its low water solubility and limited bioavailability. Therefore, Self Nano-Emulsifying Curcumin (SNEC30) was used to treat mice exposed to arsenic. When administered, SNEC30 effectively ameliorated the adverse effects of arsenic in mice, by restoring structural alterations and reducing ROS-mediated cell death, thereby endorsing the importance of nutraceuticals in counteracting heavy metal-induced cellular toxicity.

Genetics of Resilience: Gene-by-Environment Interaction Studies as a Tool to Dissect Mechanisms of Resilience

The identification and understanding of resilience mechanisms holds potential for the development of mechanistically informed prevention and interventions in psychiatry. However, investigating resilience mechanisms is conceptually and methodologically challenging because resilience does not merely constitute the absence of disease-specific risk but rather reflects active processes that aid in the maintenance of physiological and psychological homeostasis across a broad range of environmental circumstances. In this conceptual review, we argue that the principle used in gene-by-environment interaction studies may help to unravel resilience mechanisms on different investigation levels. We present how this could be achieved by top-down designs that start with gene-by-environment interaction effects on disease phenotypes as well as by bottom-up approaches that start at the molecular level. We also discuss how recent technological advances may improve both top-down and bottom-up strategies.

Gene-environment interaction and maternal arsenic methylation efficiency during pregnancy

BACKGROUND

Single nucleotide polymorphisms (SNPs) may influence arsenic methylation efficiency, affecting arsenic metabolism. Whether gene-environment interactions affect arsenic metabolism during pregnancy remains unclear, which may have implications for pregnancy outcomes.

OBJECTIVE

We aimed to investigate main effects as well as potential SNP-arsenic interactions on arsenic methylation efficiency in pregnant women.

METHOD

We recruited 1613 pregnant women in Bangladesh, and collected two urine samples from each participant, one at 4-16 weeks, and the second at 21-37 weeks of pregnancy. We determined the proportions of each arsenic metabolite [inorganic As (iAs)%, monomethylarsonic acid (MMA)%, and dimethylarsinic acid (DMA)%] from the total urinary arsenic level of each sample. A panel of 63 candidate SNPs was selected for genotyping based on their reported associations with arsenic metabolism (including in As3MT, N6AMT1, and GSTO2 genes). We used linear regression models to assess the association between each SNP and DMA% with an additive allelic assumption, as well as SNP-arsenic interaction on DMA%. These analyses were performed separately for two urine collection time-points to capture differences in susceptibility to arsenic toxicity.

RESULT

Intron variants for As3MT were associated with DMA%. rs9527 (β = -2.98%, PFDR = 0.008) and rs1046778 (β = 1.64%, PFDR = 0.008) were associated with this measure in the early gestational period; rs3740393 (β = 2.54%, PFDR = 0.002) and rs1046778 (β = 1.97%, PFDR = 0.003) in the mid-to-late gestational period. Further, As3MT, GSTO2, and N6AMT1 polymorphisms showed different effect sizes on DMA% conditional on arsenic exposure levels. However, SNP-arsenic interactions were not statistically significant after adjusting for false discovery rate (FDR). rs1048546 in N6AMT1 had the highest significance level in the SNP-arsenic interaction test during mid-to-late gestation (β = -1.8% vs. 1.4%, PGxE_FDR = 0.075). Finally, As3MT and As3MT/CNNM2 haplotypes were associated with DMA% at both time points.

CONCLUSION

We found that not all genetic associations reported in arsenic methylation efficiency replicate in pregnant women. Arsenic exposure level has a limited effect in modifying the association between genetic variation and arsenic methylation efficiency.