Dataset Information

Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

ABSTRACT:

Background

Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesions is likely to be causal.

Methods

Using data on 2060 arsenic-exposed Bangladeshi individuals, we estimated associations for two 10q24.32 SNPs with relative concentrations of three urinary arsenic species (representing metabolism efficiency): inorganic arsenic (iAs), monomethylarsonic acid(MMA) and dimethylarsinic acid (DMA). SNP-based predictions of iAs%, MMA% and DMA% were tested for association with skin lesion status among 2483 cases and 2857 controls.

Results

Causal odds ratios for skin lesions were 0.90 (95% confidence interval[CI]: 0.87, 0.95), 1.19 (CI: 1.10, 1.28) and 1.23 (CI: 1.12, 1.36)for a one standard deviation increase in DMA%, MMA% and iAs%,respectively. We demonstrated genotype-arsenic interaction, with metabolism-related variants showing stronger associations with skin lesion risk among individuals with high arsenic exposure (synergy index: 1.37; CI: 1.11, 1.62).

Conclusions

We provide strong evidence for a causal relationship between arsenic metabolism efficiency and skin lesion risk. Mendelian randomization can be used to assess the causal role of arsenic exposure and metabolism in a wide array of health conditions.exposure and metabolism in a wide array of health conditions.Developing interventions that increase arsenic metabolism efficiency are likely to reduce the impact of arsenic exposure on health.

SUBMITTER: Pierce BL

PROVIDER: S-EPMC3887566 | biostudies-literature | 2013 Dec

REPOSITORIES: biostudies-literature

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Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

Pierce Brandon L BL Tong Lin L Argos Maria M Gao Jianjun J Farzana Jasmine J Roy Shantanu S Paul-Brutus Rachelle R Rahaman Ronald R Rakibuz-Zaman Muhammad M Parvez Faruque F Ahmed Alauddin A Quasem Iftekhar I Hore Samar K SK Alam Shafiul S Islam Tariqul T Harjes Judith J Sarwar Golam G Slavkovich Vesna V Gamble Mary V MV Chen Yu Y Yunus Mohammad M Rahman Mahfuzar M Baron John A JA Graziano Joseph H JH Ahsan Habibul H

International journal of epidemiology 20131201 6

<h4>Background</h4>Arsenic exposure through drinking water is a serious global health issue. Observational studies suggest that individuals who metabolize arsenic efficiently are at lower risk for toxicities such as arsenical skin lesions. Using two single nucleotide polymorphisms(SNPs) in the 10q24.32 region (near AS3MT) that show independent associations with metabolism efficiency, Mendelian randomization can be used to assess whether the association between metabolism efficiency and skin lesi ...[more]

PMID: 24536095

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Project description:BackgroundSingle 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.ObjectiveWe aimed to investigate main effects as well as potential SNP-arsenic interactions on arsenic methylation efficiency in pregnant women.MethodWe 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.ResultIntron 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.ConclusionWe 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.

Project description:BackgroundUveitis, characterized by inflammation of the iris, ciliary body, and choroid, presents a significant global clinical challenge, contributing substantially to visual impairment. Risk factors include autoimmune diseases and immune cell dysfunctions, yet many remain unidentified. Immune cells, notably T cells, B cells, and monocytes, play pivotal roles in uveitis pathogenesis. While biologic agents show promise, comprehensive studies on immune cell types in ocular diseases are lacking. Genome-wide association studies (GWAS) and Mendelian randomization (MR) present promising avenues to elucidate genetic susceptibilities and causal relationships between immune cell traits and uveitis risk.MethodsTwo-sample MR analysis was used to evaluate the causal relationship between 731 immune cells and uveitis, and genome-wide significance analysis was performed for genetic variation in 731 immune cells traits (P < 5 × 10-8). Immune characteristics include median fluorescence intensity (MFI), relative cell counts (RC), absolute cell counts (AC), and morphological parameters (MP), which were determined by published GWAS, and public data from the IEU Open GWAS database. The main analysis method of MR is inverse variance weighting (IVW). Heterogeneity and horizontal pleiotropy were also assessed.Results5 immunophenotypes, including CD62L-DC %DC, IgD+ CD38dim %B cell, CD3 on CM CD4+T cell, CD3 on CD45RA-CD4 +T cell, and CD3 on CD39+ CD4+ Treg may increase the risk of uveitis. 5 immunophenotypes, including CD11b on CD33dim HLA DR-Myeloid cell, HLA DR on CD33dim HLA DR+ CD11b-myeloid cell, CD14-CD16 + %monocyte, HLA DR on CD14-CD16 + monocyte and PDL-1 on CD14-CD16 + monocyte was negatively associated with the risk of uveitis. Among them, HLA DR on CD14-CD16 + monocyte (OR=0.921, 95%CI =0.875-0.970, P=0.001) and HLA DR on CD33dim HLA DR+ CD11b- (OR=0.879, 95%CI = 0.833-0.927, P=0.00) were negatively associated with the risk of uveitis in bi-direction.ConclusionThese results indicate that 10 immune cells traits are significantly associated with the risk of developing uveitis and 2 of them were strongly associated with uveitis bi-directionally, after excluding the effects of confounding factors such as some immune diseases, which provided new ideas and therapeutic targets for the study of immune mechanism of uveitis.

Project description:BackgroundComplex immune-brain interactions that affect neural development, survival and function might have causal and therapeutic implications for psychiatric illnesses. However, previous studies examining the association between immune inflammation and schizophrenia (SCZ) have yielded inconsistent findings.MethodsComprehensive two-sample Mendelian randomization (MR) analysis was performed to determine the causal association between immune cell signatures and SCZ in this study. Based on publicly available genetic data, we explored causal associations between 731 immune cell signatures and SCZ risk. A total of four types of immune signatures (median fluorescence intensities (MFI), relative cell (RC), absolute cell (AC), and morphological parameters (MP)) were included. Comprehensive sensitivity analyses were used to verify the robustness, heterogeneity, and horizontal pleiotropy of the results.ResultsAfter FDR correction, SCZ had no statistically significant effect on immunophenotypes. It was worth mentioning some phenotypes with unadjusted low P-values, including FSC-A on NKT (β = 0.119, 95% CI = 0.044 ~ 0.194, P = 0.002), DN (CD4-CD8-) NKT %T cell (β = 0.131, 95% CI = 0.054 ~ 0.208, P = 9.03 × 10- 4), and SSC-A on lymphocytes (β = 0.136, 95% CI = 0.059 ~ 0.213, P = 5.43 × 10- 4). The causal effect of SCZ IgD on transitional was estimated to 0.127 (95% CI = 0.051 ~ 0.203, P = 1.09 × 10- 3). SCZ also had a causal effect on IgD+ %B cell (β = 0.130, 95% CI = 0.054 ~ 0.207, P = 8.69 × 10- 4), and DP (CD4+CD8+) %T cell (β = 0.131, 95% CI = 0.054 ~ 0.207, P = 8.05 × 10- 4). Furthermore, four immunophenotypes were identified to be significantly associated with SCZ risk: naive CD4+ %T cell (OR = 0.986, 95% CI = 0.979 ~ 0.992, P = 1.37 × 10- 5), HLA DR on CD14- CD16- (OR = 0.738 (95% CI = 0.642 ~ 0.849, P = 2.00 × 10- 5), CD33dim HLA DR+ CD11b- AC (OR = 0.631, 95% CI = 0.529 ~ 0.753, P = 3.40 × 10- 7) and activated & resting Treg % CD4 Treg (OR = 0.937, 95% CI = 0.906 ~ 0.970, P = 1.96 × 10- 4).ConclusionsOur study has demonstrated the close connection between immune cells and SCZ by genetic means, thus providing guidance for future clinical research.

Project description:Immune system and inflammation had a great influence on the progression of muscle atrophy. However, the causal relationship with specific immune cell traits remained uncertain. The aim of this study was to elucidate the genetic influences on these associations, providing insights into the underlying mechanisms of muscle atrophy. A bidirectional two-sample Mendelian randomization (MR) analysis was conducted to investigate the causal relationship between immune cell phenotypes and muscle atrophy. Data on immune cell phenotypes were obtained from a research cohort containing data on 731 immune cell phenotypes and data on muscle atrophy were sourced from a Finnish database. MR analysis was performed using the MR-Egger method, weighted median, inverse variance weighting, heterogeneity testing, sensitivity analysis, and multiplicity analysis, with results subjected to false discovery rate(FDR) correction. Additionally, the UK Biobank cohort was utilized as an external validation. A total of 31 immune phenotypes with causal relationships with muscle atrophy were identified, including various phenotypes of conventional dendritic cells, myeloid cells, T cells/B cells/natural killer cells, regulatory cells, and T cell maturation stages. Among them, 12 immune phenotypes were identified as exhibiting a positive causal relationship with muscle atrophy, while 19 immune phenotypes were demonstrated to have a negative causal association, highlighting the complex interactions between immune cells and muscle health. The results of the reverse MR analysis indicated that a negative correlation between muscle atrophy and CD28 on secreting Treg (OR = 0.9038, 95%CI:0.8308 ~ 0.9832, P = 0.0186). A significant positive correlation was revealed by external datasets between the CD25 on IgD + CD38- immune phenotype and the risk of muscle atrophy, which was consistent with the trend observed in the training group (OR = 1.1041, 95% CI: 1.1005-1.1076, P = 0.0263). No evidence of pleiotropy was observed, and the reliability of these findings was demonstrated by the leave-one-out analysis. The findings highlight significant correlations between certain immune cell features and muscle atrophy, providing potential targets for further investigation of immunological mechanisms and therapeutic interventions for this condition.

Project description:BackgroundUveitis refers to a group inflammation affecting the uvea, retina, retinal blood vessels as well as vitreous body, which is one of the common causes of blindness. There is growing evidence linking different types of immune cells to uveitis, although it remains uncertain if these associations imply causal relationships. Recent advancements in high-density genetic markers like SNPs or CNVs for genotyping, along with the progress in genome-wide association studies (GWAS) technologies, have improved our understanding of the immunological mechanisms involved in ocular diseases. Therefore, our objective was to investigate the potential causal link between immune cells and uveitis using a Mendelian randomization study.MethodsThe exposure and outcome GWAS data for this study were sourced from an open-access database (https://gwas.mrcieu.ac.uk/). Two-sample MR analysis was utilized to evaluate the causal relationship between 731 immune cell features and uveitis. Various MR methods were employed to reduce bias and obtain dependable estimates of the causal link between the immune cell variables and the outcomes. Instrumental variable selection criteria were carefully chosen to enhance the accuracy and efficacy of the causal relationship between different immune cell types and the risk of uveitis.ResultsUsing two-sample MR, IVW modeling showed that GAD had significant effect on immunophenotypes. CD3 levels on CD45RA- CD4+ T cells (OR = 1.087, 95%CI = 1.029 ~ 1.147, p = 0.003) and CD3 levels on CM CD4+ T cells (OR = 1.086, 95%CI = 1.033 ~ 1.141, p = 0.001) were found to be elevated in cases of uveitis. HLA DR levels in CD14- CD16+ monocyte cells (OR = 0.735, 95% CI = 0.635 ~ 0.850, p < 0.001) and HLA DR levels in NK cells (OR = 0.910, 95% CI = 0.851 ~ 0.972, p = 0.005) were observed to be reduced in individuals with uveitis. Furthermore, Two cells were identified to be significantly associated with uveitis risk: HLA DR on in NK cells (OR = 0.938, 95%CI = 0.899 ~ 0.979, p = 0.003), HLA DR on CD14- CD16+ monocytes (OR = 0.924, 95%CI = 0.878 ~ 0.972, p = 0.002).ConclusionThis study highlights the intricate relationship between immune cells and generalized anxiety disorder using genetic methods, offering valuable insights for future clinical investigations.

Project description:BackgroundDifferences in arsenic metabolism capacity may influence risk for type 2 diabetes, but the mechanistic drivers are unclear. We evaluated the associations between arsenic metabolism with overall diabetes prevalence and with static and dynamic measures of insulin resistance among Mexican Americans living in Starr County, Texas.MethodsWe utilized data from cross-sectional studies conducted in Starr County, Texas, from 2010-2014. A Mendelian randomization approach was utilized to evaluate the associations between arsenic metabolism and type 2 diabetes prevalence using the intronic variant in the arsenic methylating gene, rs9527, as the instrumental variable for arsenic metabolism. To further assess mechanisms for diabetes pathogenesis, proportions of the urinary arsenic metabolites were employed to assess the association between arsenic metabolism and insulin resistance among participants without diabetes. Urinary biomarkers of arsenic metabolites were modeled as individual proportions of the total. Arsenic metabolism was evaluated both with a static outcome of insulin resistance, homeostatic measure of assessment (HOMA-IR), and a dynamic measure of insulin sensitivity, Matsuda Index.ResultsAmong 475 Mexican American participants from Starr County, higher metabolism capacity for arsenic is associated with higher diabetes prevalence driven by worse insulin resistance. Presence of the minor T allele of rs9527 is independently associated with an increase in the proportion of monomethylated arsenic (MMA%) and is associated with an odds ratio of 0.50 (95% CI: 0.24, 0.90) for type 2 diabetes. This association was conserved after potential covariate adjustment. Furthermore, among participants without type 2 diabetes, the highest quartile of MMA% was associated with 22% (95% CI: -33.5%, -9.07%) lower HOMA-IR and 56% (95% CI: 28.3%, 91.3%) higher Matsuda Index for insulin sensitivity.ConclusionsArsenic metabolism capacity, indicated by a lower proportion of monomethylated arsenic, is associated with increased diabetes prevalence driven by an insulin resistant phenotype among Mexican Americans living in Starr County, Texas.

Dataset Information

Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

Background

Methods

Results

Conclusions

Publications

Arsenic metabolism efficiency has a causal role in arsenic toxicity: Mendelian randomization and gene-environment interaction.

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