# Identifying inherited genetic determinants of arsenic metabolism efficiency and their mechanisms

> **NIH NIH F30** · UNIVERSITY OF CHICAGO · 2021 · $51,036

## Abstract

PROJECT SUMMARY/ABSTRACT
This project seeks to identify the causal variants and mechanisms underlying the association between inherited
genetic variants in the 10q24.32 region and arsenic metabolism efficiency (AME). Exposure to arsenic-
contaminated drinking water impacts approximately 140 million individuals across the globe including 13 million
in the U.S and 56 million in Bangladesh. This exposure increases the risk of multiple cancers as well as
cardiovascular and neurologic diseases, pregnancy complications, and diabetes. There is considerable inter-
individual variation in AME with lower AME associated with a higher risk of arsenic toxicity. A genome-wide
association study (GWAS) of AME in a Bangladeshi population conducted by our group identified multiple
genetic variants in the 10q24.32 region independently associated with AME (measured as relative
concentrations of arsenic metabolites in urine). These variants reside in close proximity to AS3MT, a gene
coding for arsenite methyltransferase, a key enzyme involved in arsenic metabolism. However, neither the
causal variants in this region nor the mechanisms underlying their effects are known. These gaps in our
knowledge are likely due to the small sample size, incomplete genetic data, and single-population focus of
many previous studies, as well as a lack of integration of data sources on the potential functional effects of
associated variants. To address the limitations of prior studies, we will analyze dense genotyping data from
targeted sequencing of the 10q24.32 region for ~4100 individuals from 3 arsenic-exposed cohorts: the Health
Effects of Arsenic Longitudinal Study, the Strong Heart Study, and the New Hampshire Skin Cancer Study of
Squamous Cell Carcinoma. First, we will use association analysis approaches to identify potential causal
variants underlying observed associations between AME and inherited variation in the 10q24.32 region. Our
use of targeted sequencing data from three distinct ancestry groups will enable us to leverage differences in
their patterns of linkage disequilibrium to identify shared causal variants through Bayesian fine-mapping.
Second, we will identify potential mechanisms by which causal variants impact arsenic metabolism efficiency
by integrating our association results (from Aim 1) with results from analyses of expression and methylation
quantitative trait loci (eQTL, meQTL) in multiple tissue types as well as with expression and methylation data
from a Bangladeshi population. Finally, we will determine how AS3MT genotype modifies the association
between arsenic-exposure and risk for arsenic-related diseases (i.e., arsenic-induced skin lesions and skin
cancer). Our work will be the first to use targeted sequencing to identify potential causal variants and
mechanisms underlying the association between the 10q24.32 region and AME. Our results will provide a
more complete picture of genetic susceptibility to arsenic toxicity, enabling us to better identify ...

## Key facts

- **NIH application ID:** 10157648
- **Project number:** 1F30ES031858-01A1
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Meytal Batya Chernoff
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $51,036
- **Award type:** 1
- **Project period:** 2021-04-01 → 2025-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10157648

## Citation

> US National Institutes of Health, RePORTER application 10157648, Identifying inherited genetic determinants of arsenic metabolism efficiency and their mechanisms (1F30ES031858-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10157648. Licensed CC0.

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