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Interdisciplinary Approaches for Understanding how Arsenic and Micronutrients Affect the Epigenome to Influence Spina Bifida Risk

This hospital-based case-control study was conducted in Bangladesh between December 2016 and December 2022 to investigate the association between environmental arsenic exposure and the risk of spina bifida. The study enrolled children with spina bifida (cases) and unaffected children (controls), along with their biological parents. Cases included infants under one year of age with clinically confirmed diagnoses of myelomeningocele or meningocele at the National Institute of Neurosciences & Hospital (NINS). Controls were frequency-matched on age and recruited from the same catchment area through NINS and Dhaka Shishu Hospital. Children with conditions potentially related to arsenic exposure, such as keratosis or cancer, were excluded from the control group. A small subset of case families were reclassified as controls following surgical reevaluation and a revised diagnosis of lipomeningocele, then later removed from the control group. They are no longer assigned to either the case or control category in the datasets. Saliva samples were collected from children and parents using Oragene® kits and stored at room temperature before shipment to Boston, MA, USA. DNA extraction was carried out with the Maxwell® RSC Buccal Swab DNA kit. A total of 749 saliva DNA samples, representing 713 unique individuals and 36 replicates, were shipped to the Broad Institute for analysis. Samples were randomized across Illumina Global Screening Array (GSA) chips to minimize batch effects.

The primary molecular technology employed in this study was the Illumina Global Screening Array (GSAMD-24v1-0), which includes approximately 688,000 genetic markers. Data generated include raw and processed genotype files as well as a comprehensive quality control report. The genotyping dataset available through dbGaP will consist of genotype calls from spina bifida cases, controls, and their parents, along with associated demographic, clinical, and exposure metadata, enabling future analyses of gene-environment interactions in the context of neural tube defect risk.