Transcriptome responses in blood reveal distinct biological pathways associated with arsenic exposure through...

Groundwater Arsenic (As) contamination is a global public health concern responsible for various health implications and a neglected area of environmental health research in Pakistan. Because of interindividual differences in genetic predisposition, As-related health issues may not be equally distributed among the As-exposed population. However, till date, no studies have been conducted including multiple SNPs involved in As metabolism and disease risk using a linear mixed effect model approach to analyze peripheral blood transcriptomics results.

In order to detect early responses on the gene expression level and to evaluate the impact of selected SNPs inferring disease risks associated with As exposure, we designed a systematic study to investigate blood transcriptomics profiles of 57 differentially exposed rural subjects living in drinking water As-contaminated settings of Lahore and Kasur districts in Punjab Province in southeast Pakistan. Exposure among the subjects was correlated with individual transcriptome responses applying urinary As profiles as the main biomarker for risk stratification.

We performed whole genome gene expression analysis in blood of subjects using microarrays. Linear effect mixed models were applied for evaluating the combined impact of SNPs hypothetically increasing the risk for As exposure-induced health effects (GSTM1, GSTT1, As3MT, DNMT1, MTHFR, ERCC2 and EGFR).

Our findings confirmed important signaling, growth factor, cancer and other disease related pathways known to be associated with increased As exposure levels. In addition, upon implementing our integrative SNPs-based genetic risk factor, pathways associated with an increased risk of NAFLD and diabetes appeared significantly enhanced by down-regulation of genes NDUFV3, IKBKB, IL6R, ADIPOR1, PPARA, OGT and FOXO1.

We report the first comprehensive study applying state-of-the-art bioinformatics approaches to address multiple SNP-based inter-individual variability in adverse molecular responses among subjects exposed to drinking water As contamination in Pakistan thereby providing strong evidence of various gene expression targets associated with development of known As-related diseases.