Abstract

Chronic exposure to arsenic causes adverse health effects in children. Aberrant epigenetic modifications including altered DNA methylation pattern are one of the major steps towards malignant transformation of cells. Our group has previously identified significant alteration in DNA methylation mark in arsenic exposed adults, affecting major biological pathways. Till date, no information is available exploring the altered DNA methylation mark in telomere regulation and altered mitochondrial functionality in association with DNA damage in arsenic-exposed children. Our study aims in identifying signature epigenetic pattern associated with telomere lengthening, mitochondrial functionality and DNA damage repair in children with special emphasis on DNA methylation. Biological samples (blood and urine) and drinking water were collected from the children aged between 5 and 16 years of arsenic exposed areas (N = 52) of Murshidabad district and unexposed areas (N = 50) of East Midnapur districts, West Bengal, India. Methylation-specific PCR was performed to analyse subtelomeric methylation status and promoter methylation status of target genes. Results revealed altered DNA methylation profile in the exposed children compared to unexposed. Promoter hypermethylation was observed in MLH1 and MSH2 (p < 0.05 and p < 0.001) indicating inefficiency in DNA damage repair. Hypomethylation in mitochondrial D-loop (p < 0.05) and TFAM promoter region (p < 0.05) along with increased mitochondrial DNA copy number among exposed children was also observed. Significant increase in telomere length and region specific subtelomeric hypermethylation (XpYp, p < 0.05) was found. Analysis of S-Adenosyl Methionine (SAM) and 8-oxoDG level revealed significant depletion of SAM (p < 0.001) and elevated oxidative DNA damage (p < 0.001) respectively in arsenic toxicity. Our study identified key methylation patterns in arsenic-exposed children which may act as an early predictive biomarker in the near future. Further in-depth studies involving large sample size and transcriptomic analysis are required for understanding the mechanistic details.

Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call