Differential gene expression and a functional analysis of PCB-exposed children: Understanding disease and disorder development

Abstract

The goal of the present study is to understand the probable molecular mechanism of toxicities and the associated pathways related to observed pathophysiology in high PCB-exposed populations. We have performed a microarray-based differential gene expression analysis of children (mean age 46.1months) of Central European descent from Slovak Republic in a well-defined study cohort. The subset of children having high blood PCB concentrations (>75 percentile) were compared against their low PCB counterparts (<25 percentile), with mean lipid-adjusted PCB values of 3.02±1.3 and 0.06±0.03ng/mg of serum lipid, for the two groups, respectively (18.1±4.4 and 0.3±0.1ng/ml of serum). The microarray was conducted with the total RNA from the peripheral blood mononuclear cells of the children using an Affymetrix platform (GeneChip Human genome U133 Plus 2.0 Array) and was analyzed by Gene Spring (GX 10.0). A highly significant set of 162 differentially expressed genes between high and low PCB groups (p value <0.00001) were identified and subsequently analyzed using the Ingenuity Pathway Analysis tool. The results indicate that Cell-To-Cell Signaling and Interaction, Cellular Movement, Cell Signaling, Molecular Transport, and Vitamin and Mineral Metabolism were the major molecular and cellular functions associated with the differentially altered gene set in high PCB-exposed children. The differential gene expressions appeared to play a pivotal role in the development of probable diseases and disorders, including cardiovascular disease and cancer, in the PCB-exposed population. The analyses also pointed out possible organ-specific effects, e.g., cardiotoxicity, hepatotoxicity and nephrotoxicity, in high PCB-exposed subjects. A few notable genes, such as BCL2, PON1, and ITGB1, were significantly altered in our study, and the related pathway analysis explained their plausible involvement in the respective disease processes, as mentioned. Our results provided insight into understanding the associated molecular mechanisms of complex gene–environment interactions in a PCB-exposed population. Future endeavors of supervised genotyping of pathway-specific molecular epidemiological studies and population biomarker validations are already underway to reveal individual risk factors in these PCB-exposed populations.