Aims
Our earlier gene-expression studies with a Slovak PCBs-exposed population have revealed possible disease and disorder development in accordance with epidemiological studies. The present investigation aimed to develop an in vitro model system that can provide an indication of disrupted biological pathways associated with developing future diseases, well in advance of the clinical manifestations that may take years to appear in the actual human exposure scenario.
Background and aims
Our earlier gene-expression studies with a Slovak PCBs-exposed population have revealed possible disease and disorder development in accordance with epidemiological studies. The present investigation aimed to develop an in vitro model system that can provide an indication of disrupted biological pathways associated with developing future diseases, well in advance of the clinical manifestations that may take years to appear in the actual human exposure scenario.
Methods
We used human Primary Blood Mononuclear Cells (PBMC) and exposed them to a mixture of human equivalence levels of PCBs (PCB-118, -138, -153, -170, -180) as found in the PCBs-exposed Slovak population. The microarray studies of global gene expression were conducted on the Affymetrix platform using Human Genome U133 Plus 2.0 Array along with Ingenuity Pathway Analysis (IPA) to associate the affected genes with their mechanistic pathways. High-throughput qRT-PCR Taqman Low Density Array (TLDA) was done to further validate the selected 6 differentially expressed genes of our interest, viz., ARNT, CYP2D6, LEPR, LRP12, RRAD, TP53, with a small population validation sample (n=71).
Results
Overall, we revealed a discreet gene expression profile in the experimental model that resembled the diseases and disorders observed in PCBs-exposed population studies. The disease pathways included endocrine system disorders, genetic disorders, metabolic diseases, developmental disorders, and cancers, strongly consistent with the evidence from epidemiological studies. Interpretation: These gene finger prints could lead to the identification of populations and subgroups at high risk for disease, and can pose as early disease biomarkers well ahead of time, before the actual disease becomes visible.