Transcriptional profiling and biological pathway analysis of human equivalence PCB exposure in vitro: Indicator of disease and disorder development in humans

• Generated knowledge of disease pathways that were associated with human equivalence PCB exposures.
• Identified discrete gene sets that were perturbed in the in vitro experiments.
• Evaluated and validated the candidate genes status by comparison to the population study.
• Identified pathways for Obesity, Type 2 diabetes, and Cancers towards potential disease development.
• Explored the potential use of these gene fingerprints as disease susceptibility markers.

Background and aimsOur 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.MethodsWe 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).ResultsOverall, 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.InterpretationThese 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.