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

Ghosh, Somiranjan, Mitra, Partha S., Loffredo, Christopher A., Trnovec, Tomas, Murinova, Lubica, Sovcikova, Eva, Ghimbovschi, Svetlana, Zang, Shizhu, Hoffman, Eric P., Dutta, Sisir K.
Environmental Research 2015 v.138 pp. 202-216
biomarkers, endocrine system, epidemiological studies, gene expression, gene expression regulation, genes, genetic disorders, humans, metabolic diseases, microarray technology, models, mononuclear leukocytes, neoplasms, polychlorinated biphenyls, quantitative polymerase chain reaction, reverse transcriptase polymerase chain reaction, risk, transcription (genetics)
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.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).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.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.