Toxicogenomics in the 3T3-L1 cell line, a new approach for screening of obesogenic compounds.

The obesogen hypothesis states that together with an energy imbalance between calories consumed and calories expended, exposure to environmental compounds early in life or throughout lifetime might have an influence on obesity development. In this work, we propose a new approach for obesogen screening, i.e., the use of transcriptomics in the 3T3-L1 pre-adipocyte cell line. Based on the data from a previous study of our group using a lipid accumulation based adipocyte differentiation assay, several human-relevant obesogenic compounds were selected: reference obesogens (Rosiglitazone, Tributyltin), test obesogens (Butylbenzyl phthalate, butylparaben, propylparaben, Bisphenol A), and non-obesogens (Ethylene Brassylate, Bis (2-ethylhexyl)phthalate). The high stability and reproducibility of the 3T3-L1 gene transcription patterns over different experiments and cell batches is demonstrated by this study. Obesogens and non-obesogen gene transcription profiles were clearly distinguished using hierarchical clustering. Furthermore, a gradual distinction corresponding to differences in induction of lipid accumulation could be made between test and reference obesogens based on transcription patterns, indicating the potential use of this strategy for classification of obesogens. Marker genes that are able to distinguish between non, test, and reference obesogens were identified. Well-known genes involved in adipocyte differentiation as well as genes with unknown functions were selected, implying a potential adipocyte-related function of the latter. Cell-physiological lipid accumulation was well estimated based on transcription levels of the marker genes, indicating the biological relevance of omics data. In conclusion, this study shows the high relevance and reproducibility of this 3T3-L1 based in vitro toxicogenomics tool for classification of obesogens and biomarker discovery. Although the results presented here are promising, further confirmation of the predictive value of the set of candidate biomarkers identified as well as the validation of their clinical role will be needed.