Notice of RetractionNormal and Obese Liver Expressional QTLs Reveal Genes and Pathways Underlying Metabolic Disorders

Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

Expression quantitative trait loci (eQTLs) have been shown as valuable tools in dissecting the genetics architecture of gene expression. It also noted that the eQTLs of a given tissue are broadly affected by modifiers such as environmental exposure and health status. Herein, we report a large scale gene expression and genotyping study aiming to identify pathways underlying obesity and related metabolic disorders. Toward this goal, we collected 378 liver samples from healthy Caucasian individuals and 580 liver samples from obese patients. RNA extracted from these tissues underwent genome-wide expression array assay; and DNA were genotyped using Illumina SNP 650Y platform. We than compared eQTLs of these two human liver sets. Detected using linear model with interaction term, 465 cis-eQTLs showed significant heterogeneity between the two liver sets (termed as differential eQTLs), possibly modified by health status (ie., obesity). The corresponding genes of these eQTLs are enriched for the inhibition of RXR pathway (p=7.8E-4), which closely relates to obesity and diabetes phenotypes. Lastly, we investigate the function of the differential eSNPs in the Wellcome Trust Case Control Consortium cohorts. These SNPs are significantly enrichment for association with type II diabetes comparing to negative controls, bipolar disorders (pvalue=5.6E-13). The contributions of our study are at least two fold. First, we revealed genes and SNPs associated with metabolic disorders; and second, established a powerful method to detect - nd interpreting differential eQTLs. This method has wide applications given the fast growing genetic and expression studies.