PPARalpha siRNA-treated expression profiles uncover the causal sufficiency network for compound-induced liver hypertrophy.

Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi) phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs) against the gene for peroxisome proliferator-activated receptor alpha (Ppara), our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARalpha-induced liver hypertrophy is supported by their ability to predict non-PPARalpha-induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005). Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug-induced toxicity from siRNA-treated expression profiles. When combined with phenotypic evaluation, our approach should help to unleash the full potential of siRNAs in systematically unveiling the molecular mechanism of biological events.

Transcriptional and phenotypic comparisons of Ppara knockout and siRNA knockdown mice.

RNA interference (RNAi) has great potential as a tool for studying gene function in mammals. However, the specificity and magnitude of the in vivo response to RNAi remains to be fully characterized. A molecular and phenotypic comparison of a genetic knockout mouse and the corresponding knockdown version would help clarify the utility of the RNAi approach. Here, we used hydrodynamic delivery of small interfering RNA (siRNA) to knockdown peroxisome proliferator activated receptor alpha (Ppara), a gene that is central to the regulation of fatty acid metabolism. We found that Ppara knockdown in the liver results in a transcript profile and metabolic phenotype that is comparable to those of Ppara-/- mice. Combining the profiles from mice treated with the PPARalpha agonist fenofibrate, we confirmed the specificity of the RNAi response and identified candidate genes proximal to PPARalpha regulation. Ppara knockdown animals developed hypoglycemia and hypertriglyceridemia, phenotypes observed in Ppara-/- mice. In contrast to Ppara-/- mice, fasting was not required to uncover these phenotypes. Together, these data validate the utility of the RNAi approach and suggest that siRNA can be used as a complement to classical knockout technology in gene function studies.

Agonists of the peroxisome proliferator-activated receptor alpha induce a fiber-type-selective transcriptional response in rat skeletal muscle.

In rodents, treatment with peroxisome proliferator-activated receptor alpha (PPARalpha) agonists results in peroxisome proliferation, hepatocellular hypertrophy, and hepatomegaly. Drugs in the fibrate class of PPARalpha agonists have also been reported to produce rare skeletal muscle toxicity. Although target-driven hepatic effects of PPARalpha treatment have been extensively studied, a characterization of the transcriptional effects of this nuclear receptor/transcription factor on skeletal muscle responses has not been reported. In this study we investigated the effects of PPARalpha agonists on skeletal muscle gene transcription in rats. Further, since statins have been reported to preferentially effect type II muscle fibers, we compared PPARalpha signaling effects between type I and type II muscles. By comparing the transcriptional responses of agonists that signal through different nuclear receptors and using a selection/deselection analytical strategy based on ANOVA, we identified a PPARalpha activation signature that is evident in type I (soleus), but not type II (quadriceps femoris), skeletal muscle fibers. The fiber-type-selective nature of this response is consistent with increased fatty acid uptake and beta-oxidation, which represent the major clinical benefits of the hypolipidemic compounds used in this study, but does not reveal any obvious off-target pathways that may drive adverse effects.

Profiling of hepatic gene expression in rats treated with fibric acid analogs.

Peroxisome proliferator-activated receptors (PPARs) are a group of nuclear receptors whose ligands include fatty acids, eicosanoids and the fibrate class of drugs. In humans, fibrates are used to treat dyslipidemias. In rodents, fibrates cause peroxisome proliferation, a change that might explain the observed hepatomegaly. In this study, rats were treated with multiple dose levels of six fibric acid analogs (including fenofibrate) for up to two weeks. Pathological analysis identified hepatocellular hypertrophy as the only sign of hepatotoxicity, and only one compound at the highest dose caused any significant increase in serum ALT or AST activity. RNA profiling revealed that the expression of 1288 genes was related to dose or length of treatment and correlated with hepatocellular hypertrophy. This gene list included expression changes that were consistent with increased mitochondrial and peroxisomal beta-oxidation, increased fatty acid transport, increased hepatic uptake of LDL-cholesterol, decreased hepatic uptake of glucose, decreased gluconeogenesis and decreased glycolysis. These changes are likely linked to many of the clinical benefits of fibrate drugs, including decreased serum triglycerides, decreased serum LDL-cholesterol and increased serum HDL-cholesterol. In light of the fact that all six compounds stimulated similar or identical changes in the expression of this set of 1288 genes, these results indicate that hepatomegaly is due to PPARalpha activation, although signaling through other receptors (e.g. PPARgamma, RXR) or through non-receptor pathways cannot be excluded.

Clofibrate-induced gene expression changes in rat liver: a cross-laboratory analysis using membrane cDNA arrays.

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically relevant markers of toxicity. To be useful for risk assessment, however, microarray data must be challenged to determine reliability and interlaboratory reproducibility. As part of a series of studies conducted by the International Life Sciences Institute Health and Environmental Science Institute Technical Committee on the Application of Genomics to Mechanism-Based Risk Assessment, the biological response in rats to the hepatotoxin clofibrate was investigated. Animals were treated with high (250 mg/kg/day) or low (25 mg/kg/day) doses for 1, 3, or 7 days in two laboratories. Clinical chemistry parameters were measured, livers removed for histopathological assessment, and gene expression analysis was conducted using cDNA arrays. Expression changes in genes involved in fatty acid metabolism (e.g., acyl-CoA oxidase), cell proliferation (e.g., topoisomerase II-Alpha), and fatty acid oxidation (e.g., cytochrome P450 4A1), consistent with the mechanism of clofibrate hepatotoxicity, were detected. Observed differences in gene expression levels correlated with the level of biological response induced in the two in vivo studies. Generally, there was a high level of concordance between the gene expression profiles generated from pooled and individual RNA samples. Quantitative real-time polymerase chain reaction was used to confirm modulations for a number of peroxisome proliferator marker genes. Though the results indicate some variability in the quantitative nature of the microarray data, this appears due largely to differences in experimental and data analysis procedures used within each laboratory. In summary, this study demonstrates the potential for gene expression profiling to identify toxic hazards by the identification of mechanistically relevant markers of toxicity.