Activation, PPARα

Gene expression occurs in a coordinated fashion (Judson et al., 2012). The many observations of altered gene expression following binding of ligand to PPARα led to systematic investigations of the genomic signature that corresponds to PPARα activation (Tamura et al., 2006; Kupershmidt et al., 2010; Rosen et al., 2017; Rooney et al., 2018; Corton et al., 2020; Hill et al., 2020; Lewis et al., 2020). Specific gene with increased expression following PPARα activation include Cyp4a1, Cpt1B, and Lpl. More generally, the pathways activated include:

• Genes involved in Metabolism of lipids and lipoproteins
• Fatty acid metabolism
• Genes involved in Fatty acid, triacylglycerol, and ketone body metabolism
• PPAR signaling pathway
• Peroxisome
• Genes involved in Cell Cycle

Biological state

The Peroxisome Proliferator Activated receptor α (PPARα) belongs to the Peroxisome Proliferator Activated receptors (PPARs; NR1C) steroid/thyroid/retinoid receptor superfamily of transcription factors.

Biological compartments

PPARα is expressed in high levels in tissues that perform significant catabolism of fatty acids (FAs), such as brown adipose tissue, liver, heart, kidney, and intestine (Michalik et al. 2006). The receptor is present also in skeletal muscle, intestine, pancreas, lung, placenta and testes (Mukherjee et al. 1997), (Schultz et al. 1999).

General role in biology

PPARs are activated by fatty acids and their derivatives; they are sensors of dietary lipids and are involved in lipid and carbohydrate metabolism, immune response and peroxisome proliferation (Wahli and Desvergne 1999), (Evans, Barish, & Wang, 2004). PAPRα is a also a target of hypothalamic hormone signalling and was found to play a role in embryonic development (Yessoufou and Wahli 2010).

Fibrates, activators of PPARα, are commonly used to treat hypertriglyceridemia and other dyslipidemic states as they have been shown to decrease circulating lipid levels (Lefebvre et al. 2006).

Binding of ligands to PPARα is measured using binding assays in vitro and in silico, whereas the information about functional activation is derived from transactivation assays (e.g. transactivation assay with reporter gene) that demonstrate functional activation of a nuclear receptor by a specific compound. Binding of agonists within the ligand-binding site of PPARs causes a conformational change of nuclear receptor that promotes binding to transcriptional co-activators. Conversely, binding of antagonists results in a conformation that favours the binding of co-repressors (Yu and Reddy 2007), (Viswakarma et al. 2010). Transactivation assays are performed using transient or stably transfected cells with the PPARα expression plasmid and a reporter plasmid, respectively. There are also other methods that have been used to measure PPARα activity, such as the Electrophoretic Mobility Shift Assay (EMSA) or commercially available PPARα transcription factor assay kits, see Table 1. The transactivation (stable transfection) assay provides the most applicable OECD Level 2 assay (i.e. In vitro assays providing mechanistic data) aimed at identifying the initiating event leading to an adverse outcome (LeBlanc, Norris, and Kloas 2011). A recent study characterized the PPARα ligand binding domain for the purpose of next-generation metabolic disease drugs (Kamata et al. 2020).

The most direct measure of this MIE is microarray profiling from large gene expression databases TG-GATEs and DrugMatrix coupled with t statistical analysis of whole genome expression profiles (Svoboda et al., 2019; Igarashi et al., 2015) From these data, A gene expression signature of 131 PPARα-dependent genes was built using microarray profiles from the livers of wild-type and PPARα-null mice. A quantitative measure of this expression signature is a measure of similarity/correlation between the PPARα signature and positive and negative test sets is provided by the Running Fisher test (Corton et al., 2020; Hill et al., 2020; Kupershmidt et al., 2010; Lewis et al., 2020; Rooney et al., 2018).

A gene expression signature of 131 PPARα-dependent genes was built using microarray profiles from the livers of wild-type and PPARα-null mice. A quantitative measure of this expression signature would be a measure of similarity/correlation between the PPARα signature and positive and negative test sets is provided by the Running Fisher test (Kupershmidt et al., 2010; Rooney et al., 2018; Corton et al., 2020).

For all substances, MIE activation does not rise monotonically over dose or time. These fluctuations are likely due to variations in cofactor availability or access to the site of transcription (Gaillard et al., 2006; Koppen et al., 2009; Kupershmidt et al., 2010; Ong et al., 2010; Chow et al., 2011; De Vos et al., 2011; Simon et al., 2015).

.

PPARα has been identified in frog (Xenopus laevis), mouse, human, rat, fish, hamster and chicken (reviewed in (Wahli and Desvergne 1999)).

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