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Activation of lipid-burning pathways in the fat-storing white adipose tissue (WAT) is a promising strategy to improve metabolic health and reduce obesity, insulin resistance, and type II diabetes. For unknown reasons, bilirubin levels are negatively associated with obesity and diabetes. Here, using mice and an array of approaches, including MRI to assess body composition, biochemical assays to measure bilirubin and fatty acids, MitoTracker-based mitochondrial analysis, immunofluorescence, and high-throughput coregulator analysis, we show that bilirubin functions as a molecular switch for the nuclear receptor transcription factor peroxisome proliferator–activated receptor α (PPARα). Bilirubin exerted its effects by recruiting and dissociating specific coregulators in WAT, driving the expression of PPARα target genes such as uncoupling protein 1 (Ucp1) and adrenoreceptor β 3 (Adrb3). We also found that bilirubin is a selective ligand for PPARα and does not affect the activities of the related proteins PPARγ and PPARδ. We further found that diet-induced obese mice with mild hyperbilirubinemia have reduced WAT size and an increased number of mitochondria, associated with a restructuring of PPARα-binding coregulators. We conclude that bilirubin strongly affects organismal body weight by reshaping the PPARα coregulator profile, remodeling WAT to improve metabolic function, and reducing fat accumulation.

CNS disorders, and in particular psychiatric illnesses, lack definitive disease-altering therapeutics. The limited understanding of the mechanisms driving these illnesses with the slow pace and high cost of drug development exacerbates this issue. For these reasons, drug repurposing - both a less expensive and time-efficient practice compared to de novo drug development - has been a promising strategy to overcome the paucity of treatments available for these debilitating disorders. While empirical drug-repurposing has been a routine practice in clinical psychiatry, innovative, informed, and cost-effective repurposing efforts using big data ("omics") have been designed to characterize drugs by structural and transcriptomic signatures. These strategies, in conjunction with ontological integration, provide an important opportunity to address knowledge-based challenges associated with drug development for CNS disorders. In this review, we discuss various signature-based in silico approaches to drug repurposing, its integration with multiple omics platforms, and how this data can be used for clinically relevant, evidence-based drug repurposing. These tools provide an exciting translational avenue to merge omics-based drug discovery platforms with patient-specific disease signatures, ultimately facilitating the identification of new therapies for numerous psychiatric disorders.

The treatment of CNS disorders, and in particular psychiatric illnesses, lacks disease-altering therapeutics for many conditions. This is likely due to regulatory challenges involving the high cost and slow-pace of drug development for CNS disorders as well as due to limited understanding of disease causality. Repurposing drugs for new indications have lower cost and shorter development timeline compared to that of de novo drug development. Historically, empirical drug-repurposing is a standard practice in psychiatry; however, recent advances in characterizing molecules with their structural and transcriptomic signatures along with ensemble of data analysis approaches, provides informed and cost-effective repurposing strategies that ameliorate the regulatory challenges. In addition, the potential to incorporate ontological approaches along with signature-based repurposing techniques addresses the various knowledge-based challenges associated with CNS drug development. In this review we primarily discuss signature-basedin silicoapproaches to drug repurposing, and its integration with data science platforms for evidence-based drug repurposing. We contrast variousin silicoand empirical approaches and discuss possible avenues to improve the clinical relevance. These concepts provide a promising new translational avenue for developing new therapies for difficult to treat disorders, and offer the possibility of connecting drug discovery platforms and big data analytics with personalized disease signatures.

Bilirubin is a potent antioxidant that reduces inflammation and the accumulation of fat. There have been reports of gene responses to bilirubin, which was mostly attributed to its antioxidant function. Using RNA sequencing, we found that biliverdin, which is rapidly reduced to bilirubin, induced transcriptome responses in human HepG2 hepatocytes in a peroxisome proliferator-activated receptor (PPAR)-α-dependent fashion (398 genes with >2-fold change; false discovery rate P < 0.05). For comparison, a much narrower set of genes demonstrated differential expression when PPAR-α was suppressed via lentiviral shRNA knockdown (23 genes). Gene set enrichment analysis revealed the bilirubin-PPAR-α transcriptome mediates pathways for oxidation-reduction processes, mitochondrial function, response to nutrients, fatty acid oxidation, and lipid homeostasis. Together, these findings suggest that transcriptome responses from the generation of bilirubin are mostly PPAR-α dependent, and its antioxidant function regulates a smaller set of genes.