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Transcriptomics-driven drug screening identifies BRD-K78062244 in promoting white adipose tissue browning
Na Xiong1, Lin Mi1, Xiaoyu Wang2
1Department of Endocrinology and Metabolism, Guangdong Provincial Key Laboratory of Diabetology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510630, China.
Abstract:
Obesity and its related comorbidities have become increasingly challenging in public health globally, and white adipose tissue (WAT) browning enhances energy expenditure and provides a promising therapeutic strategy for treating obesity. However, few drugs have been clinically approved for promoting WAT browning largely due to the involvement of complex signaling pathways, which limits the application of traditional drug screening approaches. Thus, a cross-species gene set that marks the adipose browning process was constructed, and a systematic strategy for compound screening was developed. By integrating single-nucleus and bulk RNA sequencing data from both humans and mice, we established a signature gene set named "white adipose tissue browning-associated gene" (WAT-BAG) through differential gene expression analysis. Candidate compounds were identified by integrating the WAT-BAG gene set with the Connectivity Map (CMap) database, followed by functional validation both in vitro and in vivo. Among the candidates, BRD-K78062244 was ranked as a top compound that induced transcriptional changes resembling the WAT-to-BAT transition. Further analysis revealed that BRD-K78062244 activated the PPAR signaling pathway and inhibited lipid droplet accumulation in adipocytes in vitro. Moreover, intra-inguinal injection of BRD-K78062244 enhanced glucose handling capacity in lean adult mice, accompanied by transcriptomic evidence of enhanced thermogenesis and suppression of lipogenic programs in adipose tissue. This study introduces a transcriptome-guided drug screening strategy that overcomes the limitations of conventional single-target approaches and highlights the potential of BRD-K78062244 in metabolic remodeling. Our findings offer a new framework for identifying compounds that promotes WAT browning via multi-omics-derived gene signatures.
Insights
Researchers developed a new method to find drugs that promote white adipose tissue (WAT) browning, a process that burns energy. They identified a compound, BRD-K78062244, which shows promise for treating obesity and related conditions.
Area of Science:
- Metabolic Research
- Pharmacology
- Genomics
Background:
- Obesity and related diseases pose global health challenges.
- White adipose tissue (WAT) browning increases energy expenditure, offering a therapeutic target for obesity.
- Current drug screening methods are limited by complex signaling pathways involved in WAT browning.
Purpose of the Study:
- To develop a novel, cross-species strategy for identifying compounds that promote WAT browning.
- To establish a reliable gene signature for adipose browning.
- To validate candidate compounds for their potential in metabolic remodeling.
Main Methods:
- Integrated human and mouse single-nucleus and bulk RNA sequencing data.
- Constructed a "white adipose tissue browning-associated gene" (WAT-BAG) signature.
- Utilized the Connectivity Map (CMap) database for compound screening.
- Performed in vitro and in vivo functional validation of candidate compounds.
Main Results:
- Identified a cross-species gene set (WAT-BAG) for adipose browning.
- Screened compounds using WAT-BAG and CMap, identifying BRD-K78062244 as a top candidate.
- BRD-K78062244 promoted WAT-to-BAT transition, activated the PPAR signaling pathway, and inhibited lipid accumulation in vitro.
- In vivo studies showed BRD-K78062244 improved glucose handling and enhanced thermogenesis in mice.
Conclusions:
- A transcriptome-guided drug discovery strategy was successfully developed for identifying WAT browning promoters.
- BRD-K78062244 demonstrates significant potential for metabolic remodeling and obesity treatment.
- The study provides a new framework for discovering compounds targeting WAT browning using multi-omics data.
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