Truong Trang T T, Liu Zoe S J, Panizzutti Bruna, Dean Olivia M, Berk Michael, Kim Jee Hyun, Walder Ken
Deakin University, IMPACT, The Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Geelong, Australia.
Deakin University, IMPACT, The Institute for Mental and Physical Health and Clinical Translation, School of Medicine, Geelong, Australia; Florey Institute of Neuroscience and Mental Health, Parkville, Australia.
J Affect Disord. 2024 Apr 1;350:230-239. doi: 10.1016/j.jad.2024.01.034. Epub 2024 Jan 6.
Bipolar disorder (BD) presents significant challenges in drug discovery, necessitating alternative approaches. Drug repurposing, leveraging computational techniques and expanding biomedical data, holds promise for identifying novel treatment strategies.
This study utilized gene regulatory networks (GRNs) to identify significant regulatory changes in BD, using network-based signatures for drug repurposing. Employing the PANDA algorithm, we investigated the variations in transcription factor-GRNs between individuals with BD and unaffected individuals, incorporating binding motifs, protein interactions, and gene co-expression data. The differences in edge weights between BD and controls were then used as differential network signatures to identify drugs potentially targeting the disease-associated gene signature, employing the CLUEreg tool in the GRAND database.
Using a large RNA-seq dataset of 216 post-mortem brain samples from the CommonMind consortium, we constructed GRNs based on co-expression for individuals with BD and unaffected controls, involving 15,271 genes and 405 TFs. Our analysis highlighted significant influences of these TFs on immune response, energy metabolism, cell signalling, and cell adhesion pathways in the disorder. By employing drug repurposing, we identified 10 promising candidates potentially repurposed as BD treatments.
Non-drug-naïve transcriptomics data, bulk analysis of BD samples, potential bias of GRNs towards well-studied genes.
Further investigation into repurposing candidates, especially those with preclinical evidence supporting their efficacy, like kaempferol and pramocaine, is warranted to understand their mechanisms of action and effectiveness in treating BD. Additionally, novel targets such as PARP1 and A2b offer opportunities for future research on their relevance to the disorder.
双相情感障碍（BD）在药物研发中面临重大挑战，需要采用替代方法。药物再利用借助计算技术并扩展生物医学数据，有望识别新的治疗策略。
本研究利用基因调控网络（GRN）来识别BD中显著的调控变化，使用基于网络的特征进行药物再利用。采用PANDA算法，我们研究了BD患者与未受影响个体之间转录因子 - GRN的差异，纳入了结合基序、蛋白质相互作用和基因共表达数据。然后，将BD与对照组之间边权重的差异用作差异网络特征，以识别可能靶向疾病相关基因特征的药物，使用GRAND数据库中的CLUEreg工具。
利用来自CommonMind联盟的216个死后脑样本的大型RNA测序数据集，我们基于共表达构建了BD患者和未受影响对照组的GRN，涉及15271个基因和405个转录因子。我们的分析突出了这些转录因子对该疾病中免疫反应、能量代谢、细胞信号传导和细胞粘附途径的显著影响。通过药物再利用，我们确定了10种有前景的候选药物，可能被重新用作BD的治疗药物。
非初治转录组学数据、BD样本的批量分析、GRN对研究充分的基因的潜在偏差。
有必要对重新利用的候选药物进行进一步研究，特别是那些有临床前证据支持其疗效的药物，如槲皮素和丙胺卡因，以了解它们在治疗BD中的作用机制和有效性。此外，PARP1和A2b等新靶点为未来研究它们与该疾病的相关性提供了机会。
