Cross-species signaling pathways analysis inspire animal model selections for drug screening and target prediction in vascular aging diseases

IF 3.5 2区 生物学 Q1 EVOLUTIONARY BIOLOGY
Fei Sun, Xingxing Chen, Shuqing Zhang, Haihong Jiang, Tianhong Chen, Tongying Xing, Xueyi Li, Rabia Sultan, Zhimin Wang, Jia Jia
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Abstract

Age is a significant contributing factor to the occurrence and progression of cardiovascular disease (CVD). Pharmacological treatment can effectively alleviate CVD symptoms caused by aging. However, 90% of the drugs have failed in clinics because of the loss of drug effects or the occurrence of the side effects. One of the reasons is the disparity between animal models used and the actual physiological levels in humans. Therefore, we integrated multiple datasets from single-cell and bulk-seq RNA-sequencing data in rats, monkeys, and humans to identify genes and pathways with consistent/differential expression patterns across these three species. An approach called “Cross-species signaling pathway analysis” was developed to select suitable animal models for drug screening. The effectiveness of this method was validated through the analysis of the pharmacological predictions of four known anti-vascular aging drugs used in animal/clinical experiments. The effectiveness of drugs was consistently observed between the models and clinics when they targeted pathways with the same trend in our analysis. However, drugs might have exhibited adverse effects if they targeted pathways with opposite trends between the models and the clinics. Additionally, through our approach, we discovered four targets for anti-vascular aging drugs, which were consistent with their pharmaceutical effects in literatures, showing the value of this approach. In the end, software was established to facilitate the use of “Cross-species signaling pathway analysis.” In sum, our study suggests utilizing bioinformatics analysis based on disease characteristics can help in choosing more appropriate animal models.

Abstract Image

跨物种信号通路分析启发动物模型选择,用于血管老化疾病的药物筛选和靶点预测
年龄是导致心血管疾病(CVD)发生和发展的重要因素。药物治疗可以有效缓解因衰老引起的心血管疾病症状。然而,90% 的药物在临床上都因药效消失或出现副作用而失效。其中一个原因是所使用的动物模型与人体的实际生理水平存在差异。因此,我们整合了来自大鼠、猴子和人类的单细胞和大量序列 RNA 测序数据的多个数据集,以确定这三个物种中具有一致/差异表达模式的基因和通路。研究人员开发了一种名为 "跨物种信号通路分析 "的方法,用于选择合适的动物模型进行药物筛选。通过分析动物/临床实验中使用的四种已知抗血管老化药物的药理预测,验证了这种方法的有效性。在我们的分析中,当药物以相同趋势的途径为靶点时,在模型和临床之间观察到的药物有效性是一致的。但是,如果药物针对的通路在模型和临床中的趋势相反,则可能会产生不利影响。此外,通过我们的方法,我们发现了抗血管老化药物的四个靶点,这些靶点与文献中的药物效果一致,显示了这种方法的价值。最后,我们还建立了便于使用 "跨物种信号通路分析 "的软件。总之,我们的研究表明,基于疾病特征的生物信息学分析有助于选择更合适的动物模型。
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来源期刊
Evolutionary Applications
Evolutionary Applications 生物-进化生物学
CiteScore
8.50
自引率
7.30%
发文量
175
审稿时长
6 months
期刊介绍: Evolutionary Applications is a fully peer reviewed open access journal. It publishes papers that utilize concepts from evolutionary biology to address biological questions of health, social and economic relevance. Papers are expected to employ evolutionary concepts or methods to make contributions to areas such as (but not limited to): medicine, agriculture, forestry, exploitation and management (fisheries and wildlife), aquaculture, conservation biology, environmental sciences (including climate change and invasion biology), microbiology, and toxicology. All taxonomic groups are covered from microbes, fungi, plants and animals. In order to better serve the community, we also now strongly encourage submissions of papers making use of modern molecular and genetic methods (population and functional genomics, transcriptomics, proteomics, epigenetics, quantitative genetics, association and linkage mapping) to address important questions in any of these disciplines and in an applied evolutionary framework. Theoretical, empirical, synthesis or perspective papers are welcome.
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