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多模态单细胞/核 RNA 测序数据分析揭示了与疾病相关的小胶质细胞和星形胶质细胞之间的分子网络,这对阿尔茨海默病药物再利用具有启示意义。

Multimodal single-cell/nucleus RNA sequencing data analysis uncovers molecular networks between disease-associated microglia and astrocytes with implications for drug repurposing in Alzheimer's disease.

机构信息

Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio 44195, USA.

Department of Biostatistics, School of Medicine, Indiana University, Indianapolis, Indiana 46202, USA.

出版信息

Genome Res. 2021 Oct;31(10):1900-1912. doi: 10.1101/gr.272484.120. Epub 2021 Feb 24.

Abstract

Because disease-associated microglia (DAM) and disease-associated astrocytes (DAA) are involved in the pathophysiology of Alzheimer's disease (AD), we systematically identified molecular networks between DAM and DAA to uncover novel therapeutic targets for AD. Specifically, we develop a network-based methodology that leverages single-cell/nucleus RNA sequencing data from both transgenic mouse models and AD patient brains, as well as drug-target network, metabolite-enzyme associations, the human protein-protein interactome, and large-scale longitudinal patient data. Through this approach, we find both common and unique gene network regulators between DAM (i.e., , , and ) and DAA (i.e., , , and ) that are significantly enriched by neuro-inflammatory pathways and well-known genetic variants (i.e., ). We identify shared immune pathways between DAM and DAA, including Th17 cell differentiation and chemokine signaling. Last, integrative metabolite-enzyme network analyses suggest that fatty acids and amino acids may trigger molecular alterations in DAM and DAA. Combining network-based prediction and retrospective case-control observations with 7.2 million individuals, we identify that usage of fluticasone (an approved glucocorticoid receptor agonist) is significantly associated with a reduced incidence of AD (hazard ratio [HR] = 0.86, 95% confidence interval [CI] 0.83-0.89, < 1.0 × 10). Propensity score-stratified cohort studies reveal that usage of mometasone (a stronger glucocorticoid receptor agonist) is significantly associated with a decreased risk of AD (HR = 0.74, 95% CI 0.68-0.81, < 1.0 × 10) compared to fluticasone after adjusting age, gender, and disease comorbidities. In summary, we present a network-based, multimodal methodology for single-cell/nucleus genomics-informed drug discovery and have identified fluticasone and mometasone as potential treatments in AD.

摘要

由于与疾病相关的小胶质细胞(DAM)和与疾病相关的星形胶质细胞(DAA)参与了阿尔茨海默病(AD)的病理生理学过程,我们系统地确定了 DAM 和 DAA 之间的分子网络,以发现 AD 的新治疗靶点。具体来说,我们开发了一种基于网络的方法,该方法利用来自转基因小鼠模型和 AD 患者大脑的单细胞/核 RNA 测序数据,以及药物-靶标网络、代谢物-酶关联、人类蛋白质-蛋白质相互作用组和大规模纵向患者数据。通过这种方法,我们发现了 DAM(即 、 、 和 )和 DAA(即 、 、 和 )之间既有共同又有独特的基因网络调节剂,这些调节剂显著富集了神经炎症途径和众所周知的遗传变异(即 )。我们确定了 DAM 和 DAA 之间共同的免疫途径,包括 Th17 细胞分化和趋化因子信号。最后,整合代谢物-酶网络分析表明,脂肪酸和氨基酸可能引发 DAM 和 DAA 的分子改变。结合基于网络的预测和对 720 万人的回顾性病例对照观察,我们发现使用氟替卡松(一种已批准的糖皮质激素受体激动剂)与 AD 发病率降低显著相关(风险比[HR] = 0.86,95%置信区间[CI] 0.83-0.89, < 1.0×10)。倾向评分分层队列研究表明,与氟替卡松相比,使用莫米松(一种更强的糖皮质激素受体激动剂)与 AD 风险降低显著相关(HR = 0.74,95%CI 0.68-0.81, < 1.0×10),在调整年龄、性别和疾病合并症后。总之,我们提出了一种基于网络的、多模式的单细胞/核基因组学指导药物发现方法,并确定了氟替卡松和莫米松作为 AD 的潜在治疗方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/613e/8494225/e1f14c244bbc/1900f01.jpg

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