Xu Jielin, Song Wenqiang, Xu Zhenxing, Danziger Michael M, Karavani Ehud, Zang Chengxi, Chen Xin, Li Yichen, Paz Isabela M Rivera, Gohel Dhruv, Su Chang, Zhou Yadi, Hou Yuan, Shimoni Yishai, Pieper Andrew A, Hu Jianying, Wang Fei, Rosen-Zvi Michal, Leverenz James B, Cummings Jeffrey, Cheng Feixiong
Cleveland Clinic Genome Center, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Genomic Medicine Institute, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.
Alzheimers Dement. 2025 Jan;21(1):e14373. doi: 10.1002/alz.14373. Epub 2024 Dec 6.
High microglial heterogeneities hinder the development of microglia-targeted treatment for Alzheimer's disease (AD).
We integrated 0.7 million single-nuclei RNA-sequencing transcriptomes from human brains using a variational autoencoder. We predicted AD-relevant microglial subtype-specific transition networks for disease-associated microglia (DAM), tau microglia, and neuroinflammation-like microglia (NIM). We prioritized drugs by specifically targeting microglia-specific transition networks and validated drugs using two independent real-world patient databases.
We identified putative AD molecular drivers (e.g., SYK, CTSB, and INPP5D) in transition networks of DAM and NIM. Via specifically targeting NIM, we identified that usage of ketorolac was associated with reduced AD incidence in both MarketScan (hazard ratio [HR] = 0.89) and INSIGHT (HR = 0.83) Clinical Research Network databases, mechanistically supported by ketorolac-treated transcriptomic data from AD patient induced pluripotent stem cell-derived microglia.
This study offers insights into the pathobiology of AD-relevant microglial subtypes and identifies ketorolac as a potential anti-inflammatory treatment for AD.
An integrative analysis of ≈ 0.7 million single-nuclei RNA-sequencing transcriptomes from human brains identified Alzheimer's disease (AD)-relevant microglia subtypes. Network-based analysis identified putative molecular drivers (e.g., SYK, CTSB, INPP5D) of transition networks between disease-associated microglia (DAM) and neuroinflammation-like microglia (NIM). Via network-based prediction and population-based validation, we identified that usage of ketorolac (a US Food and Drug Administration-approved anti-inflammatory medicine) was associated with reduced AD incidence in two independent patient databases. Mechanistic observation showed that ketorolac treatment downregulated the Type-I interferon signaling in patient induced pluripotent stem cell-derived microglia, mechanistically supporting its protective effects in real-world patient databases.
高度的小胶质细胞异质性阻碍了针对阿尔茨海默病（AD）的小胶质细胞靶向治疗的发展。
我们使用变分自编码器整合了来自人类大脑的70万个单核RNA测序转录组。我们预测了与AD相关的小胶质细胞亚型特异性转变网络，用于疾病相关小胶质细胞（DAM）、tau小胶质细胞和神经炎症样小胶质细胞（NIM）。我们通过特异性靶向小胶质细胞特异性转变网络对药物进行优先级排序，并使用两个独立的真实世界患者数据库对药物进行验证。
我们在DAM和NIM的转变网络中鉴定出推定的AD分子驱动因素（如SYK、CTSB和INPP5D）。通过特异性靶向NIM，我们发现在MarketScan（风险比[HR]=0.89）和INSIGHT（HR=0.83）临床研究网络数据库中，使用酮咯酸与AD发病率降低相关，AD患者诱导多能干细胞衍生的小胶质细胞的酮咯酸处理转录组数据在机制上支持了这一点。
本研究为与AD相关的小胶质细胞亚型的病理生物学提供了见解，并确定酮咯酸为AD的潜在抗炎治疗药物。
对来自人类大脑的约70万个单核RNA测序转录组进行综合分析，确定了与阿尔茨海默病（AD）相关的小胶质细胞亚型。基于网络的分析确定了疾病相关小胶质细胞（DAM）和神经炎症样小胶质细胞（NIM）之间转变网络的推定分子驱动因素（如SYK、CTSB、INPP5D）。通过基于网络的预测和基于人群的验证，我们发现在两个独立的患者数据库中，使用酮咯酸（一种美国食品药品监督管理局批准的抗炎药物）与AD发病率降低相关。机制观察表明，酮咯酸治疗下调了患者诱导多能干细胞衍生的小胶质细胞中的I型干扰素信号，在机制上支持了其在真实世界患者数据库中的保护作用。
