He Yijie, Zhu Ping, Gao Shan, Wu Shiyang, Li Xuan, Huang Chen, Chen Yan, Liu Guiyou
Beijing Institute of Brain Disorders, Laboratory of Brain Disorders, Ministry of Science and Technology, Collaborative Innovation Center for Brain Disorders, Capital Medical University, Beijing, China.
Dr. Neher's Biophysics Laboratory for Innovative Drug Discovery, State Key Laboratory of Quality Research in Chinese Medicine, Macau University of Science and Technology, Taipa, China.
J Neurochem. 2025 Jan;169(1):e16276. doi: 10.1111/jnc.16276.
To date, several studies have integrated genome-wide association studies (GWAS) and expression quantitative trait loci (eQTL) data from bulk tissues to identify novel Alzheimer's disease (AD) genetic variants and susceptibility genes. However, there is highly cell-type-specific nature in different bulk eQTL data. Until now, eQTL data from different brain single cells have been reported. Therefore, integrating eQTL data from different brain single-cell types along with AD GWAS data makes biological sense for studying the potential biological explanations of AD. Here, we utilized the summary-data-based Mendelian randomization (SMR) method to integrate AD GWAS data with eQTL data from eight brain single-cell types. We identified a larger number of significant genes compared to previous SMR study based on bulk eQTL. Notably, microglia exhibited the highest number of significant genes. Moreover, we conducted validation-phase SMR analysis, single-cell analysis, protein-protein interaction (PPI), druggability evaluation, functional enrichment analyses, and colocalization analysis of the top 20 SMR significant genes in microglia. We found that most genes passed the validation and were significantly enriched in microglia. PPI analysis uncovered interactions among PICALM, BIN1, RIN3, CD2AP, CASS4, and MS4A6E. Five most significant SMR genes were further validated through colocalization analysis. RIN3 is the only significant gene across all mentioned analyses and is a novel AD susceptibility gene at the genome-wide significance level. Druggability evaluation identified KCNQ3, HLA-DQB1, and RABEP1 as known genes previously targeted for drug development in neurological disorders, suggesting their potential therapeutic relevance in AD.
迄今为止，已有多项研究整合了来自大块组织的全基因组关联研究（GWAS）和表达定量性状基因座（eQTL）数据，以识别新的阿尔茨海默病（AD）遗传变异和易感基因。然而，不同的大块eQTL数据具有高度的细胞类型特异性。到目前为止，已经报道了来自不同脑单细胞的eQTL数据。因此，将来自不同脑单细胞类型的eQTL数据与AD GWAS数据整合起来，对于研究AD的潜在生物学解释具有生物学意义。在这里，我们利用基于汇总数据的孟德尔随机化（SMR）方法，将AD GWAS数据与来自八种脑单细胞类型的eQTL数据进行整合。与之前基于大块eQTL的SMR研究相比，我们鉴定出了更多的显著基因。值得注意的是，小胶质细胞表现出的显著基因数量最多。此外，我们对小胶质细胞中排名前20的SMR显著基因进行了验证阶段的SMR分析、单细胞分析、蛋白质-蛋白质相互作用（PPI）分析、药物可及性评估、功能富集分析和共定位分析。我们发现大多数基因通过了验证，并且在小胶质细胞中显著富集。PPI分析揭示了PICALM、BIN1、RIN3、CD2AP、CASS4和MS4A6E之间的相互作用。通过共定位分析进一步验证了五个最显著的SMR基因。RIN3是所有上述分析中唯一的显著基因，并且是全基因组显著性水平上的一个新的AD易感基因。药物可及性评估确定KCNQ3、HLA-DQB1和RABEP1为先前在神经疾病中作为药物开发靶点的已知基因，表明它们在AD中具有潜在的治疗相关性。
