Bulk-RNA and single-nuclei RNA seq analyses reveal the role of lactate metabolism-related genes in Alzheimer's disease.

IF 3.2 3区 医学 Q2 ENDOCRINOLOGY & METABOLISM
Hanjie Liu, Xiaohong Yi, Maochun You, Hui Yang, Siyu Zhang, Sihan Huang, Lushuang Xie
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引用次数: 0

Abstract

Dysfunctional lactate metabolism in the brain has been implicated in neuroinflammation, Aβ deposition, and cell disturbance, all of which play a significant role in the pathogenesis of Alzheimer's disease (AD). In this study, we aimed to investigate the lactate metabolism-related genes (LMRGs) in AD via an integrated bulk RNA and single-nuclei RNA sequencing (snRNA-seq) analysis, with a specific focus on microglia. We obtained 26 HC and 24 AD snRNA-seq samples originated from human prefrontal cortex in Gene Expression Omnibus (GEO) database and collected 873 LMRGs from three databases, namely MSigDB, The Human Protein Atlas and GeneCards. Bulk RNA was analyzed with LMRG characteristics in AD by using Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), the protein-protein interaction (PPI), CytoHubba-MCC, Support Vector Machine (SVM) algorithms analyses. Then we conducted the Receiver Operating Characteristic (ROC) curve, correlation, and connection network analyses for biomarkers. Their differential expression validation was performed using AlzData database. The single-nuclei RNA analysis of microglia was applied to identify hub genes and pathways using cell-cell communication analysis and high dimensional Weighted Gene Co-Expression Network Analysis (hdWGCNA). Support Vector Machine (SVM) algorithm showed an AUC of 0.967, a sensitivity of 93.30% and a specificity of 100.00%. Our analysis identified biomarkers with LMRG characteristics, namely INSR, CDKL1, and PNISR. ROC analysis revealed that each of these biomarkers exhibited excellent diagnostic potential, as evidenced by their respective area under the curve (AUC) values: INSR (AUC: 0.679), CDKL1 (AUC: 0.788), and PNISR (AUC: 0.724). Correlation analysis showed that biomarkers exhibited a positive correlation with each other. Connection network illustrated their shared biological processes: aging, phosphorylation, metabolic process, and apoptosis. Cell-cell communication analysis revealed that GALECTIN signaling pathway was exclusively expressed in AD microglia, and only LGALS9 exhibited significant overexpression. HdWGCNA identified FTH1 as a hub gene enriched in ferroptosis and mineral absorption pathways within microglia. The roles of INSR, CDKL1, PNISR, LGALS9, and FTH1 should be taken into account to enhance our understanding of lactate metabolism in the context of AD.

Abstract Image

大量 RNA 和单核 RNA seq 分析揭示了乳酸代谢相关基因在阿尔茨海默病中的作用。
大脑中的乳酸代谢功能失调与神经炎症、Aβ沉积和细胞紊乱有关,这些因素在阿尔茨海默病(AD)的发病机制中发挥着重要作用。在本研究中,我们旨在通过整合大分子 RNA 和单核 RNA 测序(snRNA-seq)分析,研究 AD 中的乳酸代谢相关基因(LMRGs),并特别关注小胶质细胞。我们从基因表达总库(GEO)数据库中获得了26份HC和24份AD snRNA-seq样本,并从MSigDB、人类蛋白质图谱(The Human Protein Atlas)和基因卡片(GeneCards)三个数据库中收集了873个LMRGs。利用基因本体(GO)、京都基因组百科全书(KEGG)、蛋白质相互作用(PPI)、CytoHubba-MCC、支持向量机(SVM)等算法分析了AD中大块RNA的LMRG特征。然后,我们对生物标记物进行了接收操作特征曲线(ROC)、相关性和连接网络分析。我们还利用 AlzData 数据库对生物标志物的差异表达进行了验证。利用细胞-细胞通讯分析和高维加权基因共表达网络分析(hdWGCNA)对小胶质细胞进行单核 RNA 分析,以确定枢纽基因和通路。支持向量机(SVM)算法的AUC为0.967,灵敏度为93.30%,特异度为100.00%。我们的分析确定了具有 LMRG 特征的生物标记物,即 INSR、CDKL1 和 PNISR。ROC分析表明,这些生物标记物各自的曲线下面积(AUC)值都显示出卓越的诊断潜力:INSR(AUC:0.679)、CDKL1(AUC:0.788)和 PNISR(AUC:0.724)。相关性分析表明,生物标志物之间呈现出正相关性。连接网络显示了它们共同的生物过程:衰老、磷酸化、代谢过程和细胞凋亡。细胞-细胞通讯分析表明,GALECTIN 信号通路只在 AD 小胶质细胞中表达,只有 LGALS9 表现出明显的过表达。HdWGCNA发现FTH1是富集于小胶质细胞内铁凋亡和矿物质吸收通路的枢纽基因。应考虑 INSR、CDKL1、PNISR、LGALS9 和 FTH1 的作用,以加深我们对 AD 背景下乳酸代谢的理解。
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来源期刊
Metabolic brain disease
Metabolic brain disease 医学-内分泌学与代谢
CiteScore
5.90
自引率
5.60%
发文量
248
审稿时长
6-12 weeks
期刊介绍: Metabolic Brain Disease serves as a forum for the publication of outstanding basic and clinical papers on all metabolic brain disease, including both human and animal studies. The journal publishes papers on the fundamental pathogenesis of these disorders and on related experimental and clinical techniques and methodologies. Metabolic Brain Disease is directed to physicians, neuroscientists, internists, psychiatrists, neurologists, pathologists, and others involved in the research and treatment of a broad range of metabolic brain disorders.
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