Your browser doesn't support javascript.
loading
Bulk-RNA and single-nuclei RNA seq analyses reveal the role of lactate metabolism-related genes in Alzheimer's disease.
Liu, Hanjie; Yi, Xiaohong; You, Maochun; Yang, Hui; Zhang, Siyu; Huang, Sihan; Xie, Lushuang.
Afiliación
  • Liu H; Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, P.R. China.
  • Yi X; Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, P.R. China.
  • You M; Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, P.R. China. youmaochun@cdutcm.edu.cn.
  • Yang H; Chengdu Shuangliu Hospital of Traditional Chinese Medicine, Chengdu, 610200, Sichuan, P.R. China.
  • Zhang S; Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, P.R. China.
  • Huang S; Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, P.R. China.
  • Xie L; Chengdu University of Traditional Chinese Medicine, Chengdu, 611137, Sichuan, P.R. China. xielushuang@cdutcm.edu.cn.
Metab Brain Dis ; 2024 Aug 13.
Article en En | MEDLINE | ID: mdl-39136807
ABSTRACT
Dysfunctional lactate metabolism in the brain has been implicated in neuroinflammation, Aß 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.
Palabras clave

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Metab Brain Dis Asunto de la revista: CEREBRO / METABOLISMO Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Metab Brain Dis Asunto de la revista: CEREBRO / METABOLISMO Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos