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Gene interactions analysis of brain spatial transcriptome for Alzheimer's disease.
Wang, Shengran; Greenbaum, Jonathan; Qiu, Chuan; Swerdlow, Russell H; Haeri, Mohammad; Gong, Yun; Shen, Hui; Xiao, Hongmei; Deng, Hongwen.
Afiliación
  • Wang S; Reproductive Medicine Center, The Sun Yat-sen Memorial Hospital, Sun Yat-sen University, Guangzhou, Guangdong 510120, China.
  • Greenbaum J; Center for System Biology, Data Sciences and Reproductive Health, School of Basic Medical Science, Central South University, Changsha, Hunan 410008, China.
  • Qiu C; Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, New Orleans, LA 70112, USA.
  • Swerdlow RH; Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, New Orleans, LA 70112, USA.
  • Haeri M; Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, New Orleans, LA 70112, USA.
  • Gong Y; Department of Pathology and KU Alzheimer's Disease Research Center, University of Kansas Medical Center, Kansas City, KS 66160, USA.
  • Shen H; Department of Pathology and KU Alzheimer's Disease Research Center, University of Kansas Medical Center, Kansas City, KS 66160, USA.
  • Xiao H; Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, New Orleans, LA 70112, USA.
  • Deng H; Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University School of Medicine, Tulane University, New Orleans, LA 70112, USA.
Genes Dis ; 11(6): 101337, 2024 Nov.
Article en En | MEDLINE | ID: mdl-39281834
ABSTRACT
Recent studies have explored the spatial transcriptomics patterns of Alzheimer's disease (AD) brain by spatial sequencing in mouse models, enabling the identification of unique genome-wide transcriptomic features associated with different spatial regions and pathological status. However, the dynamics of gene interactions that occur during amyloid-ß accumulation remain largely unknown. In this study, we performed analyses on ligand-receptor communication, transcription factor regulatory network, and spot-specific network to reveal the dependence and the dynamics of gene associations/interactions on spatial regions and pathological status with mouse and human brains. We first used a spatial transcriptomics dataset of the App NL-G-F knock-in AD and wild-type mouse model. We revealed 17 ligand-receptor pairs with opposite tendencies throughout the amyloid-ß accumulation process and showed the specific ligand-receptor interactions across the hippocampus layers at different extents of pathological changes. We then identified nerve function related transcription factors in the hippocampus and entorhinal cortex, as well as genes with different transcriptomic association degrees in AD versus wild-type mice. Finally, another independent spatial transcriptomics dataset from different AD mouse models and human single-nuclei RNA-seq data/AlzData database were used for validation. This is the first study to identify various gene associations throughout amyloid-ß accumulation based on spatial transcriptomics, establishing the foundations to reveal advanced and in-depth AD etiology from a novel perspective based on the comprehensive analyses of gene interactions that are spatio-temporal dependent.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Genes Dis Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Genes Dis Año: 2024 Tipo del documento: Article País de afiliación: China Pais de publicación: Países Bajos