دورية أكاديمية
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Elucidating Microglial Heterogeneity and Functions in Alzheimer's Disease Using Single-cell Analysis and Convolutional Neural Network Disease Model Construction.

التفاصيل البيبلوغرافية
العنوان: Elucidating Microglial Heterogeneity and Functions in Alzheimer's Disease Using Single-cell Analysis and Convolutional Neural Network Disease Model Construction.
المؤلفون: Wu X; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Liu M; Department of Vascular and Thyroid Surgery, The First Hospital of China Medical University, Shenyang, China., Zhang X; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Pan X; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Cui X; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Jin J; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Sun H; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Xiao C; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Tong X; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Ren L; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Wang Y; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China., Cao X; Department of Anesthesiology, The First Hospital of China Medical University, 155 Nanjing North Street, Shenyang, 110001, China. xuezhaocao2011@163.com.
المصدر: Scientific reports [Sci Rep] 2024 Jul 27; Vol. 14 (1), pp. 17271. Date of Electronic Publication: 2024 Jul 27.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: Nature Publishing Group Country of Publication: England NLM ID: 101563288 Publication Model: Electronic Cited Medium: Internet ISSN: 2045-2322 (Electronic) Linking ISSN: 20452322 NLM ISO Abbreviation: Sci Rep Subsets: MEDLINE
أسماء مطبوعة: Original Publication: London : Nature Publishing Group, copyright 2011-
مواضيع طبية MeSH: Alzheimer Disease*/genetics , Alzheimer Disease*/pathology , Alzheimer Disease*/metabolism , Single-Cell Analysis*/methods , Microglia*/metabolism , Microglia*/pathology , Neural Networks, Computer*, Humans ; Gene Regulatory Networks ; Gene Expression Profiling ; Deep Learning
مستخلص: In this study, we conducted an in-depth exploration of Alzheimer's Disease (AD) by integrating state-of-the-art methodologies, including single-cell RNA sequencing (scRNA-seq), weighted gene co-expression network analysis (WGCNA), and a convolutional neural network (CNN) model. Focusing on the pivotal role of microglia in AD pathology, our analysis revealed 11 distinct microglial subclusters, with 4 exhibiting obviously alterations in AD and HC groups. The investigation of cell-cell communication networks unveiled intricate interactions between AD-related microglia and various cell types within the central nervous system (CNS). Integration of WGCNA and scRNA-seq facilitated the identification of critical genes associated with AD-related microglia, providing insights into their involvement in processes such as peptide chain elongation, synapse-related functions, and cell adhesion. The identification of 9 hub genes, including USP3, through the least absolute shrinkage and selection operator (LASSO) and COX regression analyses, presents potential therapeutic targets. Furthermore, the development of a CNN-based model showcases the application of deep learning in enhancing diagnostic accuracy for AD. Overall, our findings significantly contribute to unraveling the molecular intricacies of microglial responses in AD, offering promising avenues for targeted therapeutic interventions and improved diagnostic precision.
(© 2024. The Author(s).)
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معلومات مُعتمدة: (No. 81300938) National Natural Science Foundation of China; (No. 2022-MS-222) Natural Science Foundation of Liaoning Province
فهرسة مساهمة: Keywords: Alzheimer’s disease; Convolutional neural network; Microglia; scRNA-seq
تواريخ الأحداث: Date Created: 20240727 Date Completed: 20240728 Latest Revision: 20240806
رمز التحديث: 20240806
مُعرف محوري في PubMed: PMC11283484
DOI: 10.1038/s41598-024-67537-1
PMID: 39068182
قاعدة البيانات: MEDLINE
الوصف
تدمد:2045-2322
DOI:10.1038/s41598-024-67537-1