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引用次数: 0
摘要
背景：阿尔茨海默病（AD）是一种不可逆的神经退行性疾病，目前尚无完全治愈的方法：阿尔茨海默病（AD）是一种不可逆的神经退行性疾病，目前尚无完全治愈的方法。目的：本研究旨在通过结合多组学和孟德尔随机化（MR）分析，确定诊断和治疗AD的有效生物标志物：采用先进的相关分析方法（AdaSMCCA、rAdaSMCCA和unAdaSMCCA算法）整合AD患者的正电子发射断层扫描（PET）、单核苷酸多态性（SNP）和基因表达数据：结果：确定了与注意力缺失症相关的几个感兴趣区域、风险 SNP 位点和风险基因。从公共数据集中检索到了前 100 个风险基因的表达定量性状位点（eQTL）。利用全基因组关联研究（GWAS）数据进行的双样本 MR 分析发现了两个与 AD 有因果关系的基因（FAM117A 和 ACSL1）。此外，还对来自AD样本的单细胞转录组（scRNA-seq）数据进行了分析，以确定高分细胞集群及其相互作用：结论：已确定的多组学生物标志物和与AD有因果关系的基因可为临床诊断和治疗提供依据。
Exploring biomarkers of Alzheimer's disease based on multi-omics and Mendelian randomisation analysis.
Background: Alzheimer's disease (AD) is an irreversible neurodegenerative disorder with no fully curative treatment.
Aim: This study aims to identify effective biomarkers for AD diagnosis and treatment by combining multi-omics and Mendelian randomisation (MR) analyses.
Subjects and methods: Positron emission tomography (PET), single nucleotide polymorphism (SNP), and gene expression data of AD patients using advanced correlation analysis methods (AdaSMCCA, rAdaSMCCA, and unAdaSMCCA algorithms) are integrated.
Results: Several regions of interest, risk SNP sites, and risk genes associated with AD are identified. Expression quantitative trait loci (eQTL) for the top 100 risk genes are retrieved from public datasets. A two-sample MR analysis using genome-wide association study (GWAS) data reveals two genes (FAM117A and ACSL1) causally related to AD. Additionally, single-cell transcriptome (scRNA-seq) data from AD samples are analysed to identify high-scoring cell clusters and their interactions.
Conclusions: The identified multi-omics biomarkers and genes causally related to AD could inform clinical diagnosis and treatment.
期刊介绍：
Annals of Human Biology is an international, peer-reviewed journal published six times a year in electronic format. The journal reports investigations on the nature, development and causes of human variation, embracing the disciplines of human growth and development, human genetics, physical and biological anthropology, demography, environmental physiology, ecology, epidemiology and global health and ageing research.
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