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阿尔茨海默病的综合多组学分析显示了与疾病进展相关的分子特征和潜在的治疗靶点。

Integrated multi-omics analysis of Alzheimer's disease shows molecular signatures associated with disease progression and potential therapeutic targets.

机构信息

Department of Biological Sciences, Birla Institute of Technology and Science Pilani, Hyderabad Campus, Jawahar Nagar, Hyderabad, Telangana, 500078, India.

Disease Biology Lab, Department of Biosciences, Sri Sathya Sai Institute of Higher Learning, Prasanthi Nilayam, Anantapur, Andhra Pradesh, 515134, India.

出版信息

Sci Rep. 2023 Mar 6;13(1):3695. doi: 10.1038/s41598-023-30892-6.

Abstract

Alzheimer's disease (AD) is a progressive neurodegenerative disease characterized by the formation of amyloid plaques implicated in neuronal death. Genetics, age, and sex are the risk factors attributed to AD. Though omics studies have helped to identify pathways associated with AD, an integrated systems analysis with the available data could help to understand mechanisms, potential biomarkers, and therapeutic targets. Analysis of transcriptomic data sets from the GEO database, and proteomic and metabolomic data sets from literature was performed to identify deregulated pathways and commonality analysis identified overlapping pathways among the data sets. The deregulated pathways included those of neurotransmitter synapses, oxidative stress, inflammation, vitamins, complement, and coagulation pathways. Cell type analysis of GEO data sets showed microglia, endothelial, myeloid, and lymphoid cells are affected. Microglia are associated with inflammation and pruning of synapses with implications for memory and cognition. Analysis of the protein-cofactor network of B, B and pantothenate shows metabolic pathways modulated by these vitamins which overlap with the deregulated pathways from the multi-omics analysis. Overall, the integrated analysis identified the molecular signature associated with AD. Treatment with anti-oxidants, B, B, and pantothenate in genetically susceptible individuals in the pre-symptomatic stage might help in better management of the disease.

摘要

阿尔茨海默病(AD)是一种进行性神经退行性疾病,其特征是形成淀粉样斑块,与神经元死亡有关。遗传学、年龄和性别是导致 AD 的风险因素。尽管组学研究有助于确定与 AD 相关的途径,但对现有数据进行综合系统分析有助于了解机制、潜在生物标志物和治疗靶点。对 GEO 数据库中的转录组数据集、文献中的蛋白质组学和代谢组学数据集进行分析,以确定失调途径,共同分析确定了数据集之间的重叠途径。失调途径包括神经递质突触、氧化应激、炎症、维生素、补体和凝血途径。GEO 数据集的细胞类型分析显示小胶质细胞、内皮细胞、髓样细胞和淋巴样细胞受到影响。小胶质细胞与炎症和突触修剪有关,这对记忆和认知有影响。B、B 和泛酸蛋白-辅因子网络的分析表明,这些维生素调节的代谢途径与多组学分析中失调的途径重叠。总的来说,综合分析确定了与 AD 相关的分子特征。在有遗传易感性的个体处于无症状前阶段时,用抗氧化剂、B、B 和泛酸进行治疗可能有助于更好地管理这种疾病。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bb34/9988859/d0677988ed93/41598_2023_30892_Fig1_HTML.jpg

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