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首页> 外文期刊>Informatics in Medicine Unlocked >Systems biology and bioinformatics approach to identify gene signatures, pathways and therapeutic targets of Alzheimer's disease
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Systems biology and bioinformatics approach to identify gene signatures, pathways and therapeutic targets of Alzheimer's disease

机译：系统生物学和生物信息学方法，以鉴定基因签名，途径和阿尔茨海默病的治疗靶标

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Alzheimer's disease (AD) develops relentlessly in affected individuals and its occurrence is increasing. A clinical test to diagnose early-stage AD could be an important means of enabling interventions to slow its progression. However, available neuroimaging and cerebrospinal fluid-based diagnoses are very costly. Therefore, detecting AD from blood transcripts that mirror the expression of brain transcripts in the AD could improve the diagnosis. To achieve this goal, we employed a transcriptional analysis of affected tissues and integrated them with cis-eQTL data. In this study, we analyzed microarray gene expression data of brain and blood cells from AD patients and control individuals. Differentially expressed genes (DEGs) common to both brain tissue and blood cells were identified. Potential common genes and molecular pathways were identified using overlapping DEGs through the pathway and gene ontology enrichment analysis. We identified 18 significantly dysregulated genes shared by both brain and blood cells in AD affected individuals. We validated these candidates as disease-associated genes using gold-standard benchmarking databases (gene SNP-disease linkage). Significant molecular pathway and gene ontology indicating AD progression were identified. This study also identified regulatory factors, including transcription factors (TFs), microRNAs and candidate drugs. In sum, we identified new putative links between pathological processes in brain tissue and blood cells in AD that may allow assessment of AD status using blood samples. Thus, our formulated methodologies demonstrate the power of gene and gene expression analysis for brain-related pathologies transcriptomics, cis-eQTL, and epigenetics data from brain and blood cells.
机译：阿尔茨海默病的疾病（AD）在受影响的个体中无情地发展，其发生正在增加。诊断早期广告的临床测试可能是使干预措施减缓其进展的重要手段。然而，可用的神经影像动物和基于脑脊液的诊断非常昂贵。因此，检测来自血液转录物的广告，镜像广告中脑转录物的表达可以改善诊断。为实现这一目标，我们使用受影响组织的转录分析，并与CIS-EQTL数据集成。在本研究中，我们分析了来自AD患者和对照个体的脑和血细胞的微阵列基因表达数据。鉴定了对脑组织和血细胞共同的差异表达的基因（DEGS）。通过通过途径和基因本体富集分析使用重叠的次数来鉴定潜在的常见基因和分子途径。我们鉴定了18名明显失调的基因，受影响的脑和血细胞共享的。我们使用金标准的基准数据库（基因SNP-DICHILE LINGAGE）验证了这些候选者作为疾病相关基因。确定了表明AD进展的重要分子途径和基因本体。本研究还确定了调节因子，包括转录因子（TFS），MicroRNA和候选药物。总而言之，我们确定了可允许使用血样评估AD状态的脑组织和血细胞的病理过程之间的新推定联系。因此，我们配制的方法表明了基因和基因表达分析的力量与脑和血细胞脑相关病理转录组科，CIS-EQTL和表观遗传学数据的力量。

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