Data_Sheet_1_Identification of KIAA0513 and Other Hub Genes Associated With Alzheimer Disease Using Weighted Gene Coexpression Network Analysis.DOCX

Alzheimer disease (AD) is the most common cause of dementia and creates a significant burden on society. As a result, the investigation of hub genes for the discovery of potential therapeutic targets and candidate biomarkers is warranted. In this study, we used the ComBat method to merge three gene expression datasets of AD from the Gene Expression Omnibus (GEO). During combined analysis, we identified 850 differentially expressed genes (DEGs) from the temporal cortex of AD and cognitively normal (CN) samples. We performed weighted gene coexpression network analysis to build gene coexpression networks incorporating these DEGs to identify key modules and hub genes. We found one module most strongly correlated with AD onset as the key module and 19 hub genes in the key module that were down-regulated in AD brains. According to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analyses, DEGs were mostly enriched in synapse function, and genes in the key module were mostly related to learning and memory. We selected five little-studied genes, AP3B2, GABRD, GPR158, KIAA0513, and MAL2, to validate their expression in AD mouse model by performing quantitative real-time polymerase chain reaction. We found that all of them were down-regulated in cortices of 8-month 5xFAD mice compared to those of wild-type mice. We then further investigated their correlations with β-secretase activity and Aβ42 levels in AD samples of different Braak stages. We found that all five hub genes had significant negative associations with β-secretase activity and that AP3B2 and KIAA0513 had significant negative associations with Aβ42 levels. We tested the differential expressions of the five hub genes in two AD GEO datasets from the blood and found that KIAA0513 was significantly up-regulated in patients with both mild cognitive impairment (MCI) and AD and was able to differentiate MCI and AD from CN in the two datasets. In conclusion, these five novel vulnerable genes were involved in AD progression, and KIAA0513 was a promising candidate biomarker for early diagnosis of AD.

阿尔茨海默病（Alzheimer disease, AD）是痴呆最常见的病因，给社会带来沉重负担。因此，探索可用于发现潜在治疗靶点与候选生物标志物的枢纽基因具有重要研究价值。本研究采用ComBat算法，整合来自基因表达综合数据库（Gene Expression Omnibus, GEO）的3组阿尔茨海默病基因表达数据集。在整合分析过程中，我们从AD患者与认知正常（cognitively normal, CN）个体的颞叶皮层样本中，筛选得到850个差异表达基因（differentially expressed genes, DEGs）。我们通过加权基因共表达网络分析，基于上述DEGs构建基因共表达网络，以识别关键模块与枢纽基因。研究发现，与AD发病相关性最强的模块即为关键模块，该模块内共有19个在AD脑内表达下调的枢纽基因。经基因本体（Gene Ontology, GO）与京都基因与基因组百科全书（Kyoto Encyclopedia of Genes and Genomes, KEGG）富集分析，DEGs主要富集于突触功能相关通路，而关键模块内的基因则多与学习记忆功能密切相关。我们选取AP3B2、GABRD、GPR158、KIAA0513及MAL2这5个鲜有研究的基因，通过实时定量聚合酶链反应验证其在AD小鼠模型中的表达水平。结果显示，相较于野生型小鼠，8月龄5xFAD小鼠的皮层组织中上述5个基因的表达均显著下调。随后，我们进一步探究了这5个基因在不同Braak分期的AD样本中，与β分泌酶活性及Aβ42水平的相关性。结果表明，所有5个枢纽基因的表达均与β分泌酶活性呈显著负相关；其中AP3B2与KIAA0513的表达还与Aβ42水平呈显著负相关。我们另外在2组来自血液的AD GEO数据集内，验证了这5个枢纽基因的差异表达情况，发现KIAA0513在轻度认知障碍（mild cognitive impairment, MCI）患者与AD患者中均显著上调，且可在两个数据集内有效区分MCI、AD与认知正常个体。综上，这5个全新的易感基因参与了AD的疾病进程，其中KIAA0513有望成为AD早期诊断的潜在候选生物标志物。