A systematic integrated analysis of brain expression profiles reveals <i>YAP1</i> and other prioritized hub genes as important upstream regulators in Alzheimer's disease

Xu, Min; Df, Zhang; Luo, Rongcan; Wu, Yong; Zhou, Hejiang; Kong, Lili; Bi, Rui; Yao, Yong‐Gang

doi:10.1016/j.jalz.2017.08.012

Cited by 199 publications

(216 citation statements)

References 86 publications

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“…ADRA1A has been implicated in gene-gene interaction analysis for LOAD 61 . Its protein product physically interacts with amyloid precursor protein (APP) 60 and an α1-adrenoceptor antagonist has been shown to prevent memory deficits in APP23 transgenic mice 62 . EXTL3 encodes a putative membrane receptor for regenerating islet-derived 1α (Reg-1α), whose overexpression and involvement in the early stages of Alzheimer's disease has been reported 63 .…”

Section: Utmost Identifies Novel Risk Genes For Alzheimer's Diseasementioning

confidence: 99%

A statistical framework for cross-tissue transcriptome-wide association analysis

et al. 2018

Preprint

154

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Transcriptome-wide association analysis is a powerful approach to studying the genetic architecture of complex traits. A key component of this approach is to build a model to impute gene expression levels from genotypes using samples with matched genotypes and gene expression data in a given tissue. However, it is challenging to develop robust and accurate imputation models with a limited sample size for any single tissue. Here, we first introduce a multi-task learning method to jointly impute gene expression in 44 human tissues. Compared with single-tissue methods, our approach achieved an average 39% improvement in imputation accuracy and generated effective imputation models for an average 120% more genes. We then describe a summary statistic-based testing framework that combines multiple single-tissue associations into a powerful metric to quantify the overall gene-trait association. We applied our method, called UTMOST, to multiple genome wide association results and demonstrate its advantages over single-tissue strategies.

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Section: Utmost Identifies Novel Risk Genes For Alzheimer's Diseasementioning

confidence: 99%

A statistical framework for cross-tissue transcriptome-wide association analysis

et al. 2018

Preprint

154

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“…Data-mining of mRNA expression in AD patients The expression level of the COX-related genes in AD was retrieved from the AlzData database (www.alzdata.org) [73], in which we have integrated and normalized the original microarray data of 684 AD brain tissues and 562 control tissues from Gene Expression Omnibus (GEO: http://www.ncbi.nlm.nih.gov/sites/GDSbrowser) [19,[74][75][76][77][78][79][80][81][82][83][84][85][86]. We used the stage I data as defined in Xu et al [73] that contains expression data of 269 AD brain tissues and 271 control brain tissues from four brain regions (entorhinal cortex, hippocampus, temporal cortex, and frontal cortex) to investigate the alteration of mRNA levels of the COX-related genes in AD, by using a two-tailed Student's t-test with the GraphPad Prism software (GraphPad Software, La Jolla, CA, USA). The expression levels of the COX-related genes were further investigated in the stage II data as defined in Xu et al [73], which contained the microarray data of 415 AD brain tissues and 291 control tissues from temporal cortex and frontal cortex.…”

Section: Subjectsmentioning

confidence: 99%

“…We used the stage I data as defined in Xu et al [73] that contains expression data of 269 AD brain tissues and 271 control brain tissues from four brain regions (entorhinal cortex, hippocampus, temporal cortex, and frontal cortex) to investigate the alteration of mRNA levels of the COX-related genes in AD, by using a two-tailed Student's t-test with the GraphPad Prism software (GraphPad Software, La Jolla, CA, USA). The expression levels of the COX-related genes were further investigated in the stage II data as defined in Xu et al [73], which contained the microarray data of 415 AD brain tissues and 291 control tissues from temporal cortex and frontal cortex.…”

Section: Subjectsmentioning

confidence: 99%

Genetic association of the cytochrome c oxidase-related genes with Alzheimer’s disease in Han Chinese

Zhang

et al. 2018

Neuropsychopharmacol

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Alzheimer's disease (AD) is the most common cause of dementia. Mitochondrial dysfunction has been widely reported in AD due to its important role in cellular metabolism and energy production. Complex IV (cytochrome c oxidase, COX) of mitochondrial electron transport chain, is particularly vulnerable in AD. Defects of COX in AD have been well documented, but there is little evidence to support the genetic association of the COX-related genes with AD. In this study, we investigated the genetic association between 17 nuclear-encoded COX-related genes and AD in 1572 Han Chinese. The whole exons of these genes were also screened in 107 unrelated AD patients with a high probability of hereditarily transmitted AD. Variants in COX6B1, NDUFA4, SURF1, and COX10 were identified to be associated with AD. An integrative analysis with data of eQTL, expression and pathology revealed that most of the COX-related genes were significantly downregulated in AD patients and mouse models, and the AD-associated variants in COX6B1, SURF1, and COX10 were linked to altered mRNA levels in brain tissues. Furthermore, mRNA levels of Ndufa4, Cox5a, Cox10, Cox6b2, Cox7a2, and Lrpprc were significantly correlated with Aβ plaque burden in hippocampus of AD mice. Convergent functional genomics analysis revealed strong supportive evidence for the roles of COX6B1, COX10, NDUFA4, and SURF1 in AD. As the result of our comprehensive analysis of the COX-related genes at the genetic, expression, and pathology levels, we have been able to provide a systematic view for understanding the relationships of the COX-related genes in the pathology of AD.

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“…We used AlzData to obtain gene expression levels in publicly available data sets (76). AlzData is a database storing statistical meta-analysis results using 78 samples…”

Section: Validation Of Rac1 Expression Changes Using Independent Datamentioning

confidence: 99%

Disruption of aRAC1-centred protein interaction network is associated with Alzheimer’s disease pathology and causes age-dependent neurodegeneration

Kikuchi

Sekiya

Hara

et al. 2019

Preprint

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The molecular biological mechanisms of Alzheimer's disease (AD) involve disease-associated cross-talk through many genes and include a loss of normal as well as a gain of abnormal interactions among genes. A protein domain network (PDN) is a collection of physical bindings that occur between protein domains, and the states of the PDNs in patients with AD are likely to be perturbed compared to those in normal healthy individuals. To identify PDN changes that cause neurodegeneration, we analysed the PDNs that occur among genes co-expressed in each of three brain regions at each stage of AD. Our analysis revealed that the PDNs collapsed with the progression of AD stage and identified five hub genes, including Rac1, as key players in PDN collapse. Using publicly available gene expression data, we confirmed that the mRNA expression level of the RAC1 gene was downregulated in the entorhinal cortex (EC) of AD brains. To test the causality of these changes in neurodegeneration, we utilizedDrosophila as a genetic model and found that modest knockdown of Rac1 in neurons was sufficient to cause age-dependent behavioural deficits and neurodegeneration.Finally, we identified a microRNA, hsa-miR-101-3p, as a potential regulator of RAC1 in AD brains. As the Braak neurofibrillary tangle (NFT) stage progressed, the expression levels of hsa-miR-101-3p were upregulated specifically in the EC. Furthermore, overexpression of hsa-miR-101-3p in the human neuronal cell line SH-SY5Y caused RAC1 downregulation. These results highlight the utility of our integrated network approach for identifying causal changes leading to neurodegeneration in AD.

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A systematic integrated analysis of brain expression profiles reveals YAP1 and other prioritized hub genes as important upstream regulators in Alzheimer's disease

Abstract: Early expression disturbance of hub genes is an important feature of AD development, and interfering with this process may reverse the disease progression.

Cited by 199 publications

References 86 publications

A statistical framework for cross-tissue transcriptome-wide association analysis

A statistical framework for cross-tissue transcriptome-wide association analysis

Genetic association of the cytochrome c oxidase-related genes with Alzheimer’s disease in Han Chinese

Disruption of aRAC1-centred protein interaction network is associated with Alzheimer’s disease pathology and causes age-dependent neurodegeneration

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