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postgraduate thesis: Integrated bioinformatics analysis of genetic, expression and interaction data to understand the molecular mechanisms of Alzheimer's disease

TitleIntegrated bioinformatics analysis of genetic, expression and interaction data to understand the molecular mechanisms of Alzheimer's disease
Authors
Issue Date2014
PublisherThe University of Hong Kong (Pokfulam, Hong Kong)
Citation
Jia, Y. [賈亦真]. (2014). Integrated bioinformatics analysis of genetic, expression and interaction data to understand the molecular mechanisms of Alzheimer's disease. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5570785
AbstractThis thesis presents an integrated analysis to understand different aspects of the molecular mechanisms of Alzheimer’s disease (AD). Genetics data from genome-wide association studies (GWASs), expression data from newly developed RNA-seq technology and published microarray experiments, and interaction data from public protein database were integrated to build up networks using bioinformatics and systems biology approaches. Previous experiments have identified Pax6, a multifunctional transcription factor which plays essential roles in eye development and pancreatic β-cell function, as a new regulator involved in the cell-cycle related neuronal death model of AD. However, downstream targets of Pax6 in brain remains undiscovered and upon up-regulation of Pax6, the downstream molecular mechanisms by which neuronal death is triggered and eventually leads to AD are largely unclear. In Chapter 3, downstream network of Pax6 in AD neuronal death model was constructed by integrating expression data of AD brain, Pax6 binding sites prediction and literature search. Expression level of Pax6 significantly increased during AD progression among different brain regions, shown by microarray. 70 potential downstream targets of Pax6, including ACAD8, YWHAZ and OGT, were identified and ranked by their binding affinity. Network was constructed based on these 70 candidates. 9 KEGG pathways harboring well-defined AD-related sub-pathways were identified, among which the PI3K/PDK1/AKT sub-pathway was shown to be activated in AD brain. In Chapter 4, expression alterations after Pax6 knockdown were examined by siPax6 in mouse cortical neurons followed by RNA-seq. An analysis pipeline was built to quantify expression level, identify splicing isoforms and discover new genes/transcripts from raw RNA-seq data. 8,584 genes were identified as differentially expressed (DEGs) after Pax6 knockdown, validated preliminarily by qPCR random sampling of 10 DEGs. KEGG pathways interrupted by Pax6 knockdown were largely overlapped with AD-related pathways identified in Chapter 3. GSK3B was selected as prime candidate downstream of Pax6. Cell cycle/Pax6/GSK3β pathway provides a possible link from Aβ-mediated neuronal death to tau pathology. Chapter 3&4 both indicated the role of Pax6/GSK3β-mediated insulin signaling pathway in AD. Type 2 diabetes mellitus (T2DM), characterized by insulin resistance and interrupted insulin signaling, is a strong risk factor of AD. An integrated analysis was carried out to study the shared molecular mechanisms linking AD and T2DM. APOE, APOC1 and TOMM40 were identified as common GWAS genes. 40 pathways were enriched in both diseases, including PI3K/AKT mediated insulin signaling pathways. Stronger connections between AD and T2DM GWAS genes were detected compared with random generated genes and bone mineral density (BMD) GWAS genes. TNF, MMP3, PPARG and CLU were identified as hub-/bottleneck-genes in the connection network which might perform the most essential functions in the progression of AD for patients with T2DM. UBC (Ubiquitin C) was suggested as an important linker gene in the two disease-specific sub-networks, which provides possible explanations for the shared pathology of AD and T2DM.
DegreeDoctor of Philosophy
SubjectBioinformatics
Alzheimer's disease - Molecular aspects
Dept/ProgramBiochemistry
Persistent Identifierhttp://hdl.handle.net/10722/219981

 

DC FieldValueLanguage
dc.contributor.authorJia, Yizhen-
dc.contributor.author賈亦真-
dc.date.accessioned2015-10-08T23:12:16Z-
dc.date.available2015-10-08T23:12:16Z-
dc.date.issued2014-
dc.identifier.citationJia, Y. [賈亦真]. (2014). Integrated bioinformatics analysis of genetic, expression and interaction data to understand the molecular mechanisms of Alzheimer's disease. (Thesis). University of Hong Kong, Pokfulam, Hong Kong SAR. Retrieved from http://dx.doi.org/10.5353/th_b5570785-
dc.identifier.urihttp://hdl.handle.net/10722/219981-
dc.description.abstractThis thesis presents an integrated analysis to understand different aspects of the molecular mechanisms of Alzheimer’s disease (AD). Genetics data from genome-wide association studies (GWASs), expression data from newly developed RNA-seq technology and published microarray experiments, and interaction data from public protein database were integrated to build up networks using bioinformatics and systems biology approaches. Previous experiments have identified Pax6, a multifunctional transcription factor which plays essential roles in eye development and pancreatic β-cell function, as a new regulator involved in the cell-cycle related neuronal death model of AD. However, downstream targets of Pax6 in brain remains undiscovered and upon up-regulation of Pax6, the downstream molecular mechanisms by which neuronal death is triggered and eventually leads to AD are largely unclear. In Chapter 3, downstream network of Pax6 in AD neuronal death model was constructed by integrating expression data of AD brain, Pax6 binding sites prediction and literature search. Expression level of Pax6 significantly increased during AD progression among different brain regions, shown by microarray. 70 potential downstream targets of Pax6, including ACAD8, YWHAZ and OGT, were identified and ranked by their binding affinity. Network was constructed based on these 70 candidates. 9 KEGG pathways harboring well-defined AD-related sub-pathways were identified, among which the PI3K/PDK1/AKT sub-pathway was shown to be activated in AD brain. In Chapter 4, expression alterations after Pax6 knockdown were examined by siPax6 in mouse cortical neurons followed by RNA-seq. An analysis pipeline was built to quantify expression level, identify splicing isoforms and discover new genes/transcripts from raw RNA-seq data. 8,584 genes were identified as differentially expressed (DEGs) after Pax6 knockdown, validated preliminarily by qPCR random sampling of 10 DEGs. KEGG pathways interrupted by Pax6 knockdown were largely overlapped with AD-related pathways identified in Chapter 3. GSK3B was selected as prime candidate downstream of Pax6. Cell cycle/Pax6/GSK3β pathway provides a possible link from Aβ-mediated neuronal death to tau pathology. Chapter 3&4 both indicated the role of Pax6/GSK3β-mediated insulin signaling pathway in AD. Type 2 diabetes mellitus (T2DM), characterized by insulin resistance and interrupted insulin signaling, is a strong risk factor of AD. An integrated analysis was carried out to study the shared molecular mechanisms linking AD and T2DM. APOE, APOC1 and TOMM40 were identified as common GWAS genes. 40 pathways were enriched in both diseases, including PI3K/AKT mediated insulin signaling pathways. Stronger connections between AD and T2DM GWAS genes were detected compared with random generated genes and bone mineral density (BMD) GWAS genes. TNF, MMP3, PPARG and CLU were identified as hub-/bottleneck-genes in the connection network which might perform the most essential functions in the progression of AD for patients with T2DM. UBC (Ubiquitin C) was suggested as an important linker gene in the two disease-specific sub-networks, which provides possible explanations for the shared pathology of AD and T2DM.-
dc.languageeng-
dc.publisherThe University of Hong Kong (Pokfulam, Hong Kong)-
dc.relation.ispartofHKU Theses Online (HKUTO)-
dc.rightsCreative Commons: Attribution 3.0 Hong Kong License-
dc.rightsThe author retains all proprietary rights, (such as patent rights) and the right to use in future works.-
dc.subject.lcshBioinformatics-
dc.subject.lcshAlzheimer's disease - Molecular aspects-
dc.titleIntegrated bioinformatics analysis of genetic, expression and interaction data to understand the molecular mechanisms of Alzheimer's disease-
dc.typePG_Thesis-
dc.identifier.hkulb5570785-
dc.description.thesisnameDoctor of Philosophy-
dc.description.thesislevelDoctoral-
dc.description.thesisdisciplineBiochemistry-
dc.description.naturepublished_or_final_version-

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