Identification of a novel distal regulatory element of the human<i>Neuroglobin</i>gene by the chromosome conformation capture approach

Tam, Kin Tung; Chan, Pui-Kwong; Zhang, Wei; P, Law; Tian, Zhipeng; Chan, Godfrey Chi Fung; Philipsen, Sjaak; Festenstein, Richard; Tan-Un, KC

doi:10.1093/nar/gkw820

Cited by 21 publications

(11 citation statements)

References 68 publications

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“…High expression of GATA2 is observed in Dopamine Cells and Brain Regions of a PD patient [73]. The knockdown of GATA2 was found to be involved in reduced expression of neuroglobin as evident in a laboratory experiment [74].…”

Section: Discussionmentioning

confidence: 85%

Identification of Common Molecular Signatures Shared between Alzheimer’s and Parkinson’s Diseases and Therapeutic Agents Exploration: An Integrated Genomics Approach

Faruqui

Prium

Mowna

et al. 2021

Preprint

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Alzheimer’s disease (AD) and Parkinson’s disease (PD) are two most prevalent age-related dementias that severely affect a large number of elderly people around the globe. Poor understanding of pathogenesis of these neurological diseases imposes challenge to discover therapeutic measures and effective diagnosis methods. In this study, a network-based approach was utilized to identify potential common molecular signatures and therapeutic agents for AD and PD. Protein-protein interaction analysis revealed NCK1, UBC, CDH1, CDC20, ACTB, PSMA7, PRPF8, RPL7, XRCC6 and HSP90AB1 as the best proteome signatures. Different regulatory transcriptional signatures i.e., YY1, NFKB1, BRCA1, TP53, GATA2, SREBF2, E2F1, FOXC1, RELA and NFIC and post-transcriptional signatures i.e., hsa-mir-186-5p, hsamir-92a-3p, hsa-mir-615-3p, hsa-let-7c-5p, hsa-mir-100-5p, hsa-mir-93-3p, hsa-mir-5681a, hsamir-484, hsa-mir-193b-3p and hsa-mir-16p-5p were identified from other interaction network. Drug-gene interaction study revealed possible therapeutic agents which may reverse the AD and PD condition. The scientific approach of this study should contribute to identify potential biomarkers, drug targets and therapeutic agents against AD and PD which should in turn advance the present efforts of scientists to secure effective diagnosis and therapeutic options. However, further in vivo and in vitro experiments might be required to validate the outcomes of this study.

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Section: Discussionmentioning

confidence: 85%

Identification of Common Molecular Signatures Shared between Alzheimer’s and Parkinson’s Diseases and Therapeutic Agents Exploration: An Integrated Genomics Approach

Faruqui

Prium

Mowna

et al. 2021

Preprint

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“…viruses (HSV), a virus found to be a risk factor for AD [25, 26]. GATA-2 activates transcription of Neuroglobin, which is implicated to reduce AD severity [27]. There is still a controversy about the effect of TOMM40 on AD, but TOMM40, as a mitochondrial transmembrane protein, is believed to be a risk gene in mitochondrial dysfunction in AD [28–30].…”

Section: Resultsmentioning

confidence: 99%

VariFunNet, an integrated multiscale modeling framework to study the effects of rare non-coding variants in genome-wide association studies: Applied to Alzheimer's disease

Chen

Gao

et al. 2017

2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

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It is a grand challenge to reveal the causal effects of DNA variants in complex phenotypes. Although statistical techniques can establish correlations between genotypes and phenotypes in Genome-Wide Association Studies (GWAS), they often fail when the variant is rare. The emerging Network-based Association Studies aim to address this shortcoming in statistical analysis, but are mainly applied to coding variations. Increasing evidences suggest that non-coding variants play critical roles in the etiology of complex diseases. However, few computational tools are available to study the effect of rare non-coding variants on phenotypes. Here we have developed a multiscale modeling variant-to-function-to-network framework VariFunNet to address these challenges. VariFunNet first predict the functional variations of molecular interactions, which result from the non-coding variants. Then we incorporate the genes associated with the functional variation into a tissue-specific gene network, and identify subnetworks that transmit the functional variation to molecular phenotypes. Finally, we quantify the functional implication of the subnetwork, and prioritize the association of the non-coding variants with the phenotype. We have applied VariFunNet to investigating the causal effect of rare non-coding variants on Alzheimer’s disease (AD). Among top 21 ranked causal non-coding variants, 16 of them are directly supported by existing evidences. The remaining 5 novel variants dysregulate multiple downstream biological processes, all of which are associated with the pathology of AD. Furthermore, we propose potential new drug targets that may modulate diverse pathways responsible for AD. These findings may shed new light on discovering new biomarkers and therapies for the prevention, diagnosis, and treatment of AD. Our results suggest that multiscale modeling is a potentially powerful approach to studying causal genotype-phenotype associations.

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“…For negatively expressed genes, GATA binding protein 2 is known to be an essential transcription factor for neuroglobin; GATA-2 knockdown causes significant drops in neuroglobin expression. Neuroglobin has been observed to have a protective effect on neural cells and has been implicated in reducing the severity of AD [24]. It experiences the most rewiring relative to the negative correlation networks.…”

Section: Highly Disrupted Genesmentioning

confidence: 99%

Network Medicine Approach for Analysis of Alzheimer’s Disease Gene Expression Data

Cohen

Pilozzi

Huang

2020

IJMS

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Alzheimer’s disease (AD) is the most widespread diagnosed cause of dementia in the elderly. It is a progressive neurodegenerative disease that causes memory loss as well as other detrimental symptoms that are ultimately fatal. Due to the urgent nature of this disease, and the current lack of success in treatment and prevention, it is vital that different methods and approaches are applied to its study in order to better understand its underlying mechanisms. To this end, we have conducted network-based gene co-expression analysis on data from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. By processing and filtering gene expression data taken from the blood samples of subjects with varying disease states and constructing networks based on that data to evaluate gene relationships, we have been able to learn about gene expression correlated with the disease, and we have identified several areas of potential research interest.

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Identification of a novel distal regulatory element of the humanNeuroglobingene by the chromosome conformation capture approach

Cited by 21 publications

References 68 publications

Identification of Common Molecular Signatures Shared between Alzheimer’s and Parkinson’s Diseases and Therapeutic Agents Exploration: An Integrated Genomics Approach

Identification of Common Molecular Signatures Shared between Alzheimer’s and Parkinson’s Diseases and Therapeutic Agents Exploration: An Integrated Genomics Approach

VariFunNet, an integrated multiscale modeling framework to study the effects of rare non-coding variants in genome-wide association studies: Applied to Alzheimer's disease

Network Medicine Approach for Analysis of Alzheimer’s Disease Gene Expression Data

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