Dataset Information

Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease.

ABSTRACT:

Background

The etiology of Alzheimer's disease remains poorly understood at the mechanistic level, and genome-wide network-based genetics have the potential to provide new insights into the disease mechanisms.

Objective

The study aimed to explore the collective effects of multiple genetic association signals on an AV-45 PET measure, which is a well-known Alzheimer's disease biomarker, by employing a network assisted strategy.

Methods

First, we took advantage of a dense module search algorithm to identify modules enriched by genetic association signals in a protein-protein interaction network. Next, we performed statistical evaluation to the modules identified by dense module search, including a normalization process to adjust the topological bias in the network, a replication test to ensure the modules were not found randomly , and a permutation test to evaluate unbiased associations between the modules and amyloid imaging phenotype. Finally, topological analysis, module similarity tests and functional enrichment analysis were performed for the identified modules.

Results

We identified 24 consensus modules enriched by robust genetic signals in a genome-wide association analysis. The results not only validated several previously reported AD genes (APOE, APP, TOMM40, DDAH1, PARK2, ATP5C1, PVRL2, ELAVL1, ACTN1 and NRF1), but also nominated a few novel genes (ABL1, ABLIM2) that have not been studied in Alzheimer's disease but have shown associations with other neurodegenerative diseases.

Conclusion

The identified genes, consensus modules and enriched pathways may provide important clues to future research on the neurobiology of Alzheimer's disease and suggest potential therapeutic targets.

SUBMITTER: Li J

PROVIDER: S-EPMC8407042 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

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Publications

Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease.

Li Jin J Chen Feng F Zhang Qiushi Q Meng Xianglian X Yao Xiaohui X Risacher Shannon L SL Yan Jingwen J Saykin Andrew J AJ Liang Hong H Shen Li L

Current Alzheimer research 20190101 13

<h4>Background</h4>The etiology of Alzheimer's disease remains poorly understood at the mechanistic level, and genome-wide network-based genetics have the potential to provide new insights into the disease mechanisms.<h4>Objective</h4>The study aimed to explore the collective effects of multiple genetic association signals on an AV-45 PET measure, which is a well-known Alzheimer's disease biomarker, by employing a network assisted strategy.<h4>Methods</h4>First, we took advantage of a dense modu ...[more]

PMID: 31755389

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Project description:BackgroundUnderstanding gene regulation is important but difficult. Elucidating tissue-specific gene regulation mechanism is even more challenging and requires gene co-expression network assembled from protein-protein interaction, transcription factor and gene binding, and post-transcriptional regulation (e.g., miRNA targeting) information. The miRNA binding affinity could therefore be changed by SNP(s) located at the 3' untranslated regions (3'UTR) of the target messenger RNA (mRNA) which miRNA(s) interacts with. Genome-wide association study (GWAS) has reported significant numbers of loci hosting SNPs associated with many traits. The goal of this study is to pinpoint GWAS functional variants located in 3'UTRs and elucidate if the genes harboring these variants along with their targeting miRNAs are associated with genetic traits relevant to certain tissues.MethodsBy applying MIGWAS, CoCoNet, ANNOVAR, and DAVID bioinformatics software and utilizing the gene expression database (e.g. GTEx data) to study GWAS summary statistics for 43 traits from 28 GWAS studies, we have identified a list of miRNAs and targeted genes harboring 3'UTR variants, which could contribute to trait-relevant tissue over miRNA-target gene network.ResultsOur result demonstrated that strong association between traits and tissues exists, and in particular, the Primary Biliary Cirrhosis (PBC) trait has the most significant p-value for all 180 tissues among all 43 traits used for this study. We reported SNPs located in 3'UTR regions of genes (SFMBT2, ZC3HAV1, and UGT3A1) targeted by miRNAs for PBC trait and its tissue association network. After employing Gene Ontology (GO) analysis for PBC trait, we have also identified a very important miRNA targeted gene over miRNA-target gene network, PFKL, which encodes the liver subunit of an enzyme.ConclusionsThe non-coding variants identified from GWAS studies are casually assumed to be not critical to translated protein product. However, 3' untranslated regions (3'UTRs) of genes harbor variants can often change the binding affinity of targeting miRNAs playing important roles in protein translation degree. Our study has shown that GWAS variants could play important roles on miRNA-target gene networks by contributing the association between traits and tissues. Our analysis expands our knowledge on trait-relevant tissue network and paves way for future human disease studies.

Dataset Information

Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease.

Background

Objective

Methods

Results

Conclusion

Publications

Genome-wide Network-assisted Association and Enrichment Study of Amyloid Imaging Phenotype in Alzheimer's Disease.

Similar Datasets

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