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Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis

The genetic predisposition to chronic kidney disease (CKD) has been widely evaluated especially using the genome-wide association studies, which highlighted some novel genetic susceptibility variants in many genes, and estimated glomerular filtration rate to diagnose and stage CKD. Of these variants...

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Autores principales: Wang, Ermin, Zhao, Hainan, Zhao, Deyan, Li, Lijing, Du, Limin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6287114/
https://www.ncbi.nlm.nih.gov/pubmed/30559760
http://dx.doi.org/10.3389/fgene.2018.00573
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author Wang, Ermin
Zhao, Hainan
Zhao, Deyan
Li, Lijing
Du, Limin
author_facet Wang, Ermin
Zhao, Hainan
Zhao, Deyan
Li, Lijing
Du, Limin
author_sort Wang, Ermin
collection PubMed
description The genetic predisposition to chronic kidney disease (CKD) has been widely evaluated especially using the genome-wide association studies, which highlighted some novel genetic susceptibility variants in many genes, and estimated glomerular filtration rate to diagnose and stage CKD. Of these variants, rs7805747 in PRKAG2 was identified to be significantly associated with both serum creatinine and CKD with genome wide significance level. Until now, the potential mechanism by which rs7805747 affects CKD risk is still unclear. Here, we performed a functional analysis of rs7805747 variant using multiple bioinformatics software and databases. Using RegulomeDB and HaploReg (version 4.1), rs7805747 was predicated to locate in enhancer histone marks (Liver, Duodenum Mucosa, Fetal Intestine Large, Fetal Intestine Small, and Right Ventricle tissues). Using GWAS analysis in PhenoScanner, we showed that rs7805747 is not only associated with CKD, but also is significantly associated with other diseases or phenotypes. Using metabolite analysis in PhenoScanner, rs7805747 is identified to be significantly associated with not only the serum creatinine, but also with other 16 metabolites. Using eQTL analysis in PhenoScanner, rs7805747 is identified to be significantly associated with gene expression in multiple human tissues and multiple genes including PRKAG2. The gene expression analysis of PRKAG2 using 53 tissues from GTEx RNA-Seq of 8555 samples (570 donors) in GTEx showed that PRKAG2 had the highest median expression in Heart-Atrial Appendage. Using the gene expression profiles in human CKD, we further identified different expression of PRKAG2 gene in CKD cases compared with control samples. In summary, our findings provide new insight into the underlying susceptibility of PRKAG2 gene to CKD.
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spelling pubmed-62871142018-12-17 Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis Wang, Ermin Zhao, Hainan Zhao, Deyan Li, Lijing Du, Limin Front Genet Genetics The genetic predisposition to chronic kidney disease (CKD) has been widely evaluated especially using the genome-wide association studies, which highlighted some novel genetic susceptibility variants in many genes, and estimated glomerular filtration rate to diagnose and stage CKD. Of these variants, rs7805747 in PRKAG2 was identified to be significantly associated with both serum creatinine and CKD with genome wide significance level. Until now, the potential mechanism by which rs7805747 affects CKD risk is still unclear. Here, we performed a functional analysis of rs7805747 variant using multiple bioinformatics software and databases. Using RegulomeDB and HaploReg (version 4.1), rs7805747 was predicated to locate in enhancer histone marks (Liver, Duodenum Mucosa, Fetal Intestine Large, Fetal Intestine Small, and Right Ventricle tissues). Using GWAS analysis in PhenoScanner, we showed that rs7805747 is not only associated with CKD, but also is significantly associated with other diseases or phenotypes. Using metabolite analysis in PhenoScanner, rs7805747 is identified to be significantly associated with not only the serum creatinine, but also with other 16 metabolites. Using eQTL analysis in PhenoScanner, rs7805747 is identified to be significantly associated with gene expression in multiple human tissues and multiple genes including PRKAG2. The gene expression analysis of PRKAG2 using 53 tissues from GTEx RNA-Seq of 8555 samples (570 donors) in GTEx showed that PRKAG2 had the highest median expression in Heart-Atrial Appendage. Using the gene expression profiles in human CKD, we further identified different expression of PRKAG2 gene in CKD cases compared with control samples. In summary, our findings provide new insight into the underlying susceptibility of PRKAG2 gene to CKD. Frontiers Media S.A. 2018-12-03 /pmc/articles/PMC6287114/ /pubmed/30559760 http://dx.doi.org/10.3389/fgene.2018.00573 Text en Copyright © 2018 Wang, Zhao, Zhao, Li and Du. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Genetics
Wang, Ermin
Zhao, Hainan
Zhao, Deyan
Li, Lijing
Du, Limin
Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis
title Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis
title_full Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis
title_fullStr Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis
title_full_unstemmed Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis
title_short Functional Prediction of Chronic Kidney Disease Susceptibility Gene PRKAG2 by Comprehensively Bioinformatics Analysis
title_sort functional prediction of chronic kidney disease susceptibility gene prkag2 by comprehensively bioinformatics analysis
topic Genetics
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6287114/
https://www.ncbi.nlm.nih.gov/pubmed/30559760
http://dx.doi.org/10.3389/fgene.2018.00573
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