Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach
Kawasaki disease (KD) is an inflammatory condition in children, which has unknown etiology with an insufficiently described genetic mechanism. There is no accurate molecular diagnostic test for KD, but some genetic factors have been proposed in previous studies. In this study, we investigated the un...
Main Authors: | , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2020-01-01
|
Series: | Informatics in Medicine Unlocked |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2352914820305736 |
id |
doaj-97062d877ce1409bac3f24fd5745fb71 |
---|---|
record_format |
Article |
spelling |
doaj-97062d877ce1409bac3f24fd5745fb712020-11-25T03:53:44ZengElsevierInformatics in Medicine Unlocked2352-91482020-01-0120100423Gene expression analysis in Kawasaki disease; bioinformatics and experimental approachYazdan Rahmati0Hasan Mollanoori1Naser Kakavandi2Alireza Nateghian3Shirin Sayyahfar4Vahid Babaei5Sajad Esmaeili6Shahram Teimourian7Department of Medical Genetics, Iran University of Medical Sciences (IUMS), Tehran, IranDepartment of Medical Genetics, Iran University of Medical Sciences (IUMS), Tehran, IranBiochemistry Department, Iran University of Medical Sciences, Tehran, IranDepartment of Pediatrics, Ali Asghar Children Hospital, Tehran, IranDepartment of Pediatrics, Ali Asghar Children Hospital, Tehran, IranDepartment of Medical Genetics, Iran University of Medical Sciences (IUMS), Tehran, IranMedical Biology Research Center, Health Technology Institute, Kermanshah University of Medical Sciences, Kermanshah, IranDepartment of Medical Genetics, Iran University of Medical Sciences (IUMS), Tehran, Iran; Corresponding author. Department of Medical Genetics, Iran University of Medical Sciences, Crossroads of Shahid Hemmat & Shahid Chamran Highways, P.O. Box: 15875-6171, Tehran, 1449614535, Iran.Kawasaki disease (KD) is an inflammatory condition in children, which has unknown etiology with an insufficiently described genetic mechanism. There is no accurate molecular diagnostic test for KD, but some genetic factors have been proposed in previous studies. In this study, we investigated the underlying molecular alterations based on both in silico and wet lab analysis to candidate transcriptional biosignature and biomarker. metaQC, metaDE, and metapath packages have been used in the bioinformatic analysis for the assessment of quality control, investigation of differentially expressed genes, and enrichment of detected genes, respectively. In the next step, miRNA array was analyzed by biobase, GEOquery, and limma packages. All bioinformatic studies were conducted with the R software platform. Finally, Real-Time PCR was performed on patient samples for the evaluation of the bioinformatic results. The results of bioinformatic analysis led to the introduction of 28 genes with the highest difference in gene expression, and 14 miRNAs with the highest difference in expression after microRNA array analysis. Real-time PCR results validated candidate genes and miRNAs as KD transcriptional biosignatures and biomarkers, respectively. Our studies have shown MyD88, KREMEN1, TLR5, ALPK1, IRAK4, PFKFB3, HK3, CREB, CR1, SLC2A14, and FPR1 as the most important genes involved in KD. Also, hsa-miR-575, hsa-miR-483-5p, hsa-miR-4271, hsa-miR-4327 as the most likely miRNAs to interfere with KD. The altered expression levels of the aforementioned genes and miRNAs can be studied further for therapeutic targets.http://www.sciencedirect.com/science/article/pii/S2352914820305736Kawasaki diseaseMolecular mechanismBioinformatic analysisReal-time PCR |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yazdan Rahmati Hasan Mollanoori Naser Kakavandi Alireza Nateghian Shirin Sayyahfar Vahid Babaei Sajad Esmaeili Shahram Teimourian |
spellingShingle |
Yazdan Rahmati Hasan Mollanoori Naser Kakavandi Alireza Nateghian Shirin Sayyahfar Vahid Babaei Sajad Esmaeili Shahram Teimourian Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach Informatics in Medicine Unlocked Kawasaki disease Molecular mechanism Bioinformatic analysis Real-time PCR |
author_facet |
Yazdan Rahmati Hasan Mollanoori Naser Kakavandi Alireza Nateghian Shirin Sayyahfar Vahid Babaei Sajad Esmaeili Shahram Teimourian |
author_sort |
Yazdan Rahmati |
title |
Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach |
title_short |
Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach |
title_full |
Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach |
title_fullStr |
Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach |
title_full_unstemmed |
Gene expression analysis in Kawasaki disease; bioinformatics and experimental approach |
title_sort |
gene expression analysis in kawasaki disease; bioinformatics and experimental approach |
publisher |
Elsevier |
series |
Informatics in Medicine Unlocked |
issn |
2352-9148 |
publishDate |
2020-01-01 |
description |
Kawasaki disease (KD) is an inflammatory condition in children, which has unknown etiology with an insufficiently described genetic mechanism. There is no accurate molecular diagnostic test for KD, but some genetic factors have been proposed in previous studies. In this study, we investigated the underlying molecular alterations based on both in silico and wet lab analysis to candidate transcriptional biosignature and biomarker. metaQC, metaDE, and metapath packages have been used in the bioinformatic analysis for the assessment of quality control, investigation of differentially expressed genes, and enrichment of detected genes, respectively. In the next step, miRNA array was analyzed by biobase, GEOquery, and limma packages. All bioinformatic studies were conducted with the R software platform. Finally, Real-Time PCR was performed on patient samples for the evaluation of the bioinformatic results. The results of bioinformatic analysis led to the introduction of 28 genes with the highest difference in gene expression, and 14 miRNAs with the highest difference in expression after microRNA array analysis. Real-time PCR results validated candidate genes and miRNAs as KD transcriptional biosignatures and biomarkers, respectively. Our studies have shown MyD88, KREMEN1, TLR5, ALPK1, IRAK4, PFKFB3, HK3, CREB, CR1, SLC2A14, and FPR1 as the most important genes involved in KD. Also, hsa-miR-575, hsa-miR-483-5p, hsa-miR-4271, hsa-miR-4327 as the most likely miRNAs to interfere with KD. The altered expression levels of the aforementioned genes and miRNAs can be studied further for therapeutic targets. |
topic |
Kawasaki disease Molecular mechanism Bioinformatic analysis Real-time PCR |
url |
http://www.sciencedirect.com/science/article/pii/S2352914820305736 |
work_keys_str_mv |
AT yazdanrahmati geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT hasanmollanoori geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT naserkakavandi geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT alirezanateghian geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT shirinsayyahfar geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT vahidbabaei geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT sajadesmaeili geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach AT shahramteimourian geneexpressionanalysisinkawasakidiseasebioinformaticsandexperimentalapproach |
_version_ |
1724476916476411904 |