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A Review of Candidate Genes and Pathways in Preeclampsia: An Integrated Bioinformatical Analysis

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dc.contributor.authorMohamad, MAen_US
dc.contributor.authorManzor, NFMen_US
dc.contributor.authorZulkifli, NFen_US
dc.contributor.authorZainal, Nen_US
dc.contributor.authorHayati, Aen_US
dc.contributor.authorProf. Madya Dr. Asral Wirda Binti Ahmad Asnawien_US
dc.date.accessioned2024-05-29T02:50:54Z
dc.date.available2024-05-29T02:50:54Z
dc.date.issued2020
dc.description.abstractPreeclampsia is a pregnancy-specific disorder characterized by the presence of hypertension with the onset of either proteinuria, maternal organ or uteroplacental dysfunction. Preeclampsia is one of the leading causes of maternal and fetal mortality and morbidity worldwide. However, the etiopathologies of preeclampsia are not fully understood. Many studies have indicated that genes are differentially expressed between normal and in the disease state. Hence, this study systematically searched the literature on human gene expression that was differentially expressed in preeclampsia. An electronic search was performed through 2019 through PubMed, Scopus, Ovid-Medline, and Gene Expression Omnibus where the following MeSH (Medical Subject Heading) terms were used and they had been specified as the primary focus of the articles: Gene, placenta, preeclampsia, and pregnancy in the title or abstract. We also found additional MeSH terms through Cochrane Library: Transcript, sequencing, and profiling. From 687 studies retrieved from the search, only original publications that had performed high throughput sequencing of human placental tissues that reported on differentially expressed genes in pregnancies with preeclampsia were included. Two reviewers independently scrutinized the titles and abstracts before examining the eligibility of studies that met the inclusion criteria. For each study, study design, sample size, sampling type, and method for gene analysis and gene were identified. The genes listed were further analyzed with the DAVID, STRING and Cytoscape MCODE. Three original research articles involving preeclampsia comprising the datasets in gene expression were included. By combining three studies together, 250 differentially expressed genes were produced at a significance setting of p < 0.05. We identified candidate genes: LEP, NRIP1, SASH1, and ZADHHC8P1. Through GO analysis, we found extracellular matrix organization as the highly significant enriched ontology in a group of upregulated genes and immune process in downregulated genes. Studies on a genetic level have the potential to provide new insights into the regulation and to widen the basis for identification of changes in the mechanism of preeclampsia. Integrated bioinformatics could identify differentially expressed genes which could be candidate genes and potential pathways in preeclampsia that may improve our understanding of the cause and underlying molecular mechanisms that could be used as potential biomarkers for risk stratification and treatment.en_US
dc.identifier.citationAliff, Muhammad & Mohd Manzor, Fariha & Zulkifli, Noor & Zainal, Nur Zaireena & Hayati, Abd & Asnawi, Asral. (2020). A Review of Candidate Genes and Pathways in Preeclampsia–An Integrated Bioinformatical Analysis. Biology. 9. 62. 10.3390/biology9040062.en_US
dc.identifier.doi10.3390/biology9040062
dc.identifier.isbn2079-7737
dc.identifier.issue4
dc.identifier.scopusWOS:000533889200004
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85083111233&doi=10.3390%2fbiology9040062&partnerID=40&md5=f971d9262c0722b33743009ea51b4312
dc.identifier.urihttps://www.mdpi.com/2079-7737/9/4/62
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/11128
dc.identifier.volume9
dc.languageEnglish
dc.language.isoen_USen_US
dc.publisherMdpien_US
dc.relation.ispartofBiologyen_US
dc.subjectplacentaen_US
dc.subjectpreeclampsiaen_US
dc.subjectpregnancyen_US
dc.subjecttranscripten_US
dc.subjectsequencing and differentially expressed genesen_US
dc.titleA Review of Candidate Genes and Pathways in Preeclampsia: An Integrated Bioinformatical Analysisen_US
dc.typeArticleen_US
dspace.entity.typePublication

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