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vol.24 issue1RITA LEVI-MONTALCINI, 30 YEARS OF HER NOBEL PRIZECOMPETENCES IN LEGAL MEDICINE TO RECENTLY GRADUATED DOCTORS: EXPERT OPINIONS author indexsubject indexarticles search
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Revista Med

Print version ISSN 0121-5256

Abstract

CEBALLOS-NUNEZ, VERÓNIKA et al. STRUCTURAL AND FUNCTIONAL CHARACTERIZATION OF GENES ASSOCIATED WITH PREECLAMPSIA EXPRESSED IN HUMAN PLACENTA. rev.fac.med [online]. 2016, vol.24, n.1, pp.21-32. ISSN 0121-5256.  http://dx.doi.org/10.18359/rmed.2329.

Introduction: Preeclampsia still is the main cause of perinatal morbi-mortality; due to the advance in the application of the omics sciences the knowledge about its molecular etiology has increased in the last years, this has led to the identification of candidate genes, which would be involved in its pathogenesis. Objective: To identify those genes, expressed in placenta that are associated with preeclampsia and compare their structural and functional characteristics. Methods: From a literature review, 16 genes were found, whose expression in placenta was associated to the pathology. Data mining was performed including the following genomic variables: number of genes, genomic size, coding exon count, CpG islands and repeat elements in a 100Kbp window. For the Bioinformatics analysis, we used different resources of the NCBI (www.ncbi.nlm.nih.gov) and the UCSC Genome Browser (http://genome.ucsc.edu/). Furthermore, the portal BioGPS (http://biogps.gnf.org/#goto=welcome) Was used to determine the expression levels of each gene per tissue. Results: Significant differences were found for the non-coding elements of the chromatin in that associated genes, in comparison with controls (Kruskall-Wallis test, P= 0.0341824). The genes LEP, EBI3, PROCR, FSTL3, HEXB, INHBA and ENG were the ones with the highest z- score values in preeclampsic placenta. Conclusion: The application of computational tools has become a powerful instrument for the integrated analysis of gene expression and its role in the pathogenesis of PE. This would lead to an early detection of affected women.

Keywords : Preeclampsia; Gene expression; Expression profiles; Meta-analysis; Data mining; Bioinformatics; Chromatin.

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