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Genetics of non-syndromic childhood obesity and the use of high-throughput DNA sequencing technologies

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dc.creatorda Fonseca, Ana Carolina Proençaspa
dc.creatorMastronardi, Claudiospa
dc.creatorJohar, Angadspa
dc.creatorArcos-Burgos, Mauriciospa
dc.creatorPaz-Filho, Gilbertospa
dc.date.accessioned2020-05-25T23:56:06Z
dc.date.available2020-05-25T23:56:06Z
dc.date.created2017spa
dc.description.abstractBackground Childhood obesity is a serious public health problem associated with the development of several chronic diseases, such as type 2 diabetes mellitus, dyslipidemia, and hypertension. The elevated prevalence of obesity is mostly due to inadequate diet and lifestyle, but it is also influenced by genetic factors. Objectives To review recent advances in the field of the genetics of obesity. We summarize the list of genes associated with the rare non-syndromic forms of obesity, and explain their function. Furthermore, we discuss the technologies that are available for the genetic diagnosis of obesity. Results Several studies reported that single gene variants cause Mendelian forms of obesity, determined by mutations of major effect in single genes. Rare, non-syndromic forms of obesity are a result of loss-of-function mutations in genes that act on the development and function of the hypothalamus or the leptin-melanocortin pathway. These variants disrupt enzymes and receptors that play a role in energy homeostasis, resulting in severe early-onset obesity and endocrine dysfunctions. Different approaches and technologies have been used to understand the genetic background of obesity. Currently, whole genome and whole exome sequencing are important diagnostic tools to identify new genes and variants associated with severe obesity, but other approaches are also useful at individual or population levels, such as linkage analysis, candidate gene sequencing, chromosomal microarray analysis, and genome-wide association studies. Conclusions The understanding of the genetic causes of obesity and the usefulness and limitations of the genetic diagnostic approaches can contribute to the development of new personalized therapeutic targets against obesity. © 2017 The Authorseng
dc.format.mimetypeapplication/pdf
dc.identifier.doihttps://doi.org/10.1016/j.jdiacomp.2017.04.026
dc.identifier.issn10568727
dc.identifier.urihttps://repository.urosario.edu.co/handle/10336/22326
dc.language.isoengspa
dc.publisherElsevier Inc.spa
dc.relation.citationEndPage1561
dc.relation.citationIssueNo. 10
dc.relation.citationStartPage1549
dc.relation.citationTitleJournal of Diabetes and its Complications
dc.relation.citationVolumeVol. 31
dc.relation.ispartofJournal of Diabetes and its Complications, ISSN:10568727, Vol.31, No.10 (2017); pp. 1549-1561spa
dc.relation.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85025434567&doi=10.1016%2fj.jdiacomp.2017.04.026&partnerID=40&md5=4f47bda80985c8af26aab1e5f82eaf24spa
dc.rights.accesRightsinfo:eu-repo/semantics/openAccess
dc.rights.accesoAbierto (Texto Completo)spa
dc.source.instnameinstname:Universidad del Rosariospa
dc.source.reponamereponame:Repositorio Institucional EdocURspa
dc.subject.keywordLeptinspa
dc.subject.keywordMelanocortinspa
dc.subject.keywordDnaspa
dc.subject.keywordAppetitespa
dc.subject.keywordBrain developmentspa
dc.subject.keywordChildhood obesityspa
dc.subject.keywordChromosome analysisspa
dc.subject.keywordDisease severityspa
dc.subject.keywordDna sequencespa
dc.subject.keywordEndocrine diseasespa
dc.subject.keywordGene mutationspa
dc.subject.keywordGene sequencespa
dc.subject.keywordGenetic analysisspa
dc.subject.keywordGenetic associationspa
dc.subject.keywordGenetic backgroundspa
dc.subject.keywordGenetic screeningspa
dc.subject.keywordGenetic variabilityspa
dc.subject.keywordGenome analysisspa
dc.subject.keywordGenome-wide association studyspa
dc.subject.keywordHeredityspa
dc.subject.keywordHigh throughput sequencingspa
dc.subject.keywordHumanspa
dc.subject.keywordHypothalamusspa
dc.subject.keywordLinkage analysisspa
dc.subject.keywordLoss of function mutationspa
dc.subject.keywordMedical decision makingspa
dc.subject.keywordMeta analysis (topic)spa
dc.subject.keywordMicroarray analysisspa
dc.subject.keywordMonogenic disorderspa
dc.subject.keywordNext generation sequencingspa
dc.subject.keywordNonhumanspa
dc.subject.keywordObesityspa
dc.subject.keywordPriority journalspa
dc.subject.keywordRare variant association testspa
dc.subject.keywordReviewspa
dc.subject.keywordSignal transductionspa
dc.subject.keywordWhole exome sequencingspa
dc.subject.keywordBiological modelspa
dc.subject.keywordChemistryspa
dc.subject.keywordChildspa
dc.subject.keywordChildhood obesityspa
dc.subject.keywordGenetic association studyspa
dc.subject.keywordGenetic linkagespa
dc.subject.keywordGenetic polymorphismspa
dc.subject.keywordGenetic predispositionspa
dc.subject.keywordGeneticsspa
dc.subject.keywordMetabolismspa
dc.subject.keywordMutationspa
dc.subject.keywordProceduresspa
dc.subject.keywordTrendsspa
dc.subject.keywordChildspa
dc.subject.keywordDnaspa
dc.subject.keywordGenetic association studiesspa
dc.subject.keywordGenetic linkagespa
dc.subject.keywordGenetic predisposition to diseasespa
dc.subject.keywordGenetic testingspa
dc.subject.keywordGenome-wide association studyspa
dc.subject.keywordHigh-throughput nucleotide sequencingspa
dc.subject.keywordHumansspa
dc.subject.keywordModelseng
dc.subject.keywordMutationspa
dc.subject.keywordPediatric obesityspa
dc.subject.keywordPolymorphismeng
dc.subject.keywordDna sequencingspa
dc.subject.keywordGenespa
dc.subject.keywordGeneticsspa
dc.subject.keywordLeptinspa
dc.subject.keywordMelanocortinspa
dc.subject.keywordObesityspa
dc.titleGenetics of non-syndromic childhood obesity and the use of high-throughput DNA sequencing technologiesspa
dc.typearticleeng
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersion
dc.type.spaArtículospa
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