Early Prediction of Asthma

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dc.catalogadorgrr
dc.contributor.authorRomero-Tapia, Sergio de Jesus
dc.contributor.authorBecerril-Negrete, Jose Raul
dc.contributor.authorCastro Rodriguez, José Antonio
dc.contributor.authorDel-Rio-Navarro, Blanca E.
dc.date.accessioned2023-09-10T11:00:30Z
dc.date.available2023-09-10T11:00:30Z
dc.date.issued2023
dc.description.abstractThe clinical manifestations of asthma in children are highly variable, are associated with different molecular and cellular mechanisms, and are characterized by common symptoms that may diversify in frequency and intensity throughout life. It is a disease that generally begins in the first five years of life, and it is essential to promptly identify patients at high risk of developing asthma by using different prediction models. The aim of this review regarding the early prediction of asthma is to summarize predictive factors for the course of asthma, including lung function, allergic comorbidity, and relevant data from the patient's medical history, among other factors. This review also highlights the epigenetic factors that are involved, such as DNA methylation and asthma risk, microRNA expression, and histone modification. The different tools that have been developed in recent years for use in asthma prediction, including machine learning approaches, are presented and compared. In this review, emphasis is placed on molecular mechanisms and biomarkers that can be used as predictors of asthma in children.
dc.format.extent22 páginas
dc.fuente.origenWOS
dc.identifier.doi10.3390/jcm12165404
dc.identifier.eissn2077-0383
dc.identifier.scopusidSCOPUS_ID: 85169081035
dc.identifier.urihttps://doi.org/10.3390/jcm12165404
dc.identifier.urihttps://repositorio.uc.cl/handle/11534/75213
dc.identifier.wosidWOS:001056063100001
dc.information.autorucEscuela de Medicina; Castro Rodriguez, José Antonio; 0000-0002-0708-4281; 113247
dc.issue.numero16
dc.language.isoen
dc.nota.accesoContenido completo
dc.publisherMDPI
dc.revistaJournal of Clinical Medicine
dc.rightsacceso abierto
dc.rights.licenseAtribución 4.0 Internacional (CC BY 4.0)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/deed.es
dc.subjectAsthma
dc.subjectEpigenetics
dc.subjectBiomarkers
dc.subjectPredictive models
dc.subjectMachine learning
dc.subject.ddc610
dc.subject.deweyMedicina y saludes_ES
dc.subject.ods03 Good Health and Well-being
dc.subject.odspa03 Salud y bienestar
dc.titleEarly Prediction of Asthma
dc.typeartículo de revisión
dc.volumen12
sipa.codpersvinculados113247
sipa.indexWOS
sipa.trazabilidadWOS;2023-09-09
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