Evaluation of clinical and genetic factors in obstructive sleep apnoea

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dc.creatorMaria de Lourdes Rabelo Guimarães
dc.creatorPedro Guimarães de Azevedo
dc.creatorRenan Pedra de Souza
dc.creatorEitan Friedman
dc.creatorLuíz Armando Cunha de Marco
dc.creatorLuciana Bastos Rodrigues
dc.date.accessioned2025-02-06T21:03:19Z
dc.date.accessioned2025-09-08T22:59:10Z
dc.date.available2025-02-06T21:03:19Z
dc.date.issued2023-10-10
dc.format.mimetypepdf
dc.identifier.doi10.14639/0392-100X-N2532
dc.identifier.issn1827-675X
dc.identifier.urihttps://hdl.handle.net/1843/79738
dc.languageeng
dc.publisherUniversidade Federal de Minas Gerais
dc.relation.ispartofActa Otorhinolaryngol Italica
dc.rightsAcesso Aberto
dc.subjectGenética
dc.subjectSíndromes da apnéia do sono
dc.subjectAlgorítmos genéticos
dc.subject.otherObstructive sleep apnea
dc.subject.otherGenetic polymorphisms
dc.subject.otherPhenotype
dc.subject.otherAlgorithms
dc.subject.otherCase-control studies
dc.titleEvaluation of clinical and genetic factors in obstructive sleep apnoea
dc.title.alternativeValutazione dei fattori clinici e genetici nella sindrome da apnee ostruttive del sonno
dc.typeArtigo de periódico
local.citation.epage416
local.citation.issue6
local.citation.spage409
local.citation.volume43
local.description.resumoPurpose. To evaluate the correlation between several presumed candidate genes for obstructive sleep apnoea (OSA) and clinical OSA phenotypes and propose a predictive comprehensive model for diagnosis of OSA. Methods. This case-control study compared polysomnographic patterns, clinical data, morbidities, dental factors and genetic data for polymorphisms in PER3, BDNF, NRXN3, APOE, HCRTR2, MC4R between confirmed OSA cases and ethnically matched clinically unaffected controls. A logistic regression model was developed to predict OSA using the combined data. Results. The cohort consisted of 161 OSA cases and 81 controls. Mean age of cases was 53.5 ± 14.0 years, mostly males (57%) and mean body mass index (BMI) of 27.5 ± 4.3 kg/ m2. None of the genotyped markers showed a statistically significant association with OSA after adjusting for age and BMI. A predictive algorithm included the variables gender, age, snoring, hypertension, mouth breathing and number of T alleles of PER3 (rs228729) presenting 76.5% specificity and 71.6% sensitivity. Conclusions. No genetic variant tested showed a statistically significant association with OSA phenotype. Logistic regression analysis resulted in a predictive model for diagnosing OSA that, if validated by larger prospective studies, could be applied clinically to allow risk stratification for OSA.
local.identifier.orcidhttps://orcid.org/0000-0002-5271-5548
local.identifier.orcidhttps://orcid.org/0000-0001-9352-1224
local.identifier.orcidhttps://orcid.org/0000-0002-9479-4432
local.identifier.orcidhttps://orcid.org/0000-0002-6745-1733
local.identifier.orcidhttps://orcid.org/0000-0002-1161-8936
local.identifier.orcidhttps://orcid.org/0000-0002-9053-7201
local.publisher.countryBrasil
local.publisher.departmentMEDICINA - FACULDADE DE MEDICINA
local.publisher.initialsUFMG
local.url.externahttps://old.actaitalica.it/article/view/2532

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