Evaluation of clinical and genetic factors in obstructive sleep apnoea.

IF 2.1 4区医学 Q2 OTORHINOLARYNGOLOGY Acta Otorhinolaryngologica Italica Pub Date : 2023-12-01 Epub Date: 2023-10-10 DOI:10.14639/0392-100X-N2532

Maria de Lourdes Rabelo Guimarães, Pedro Guimarães de Azevedo, Renan Pedra Souza, Bianca Gomes-Fernandes, Eitan Friedman, Luiz De Marco, Luciana Bastos-Rodrigues

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Abstract

Purpose: 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.

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阻塞性睡眠呼吸暂停的临床和遗传因素评估。

目的：评估阻塞性睡眠呼吸暂停（OSA）的几个推测候选基因与临床OSA表型之间的相关性，并提出一个诊断OSA的预测综合模型。方法：本病例对照研究比较了确诊OSA病例和种族匹配的临床未受影响对照组之间PER3、BDNF、NRXN3、APOE、HCRTR2、MC4R多态性的多导睡眠图模式、临床数据、发病率、牙科因素和遗传数据。使用组合数据开发了一个逻辑回归模型来预测OSA。结果：队列包括161例OSA病例和81例对照组。病例的平均年龄为53.5±14.0岁，大多数为男性（57.0%），平均体重指数（BMI）为27.5±4.3 kg/m2。在对年龄和BMI进行调整后，没有一项基因型标志物显示出与OSA有统计学意义的相关性。预测算法包括性别、年龄、打鼾、高血压、口呼吸和PER3 rs228729的T等位基因数量，特异性为76.5%，敏感性为71.6%。结论：没有检测到遗传变异与OSA表型有统计学意义的相关性。Logistic回归分析得出了诊断OSA的预测模型，如果通过更大规模的前瞻性研究进行验证，该模型可以应用于临床，以实现OSA的风险分层。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Acta Otorhinolaryngologica Italica OTORHINOLARYNGOLOGY-

CiteScore

3.40

自引率

10.00%

发文量

审稿时长

6-12 weeks

期刊介绍： Acta Otorhinolaryngologica Italica first appeared as “Annali di Laringologia Otologia e Faringologia” and was founded in 1901 by Giulio Masini. It is the official publication of the Italian Hospital Otology Association (A.O.O.I.) and, since 1976, also of the Società Italiana di Otorinolaringoiatria e Chirurgia Cervico-Facciale (S.I.O.Ch.C.-F.). The journal publishes original articles (clinical trials, cohort studies, case-control studies, cross-sectional surveys, and diagnostic test assessments) of interest in the field of otorhinolaryngology as well as clinical techniques and technology (a short report of unique or original methods for surgical techniques, medical management or new devices or technology), editorials (including editorial guests – special contribution) and letters to the Editor-in-Chief. Articles concerning science investigations and well prepared systematic reviews (including meta-analyses) on themes related to basic science, clinical otorhinolaryngology and head and neck surgery have high priority.