PDF(Pubmed)
Abstract：
OBJECTIVE: Sleep bruxism (SB) can cause damage on teeth, headache and severe pain affecting both sleep and daily functioning. Yet despite the growing interest into bruxism, the underlying clinically relevant biological mechanisms remain unresolved. The aim of our study was to understand biological mechanisms and clinical correlates of SB including previously reported disease associations.
METHODS: We used data from the FinnGen release R9 (N = 377 277 individuals) that are linked with Finnish hospital and primary care registries. We identified 12 297 (3.26%) individuals with International Classification of Diseases (ICD)-10 codes used for SB. In addition, we used logistic regression to examine the association between probable SB and its clinically diagnosed risk factors and comorbidities using ICD-10 codes. Furthermore, we examined medication purchases using prescription registry. Finally, we performed the first genome-wide association analysis for probable SB and computed genetic correlations using questionnaire, lifestyle, and clinical traits.
RESULTS: The genome-wide association analysis revealed one significant association: rs10193179 intronic to Myosin IIIB (MYO3B) gene. In addition, we observed phenotypic associations and high genetic correlations with pain diagnoses, sleep apnea, reflux disease, upper respiratory diseases, psychiatric traits, and also their related medications such as antidepressants and sleep medication (p < 1e-4 for each trait).
CONCLUSIONS: Our study provides a large-scale genetic framework to understand risk factors for SB and suggests potential biological mechanisms. Furthermore, our work strengthens the important earlier work that highlights SB as a trait that is associated with multiple axes of health. As part of this study, we provide genome-wide summary statistics that we hope will be useful for the scientific community studying SB.
METHODS: We used data from the FinnGen release R9 (N = 377 277 individuals) that are linked with Finnish hospital and primary care registries. We identified 12 297 (3.26%) individuals with International Classification of Diseases (ICD)-10 codes used for SB. In addition, we used logistic regression to examine the association between probable SB and its clinically diagnosed risk factors and comorbidities using ICD-10 codes. Furthermore, we examined medication purchases using prescription registry. Finally, we performed the first genome-wide association analysis for probable SB and computed genetic correlations using questionnaire, lifestyle, and clinical traits.
RESULTS: The genome-wide association analysis revealed one significant association: rs10193179 intronic to Myosin IIIB (MYO3B) gene. In addition, we observed phenotypic associations and high genetic correlations with pain diagnoses, sleep apnea, reflux disease, upper respiratory diseases, psychiatric traits, and also their related medications such as antidepressants and sleep medication (p < 1e-4 for each trait).
CONCLUSIONS: Our study provides a large-scale genetic framework to understand risk factors for SB and suggests potential biological mechanisms. Furthermore, our work strengthens the important earlier work that highlights SB as a trait that is associated with multiple axes of health. As part of this study, we provide genome-wide summary statistics that we hope will be useful for the scientific community studying SB.
摘要：
目的：睡眠磨牙症（SB）会对牙齿造成损伤，头痛和严重的疼痛影响睡眠和日常功能。然而，尽管人们对磨牙症的兴趣越来越大，潜在的临床相关生物学机制仍未解决.我们研究的目的是了解SB的生物学机制和临床相关性，包括先前报道的疾病相关性。
方法：我们使用了FinnGen版本R9（N=377277人）的数据，这些数据与芬兰医院和初级保健登记相关联。我们确定了12297名（3.26％）具有用于SB的国际疾病分类（ICD）-10代码的个体。此外,我们使用ICD-10代码,采用logistic回归分析了可能的SB与其临床诊断的危险因素和合并症之间的关联.此外，我们使用处方登记检查了药物购买情况.最后,我们使用问卷对可能的SB和计算的遗传相关性进行了首次全基因组关联分析，生活方式,和临床特征。
结果：全基因组关联分析揭示了一个显著关联：rs10193179内含子与肌球蛋白IIIB（MYO3B）基因。此外,我们观察到疼痛诊断的表型关联和高度遗传相关性，睡眠呼吸暂停,反流病,上呼吸道疾病,精神病学特征，以及他们的相关药物，如抗抑郁药和睡眠药物（每个性状p<1e-4）。
结论：我们的研究为了解SB的危险因素提供了一个大规模的遗传框架，并提出了潜在的生物学机制。此外，我们的工作加强了重要的早期工作,强调SB是与多个健康轴相关的特征.作为这项研究的一部分,我们提供全基因组汇总统计数据，希望对研究SB的科学界有用。
方法：我们使用了FinnGen版本R9（N=377277人）的数据，这些数据与芬兰医院和初级保健登记相关联。我们确定了12297名（3.26％）具有用于SB的国际疾病分类（ICD）-10代码的个体。此外,我们使用ICD-10代码,采用logistic回归分析了可能的SB与其临床诊断的危险因素和合并症之间的关联.此外，我们使用处方登记检查了药物购买情况.最后,我们使用问卷对可能的SB和计算的遗传相关性进行了首次全基因组关联分析，生活方式,和临床特征。
结果：全基因组关联分析揭示了一个显著关联：rs10193179内含子与肌球蛋白IIIB（MYO3B）基因。此外,我们观察到疼痛诊断的表型关联和高度遗传相关性，睡眠呼吸暂停,反流病,上呼吸道疾病,精神病学特征，以及他们的相关药物，如抗抑郁药和睡眠药物（每个性状p<1e-4）。
结论：我们的研究为了解SB的危险因素提供了一个大规模的遗传框架，并提出了潜在的生物学机制。此外，我们的工作加强了重要的早期工作,强调SB是与多个健康轴相关的特征.作为这项研究的一部分,我们提供全基因组汇总统计数据，希望对研究SB的科学界有用。
