{"title":"探索阻塞性睡眠呼吸暂停与体重指数之间的共同遗传结构。","authors":"Peng Zhou, Ling Li, Zehua Lin, Xiaoping Ming, Yiwei Feng, Yifan Hu, Xiong Chen","doi":"10.2147/NSS.S459136","DOIUrl":null,"url":null,"abstract":"<p><strong>Purpose: </strong>The reciprocal comorbidity of obstructive sleep apnea (OSA) and body mass index (BMI) has been observed, yet the shared genetic architecture between them remains unclear. This study aimed to explore the genetic overlaps between them.</p><p><strong>Methods: </strong>Summary statistics were acquired from the genome-wide association studies (GWASs) on OSA (N<sub>case</sub> = 41,704; N<sub>control</sub> = 335,573) and BMI (N<sub>overall</sub> = 461,460). A comprehensive genome-wide cross-trait analysis was performed to quantify global and local genetic correlation, infer the bidirectional causal relationships, detect independent pleiotropic loci, and investigate potential comorbid genes.</p><p><strong>Results: </strong>A positive significant global genetic correlation between OSA and BMI was observed (<i>r</i> <sub>g</sub> = 0.52, <i>P</i> = 2.85e-122), which was supported by three local signal. The Mendelian randomization analysis confirmed bidirectional causal associations. In the meta-analysis of cross-traits GWAS, a total of 151 single-nucleotide polymorphisms were found to be pleiotropic between OSA and BMI. Additionally, we discovered that the genetic association between OSA and BMI is concentrated in 12 brain regions. Finally, a total 134 expression-tissue pairs were observed to have a significant impact on both OSA and BMI within the specified brain regions.</p><p><strong>Conclusion: </strong>Our comprehensive genome-wide cross-trait analysis indicates a shared genetic architecture between OSA and BMI, offering new perspectives on the possible mechanisms involved.</p>","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11166156/pdf/","citationCount":"0","resultStr":"{\"title\":\"Exploring the Shared Genetic Architecture Between Obstructive Sleep Apnea and Body Mass Index.\",\"authors\":\"Peng Zhou, Ling Li, Zehua Lin, Xiaoping Ming, Yiwei Feng, Yifan Hu, Xiong Chen\",\"doi\":\"10.2147/NSS.S459136\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Purpose: </strong>The reciprocal comorbidity of obstructive sleep apnea (OSA) and body mass index (BMI) has been observed, yet the shared genetic architecture between them remains unclear. 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引用次数: 0
摘要
目的：阻塞性睡眠呼吸暂停（OSA）与体重指数（BMI）之间存在互为并发症的关系，但两者之间的共同遗传结构仍不清楚。本研究旨在探索它们之间的遗传重叠：从有关 OSA（Ncase = 41,704; Ncontrol = 335,573 ）和 BMI（Noverall = 461,460 ）的全基因组关联研究（GWASs）中获得摘要统计。为了量化全局和局部遗传相关性、推断双向因果关系、检测独立的多效基因位点并研究潜在的合并基因，我们进行了全面的全基因组跨性状分析：结果：观察到 OSA 与体重指数之间存在明显的整体遗传正相关（r g = 0.52，P = 2.85e-122），并得到三个局部信号的支持。孟德尔随机分析证实了双向因果关系。在跨性状 GWAS 的荟萃分析中，共发现 151 个单核苷酸多态性在 OSA 和 BMI 之间具有多向性。此外，我们还发现 OSA 和 BMI 之间的遗传关联主要集中在 12 个脑区。最后，在指定的脑区中，共观察到134对表达-组织对OSA和BMI有显著影响：结论：我们的全基因组跨性状综合分析表明，OSA 和 BMI 之间存在共同的遗传结构，为研究其中可能的机制提供了新的视角。
Exploring the Shared Genetic Architecture Between Obstructive Sleep Apnea and Body Mass Index.
Purpose: The reciprocal comorbidity of obstructive sleep apnea (OSA) and body mass index (BMI) has been observed, yet the shared genetic architecture between them remains unclear. This study aimed to explore the genetic overlaps between them.
Methods: Summary statistics were acquired from the genome-wide association studies (GWASs) on OSA (Ncase = 41,704; Ncontrol = 335,573) and BMI (Noverall = 461,460). A comprehensive genome-wide cross-trait analysis was performed to quantify global and local genetic correlation, infer the bidirectional causal relationships, detect independent pleiotropic loci, and investigate potential comorbid genes.
Results: A positive significant global genetic correlation between OSA and BMI was observed (rg = 0.52, P = 2.85e-122), which was supported by three local signal. The Mendelian randomization analysis confirmed bidirectional causal associations. In the meta-analysis of cross-traits GWAS, a total of 151 single-nucleotide polymorphisms were found to be pleiotropic between OSA and BMI. Additionally, we discovered that the genetic association between OSA and BMI is concentrated in 12 brain regions. Finally, a total 134 expression-tissue pairs were observed to have a significant impact on both OSA and BMI within the specified brain regions.
Conclusion: Our comprehensive genome-wide cross-trait analysis indicates a shared genetic architecture between OSA and BMI, offering new perspectives on the possible mechanisms involved.
期刊介绍：
Nature and Science of Sleep is an international, peer-reviewed, open access journal covering all aspects of sleep science and sleep medicine, including the neurophysiology and functions of sleep, the genetics of sleep, sleep and society, biological rhythms, dreaming, sleep disorders and therapy, and strategies to optimize healthy sleep.
Specific topics covered in the journal include:
The functions of sleep in humans and other animals
Physiological and neurophysiological changes with sleep
The genetics of sleep and sleep differences
The neurotransmitters, receptors and pathways involved in controlling both sleep and wakefulness
Behavioral and pharmacological interventions aimed at improving sleep, and improving wakefulness
Sleep changes with development and with age
Sleep and reproduction (e.g., changes across the menstrual cycle, with pregnancy and menopause)
The science and nature of dreams
Sleep disorders
Impact of sleep and sleep disorders on health, daytime function and quality of life
Sleep problems secondary to clinical disorders
Interaction of society with sleep (e.g., consequences of shift work, occupational health, public health)
The microbiome and sleep
Chronotherapy
Impact of circadian rhythms on sleep, physiology, cognition and health
Mechanisms controlling circadian rhythms, centrally and peripherally
Impact of circadian rhythm disruptions (including night shift work, jet lag and social jet lag) on sleep, physiology, cognition and health
Behavioral and pharmacological interventions aimed at reducing adverse effects of circadian-related sleep disruption
Assessment of technologies and biomarkers for measuring sleep and/or circadian rhythms
Epigenetic markers of sleep or circadian disruption.
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