Obstructive Sleep Apnea Syndrome and Obesity Indicators, Circulating Blood Lipid Levels, and Adipokines Levels: A Bidirectional Two-Sample Mendelian Randomization Study

IF 3 2区医学 Q2 CLINICAL NEUROLOGY

Nature and Science of Sleep Pub Date : 2024-05-28 DOI:10.2147/nss.s460989

Yating Zhang, Hongyan Wang, Jie Yang, Sanchun Wang, Weifang Tong, Bo Teng

{"title":"Obstructive Sleep Apnea Syndrome and Obesity Indicators, Circulating Blood Lipid Levels, and Adipokines Levels: A Bidirectional Two-Sample Mendelian Randomization Study","authors":"Yating Zhang, Hongyan Wang, Jie Yang, Sanchun Wang, Weifang Tong, Bo Teng","doi":"10.2147/nss.s460989","DOIUrl":null,"url":null,"abstract":"Purpose: This investigation sought to elucidate the genetic underpinnings that connect obesity indicators, circulating blood lipid levels, adipokines levels and obstructive sleep apnea syndrome (OSAS), employing a bidirectional two-sample Mendelian randomization (MR) analysis that utilizes data derived from extensive genome-wide association studies (GWAS). Methods: We harnessed genetic datasets of OSAS available from the FinnGen consortium and summary data of four obesity indices (including neck circumference), seven blood lipid (including triglycerides) and eleven adipokines (including leptin) from the IEU OpenGWAS database. We primarily utilized inverse variance weighted (IVW), weighted median, and MR-Egger methods, alongside MR-PRESSO and Cochran’s Q tests, to validate and assess the diversity and heterogeneity of our findings. Results: After applying the Bonferroni correction, we identified significant correlations between OSAS and increased neck circumference (Odds Ratio [OR]: 3.472, 95% Confidence Interval [CI]: 1.954– 6.169, P= 2.201E-05) and decreased high-density lipoprotein (HDL) cholesterol levels (OR: 0.904, 95% CI: 0.858– 0.952, P= 1.251E-04). Concurrently, OSAS was linked to lower leptin levels (OR: 1.355, 95% CI: 1.069– 1.718, P= 0.012) and leptin receptor levels (OR: 0.722, 95% CI: 0.530– 0.996, P= 0.047). Sensitivity analyses revealed heterogeneity in HDL cholesterol and leptin indicators, but further multiplicative random effects IVW method analysis confirmed these correlations as significant (P< 0.05) without notable heterogeneity or horizontal pleiotropy in other instrumental variables. Conclusion: This investigation compellingly supports the hypothesis that OSAS could be a genetic predisposition for elevated neck circumference, dyslipidemia, and adipokine imbalance. These findings unveil potential genetic interactions between OSAS and metabolic syndrome, providing new pathways for research in this domain. Future investigations should aim to delineate the specific biological pathways by which OSAS impacts metabolic syndrome. Understanding these mechanisms is critical for developing targeted prevention and therapeutic strategies. Keywords: sleep disorders, metabolic syndrome, causal inference, GWAS ","PeriodicalId":18896,"journal":{"name":"Nature and Science of Sleep","volume":null,"pages":null},"PeriodicalIF":3.0000,"publicationDate":"2024-05-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature and Science of Sleep","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2147/nss.s460989","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CLINICAL NEUROLOGY","Score":null,"Total":0}

引用次数: 0

Abstract

Purpose: This investigation sought to elucidate the genetic underpinnings that connect obesity indicators, circulating blood lipid levels, adipokines levels and obstructive sleep apnea syndrome (OSAS), employing a bidirectional two-sample Mendelian randomization (MR) analysis that utilizes data derived from extensive genome-wide association studies (GWAS).
Methods: We harnessed genetic datasets of OSAS available from the FinnGen consortium and summary data of four obesity indices (including neck circumference), seven blood lipid (including triglycerides) and eleven adipokines (including leptin) from the IEU OpenGWAS database. We primarily utilized inverse variance weighted (IVW), weighted median, and MR-Egger methods, alongside MR-PRESSO and Cochran’s Q tests, to validate and assess the diversity and heterogeneity of our findings.
Results: After applying the Bonferroni correction, we identified significant correlations between OSAS and increased neck circumference (Odds Ratio [OR]: 3.472, 95% Confidence Interval [CI]: 1.954– 6.169, P= 2.201E-05) and decreased high-density lipoprotein (HDL) cholesterol levels (OR: 0.904, 95% CI: 0.858– 0.952, P= 1.251E-04). Concurrently, OSAS was linked to lower leptin levels (OR: 1.355, 95% CI: 1.069– 1.718, P= 0.012) and leptin receptor levels (OR: 0.722, 95% CI: 0.530– 0.996, P= 0.047). Sensitivity analyses revealed heterogeneity in HDL cholesterol and leptin indicators, but further multiplicative random effects IVW method analysis confirmed these correlations as significant (P< 0.05) without notable heterogeneity or horizontal pleiotropy in other instrumental variables.
Conclusion: This investigation compellingly supports the hypothesis that OSAS could be a genetic predisposition for elevated neck circumference, dyslipidemia, and adipokine imbalance. These findings unveil potential genetic interactions between OSAS and metabolic syndrome, providing new pathways for research in this domain. Future investigations should aim to delineate the specific biological pathways by which OSAS impacts metabolic syndrome. Understanding these mechanisms is critical for developing targeted prevention and therapeutic strategies.

Keywords: sleep disorders, metabolic syndrome, causal inference, GWAS

查看原文本刊更多论文

阻塞性睡眠呼吸暂停综合征与肥胖指标、循环血脂水平和脂肪因子水平：双向双样本孟德尔随机研究

目的：本研究采用双向双样本孟德尔随机化（MR）分析法，利用广泛的全基因组关联研究（GWAS）数据，试图阐明肥胖指标、循环血脂水平、脂肪因子水平和阻塞性睡眠呼吸暂停综合征（OSAS）之间的遗传基础：我们利用了芬兰基因联盟（FinnGen consortium）提供的 OSAS 遗传数据集，以及 IEU OpenGWAS 数据库中四项肥胖指数（包括颈围）、七项血脂（包括甘油三酯）和十一项脂肪因子（包括瘦素）的汇总数据。我们主要采用了反方差加权法（IVW）、加权中位法、MR-Egger 法以及 MR-PRESSO 和 Cochran's Q 检验来验证和评估研究结果的多样性和异质性：应用 Bonferroni 校正后，我们发现 OSAS 与颈围增加之间存在显著相关性（Odds Ratio [OR]：3.472，95% 置信区间 [CI]：1.954-6.169，P= 2.201E-05）和高密度脂蛋白（HDL）胆固醇水平下降（OR：0.904，95% CI：0.858-0.952，P= 1.251E-04）。同时，OSAS 与瘦素水平较低（OR：1.355，95% CI：1.069- 1.718，P= 0.012）和瘦素受体水平较低（OR：0.722，95% CI：0.530- 0.996，P= 0.047）有关。敏感性分析显示高密度脂蛋白胆固醇和瘦素指标存在异质性，但进一步的乘法随机效应 IVW 方法分析证实这些相关性显著（P< 0.05），而其他工具变量没有明显的异质性或水平多向性：这项调查有力地支持了 OSAS 可能是颈围增高、血脂异常和脂肪因子失衡的遗传易感性这一假设。这些发现揭示了 OSAS 与代谢综合征之间潜在的遗传相互作用，为这一领域的研究提供了新的途径。未来的研究应旨在阐明 OSAS 影响代谢综合征的具体生物学途径。了解这些机制对于制定有针对性的预防和治疗策略至关重要。关键词：睡眠障碍；代谢综合征；因果推断；GWAS

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Nature and Science of Sleep Neuroscience-Behavioral Neuroscience

CiteScore

5.70

自引率

5.90%

发文量

245

审稿时长

16 weeks

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.