Observational Study
Copyright ©The Author(s) 2022. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Clin Cases. Nov 6, 2022; 10(31): 11403-11410
Published online Nov 6, 2022. doi: 10.12998/wjcc.v10.i31.11403
Relationship between lipids and sleep apnea: Mendelian randomization analysis
Lian-Peng Zhang, Xiao-Xia Zhang
Lian-Peng Zhang, Department of Respiratory Medicine, Qingzhou Hospital Affiliated to Shandong First Medical University, Qingzhou People's Hospital, Qingzhou 262500, Shandong Province, China
Xiao-Xia Zhang, Department of AIDS Voluntary Counseling and Testing, Qingzhou Center for Disease Control and Prevention, Qingzhou 262500, Shandong Province, China
Author contributions: Zhang LP contributed to conceptualization, methodology, software, writing-review, and editing; Zhang XX contributed to formal analysis, writing-review, and editing.
Institutional review board statement: The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). All data base were from public research. No patients were participated in the design or study. Thus, ethical approval was not needed for our study.
Informed consent statement: Since this study does not involve human participation, it is not necessary to sign an informed document.
Conflict-of-interest statement: All authors have no conflicts of interest to declare.
Data sharing statement: The data used in this study are all from published materials, dataset available from https://gwas.mrcieu.ac.uk/.
STROBE statement: The authors have read the STROBE Statement—checklist of items, and the manuscript was prepared and revised according to the STROBE Statement—checklist of items.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Lian-Peng Zhang, Doctor, MM, Doctor, Department of Respiratory Medicine, Qingzhou Hospital Affiliated to Shandong First Medical University, Qingzhou People's Hospital, No. 1726 Linglongshan Middle Road, Qingzhou 262500, Shandong Province, China. hxzlp2013@126.com
Received: May 8, 2022
Peer-review started: May 8, 2022
First decision: July 12, 2022
Revised: July 26, 2022
Accepted: September 20, 2022
Article in press: September 20, 2022
Published online: November 6, 2022
Processing time: 171 Days and 16.4 Hours
Abstract
BACKGROUND

Lipids increase the risk of sleep apnea; however, the causality between them is still inconclusive.

AIM

To explore the causal relationship between serum lipids and sleep apnea using two-sample Mendelian randomization (MR) analysis.

METHODS

Single nucleotide polymorphism (SNP) data related to serum lipids were obtained from the Global Lipids Genetics Consortium study, which included 188578 individuals of European ancestry. Additionally, sleep apnea-related SNP data were collected from the United Kingdom Biobank study, which comprised 463005 individuals of European ancestry. Two-sample MR analysis was performed to assess the causality between serum lipids and sleep apnea based on the above public data.

RESULTS

Genetically predicted low-density lipoprotein (odds ratio [OR] = 0.99, 95% confidence interval [CI] = 0.99 to 1.00; P = 0.58), high-density lipoprotein (OR = 0.99, 95%CI = 0.99 to 1.00; P = 0.91), triglyceride (OR = 1.00, 95%CI = 0.99 to 1.00; P = 0.92), and total cholesterol (OR = 0.99, 95%CI = 0.99 to 1.00; P = 0.33) were causally unrelated to sleep apnea.

CONCLUSION

Our MR analysis suggests that genetically predicted serum lipids are not risk factors of sleep apnea.

Keywords: Lipid; Sleep apnea; Mendelian randomization; Single nucleotide polymorphism; Risk factor

Core Tip: This study had a couple of key advantages. First, compared with other observational studies, the genetic variants can be obtained from different sample of individuals, and genetic associations can be obtained from large genome-wide association studies, which can greatly improve the statistical ability to detect small effects of complex phenotypes. Second, the study excluded more confounding factors, heterogeneity and level pleiotropy, and conducted sensitivity tests to make our results more convincing.