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      Association of modifiable risk factors with obstructive sleep apnea: a Mendelian randomization study

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          Abstract

          Background: The risk factors involved in obstructive sleep apnea (OSA) have not been clearly identified yet. We attempted to systematically investigate genetically predicted modifiable risk factors and lifestyle behaviors associated with OSA.

          Methods: The association between 34 risk factors and OSA was evaluated using the two-sample Mendelian randomization (MR). Genetic variants for risk factors were acquired from European-descent genome-wide studies. Data sources for OSA were extracted from FinnGen study with 16,761 cases and 201,194 controls. The primary analysis chosen was the inverse-variance weighted method.

          Results: MR analyses provide evidence of genetically predicted poor overall health rating (odds ratio (OR), 2.82; 95% confidence interval (CI), 1.95–4.08), nap during day (OR, 2.01; 95% CI, 1.37–2.93), high body mass index (BMI) (OR, 1.14; 95% CI, 1.09–1.19), increased body fat mass (OR, 1.83; 95% CI, 1.83–2.05), elevated body water mass (OR, 1.50; 95% CI, 1.31–1.70) and hypertension (OR, 1.81; 95% CI, 1.34–2.45) were associated with higher OSA risk, while high education level (OR, 0.55; 95% CI, 0.40–0.75) correlated with reduced OSA risk. Suggestive evidence was obtained for smoking and waist-to-hip ratio (WHR) with higher OSA odds, and vigorous physical activity, and HDL cholesterol with lower OSA odds. After adjusting for BMI using multivariable MR analysis, the effects of smoking, WHR, vigorous physical activity, and HDL-cholesterol were fully attenuated.

          Conclusions: This MR study indicates that overall health rating, nap during day, BMI, body fat mass, body water mass, hypertension, and education are causally associated with the risk of OSA, which means that these modifiable risk factors are key targets for OSA prevention.

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          Measuring inconsistency in meta-analyses.

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            Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression

            Background: The number of Mendelian randomization analyses including large numbers of genetic variants is rapidly increasing. This is due to the proliferation of genome-wide association studies, and the desire to obtain more precise estimates of causal effects. However, some genetic variants may not be valid instrumental variables, in particular due to them having more than one proximal phenotypic correlate (pleiotropy). Methods: We view Mendelian randomization with multiple instruments as a meta-analysis, and show that bias caused by pleiotropy can be regarded as analogous to small study bias. Causal estimates using each instrument can be displayed visually by a funnel plot to assess potential asymmetry. Egger regression, a tool to detect small study bias in meta-analysis, can be adapted to test for bias from pleiotropy, and the slope coefficient from Egger regression provides an estimate of the causal effect. Under the assumption that the association of each genetic variant with the exposure is independent of the pleiotropic effect of the variant (not via the exposure), Egger’s test gives a valid test of the null causal hypothesis and a consistent causal effect estimate even when all the genetic variants are invalid instrumental variables. Results: We illustrate the use of this approach by re-analysing two published Mendelian randomization studies of the causal effect of height on lung function, and the causal effect of blood pressure on coronary artery disease risk. The conservative nature of this approach is illustrated with these examples. Conclusions: An adaption of Egger regression (which we call MR-Egger) can detect some violations of the standard instrumental variable assumptions, and provide an effect estimate which is not subject to these violations. The approach provides a sensitivity analysis for the robustness of the findings from a Mendelian randomization investigation.
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              Consistent Estimation in Mendelian Randomization with Some Invalid Instruments Using a Weighted Median Estimator

              ABSTRACT Developments in genome‐wide association studies and the increasing availability of summary genetic association data have made application of Mendelian randomization relatively straightforward. However, obtaining reliable results from a Mendelian randomization investigation remains problematic, as the conventional inverse‐variance weighted method only gives consistent estimates if all of the genetic variants in the analysis are valid instrumental variables. We present a novel weighted median estimator for combining data on multiple genetic variants into a single causal estimate. This estimator is consistent even when up to 50% of the information comes from invalid instrumental variables. In a simulation analysis, it is shown to have better finite‐sample Type 1 error rates than the inverse‐variance weighted method, and is complementary to the recently proposed MR‐Egger (Mendelian randomization‐Egger) regression method. In analyses of the causal effects of low‐density lipoprotein cholesterol and high‐density lipoprotein cholesterol on coronary artery disease risk, the inverse‐variance weighted method suggests a causal effect of both lipid fractions, whereas the weighted median and MR‐Egger regression methods suggest a null effect of high‐density lipoprotein cholesterol that corresponds with the experimental evidence. Both median‐based and MR‐Egger regression methods should be considered as sensitivity analyses for Mendelian randomization investigations with multiple genetic variants.
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                Author and article information

                Journal
                Aging (Albany NY)
                Aging
                Aging (Albany NY)
                Impact Journals
                1945-4589
                15 December 2023
                11 December 2023
                : 15
                : 23
                : 14039-14065
                Affiliations
                [1 ]Department of Geriatrics, Tianjin Medical University General Hospital, Tianjin 300052, China
                [2 ]Tianjin Geriatrics Institute, Tianjin 300052, China
                Author notes
                [*]

                Equal contribution

                Correspondence to: Qiang Zhang; email: zhangqiangyulv@163.com, https://orcid.org/0000-0002-5686-9253
                Article
                205288 205288
                10.18632/aging.205288
                10756101
                38085646
                c165d650-bbb9-4944-98a4-b3cafee57aff
                Copyright: © 2023 Li et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 06 July 2023
                : 16 October 2023
                Categories
                Research Paper

                Cell biology
                obstructive sleep apnea,modifiable risk factors,lifestyle behaviors,mendelian randomization

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