pmcThromb HaemostThromb Haemost10.1055/s-00035024Thrombosis and Haemostasis0340-62452567-689XGeorg Thieme Verlag KGRüdigerstraße 14, 70469 Stuttgart, Germany 3863138511518617 10.1055/a-2308-2290TH-23-11-0519Stroke, Systemic or Venous ThromboembolismThe Association between Obstructive Sleep Apnea and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization StudyHuangZhihai1*ZhengZhenzhen2*PangLingpin1*FuKaili2ChengJunfen2ZhongMing1SongLingyue1GuoDingyu1ChenQiaoyun1LiYanxi1LvYongting1ChenRiken2SunXishi1Emergency Medicine Center, Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, ChinaRespiratory and Critical Care Medicine, The Second Affiliated Hospital of Guangdong Medical University, Zhanjiang, Guangdong, ChinaAddress for correspondence Riken Chen, MD Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Guangdong Medical UniversityZhanjiang, 524003, GuangdongChinachenriken@126.comXishi Sun, MM Emergency Medicine Center, Affiliated Hospital of Guangdong Medical UniversityZhanjiang, 524000, GuangdongChina109721368@qq.com23520241120241520241241110611074271120231142024 The Author(s). This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. ( https://creativecommons.org/licenses/by-nc-nd/4.0/ ) 2024The Author(s).https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License, which permits unrestricted reproduction and distribution, for non-commercial purposes only; and use and reproduction, but not distribution, of adapted material for non-commercial purposes only, provided the original work is properly cited.

Background  Despite previous observational studies linking obstructive sleep apnea (OSA) to venous thromboembolism (VTE), these findings remain controversial. This study aimed to explore the association between OSA and VTE, including pulmonary embolism (PE) and deep vein thrombosis (DVT), at a genetic level using a bidirectional two-sample Mendelian randomization (MR) analysis.

Methods  Utilizing summary-level data from large-scale genome-wide association studies in European individuals, we designed a bidirectional two-sample MR analysis to comprehensively assess the genetic association between OSA and VTE. The inverse variance weighted was used as the primary method for MR analysis. In addition, MR–Egger, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO) were used for complementary analyses. Furthermore, a series of sensitivity analyses were performed to ensure the validity and robustness of the results.

Results  The initial and validation MR analyses indicated that genetically predicted OSA had no effects on the risk of VTE (including PE and DVT). Likewise, the reverse MR analysis did not find substantial support for a significant association between VTE (including PE and DVT) and OSA. Supplementary MR methods and sensitivity analyses provided additional confirmation of the reliability of the MR results.

Conclusion  Our bidirectional two-sample MR analysis did not find genetic evidence supporting a significant association between OSA and VTE in either direction.

Keywordsobstructive sleep apneavenous thromboembolismMendelian randomizationassociationFunding This study was supported by the High-level Talents Scientific Research Start-up Funds of the Affiliated Hospital of Guangdong Medical University (GCC2022028), the Health Development Promotion Project-Anesthesia and Critical Care Research Project (KM-20231120-01), Guangdong Medical Research Fund Project (A2024728, A2024723), Zhanjiang Science and Technology Research Project in 2022 (No: 2022A01197), and the Science and Technology Development Special Fund Competitive Allocation Project of Zhanjiang City (No: 2021A05086).
Introduction

Obstructive sleep apnea (OSA) is a prevalent sleep disorder characterized by the recurrent partial or complete obstruction and collapse of the upper airway during sleep, leading to episodes of apneas and hypoventilation. 1 2 Research studies have reported that the prevalence of OSA in the adult population ranges from 9 to 38%, with a higher prevalence observed in males (13–33%) compared to females (6–19%). Moreover, the prevalence of OSA tends to increase with age and is closely associated with the prevalence of obesity. 3 4

There is mounting evidence indicating that OSA serves as an independent risk factor for several cardiovascular diseases, including hypertension, 5 stroke, 6 pulmonary hypertension, 7 and heart failure. 8 Venous thromboembolism (VTE), including deep vein thrombosis (DVT) and pulmonary embolism (PE), is recognized as the third most common cardiovascular disease worldwide. 9 There is evidence suggesting that OSA may also be linked to an increased risk of VTE. 10 For instance, a prospective study involving 15,664 subjects (1,424 subjects with OSA) observed a twofold higher incidence of VTE in patients with OSA compared to non-OSA patients. 11 Similarly, findings from a national retrospective cohort study conducted by Peng and his colleagues indicated that patients with OSA had a 3.50-fold higher risk of DVT and a 3.97-fold higher risk of PE compared to the general population. 12 However, the results of observational studies remain somewhat controversial. A 5-year prospective study involving 2,109 subjects concluded that OSA did not increase the risk of VTE recurrence. 13 Another retrospective analysis involving 1,584 patients, of which 848 were women, revealed an intriguing discovery suggesting that OSA may serve as an independent risk factor for VTE solely in women, rather than in men. 14 Moreover, patients with VTE were found to have a higher prevalence of OSA, 15 suggesting a potential bidirectional relationship.

Although previous observational studies have investigated the potential association between OSA and VTE, elucidating aspects of the association from these studies is challenging due to the limitations of potential confounders and reverse causality bias. Mendelian randomization (MR) is a genetic epidemiological methodology that utilizes genetic variants, such as single-nucleotide polymorphisms (SNPs), as instrumental variables (IVs) to infer the genetic association between exposure and outcome. 16 The advantage of MR analysis lies in the random assignment of genetic variants during meiosis, which effectively circumvents the effects of potential confounders and reverse causality encountered in classical epidemiologic studies. 17

At present, the nature of the association between OSA and VTE remains inconclusive, and there is a dearth of pertinent studies comprehensively exploring the genetic association between OSA and VTE. Therefore, this study aimed to conduct a bidirectional two-sample MR analysis using publicly available summary statistics from large-scale genome-wide association studies (GWAS) to genetically assess the exact association between OSA and VTE, including PE and DVT.

MethodsStudy Design

MR utilizes genetic variants, primarily SNPs, as IVs to investigate the genetic association between exposure and outcome. MR is based on three fundamental assumptions: (1) genetic variants exhibit a high correlation with exposure; (2) genetic variants are independent of potential confounders; (3) genetic variants solely affect outcomes through exposure. IVs are deemed valid only when these assumptions are met.

This study employed a bidirectional two-sample MR analysis to evaluate the genetic association between OSA and VTE. Initially, SNPs associated with OSA were utilized to examine their effects on VTE. Subsequently, to investigate the possibility of reverse association, eligible IVs were employed to quantify the implications of VTE on OSA.

Data Source and Selection of Instrumental Variables

OSA was defined based on subjective symptoms, clinical examination, and sleep registration applying apnea–hypopnea index ≥5/hour or respiratory event index ≥5/hour.

Summary-level data for OSA were obtained from the GWAS study conducted by Jiang et al on European individuals, which included 2,827 cases and 453,521 controls, covering 11,831,932 SNPs. 18 To ensure the robustness of the findings, additional datasets for OSA were acquired from a GWAS meta-analysis conducted by Campos and colleagues, comprising 25,008 cases of European ancestry and 337,630 controls, involving 9,031,949 SNPs for validation analysis. 19 The study conducted a meta-analysis of GWAS datasets from five cohorts in the United Kingdom, Canada, Australia, the United States, and Finland. These summary-level GWAS statistics for OSA can be accessed from the GWAS Catalog ( https://www.ebi.ac.uk/gwas/downloads ). VTE was defined as a condition comprising PE (blockage of the pulmonary artery or its branches by an embolus) and DVT (formation of a blood clot in a deep vein). The GWAS datasets for VTE (19,372 cases and 357,905 controls), PE (9,243 cases and 367,108 controls), and DVT (9,109 cases and 324,121 controls) were derived from the FinnGen consortium (Release 9, https://r9.finngen.fi/ ). Detailed information regarding the data sources is provided in Table 1 .

Information on data sources
TraitSample sizeCaseControlNo. of SNPsParticipatesPMID/Link
OSA (Jiang et al)456,3482,827453,52111,831,932European ancestry34737426
OSA (Campos et al)362,63825,008337,6309,031,949European ancestry36525587
VTE377,27719,372357,90520,170,236European ancestry FinnGen consortium ( https://www.finngen.fi/fi )
PE376,3519,243367,10820,170,202European ancestry FinnGen consortium ( https://www.finngen.fi/fi )
DVT333,2309,109324,12120,169,198European ancestry FinnGen consortium ( https://www.finngen.fi/fi )

Abbreviations: DVT, deep vein thrombosis; OSA, obstructive sleep apnea; PE, pulmonary embolism; SNPs, single-nucleotide polymorphisms; VTE, venous thromboembolism.

The selection criteria for IVs were as follows: (1) the threshold for genome-wide significant SNPs for VTE (including PE and DVT) was set at p  < 5.0 × 10 −8 , while the threshold for OSA was adjusted to p  < 1 × 10 −5 due to the inability to detect OSA-associated SNPs using a significance level of p  < 5.0 × 10 −8 . (2) SNPs with linkage disequilibrium effects ( r 2  < 0.001 within a 10,000-kb window) were excluded to ensure the independence of the selected IVs. (3) The strength of the association between IVs and exposure was measured using the F-statistic [F-statistic = (Beta/SE) 2 ]. 20 SNPs with F-statistics >10 were retained to avoid the effects of weak instrumental bias. (4) During the harmonization process, SNPs that did not match the results were removed, along with palindromic SNPs with ambiguous allele frequencies (0.42–0.58). 21 (5) Previous studies have demonstrated obesity as an established risk factor for OSA and VTE. 22 23 SNPs associated with body mass index were queried and excluded by Phenoscanner (http://www.phenoscanner.medschl.cam.ac.uk/). The flowchart of IV selection is shown in Fig. 1 .

The flowchart of instrumental variables selection. LD, linkage disequilibrium; SNPs, single-nucleotide polymorphisms; BMI, body mass index; VTE, venous thromboembolism; PE, pulmonary embolism; DVT, deep vein thrombosis; OSA, obstructive sleep apnea; ①, represents OSA (Jiang et al) as the outcome; ②, represents OSA (Campos et al) as the outcome.

Statistical Analysis

This study employed the multiplicative random-effects inverse variance weighted (IVW) method as the primary approach for conducting MR analysis to evaluate the genetic association between OSA and VTE. The IVW method meta-analyzes the Wald ratio estimates for each SNP on the outcome, providing precise estimates of causal effects when all selected SNPs are valid IVs. 24 However, the estimates of causal effects from the IVW method may be biased by the influence of pleiotropic IVs. To ensure the validity and robustness of the results, sensitivity analyses were implemented using three additional MR methods, namely MR–Egger, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO). The MR–Egger method is able to generate reliable causal estimates even in situations where all IVs are invalid. Additionally, MR–Egger offers an intercept test to detect horizontal pleiotropy, with a significance threshold of p <0.05 indicating the presence of horizontal pleiotropy. 25 In comparison to the IVW and MR–Egger methods, the weighted median method demonstrates greater robustness and provides consistent estimates of causal effects, even when up to 50% of the IVs are invalid instruments. 26 The MR-PRESSO method identifies outliers with potential horizontal pleiotropy and provides estimates after removing the outliers, where p <0.05 for the global test indicates the presence of outliers with horizontal pleiotropy. 27 Furthermore, the Cochran Q test was utilized to examine heterogeneity, with a significance threshold of p <0.05 indicating significant heterogeneity.

All statistical analyses were carried out using the “TwoSampleMR” and “MRPRESSO” packages in R software (version 4.2.1).

ResultsInstrumental Variable Selection

As previously outlined, a total of 13 and 28 SNPs were identified through a rigorous screening process to evaluate the effects of OSA on VTE, PE, and DVT. In the reverse MR analysis, 23, 14, 18, 19, 11, and 13 SNPs were identified to assess the implications of reverse association, respectively. Additional details regarding these genetic variants utilized for MR analysis are provided in Tables 2 and 3 .

Genetic variants used in the MR analysis
Genetic instruments for OSA (Jiang et al) and their associations with VTE, PE, and DVT
Exposure: OSA (Jiang et al) Outcome: VTE Outcome: PE Outcome: DVT
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value Beta SE p -Value Beta SE p -Value
1rs114417992CG0.487980.107936.15E-0620.44090.007020.043780.87253−0.05420.062110.3832−0.00520.063340.93511
2rs115071002TC−0.37750.08072.90E-0621.8836−0.05210.050450.301460.03590.071850.61729−0.06330.072470.38241
3rs117025138CG0.427950.095717.78E-0619.9915−0.01490.054770.786110.00870.078090.91129−0.03380.078360.66637
4rs117474005TC0.641760.141385.64E-0620.6051−0.00950.041080.81724−0.00090.058620.98772−0.03010.058910.60971
5rs139183760CG0.829730.169289.50E-0724.02620.065140.076810.396430.044410.109290.684480.047610.110240.66585
6rs148047757AG0.474810.106999.08E-0619.6952−0.05220.03520.13769−0.0440.049990.37895−0.02940.050780.562
7rs150798389CA0.78750.173915.95E-0620.505−0.28840.14350.04447−0.24360.200530.22438−0.13290.206790.52056
8rs16850412AG0.195140.043537.36E-0620.09770.026740.015840.091450.047850.022530.033680.01730.022770.44739
9rs1911999CT−0.13120.029659.59E-0619.59170.017590.011110.113490.03760.015770.017140.002230.015960.88889
10rs2302012AG0.128290.028717.88E-0619.9669−0.01040.010760.33549−0.02720.01530.075410.007670.015450.61949
11rs35963104TC0.165720.034521.59E-0623.0393−0.00760.013540.57685−0.020.019240.29896−0.0070.019420.71778
12rs60445800TC0.291910.064997.06E-0620.1758−0.02680.023610.25672−0.06490.033490.052770.01120.033880.74095
13rs9587442TC0.443080.095843.78E-0621.3735−0.03850.033460.24969−0.01010.047810.833220.001820.047830.96962
Genetic instruments for OSA (Campos et al) and their associations with VTE, PE, and DVT
Exposure: OSA (Campos et al) Outcome: VTE Outcome: PE Outcome: DVT
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value Beta SE p -Value Beta SE p -Value
1rs10777826TC−0.03190.006641.58E-0623.04960.006840.010970.532960.010490.015570.500530.017630.015760.26318
2rs10878269TC0.033080.00691.61E-0623.0112−0.02080.011910.08097−0.02620.016930.12108−0.0150.017110.37964
3rs111909157TC−0.13550.026583.40E-0726.010.026640.042220.528080.039950.059990.50540.03640.060890.55
4rs116114601AG−0.08730.019699.20E-0619.6692−0.04010.040980.32779−0.06760.058140.24516−0.01820.058730.75679
5rs11989172CG−0.03780.008396.73E-0620.268−0.02170.012830.09−0.0390.018230.032220.010580.018420.56561
6rs12265404AG0.049310.010412.17E-0622.43920.052330.01660.001620.056870.02330.014670.042780.023580.06956
7rs12306339AC−0.04880.010836.64E-0620.295−0.00510.018040.77914−0.0230.025610.370060.014620.025930.57292
8rs13098300TC0.037150.007121.84E-0727.19620.002510.012020.834340.01010.017080.554325.55E-050.017270.99744
9rs140548601CG−0.11580.024281.85E-0622.75290.055030.047110.242770.092060.066920.168950.046130.067620.49515
10rs143417867AG−0.36660.070882.30E-0726.7599−0.14870.22160.50210.156640.315820.61991−0.08680.315940.78353
11rs1942263AG0.045690.010166.93E-0620.214−0.01560.017130.36361−0.01360.024360.57584−0.03180.024680.19751
12rs2876633AT−0.03550.006953.43E-0725.9896−0.01040.011580.36765−0.01040.016450.528450.00320.016640.84772
13rs35847366AG0.05450.011723.31E-0621.6318−0.03650.018310.04596−0.03830.026030.14125−0.05110.026290.0517
14rs36051007TC0.034810.007161.14E-0623.6682−0.00370.010950.73452−0.01450.015570.351990.007230.015730.64597
15rs3774800AG−0.03090.00697.79E-0619.98980.003950.011510.73124−0.01070.016340.512180.00930.016540.57396
16rs4542364AG0.030280.006736.69E-0620.277−0.00530.010840.6236−0.01990.015410.197370.001630.015590.91663
17rs4675933TC−0.03290.007093.44E-0621.54820.008220.010930.451870.003960.015540.798630.015930.015680.30957
18rs533143TC0.032370.007329.73E-0619.56290.028920.014290.043040.027570.020310.17470.01110.020540.58881
19rs60653979AG0.033840.00686.43E-0724.78050.010980.010830.31063−0.01540.015390.318440.028870.015570.06364
20rs62559379CG0.07060.014551.22E-0623.5419−0.01630.027260.54934−0.0280.038710.46867−0.01130.039150.77255
21rs7106583TC0.038680.008394.09E-0621.2244−0.04340.0140.00194−0.02050.020060.30655−0.04140.02030.04114
22rs72904209TC−0.04460.009835.67E-0620.5934−0.01530.016170.34449−0.03550.022920.1215−0.00660.023270.77599
23rs73141516TC0.064960.014154.40E-0621.08650.00840.021840.70062−0.02410.031050.437970.034050.031330.27717
24rs73164714TC−0.06950.012856.43E-0829.2248−0.0280.037210.452560.005620.052760.91513−0.01390.053190.79352
25rs7800775AG0.034870.007858.98E-0619.71360.003510.013570.795980.007580.019290.69414−0.01660.019480.39528
26rs794999AG0.034210.007647.64E-0620.02560.001080.012580.931710.01390.017860.436490.003740.018070.83582
27rs9464135AG−0.03090.006633.11E-0621.7436−0.00760.010550.471510.011640.0150.43786−0.03750.015160.01337
28rs9567762AT0.036350.008239.92E-0619.52760.012230.010840.259340.004030.01540.79340.015520.015570.31884

Abbreviations: DVT, deep vein thrombosis; EA, effect allele; MR, Mendelian randomization; OA, other allele; OSA, obstructive sleep apnea; PE, pulmonary embolism; SE, standard error; SNP, single-nucleotide polymorphism; VTE, venous thromboembolism.

Note: F-statistic = (Beta/SE) 2 , represents the strength of each instrumental variable

Genetic variants used in the reverse MR analysis
Genetic instruments for VTE/PE/DVT and their associations with OSA (Jiang et al)
Exposure: VTE Outcome: OSA (Jiang et al)
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value
1rs10896706AG0.07021420.01210066.53E-0933.669456−0.05978450.0293450.0416207
2rs113079063TG0.3781070.05077699.59E-1455.4494280.00503640.08761340.954159
3rs114026832AC0.7739250.0999159.50E-1559.9979440.05787730.1805430.748533
4rs114767153TA−0.208880.03481731.98E-0935.991798−0.07121890.09099720.433833
5rs116997538TC0.4032880.03830666.42E-26110.83665−0.0677350.1238970.584581
6rs12054563GA−0.1266770.01764316.97E-1351.5520270.06026950.06636010.363763
7rs1560711TC0.1223790.01414655.11E-1874.8369010.03100440.03210240.334145
8rs174529CT−0.06863420.01072111.54E-1040.982878−0.00534170.02766730.846904
9rs188337046TC0.160480.02504241.47E-1041.0667120.1783110.2066210.388145
10rs2066865AG0.1861120.01123691.30E-61274.318890.00831540.03136910.790945
11rs2519785GA−0.07029910.01188823.35E-0934.9677210.00743190.02971830.802526
12rs3756011AC0.1927120.01055251.65E-74333.50841−0.00263860.02728310.922956
13rs57328376GA0.06975840.01091981.68E-1040.809724−0.01018060.02905330.726031
14rs576123TC−0.2373960.01049733.09E-113511.436330.008190.02877790.775956
15rs5896TC0.1092910.01258523.82E-1875.4134060.06147730.03881910.113265
16rs6025TC0.8734150.02983882.42E-188856.798280.05022170.08997960.576745
17rs6060308AG0.1015870.01123591.55E-1981.7448760.05219360.03087370.0909227
18rs60681578CA−0.1183920.01500292.99E-1562.2722110.01691030.03907730.665204
19rs62350309GA−0.1735090.01814481.15E-2191.440721−0.0719560.06346850.256909
20rs628094AG0.08187810.01143898.19E-1351.2350290.00270280.03021680.928726
21rs72708961CT0.08919130.01594452.22E-0831.291269−0.07653070.03677980.0374539
22rs7772305GA−0.07269640.01115867.28E-1142.4430310.05857780.03071640.0565137
23rs78807356TG0.5410940.05636167.96E-2292.1677130.1016170.07961390.201825
Exposure: PE Outcome: OSA (Jiang et al)
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value
1rs117210485AG0.1507870.02286994.30E-1143.4709640.02146180.1141770.8509
2rs11758950TC0.2039470.03679072.97E-0830.7297160.04185210.08219530.610627
3rs143620474AG0.2812430.05122634.01E-0830.1423750.5468190.1552260.0004271
4rs1481808CT−0.4809290.08757593.98E-0830.157318−0.1649330.1054590.117828
5rs1560711TC0.1447040.02020738.01E-1351.2795840.03100440.03210240.334145
6rs1894692AG−0.5478080.04577645.29E-33143.210040.00023650.09515330.998017
7rs2066865AG0.2274840.01580675.85E-47207.118690.00831540.03136910.790945
8rs28584824AC−0.1552640.02792342.69E-0830.917541−0.02687560.07821080.731124
9rs3756011AC0.2347840.01491437.77E-56247.81709−0.00263860.02728310.922956
10rs62350309GA−0.2025340.02603727.33E-1560.507237−0.0719560.06346850.256909
11rs635634CT−0.2396360.01779352.43E-41181.376640.00645960.03471970.852404
12rs665082CG−0.1755810.0304848.42E-0933.175015−0.3432670.2164050.112688
13rs77165492CT0.2092690.02754623.03E-1457.714695−0.04456180.04577690.330327
14rs78807356TG0.5157840.07950968.75E-1142.0820220.1016170.07961390.201825
Exposure: DVT Outcome: OSA (Jiang et al)
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value
1rs113079063TG0.4362840.07175631.20E-0936.9673650.00503640.08761340.954159
2rs116997538TC0.4662450.05345832.74E-1876.067315−0.0677350.1238970.584581
3rs13377102AT−0.2332550.02550946.02E-2083.610619−0.02501860.03895180.520681
4rs2066865AG0.1845070.01611452.36E-30131.096780.00831540.03136910.790945
5rs2289252TC0.1979720.0151354.26E-39171.09712−0.00184110.02725710.946148
6rs2519785GA−0.09824670.01699737.46E-0933.4099680.00743190.02971830.802526
7rs576123TC−0.2976820.0149837.70E-88394.736780.008190.02877790.775956
8rs5896TC0.1410240.0179453.88E-1561.758840.06147730.03881910.113265
9rs6025TC1.104390.03939035.71E-173786.079290.05022170.08997960.576745
10rs6060237GA0.1684530.01982141.92E-1772.2252160.03184320.04140730.441879
11rs60681578CA−0.1376150.0216271.98E-1040.4891810.01691030.03907730.665204
12rs62350309GA−0.1627040.02599983.90E-1039.161241−0.0719560.06346850.256909
13rs666870AG0.09248320.01590696.10E-0933.8029490.01279680.02715580.637472
14rs7308002AG0.09781740.015765.41E-1038.522974−0.00279340.02757460.919309
15rs76151810AC0.1530730.02731122.09E-0831.413449−0.00184930.05072560.970918
16rs7772305GA−0.1002510.0160574.28E-1038.9806080.05857780.03071640.0565137
17rs78807356TG0.6214470.07924144.42E-1561.5040780.1016170.07961390.201825
18rs9865118TC0.08638040.01518141.27E-0832.3747760.03635830.02683380.175436
Genetic instruments for VTE/PE/DVT and their associations with OSA (Campos et al)
Exposure: VTE Outcome: OSA (Campos et al)
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value
1rs10896706AG0.07021420.01210066.53E-0933.6694560.00733760.00727940.3136
2rs114767153TA−0.208880.03481731.98E-0935.991798−0.02404770.02202170.2749
3rs116997538TC0.4032880.03830666.42E-26110.83665−0.02029030.03462510.558
4rs12054563GA−0.1266770.01764316.97E-1351.552027−0.01645250.01595780.3025
5rs1560711TC0.1223790.01414655.11E-1874.836901−0.00334050.00900410.7104
6rs174529CT−0.06863420.01072111.54E-1040.982878−0.00162350.00685030.8124
7rs2066865AG0.1861120.01123691.30E-61274.31889−0.00339990.00776230.6612
8rs3756011AC0.1927120.01055251.65E-74333.508410.0005750.00676450.9326
9rs57328376GA0.06975840.01091981.68E-1040.809724−0.00100620.00718730.8885
10rs576123TC−0.2373960.01049733.09E-113511.436330.01835510.00867860.03441
11rs5896TC0.1092910.01258523.82E-1875.4134060.0209850.00965270.02974
12rs6025TC0.8734150.02983882.42E-188856.798280.03801180.02188360.08241
13rs6060308AG0.1015870.01123591.55E-1981.744876−0.00092880.00749010.9013
14rs60681578CA−0.1183920.01500292.99E-1562.2722110.00850670.01171720.4678
15rs62350309GA−0.1735090.01814481.15E-2191.4407210.00751140.01529820.6233
16rs628094AG0.08187810.01143898.19E-1351.235029−0.00223540.00740210.7627
17rs72708961CT0.08919130.01594452.22E-0831.291269−0.01706360.00909570.06059
18rs7772305GA−0.07269640.01115867.28E-1142.4430310.0167090.00863960.05311
19rs80137017TC−0.2089020.01779968.30E-32137.741470.01520220.00994260.1262
Exposure: PE Outcome: OSA (Campos et al)
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value
1rs117210485AG0.1507870.02286994.30E-1143.470964−0.03465230.02391460.1473
2rs143620474AG0.2812430.05122634.01E-0830.1423750.01249880.08927690.8889
3rs1481808CT−0.4809290.08757593.98E-0830.157318−0.02812430.02696480.297
4rs1560711TC0.1447040.02020738.01E-1351.279584−0.00334050.00900410.7104
5rs2066865AG0.2274840.01580675.85E-47207.11869−0.00339990.00776230.6612
6rs28584824AC−0.1552640.02792342.69E-0830.9175410.03241350.01915690.09056
7rs3756011AC0.2347840.01491437.77E-56247.817090.0005750.00676450.9326
8rs62350309GA−0.2025340.02603727.33E-1560.5072370.00751140.01529820.6233
9rs635634CT−0.2396360.01779352.43E-41181.376640.01399750.00969350.1488
10rs77165492CT0.2092690.02754623.03E-1457.7146950.00139460.01143110.9026
11rs80137017TC−0.2300140.025431.50E-1981.8117760.01520220.00994260.1262
Exposure: DVT Outcome: OSA (Campos et al)
SNP EA OA Beta SE p -Value F-statistic Beta SE p -Value
1rs116997538TC0.4662450.05345832.74E-1876.067315−0.02029030.03462510.558
2rs13377102AT−0.2332550.02550946.02E-2083.6106190.00855790.00965910.3759
3rs2066865AG0.1845070.01611452.36E-30131.09678−0.00339990.00776230.6612
4rs576123TC−0.2976820.0149837.70E-88394.736780.01835510.00867860.03441
5rs5896TC0.1410240.0179453.88E-1561.758840.0209850.00965270.02974
6rs6025TC1.104390.03939035.71E-173786.079290.03801180.02188360.08241
7rs6060237GA0.1684530.01982141.92E-1772.2252160.00605260.01017240.5518
8rs60681578CA−0.1376150.0216271.98E-1040.4891810.00850670.01171720.4678
9rs62350309GA−0.1627040.02599983.90E-1039.1612410.00751140.01529820.6233
10rs666870AG0.09248320.01590696.10E-0933.8029490.00746160.00672210.2669
11rs7308002AG0.09781740.015765.41E-1038.522974−0.00236440.00685330.7298
12rs7772305GA−0.1002510.0160574.28E-1038.9806080.0167090.00863960.05311
13rs9865118TC0.08638040.01518141.27E-0832.374776−0.00056480.00664420.9323

Abbreviations: DVT, deep vein thrombosis; EA, effect allele; MR, Mendelian randomization; OA, other allele; OSA, obstructive sleep apnea; PE, pulmonary embolism; SE, standard error; SNP, single-nucleotide polymorphism; VTE, venous thromboembolism.

Note: F-statistic = (Beta/SE) 2 , represents the strength of each instrumental variable.

Effects of OSA on VTE

Fig. 2 shows the estimates of the effects for OSA on VTE, PE, and DVT. In the initial MR analysis using the OSA (Jiang et al) dataset, the random-effects IVW method revealed no significant association between OSA and the risk of VTE (odds ratio [OR]: 0.964, 95% confidence interval [CI]: 0.914-1.016, p  = 0.172), PE (OR: 0.929, 95% CI: 0.857–1.006, p  = 0.069), PE (OR: 0.929, 95% CI: 0.857–1.006, p  = 0.069), and DVT (OR: 1.001, 95% CI: 0.936–1.071, p  = 0.973). No heterogeneity was observed using the Cochran Q test (all p * > 0.05). The MR–Egger intercept test (all p ** > 0.05) and the MR-PRESSO global test (all p *** > 0.05) failed to detect any evidence of pleiotropy.

The genetic association of OSA with VTE/PE/DVT. OSA, obstructive sleep apnea; VTE, venous thromboembolism; PE, pulmonary embolism; DVT, deep vein thrombosis; MR, mendelian randomization; IVW, inverse variance weighted; PRESSO, pleiotropy residual sum and outlier; P*, represents P for heterogeneity test; P**, represents P for MR-Egger intercept; P***, represents P for MR-PRESSO global test.

The validation analysis using genetic variants of OSA (Campos et al) yielded similar results. Notably, heterogeneity was observed in the sensitivity analysis for OSA (Campos et al) and VTE ( p * = 0.018). However, considering the random-effects IVW model employed, the level of heterogeneity was deemed acceptable. 28 Despite the presence of outliers suggested by the MR-PRESSO global test ( p  = 0.015), no significant association between OSA and VTE (OR: 1.071, 95% CI: 0.917–1.251, p  = 0.396) was found after excluding an outlier (rs7106583). In addition, none of the three complementary MR methods supported a genetic association between OSA and VTE.

Effects of VTE on OSA

We conducted reverse MR analysis to further evaluate the effects of VTE (including PE and DVT) on OSA. Both MR analyses yielded consistent results, indicating no significant effects of VTE, PE, and DVT on OSA (see Fig. 3 ). Moreover, the Cochran Q test revealed no heterogeneity (all p * > 0.05), and both the MR–Egger intercept test and the MR-PRESSO global test found no evidence of pleiotropy (all p ** > 0.05 and p *** > 0.05, respectively) (see Fig. 3 ). In summary, a range of sensitivities confirmed the reliability of the MR results.

The genetic association of VTE/PE/DVT with OSA. OSA, obstructive sleep apnea; VTE, venous thromboembolism; PE, pulmonary embolism; DVT, deep vein thrombosis; MR, mendelian randomization; IVW, inverse variance weighted; PRESSO, pleiotropy residual sum and outlier; P*, represents P for heterogeneity test; P**, represents P for MR-Egger intercept; P***, represents P for MR-PRESSO global test.

Discussion

In this study, we conducted a comprehensive two-sample MR analysis to explore the genetic association between OSA and VTE. Our MR findings did not yield evidence of a significant association between OSA and VTE from a genetic standpoint.

Our findings contradict some previous observational studies suggesting a link between susceptibility to OSA and an increased risk of VTE. 29 30 31 32

However, these studies were hindered by inadequate consideration of confounding factors, particularly obesity, along with methodological flaws and small sample sizes. Obesity is widely recognized as a significant risk factor for both OSA 33 and VTE. 34 Therefore, it is crucial not to overlook the impact of obesity in striving for a deeper understanding of the potential association between OSA and VTE. Notably, a cohort study involving 31,309 subjects indicated a higher likelihood of VTE development among patients with more severe OSA. Yet, this association disappeared upon adjusting for confounders, notably obesity levels. 35 Thus, it is plausible that the observed association between OSA and VTE could be attributed to obesity confounding. Additionally, Aman and his colleagues' report yielded consistent results, suggesting that OSA does not elevate the risk of VTE after adjusting for obesity confounding. 36

MR is a robust analytical method that employs genetic variation as IVs to deduce the genetic association between exposure and outcome. Consequently, it effectively controls for confounders induced by environmental factors and mitigates reverse causality bias. In this study, we meticulously screened genetic variants and thoroughly accounted for the effects of obesity levels to procure reliable IVs for inferring the genetic association between OSA and VTE. To mitigate bias and enhance the reliability of our MR findings, we devised initial and validation MR analyses supplemented by a series of sensitivity analyses, drawing upon datasets sourced from various origins. Notably, neither MR analysis provided evidence supporting a genetic association between OSA and VTE. Moreover, a succession of sensitivity analyses served to bolster the robustness of our MR results. These findings indicate that, although diverging from some previous observational studies, our results are reliable and corroborate the conclusions drawn from the MR study.

While our MR study did not find evidence supporting a genetic association between OSA and VTE, it remains possible that OSA could influence the onset or progression of VTE. Virchow's triad depicts three major factors inducing VTE: endothelial injury, venous stasis, and hypercoagulability. 37 The pathophysiologic mechanism linking OSA and VTE remains unknown but may be associated with OSA's capacity to affect the three classical mechanistic pathways of Virchow's triad. 38 Intermittent hypoxia, a signature feature of OSA, can induce oxidative stress and activate inflammatory markers, further damaging the vascular endothelium. 39 40 OSA-associated hemodynamic alterations and reduced physical activities may result in venous stasis. 41 A growing number of studies have demonstrated a strong correlation between OSA and hypercoagulability. A retrospective cohort study aimed at assessing coagulation in patients with OSA suggested that patients with moderate to severe OSA experienced elevated markers of blood coagulability, primarily evidenced by shortened prothrombin time, compared to healthy individuals. 42 Two additional studies of thrombotic parameters found that patients with OSA possessed higher levels of the thrombin–antithrombin complex. 43 44 Furthermore, several coagulation factors, such as fibrinogen, coagulation factor VII, coagulation factor XII, and vascular hemophilic factor, which play a crucial role in the coagulation process, are elevated in patients with OSA. 45 Collectively, this evidence supports that patients with OSA are in a state of hypercoagulability, facilitating our understanding of the underlying pathophysiologic mechanisms between OSA and VTE. Considering these potential mechanisms, future large-scale studies are necessary to thoroughly explore the potential association between OSA and VTE, delving into greater depth.

The greatest strength of this study is that the bidirectional two-sample MR analysis designed based on summary data from large-scale GWAS was used for the first time to investigate the genetic association between OSA and VTE. Furthermore, to bolster the robustness of the findings and mitigate bias, we conducted initial and validated MR analyses using two independent OSA GWAS datasets. Subsequently, a series of sensitivity analyses provided further validation and affirmed the robustness of the results. However, our study also has several limitations. First, it was exclusively centered on European individuals, thereby constraining the generalizability of our findings to other ethnicities or ancestries. Second, the lack of individual-level data in the summary-level statistics prevented us from stratifying the study population by important factors such as age or sex. Lastly, there is a possibility of sample overlap between the exposure and outcome datasets, but the F-statistics of the IVs selected in the MR analysis were sufficiently strong to mitigate the potential effects of weak instrumental bias.

Conclusion

In conclusion, our MR study did not uncover genetic evidence supporting an association between OSA and VTE, including DVT and PE. This implies that the association between OSA and VTE reported in some previous observational studies may rely on alternative pathways to function, rather than being directly linked to the diseases themselves.

What is known about this topic?

Previous studies have linked obstructive sleep apnea (OSA) and venous thromboembolism (VTE).

Existing studies regarding the association between OSA and VTE are somewhat controversial.

The various aspects of the association between OSA and VTE remain to be evaluated.

What does this paper add?

There were no significant effects of OSA on VTE.

Similarly, VTE also had no significant effects on OSA.

The association between OSA and VTE may arise through pathways other than the diseases themselves.

Acknowledgment

We would also like to thank Yao Xiaoxia from Lianjiang No.3 Middle School for correcting the grammar in this article.

Conflict of Interest None declared.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

Authors' Contribution

All authors listed have made a substantial, direct, and intellectual contribution to the work, and approved it for publication.

These authors contributed equally to this study.

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