Causal Relationships between Overall and Abdominal Obesity and Varicose Veins: A Two- Sample Mendelian Randomization Study

Causal Relationships between Overall and Abdominal Obesity and Varicose Veins: A Two- Sample Mendelian Randomization Study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Causal Relationships between Overall and Abdominal Obesity and Varicose Veins: A Two- Sample Mendelian Randomization Study Shuo Tan, Kuang Peng, Juling Feng, Zhihui Li, Feiyu Zhao, Boling Li, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3968832/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose The association between obesity and varicose veins is recognized; however, the specific causal links between different types of obesity and varicose veins remain unclear. Our study explores the causal effects of general and abdominal obesity on varicose veins through Mendelian randomization. Methods We conducted univariable (UVMR) and multivariable (MVMR) Mendelian randomization, using body mass index (BMI) and waist circumference (WC) as proxies for general and abdominal obesity, respectively. The Mendelian randomization analysis utilized genome-wide association study (GWAS) data from the UK Biobank (UKB) and FinnGen. Instrumental variables were identified from SNP data, requiring strong association (P < 5e–8) and independence (r2 < 0.001). Inverse variance weighted (IVW) analysis was the primary method for causal inference. Extensive sensitivity analyses were also performed to confirm the validity of our results. Results UVMR showed a causal link between higher BMI and increased incidence of varicose veins (OR = 1.304, CI = 1.209–1.407, P = 6.778e-12), while WC was similarly associated (OR = 1.478, CI = 1.335–1.636, P = 5.092e-14). In MVMR analyses controlling for BMI, WC was found to have a direct causal effect on varicose veins (OR = 1.654, 95% CI: 1.066–2.568, P = 0.0248). After adjusting for WC, the data did not support a direct causal link between BMI and varicose veins (OR = 0.899, 95% CI: 0.632–1.277, P = 0.0551). Conclusion This study suggests that WC might be a more precise indicator of the relationship between obesity and varicose veins compared to BMI. Mendelian randomization body mass index waist circumference varicose veins Obesity Figures Figure 1 Figure 2 Figure 3 Figure 4 1. Introduction Varicose veins represent a prevalent chronic venous disorder, affecting over 30% of the population in Western countries[ 26 ]. This condition is not only associated with symptoms like pain and discomfort but also leads to complications, including venous ulcers, imposing a substantial burden on healthcare systems and societal welfare. The development of varicose veins is often attributed to valve insufficiency, alterations in the venous wall, and hemodynamic shifts, which collectively contribute to venous reflux disorders[ 22 ]. Identified risk factors for varicose veins encompass aging, pregnancy, obesity, and height[ 10 , 25 ]. Notably, obesity not only markedly elevates the risk of lower extremity varicose veins but also escalates the incidence of related complications[ 18 , 31 ]. Furthermore, obesity may mask the symptoms of varicose veins, thereby delaying treatment seeking. The pathophysiological link between obesity and varicose veins is frequently ascribed to chronic inflammation and heightened intra-abdominal pressure[ 21 ]. While previous research predominantly utilized BMI as the obesity metric, BMI primarily indicates overall obesity without adequately addressing the influence of fat distribution on varicose vein risk. Generally, relying solely on BMI to evaluate obesity can be imprecise, particularly in the context of abdominal obesity[ 8 , 9 ]. There is accumulating evidence suggesting that a combination of BMI and WC offers a more comprehensive assessment of obesity[ 15 ]. WC, a widely accepted measure of abdominal obesity, is both straightforward and convenient to gauge. The integration of BMI and WC is increasingly recognized as a superior approach for obesity evaluation[ 7 ]. However, previous studies have not extensively explored the association between abdominal obesity and varicose veins, resulting in a dearth of research in this area. To elucidate the relationship between different forms of obesity and varicose veins, we utilized Mendelian randomization, a genetic epidemiology technique frequently applied to investigate the link between an exposure (risk factor) and an outcome (disease)[ 1 ]. This method employs single-nucleotide polymorphisms (SNPs) as instrumental variables to establish causal relationships between risk factors and outcomes, effectively mitigating the impact of unmeasured confounding factors and reverse causation[ 4 , 30 ]. Through the Mendelian randomization approach, we aimed to rigorously assess the causal connection between obesity, particularly abdominal obesity, and the heightened risk of varicose veins. 2. Materials and Methods 2.1 Mendelian Randomization (MR) Design The premise of MR is that different genotypes determine different intermediate phenotypes. Therefore, the association between genotype and disease can accurately reflect the impact of exposure on the disease[ 6 ]. To deduce cause and effect correctly and rationally, the instrumental variable (IV) in Mendelian randomization must satisfy three core assumptions: (1) It should be strongly associated with the exposure; (2) It must be independent of any confounders that influence both the exposure and the outcome; (3) It should affect the outcome exclusively through the exposure, without any pleiotropic effects. 2.2 Genetic Instrument Selection To adhere to the first MR assumption, we selected single-nucleotide polymorphisms (SNPs) that met the genome-wide significance threshold (P 0.001 and a clumping window of less than 10,000 kb. Subsequently, we harmonized SNPs in the exposure and outcome datasets according to their coding and reference alleles. To ensure a robust correlation between IVs and exposures, we computed the proportion of variance explained by all SNPs using the F-statistic. The F-statistic was calculated using the following formula. F= \(\frac{\text{R}²\times (\text{N}-2)}{1-\text{R}²}\) R 2 = \(\frac{2\times {\beta }²\times \text{E}\text{A}\text{F}\times (1-\text{E}\text{A}\text{F})}{2\times {{\beta }}^{2}\times \text{E}\text{A}\text{F}\times \left(1-\text{E}\text{A}\text{F}\right)+2\times \text{S}\text{E}²\times \text{N}\times \text{E}\text{A}\text{F}\times (1-\text{E}\text{A}\text{F})}\) Where R2 represents the proportion of variance explained, N denotes the sample size, EAF is the effect allele frequency, and β is the estimated effect size of the SNP [ 11 , 17 , 20 ]. An F-statistic exceeding 10 is considered indicative of sufficient instrument strength. Detailed information on the F-statistic, specific SNPs, and their respective R2 values is provided in the Supplementary table 5 . 2.3 Data Sources To mitigate the impact of race as a confounder, our analysis was confined to summary statistics from individuals of European ancestry. This approach was adopted to ensure a more homogenous genetic background in the study population. For the assessment of generalized and abdominal obesity, we utilized BMI and WC, respectively. The summary statistics for these metrics were sourced from the UK Biobank (UKB), which boasts the largest sample size for such measurements. Specifically, the UKB provided BMI data for 461,460 individuals (GWAS ID: ukb-b-19953) and WC data for 462,166 individuals (GWAS ID: ukb-b-9405). The genome-wide association study (GWAS) data for BMI and WC are available in the IEU GWAS database ( https://gwas.mrcieu.ac.uk/ ). For the outcome variable of varicose veins, we obtained GWAS summary statistics from the FinnGen Consortium Release 9 (R9) publication data. The FinnGen dataset on varicose veins encompassed 29,539 cases and 324,121 controls (index endpoint: finngen_R9_I9_VARICVE). In this cohort, varicose veins were identified using the International Classification of Diseases, 10th Revision (ICD-10) code I83, which specifically denotes varicose veins of the lower extremities. The FinnGen study, initiated in 2017, is a comprehensive national cohort study in Finland, gathering genetic and health record data from a wide array of participants ( https://www.finngen.fi/en ). 2.4 Statistical Analysis We performed Two-Sample Mendelian Randomization (TSMR) analyses for both BMI and WC to determine their total causal effects on the risk of varicose veins (Fig. 1 ). Initially, MR-PRESSO was applied to identify and remove outlier SNPs[ 29 ]. The primary analysis used the Inverse-Variance Weighted (IVW) method as the principal MR technique to explore the impact of genetically determined BMI and WC on varicose vein risk. The IVW method analyses each Wald ratio and provides consistent estimates of causal effects when all instrumental variables are valid[ 13 ]. Additionally, complementary analyses such as MR-Egger, weighted median, simple mode, and weighted mode were also utilized. To verify the third MR assumption – that the instrumental variables affect the outcome solely through the exposure – we used the Cochran Q statistics to evaluate the heterogeneity of effects across independent SNPs[ 3 ]. The MR-Egger intercept test was employed to assess the presence of directional pleiotropy[ 2 ]. A p-value greater than 0.05 for the intercept term in the MR-Egger intercept test suggests an absence of horizontal pleiotropy. Furthermore, heterogeneity and stability among SNPs were examined using Cochrane's Q test, funnel plots, and leave-one-out analyses for both the IVW and MR-Egger methods. The presence of heterogeneity is indicated by a p-value less than 0.05 in Cochrane's Q test, prompting the use of random-effects models in IVW analyses; in the absence of heterogeneity, fixed-effect IVW models are appropriate. The MR–Steiger filtering test was also implemented to rule out confounders more strongly correlated with varicose veins than BMI and WC[ 14 ]. For significant TSMR results, we conducted multivariable MR (MVMR) analyses for BMI and WC. This involved combining the GWAS data for BMI and WC, followed by clumping based on linkage disequilibrium with an r2 < 0.001 and a clump window of 10,000 kb. The outcomes of the MVMR analyses were reported using the IVW MR method. All statistical analyses were conducted using the TwoSampleMR (version 0.5.7) and MRPRESSO (version 1.0) packages within the R software environment (version 4.3.1). We adopted the Bonferroni correction method, deeming p-values less than 0.025 as statistically significant and indicative of a potential causal relationship. 3. Results A total of 436 and 362 single-nucleotide polymorphisms (SNPs) were selected as genetic instruments for BMI and WC, respectively. The instrument strength was assessed using F-statistics, with the minimum F-statistic for each SNP surpassing the threshold of 10, as detailed in the Supplementary table 5 . Information on the selected SNPs is available in the supporting materials. The results of the MR analysis are shown in Fig. 4 and Supplementary Table 1–4 3.1 Causal Effect of BMI on Varicose Veins Initially, the study examined the relationship between BMI and varicose veins. MR-PRESSO identified four significant outliers (SNPs: rs2074613, rs2076603, rs3742305, and rs7420531). Following the exclusion of these outliers, no further outliers were observed in the funnel plot (Fig. 2 ). Due to the presence of heterogeneity among the instrumental variables (as indicated by a p-value < 0.05 in Cochran's Q statistic), random-effects IVW models were utilized. The analysis revealed a positive association between genetically predicted BMI and the risk of varicose veins. Specifically, a higher BMI was associated with an increased risk of varicose veins [odds ratio (OR) = 1.304, 95% confidence interval (CI) = 1.209–1.407, P = 6.778e-12, using the random-effects IVW method]. This finding was consistent across various methods including MR-Egger, weighted median, and weighted mode (Fig. 4 ). Sensitivity analyses indicated no evidence of directional pleiotropy (MR-Egger intercept = -3.510e-3; SE = 0.002; P = 0.057) (Figs. 3 and 4 ). The MR-Steiger filtering test did not lead to the exclusion of any variants, and the outcomes remained consistent (Supplementary table 5 ). Leave-one-out plots demonstrated that no individual SNP significantly influenced the overall effect estimate (Supplementary Table 1). 3.2 Causal Effect of WC on Varicose Veins Subsequently, the causal link between WC and varicose veins was analyzed. MR-PRESSO identified seven significant outliers (SNPs: rs10236214, rs13322435, rs13410783, rs35681682, rs7171864, rs76895963, rs9814758), which were subsequently removed. No outliers were observed in the funnel plot (Fig. 2 ) following this adjustment. Given that the p-value for Cochran’s Q statistic was less than 0.05, indicating heterogeneity among the instrumental variables, random-effects IVW models were applied. The results demonstrated a significant causal association between WC and varicose veins [odds ratio (OR) = 1.478, 95% confidence interval (CI) = 1.335–1.636, P = 5.092e-14] (Fig. 4 ). The MR-Egger intercept indicated no significant pleiotropy for WC (MR-Egger intercept = -2.822e-3; SE = 0.002; P = 0.218) (Figs. 3 and 4 ). Data validation using the MR-Steiger filtering test (Supplementary table 5 ) and the SNP leave-one-out method (Supplementary Table 3) did not result in the exclusion of any SNPs. 3.3 MVMR Analysis Lastly, IVW Multivariable Mendelian Randomization (MVMR) analyses were conducted to assess the direct causal impact of genetically predicted BMI and WC on the risk of varicose veins. In MVMR analyses that controlled for BMI, a significant causal effect of WC on the risk of varicose veins was observed (OR = 1.654, 95% CI: 1.066–2.568, P = 0.0248) (Table 1). Conversely, after adjusting for WC, the evidence was insufficient to establish a direct causal relationship between BMI and varicose veins (OR = 0.899, 95% CI: 0.632–1.277, P = 0.0551) (Table 1). 4. Discussion This study delves into the relationship between different types of obesity and varicose veins, a topic necessitating further exploration. Employing MR analysis, we investigated the associations of overall obesity (as indicated by BMI) and abdominal obesity (as measured by WC) with varicose veins. The Two-Sample Mendelian Randomization (TSMR) analysis revealed that both BMI and WC are associated with an increased genetic predisposition to varicose veins. Interestingly, in the Multivariable Mendelian Randomization (MVMR) analysis, a causal relationship between WC and varicose veins persisted even after adjusting for BMI. In contrast, the correlation between BMI and varicose veins significantly diminished after controlling for WC. Furthermore, the robustness of our results was reinforced through a series of sensitivity tests, including tests for pleiotropy and leave-one-out sensitivity analyses. To our knowledge, this is the first study to use Mendelian randomization to investigate the causal relationships between overall obesity, abdominal obesity, and varicose veins. Varicose veins constitute a prevalent chronic venous disorder with significant implications for human health. Obesity is a global public health challenge[ 27 ], and previous research has indicated its role not only in increasing the risk of varicose veins but also in contributing to the progression of related complications[ 32 ]. Our findings substantiate a causal link between obesity and varicose veins, thereby augmenting the existing body of evidence. The connection between obesity and varicose veins could be explained through several potential biological mechanisms. Firstly, obesity, particularly abdominal obesity, can elevate intra-abdominal pressure, which may impede lower limb venous return or cause venous dysfunction, leading to varicose veins[ 23 ]. Secondly, obesity is often associated with dyslipidemia, which can increase blood viscosity and result in hemodynamic disturbances[ 12 ]. Finally, obesity can induce a range of inflammatory factors that adversely affect the vascular wall[ 5 ]. Our findings suggest that abdominal obesity may exert a more pronounced impact on these factors compared to overall obesity. In recent years, the critical role of abdominal obesity in various diseases has gained increasing recognition[ 24 ]. While BMI is a key metric for assessing overall obesity, its ability to accurately represent fat distribution is limited[ 28 ]. Recognizing this limitation, the World Health Organization has advocated for research into aspects of abdominal obesity, such as WC, to complement the insights provided by BMI[ 19 ]. This study, focusing on the relationship between overall obesity (as measured by BMI) and abdominal obesity (as indicated by WC) with varicose veins, contributes valuable information for the prediction of varicose veins using obesity indicators. An observational study findings revealed that abdominal obesity could induce structural and hemodynamic changes in the lower limb veins even in the absence of classic reflux [ 16 ]. This suggests that abdominal obesity might be a more critical factor in the development of varicose veins than previously understood. Such insights highlight the importance of considering both overall and abdominal obesity when evaluating the risk and mechanisms underlying varicose veins. This dual approach can offer a more nuanced understanding of the interplay between different forms of obesity and vascular health. In this study, we utilized both univariate and multivariate Mendelian Randomization (MR) analyses to investigate the effects of overall and abdominal obesity on varicose veins. The MR approach significantly reduces the risk of bias, a notable limitation in previously published observational studies. Importantly, while prior studies have identified correlations between obesity and varicose veins, they have fallen short of establishing causal relationships. To address this gap, our MR analysis, leveraging a large-sample GWAS database, evaluated the causal relationship between obesity and varicose veins. Distinct from previous research that predominantly focused on BMI, our study incorporated both overall and abdominal obesity, with an emphasis on the latter. The inclusion of abdominal obesity metrics offers more comprehensive insights for assessing the relationship between obesity and varicose veins. Our results indicate causal relationships between both BMI and WC with varicose veins, with further Multivariable Mendelian Randomization (MVMR) analysis suggesting a stronger correlation for WC. This study is pioneering in using MR analysis to explore the genetic causal relationship between overall obesity, abdominal obesity, and varicose veins. A key strength of our study is the ability of MR analysis to control for confounding factors and causal biases that are unaddressable in observational studies. However, there are limitations to consider. To mitigate the bias from population stratification, our study exclusively involved European populations, which raises questions about the generalizability of our findings to other ethnic groups. Additionally, as our data sources were public databases, we did not conduct separate causal analyses for men and women. Finally, due to data limitations, our study does not address the influence of obesity on the severity of varicose veins. Further research, incorporating diverse populations and more detailed data, is required to build upon our findings and broaden their applicability. 5. Conclusions In summary, this study substantiates the role of both systemic and abdominal obesity in the development of varicose veins. Our findings indicate that high BMI and WC are potential causal risk factors for varicose veins, with the association between WC and varicose veins being more pronounced than that with BMI. These insights underscore the importance of weight management in reducing the risk of varicose veins. Particularly for individuals with a larger WC, a targeted focus on controlling abdominal obesity could be crucial. This research not only contributes to our understanding of the etiology of varicose veins but also highlights the significance of considering different types of obesity in preventative health strategies. Declarations Acknowledgements We thank all researchers and participants from the FinnGen consortium and also thank all the researchers who contributed to the IEU OpenGWAS project. Author contributions Shuo Tan provided the overall design of the study and drafted the main manuscript text. Lei Zhao supervised the progress of the implementation. Kuang Peng reviewed and edited the manuscript. Zhihui Li and Feiyu Zhao performed the main analysis of this study. Boling Li and Xiaotong Tan contributed to the data collection and statistical analysis. Jingfeng Ma collated the results into the table. All authors reviewed the manuscript. Funding This work was supported by The Joint Project of Natural Science Foundation of Hunan Province [Grant No.2023JJ60369], The National Natural Science Foundation of China [Grant No.81900488], Research Project of Hunan Provincial Health Commission [Grant No. 202104010694]. Data Availability Data supporting the findings of this study are available within the paper and its supplementary information files. All the GWAS data can be found in online repositories (https://gwas.mrcieu.ac.uk/ and https://www.finngen.fi/en) Competing interests All authors declare no competing interests. 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Cancer Epidemiol 27:995–1010. https://doi.org/10.1158/1055-9965.EPI-17-1177 Yin C, Tang F, Lao J et al (2024) Risk factors for venous ulceration in patients with varicose veins of lower extremities. Wound Repair Regen 32:47–54. https://doi.org/10.1111/wrr.13139 Yuan S, Bruzelius M, Xiong Y et al (2021) Overall and abdominal obesity in relation to venous thromboembolism. J Thromb Haemost 19:460–469. https://doi.org/10.1111/jth.15168 Additional Declarations No competing interests reported. Supplementary Files supplementarytable1.pdf supplementarytable2.pdf supplementarytable3.pdf supplementarytable4.pdf supplementarytable5.xlsx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3968832","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":276435309,"identity":"2aa37f93-35ab-46ed-99a5-cd63c7965148","order_by":0,"name":"Shuo Tan","email":"","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Shuo","middleName":"","lastName":"Tan","suffix":""},{"id":276435310,"identity":"69daf746-66d8-41ba-a388-12779e8bf653","order_by":1,"name":"Kuang Peng","email":"","orcid":"","institution":"Department of Cardiovascular, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Kuang","middleName":"","lastName":"Peng","suffix":""},{"id":276435311,"identity":"597e0cc1-9a13-4315-aa08-fff7955a9b34","order_by":2,"name":"Juling Feng","email":"","orcid":"","institution":"Department of diagnostics, School of basic medical sciences, Hengyang Medical School, University of South China, Hengyang, Hunan, 421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Juling","middleName":"","lastName":"Feng","suffix":""},{"id":276435312,"identity":"adc6536e-600b-42d7-8180-cd7910a5eb8d","order_by":3,"name":"Zhihui Li","email":"","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Zhihui","middleName":"","lastName":"Li","suffix":""},{"id":276435313,"identity":"764e9593-9bf8-426d-8167-02902006a81b","order_by":4,"name":"Feiyu Zhao","email":"","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Feiyu","middleName":"","lastName":"Zhao","suffix":""},{"id":276435314,"identity":"6ea2587f-b637-4d0a-ad8d-50e622b50dcf","order_by":5,"name":"Boling Li","email":"","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Boling","middleName":"","lastName":"Li","suffix":""},{"id":276435315,"identity":"259dd453-c708-45db-b715-a8999cf30dc6","order_by":6,"name":"Xiaotong Tan","email":"","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Xiaotong","middleName":"","lastName":"Tan","suffix":""},{"id":276435316,"identity":"82a51455-a2ca-4356-8ac2-c40992565072","order_by":7,"name":"Jingfeng Ma","email":"","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":false,"prefix":"","firstName":"Jingfeng","middleName":"","lastName":"Ma","suffix":""},{"id":276435317,"identity":"ba69bd70-923d-47a4-b39b-760a6c620043","order_by":8,"name":"Lei Zhao","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+UlEQVRIie3QsUoDMRjA8RyB3PJ5rl+IXF/hk4wWfAEfIkFw6tAHKHhH4Dp1v76FU+eWwnWp+7n1EJwLBakgaLCjkCu4OOQPyRD4JeRjLBb7h13ypNwZGoJI3fJ0tOwhcuoc7ccPeQaNOY/QdlPJer/WOd7ReYS11mkgbiuEd3mcsDxrTXIYB0RS2/IVSNhKzRYKGqZla7iqA4Tjzytgq6vnhUoKZp9aIzgEiEB/P5DfcfQmPwr22EsAVv77RFrgSOBFwQz1EUxLP2QyuYBG30CD1/Nt51SI3K7Tbmc+v2Awdd3LcTIcZJv71SFEfr3qlx9CLBaLxf7WN7+iSzG8mdlfAAAAAElFTkSuQmCC","orcid":"","institution":"Department of Gastrointestinal Surgery, The First Affiliated Hospital, Hengyang Medical School, University of South China, Hengyang, Hunan,421001, China.","correspondingAuthor":true,"prefix":"","firstName":"Lei","middleName":"","lastName":"Zhao","suffix":""}],"badges":[],"createdAt":"2024-02-19 04:07:18","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3968832/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3968832/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52137263,"identity":"11a307bb-3c99-4e88-b931-21dab6c95c7b","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":235520,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic representation of the study design. BMI, body mass index; WC, waist circumference; SNPs, single nucleotide polymorphisms\u003c/p\u003e","description":"","filename":"fig.1.png","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/02bcf4a20b25b866beb0a6e1.png"},{"id":52137268,"identity":"dce74063-ddee-4789-b2a3-091f9f7ce5a2","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":501643,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plots to assess the pleiotropy of observed causal associations between varicose veins and each of the following obesity-related anthropometric traits: (a) body mass index, (b) waist circumference\u003c/p\u003e","description":"","filename":"fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/b68639f725910520a7eaf681.png"},{"id":52137265,"identity":"46f5e14a-2cd6-48c8-a798-64b65449af74","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":489642,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plots to assess causal associations between varicose veins and each of the following obesity-related anthropometric traits: (a) body mass index, (b) waist circumference\u003c/p\u003e","description":"","filename":"fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/d9483598bdce5434f4bf2114.png"},{"id":52137269,"identity":"ebba37c6-b251-43fc-bdc7-2ad2e5062e7b","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":386530,"visible":true,"origin":"","legend":"\u003cp\u003eForest plot of Mendelian randomization results of obesity effect on varicose veins. BMI, body mass index; WC, waist circumference. OR (95%CI), OR (lower limit of 95% CI - 95% upper limit of 95% CI); mre, multiplicative random effects model.\u003c/p\u003e","description":"","filename":"fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/f665485da0acd41f9e41373d.png"},{"id":69608035,"identity":"17dcd03d-e111-4c16-b370-ee53f18d9178","added_by":"auto","created_at":"2024-11-22 07:47:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2086076,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/b551dad7-30ea-48ee-8c7b-6e4287109393.pdf"},{"id":52138521,"identity":"b22b46ce-e179-4930-ad60-e028d6bd175e","added_by":"auto","created_at":"2024-03-07 10:27:35","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":46215,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/f571445a8e7b4998da6119dc.pdf"},{"id":52137264,"identity":"a048c887-c063-4e2a-ab85-2022db3ecae4","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"pdf","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":46943,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable2.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/ec15f55786c3b1f61932a016.pdf"},{"id":52137267,"identity":"33a19479-f604-490b-980a-f411ecaa9e54","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"pdf","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":38694,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable3.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/47543d79b840c7bf06c14ef6.pdf"},{"id":52137270,"identity":"769da48d-f516-4b62-9095-c33329970a5d","added_by":"auto","created_at":"2024-03-07 10:19:35","extension":"pdf","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":39723,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable4.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/a42cb5bb2dbfa606666eb52f.pdf"},{"id":52137271,"identity":"da2859c1-f9e6-435b-906f-8a584d297771","added_by":"auto","created_at":"2024-03-07 10:19:36","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":272163,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable5.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-3968832/v1/bd5c5fffc5f4088542700d0b.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal Relationships between Overall and Abdominal Obesity and Varicose Veins: A Two- Sample Mendelian Randomization Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eVaricose veins represent a prevalent chronic venous disorder, affecting over 30% of the population in Western countries[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This condition is not only associated with symptoms like pain and discomfort but also leads to complications, including venous ulcers, imposing a substantial burden on healthcare systems and societal welfare. The development of varicose veins is often attributed to valve insufficiency, alterations in the venous wall, and hemodynamic shifts, which collectively contribute to venous reflux disorders[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. Identified risk factors for varicose veins encompass aging, pregnancy, obesity, and height[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Notably, obesity not only markedly elevates the risk of lower extremity varicose veins but also escalates the incidence of related complications[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]. Furthermore, obesity may mask the symptoms of varicose veins, thereby delaying treatment seeking. The pathophysiological link between obesity and varicose veins is frequently ascribed to chronic inflammation and heightened intra-abdominal pressure[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. While previous research predominantly utilized BMI as the obesity metric, BMI primarily indicates overall obesity without adequately addressing the influence of fat distribution on varicose vein risk.\u003c/p\u003e \u003cp\u003eGenerally, relying solely on BMI to evaluate obesity can be imprecise, particularly in the context of abdominal obesity[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. There is accumulating evidence suggesting that a combination of BMI and WC offers a more comprehensive assessment of obesity[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. WC, a widely accepted measure of abdominal obesity, is both straightforward and convenient to gauge. The integration of BMI and WC is increasingly recognized as a superior approach for obesity evaluation[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. However, previous studies have not extensively explored the association between abdominal obesity and varicose veins, resulting in a dearth of research in this area.\u003c/p\u003e \u003cp\u003eTo elucidate the relationship between different forms of obesity and varicose veins, we utilized Mendelian randomization, a genetic epidemiology technique frequently applied to investigate the link between an exposure (risk factor) and an outcome (disease)[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This method employs single-nucleotide polymorphisms (SNPs) as instrumental variables to establish causal relationships between risk factors and outcomes, effectively mitigating the impact of unmeasured confounding factors and reverse causation[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. Through the Mendelian randomization approach, we aimed to rigorously assess the causal connection between obesity, particularly abdominal obesity, and the heightened risk of varicose veins.\u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Mendelian Randomization (MR) Design\u003c/h2\u003e \u003cp\u003eThe premise of MR is that different genotypes determine different intermediate phenotypes. Therefore, the association between genotype and disease can accurately reflect the impact of exposure on the disease[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. To deduce cause and effect correctly and rationally, the instrumental variable (IV) in Mendelian randomization must satisfy three core assumptions: (1) It should be strongly associated with the exposure; (2) It must be independent of any confounders that influence both the exposure and the outcome; (3) It should affect the outcome exclusively through the exposure, without any pleiotropic effects.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Genetic Instrument Selection\u003c/h2\u003e \u003cp\u003eTo adhere to the first MR assumption, we selected single-nucleotide polymorphisms (SNPs) that met the genome-wide significance threshold (P\u0026thinsp;\u0026lt;\u0026thinsp;5 e\u0026ndash;8) and excluded SNPs exhibiting linkage disequilibrium (LD) with an r2\u0026thinsp;\u0026gt;\u0026thinsp;0.001 and a clumping window of less than 10,000 kb. Subsequently, we harmonized SNPs in the exposure and outcome datasets according to their coding and reference alleles. To ensure a robust correlation between IVs and exposures, we computed the proportion of variance explained by all SNPs using the F-statistic. The F-statistic was calculated using the following formula.\u003c/p\u003e \u003cp\u003eF=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{\\text{R}\u0026sup2;\\times (\\text{N}-2)}{1-\\text{R}\u0026sup2;}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eR\u003csup\u003e2\u003c/sup\u003e=\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\frac{2\\times {\\beta }\u0026sup2;\\times \\text{E}\\text{A}\\text{F}\\times (1-\\text{E}\\text{A}\\text{F})}{2\\times {{\\beta }}^{2}\\times \\text{E}\\text{A}\\text{F}\\times \\left(1-\\text{E}\\text{A}\\text{F}\\right)+2\\times \\text{S}\\text{E}\u0026sup2;\\times \\text{N}\\times \\text{E}\\text{A}\\text{F}\\times (1-\\text{E}\\text{A}\\text{F})}\\)\u003c/span\u003e\u003c/span\u003e\u003c/p\u003e \u003cp\u003eWhere R2 represents the proportion of variance explained, N denotes the sample size, EAF is the effect allele frequency, and β is the estimated effect size of the SNP [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. An F-statistic exceeding 10 is considered indicative of sufficient instrument strength. Detailed information on the F-statistic, specific SNPs, and their respective R2 values is provided in the Supplementary table \u003cspan refid=\"MOESM5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Data Sources\u003c/h2\u003e \u003cp\u003eTo mitigate the impact of race as a confounder, our analysis was confined to summary statistics from individuals of European ancestry. This approach was adopted to ensure a more homogenous genetic background in the study population. For the assessment of generalized and abdominal obesity, we utilized BMI and WC, respectively. The summary statistics for these metrics were sourced from the UK Biobank (UKB), which boasts the largest sample size for such measurements. Specifically, the UKB provided BMI data for 461,460 individuals (GWAS ID: ukb-b-19953) and WC data for 462,166 individuals (GWAS ID: ukb-b-9405). The genome-wide association study (GWAS) data for BMI and WC are available in the IEU GWAS database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eFor the outcome variable of varicose veins, we obtained GWAS summary statistics from the FinnGen Consortium Release 9 (R9) publication data. The FinnGen dataset on varicose veins encompassed 29,539 cases and 324,121 controls (index endpoint: finngen_R9_I9_VARICVE). In this cohort, varicose veins were identified using the International Classification of Diseases, 10th Revision (ICD-10) code I83, which specifically denotes varicose veins of the lower extremities. The FinnGen study, initiated in 2017, is a comprehensive national cohort study in Finland, gathering genetic and health record data from a wide array of participants (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.finngen.fi/en\u003c/span\u003e\u003cspan address=\"https://www.finngen.fi/en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Statistical Analysis\u003c/h2\u003e \u003cp\u003eWe performed Two-Sample Mendelian Randomization (TSMR) analyses for both BMI and WC to determine their total causal effects on the risk of varicose veins (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Initially, MR-PRESSO was applied to identify and remove outlier SNPs[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. The primary analysis used the Inverse-Variance Weighted (IVW) method as the principal MR technique to explore the impact of genetically determined BMI and WC on varicose vein risk. The IVW method analyses each Wald ratio and provides consistent estimates of causal effects when all instrumental variables are valid[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. Additionally, complementary analyses such as MR-Egger, weighted median, simple mode, and weighted mode were also utilized.\u003c/p\u003e \u003cp\u003eTo verify the third MR assumption \u0026ndash; that the instrumental variables affect the outcome solely through the exposure \u0026ndash; we used the Cochran Q statistics to evaluate the heterogeneity of effects across independent SNPs[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. The MR-Egger intercept test was employed to assess the presence of directional pleiotropy[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. A p-value greater than 0.05 for the intercept term in the MR-Egger intercept test suggests an absence of horizontal pleiotropy. Furthermore, heterogeneity and stability among SNPs were examined using Cochrane's Q test, funnel plots, and leave-one-out analyses for both the IVW and MR-Egger methods. The presence of heterogeneity is indicated by a p-value less than 0.05 in Cochrane's Q test, prompting the use of random-effects models in IVW analyses; in the absence of heterogeneity, fixed-effect IVW models are appropriate. The MR\u0026ndash;Steiger filtering test was also implemented to rule out confounders more strongly correlated with varicose veins than BMI and WC[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFor significant TSMR results, we conducted multivariable MR (MVMR) analyses for BMI and WC. This involved combining the GWAS data for BMI and WC, followed by clumping based on linkage disequilibrium with an r2\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and a clump window of 10,000 kb. The outcomes of the MVMR analyses were reported using the IVW MR method.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using the TwoSampleMR (version 0.5.7) and MRPRESSO (version 1.0) packages within the R software environment (version 4.3.1). We adopted the Bonferroni correction method, deeming p-values less than 0.025 as statistically significant and indicative of a potential causal relationship.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cp\u003eA total of 436 and 362 single-nucleotide polymorphisms (SNPs) were selected as genetic instruments for BMI and WC, respectively. The instrument strength was assessed using F-statistics, with the minimum F-statistic for each SNP surpassing the threshold of 10, as detailed in the Supplementary table \u003cspan\u003e5\u003c/span\u003e. Information on the selected SNPs is available in the supporting materials. The results of the MR analysis are shown in Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e and Supplementary Table\u0026nbsp;1\u0026ndash;4\u003c/p\u003e\n\u003cdiv id=\"Sec8\"\u003e\n \u003ch2\u003e3.1 Causal Effect of BMI on Varicose Veins\u003c/h2\u003e\n \u003cp\u003eInitially, the study examined the relationship between BMI and varicose veins. MR-PRESSO identified four significant outliers (SNPs: rs2074613, rs2076603, rs3742305, and rs7420531). Following the exclusion of these outliers, no further outliers were observed in the funnel plot (Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e). Due to the presence of heterogeneity among the instrumental variables (as indicated by a p-value\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in Cochran\u0026apos;s Q statistic), random-effects IVW models were utilized. The analysis revealed a positive association between genetically predicted BMI and the risk of varicose veins. Specifically, a higher BMI was associated with an increased risk of varicose veins [odds ratio (OR)\u0026thinsp;=\u0026thinsp;1.304, 95% confidence interval (CI)\u0026thinsp;=\u0026thinsp;1.209\u0026ndash;1.407, P\u0026thinsp;=\u0026thinsp;6.778e-12, using the random-effects IVW method]. This finding was consistent across various methods including MR-Egger, weighted median, and weighted mode (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e). Sensitivity analyses indicated no evidence of directional pleiotropy (MR-Egger intercept = -3.510e-3; SE\u0026thinsp;=\u0026thinsp;0.002; P\u0026thinsp;=\u0026thinsp;0.057) (Figs.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e and \u003cspan\u003e4\u003c/span\u003e). The MR-Steiger filtering test did not lead to the exclusion of any variants, and the outcomes remained consistent (Supplementary table \u003cspan\u003e5\u003c/span\u003e). Leave-one-out plots demonstrated that no individual SNP significantly influenced the overall effect estimate (Supplementary Table\u0026nbsp;1).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec9\"\u003e\n \u003ch2\u003e3.2 Causal Effect of WC on Varicose Veins\u003c/h2\u003e\n \u003cp\u003eSubsequently, the causal link between WC and varicose veins was analyzed. MR-PRESSO identified seven significant outliers (SNPs: rs10236214, rs13322435, rs13410783, rs35681682, rs7171864, rs76895963, rs9814758), which were subsequently removed. No outliers were observed in the funnel plot (Fig.\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e) following this adjustment. Given that the p-value for Cochran\u0026rsquo;s Q statistic was less than 0.05, indicating heterogeneity among the instrumental variables, random-effects IVW models were applied. The results demonstrated a significant causal association between WC and varicose veins [odds ratio (OR)\u0026thinsp;=\u0026thinsp;1.478, 95% confidence interval (CI)\u0026thinsp;=\u0026thinsp;1.335\u0026ndash;1.636, P\u0026thinsp;=\u0026thinsp;5.092e-14] (Fig.\u0026nbsp;\u003cspan\u003e4\u003c/span\u003e). The MR-Egger intercept indicated no significant pleiotropy for WC (MR-Egger intercept = -2.822e-3; SE\u0026thinsp;=\u0026thinsp;0.002; P\u0026thinsp;=\u0026thinsp;0.218) (Figs.\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e and \u003cspan\u003e4\u003c/span\u003e). Data validation using the MR-Steiger filtering test (Supplementary table \u003cspan\u003e5\u003c/span\u003e) and the SNP leave-one-out method (Supplementary Table\u0026nbsp;3) did not result in the exclusion of any SNPs.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003e3.3 MVMR Analysis\u003c/h2\u003e\n \u003cp\u003eLastly, IVW Multivariable Mendelian Randomization (MVMR) analyses were conducted to assess the direct causal impact of genetically predicted BMI and WC on the risk of varicose veins. In MVMR analyses that controlled for BMI, a significant causal effect of WC on the risk of varicose veins was observed (OR\u0026thinsp;=\u0026thinsp;1.654, 95% CI: 1.066\u0026ndash;2.568, P\u0026thinsp;=\u0026thinsp;0.0248) (Table\u0026nbsp;1). Conversely, after adjusting for WC, the evidence was insufficient to establish a direct causal relationship between BMI and varicose veins (OR\u0026thinsp;=\u0026thinsp;0.899, 95% CI: 0.632\u0026ndash;1.277, P\u0026thinsp;=\u0026thinsp;0.0551) (Table\u0026nbsp;1).\u003c/p\u003e\n \u003cp\u003e\u003cimg src=\"https://myfiles.space/user_files/122228_c8a1650c59388082/122228_custom_files/img1709806411.png\"\u003e\u003cbr\u003e\u003c/p\u003e\n \u003cdiv\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study delves into the relationship between different types of obesity and varicose veins, a topic necessitating further exploration. Employing MR analysis, we investigated the associations of overall obesity (as indicated by BMI) and abdominal obesity (as measured by WC) with varicose veins. The Two-Sample Mendelian Randomization (TSMR) analysis revealed that both BMI and WC are associated with an increased genetic predisposition to varicose veins. Interestingly, in the Multivariable Mendelian Randomization (MVMR) analysis, a causal relationship between WC and varicose veins persisted even after adjusting for BMI. In contrast, the correlation between BMI and varicose veins significantly diminished after controlling for WC. Furthermore, the robustness of our results was reinforced through a series of sensitivity tests, including tests for pleiotropy and leave-one-out sensitivity analyses. To our knowledge, this is the first study to use Mendelian randomization to investigate the causal relationships between overall obesity, abdominal obesity, and varicose veins.\u003c/p\u003e \u003cp\u003eVaricose veins constitute a prevalent chronic venous disorder with significant implications for human health. Obesity is a global public health challenge[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], and previous research has indicated its role not only in increasing the risk of varicose veins but also in contributing to the progression of related complications[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. Our findings substantiate a causal link between obesity and varicose veins, thereby augmenting the existing body of evidence. The connection between obesity and varicose veins could be explained through several potential biological mechanisms. Firstly, obesity, particularly abdominal obesity, can elevate intra-abdominal pressure, which may impede lower limb venous return or cause venous dysfunction, leading to varicose veins[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Secondly, obesity is often associated with dyslipidemia, which can increase blood viscosity and result in hemodynamic disturbances[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Finally, obesity can induce a range of inflammatory factors that adversely affect the vascular wall[\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Our findings suggest that abdominal obesity may exert a more pronounced impact on these factors compared to overall obesity.\u003c/p\u003e \u003cp\u003eIn recent years, the critical role of abdominal obesity in various diseases has gained increasing recognition[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. While BMI is a key metric for assessing overall obesity, its ability to accurately represent fat distribution is limited[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Recognizing this limitation, the World Health Organization has advocated for research into aspects of abdominal obesity, such as WC, to complement the insights provided by BMI[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. This study, focusing on the relationship between overall obesity (as measured by BMI) and abdominal obesity (as indicated by WC) with varicose veins, contributes valuable information for the prediction of varicose veins using obesity indicators.\u003c/p\u003e \u003cp\u003eAn observational study findings revealed that abdominal obesity could induce structural and hemodynamic changes in the lower limb veins even in the absence of classic reflux [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This suggests that abdominal obesity might be a more critical factor in the development of varicose veins than previously understood. Such insights highlight the importance of considering both overall and abdominal obesity when evaluating the risk and mechanisms underlying varicose veins. This dual approach can offer a more nuanced understanding of the interplay between different forms of obesity and vascular health.\u003c/p\u003e \u003cp\u003eIn this study, we utilized both univariate and multivariate Mendelian Randomization (MR) analyses to investigate the effects of overall and abdominal obesity on varicose veins. The MR approach significantly reduces the risk of bias, a notable limitation in previously published observational studies. Importantly, while prior studies have identified correlations between obesity and varicose veins, they have fallen short of establishing causal relationships. To address this gap, our MR analysis, leveraging a large-sample GWAS database, evaluated the causal relationship between obesity and varicose veins. Distinct from previous research that predominantly focused on BMI, our study incorporated both overall and abdominal obesity, with an emphasis on the latter. The inclusion of abdominal obesity metrics offers more comprehensive insights for assessing the relationship between obesity and varicose veins. Our results indicate causal relationships between both BMI and WC with varicose veins, with further Multivariable Mendelian Randomization (MVMR) analysis suggesting a stronger correlation for WC.\u003c/p\u003e \u003cp\u003eThis study is pioneering in using MR analysis to explore the genetic causal relationship between overall obesity, abdominal obesity, and varicose veins. A key strength of our study is the ability of MR analysis to control for confounding factors and causal biases that are unaddressable in observational studies. However, there are limitations to consider. To mitigate the bias from population stratification, our study exclusively involved European populations, which raises questions about the generalizability of our findings to other ethnic groups. Additionally, as our data sources were public databases, we did not conduct separate causal analyses for men and women. Finally, due to data limitations, our study does not address the influence of obesity on the severity of varicose veins. Further research, incorporating diverse populations and more detailed data, is required to build upon our findings and broaden their applicability.\u003c/p\u003e"},{"header":"5. Conclusions","content":"\u003cp\u003eIn summary, this study substantiates the role of both systemic and abdominal obesity in the development of varicose veins. Our findings indicate that high BMI and WC are potential causal risk factors for varicose veins, with the association between WC and varicose veins being more pronounced than that with BMI. These insights underscore the importance of weight management in reducing the risk of varicose veins. Particularly for individuals with a larger WC, a targeted focus on controlling abdominal obesity could be crucial. This research not only contributes to our understanding of the etiology of varicose veins but also highlights the significance of considering different types of obesity in preventative health strategies.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank all researchers and participants from the FinnGen consortium and also thank all the researchers who contributed to the IEU OpenGWAS project.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShuo Tan provided the overall design of the study and drafted the main manuscript text. Lei Zhao supervised the progress of the implementation. Kuang Peng reviewed and edited the manuscript. Zhihui Li and Feiyu Zhao performed the main analysis of this study. Boling Li and Xiaotong Tan contributed to the data collection and statistical analysis. Jingfeng Ma collated the results into the table. All authors reviewed the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis work was supported by The Joint Project of Natural Science Foundation of Hunan Province [Grant No.2023JJ60369], The National Natural Science Foundation of China [Grant No.81900488], Research Project of Hunan Provincial Health Commission [Grant No. 202104010694].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData supporting the findings of this study are available within the paper and its supplementary information files. All the GWAS data can be found in online repositories (https://gwas.mrcieu.ac.uk/ and https://www.finngen.fi/en)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical and informed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis article does not contain any studies involving human or animal subjects conducted by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor this type of study formal consent is not required.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eBirney E (2021) Mendelian randomization. Cold Spring Harbor Perspectives in Medicine 12:a041302. https://doi.org/10.1101/cshperspect.a041302\u003c/li\u003e\n\u003cli\u003eBowden J, Davey Smith G, Burgess S (2015) Mendelian randomization with invalid instruments: Effect estimation and bias detection through egger regression. Int J Epidemiol 44:512\u0026ndash;525. https://doi.org/10.1093/ije/dyv080\u003c/li\u003e\n\u003cli\u003eBurgess S, Butterworth A, Thompson SG (2013) Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol 37:658\u0026ndash;665. https://doi.org/10.1002/gepi.21758\u003c/li\u003e\n\u003cli\u003eBurgess S, Small DS, Thompson SG (2017) A review of instrumental variable estimators for mendelian randomization. Stat Methods Med Res 26:2333\u0026ndash;2355. https://doi.org/10.1177/0962280215597579\u003c/li\u003e\n\u003cli\u003eB\u0026uuml;schges J, Schaffrath Rosario A, Schienkiewitz A et al (2022) Vascular aging in the young: New carotid stiffness centiles and association with general and abdominal obesity \u0026ndash; the KIGGS cohort. Atherosclerosis 355:60\u0026ndash;67. https://doi.org/10.1016/j.atherosclerosis.2022.05.003\u003c/li\u003e\n\u003cli\u003eDavey Smith G, Hemani G (2014) Mendelian randomization: Genetic anchors for causal inference in epidemiological studies. Hum Mol Genet 23:R89\u0026ndash;R98. https://doi.org/10.1093/hmg/ddu328\u003c/li\u003e\n\u003cli\u003eDi Fusco SA, Mocini E, Gulizia MM et al (2024) ANMCO (italian association of hospital cardiologists) scientific statement: Obesity in adults\u0026mdash;an approach for cardiologists. Eating and Weight Disorders - Studies on Anorexia, Bulimia and Obesity 29:1. https://doi.org/10.1007/s40519-023-01630-8\u003c/li\u003e\n\u003cli\u003eFrank AP, De Souza Santos R, Palmer BF, Clegg DJ (2019) Determinants of body fat distribution in humans may provide insight about obesity-related health risks. J Lipid Res 60:1710\u0026ndash;1719. https://doi.org/10.1194/jlr.R086975\u003c/li\u003e\n\u003cli\u003eFrezza EE, Shebani KO, Robertson J, Wachtel MS (2007) Morbid obesity causes chronic increase of intraabdominal pressure. Digestive Diseases and Sciences 52:1038\u0026ndash;1041. https://doi.org/10.1007/s10620-006-9203-4\u003c/li\u003e\n\u003cli\u003eFukaya E, Flores AM, Lindholm D et al (2018) Clinical and genetic determinants of varicose veins: Prospective, community-based study of \u0026asymp;500 000 individuals. Circulation 138:2869\u0026ndash;2880. https://doi.org/10.1161/CIRCULATIONAHA.118.035584\u003c/li\u003e\n\u003cli\u003eGill D, Efstathiadou A, Cawood K et al (2019) Education protects against coronary heart disease and stroke independently of cognitive function: Evidence from mendelian randomization. Int J Epidemiol 48:1468\u0026ndash;1477. https://doi.org/10.1093/ije/dyz200\u003c/li\u003e\n\u003cli\u003eH\u0026auml;rdfeldt J, Cariello M, Simonelli S et al (2022) Abdominal obesity negatively influences key metrics of reverse cholesterol transport. Biochimica et Biophysica Acta (BBA) - Molecular and Cell Biology of Lipids 1867:159087. https://doi.org/10.1016/j.bbalip.2021.159087\u003c/li\u003e\n\u003cli\u003eHartwig FP, Davies NM, Hemani G, Davey Smith G (2016) Two-sample mendelian randomization: Avoiding the downsides of a powerful, widely applicable but potentially fallible technique. Int J Epidemiol 45:1717\u0026ndash;1726. https://doi.org/10.1093/ije/dyx028\u003c/li\u003e\n\u003cli\u003eHemani G, Tilling K, Davey Smith G (2017) Orienting the causal relationship between imprecisely measured traits using GWAS summary data. Plos Genet 13:e1007081. https://doi.org/10.1371/journal.pgen.1007081\u003c/li\u003e\n\u003cli\u003eJayedi A, Soltani S, Zargar MS et al (2020) Central fatness and risk of all cause mortality: Systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ 370:m3324. https://doi.org/10.1136/bmj.m3324\u003c/li\u003e\n\u003cli\u003eLangan EA, Wienandt M, Bayer A et al (2023) Effect of obesity on venous blood flow in the lower limbs. Journal der Deutschen Dermatologischen Gesellschaft 21:622\u0026ndash;629. https://doi.org/10.1111/ddg.15062\u003c/li\u003e\n\u003cli\u003eLevin MG, Judy R, Gill D et al (2020) Genetics of height and risk of atrial fibrillation: A mendelian randomization study. PLOS Medicine 17:e1003288. https://doi.org/10.1371/journal.pmed.1003288\u003c/li\u003e\n\u003cli\u003eMusil D, Kaletova M, Herman J (2011) Age, body mass index and severity of primary chronic venous disease. Biomedical Papers 155:367\u0026ndash;371. https://doi.org/10.5507/bp.2011.054\u003c/li\u003e\n\u003cli\u003eNishida C, Ko G, Kumanyika S (2010) Body fat distribution and noncommunicable diseases in populations: Overview of the 2008 WHO expert consultation on waist circumference and waist\u0026ndash;hip ratio. Eur J Clin Nutr 64:2\u0026ndash;5. https://doi.org/10.1038/ejcn.2009.139\u003c/li\u003e\n\u003cli\u003ePalmer TM, Lawlor DA, Harbord RM et al (2012) Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res 21:223\u0026ndash;242. https://doi.org/10.1177/0962280210394459\u003c/li\u003e\n\u003cli\u003ePfisterer L, K\u0026ouml;nig G, Hecker M, Korff T (2014) Pathogenesis of varicose veins - lessons from biomechanics. Vasa 43:88\u0026ndash;99. https://doi.org/10.1024/0301-1526/a000335\u003c/li\u003e\n\u003cli\u003eRaffetto JD (2018) Pathophysiology of chronic venous disease and venous ulcers. Surg Clin North Am 98:337\u0026ndash;347. https://doi.org/10.1016/j.suc.2017.11.002\u003c/li\u003e\n\u003cli\u003eRobertson LA, Evans CJ, Lee AJ et al (2014) Incidence and risk factors for venous reflux in the general population: Edinburgh vein study. Eur J Vasc Endovasc Surg 48:208\u0026ndash;214. https://doi.org/10.1016/j.ejvs.2014.05.017\u003c/li\u003e\n\u003cli\u003eRoss R, Neeland IJ, Yamashita S et al (2020) Waist circumference as a vital sign in clinical practice: A consensus statement from the IAS and ICCR working group on visceral obesity. Nat Rev Endocrinol 16:177\u0026ndash;189. https://doi.org/10.1038/s41574-019-0310-7\u003c/li\u003e\n\u003cli\u003eSegiet OA, Brzozowa-Zasada M, Piecuch A et al (2015) Biomolecular mechanisms in varicose veins development. Ann Vasc Surg 29:377\u0026ndash;384. https://doi.org/10.1016/j.avsg.2014.10.009\u003c/li\u003e\n\u003cli\u003eShadrina AS, Sharapov SZ, Shashkova TI, Tsepilov YA (2019) Varicose veins of lower extremities: Insights from the first large-scale genetic study. Plos Genet 15:e1008110. https://doi.org/10.1371/journal.pgen.1008110\u003c/li\u003e\n\u003cli\u003eThe Council of The Obesity Society (2008) Obesity as a disease: The obesity society council resolution. Obesity 16:1151\u0026ndash;1151. https://doi.org/10.1038/oby.2008.246\u003c/li\u003e\n\u003cli\u003eVan Rij AM, De Alwis CS, Jiang P et al (2008) Obesity and impaired venous function. Eur J Vasc Endovasc Surg 35:739\u0026ndash;744. https://doi.org/10.1016/j.ejvs.2008.01.006\u003c/li\u003e\n\u003cli\u003eVerbanck M, Chen C-Y, Neale B, Do R (2018) Detection of widespread horizontal pleiotropy in causal relationships inferred from mendelian randomization between complex traits and diseases. Nat Genet 50:693\u0026ndash;698. https://doi.org/10.1038/s41588-018-0099-7\u003c/li\u003e\n\u003cli\u003eYarmolinsky J, Wade KH, Richmond RC et al (2018) Causal inference in cancer epidemiology: What is the role of mendelian randomization? Cancer Epidemiol 27:995\u0026ndash;1010. https://doi.org/10.1158/1055-9965.EPI-17-1177\u003c/li\u003e\n\u003cli\u003eYin C, Tang F, Lao J et al (2024) Risk factors for venous ulceration in patients with varicose veins of lower extremities. Wound Repair Regen 32:47\u0026ndash;54. https://doi.org/10.1111/wrr.13139\u003c/li\u003e\n\u003cli\u003eYuan S, Bruzelius M, Xiong Y et al (2021) Overall and abdominal obesity in relation to venous thromboembolism. J Thromb Haemost 19:460\u0026ndash;469. https://doi.org/10.1111/jth.15168\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Mendelian randomization, body mass index, waist circumference, varicose veins, Obesity","lastPublishedDoi":"10.21203/rs.3.rs-3968832/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3968832/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThe association between obesity and varicose veins is recognized; however, the specific causal links between different types of obesity and varicose veins remain unclear. Our study explores the causal effects of general and abdominal obesity on varicose veins through Mendelian randomization.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted univariable (UVMR) and multivariable (MVMR) Mendelian randomization, using body mass index (BMI) and waist circumference (WC) as proxies for general and abdominal obesity, respectively. The Mendelian randomization analysis utilized genome-wide association study (GWAS) data from the UK Biobank (UKB) and FinnGen. Instrumental variables were identified from SNP data, requiring strong association (P\u0026thinsp;\u0026lt;\u0026thinsp;5e\u0026ndash;8) and independence (r2\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Inverse variance weighted (IVW) analysis was the primary method for causal inference. Extensive sensitivity analyses were also performed to confirm the validity of our results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eUVMR showed a causal link between higher BMI and increased incidence of varicose veins (OR\u0026thinsp;=\u0026thinsp;1.304, CI\u0026thinsp;=\u0026thinsp;1.209\u0026ndash;1.407, P\u0026thinsp;=\u0026thinsp;6.778e-12), while WC was similarly associated (OR\u0026thinsp;=\u0026thinsp;1.478, CI\u0026thinsp;=\u0026thinsp;1.335\u0026ndash;1.636, P\u0026thinsp;=\u0026thinsp;5.092e-14). In MVMR analyses controlling for BMI, WC was found to have a direct causal effect on varicose veins (OR\u0026thinsp;=\u0026thinsp;1.654, 95% CI: 1.066\u0026ndash;2.568, P\u0026thinsp;=\u0026thinsp;0.0248). After adjusting for WC, the data did not support a direct causal link between BMI and varicose veins (OR\u0026thinsp;=\u0026thinsp;0.899, 95% CI: 0.632\u0026ndash;1.277, P\u0026thinsp;=\u0026thinsp;0.0551).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThis study suggests that WC might be a more precise indicator of the relationship between obesity and varicose veins compared to BMI.\u003c/p\u003e","manuscriptTitle":"Causal Relationships between Overall and Abdominal Obesity and Varicose Veins: A Two- Sample Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-07 10:19:30","doi":"10.21203/rs.3.rs-3968832/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"1c2ff85c-a471-42ac-8a8d-0e84368ea40f","owner":[],"postedDate":"March 7th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-22T07:38:52+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-07 10:19:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3968832","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3968832","identity":"rs-3968832","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}