Causal Effect of Omega-3 on male infertility and female infertility: A Mendelian Randomization Study

Causal Effect of Omega-3 on male infertility and female infertility: A 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 Effect of Omega-3 on male infertility and female infertility: A Mendelian Randomization Study Yan Wang, Jiamin Chen, Zuogang Xie, Yali Bo, Lingyi wan, Wangqiang Chen This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3966971/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 The association between Omega-3 and human reproduction is uncertain. This Mendelian randomization (MR) study aims to examine the causal relationship between Omega-3 intake and male and female reproduction. We utilized summary statistics data from 120,550 male participants and 120,706 female participants in the FinnGen consortium. Summary statistics for Omega-3 were extracted from a genome-wide association study involving up to 445,562 participants predominantly of European ancestry. MR analysis employed established methods, including Inverse Variance Weighting (IVW), Weighted Median (WM), and MR-Egger. Genetic determination of male infertility [IVW odds ratio (OR) = 2.33, 95% confidence interval (CI) = 0.13, 42.03, P = 0.57] and female infertility [IVW odds ratio (OR) = 1.49, 95% CI = 0.13, 0.63, 3.54, P = 0.37] was not associated with Omega-3 intake. The result of MR study does not provide support for a causal impact of Omega-3 intake on male and female reproduction. Health sciences/Urology/Urogenital diseases/Male factor infertility Health sciences/Diseases/Reproductive disorders/Endocrine reproductive disorders Health sciences/Diseases/Reproductive disorders/Infertility polygenic risk docasahexaenoic acid male infertility female infertility UK biobank Figures Figure 1 Figure 2 Figure 3 1. Introduction In recent decades, Omega-3 has been widely employed globally as a dietary supplement, with a noticeable annual increase in usage, especially in developed countries over the last two decades 1 . In the United States, the proportion of individuals utilizing ω-3 fatty acids has surged from 12–26% 2,3 . Omega-3 polyunsaturated fatty acids (PUFAs) mainly include eicosapentaenoic acid (EPA; 20:5 ω-3), docosapentaenoic acid (DPA; 22:5 ω-3), and docosahex aenoic acid (DHA; 22:6 ω-3) 4 . Numerous studies have elucidated the relationship between Omega-3 (ω3) fatty acids and human health 5 , 6 , encompassing their potential to ameliorate conditions such as cardiovascular diseases 7 , diabetes 8 , Alzheimer's Disease and dementia 9 . As we entered the 21st century, infertility remained a prevalent challenge that demands significant human attention. Studies indicate that approximately 9.5–11.7% of couples in their reproductive years worldwide are affected by the impact of infertility 10 . In certain regions, the incidence of primary infertility has exhibited a notable increase compared to secondary infertility, such as in North Africa and the Middle East, particularly in Morocco and Yemen. However, in some areas, the prevalence of secondary infertility surpasses that of primary infertility, exemplified in Eastern Europe and Central Asia 11 . The prevalence of male-factor infertility demonstrates considerable global variability, extending from a low of 20% to as high as 70%. The proportion of infertile males within the male population is estimated to range from 2.5% and 12%. Among these, the highest incidence rates are documented in Africa, as well as in Central and Eastern European regions 12 . Humans have been endeavoring to treat infertility for millennia. In addition to pharmaceutical and surgical interventions, dietary supplements have emerged as a novel avenue for addressing human infertility, offering a promising direction in therapeutic approaches. In numerous previously published studies, dietary supplements such as antioxidant supplements, vitamins (including vitamin B12, vitamin E, vitamin C), dietary fats, and trace elements have been implicated in influencing male and female infertility. However, extant evidence concerning the impact of Omega-3 on human infertility exhibits certain limitations and, in some instances, even conflicting outcomes. A definitive conclusion regarding the impact of Omega-3 fatty acids on reproductive aspects has not yet been reached. In female animal models, supplementation with Omega-3 has been demonstrated to alter the prostaglandin biosynthetic pathway, potentially impacting steroidogenesis, follicle formation, and oocyte maturation, thereby improving female fertility 13 , 14 ; Concurrently, in male animal models, the consumption of Omega-3 polyunsaturated fatty acids ( PUFA ) has been shown to enhance the activity of sperm lactate dehydrogenase isoenzyme, a crucial enzyme in sperm glycolytic metabolism that provides ample energy for sperm motility in the reproductive tract 15 , 16 . However, current clinical research findings regarding the influence of omega-3 on fertility are inconsistent, and in the context of natural conception, there is a lack of large-scale randomized controlled studies assessing the influence of omega-3 fatty acids on natural fertility. To minimize the impact of acquired confounding factors, Mendelian randomization was employed to assess the potential causal relationship between omega-3 fatty acids and human reproduction 17 .In the Mendelian randomization study, we selected exposure factors and outcomes associated with genetic variations, exploring their causal relationship 18 . 2. Materials and Methods Study design overview The design of the Mendelian Randomization (MR) study is shown in Fig. 1 . In briefly, we separately estimated the causal effects of omega-3 on male infertility and female infertility. In Mendelian randomization, a genetic variant can be considered an instrumental variable only when it satisfies the following three assumptions: 1. The genetic variant is strongly correlated with the exposure factor. 2. The genetic variant is unrelated to confounding factors (e.g., body mass index, socioeconomic status, race, gender, and age). 3. The genetic variant does not have a direct impact on the outcome but affects the outcome only through the exposure pathway. We employed summary statistics from recent meta-analyses of genome-wide association studies (GWASs) on male infertility, female infertility, and omega-3. The design of bidirectional Mendelian randomization (MR) study. The 'X ' means that genetic variants are not associated with confounders or cannot be directly involved in outcome but via the exposure pathway. The '√' means that genetic variants are highly correlated with exposure. Solid paths are significant; dashed paths should not exist in the MR study. Data sources and SNP selection for fish oil The genome-wide association study (GWAS) summary statistics for fish oil-derived n-3 PUFAs, including eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA), were sourced from the UK Biobank. The GWAS employed inverse-variance-weighted meta-analysis across 445,562 participants of European ancestry. The UK Biobank delineated the reproducibility of touchscreen questionnaires in a subset of approximately 500,000 participants, with a questionnaire completion interval of approximately 4 years among these participants. In assessing the intake of major food groups, fruits, vegetables, fish, meat, and novel fibers, UK biobank observed a moderate to significant consistency between responses to dietary questions and repeated responses at specific observation time points. The UK Biobank has validated that, with respect to major food groups, participants exhibited considerable stability in dietary exposure assessments over a 4-year follow-up duration. Notably, responses to queries about meat and oily fish consumption on the touchscreen questionnaire demonstrated a high degree of concordance with repeated assessments approximately 4 years subsequent 19 . Due to the limited number of SNPs, we expanded the instrumental variable for omega-3, and relative variants associated with omega-3 at genome-wide significance (P < 5 × 10⁻⁶) were reported by the GWAS. Simultaneously, to validate the independence of SNPs, we conducted linkage disequilibrium (LD) tests on these single nucleotide polymorphisms (SNPs). Pairwise genetic variants with LD (r² > 0.001) were pruned. A total of 27 SNPs were included in the MR analysis. These SNPs were subsequently employed for matching with SNPs associated with male and female infertility. Furthermore, we computed r2 and f-statistics to evaluate the strength of the instrumental variables (IVs) on the basis of the sample size of the exposure dataset, the count of instrumental variables, and the genetic variance 20 . The F-values for all instrumental variables were found to exceed 10, signifying that they are robust instruments. Finally, we conducted a search in the Phenoscanner database for all SNPs and their proxies related to the exposure ( http://www.phenoscanner.medschl.cam.ac.uk/ ) to determine the presence of SNPs associated with confounding factors (P < 1 × 10⁻⁵). We manually excluded these SNPs to mitigate potential pleiotropic effects. The specifics of the SNPs associated with Omega-3 and infertility are provided in the Supplementary Material. Data sources and SNP selection for male infertility and female infertility We obtained data from a previously published large-scale GWAS meta-analysis. The summary statistics for GWAS related to male infertility and female infertility were downloaded from the FinnGen consortium's R9 release ( https://www.finngen.fi/en ). This dataset comprises 1,271 cases of male infertility and 119,279 male infertility controls, as well as 13,142 cases of female infertility and 107,564 female infertility controls. Individuals of undetermined gender, those with a high genotype failure rate (> 5%), and individuals of non-Finnish ancestry were excluded. The diagnosis of infertility was based on the International Classification of Diseases code N14 (8th, 9th, and 10th revisions). Details of the GWAS studies used in this study are shown in Table 1 . The FinnGen consortium leveraged genomic data (genetic data) from the biobank sample and health-related data from social and healthcare registers. Data on citizens' utilization of healthcare services throughout their entire lifespan were collected from the Finnish National Health Register. The biobank constitutes a repository of biological specimens and their corresponding data, assembled with the informed consent of the donors. Seven regional biobanks and three national biobanks across Finland participated in this study. These biobanks were established by universities, hospitals, and other research institutions. Each participant provided written informed consent. Table 1 Details of the GWASs included in the Mendelian randomization Traits Consortium Sample Size N cases N controls Total number of SNPs tested Population Studied Omega-3 Neale Lab 336,314 106,738 229,576 10,894,596 European Male infertility FinnGen consortium 120,568 1,271 119,297 18,687,536 European Female infertility FinnGen consortium 120,706 13,142 107,564 18,687,521 European Finally, we respectively obtained the variants associated with male infertility and female infertility at genome-wide significance(P < 5×10<6) and independence (r2 < 0.001) level. We utilized the Phenoscanner database to check the SNPs. Details of instrument SNPs are listed in Supplementary Tables. 3. Results After screening through the Phenoscanner database, 27 genetic variants were selected as instrumental variables for male infertility, and another 27 genetic variants were chosen as instrumental variables for female infertility. The F-statistics for the instrumental variables (IVs) for both male and female infertility were all above 10. This indicates that the included instrumental variables are strong, thereby reducing the bias introduced by instrumental variable assessment. As depicted in Table 2 , the heterogeneity among the instrumental variables was evaluated utilizing Cochran's Q test (P > 0.05), indicating that no significant heterogeneity is present with respect to the incorporated SNP effects. This lack of association was further supported by the scatter plot presented in Fig. 2 A. In the inverse-variance weighted (IVW) model, the results indicated no significant causal relationship between omega-3 intake and male infertility [OR = 2.33,95% confidence interval (CI) = 0.64, 3.58, P = 0.566]. Additionally, the results from MR-Egger and the weighted mode (WM) model were consistent with the IVW results. MR-Egger assessed that genetic variants did not exhibit average directional pleiotropy (i.e., no directional pleiotropy) on the outcome (P for intercept = 0.031; P = 0.35). The results from the Mendelian randomization-weighted (MW) method indicate no significant causal relationship between genetic predisposition to omega-3 intake and male infertility (OR = 4.53, 95% CI = 0.83, 6.16, P = 0.429). The Leave-One-Out (LOO) analysis revealed that no individual SNP altered the overall effect (Fig. 2 B). Furthermore, the funnel plot was nearly symmetric (Fig. 2 C), showing the absence of pleiotropy. Table 2 Abbreviation: MR, Mendelian randomization; SNPs, single nucleotide polymorphisms; IVW, inverse variance weighted; OR, odds ratio; CI, confidence interval; WM, weighted median. Exposures Outcomes No.of SNPs Method OR(95% CI) P Heterogeneity test Pleiotropy test Cochran's Q (I 2 ) P * Intercept P Omega-3 Male infertility 27 IVW 2.33 (0.13,42.03) 0.57 16.74% 0.23 MR Egger 0.04 (0,253.78) 0.48 16.37% 0.23 0.031 0.35 WM 7.83 (0.01,7981.4) 0.43 Female infertility 27 IVW 1.49 (0.63,3.54) 0.37 0% 0.53 MR Egger 13.00 (0.96,176.32) 0.07 0% 0.65 -0.017 0.10 WM 0.97 (0.11,8.69) 0.98 * Bolded P represents heterogeneity. In the Mendelian randomization analysis of Omega-3 and female infertility, as depicted in Table 2 , the random-effects model using the inverse-variance weighting (IVW) method suggests no evident causal relationship between fish oil and female infertility (OR = 1.489, 95% CI = 0.192, 1.866, P = 0.368). The Mendelian randomization-weighted (MW) method also indicates no significant causal relationship between the two (OR = 1.018, 95% CI = 0.466, 1.571, P = 0.978). Subsequent sensitivity analyses demonstrate the absence of apparent pleiotropy in our analysis, as indicated by MR-Egger regression analysis (intercept =-0.017; P = 0.10). Similarly, Cochran's Q test showed no heterogeneity in any of the analyses This lack of association was further supported by the scatter plot shown in Fig. 3 A. The LOO analysis shows that the overall result is not affected by excluding individual SNPs (Fig. 3 B), and the funnel plot is almost symmetrical (Fig. 3 C), meaning that our analysis is relatively robust. Discussion This MR analysis provides no evidence in favor of the causal association of omega-3 and male infertility or female infertility. To our knowledge, this is the first Mendelian randomization study to examine the causal relationship between omega-3 intake and both male and female reproductive outcomes. Previous studies have also explored the impact of omega-3 on male reproductive outcomes. In prior in vitro and animal experiments, researchers suggested that omega-3 may be involved in regulating sperm utilization of free fatty acids 21 , modulating acrosome reaction 22 , or that the biophysical properties of DHA contribute to membrane fluidity, flexibility, and receptor function 23 . However, the efficacy of Omega-3 PUFA supplementation in animal experiments is susceptible to factors such as the quantity of Omega-3, duration of supplementation, characteristics of the digestive system, reproductive status of the animals, and experimental design. Observational experiments conducted on patients, on the other hand, yield varying results. Some studies indicate that male participants did not exhibit improvements in spermatic parameters (including seminal volume, sperm concentration, motility, and morphology) after a period of omega-3 supplementation 24 – 26 . Nevertheless, Safarinejad reported an analysis of the outcomes from sustained supplementation with 1840 mg/day of omega-3 fatty acids over a 32-week period. The investigation revealed significant enhancements in sperm concentration, motility, normal morphology, and antioxidant status upon completion of the trial. Additionally, the levels of Omega-3 PUFAs (DHA and EPA) in both sperm and seminal plasma increased 27 . The primary distinction among these experiments lies in the variation in treatment duration. Similarly, the causal relationship between omega-3 and female reproductive outcomes remains uncertain, even conflicting 28 – 30 . Jungheim et al. found that increasing fasting serum concentrations of ALA (a precursor of ω-3 polyunsaturated fatty acids) could decrease the probability of pregnancy. Additionally, a higher ratio of omega-6 to omega-3 (LA:ALA) in fasting serum was associated with higher implantation and pregnancy rates 31 , 32 . Contrasting results were reported in the EARTH cohort, where serum omega-3 PUFA concentrations and intake were positively correlated with the probability of pregnancy and live birth. Additionally, no association was found between the ratio of omega-6 to omega-3 and reproductive outcomes. 33 In the PRESTO study targeting North American women, an increase in dietary intake of omega-3 was observed to be accompanied by a rise in fertility rates. However, a similar scenario was not observed in the Danish study cohort 30 . It is worth noting that the median intake of omega-3 fatty acids in the Danish Snart Foraeldre cohort is relatively high. Therefore, whether differences in omega-3 intake would impact fertility outcomes remains unknown. As described in other literature, an increase in the intake of EPA and DHA may lead to a reduction in the quantity of MII oocytes and E2 response. This could be attributed to the intake-induced decrease in prostaglandin F2α, a substance positively involved in follicle growth and ovulation. 34 , 35 This study has several limitations. Firstly, the number of SNPs involved in our research is relatively small. Therefore, it is hoped that in the future, a larger set of single nucleotide polymorphisms (SNPs) can be utilized as instruments to replicate Mendelian randomization (MR) studies, thereby enhancing the power of association detection. Secondly, this study only included participants of European descent, and the instruments identified in the European population may not be transferable to other populations. Especially considering the established polymorphisms in the FADS gene leading to interethnic differences in the biosynthetic capacity of LC-PUFAs for LA and ALA 36 , additional MR studies in other ethnic populations are warranted to validate the causal relationship. In addition, MR studies assume causal relationships to occur in a single direction. Due to the complexity of biological systems, feedback loops between exposure and outcome may exist, potentially introducing inaccuracies in the results. Nevertheless, this study possesses several strengths. Firstly, we incorporated variations in male and female reproductive phenotypes from the latest meta-analysis and extracted instrumental variables for omega-3 from the largest genome-wide association studies. Secondly, utilizing causal inference methods allowed us to easily obtain extensive outcome genetic data from publicly available genetic datasets. Lastly, the avoidance of population overlap was ensured by selecting samples from two distinct databases: the FinnGen consortium for male and female reproductive samples and the UK Biobank for omega-3 samples. In conclusion, our Mendelian Randomization (MR) analysis did not reveal a causal relationship between omega-3 intake and male or female fertility. This suggests that omega-3 intake may not have an impact on reproductive outcomes in both men and women. Declarations Author Contributions: Conceptualization, Y.W. and JM.C.; Data curation, Y.W.; Formal analysis, Y.W. and JM.C.; Funding acquisition, WQ.C.; Investigation, WQ.C.; Methodology, YL.B. and XZ.G.; Software, Y.W. and LY.W.; Supervision, XZ.G, WQ.C. and Y.W; Validation, JM.C. and LY.W.; Visualization, Y.W.; Writing—original draft, Y.W. and JM.C.; Writing—review and editing, XZ.G., WQ.C. All authors have read and agreed to the published version of the manuscript. Funding: This research was supported by the Natural Science Foundation of Zhejiang Province, China, No. LGF20H270002 Data Availability Statement: The data supporting the findings of this study are available on the IEU open GWAS project websites (https://gwas.mrcieu.ac.uk/) and FinnGen database（https://www.finngen.fi/fi）, accessed on 02 February 2024). Acknowledgments: Data from a publicly available GWAS were used in this study, and the authors would like to thank all those who contributed and participated in the data collection. Conflicts of Interest: The authors declare no conflict of interest. References Mengelberg, A., Leathem, J. & Podd, J. Fish oil supplement use in New Zealand: A cross-sectional survey. Complementary therapies in clinical practice 33, 118–123, doi: 10.1016/j.ctcp.2018.09.005 (2018). Kantor, E. D., Rehm, C. D., Du, M., White, E. & Giovannucci, E. L. Trends in Dietary Supplement Use Among US Adults From 1999–2012. 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The Journal of clinical endocrinology and metabolism 98, E1364-1368, doi: 10.1210/jc.2012-4115 (2013). Chiu, Y. H., Chavarro, J. E. & Souter, I. Diet and female fertility: doctor, what should I eat? Fertility and sterility 110, 560–569, doi: 10.1016/j.fertnstert.2018.05.027 (2018). Hammiche, F. et al. Increased preconception omega-3 polyunsaturated fatty acid intake improves embryo morphology. Fertility and sterility 95, 1820–1823, doi: 10.1016/j.fertnstert.2010.11.021 (2011). Jahangirifar, M., Taebi, M., Nasr-Esfahani, M. H., Heidari-Beni, M. & Asgari, G. H. Dietary Fatty Acid Intakes and the Outcomes of Assisted Reproductive Technique in Infertile Women. Journal of reproduction & infertility 22, 173–183, doi: 10.18502/jri.v22i3.6718 (2021). Mathias, R. A. et al. Adaptive evolution of the FADS gene cluster within Africa. PloS one 7, e44926, doi: 10.1371/journal.pone.0044926 (2012). Additional Declarations No competing interests reported. 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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-3966971","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":275454892,"identity":"d73cbb84-ce33-45ac-9358-de35ec3d5b0d","order_by":0,"name":"Yan Wang","email":"","orcid":"","institution":"Zhejiang Chinese Medical University Affiliated Integrated Traditional and Western Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yan","middleName":"","lastName":"Wang","suffix":""},{"id":275454893,"identity":"efacff89-077c-4701-a17e-a246e63aef86","order_by":1,"name":"Jiamin Chen","email":"","orcid":"","institution":"Zhejiang Chinese Medical University","correspondingAuthor":false,"prefix":"","firstName":"Jiamin","middleName":"","lastName":"Chen","suffix":""},{"id":275454894,"identity":"a6ca6e74-d32a-428d-9940-e37700e79d85","order_by":2,"name":"Zuogang Xie","email":"","orcid":"","institution":"Zhejiang Chinese Medical University Affiliated Wenzhou Hospital of Integrated Traditional and Western Medicine","correspondingAuthor":false,"prefix":"","firstName":"Zuogang","middleName":"","lastName":"Xie","suffix":""},{"id":275454895,"identity":"c70567f0-bf7c-401c-891c-3b6e41d015b1","order_by":3,"name":"Yali Bo","email":"","orcid":"","institution":"Zhejiang Chinese Medical University Affiliated Integrated Traditional and Western Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yali","middleName":"","lastName":"Bo","suffix":""},{"id":275454896,"identity":"1f339a95-c118-4409-b096-8b9ab222d502","order_by":4,"name":"Lingyi wan","email":"","orcid":"","institution":"Zhejiang Chinese Medical University Affiliated Integrated Traditional and Western Medicine Hospital","correspondingAuthor":false,"prefix":"","firstName":"Lingyi","middleName":"","lastName":"wan","suffix":""},{"id":275454897,"identity":"3d36dcf8-d266-4c22-8982-8e5f964b7346","order_by":5,"name":"Wangqiang Chen","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYNACNiBmBmIeBjk5MIMoLTwQLcbGJGhhgGhJbCCk2Ly999iHD2WH5e3ZeQwfvKkxSJ/fznvwA0ONTTQuLTJnziXPnHHusGEPM4+x4ZxjBrkbDvMlSzAcS8vFZZ2ERI4xM2/b4QQeZrY0ad6GP7kbmHkMJBgbDuPWIv8GriX9N2+DQbp8M4/xD7xaJHhgWpiPMQO1JDAc5jHDbwtPXjLjjHPphj2HmQ9LAv1iuAGoxSIBn1/Yzx5m+FBmLc/ef7DxAzDE5OX7zxjf+FBjg1MLNELQQQJO5Ti1jIJRMApGwShAAgDXVk0L15EsAwAAAABJRU5ErkJggg==","orcid":"","institution":"Zhejiang Chinese Medical University Affiliated Integrated Traditional and Western Medicine Hospital","correspondingAuthor":true,"prefix":"","firstName":"Wangqiang","middleName":"","lastName":"Chen","suffix":""}],"badges":[],"createdAt":"2024-02-18 12:45:31","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3966971/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3966971/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52025268,"identity":"4588e6ed-286e-4b87-b0ce-f326ba88d272","added_by":"auto","created_at":"2024-03-05 15:47:11","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":21075,"visible":true,"origin":"","legend":"\u003cp\u003eThe design of bidirectional Mendelian randomization (MR) study. The 'X ' means that genetic variants are not associated with confounders or cannot be directly involved in outcome but via the exposure pathway. The '√' means that genetic variants are highly correlated with exposure. Solid paths are significant; dashed paths should not exist in the MR study.\u003c/p\u003e","description":"","filename":"Picture1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3966971/v1/5e90d55c741f46b56fc7ae53.jpg"},{"id":52026861,"identity":"2ecea771-9a0c-4613-8ee8-482738a0b700","added_by":"auto","created_at":"2024-03-05 15:55:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":103560,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of Omega-3 on male infertility. (A) Scatter plot of the causal effect of Omega-3 concentrations on male infertility; (B) forest plot of the LOO analysis; (C) funnel plot of the causal effect of Omega-3 concentrations on male infertility\u003c/p\u003e","description":"","filename":"F2.png","url":"https://assets-eu.researchsquare.com/files/rs-3966971/v1/7a8c343af5b6e89563a526bb.png"},{"id":52025270,"identity":"68fe6083-10bf-4c25-ac75-6eb9395a710d","added_by":"auto","created_at":"2024-03-05 15:47:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":63686,"visible":true,"origin":"","legend":"\u003cp\u003eEffects of Omega-3 on female infertility. (A) Scatter plot of the causal effect of Omega-3 concentrations on female infertility; (B) forest plot of the LOO analysis; (C) funnel plot of the causal effect of Omega-3 concentrations on female infertility\u003c/p\u003e","description":"","filename":"F3.png","url":"https://assets-eu.researchsquare.com/files/rs-3966971/v1/80a3e4d8bed06fa5df418285.png"},{"id":53904460,"identity":"322edb25-c5c2-479d-959f-13dff4d462a1","added_by":"auto","created_at":"2024-04-02 04:24:56","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":367118,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3966971/v1/e91195f0-b0fa-433c-946a-99cca4c73e03.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Causal Effect of Omega-3 on male infertility and female infertility: A Mendelian Randomization Study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn recent decades, Omega-3 has been widely employed globally as a dietary supplement, with a noticeable annual increase in usage, especially in developed countries over the last two decades \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. In the United States, the proportion of individuals utilizing ω-3 fatty acids has surged from 12\u0026ndash;26%\u003csup\u003e2,3\u003c/sup\u003e. Omega-3 polyunsaturated fatty acids (PUFAs) mainly include eicosapentaenoic acid (EPA; 20:5 ω-3), docosapentaenoic acid (DPA; 22:5 ω-3), and docosahex aenoic acid (DHA; 22:6 ω-3)\u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. Numerous studies have elucidated the relationship between Omega-3 (ω3) fatty acids and human health\u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e, encompassing their potential to ameliorate conditions such as cardiovascular diseases\u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, diabetes\u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, Alzheimer's Disease and dementia\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eAs we entered the 21st century, infertility remained a prevalent challenge that demands significant human attention. Studies indicate that approximately 9.5\u0026ndash;11.7% of couples in their reproductive years worldwide are affected by the impact of infertility\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. In certain regions, the incidence of primary infertility has exhibited a notable increase compared to secondary infertility, such as in North Africa and the Middle East, particularly in Morocco and Yemen. However, in some areas, the prevalence of secondary infertility surpasses that of primary infertility, exemplified in Eastern Europe and Central Asia\u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. The prevalence of male-factor infertility demonstrates considerable global variability, extending from a low of 20% to as high as 70%. The proportion of infertile males within the male population is estimated to range from 2.5% and 12%. Among these, the highest incidence rates are documented in Africa, as well as in Central and Eastern European regions\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Humans have been endeavoring to treat infertility for millennia. In addition to pharmaceutical and surgical interventions, dietary supplements have emerged as a novel avenue for addressing human infertility, offering a promising direction in therapeutic approaches. In numerous previously published studies, dietary supplements such as antioxidant supplements, vitamins (including vitamin B12, vitamin E, vitamin C), dietary fats, and trace elements have been implicated in influencing male and female infertility. However, extant evidence concerning the impact of Omega-3 on human infertility exhibits certain limitations and, in some instances, even conflicting outcomes. A definitive conclusion regarding the impact of Omega-3 fatty acids on reproductive aspects has not yet been reached.\u003c/p\u003e \u003cp\u003eIn female animal models, supplementation with Omega-3 has been demonstrated to alter the prostaglandin biosynthetic pathway, potentially impacting steroidogenesis, follicle formation, and oocyte maturation, thereby improving female fertility \u003csup\u003e\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e,\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e; Concurrently, in male animal models, the consumption of Omega-3 polyunsaturated fatty acids ( PUFA ) has been shown to enhance the activity of sperm lactate dehydrogenase isoenzyme, a crucial enzyme in sperm glycolytic metabolism that provides ample energy for sperm motility in the reproductive tract\u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. However, current clinical research findings regarding the influence of omega-3 on fertility are inconsistent, and in the context of natural conception, there is a lack of large-scale randomized controlled studies assessing the influence of omega-3 fatty acids on natural fertility.\u003c/p\u003e \u003cp\u003eTo minimize the impact of acquired confounding factors, Mendelian randomization was employed to assess the potential causal relationship between omega-3 fatty acids and human reproduction\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e.In the Mendelian randomization study, we selected exposure factors and outcomes associated with genetic variations, exploring their causal relationship \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"2. Materials and Methods","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eStudy design overview\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe design of the Mendelian Randomization (MR) study is shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. In briefly, we separately estimated the causal effects of omega-3 on male infertility and female infertility. In Mendelian randomization, a genetic variant can be considered an instrumental variable only when it satisfies the following three assumptions: 1. The genetic variant is strongly correlated with the exposure factor. 2. The genetic variant is unrelated to confounding factors (e.g., body mass index, socioeconomic status, race, gender, and age). 3. The genetic variant does not have a direct impact on the outcome but affects the outcome only through the exposure pathway. We employed summary statistics from recent meta-analyses of genome-wide association studies (GWASs) on male infertility, female infertility, and omega-3.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe design of bidirectional Mendelian randomization (MR) study. The 'X ' means that genetic variants are not associated with confounders or cannot be directly involved in outcome but via the exposure pathway. The '\u0026radic;' means that genetic variants are highly correlated with exposure. Solid paths are significant; dashed paths should not exist in the MR study.\u003c/p\u003e\u003cp\u003e\u003cem\u003eData sources and SNP selection for fish oil\u003c/em\u003e\u003c/p\u003e\u003cp\u003eThe genome-wide association study (GWAS) summary statistics for fish oil-derived n-3 PUFAs, including eicosapentaenoic acid (EPA), docosapentaenoic acid (DPA), and docosahexaenoic acid (DHA), were sourced from the UK Biobank. The GWAS employed inverse-variance-weighted meta-analysis across 445,562 participants of European ancestry. The UK Biobank delineated the reproducibility of touchscreen questionnaires in a subset of approximately 500,000 participants, with a questionnaire completion interval of approximately 4 years among these participants. In assessing the intake of major food groups, fruits, vegetables, fish, meat, and novel fibers, UK biobank observed a moderate to significant consistency between responses to dietary questions and repeated responses at specific observation time points. The UK Biobank has validated that, with respect to major food groups, participants exhibited considerable stability in dietary exposure assessments over a 4-year follow-up duration. Notably, responses to queries about meat and oily fish consumption on the touchscreen questionnaire demonstrated a high degree of concordance with repeated assessments approximately 4 years subsequent\u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e .\u003c/p\u003e\u003cp\u003eDue to the limited number of SNPs, we expanded the instrumental variable for omega-3, and relative variants associated with omega-3 at genome-wide significance (P\u0026thinsp;\u0026lt;\u0026thinsp;5 \u0026times; 10⁻⁶) were reported by the GWAS. Simultaneously, to validate the independence of SNPs, we conducted linkage disequilibrium (LD) tests on these single nucleotide polymorphisms (SNPs). Pairwise genetic variants with LD (r\u0026sup2; \u0026gt; 0.001) were pruned. A total of 27 SNPs were included in the MR analysis. These SNPs were subsequently employed for matching with SNPs associated with male and female infertility. Furthermore, we computed r2 and f-statistics to evaluate the strength of the instrumental variables (IVs) on the basis of the sample size of the exposure dataset, the count of instrumental variables, and the genetic variance\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. The F-values for all instrumental variables were found to exceed 10, signifying that they are robust instruments.\u003c/p\u003e\u003cp\u003eFinally, we conducted a search in the Phenoscanner database for all SNPs and their proxies related to the exposure (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.phenoscanner.medschl.cam.ac.uk/\u003c/span\u003e\u003cspan address=\"http://www.phenoscanner.medschl.cam.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to determine the presence of SNPs associated with confounding factors (P\u0026thinsp;\u0026lt;\u0026thinsp;1 \u0026times; 10⁻⁵). We manually excluded these SNPs to mitigate potential pleiotropic effects. The specifics of the SNPs associated with Omega-3 and infertility are provided in the Supplementary Material.\u003c/p\u003e\u003cp\u003e\u003cem\u003eData sources and SNP selection for male infertility and female infertility\u003c/em\u003e\u003c/p\u003e\u003cp\u003eWe obtained data from a previously published large-scale GWAS meta-analysis. The summary statistics for GWAS related to male infertility and female infertility were downloaded from the FinnGen consortium's R9 release (\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). This dataset comprises 1,271 cases of male infertility and 119,279 male infertility controls, as well as 13,142 cases of female infertility and 107,564 female infertility controls. Individuals of undetermined gender, those with a high genotype failure rate (\u0026gt;\u0026thinsp;5%), and individuals of non-Finnish ancestry were excluded. The diagnosis of infertility was based on the International Classification of Diseases code N14 (8th, 9th, and 10th revisions).\u003c/p\u003e\u003cp\u003eDetails of the GWAS studies used in this study are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. The FinnGen consortium leveraged genomic data (genetic data) from the biobank sample and health-related data from social and healthcare registers. Data on citizens' utilization of healthcare services throughout their entire lifespan were collected from the Finnish National Health Register. The biobank constitutes a repository of biological specimens and their corresponding data, assembled with the informed consent of the donors. Seven regional biobanks and three national biobanks across Finland participated in this study. These biobanks were established by universities, hospitals, and other research institutions. Each participant provided written informed consent.\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eDetails of the GWASs included in the Mendelian randomization\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTraits\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eConsortium\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSample Size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eN cases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eN controls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eTotal number of SNPs tested\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePopulation Studied\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eOmega-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNeale Lab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e336,314\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e106,738\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e229,576\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e10,894,596\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMale infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen consortium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120,568\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e1,271\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e119,297\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18,687,536\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003cp\u003einfertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen consortium\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e120,706\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e13,142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e \u003cp\u003e107,564\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e \u003cp\u003e18,687,521\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eFinally, we respectively obtained the variants associated with male infertility and female infertility at genome-wide significance(P\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003c6) and independence (r2\u0026thinsp;\u0026lt;\u0026thinsp;0.001) level. We utilized the Phenoscanner database to check the SNPs. Details of instrument SNPs are listed in Supplementary Tables.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"3. Results","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eAfter screening through the Phenoscanner database, 27 genetic variants were selected as instrumental variables for male infertility, and another 27 genetic variants were chosen as instrumental variables for female infertility. The F-statistics for the instrumental variables (IVs) for both male and female infertility were all above 10. This indicates that the included instrumental variables are strong, thereby reducing the bias introduced by instrumental variable assessment.\u003c/p\u003e \u003cp\u003eAs depicted in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the heterogeneity among the instrumental variables was evaluated utilizing Cochran's Q test (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05), indicating that no significant heterogeneity is present with respect to the incorporated SNP effects. This lack of association was further supported by the scatter plot presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA. In the inverse-variance weighted (IVW) model, the results indicated no significant causal relationship between omega-3 intake and male infertility [OR\u0026thinsp;=\u0026thinsp;2.33,95% confidence interval (CI)\u0026thinsp;=\u0026thinsp;0.64, 3.58, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.566]. Additionally, the results from MR-Egger and the weighted mode (WM) model were consistent with the IVW results. MR-Egger assessed that genetic variants did not exhibit average directional pleiotropy (i.e., no directional pleiotropy) on the outcome (P for intercept\u0026thinsp;=\u0026thinsp;0.031; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.35). The results from the Mendelian randomization-weighted (MW) method indicate no significant causal relationship between genetic predisposition to omega-3 intake and male infertility (OR\u0026thinsp;=\u0026thinsp;4.53, 95% CI\u0026thinsp;=\u0026thinsp;0.83, 6.16, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.429). The Leave-One-Out (LOO) analysis revealed that no individual SNP altered the overall effect (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB). Furthermore, the funnel plot was nearly symmetric (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC), showing the absence of pleiotropy.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAbbreviation: MR, Mendelian randomization; SNPs, single nucleotide polymorphisms; IVW, inverse variance weighted; OR, odds ratio; CI, confidence interval; WM, weighted median.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"11\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c11\" colnum=\"11\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eExposures\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOutcomes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eNo.of SNPs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eMethod\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eOR(95% CI)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e \u003cp\u003eHeterogeneity test\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c11\" namest=\"c10\"\u003e \u003cp\u003ePleiotropy test\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003eCochran's Q (I\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u003cb\u003eP\u003c/b\u003e\u003cem\u003e*\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eIntercept\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003eOmega-3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eMale infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2.33 (0.13,42.03)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.74%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMR\u0026nbsp;Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.04 (0,253.78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e16.37%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.23\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e0.031\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e7.83 (0.01,7981.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eFemale infertility\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e27\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eIVW\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1.49 (0.63,3.54)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eMR\u0026nbsp;Egger\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e13.00 (0.96,176.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.65\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003e-0.017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e \u003cp\u003e0.10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eWM\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.97 (0.11,8.69)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c11\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e* Bolded P represents heterogeneity.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn the Mendelian randomization analysis of Omega-3 and female infertility, as depicted in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, the random-effects model using the inverse-variance weighting (IVW) method suggests no evident causal relationship between fish oil and female infertility (OR\u0026thinsp;=\u0026thinsp;1.489, 95% CI\u0026thinsp;=\u0026thinsp;0.192, 1.866, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.368). The Mendelian randomization-weighted (MW) method also indicates no significant causal relationship between the two (OR\u0026thinsp;=\u0026thinsp;1.018, 95% CI\u0026thinsp;=\u0026thinsp;0.466, 1.571, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.978). Subsequent sensitivity analyses demonstrate the absence of apparent pleiotropy in our analysis, as indicated by MR-Egger regression analysis (intercept =-0.017; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.10). Similarly, Cochran's Q test showed no heterogeneity in any of the analyses This lack of association was further supported by the scatter plot shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA. The LOO analysis shows that the overall result is not affected by excluding individual SNPs (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB), and the funnel plot is almost symmetrical (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC), meaning that our analysis is relatively robust.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e "},{"header":"Discussion","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThis MR analysis provides no evidence in favor of the causal association of omega-3 and male infertility or female infertility.\u003c/p\u003e \u003cp\u003eTo our knowledge, this is the first Mendelian randomization study to examine the causal relationship between omega-3 intake and both male and female reproductive outcomes. Previous studies have also explored the impact of omega-3 on male reproductive outcomes. In prior in vitro and animal experiments, researchers suggested that omega-3 may be involved in regulating sperm utilization of free fatty acids\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, modulating acrosome reaction\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, or that the biophysical properties of DHA contribute to membrane fluidity, flexibility, and receptor function\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. However, the efficacy of Omega-3 PUFA supplementation in animal experiments is susceptible to factors such as the quantity of Omega-3, duration of supplementation, characteristics of the digestive system, reproductive status of the animals, and experimental design. Observational experiments conducted on patients, on the other hand, yield varying results. Some studies indicate that male participants did not exhibit improvements in spermatic parameters (including seminal volume, sperm concentration, motility, and morphology) after a period of omega-3 supplementation\u003csup\u003e\u003cspan additionalcitationids=\"CR25\" citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e. Nevertheless, Safarinejad reported an analysis of the outcomes from sustained supplementation with 1840 mg/day of omega-3 fatty acids over a 32-week period. The investigation revealed significant enhancements in sperm concentration, motility, normal morphology, and antioxidant status upon completion of the trial. Additionally, the levels of Omega-3 PUFAs (DHA and EPA) in both sperm and seminal plasma increased\u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. The primary distinction among these experiments lies in the variation in treatment duration.\u003c/p\u003e \u003cp\u003eSimilarly, the causal relationship between omega-3 and female reproductive outcomes remains uncertain, even conflicting\u003csup\u003e\u003cspan additionalcitationids=\"CR29\" citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. Jungheim et al. found that increasing fasting serum concentrations of ALA (a precursor of ω-3 polyunsaturated fatty acids) could decrease the probability of pregnancy. Additionally, a higher ratio of omega-6 to omega-3 (LA:ALA) in fasting serum was associated with higher implantation and pregnancy rates\u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Contrasting results were reported in the EARTH cohort, where serum omega-3 PUFA concentrations and intake were positively correlated with the probability of pregnancy and live birth. Additionally, no association was found between the ratio of omega-6 to omega-3 and reproductive outcomes. \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e In the PRESTO study targeting North American women, an increase in dietary intake of omega-3 was observed to be accompanied by a rise in fertility rates. However, a similar scenario was not observed in the Danish study cohort\u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. It is worth noting that the median intake of omega-3 fatty acids in the Danish Snart Foraeldre cohort is relatively high. Therefore, whether differences in omega-3 intake would impact fertility outcomes remains unknown. As described in other literature, an increase in the intake of EPA and DHA may lead to a reduction in the quantity of MII oocytes and E2 response. This could be attributed to the intake-induced decrease in prostaglandin F2α, a substance positively involved in follicle growth and ovulation. \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e\u003c/p\u003e \u003cp\u003eThis study has several limitations. Firstly, the number of SNPs involved in our research is relatively small. Therefore, it is hoped that in the future, a larger set of single nucleotide polymorphisms (SNPs) can be utilized as instruments to replicate Mendelian randomization (MR) studies, thereby enhancing the power of association detection. Secondly, this study only included participants of European descent, and the instruments identified in the European population may not be transferable to other populations. Especially considering the established polymorphisms in the FADS gene leading to interethnic differences in the biosynthetic capacity of LC-PUFAs for LA and ALA\u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e, additional MR studies in other ethnic populations are warranted to validate the causal relationship. In addition, MR studies assume causal relationships to occur in a single direction. Due to the complexity of biological systems, feedback loops between exposure and outcome may exist, potentially introducing inaccuracies in the results.\u003c/p\u003e \u003cp\u003eNevertheless, this study possesses several strengths. Firstly, we incorporated variations in male and female reproductive phenotypes from the latest meta-analysis and extracted instrumental variables for omega-3 from the largest genome-wide association studies. Secondly, utilizing causal inference methods allowed us to easily obtain extensive outcome genetic data from publicly available genetic datasets. Lastly, the avoidance of population overlap was ensured by selecting samples from two distinct databases: the FinnGen consortium for male and female reproductive samples and the UK Biobank for omega-3 samples.\u003c/p\u003e \u003cp\u003eIn conclusion, our Mendelian Randomization (MR) analysis did not reveal a causal relationship between omega-3 intake and male or female fertility. This suggests that omega-3 intake may not have an impact on reproductive outcomes in both men and women.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAuthor Contributions:\u0026nbsp;\u003c/strong\u003eConceptualization, Y.W. and JM.C.; Data curation, Y.W.; Formal analysis, Y.W. and JM.C.; Funding acquisition, WQ.C.; Investigation, WQ.C.; Methodology, YL.B. and XZ.G.; Software, Y.W. and LY.W.; Supervision, XZ.G, WQ.C. and Y.W; Validation, JM.C. and LY.W.; Visualization, Y.W.; Writing\u0026mdash;original draft, Y.W. and JM.C.; Writing\u0026mdash;review and editing, XZ.G., WQ.C. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research was supported by the Natural Science Foundation of Zhejiang Province, China, No. LGF20H270002\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability Statement:\u003c/strong\u003e The data supporting the findings of this study are available on the IEU open GWAS project websites (https://gwas.mrcieu.ac.uk/) and FinnGen database（https://www.finngen.fi/fi）, accessed on 02 February 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003e Data from a publicly available GWAS were used in this study, and the authors\u003c/p\u003e\n\u003cp\u003ewould like to thank all those who contributed and participated in the data collection.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of Interest:\u003c/strong\u003e The authors declare no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMengelberg, A., Leathem, J. \u0026amp; Podd, J. 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A. \u003cem\u003eet al.\u003c/em\u003e Adaptive evolution of the FADS gene cluster within Africa. PloS one 7, e44926, doi:\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1371/journal.pone.0044926\u003c/span\u003e\u003cspan address=\"10.1371/journal.pone.0044926\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e (2012).\u003c/span\u003e\u003c/li\u003e\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":"polygenic risk, docasahexaenoic acid, male infertility, female infertility, UK biobank","lastPublishedDoi":"10.21203/rs.3.rs-3966971/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3966971/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe association between Omega-3 and human reproduction is uncertain. This Mendelian randomization (MR) study aims to examine the causal relationship between Omega-3 intake and male and female reproduction. We utilized summary statistics data from 120,550 male participants and 120,706 female participants in the FinnGen consortium. Summary statistics for Omega-3 were extracted from a genome-wide association study involving up to 445,562 participants predominantly of European ancestry. MR analysis employed established methods, including Inverse Variance Weighting (IVW), Weighted Median (WM), and MR-Egger. Genetic determination of male infertility [IVW odds ratio (OR)\u0026thinsp;=\u0026thinsp;2.33, 95% confidence interval (CI)\u0026thinsp;=\u0026thinsp;0.13, 42.03, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.57] and female infertility [IVW odds ratio (OR)\u0026thinsp;=\u0026thinsp;1.49, 95% CI\u0026thinsp;=\u0026thinsp;0.13, 0.63, 3.54, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.37] was not associated with Omega-3 intake. The result of MR study does not provide support for a causal impact of Omega-3 intake on male and female reproduction.\u003c/p\u003e","manuscriptTitle":"Causal Effect of Omega-3 on male infertility and female infertility: A Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-05 15:47:06","doi":"10.21203/rs.3.rs-3966971/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":"74254994-fa53-48f8-9027-9bd79d734a16","owner":[],"postedDate":"March 5th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":29037935,"name":"Health sciences/Urology/Urogenital diseases/Male factor infertility"},{"id":29037936,"name":"Health sciences/Diseases/Reproductive disorders/Endocrine reproductive disorders"},{"id":29037937,"name":"Health sciences/Diseases/Reproductive disorders/Infertility"}],"tags":[],"updatedAt":"2024-04-02T04:16:47+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-05 15:47:06","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3966971","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3966971","identity":"rs-3966971","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}