Sex hormones and Sjögren’s Disease: A Mendelian randomization study

Sex hormones and Sjögren’s Disease: 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 Help Center Sign In Submit a Preprint Cite Share Download PDF Article Sex hormones and Sjögren’s Disease: A Mendelian randomization study haonan jin, shanshan ru, mengdi zhang, bo li, lidong gao, jiajia xia, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4690434/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 Background Postmenopausal women have a higher risk of developing Sjögren’s Disease (SjD) than men, indicating the involvement of sex hormones. The objective of this study was to investigate the causal relationship between sex hormones and SjD using a two-sample Mendelian randomization (MR) study. Methods Specific genetic tools obtained from genome-wide association studies (GWAS) were used to investigate serum estradiol (E2), total testosterone (TT), bioavailable testosterone (BT), and sex hormone-binding globulin (SHBG) levels. A two-sample MR analysis was conducted to examine sex hormone associations with SjD. Sex-stratified designs were employed, with additional databases used for further analysis of the outcomes. A Bonferroni correction was applied to ensure robust conclusions. Additionally, bioinformatics methods were employed to explore the underlying connections between sex hormones and SjD. Results The results of the MR analysis showed a significant inverse association between BT levels and the risk of SjD, with each one standard deviation (SD) increase in BT levels associated with a 55% decrease in SjD risk ( P = 5.2357E–05). The sex-stratified analysis provided that, for every one SD increase in BT levels, the risk of SjD decreased by 27% in males and 20% in females ( P = 0.036, P = 0.0377). Specifically, among females, each one SD increase in TT levels resulted in a 28% reduction of SjD risk ( P = 0.0306). However, following a sensitivity analysis, the observed causal association between BT (males) and SjD became non-significant ( P = 0.0856), while the remaining causal relationships persisted. The bioinformatics analysis suggested that inflammation and immune-related pathways underlie their connection. Conclusion Our study demonstrated a definitive causal relationship between androgen levels and the susceptibility to SjD, particularly among females. Androgen deficiency was shown to play a pivotal role in the pathogenesis of SjD, with inflammation and immune-related pathways underpinning the association. Health sciences/Medical research/Genetics research Health sciences/Rheumatology/Rheumatic diseases Health sciences/Risk factors sex hormone Mendelian randomization Bioavailable testosterone Sjögren’s Disease bioinformatics Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Sjögren's syndrome (SjD) is a chronic inflammatory autoimmune disease characterized by lymphocyte proliferation and the involvement of various exocrine glands throughout the body, leading to impaired secretion. It can be classified into primary and secondary types [ 1 ] . According to consensus standards in the United States and Europe, SjD is one of the most prevalent autoimmune diseases, alongside systemic lupus erythematosus and rheumatoid arthritis. The prevalence of SjD varies from 0.1–4.8%, a range that reflects differences in population demographics [ 2 ] , with a significantly higher incidence in females than in males (ratio of approximately 9:1). Postmenopausal women around the age of 50 are particularly susceptible [ 3 ] . SjD affects multiple systems throughout the body, resulting not only in obvious dryness of the eyes and mouth but also interstitial lung disease, gastrointestinal disorders, cognitive impairment, and even cancer [ 4 – 5 ] . While the specific causes and mechanisms underlying SjD are unclear, genetic susceptibility may lead to disease development under certain environmental influences. The interaction between innate immunity and the adaptive immune system plays a crucial role in the onset and progression of SjD, as B cells produce autoantibodies that trigger chronic inflammation in tear glands, salivary glands, and other exocrine glands [ 6 ] . Autoimmune diseases often exhibit sex-based differences, with a higher prevalence in females than in males. The severity, course, treatment, and survival rates also vary between sexes [ 7 ] . The immunostimulatory effects of estrogen are thought to underlie its role in autoimmune diseases, whereas testosterone plays an immunosuppressive role [ 8 ] . Hormone replacement therapy has therefore been used in the treatment of certain autoimmune diseases [ 9 – 11 ] . Several studies have investigated the association between sex hormones and SjD. A case-control study involving 2680 participants found that women with primary SjD had a lower exposure to estrogen and that increased exposure correlated negatively with the occurrence of primary SjD [ 12 ] . However, another nested case-control study suggested that estrogen exposure contributes to SjD onset [ 13 ] . Furthermore, research has shown that female SjD patients lack testosterone, including a significant deficiency in salivary gland testosterone levels, thus pointing to testosterone deficiency as a driving factor in SjD [ 14 – 16 ] . Interestingly, female patients with Turner syndrome who have normal levels of sex hormones and normal development still have an elevated risk of developing SjD. This suggests that the risk of SjD is associated with chromosomal abnormalities rather than being solely influenced by sex hormone levels [ 17 ] . The conflicting results regarding the relationship between sex hormones and SjD are likely to reflect limitations within existing studies and thus the need for further investigation of a causal effect between sex hormones and SjD. Mendelian randomization (MR) uses genetic variation to investigate causal relationships between exposure and outcome [ 18 ] . Three assumptions must be satisfied in a MR analysis: 1) genetic variation is associated with exposure, 2) genetic variation is independent of confounding factors between exposure and outcome, and 3) genetic variation only affects the outcome through exposure [ 19 ] . According to Mendel's law of random assortment, genetic variation is randomly allocated during meiosis and is therefore unaffected by confounding factors [ 20 ] . In this study, we employed two-sample MR analysis methods utilizing published European-population-wide genome-wide association study (GWAS) data and the FinnGen database data to investigate the causal effects of sex hormones (estradiol (E2), total testosterone (TT), bioavailable testosterone (BT), and sex-hormone-binding globulin (SHBG)) on SjD. We then validated the findings by stratifying them based on sex. The data were analyzed by employing bioinformatics techniques. Bioinformatics can assist researchers in comprehensively analyzing the relationship between drugs and diseases from a systematic perspective. It aids in predicting drug targets and functions while providing insights into potential therapeutic strategies. By integrating disciplines such as systems biology, computer databases, biological networks, and pharmacology, it facilitates exploration of the connections between diseases and drugs. In this study, a bioinformatics approach was applied to explore the overlapping targets between our experimental findings and SjD by constructing a 'drug-target-disease' network. The results were further examined in protein-protein interaction (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, with the aim of deciphering the connections between SjD and sex hormones. Materials and methods Research design The present study is based on publicly available research data, including published summary data, the FinnGen database, and IEU OpenGWAS data. Ethical approval and participant consent were previously obtained for the use of these datasets in research. A two-sample MR analysis was employed to investigate potential causal relationships between sex hormones and SjD. Sex stratification was then conducted to examine whether those relationships differ between males and females. The instrumental variables (IVs) satisfied all three assumptions (Fig. 1 ). Bioinformatics methods were subsequently applied to examine further underlying connections between the results and SjD. Data source The IEU OpenGWAS database ( https://gwas.mrcieu.ac.uk/ ) provides comprehensive summary statistics on sex hormones, sourced from the UK Biobank. To account for relatedness and population structure, researchers employed a linear mixed model and estimated BT content. The summary statistics for SjD were derived from the FinnGen database version R9 ( https://www.finngen.fi/en/access_results ), ensuring no overlap in samples between the two datasets. Details are provided in Table 1 . Table 1 Description of GWAS used by phenotypes Phenotype Sample size SNPs GWAS ID Ancestry E2 54498 13556363 ukb-d-30800_irnt European E2(males) 147690 7489424 GCST90020091 European E2(females) 163985 7488193 GCST90020092 European TT 425097 16578495 GCST90012114 European TT(males) 199569 12321875 ieu-b-4865 European TT(females) 199569 12321875 ieu-b-4864 European BT 382988 16583148 GCST90012104 European BT(males) 184205 12321875 ieu-b-4868 European BT(females) 180386 12321875 ieu-b-4869 European SHBG 370125 16582965 GCST90012111 European SHBG(males) 185221 12321875 ieu-b-4871 European SHBG(females) 214989 12321875 ieu-b-4870 European SjD 368028 20170011 M13_SJOGREN(R9) European Note: GWAS, Genome-wide association studies, E2, Estradiol, TT, Total testosterone, BT, Bioavailable testosterone, SHBG, Sex hormone binding globulin, SjD, Sjögren’s Disease, SNPs, Single nucleotide polymorphisms Selection of instrumental variables The GWAS database was screened for SNPs that highly correlated with exposure ( P < 5×10 − 8 ), after which a linkage disequilibrium analysis (r 2 10000kb) was conducted. During the analysis, all palindromic SNPs, duplicate SNPs, and SNPs with missing information were excluded. Additionally, the PhenoScanner website was referenced to exclude SNPs significantly associated with SjD ( http://www.phenoscanner.medschl.cam.ac.uk/ ). To avoid bias from weak IVs, F-statistics and the R 2 value were calculated using the following formulas: F = \(\:\:\frac{{\text{R}}^{2}\times\:(\text{n}-2)}{{1-\text{R}}^{2}}\) (n: sample size of the GWAS, R: the proportion of explained variance of the IV), R 2 = 2 × β 2 × (1-EAF) × EAF (β: estimate of the genetic effect of each SNP on iron status, EAF: effect allele frequency). A higher F-value indicates less bias, with the bias level generally considered satisfactory if F > 10 [ 21 – 23 ] . MR analysis and sensitivity analysis Given that all MR assumptions were met, the causal relationship between sex hormones and SjD was assessed using the inverse variance weighted (IVW) random effects model as the primary analytical method [ 24 ] . Supplementary analyses included MR-Egger, weighted median, simple mode, and median mode [ 25 – 26 ] . If one SNP was selected through screening, the Wald ratio method was applied for the analysis. A series of sensitivity analyses were conducted as well, with Cochran's Q test applied to detect heterogeneity, and the MR-Egger intercept test and MR pleiotropy residual sum and outlier (MR-PRESSO) test to evaluate horizontal pleiotropy. The robustness of the results was ensured by correcting for outliers, with the removal of abnormal SNPs from the analysis, and the stability of the results by a leave-one-out analysis. Scatter plots and funnel plots were visualized using the appropriate software. The MR analyses were performed using version 4.3.1 of the R software packages 'TwoSampleMR' and 'MR-PRESSO'. A Bonferroni correction was applied to the results. A significant difference between two groups was defined as a P-value < 0.0042 (0.05/12), and suggestive evidence as a P-value of 0.0042–0.05. Bioinformatics analysis The NCBI PubChem database ( https://pubchem.ncbi.nlm.nih.gov/ ) was queried to retrieve chemical molecular information of testosterone, employing the Swiss Target Prediction ( http://www.swisstargetprediction.ch/ ) and PharmMapper ( http://www.lilab-ecust.cn/pharmmapper/index.html ) databases to predict the targets of testosterone. Duplicate targets were eliminated through merging, to obtain a comprehensive list of testosterone-related targets. Genecard ( https://www.genecards.org/ ) and OMIM ( https://omim.org/ ) databases were used to extract targets associated with SjD, with duplicate targets removed after merging to acquire a refined set of SjD-related targets. Subsequently, the filtered target lists were input into the Venny 2.1 online tool ( https:/bioinfogp.cnb.csic.es/tools/venny/index.html ) to generate a Venn diagram, to identify common targets of testosterone and SjD. Cytoscape software was used to construct a 'drug-target-disease' network diagram. The gene names of the overlapping targets were uploaded to the String database ( https://cn.string-db.org/ ), specifying 'Homo sapiens' as the species, to construct a protein-protein interaction (PPI) network and identify key targets. A GO analysis of the overlapping targets was performed using the Metascape database ( https://metascape.org ), with 'Homo sapiens' selected as the species, to obtain GO data encompassing Molecular Functions, Biological Processes, and Cellular Components. Plotting the results using bioinformatics online tools ( https://www.bioinformatics.com.cn/ ) provided a comprehensive diagram of GO cellular components, molecular functions, and biological processes. A KEGG pathway enrichment analysis on the overlapping targets was conducted using the Metascape database, with 'Homo sapiens' selected as the species to acquire KEGG data. Finally, a bubble chart was generated using bioinformatics online tools to visualize the KEGG pathway enrichment data. Results SNP selection Through rigorous filtering ( P < 5 × 10 -8 , LD–r 2 10000 kb) and based on an F-statistic > 10 for the IVs, a set of 1–184 SNPs was obtained as IVs (Supplementary Table 1) that exhibited a robust association with SjD. There were minimal missing SNPs, and proxy SNPs were not utilized. Causal relationship between sex hormones and SjD The main causal relationship between sex hormones and SjD is illustrated in Figure 2. Based on the IVW results, each one standard deviation (SD) increase in the genetically predicted BT level was associated with a 55% decrease in the risk of developing SjD (odds ratio [OR] = 0.45, 95% confidence interval [95%CI]: 0.30–0.66, P = 5.2357E–05). Suggestive evidence was obtained that each unit increase in genetically predicted BT leads to a 27% reduction in SjD risk among males (OR = 0.73, 95%CI: 0.55–0.98, P = 0.036) and a 20% reduction among females (OR = 0.80, 95%CI: 0.64–0.99, P = 0.377). These findings support a causal relationship between BT and SjD. Additionally, for every one SD decrease in genetically predicted TT, there was a 28% reduction in the risk of developing SjD among females (OR = 0.72, 95% CI: 0.54–0.97, P = 0.306). However, no significant correlations were found with other factors. The findings were corroborated by other analytical methods as well. Consistent and concordant results were observed between BT and SjD in MR-Egger, weighted median, and weighted mode analyses. In the MR-Egger analysis, consistent and concordant results were found between BT (males) and SjD. Similarly, in MR-Egger, weighted median, and weighted mode analyses, consistent and concordant results were obtained between BT (females) and SjD. Only the weighted mode analysis showed consistent and concordant results between TT (females) and SjD (Supplementary Table 2: S1). Sensitivity analysis The reliability of the MR results was assessed in a sensitivity analysis (Supplementary Table 2: S2–S4). There was no horizontal pleiotropy, although some heterogeneity was determined. After the removal of outlier SNPs using MR-PRESSO, the causal effect between BT (males) and SjD disappeared in the MR analysis (rs1264327), (OR = 0.81, 95%CI: 0.64–1.03, P = 0.0856, Supplementary Table 2: S5), all other identified causal relationships were confirmed. The scatter plots, funnel plots, and the results of the leave-one-out analyses are presented in Figure 3 and Supplementary Figure 1. Bioinformatics The results of the 'Drug-Target-Disease', PPI, GO, and KEGG signaling pathway analyses are shown in Figure 4, with details provided in Supplementary Table 3: S4–S7. Among the 380 targets related to testosterone and the 1803 targets related to SjD, there was an overlap of 33 targets (Supplementary Table 3: S1–S3). According to the GO Cellular Components analysis, these genes are associated with cell membranes, transcription regulatory complexes, and complex receptors. The GO Molecular Functions analysis indicated their involvement in transcription factor binding, nuclear receptor activity, steroid binding, and oxidoreductase activity, and the GO Biological Processes analysis their involvement in hormone level regulation, leukocyte differentiation, lipid response regulation, and cellular secretion regulation. These results, combined with the top-ranked KEGG signaling pathways (top 20), were consistent with a role for testosterone in the occurrence and development of SjD through its involvement in hormone synthesis, the inflammatory response, and immune pathways. Discussion In this study, a two-sample MR analysis revealed a significant inverse causal relationship between BT and SjD, as well as a negative correlation between TT (females) and BT (females) with SjD. The subsequent removal of outliers using the MR-PRESSO method eliminated the negative causal effect of BT (males), suggesting that other factors do not have a causal relationship with SjD. These results highlight the crucial role of androgens, particularly in females, in the pathogenesis and progression of SjD. A bioinformatics analysis identified 33 targets shared by testosterone and SjD, while the GO and KEGG pathway analyses indicated the participation of inflammatory and immune-related pathways in the mechanisms linking testosterone to SjD. Our findings of a robust correlation between decreased androgen levels and the occurrence of SjD are supported by previous research [ 14 ] , including the demonstration of a significant deficiency of androgens in patients with SjD and its contribution to dry eye symptoms [ 15 ] . Another study found a persistent and substantial lack of androgens in the salivary glands of SjD patients [ 27 ] . A randomized controlled trial showed that treatment with traditional Chinese medicine aimed at nourishing Yin, invigorating Qi, and promoting blood circulation resulted in remarkable symptom improvement and a notable increase in testosterone levels [ 28 ] . These results, together with our own, point to an association between the development of SjD and insufficient levels of androgens. SjD can lead to glandular secretion disorders, characterized by prominent symptoms of xerostomia and keratoconjunctivitis sicca. Research into the protective and promoting effects of androgens on glandular secretion has included animal studies showing that androgens safeguard salivary gland epithelial cells against apoptosis [ 29 ] . Androgen deficiency was also shown to impair meibomian gland function, resulting in the development of dry eye syndrome [ 30 ] , while clinical studies have indicated an increased risk of meibomian gland dysfunction and dry eye syndrome in patients undergoing anti-androgen therapy [ 31 – 33 ] . Moreover, there is a notable prevalence of dry eye syndrome among older adults, in whom androgen levels are decreased, as well as in postmenopausal women [ 34 – 35 ] . Androgens also play a protective role in tear production and lacrimal gland function [ 36 – 37 ] . These findings suggest that decreased levels of androgens contribute to reduced glandular secretion and thus to the onset and progression of SjD. Testosterone inhibits the inflammatory reactions of SjD through various pathways, including by suppressing the production of pro-inflammatory cytokines such as TNF-α, IL-6, IFN-γ, and IL-2 [ 38 ] , and hindering the activation of the NF-κB signaling pathway to prevent inflammation [ 39 ] . Testosterone also promotes the production of anti-inflammatory cytokine IL-10 [ 40 ] . In mouse models, testosterone reduced toll-like receptor 4 (TLR4) expression and sensitivity in macrophages, while TLR4 expression, which is strongly correlated with NF-κB signaling pathway activation, was significantly increased in castrated mice [ 41 – 42 ] . Human studies have also shown that testosterone treatment downregulates pro-inflammatory TNF-α and IL-1β while upregulating anti-inflammatory IL-10 [ 43 ] . Additionally, reduced levels of inflammatory markers such as TNF-a, IL-lβ and CRP were determined in males with hypogonadism who received intramuscular testosterone injections for 30 weeks [ 44 ] . Testosterone may therefore inhibit the occurrence and development of SjD, by suppressing inflammatory responses. Testosterone plays an immunosuppressive role [ 8 ] and influences various types of immune cells, such as the differentiation of helper T lymphocytes. T lymphocytes primarily undergo development in the thymus and are a crucial component of immune system processes, including antigen recognition, immune memory, and self-tolerance. As such they are one of the main driving forces behind SjD and other autoimmune diseases. Testosterone deficiency leads to thymic enlargement whereas testosterone supplementation restores the thymus to its normal size [ 45 – 46 ] . Additionally, testosterone limits the number of CD4 + and CD8 + cells while promoting the production of TGF-β to induce immune tolerance and affect T cell development [ 47 – 48 ] . The effects of testosterone on B lymphocytes resemble those on T lymphocytes; low levels of testosterone increase B cell numbers [ 49 ] by inducing bone marrow stromal cells to secrete TGF-β while reducing IL-7 levels, required for B cell proliferation and differentiation [ 50 ] . This relationship is supported by the poor antibody responses after vaccination in males with higher testosterone levels [ 51 ] . Furthermore, differences have been noted in B cell subgroups among children 3–8 years of age, with elevated levels of CD5 + cells in males and a larger proportion of memory-type B cells in females, which also correlates with their respective testosterone levels [ 52 ] . In summary, androgens have a direct impact on the quantity and differentiation of lymphocytes, thereby exerting immunosuppressive effects and impeding the development of autoimmune diseases. This may also account for the lower incidence rates of those diseases in males. That androgen deficiency results in reduced immune suppression, leading to the occurrence of SjD, aligns with the findings of the present study. The relationship between testosterone and autoimmune diseases, and specifically SjD, was supported by the bioinformatics analysis, which identified 33 common target genes. The PPI analysis revealed the significance of genes encoding PPARG, IL-6, TNF, CYP19A1, CYP17A1, and ERBB2 in mediating the interaction between testosterone and SjD. These genes are closely associated with oxidative stress, inflammation, and immunity. The GO analysis demonstrated strong associations between these biological processes and hormone regulation, leukocyte differentiation, cell secretion regulation and inflammation/immunity, and the KEGG pathway analysis a close relationship between TNF/NF-κB signaling pathways and inflammation [ 53 – 54 ] . Interactions involving viral proteins/cytokines/receptors and viral infections also showed significant relevance to the immune system. In summary, our results indicate that inflammatory and immune-related pathways underlie the connection between testosterone and SjD. Although we did not obtain evidence of a causal relationship involving E2 and SHBG with SjD, a negative correlation between SHBG and serum immunoglobulin levels (anti-SSA and anti-SSB) was determined in a case-control study [ 55 ] . In our study there was also no association between disease activity in SjD and estrogen, whereas another case-control study focusing on primary SjD patients demonstrated an inverse association between increased estrogen exposure and the occurrence of primary SjD [ 12 ] . Given the intricate mechanisms underlying estrogen, SHBG, and SjD, the differences in susceptibility to confounding factors, and the limitations posed by a small sample size, drawing reliable conclusions regarding causal relationships must await further research. Our study is the first to employ MR analysis to evaluate the potential causal association between sex hormones and SjD. By implementing stringent selection criteria, we were able to mitigate partially the influence of confounding factors. Moreover, our sex-stratified design corroborated the impact of androgens in female SjD patients, while also providing evidence of a higher prevalence of SjD in females due to androgenic effects. By leveraging bioinformatics techniques, we obtained insights into the mechanisms linking these variables together. Consistent with findings from previous basic research, we showed that androgens exert a suppressive effect on SjD development by protecting glandular secretion, inhibiting inflammatory responses, and inducing immunosuppression. These findings suggest valuable avenues of further research into the pathogenesis, treatment, and prevention of SjD. Despite its strengths, our study also had several limitations. First, the generalizability of our findings to other populations may be limited as our data were derived only from Europeans. Second, the power of our study results may have been reduced by the relatively small number of SNPs identified through screening when estrogen was used as an exposure; validation with GWAS data based on a larger sample is needed. Third, while our analyses were sex-stratified, we have not conducted an age-stratified analysis, which prevented the definitive exclusion of age factors. Conclusions Our study showed a clear causal relationship between androgens and the risk of SjD, particularly in females. Androgen deficiency contributed to the development of SjD via inflammation and immune-related pathways. Further elucidation of the relationship between androgen deficiency and SjD awaits larger-scale clinical and experimental research investigating specific mechanisms for intervention as well as potential avenues for the prevention and treatment of SjD. Abbreviations BT Bioavailable testosterone CI Confidence interval E2 Estradiol EAF Effect allele frequency GWAS Genome-wide association studies IV Instrumental variable IVW Inverse-variance weighted LD Linkage disequilibrium MR Mendelian randomization MR-PRESSO MR-Pleiotropy Residual Sum and Outlier methods OR Odds ratio SHBG Sex hormone binding globulin SNPs Single nucleotide polymorphisms SjD Sjögren’s Disease TT Total testosterone Declarations Ethics approval and consent: not applicable. Conflicts of interest The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Authors’ contributions HJ, SR, MZ designed this study, HJ, JX, LG obtained and analyzed the data, HJ, DX, SR, BL, YC, participated in article writing and chart design, YZ, JG guided the entire study, all authors contributed to this paper, and read and approved the final manuscript. Funding This research received no funding. Acknowledgement We would like to extend our sincere appreciation to all the data providers and participants involved in this study, as well as FinnGen and UK Biobank and their affiliated alliances for their exceptional management and collaborative efforts in sharing these invaluable statistical data. We appreciate the review by two professional English editors. For a certificate, please see: http://www.textcheck.com/certificate/cXYHxs. Data availability statement Summary statistics are available in the website https://www.ebi.ac.uk/gwas/ for GWAS of estradiol (males), estradiol (females), testosterone, bioavailable testosterone and sex hormone-binding globulin, https://gwas.mrcieu.ac.uk/ for GWAS of estradiol, testosterone (males), testosterone (females), bioavailable testosterone (males), bioavailable testosterone (females), sex hormone-binding globulin (males), sex hormone-binding globulin (females), https://www.finngen.fi/en/access_results for GWAS of Sjögren’s Disease. Further information is available from the corresponding author upon request. References Fox RI. Sjögren’s syndrome. Lancet . 2005;366(9482):321-331. doi:10.1016/S0140-6736(05)66990-5 Mavragani CP, Moutsopoulos HM. The geoepidemiology of Sjögren’s syndrome. Autoimmun Rev . 2010;9(5):A305-310. doi:10.1016/j.autrev.2009.11.004 Patel R, Shahane A. The epidemiology of Sjögren’s syndrome. 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Ann N Y Acad Sci . 2002;966:211-222. doi:10.1111/j.1749-6632.2002.tb04217.x Sullivan DA, Yamagami H, Liu M, et al. Sex steroids, the meibomian gland and evaporative dry eye. Adv Exp Med Biol . 2002;506(Pt A):389-399. doi:10.1007/978-1-4615-0717-8_56 Cermak JM, Krenzer KL, Sullivan RM, Dana MR, Sullivan DA. Is complete androgen insensitivity syndrome associated with alterations in the meibomian gland and ocular surface? Cornea . 2003;22(6):516-521. doi:10.1097/00003226-200308000-00006 Sriprasert I, Warren DW, Mircheff AK, Stanczyk FZ. Dry eye in postmenopausal women: a hormonal disorder. Menopause . 2016;23(3):343-351. doi:10.1097/GME.0000000000000530 Grossmann M, Wu FC. Male androgen deficiency: a multisystem syndrome. Asian J Androl . 2014;16(2):159-160. doi:10.4103/1008-682X.122587 Song X, Zhao P, Wang G, Zhao X. The effects of estrogen and androgen on tear secretion and matrix metalloproteinase-2 expression in lacrimal glands of ovariectomized rats. Invest Ophthalmol Vis Sci . 2014;55(2):745-751. doi:10.1167/iovs.12-10457 Truong S, Cole N, Stapleton F, Golebiowski B. Sex hormones and the dry eye. Clin Exp Optom . 2014;97(4):324-336. doi:10.1111/cxo.12147 Fijak M, Schneider E, Klug J, et al. Testosterone replacement effectively inhibits the development of experimental autoimmune orchitis in rats: evidence for a direct role of testosterone on regulatory T cell expansion. J Immunol . 2011;186(9):5162-5172. doi:10.4049/jimmunol.1001958 Wang X, Huang L, Jiang S, et al. Testosterone attenuates pulmonary epithelial inflammation in male rats of COPD model through preventing NRF1-derived NF-κB signaling. J Mol Cell Biol . 2021;13(2):128-140. doi:10.1093/jmcb/mjaa079 Mohamad NV, Wong SK, Wan Hasan WN, et al. The relationship between circulating testosterone and inflammatory cytokines in men. Aging Male . 2019;22(2):129-140. doi:10.1080/13685538.2018.1482487 Rettew JA, Huet-Hudson YM, Marriott I. Testosterone reduces macrophage expression in the mouse of toll-like receptor 4, a trigger for inflammation and innate immunity. Biol Reprod . 2008;78(3):432-437. doi:10.1095/biolreprod.107.063545 Chen L, Deng H, Cui H, et al. Inflammatory responses and inflammation-associated diseases in organs. Oncotarget . 2018;9(6):7204-7218. doi:10.18632/oncotarget.23208 Malkin CJ, Pugh PJ, Jones RD, Kapoor D, Channer KS, Jones TH. The effect of testosterone replacement on endogenous inflammatory cytokines and lipid profiles in hypogonadal men. J Clin Endocrinol Metab . 2004;89(7):3313-3318. doi:10.1210/jc.2003-031069 Kalinchenko SY, Tishova YA, Mskhalaya GJ, Gooren LJG, Giltay EJ, Saad F. Effects of testosterone supplementation on markers of the metabolic syndrome and inflammation in hypogonadal men with the metabolic syndrome: the double-blinded placebo-controlled Moscow study. Clin Endocrinol (Oxf) . 2010;73(5):602-612. doi:10.1111/j.1365-2265.2010.03845.x Sutherland JS, Goldberg GL, Hammett MV, et al. Activation of thymic regeneration in mice and humans following androgen blockade. J Immunol . 2005;175(4):2741-2753. doi:10.4049/jimmunol.175.4.2741 Olsen NJ, Watson MB, Henderson GS, Kovacs WJ. Androgen deprivation induces phenotypic and functional changes in the thymus of adult male mice. Endocrinology . 1991;129(5):2471-2476. doi:10.1210/endo-129-5-2471 Roden AC, Moser MT, Tri SD, et al. Augmentation of T cell levels and responses induced by androgen deprivation. J Immunol . 2004;173(10):6098-6108. doi:10.4049/jimmunol.173.10.6098 Zhu ML, Bakhru P, Conley B, et al. Sex bias in CNS autoimmune disease mediated by androgen control of autoimmune regulator. Nat Commun . 2016;7:11350. doi:10.1038/ncomms11350 Olsen NJ, Kovacs WJ. Effects of androgens on T and B lymphocyte development. Immunol Res . 2001;23(2-3):281-288. doi:10.1385/IR:23:2-3:281 Ellis TM, Moser MT, Le PT, Flanigan RC, Kwon ED. Alterations in peripheral B cells and B cell progenitors following androgen ablation in mice. Int Immunol . 2001;13(4):553-558. doi:10.1093/intimm/13.4.553 Furman D, Hejblum BP, Simon N, et al. Systems analysis of sex differences reveals an immunosuppressive role for testosterone in the response to influenza vaccination. Proc Natl Acad Sci U S A . 2014;111(2):869-874. doi:10.1073/pnas.1321060111 Lundell AC, Nordström I, Andersson K, et al. Dihydrotestosterone levels at birth associate positively with higher proportions of circulating immature/naïve CD5+ B cells in boys. Sci Rep . 2017;7(1):15503. doi:10.1038/s41598-017-15836-1 Hayden MS, Ghosh S. NF-κB, the first quarter-century: remarkable progress and outstanding questions. Genes Dev. 2012;26(3):203-234. doi:10.1101/gad.183434.111 van Loo G, Bertrand MJM. Death by TNF: a road to inflammation. Nat Rev Immunol. 2023;23(5):289-303. doi:10.1038/s41577-022-00792-3 Brennan MT, Sankar V, Leakan RA, et al. Sex steroid hormones in primary Sjögren's syndrome. J Rheumatol. 2003;30(6):1267-1271. Additional Declarations No competing interests reported. Supplementary Files STROBEMR.docx SupplementaryFigure1.docx Supplementarytable1.xlsx Supplementarytable2.xlsx Supplementarytable3.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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies 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-4690434","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":337839272,"identity":"2f0b0a61-928a-40f9-a933-3848539b30da","order_by":0,"name":"haonan jin","email":"","orcid":"","institution":"the Central Hospital Affiliated to Shaoxing University","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"haonan","middleName":"","lastName":"jin","suffix":""},{"id":337839273,"identity":"9e47dab3-b911-4db2-9c37-24c5314eb377","order_by":1,"name":"shanshan ru","email":"","orcid":"","institution":"the Central Hospital Affiliated to Shaoxing 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07:31:13","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4690434/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4690434/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62466509,"identity":"c4af569c-4b80-4f7f-93ad-73e271e26df7","added_by":"auto","created_at":"2024-08-14 13:35:32","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":42771,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eMR Study design of sex hormones and SjD\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/74331bee275d2c4eb683d870.png"},{"id":62467165,"identity":"f239f73a-3d7d-4d54-b8a5-37fb16ff33b0","added_by":"auto","created_at":"2024-08-14 13:43:33","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":150102,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eCausal effects of sex hormones on SjD risk in MR Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: OR, Odds ratio, CI, Confidence intervals, IVW, Inverse-variance weighted, E2, Estradiol, TT, Total testosterone, BT, Bioavailable testosterone, SHBG, Sex hormone binding globulin, SjD, Sjögren’s Disease, SNPs, Single nucleotide polymorphisms\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/51800759c6afcc1fe0cb0135.png"},{"id":62467163,"identity":"4cbc99b1-aba5-4e26-9b3c-288afbb3415f","added_by":"auto","created_at":"2024-08-14 13:43:32","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1645793,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe result of Sensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: (A) Scatter plot of causality between TT (females) and SjD, (B) Scatter plot of causality between BT and SjD, (C) Scatter plot of causality between BT (females) and SjD, (D) Funnel plot of causality between TT (females) and SjD, (E) Funnel plot of causality between BT and SjD, (F) Funnel plot of causality between BT (females) and SjD, (G) Leave-one-out analysis between TT (females) and SjD, (H) Leave-one-out analysis between BT and SjD, (I) Leave-one-out analysis between BT (females) and SjD.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/48bf221f8b37157a3527ba11.png"},{"id":62467166,"identity":"1f6f446b-6ae5-4018-ac3d-bf65426e1017","added_by":"auto","created_at":"2024-08-14 13:43:33","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":2428632,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eThe result of Sensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNote: (A) Scatter plot of causality between TT (females) and SjD, (B) Scatter plot of causality between BT and SjD, (C) Scatter plot of causality between BT (females) and SjD, (D) Funnel plot of causality between TT (females) and SjD, (E) Funnel plot of causality between BT and SjD, (F) Funnel plot of causality between BT (females) and SjD, (G) Leave-one-out analysis between TT (females) and SjD, (H) Leave-one-out analysis between BT and SjD, (I) Leave-one-out analysis between BT (females) and SjD.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/1cfdac1a824806e3ec7ca934.png"},{"id":64034026,"identity":"1ffcd5ef-56e7-4d8e-8fed-c836ca5d9ba8","added_by":"auto","created_at":"2024-09-05 10:02:16","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":5204910,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/861a3d62-9271-4f74-b56e-3f8ca511c4a5.pdf"},{"id":62467929,"identity":"9d134da3-eef9-430e-9360-e060a2e93b28","added_by":"auto","created_at":"2024-08-14 13:51:33","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":48691,"visible":true,"origin":"","legend":"","description":"","filename":"STROBEMR.docx","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/51c0b00e58071e375dd9fcae.docx"},{"id":62466514,"identity":"f9bbd8ca-e283-467a-b899-530fc55c80c2","added_by":"auto","created_at":"2024-08-14 13:35:33","extension":"docx","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":1314265,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryFigure1.docx","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/47e988c316df1cb132641086.docx"},{"id":62466512,"identity":"10113b37-edbe-4f11-bebe-a0e84408ba77","added_by":"auto","created_at":"2024-08-14 13:35:33","extension":"xlsx","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":334381,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable1.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/f22ddd3418b8171efd196dcd.xlsx"},{"id":62466513,"identity":"9938b014-57dd-4892-bbeb-a3f10d097312","added_by":"auto","created_at":"2024-08-14 13:35:33","extension":"xlsx","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":21226,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable2.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/dfc1d055dac9148625b4ec59.xlsx"},{"id":62466516,"identity":"dda70217-1b2a-4429-b37a-d6773db447c0","added_by":"auto","created_at":"2024-08-14 13:35:34","extension":"xlsx","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":240922,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarytable3.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4690434/v1/67a46583193cc669d59cb57d.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSex hormones and Sjögren’s Disease: A Mendelian randomization study\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eSj\u0026ouml;gren's syndrome (SjD) is a chronic inflammatory autoimmune disease characterized by lymphocyte proliferation and the involvement of various exocrine glands throughout the body, leading to impaired secretion. It can be classified into primary and secondary types \u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. According to consensus standards in the United States and Europe, SjD is one of the most prevalent autoimmune diseases, alongside systemic lupus erythematosus and rheumatoid arthritis. The prevalence of SjD varies from 0.1\u0026ndash;4.8%, a range that reflects differences in population demographics \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e, with a significantly higher incidence in females than in males (ratio of approximately 9:1). Postmenopausal women around the age of 50 are particularly susceptible \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. SjD affects multiple systems throughout the body, resulting not only in obvious dryness of the eyes and mouth but also interstitial lung disease, gastrointestinal disorders, cognitive impairment, and even cancer \u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. While the specific causes and mechanisms underlying SjD are unclear, genetic susceptibility may lead to disease development under certain environmental influences.\u003c/p\u003e \u003cp\u003eThe interaction between innate immunity and the adaptive immune system plays a crucial role in the onset and progression of SjD, as B cells produce autoantibodies that trigger chronic inflammation in tear glands, salivary glands, and other exocrine glands \u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. Autoimmune diseases often exhibit sex-based differences, with a higher prevalence in females than in males. The severity, course, treatment, and survival rates also vary between sexes \u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. The immunostimulatory effects of estrogen are thought to underlie its role in autoimmune diseases, whereas testosterone plays an immunosuppressive role \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Hormone replacement therapy has therefore been used in the treatment of certain autoimmune diseases \u003csup\u003e[\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eSeveral studies have investigated the association between sex hormones and SjD. A case-control study involving 2680 participants found that women with primary SjD had a lower exposure to estrogen and that increased exposure correlated negatively with the occurrence of primary SjD \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. However, another nested case-control study suggested that estrogen exposure contributes to SjD onset \u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. Furthermore, research has shown that female SjD patients lack testosterone, including a significant deficiency in salivary gland testosterone levels, thus pointing to testosterone deficiency as a driving factor in SjD \u003csup\u003e[\u003cspan additionalcitationids=\"CR15\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]\u003c/sup\u003e. Interestingly, female patients with Turner syndrome who have normal levels of sex hormones and normal development still have an elevated risk of developing SjD. This suggests that the risk of SjD is associated with chromosomal abnormalities rather than being solely influenced by sex hormone levels \u003csup\u003e[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. The conflicting results regarding the relationship between sex hormones and SjD are likely to reflect limitations within existing studies and thus the need for further investigation of a causal effect between sex hormones and SjD.\u003c/p\u003e \u003cp\u003eMendelian randomization (MR) uses genetic variation to investigate causal relationships between exposure and outcome \u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e. Three assumptions must be satisfied in a MR analysis: 1) genetic variation is associated with exposure, 2) genetic variation is independent of confounding factors between exposure and outcome, and 3) genetic variation only affects the outcome through exposure \u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. According to Mendel's law of random assortment, genetic variation is randomly allocated during meiosis and is therefore unaffected by confounding factors \u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we employed two-sample MR analysis methods utilizing published European-population-wide genome-wide association study (GWAS) data and the FinnGen database data to investigate the causal effects of sex hormones (estradiol (E2), total testosterone (TT), bioavailable testosterone (BT), and sex-hormone-binding globulin (SHBG)) on SjD. We then validated the findings by stratifying them based on sex. The data were analyzed by employing bioinformatics techniques. Bioinformatics can assist researchers in comprehensively analyzing the relationship between drugs and diseases from a systematic perspective. It aids in predicting drug targets and functions while providing insights into potential therapeutic strategies. By integrating disciplines such as systems biology, computer databases, biological networks, and pharmacology, it facilitates exploration of the connections between diseases and drugs. In this study, a bioinformatics approach was applied to explore the overlapping targets between our experimental findings and SjD by constructing a 'drug-target-disease' network. The results were further examined in protein-protein interaction (PPI), gene ontology (GO), and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses, with the aim of deciphering the connections between SjD and sex hormones.\u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eResearch design\u003c/h2\u003e \u003cp\u003eThe present study is based on publicly available research data, including published summary data, the FinnGen database, and IEU OpenGWAS data. Ethical approval and participant consent were previously obtained for the use of these datasets in research. A two-sample MR analysis was employed to investigate potential causal relationships between sex hormones and SjD. Sex stratification was then conducted to examine whether those relationships differ between males and females. The instrumental variables (IVs) satisfied all three assumptions (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Bioinformatics methods were subsequently applied to examine further underlying connections between the results and SjD.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData source\u003c/h2\u003e \u003cp\u003eThe IEU OpenGWAS 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) provides comprehensive summary statistics on sex hormones, sourced from the UK Biobank. To account for relatedness and population structure, researchers employed a linear mixed model and estimated BT content. The summary statistics for SjD were derived from the FinnGen database version R9 (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.finngen.fi/en/access_results\u003c/span\u003e\u003cspan address=\"https://www.finngen.fi/en/access_results\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), ensuring no overlap in samples between the two datasets. Details are provided in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\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\u003eDescription of GWAS used by phenotypes\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"5\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" 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=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhenotype\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSample size\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eSNPs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGWAS ID\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eAncestry\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e54498\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13556363\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eukb-d-30800_irnt\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2(males)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e147690\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7489424\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGCST90020091\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE2(females)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e163985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e7488193\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGCST90020092\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e425097\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16578495\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGCST90012114\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT(males)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e199569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12321875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eieu-b-4865\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTT(females)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e199569\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12321875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eieu-b-4864\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBT\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e382988\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16583148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGCST90012104\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBT(males)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e184205\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12321875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eieu-b-4868\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBT(females)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e180386\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12321875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eieu-b-4869\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSHBG\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e370125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e16582965\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eGCST90012111\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSHBG(males)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e185221\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12321875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eieu-b-4871\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSHBG(females)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e214989\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12321875\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eieu-b-4870\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSjD\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e368028\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e20170011\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eM13_SJOGREN(R9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eEuropean\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"5\"\u003eNote: GWAS, Genome-wide association studies, E2, Estradiol, TT, Total testosterone, BT, Bioavailable testosterone, SHBG, Sex hormone binding globulin, SjD, Sj\u0026ouml;gren\u0026rsquo;s Disease, SNPs, Single nucleotide polymorphisms\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eSelection of instrumental variables\u003c/h2\u003e \u003cp\u003eThe GWAS database was screened for SNPs that highly correlated with exposure (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e), after which a linkage disequilibrium analysis (r\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001 and clumping distance\u0026thinsp;\u0026gt;\u0026thinsp;10000kb) was conducted. During the analysis, all palindromic SNPs, duplicate SNPs, and SNPs with missing information were excluded. Additionally, the PhenoScanner website was referenced to exclude SNPs significantly associated with SjD (\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 avoid bias from weak IVs, F-statistics and the R\u003csup\u003e2\u003c/sup\u003e value were calculated using the following formulas: F =\u003cspan class=\"InlineEquation\"\u003e\u003cspan class=\"mathinline\"\u003e\\(\\:\\:\\frac{{\\text{R}}^{2}\\times\\:(\\text{n}-2)}{{1-\\text{R}}^{2}}\\)\u003c/span\u003e\u003c/span\u003e (n: sample size of the GWAS, R: the proportion of explained variance of the IV), R\u003csup\u003e2\u003c/sup\u003e = 2\u0026thinsp;\u0026times;\u0026thinsp;β\u003csup\u003e2\u003c/sup\u003e \u0026times; (1-EAF) \u0026times; EAF (β: estimate of the genetic effect of each SNP on iron status, EAF: effect allele frequency). A higher F-value indicates less bias, with the bias level generally considered satisfactory if F \u0026gt;\u0026thinsp;10 \u003csup\u003e[\u003cspan additionalcitationids=\"CR22\" citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eMR analysis and sensitivity analysis\u003c/h2\u003e \u003cp\u003eGiven that all MR assumptions were met, the causal relationship between sex hormones and SjD was assessed using the inverse variance weighted (IVW) random effects model as the primary analytical method \u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e. Supplementary analyses included MR-Egger, weighted median, simple mode, and median mode \u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. If one SNP was selected through screening, the Wald ratio method was applied for the analysis. A series of sensitivity analyses were conducted as well, with Cochran's Q test applied to detect heterogeneity, and the MR-Egger intercept test and MR pleiotropy residual sum and outlier (MR-PRESSO) test to evaluate horizontal pleiotropy. The robustness of the results was ensured by correcting for outliers, with the removal of abnormal SNPs from the analysis, and the stability of the results by a leave-one-out analysis. Scatter plots and funnel plots were visualized using the appropriate software.\u003c/p\u003e \u003cp\u003eThe MR analyses were performed using version 4.3.1 of the R software packages 'TwoSampleMR' and 'MR-PRESSO'. A Bonferroni correction was applied to the results. A significant difference between two groups was defined as a P-value\u0026thinsp;\u0026lt;\u0026thinsp;0.0042 (0.05/12), and suggestive evidence as a P-value of 0.0042\u0026ndash;0.05.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eBioinformatics analysis\u003c/h2\u003e \u003cp\u003eThe NCBI PubChem database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://pubchem.ncbi.nlm.nih.gov/\u003c/span\u003e\u003cspan address=\"https://pubchem.ncbi.nlm.nih.gov/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was queried to retrieve chemical molecular information of testosterone, employing the Swiss Target Prediction (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.swisstargetprediction.ch/\u003c/span\u003e\u003cspan address=\"http://www.swisstargetprediction.ch/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and PharmMapper (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.lilab-ecust.cn/pharmmapper/index.html\u003c/span\u003e\u003cspan address=\"http://www.lilab-ecust.cn/pharmmapper/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases to predict the targets of testosterone. Duplicate targets were eliminated through merging, to obtain a comprehensive list of testosterone-related targets. Genecard (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.genecards.org/\u003c/span\u003e\u003cspan address=\"https://www.genecards.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) and OMIM (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://omim.org/\u003c/span\u003e\u003cspan address=\"https://omim.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) databases were used to extract targets associated with SjD, with duplicate targets removed after merging to acquire a refined set of SjD-related targets. Subsequently, the filtered target lists were input into the Venny 2.1 online tool (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps:/bioinfogp.cnb.csic.es/tools/venny/index.html\u003c/span\u003e\u003cspan address=\"https://bioinfogp.cnb.csic.es/tools/venny/index.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to generate a Venn diagram, to identify common targets of testosterone and SjD. Cytoscape software was used to construct a 'drug-target-disease' network diagram. The gene names of the overlapping targets were uploaded to the String database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://cn.string-db.org/\u003c/span\u003e\u003cspan address=\"https://cn.string-db.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), specifying 'Homo sapiens' as the species, to construct a protein-protein interaction (PPI) network and identify key targets. A GO analysis of the overlapping targets was performed using the Metascape database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://metascape.org\u003c/span\u003e\u003cspan address=\"https://metascape.org\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e), with 'Homo sapiens' selected as the species, to obtain GO data encompassing Molecular Functions, Biological Processes, and Cellular Components. Plotting the results using bioinformatics online tools (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.bioinformatics.com.cn/\u003c/span\u003e\u003cspan address=\"https://www.bioinformatics.com.cn/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) provided a comprehensive diagram of GO cellular components, molecular functions, and biological processes. A KEGG pathway enrichment analysis on the overlapping targets was conducted using the Metascape database, with 'Homo sapiens' selected as the species to acquire KEGG data. Finally, a bubble chart was generated using bioinformatics online tools to visualize the KEGG pathway enrichment data.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eSNP selection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThrough rigorous filtering (\u003cem\u003eP\u003c/em\u003e \u0026lt; 5 \u0026times; 10\u003csup\u003e-8\u003c/sup\u003e, LD\u0026ndash;r\u003csup\u003e2\u0026nbsp;\u003c/sup\u003e\u0026lt; 0.001, clumping distance \u0026gt; 10000 kb) and based on an F-statistic \u0026gt; 10 for the IVs, a set of 1\u0026ndash;184 SNPs was obtained as IVs (Supplementary Table 1) that exhibited a robust association with SjD. There were minimal missing SNPs, and proxy SNPs were not utilized.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCausal relationship between sex hormones and SjD\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe main causal relationship between sex hormones and SjD is illustrated in Figure 2. Based on the IVW results, each one standard deviation (SD) increase in the genetically predicted BT level was associated with a 55% decrease in the risk of developing SjD (odds ratio [OR] = 0.45, 95% confidence interval [95%CI]: 0.30\u0026ndash;0.66, \u003cem\u003eP\u003c/em\u003e = 5.2357E\u0026ndash;05). Suggestive evidence was obtained that each unit increase in genetically predicted BT leads to a 27% reduction in SjD risk among males (OR = 0.73, 95%CI: 0.55\u0026ndash;0.98, \u003cem\u003eP\u003c/em\u003e = 0.036) and a 20% reduction among females (OR = 0.80, 95%CI: 0.64\u0026ndash;0.99, \u003cem\u003eP\u003c/em\u003e = 0.377). These findings support a causal relationship between BT and SjD. Additionally, for every one SD decrease in genetically predicted TT, there was a 28% reduction in the risk of developing SjD among females (OR = 0.72, 95% CI: 0.54\u0026ndash;0.97, \u003cem\u003eP\u003c/em\u003e = 0.306). However, no significant correlations were found with other factors. The findings were corroborated by other analytical methods as well. Consistent and concordant results were observed between BT and SjD in MR-Egger, weighted median, and weighted mode analyses. In the MR-Egger analysis, consistent and concordant results were found between BT (males) and SjD. Similarly, in MR-Egger, weighted median, and weighted mode analyses, consistent and concordant results were obtained between BT (females) and SjD. Only the weighted mode analysis showed consistent and concordant results between TT (females) and SjD (Supplementary Table 2: S1).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSensitivity analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe reliability of the MR results was assessed in a sensitivity analysis (Supplementary Table 2: S2\u0026ndash;S4). There was no horizontal pleiotropy, although some heterogeneity was determined. After the removal of outlier SNPs using MR-PRESSO, the causal effect between BT (males) and SjD disappeared in the MR analysis (rs1264327), (OR = 0.81, 95%CI: 0.64\u0026ndash;1.03, P = 0.0856, Supplementary Table 2: S5), all other identified causal relationships were confirmed. The scatter plots, funnel plots, and the results of the leave-one-out analyses are presented in Figure 3 and Supplementary Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eBioinformatics\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe results of the \u0026apos;Drug-Target-Disease\u0026apos;, PPI, GO, and KEGG signaling pathway analyses are shown in Figure 4, with details provided in Supplementary Table 3: S4\u0026ndash;S7. Among the 380 targets related to testosterone and the 1803 targets related to SjD, there was an overlap of 33 targets (Supplementary Table 3: S1\u0026ndash;S3). According to the GO Cellular Components analysis, these genes are associated with cell membranes, transcription regulatory complexes, and complex receptors. The GO Molecular Functions analysis indicated their involvement in transcription factor binding, nuclear receptor activity, steroid binding, and oxidoreductase activity, \u0026nbsp;and the GO Biological Processes analysis their involvement in hormone level regulation, leukocyte differentiation, lipid response regulation, and cellular secretion regulation. These results, combined with the top-ranked KEGG signaling pathways (top 20), were consistent with a role for testosterone in the occurrence and development of SjD through its involvement in hormone synthesis, the inflammatory response, and immune pathways.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, a two-sample MR analysis revealed a significant inverse causal relationship between BT and SjD, as well as a negative correlation between TT (females) and BT (females) with SjD. The subsequent removal of outliers using the MR-PRESSO method eliminated the negative causal effect of BT (males), suggesting that other factors do not have a causal relationship with SjD. These results highlight the crucial role of androgens, particularly in females, in the pathogenesis and progression of SjD. A bioinformatics analysis identified 33 targets shared by testosterone and SjD, while the GO and KEGG pathway analyses indicated the participation of inflammatory and immune-related pathways in the mechanisms linking testosterone to SjD.\u003c/p\u003e \u003cp\u003eOur findings of a robust correlation between decreased androgen levels and the occurrence of SjD are supported by previous research \u003csup\u003e[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e, including the demonstration of a significant deficiency of androgens in patients with SjD and its contribution to dry eye symptoms \u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e. Another study found a persistent and substantial lack of androgens in the salivary glands of SjD patients \u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. A randomized controlled trial showed that treatment with traditional Chinese medicine aimed at nourishing Yin, invigorating Qi, and promoting blood circulation resulted in remarkable symptom improvement and a notable increase in testosterone levels \u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e. These results, together with our own, point to an association between the development of SjD and insufficient levels of androgens.\u003c/p\u003e \u003cp\u003eSjD can lead to glandular secretion disorders, characterized by prominent symptoms of xerostomia and keratoconjunctivitis sicca. Research into the protective and promoting effects of androgens on glandular secretion has included animal studies showing that androgens safeguard salivary gland epithelial cells against apoptosis \u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e. Androgen deficiency was also shown to impair meibomian gland function, resulting in the development of dry eye syndrome \u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e, while clinical studies have indicated an increased risk of meibomian gland dysfunction and dry eye syndrome in patients undergoing anti-androgen therapy \u003csup\u003e[\u003cspan additionalcitationids=\"CR32\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e. Moreover, there is a notable prevalence of dry eye syndrome among older adults, in whom androgen levels are decreased, as well as in postmenopausal women \u003csup\u003e[\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]\u003c/sup\u003e. Androgens also play a protective role in tear production and lacrimal gland function \u003csup\u003e[\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/sup\u003e. These findings suggest that decreased levels of androgens contribute to reduced glandular secretion and thus to the onset and progression of SjD.\u003c/p\u003e \u003cp\u003eTestosterone inhibits the inflammatory reactions of SjD through various pathways, including by suppressing the production of pro-inflammatory cytokines such as TNF-α, IL-6, IFN-γ, and IL-2 \u003csup\u003e[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]\u003c/sup\u003e, and hindering the activation of the NF-κB signaling pathway to prevent inflammation \u003csup\u003e[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/sup\u003e. Testosterone also promotes the production of anti-inflammatory cytokine IL-10 \u003csup\u003e[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/sup\u003e. In mouse models, testosterone reduced toll-like receptor 4 (TLR4) expression and sensitivity in macrophages, while TLR4 expression, which is strongly correlated with NF-κB signaling pathway activation, was significantly increased in castrated mice \u003csup\u003e[\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]\u003c/sup\u003e. Human studies have also shown that testosterone treatment downregulates pro-inflammatory TNF-α and IL-1β while upregulating anti-inflammatory IL-10 \u003csup\u003e[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]\u003c/sup\u003e. Additionally, reduced levels of inflammatory markers such as TNF-a, IL-lβ and CRP were determined in males with hypogonadism who received intramuscular testosterone injections for 30 weeks \u003csup\u003e[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]\u003c/sup\u003e. Testosterone may therefore inhibit the occurrence and development of SjD, by suppressing inflammatory responses.\u003c/p\u003e \u003cp\u003eTestosterone plays an immunosuppressive role \u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e and influences various types of immune cells, such as the differentiation of helper T lymphocytes. T lymphocytes primarily undergo development in the thymus and are a crucial component of immune system processes, including antigen recognition, immune memory, and self-tolerance. As such they are one of the main driving forces behind SjD and other autoimmune diseases. Testosterone deficiency leads to thymic enlargement whereas testosterone supplementation restores the thymus to its normal size \u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e. Additionally, testosterone limits the number of CD4\u003csup\u003e+\u003c/sup\u003e and CD8\u003csup\u003e+\u003c/sup\u003e cells while promoting the production of TGF-β to induce immune tolerance and affect T cell development \u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e. The effects of testosterone on B lymphocytes resemble those on T lymphocytes; low levels of testosterone increase B cell numbers \u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]\u003c/sup\u003e by inducing bone marrow stromal cells to secrete TGF-β while reducing IL-7 levels, required for B cell proliferation and differentiation \u003csup\u003e[\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e. This relationship is supported by the poor antibody responses after vaccination in males with higher testosterone levels \u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]\u003c/sup\u003e. Furthermore, differences have been noted in B cell subgroups among children 3\u0026ndash;8 years of age, with elevated levels of CD5\u003csup\u003e+\u003c/sup\u003e cells in males and a larger proportion of memory-type B cells in females, which also correlates with their respective testosterone levels \u003csup\u003e[\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e. In summary, androgens have a direct impact on the quantity and differentiation of lymphocytes, thereby exerting immunosuppressive effects and impeding the development of autoimmune diseases. This may also account for the lower incidence rates of those diseases in males. That androgen deficiency results in reduced immune suppression, leading to the occurrence of SjD, aligns with the findings of the present study.\u003c/p\u003e \u003cp\u003eThe relationship between testosterone and autoimmune diseases, and specifically SjD, was supported by the bioinformatics analysis, which identified 33 common target genes. The PPI analysis revealed the significance of genes encoding PPARG, IL-6, TNF, CYP19A1, CYP17A1, and ERBB2 in mediating the interaction between testosterone and SjD. These genes are closely associated with oxidative stress, inflammation, and immunity. The GO analysis demonstrated strong associations between these biological processes and hormone regulation, leukocyte differentiation, cell secretion regulation and inflammation/immunity, and the KEGG pathway analysis a close relationship between TNF/NF-κB signaling pathways and inflammation \u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e. Interactions involving viral proteins/cytokines/receptors and viral infections also showed significant relevance to the immune system. In summary, our results indicate that inflammatory and immune-related pathways underlie the connection between testosterone and SjD.\u003c/p\u003e \u003cp\u003eAlthough we did not obtain evidence of a causal relationship involving E2 and SHBG with SjD, a negative correlation between SHBG and serum immunoglobulin levels (anti-SSA and anti-SSB) was determined in a case-control study \u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. In our study there was also no association between disease activity in SjD and estrogen, whereas another case-control study focusing on primary SjD patients demonstrated an inverse association between increased estrogen exposure and the occurrence of primary SjD \u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Given the intricate mechanisms underlying estrogen, SHBG, and SjD, the differences in susceptibility to confounding factors, and the limitations posed by a small sample size, drawing reliable conclusions regarding causal relationships must await further research.\u003c/p\u003e \u003cp\u003eOur study is the first to employ MR analysis to evaluate the potential causal association between sex hormones and SjD. By implementing stringent selection criteria, we were able to mitigate partially the influence of confounding factors. Moreover, our sex-stratified design corroborated the impact of androgens in female SjD patients, while also providing evidence of a higher prevalence of SjD in females due to androgenic effects. By leveraging bioinformatics techniques, we obtained insights into the mechanisms linking these variables together. Consistent with findings from previous basic research, we showed that androgens exert a suppressive effect on SjD development by protecting glandular secretion, inhibiting inflammatory responses, and inducing immunosuppression. These findings suggest valuable avenues of further research into the pathogenesis, treatment, and prevention of SjD.\u003c/p\u003e \u003cp\u003eDespite its strengths, our study also had several limitations. First, the generalizability of our findings to other populations may be limited as our data were derived only from Europeans. Second, the power of our study results may have been reduced by the relatively small number of SNPs identified through screening when estrogen was used as an exposure; validation with GWAS data based on a larger sample is needed. Third, while our analyses were sex-stratified, we have not conducted an age-stratified analysis, which prevented the definitive exclusion of age factors.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eOur study showed a clear causal relationship between androgens and the risk of SjD, particularly in females. Androgen deficiency contributed to the development of SjD via inflammation and immune-related pathways. Further elucidation of the relationship between androgen deficiency and SjD awaits larger-scale clinical and experimental research investigating specific mechanisms for intervention as well as potential avenues for the prevention and treatment of SjD.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eBT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eBioavailable testosterone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eCI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eConfidence interval\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eE2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eEstradiol\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eEAF\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eEffect allele frequency\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eGWAS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eGenome-wide association studies\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eInstrumental variable\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eIVW\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eInverse-variance weighted\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eLD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eLinkage disequilibrium\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eMendelian randomization\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eMR-PRESSO\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eMR-Pleiotropy Residual Sum and Outlier methods\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eOdds ratio\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eSHBG\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eSex hormone binding globulin\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eSNPs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eSingle nucleotide polymorphisms\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eSjD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eSjögren’s Disease\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"30.741410488245933%\"\u003e\n \u003cp\u003eTT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"69.25858951175407%\"\u003e\n \u003cp\u003eTotal testosterone\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval and consent: not applicable.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConflicts of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHJ, SR, MZ designed this study, HJ, JX, LG obtained and analyzed the data, HJ, DX, SR, BL, YC, participated in article writing and chart design, YZ, JG guided the entire study, all authors contributed to this paper, and read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to extend our sincere appreciation to all the data providers and participants involved in this study, as well as FinnGen and UK Biobank and their affiliated alliances for their exceptional management and collaborative efforts in sharing these invaluable statistical data. We appreciate the review by two professional English editors. For a certificate, please see: http://www.textcheck.com/certificate/cXYHxs.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSummary statistics are available in the website https://www.ebi.ac.uk/gwas/ for GWAS of estradiol (males), estradiol (females), testosterone, bioavailable testosterone and sex hormone-binding globulin, https://gwas.mrcieu.ac.uk/ for GWAS of estradiol, testosterone (males), testosterone (females), bioavailable testosterone (males), bioavailable testosterone (females), sex hormone-binding globulin (males), sex hormone-binding globulin (females), https://www.finngen.fi/en/access_results for GWAS of Sj\u0026ouml;gren\u0026rsquo;s Disease. Further information is available from the corresponding author upon request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFox RI. 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Effects of testosterone supplementation on markers of the metabolic syndrome and inflammation in hypogonadal men with the metabolic syndrome: the double-blinded placebo-controlled Moscow study. \u003cem\u003eClin Endocrinol (Oxf)\u003c/em\u003e. 2010;73(5):602-612. doi:10.1111/j.1365-2265.2010.03845.x\u003c/li\u003e\n\u003cli\u003eSutherland JS, Goldberg GL, Hammett MV, et al. Activation of thymic regeneration in mice and humans following androgen blockade. \u003cem\u003eJ Immunol\u003c/em\u003e. 2005;175(4):2741-2753. doi:10.4049/jimmunol.175.4.2741\u003c/li\u003e\n\u003cli\u003eOlsen NJ, Watson MB, Henderson GS, Kovacs WJ. Androgen deprivation induces phenotypic and functional changes in the thymus of adult male mice. \u003cem\u003eEndocrinology\u003c/em\u003e. 1991;129(5):2471-2476. doi:10.1210/endo-129-5-2471\u003c/li\u003e\n\u003cli\u003eRoden AC, Moser MT, Tri SD, et al. 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Sex steroid hormones in primary Sj\u0026ouml;gren\u0026apos;s syndrome. J Rheumatol. 2003;30(6):1267-1271.\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":"sex hormone, Mendelian randomization, Bioavailable testosterone, Sjögren’s Disease, bioinformatics","lastPublishedDoi":"10.21203/rs.3.rs-4690434/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4690434/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003ePostmenopausal women have a higher risk of developing Sj\u0026ouml;gren\u0026rsquo;s Disease (SjD) than men, indicating the involvement of sex hormones. The objective of this study was to investigate the causal relationship between sex hormones and SjD using a two-sample Mendelian randomization (MR) study.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eSpecific genetic tools obtained from genome-wide association studies (GWAS) were used to investigate serum estradiol (E2), total testosterone (TT), bioavailable testosterone (BT), and sex hormone-binding globulin (SHBG) levels. A two-sample MR analysis was conducted to examine sex hormone associations with SjD. Sex-stratified designs were employed, with additional databases used for further analysis of the outcomes. A Bonferroni correction was applied to ensure robust conclusions. Additionally, bioinformatics methods were employed to explore the underlying connections between sex hormones and SjD.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe results of the MR analysis showed a significant inverse association between BT levels and the risk of SjD, with each one standard deviation (SD) increase in BT levels associated with a 55% decrease in SjD risk (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;5.2357E\u0026ndash;05). The sex-stratified analysis provided that, for every one SD increase in BT levels, the risk of SjD decreased by 27% in males and 20% in females (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.036, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0377). Specifically, among females, each one SD increase in TT levels resulted in a 28% reduction of SjD risk (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0306). However, following a sensitivity analysis, the observed causal association between BT (males) and SjD became non-significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.0856), while the remaining causal relationships persisted. The bioinformatics analysis suggested that inflammation and immune-related pathways underlie their connection.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eOur study demonstrated a definitive causal relationship between androgen levels and the susceptibility to SjD, particularly among females. Androgen deficiency was shown to play a pivotal role in the pathogenesis of SjD, with inflammation and immune-related pathways underpinning the association.\u003c/p\u003e","manuscriptTitle":"Sex hormones and Sjögren’s Disease: A Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-14 13:35:28","doi":"10.21203/rs.3.rs-4690434/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":"86079c31-8f25-41f9-b759-fe3434387c9b","owner":[],"postedDate":"August 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36049645,"name":"Health sciences/Medical research/Genetics research"},{"id":36049646,"name":"Health sciences/Rheumatology/Rheumatic diseases"},{"id":36049647,"name":"Health sciences/Risk factors"}],"tags":[],"updatedAt":"2024-09-30T02:23:21+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-14 13:35:28","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4690434","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4690434","identity":"rs-4690434","version":["v1"]},"buildId":"cTy_lsJlmDsVRNrSptgXS","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}