Rheumatoid Arthritis and Adverse Pregnancy Outcomes: A Bidirectional Two-Sample Mendelian Randomization Study

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Therefore, we explored the potential causal relationships between rheumatoid arthritis and APOs using a bidirectional two-sample Mendelian randomization (MR). Methods We conducted a bidirectional two-sample Mendelian randomization analysis using available summary statistics from released genome-wide association studies. Summary statistics for instrument–outcome associations were retrieved from two separate databases for rheumatoid arthritis and adverse pregnancy outcomes, respectively. The inverse-variance weighted method was used as the primary MR analysis. MR-Egger, MR pleiotropy residual sum and outlier (MR-PRESSO), and Cochran Q statistic method were implemented as sensitivity analyses approach to ensure the robustness of the results. Results Our study showed that a higher risk of genetically predicted rheumatoid arthritis was associated with gestational hypertension (OR: 1.04, 95%CI: 1.02–1.06), pre-eclampsia (OR: 1.06, 95%CI: 1.01–1.11), fetal growth restriction (OR: 1.08, 95%CI: 1.04–1.12), preterm delivery (OR:1.04, 95%CI: 1.01–1.07). Furthermore, we found no evidence that APOs had causal effects on rheumatoid arthritis in the reverse MR analysis. There was no heterogeneity or horizontal pleiotropy. Conclusions This MR analysis provides evidence of a positive causal association between rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery genetically. It highlights the importance of more intensive prenatal care and early intervention among pregnant women with rheumatoid arthritis to prevent potential adverse obstetric outcomes. rheumatoid arthritis adverse pregnancy outcomes bidirectional two-sample Mendelian randomization Figures Figure 1 Figure 2 Figure 3 INTRODUCTION Rheumatoid arthritis is a common chronic autoimmune disease, which characterized by synovial inflammation, autoantibody production, cartilage and bone destruction, and systemic features, including cardiovascular, pulmonary, psychological, and skeletal disorders ( 1 ) . Certain risk factors are known to be associated with an increased likelihood of developing rheumatoid arthritis ( 2 ) . First, a positive family history of rheumatoid arthritis increases the risk by approximately three to five times, implicating genetic factors in its pathogenesis ( 3 ) . Then, the development of rheumatoid arthritis is associated with environmental factors. Known risk factors include smoking and low socioeconomic status or education. In addition, rheumatoid arthritis can be linked to hormone levels. The global prevalence of rheumatoid arthritis is approximately 0.5–1.0%, and 2 to 3 times more common in women than in men. Several studies have shown that autoimmune diseases are more prevalent in females and are one of the fourth leading causes of disability for women ( 4 , 5 ) . Rheumatoid arthritis can affect individuals of any age ( 2 ) and its incidence of increases with age ( 6 ) . Rheumatoid arthritis is a significant global public health challenge. Therefore, early identification and treatment of the disease is vital, especially among females, to minimize the persistent impact of this condition. Poor maternal and neonatal health remain a recognized public issue and is crucial for sustainable development worldwide ( 7 ) . Adverse pregnancy outcomes (APOs) significantly contribute to maternal and neonatal mortality. APOs refer to all pathological complications related to pregnancy and childbirth ( 8 ) , such as hypertensive disorders of pregnancy, pre-eclampsia, preterm delivery, gestational diabetes, fetal growth restriction, delivering a small-for-gestational age baby, placental abruption, and pregnancy loss ( 9 ) . The World Health Organization (WHO) reported that in 2020, nearly 800 women died each day due to complications during pregnancy or childbirth ( 10 ) , and approximately 13.4 million babies were born prematurely ( 11 ) . It is clear that preterm birth is currently the primary cause of child deaths ( 11 ) . Furthermore, it is estimated that 23 million miscarriages occur worldwide each year, which was equivalent to 44 miscarriages every minute. The pooled risk of miscarriage was 15.3% (95% CI: 12.5–18.7%) of all recognized pregnancies ( 12 ) . However, a significant number of adverse maternal and neonatal outcomes can be prevented in advance. Preventing APOs are therefore essential for preserving and extending a healthy lifespan among women. Previous studies have shown inconsistent results regarding pregnancy-related hypertension and pre-eclampsia/eclampsia in pregnant women with rheumatoid arthritis. Some studies have found a positive association with these complications in pregnant women with rheumatoid arthritis ( 5 , 13 , 14 ) , and a retrospective study suggested that women with rheumatoid arthritis had a modestly increased risk for preterm birth and pre-eclampsia ( 15 ) , while other studies did not find the same associations ( 16 , 17 ) . Furthermore, there are no articles examining the relationship between rheumatoid arthritis and ectopic pregnancy. Previous studies have shown an association between APOs, such as hyperemesis gravidarum, pre-eclampsia and gestational hypertension, and an increased subsequent risk of developing rheumatoid arthritis ( 18 , 19 ) . In contrast, an analysis of a prospective case-control study of women who had been pregnant found no statistically significant differences in any APOs, including spontaneous abortion and stillbirth, between rheumatoid arthritis cases and controls ( 20 ) . Associations between other APOs and the subsequent risk of rheumatoid arthritis have not been explored. Therefore, a clear assessment of the causality and direction of these associations will help in understanding the disease and contribute to more targeted treatment. The most important advantage of Mendelian randomization (MR) is that it uses genetic variation as an instrumental variable (IV) to estimate the causal relationship directly and accurately between the exposure phenotype and the outcome phenotype. This approach is independent of external environmental and social behavioral factors, thus overcoming the confounding factors inherent in observational studies, and is a long-term and stable exposure factor ( 21 ) . This approach is essentially equivalent to a randomized clinical trial ( 22 ) . In this study, we applied a bidirectional two-sample MR analysis to investigate the potential bidirectional causal association between rheumatoid arthritis and APOs, so as to provide evidence for the prevention and control of these diseases. METHODS Data sources We performed a bidirectional two-sample MR analysis using data from genome-wide association studies (GWAS) to investigate the relationships between rheumatoid arthritis and APOs, including gestational hypertension, gestational diabetes, pre-eclampsia, hyperemesis gravidarum, ectopic pregnancy, fetal growth restriction, preterm delivery and spontaneous abortion. Single nucleotide polymorphisms (SNPs) linked to exposure were used as genetic instrumental variables (IVs). MR analysis is based on three core assumptions ( 23 ) : (a) There is a strong link between IVs and exposure; (b) There are no unmeasured confounders of the associations between genetic IVs and outcome; (c) The genetic IVs influence the outcome only through the exposures and not via other biological pathways. The three prerequisites for IVs in our study were summarized in Fig. 1 A. The flowchart illustrating the study design and the process of our MR analysis in this study was shown in Fig. 1 B. Data sources GWAS dataset for rheumatoid arthritis was obtained from the IEU Open GWAS project ( https://gwas.mrcieu.ac.uk/ ), with corresponding GWAS IDs of ebi-a-GCST90013534. The dataset included 14,361 cases and 43,923 controls of European ancestry. This resource is developed at the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol and is a manually curated collection of complete GWAS summary datasets. Summary-level genetic data for APOs were obtained from the Finnegan study ( https://www.finngen.fi/en , R9 released in 2023). FinnGen combines imputed genotype data generated from newly collected and legacy samples from Finnish biobanks and digital health record data from Finnish health registries, with the aim of providing new insights into disease genetics ( 24 ) . The FinnGen study included 14,727 cases of gestational hypertension (196,143 controls), 13,039 cases of gestational diabetes (197,831 controls), 6,663 cases of pre-eclampsia (194,266 controls), 2,361 cases of hyperemesis gravidarum (179,899 controls), 5,648 cases of ectopic pregnancy (149,622 controls), 3,558 cases of fetal growth restriction (207,312 controls), 8,507 cases of preterm delivery (162,777 controls), 16,906 cases of spontaneous abortion (149,622 controls). Table 1 shows the summary statistics of the genetic variants associated with these traits. Table 1 The summary of rheumatoid arthritis and adverse pregnancy outcomes. Trait Sources Cases Controls No.SNP in MR* Rheumatoid arthritis IEU (ebi-a-GCST90013534) 14,361 43,923 78 Adverse pregnancy outcomes Gestational hypertension FinnGen (O15_HYPTENSPREG) 14,727 196,143 25 Gestational diabetes FinnGen (GEST_DIABETES) 13,039 197,831 52 Pre-eclampsia FinnGen (O15_PREECLAMPS) 6,663 194,266 31 Hyperemesis gravidarum FinnGen (O15_EXCESS_VOMIT_PREG) 2,361 179,899 19 Ectopic pregnancy FinnGen (O15_PREG_ECTOP) 5,648 149,622 9 Fetal growth restriction FinnGen (O15_POOR_FETGRO) 3,558 207,312 10 Preterm delivery FinnGen (O15_PRETERM) 8,507 162,777 8 Spontaneous abortion FinnGen (O15_ABORT_SPONTAN) 16,906 149,622 11 SNPs, single nucleotide polymorphisms; MR: Mendelian randomization. * When rheumatoid arthritis was used as an exposure, the significance threshold for SNPs was set at P < 5×10 − 8 . And when adverse pregnancy outcomes were used as an exposure, the significance threshold for SNPs was set at P < 5×10 − 6 . Instruments selection SNPs were used as instrumental variables (IVs). When rheumatoid arthritis was used as exposure, the significance threshold for SNPs was set at P < 5×10 − 8 . However, when APOs were used as exposures, the significance threshold was expanded to P < 5×10 − 6 . This adjustment was made to ensure that an adequate number of SNPs were available for the heterogeneity test and pleiotropy test. Secondly, to exclude SNPs that were in strong linkage disequilibrium (LD), we performed the clumping procedure with R 2 < 0.01 and clump distance = 10,000kb. The strength of IVs was assessed by calculating the F-statistic using the formula F = R 2 (N-2)/(1-R 2 ), where R 2 represents the proportion of variance in the phenotype explained by the genetic variants, and N is the sample size of the GWAS for the exposure ( 25 ) . The R 2 of instrumental variables can be calculated using the formula below ( 26 ) : R 2 = 2×(1-MAF)×MAF × β 2 . whereas for the extended 10 SNP instruments, we used:R 2 =[2×EAF×(1-EAF)×β 2 ]/[2×EAF×(1-EAF)×β 2 + 2×EAF×(1-EAF)×N×SE 2 ], where β indicates the estimated genetic effect of the SNP on exposure, EAF denotes the effect allele frequency, MAF represents the other effect allele frequency, Ν is the sample size of the GWAS, and SE is the standard error of the genetic effect. The data mentioned above can be obtained from the original summary data. We retained the SNPs with F > 10 as the final genetic variables to avoid the risk of selecting weak instrumental variables. Statistical analysis To investigate the causal relationship between exposure and outcome, bidirectional two-sample MR analyses were performed using several methods, including inverse variance weighting (IVW), weighted median, MR-Egger regression, simple mode, and weighted modal methods. We used the fixed-effects inverse-variance weighting (IVW) as the primary analytical method. However, when heterogeneity is observed, the random-effects IVW was used. The heterogeneity was quantified using the P -value of Cochran's Q-statistics test, which quantifies the extent to which any differences in the individual effect sizes among the selected genetic variants are due to actual differences between SNPs rather than sampling error. A P -value of less than 0.05 implies the presence of heterogeneity. In addition, we conducted a sensitivity analysis to evaluate the robustness of the association. To assess the influence of horizontal pleiotropy, the P -value of the MR-Egger regression intercept was used to identify and adjust for bias resulting from directional pleiotropy. When P < 0.05, it indicated that there was significant pleiotropy bias. Then, the MR pleiotropy residual sum and outlier (MR-PRESSO) test was conducted to detect and rectify any horizontal pleiotropic outliers. This was done to obtain accurate results by removing any outliers. The associations between rheumatoid arthritis and APOs were presented using ORs along with their 95% confidence intervals (CIs). We adjusted for multiple testing using a Bonferroni-corrected threshold of P < 0.0063 ( P < 0.05/8). The P -values ranging from 0.0063 to 0.05 were considered to indicate suggestive associations. All analyses were performed using R statistical software (Version 4.2.3; https://www.r-project.org/ ). MR analyses were performed using the R-based "TwoSampleMR" and "MRPROSSO" packages, and forest plots were generated using the "forestplot" package. RESULTS Causal effects of rheumatoid arthritis on APOs risk For IVs used for rheumatoid arthritis, all the F-statistics were greater than 10, indicating no presence of weak instrumental bias. After removing linkage disequilibrium (LD) and anomalous outliers, we incorporated 78 SNPs with a significant P -value less than 5×10 − 8 as IVs for rheumatoid arthritis, Detailed information about exposure was listed in the Table S1 . Figure 2 illustrated the primary results of the causal relationship between rheumatoid arthritis and APOs. Among the main results of using IVW, we observed a causal association between rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery, with corresponding odds ratio (OR) =1.04 (95%CI: 1.02–1.06; P = 9.89×10 − 5 ), 1.06 (95%CI: 1.01–1.11; P = 6.47×10 − 5 ), 1.08 (95%CI: 1.04–1.12; P = 7.20×10 − 5 ), 1.04 (95%CI: 1.01–1.07; P = 0.001). respectively, none of them changed their significance levels after applying the Bonferroni correction. Detailed results of the MR analyses using different methods, such as MR Egger, weighted median, simple mode, weighted mode, were presented in the Table S2. The methods mentioned above are consistent with IVW, except for the Simple model. Furthermore, we found no evidence that rheumatoid arthritis was associated with the risk of gestational diabetes, hyperemesis gravidarum, ectopic pregnancy, or spontaneous abortion. In the sensitivity analyses (Table S3), heterogeneity was evaluated using Cochran's Q test, which was not found to be significant ( P > 0.5). The MR Egger intercept test did not observe a significant pleiotropy, with P -values ranging from 0.053 to 0.891. And no outlier SNPs were identified by using MR-PRESSO in our study, with P -values ranging from 0.088 to 0.444. Causal effects of APOs on rheumatoid arthritis risk Based on the same screening criteria, 25 SNPs were selected as IVs for gestational hypertension, 52 SNPs for gestational diabetes, 31 SNPs for pre-eclampsia, 19 SNPs for hyperemesis gravidarum, 9 SNPs for ectopic pregnancy, 10 SNPs for fetal growth restriction, 8 SNPs for preterm delivery, and 11 SNPs for spontaneous abortion. A summary and detailed information about the SNPs for each exposure were presented in the Table S4. In general, the primary analysis using IVW did not reveal a statistically significant relationship between an increase in the risk of having APOs and an increased risk of rheumatoid arthritis (Fig. 3 ). The ORs of gestational hypertension, gestational diabetes, pre-eclampsia, hyperemesis gravidarum, ectopic pregnancy, fetal growth restriction, preterm delivery, and spontaneous abortion on rheumatoid arthritis were as follows: 1.04 (95%CI: 0.95–1.13; P = 0.397), 0.98 (95%CI: 0.93–1.04; P = 0.524), 1.04 (95%CI: 0.97–1.11; P = 0.292), 1.02 (95%CI: 0.97–1.07; P = 0.448), 1.00 (95%CI: 0.90–1.10; P = 0.936), 1.03 (95%CI: 0.95–1.11; P = 0.522), 1.12 (95%CI: 0.97–1.29; P = 0.116), 1.19 (95%CI: 1.00-1.43; P = 0.056). Neither the MR-Egger intercept test nor Cochran's Q statistic revealed any evidence of directional pleiotropy or heterogeneity. In addition, the MR-PRESSO global test did not reveal any evidence of horizontal pleiotropy (all P > 0.18). The results of the MR analyses, as well as the sensitivity analyses, were shown in Table S5, S6. DISCUSSION Main Findings In this study, we investigated the causal relationship between rheumatoid arthritis and adverse pregnancy outcomes using a bidirectional two-sample Mendelian randomization analysis. This study indicated that genetically predicted rheumatoid arthritis was associated with the increased risk of gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery. And these associations remained consistent even after multiple corrections were applied to the data. Furthermore, our study did not find evidence of causal associations of genetically predicted APOs on the increased risk of rheumatoid arthritis. It was also evident from the sensitivity analysis that the results of this study were robust and reliable. Interpretation Our findings in bidirectional Mendelian randomization of the association of RA with gestational hypertension and preeclampsia are consistent with previous observational studies ( 5 , 27 ) . A systematic review ( 28 ) also found that women with rheumatoid arthritis tended to have a higher risk of maternal and neonatal complications compared to the general pregnant population. There have been observational studies ( 29 , 30 ) and a meta-analysis ( 31 ) demonstrated that maternal rheumatoid arthritis during pregnancy was associated with a significantly increased risk of preterm birth and low birth weight in the fetus. The aforementioned studies provide support for our findings regarding the causal associations between genetically predicted rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction, and preterm delivery. There was certainly a good deal of evidence that rheumatoid arthritis was the risk factor for small for gestational age infants ( 5 , 13 , 32 ) . However, due to the limited number of GWAS studies, we have been unable to find a suitable database. Several possible mechanisms have been proposed to explain the association between rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery. First, in patients with rheumatoid arthritis, the CD4 protein on helper T lymphocytes is activated, which then stimulates monocytes, macrophages, and fibroblast-like synoviocytes. This activation can result in an increased release of proinflammatory cytokines, such as interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Additionally, it can lead to a decrease in the release of regulatory and anti-inflammatory cytokines ( 33 ) . High levels of proinflammatory cytokines, as well as chronic stress states, can reduce the activity of 11β-HSD2 and result in elevated maternal cortisol levels, which may have potentially deleterious effects on the placenta, leading to preterm birth, low birth weight, and small for gestational age ( 34 , 35 ) . Secondly, endothelial dysfunction is a common complication of active rheumatoid arthritis. Vasculopathy resulting from endothelial dysfunction may contribute to placental maldevelopment. Maldevelopment of the placenta is associated with unfavorable pregnancy outcomes, such as lower birth weight and hypertension ( 36 ) . Endothelial dysfunction is considered the initial stage of atherosclerosis ( 37 ) , and proinflammatory cytokines implicated in rheumatoid arthritis also contribute to the development of atherosclerosis ( 38 ) . Furthermore, in patients with rheumatoid arthritis, the upregulated expression of vascular endothelial growth factor (VEGF), a crucial regulator of endothelial dysfunction ( 39 ) , may lead to the development of pre-eclampsia during pregnancy ( 40 ) . Epidemiologic data suggests that pregnancy-related hormones may influence the link between reproduction and the risk of rheumatoid arthritis. Excessive level of female hormones, such as estrogen and progesterone, may be protective against the development of rheumatoid arthritis ( 41 ) . During pregnancy, when estradiol and progesterone levels are high, women have a reduced risk of developing rheumatoid arthritis ( 42 ) . Hormone levels return to a non-pregnant state rapidly after delivery ( 43 ) , especially during the first 3 months, which appears to be a period of increased risk. A nationwide cohort study in Denmark found that women with hyperemesis gravidarum, gestational hypertension, or pre-eclampsia have a significantly higher risk of developing rheumatoid arthritis ( 18 ) . However, a population-based prospective study found that preterm delivery and small-for-gestational-age infants did not appear to have a significant association with subsequent rheumatoid arthritis ( 44 ) . Our study also did not find the causal relationship from the gene perspective. This may be due to the lack of individual-level information in the pooled data used, and the fact that the data on rheumatoid arthritis did not include data on its typing, due to which limitation it is difficult to determine a causal association of APOs on rheumatoid arthritis progression. Strengths and Limitations This bidirectional two-sample MR study, which investigated the causal association between rheumatoid arthritis and APOs risk, had several strengths. First, the bidirectional two-sample Mendelian randomization analysis can reduce the effects of unknown confounders and small-sample selection bias. The bidirectional analysis ensures the inference of causality between rheumatoid arthritis and APOs in both directions. Furthermore, the study used a large sample size and SNPs from GWASs, which provided sufficient statistical validity to estimate causality. Finally, we applied a series of sensitivity analyses to ensure the consistency and the robustness of causal estimates. Inevitably, there were several limitations in our study. First, the summary data used in this study were all derived from individuals of European ancestry, which limited the generalizability of the findings to other ethnic groups. Therefore, there were limitations to extrapolation. Secondly, when examining the risk of rheumatoid arthritis associated with APOs, we set the P -value threshold for SNPs at P < 5×10 − 6 to ensure an adequate number of instrumental variables for heterogeneity and horizontal multivariate tests. This threshold may explain only a small portion of the variability in exposures and could affect the statistical efficacy of the causal estimates. Finally, we were unable to perform subgroup analyses due to the lack of specific information describing the severity of the disease and specific information at the individual level. CONCLUSIONS In conclusion, this study confirmed the causal relationship between rheumatoid arthritis and adverse pregnancy outcomes, that is, rheumatoid arthritis is associated with an increased risk of gestational hypertension, pre-eclampsia, fetal growth restriction, and preterm delivery. It highlights the importance of more intensive prenatal care and early intervention among pregnant women with rheumatoid arthritis to prevent potential adverse obstetric outcomes. However, due to the limitations of the study, further research is warranted. Abbreviations APOs: Adverse Pregnancy Outcomes LD: Linkage Disequilibrium MR: Mendelian randomization SNP: Single-nucleotide polymorphism GWAS: Genome-Wide Association Studies IV: Instrumental Variable IVW: Inverse Variance-Weighted MR-PRESSO: MR pleiotropy residual sum and outlier Declarations Ethics approval and consent to participate: All the data were publicly available GWAS summary statistics, and therefore no additional ethical approval or informed consent was required. Ethical approval and participant consent were obtained in the original studies. Consent for publication: Not applicable Availability of data and materials: This study uses publicly available datasets, which can be found in the IEU Open Project (https://gwas.mrcieu.ac.uk/), and the FinnGen study (https://www.finngen.fi/en). Competing interests: The authors declare that they have no competing interests. Funding: This work was supported by the Shandong Provincial Medical Association (YXH2022PT06001), the National Key Research and Development Program of China (2021YFF1201101) and ECCM Program of Clinical Research Center of Shandong University (2021SDUCRCE001). Author contribution: Data collection, data curation, Methodology, Formal analysis, Software, and Visualization were performed by ZZ, TC, XL, XZ, JC, YZ, and XL. Writing original draft: ZZ, YZ. Funding acquisition: ML. Writing review and editing: YZ, XL, and ML. The corresponding authors attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted. Acknowledgments: The authors acknowledge the participants and investigators of the IEU Open Project study and FinnGen study. References IB M, G S. The pathogenesis of rheumatoid arthritis. N Engl J Med. 2011;365(23):2205-19. Smith MH, Berman JR. What Is Rheumatoid Arthritis? Jama. 2022;327(12):1194. Silman AJ, Pearson JE. 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Mendelian randomization study reveals a causal relationship between rheumatoid arthritis and risk for pre-eclampsia. Frontiers in immunology. 2022;13:1080980. Karlson EW, Mandl LA, Hankinson SE, Grodstein F. Do breast-feeding and other reproductive factors influence future risk of rheumatoid arthritis? Results from the Nurses' Health Study. Arthritis and rheumatism. 2004;50(11):3458-67. Silman A, Kay A, Brennan P. Timing of pregnancy in relation to the onset of rheumatoid arthritis. Arthritis and rheumatism. 1992;35(2):152-5. Mastorakos G, Ilias I. Maternal hypothalamic-pituitary-adrenal axis in pregnancy and the postpartum period. Postpartum-related disorders. Annals of the New York Academy of Sciences. 2000;900:95-106. Ma KK, Nelson JL, Guthrie KA, Dugowson CE, Gammill HS. Adverse pregnancy outcomes and risk of subsequent rheumatoid arthritis. Arthritis & rheumatology (Hoboken, NJ). 2014;66(3):508-12. Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial.xlsx Cite Share Download PDF Status: Published Journal Publication published 31 Jul, 2024 Read the published version in BMC Pregnancy and Childbirth → Version 1 posted Editorial decision: Revision requested 17 May, 2024 Reviews received at journal 16 May, 2024 Reviewers agreed at journal 28 Apr, 2024 Reviews received at journal 19 Apr, 2024 Reviewers agreed at journal 30 Mar, 2024 Reviewers agreed at journal 27 Mar, 2024 Reviewers invited by journal 21 Mar, 2024 Editor assigned by journal 21 Mar, 2024 Submission checks completed at journal 20 Mar, 2024 First submitted to journal 18 Mar, 2024 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. 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University","correspondingAuthor":false,"prefix":"","firstName":"Zengle","middleName":"","lastName":"Zhao","suffix":""},{"id":283102924,"identity":"6ae608f9-ad62-4b5a-973d-4ffab924b919","order_by":2,"name":"Xiaoyan Liu","email":"","orcid":"","institution":"Qilu Hospital of Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Xiaoyan","middleName":"","lastName":"Liu","suffix":""},{"id":283102926,"identity":"7538d679-94d8-463f-a7a5-8dbe954e6b50","order_by":3,"name":"Xuening Zhang","email":"","orcid":"","institution":"Shandong University","correspondingAuthor":false,"prefix":"","firstName":"Xuening","middleName":"","lastName":"Zhang","suffix":""},{"id":283102928,"identity":"d356a07c-9d8d-4f73-81cc-acbf008c9966","order_by":4,"name":"Yuan Zhang","email":"","orcid":"","institution":"Shandong 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zhang","email":"data:image/png;base64,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","orcid":"","institution":"Clinical Epidemiology Unit, Qilu Hospital of Shandong University, Jinan, Shandong","correspondingAuthor":true,"prefix":"","firstName":"Yuan","middleName":"","lastName":"zhang","suffix":""}],"badges":[],"createdAt":"2024-03-18 07:37:16","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4120942/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4120942/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12884-024-06698-3","type":"published","date":"2024-07-31T15:57:01+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":53411710,"identity":"8a87a93e-4435-4a61-a216-08ddc1b5c21a","added_by":"auto","created_at":"2024-03-25 16:38:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":256680,"visible":true,"origin":"","legend":"\u003cp\u003eSchematic overview of the study design.\u003cstrong\u003e [A]\u003c/strong\u003e Mendelian randomization illustration. \u003cstrong\u003e[B]\u003c/strong\u003e The research design and framework of our study.\u003c/p\u003e","description":"","filename":"figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4120942/v1/1b2cac8bcf3f02587da27d3e.png"},{"id":53411709,"identity":"3ecf5dc9-0625-42d7-a08a-6037872a74c9","added_by":"auto","created_at":"2024-03-25 16:38:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":224287,"visible":true,"origin":"","legend":"\u003cp\u003eTotal causal effects of rheumatoid arthritis on APOs.\u003c/p\u003e","description":"","filename":"figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4120942/v1/ff829bda192d99a7167388af.png"},{"id":53411711,"identity":"cc063dd6-8d07-457d-add9-3d098f77e2d0","added_by":"auto","created_at":"2024-03-25 16:38:06","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":200751,"visible":true,"origin":"","legend":"\u003cp\u003eTotal causal effects of APOs on rheumatoid arthritis.\u003c/p\u003e","description":"","filename":"figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4120942/v1/9bdb1ea3b90ef76d994766b0.png"},{"id":61793340,"identity":"0412c31e-c6c9-44c3-854c-7e5ffc1b9cbe","added_by":"auto","created_at":"2024-08-05 16:11:04","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1118414,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4120942/v1/85ff8e98-0274-48cc-a2e6-71d5444df283.pdf"},{"id":53411713,"identity":"bf36b181-3362-43d0-9670-b0442c7187ad","added_by":"auto","created_at":"2024-03-25 16:38:06","extension":"xlsx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":46156,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.xlsx","url":"https://assets-eu.researchsquare.com/files/rs-4120942/v1/2d6f0417bd45a68f2d7ce395.xlsx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rheumatoid Arthritis and Adverse Pregnancy Outcomes: A Bidirectional Two-Sample Mendelian Randomization Study","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRheumatoid arthritis is a common chronic autoimmune disease, which characterized by synovial inflammation, autoantibody production, cartilage and bone destruction, and systemic features, including cardiovascular, pulmonary, psychological, and skeletal disorders \u003csup\u003e(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e)\u003c/sup\u003e. Certain risk factors are known to be associated with an increased likelihood of developing rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/sup\u003e. First, a positive family history of rheumatoid arthritis increases the risk by approximately three to five times, implicating genetic factors in its pathogenesis \u003csup\u003e(\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e)\u003c/sup\u003e. Then, the development of rheumatoid arthritis is associated with environmental factors. Known risk factors include smoking and low socioeconomic status or education. In addition, rheumatoid arthritis can be linked to hormone levels. The global prevalence of rheumatoid arthritis is approximately 0.5\u0026ndash;1.0%, and 2 to 3 times more common in women than in men. Several studies have shown that autoimmune diseases are more prevalent in females and are one of the fourth leading causes of disability for women \u003csup\u003e(\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e)\u003c/sup\u003e. Rheumatoid arthritis can affect individuals of any age \u003csup\u003e(\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e)\u003c/sup\u003e and its incidence of increases with age \u003csup\u003e(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e)\u003c/sup\u003e. Rheumatoid arthritis is a significant global public health challenge. Therefore, early identification and treatment of the disease is vital, especially among females, to minimize the persistent impact of this condition.\u003c/p\u003e \u003cp\u003ePoor maternal and neonatal health remain a recognized public issue and is crucial for sustainable development worldwide \u003csup\u003e(\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e)\u003c/sup\u003e. Adverse pregnancy outcomes (APOs) significantly contribute to maternal and neonatal mortality. APOs refer to all pathological complications related to pregnancy and childbirth \u003csup\u003e(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e)\u003c/sup\u003e, such as hypertensive disorders of pregnancy, pre-eclampsia, preterm delivery, gestational diabetes, fetal growth restriction, delivering a small-for-gestational age baby, placental abruption, and pregnancy loss \u003csup\u003e(\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/sup\u003e. The World Health Organization (WHO) reported that in 2020, nearly 800 women died each day due to complications during pregnancy or childbirth \u003csup\u003e(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/sup\u003e, and approximately 13.4\u0026nbsp;million babies were born prematurely \u003csup\u003e(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/sup\u003e. It is clear that preterm birth is currently the primary cause of child deaths \u003csup\u003e(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e)\u003c/sup\u003e. Furthermore, it is estimated that 23\u0026nbsp;million miscarriages occur worldwide each year, which was equivalent to 44 miscarriages every minute. The pooled risk of miscarriage was 15.3% (95% CI: 12.5\u0026ndash;18.7%) of all recognized pregnancies \u003csup\u003e(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e)\u003c/sup\u003e. However, a significant number of adverse maternal and neonatal outcomes can be prevented in advance. Preventing APOs are therefore essential for preserving and extending a healthy lifespan among women.\u003c/p\u003e \u003cp\u003ePrevious studies have shown inconsistent results regarding pregnancy-related hypertension and pre-eclampsia/eclampsia in pregnant women with rheumatoid arthritis. Some studies have found a positive association with these complications in pregnant women with rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e)\u003c/sup\u003e, and a retrospective study suggested that women with rheumatoid arthritis had a modestly increased risk for preterm birth and pre-eclampsia \u003csup\u003e(\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e)\u003c/sup\u003e, while other studies did not find the same associations \u003csup\u003e(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e)\u003c/sup\u003e. Furthermore, there are no articles examining the relationship between rheumatoid arthritis and ectopic pregnancy. Previous studies have shown an association between APOs, such as hyperemesis gravidarum, pre-eclampsia and gestational hypertension, and an increased subsequent risk of developing rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e)\u003c/sup\u003e. In contrast, an analysis of a prospective case-control study of women who had been pregnant found no statistically significant differences in any APOs, including spontaneous abortion and stillbirth, between rheumatoid arthritis cases and controls \u003csup\u003e(\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e)\u003c/sup\u003e. Associations between other APOs and the subsequent risk of rheumatoid arthritis have not been explored. Therefore, a clear assessment of the causality and direction of these associations will help in understanding the disease and contribute to more targeted treatment.\u003c/p\u003e \u003cp\u003eThe most important advantage of Mendelian randomization (MR) is that it uses genetic variation as an instrumental variable (IV) to estimate the causal relationship directly and accurately between the exposure phenotype and the outcome phenotype. This approach is independent of external environmental and social behavioral factors, thus overcoming the confounding factors inherent in observational studies, and is a long-term and stable exposure factor \u003csup\u003e(\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e)\u003c/sup\u003e. This approach is essentially equivalent to a randomized clinical trial \u003csup\u003e(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn this study, we applied a bidirectional two-sample MR analysis to investigate the potential bidirectional causal association between rheumatoid arthritis and APOs, so as to provide evidence for the prevention and control of these diseases.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eWe performed a bidirectional two-sample MR analysis using data from genome-wide association studies (GWAS) to investigate the relationships between rheumatoid arthritis and APOs, including gestational hypertension, gestational diabetes, pre-eclampsia, hyperemesis gravidarum, ectopic pregnancy, fetal growth restriction, preterm delivery and spontaneous abortion. Single nucleotide polymorphisms (SNPs) linked to exposure were used as genetic instrumental variables (IVs). MR analysis is based on three core assumptions \u003csup\u003e(\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/sup\u003e: (a) There is a strong link between IVs and exposure; (b) There are no unmeasured confounders of the associations between genetic IVs and outcome; (c) The genetic IVs influence the outcome only through the exposures and not via other biological pathways. The three prerequisites for IVs in our study were summarized in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eA. The flowchart illustrating the study design and the process of our MR analysis in this study was shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003eB.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eData sources\u003c/h2\u003e \u003cp\u003eGWAS dataset for rheumatoid arthritis was obtained from the IEU Open GWAS project (\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), with corresponding GWAS IDs of ebi-a-GCST90013534. The dataset included 14,361 cases and 43,923 controls of European ancestry. This resource is developed at the MRC Integrative Epidemiology Unit (IEU) at the University of Bristol and is a manually curated collection of complete GWAS summary datasets. Summary-level genetic data for APOs were obtained from the Finnegan study (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.finngen.fi/en\u003c/span\u003e\u003cspan address=\"https://www.finngen.fi/en\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e, R9 released in 2023). FinnGen combines imputed genotype data generated from newly collected and legacy samples from Finnish biobanks and digital health record data from Finnish health registries, with the aim of providing new insights into disease genetics \u003csup\u003e(\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e)\u003c/sup\u003e. The FinnGen study included 14,727 cases of gestational hypertension (196,143 controls), 13,039 cases of gestational diabetes (197,831 controls), 6,663 cases of pre-eclampsia (194,266 controls), 2,361 cases of hyperemesis gravidarum (179,899 controls), 5,648 cases of ectopic pregnancy (149,622 controls), 3,558 cases of fetal growth restriction (207,312 controls), 8,507 cases of preterm delivery (162,777 controls), 16,906 cases of spontaneous abortion (149,622 controls). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the summary statistics of the genetic variants associated with these traits.\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\u003eThe summary of rheumatoid arthritis and adverse pregnancy outcomes.\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=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTrait\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSources\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCases\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eControls\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNo.SNP in MR*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eRheumatoid arthritis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIEU\u003c/p\u003e \u003cp\u003e(ebi-a-GCST90013534)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43,923\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAdverse pregnancy outcomes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational hypertension\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_HYPTENSPREG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14,727\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e196,143\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eGestational diabetes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(GEST_DIABETES)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e13,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e197,831\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePre-eclampsia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_PREECLAMPS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6,663\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e194,266\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHyperemesis gravidarum\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_EXCESS_VOMIT_PREG)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2,361\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e179,899\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEctopic pregnancy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_PREG_ECTOP)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5,648\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149,622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFetal growth restriction\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_POOR_FETGRO)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3,558\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e207,312\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e10\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreterm delivery\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_PRETERM)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e8,507\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e162,777\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSpontaneous abortion\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFinnGen\u003c/p\u003e \u003cp\u003e(O15_ABORT_SPONTAN)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16,906\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e149,622\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eSNPs, single nucleotide polymorphisms; MR: Mendelian randomization.\u003c/p\u003e \u003cp\u003e* When rheumatoid arthritis was used as an exposure, the significance threshold for SNPs was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e. And when adverse pregnancy outcomes were used as an exposure, the significance threshold for SNPs was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003eInstruments selection\u003c/h2\u003e \u003cp\u003eSNPs were used as instrumental variables (IVs). When rheumatoid arthritis was used as exposure, the significance threshold for SNPs was set at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e. However, when APOs were used as exposures, the significance threshold was expanded to \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e. This adjustment was made to ensure that an adequate number of SNPs were available for the heterogeneity test and pleiotropy test. Secondly, to exclude SNPs that were in strong linkage disequilibrium (LD), we performed the clumping procedure with R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 and clump distance\u0026thinsp;=\u0026thinsp;10,000kb. The strength of IVs was assessed by calculating the F-statistic using the formula F\u0026thinsp;=\u0026thinsp;R\u003csup\u003e2\u003c/sup\u003e(N-2)/(1-R\u003csup\u003e2\u003c/sup\u003e), where R\u003csup\u003e2\u003c/sup\u003e represents the proportion of variance in the phenotype explained by the genetic variants, and N is the sample size of the GWAS for the exposure \u003csup\u003e(\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e)\u003c/sup\u003e. The R\u003csup\u003e2\u003c/sup\u003e of instrumental variables can be calculated using the formula below \u003csup\u003e(\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e)\u003c/sup\u003e: R\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;2\u0026times;(1-MAF)\u0026times;MAF\u0026thinsp;\u0026times;\u0026thinsp;β\u003csup\u003e2\u003c/sup\u003e. whereas for the extended 10 SNP instruments, we used:R\u003csup\u003e2\u003c/sup\u003e=[2\u0026times;EAF\u0026times;(1-EAF)\u0026times;β\u003csup\u003e2\u003c/sup\u003e]/[2\u0026times;EAF\u0026times;(1-EAF)\u0026times;β\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;+\u0026thinsp;2\u0026times;EAF\u0026times;(1-EAF)\u0026times;N\u0026times;SE\u003csup\u003e2\u003c/sup\u003e], where β indicates the estimated genetic effect of the SNP on exposure, EAF denotes the effect allele frequency, MAF represents the other effect allele frequency, Ν is the sample size of the GWAS, and SE is the standard error of the genetic effect. The data mentioned above can be obtained from the original summary data. We retained the SNPs with F\u0026thinsp;\u0026gt;\u0026thinsp;10 as the final genetic variables to avoid the risk of selecting weak instrumental variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eTo investigate the causal relationship between exposure and outcome, bidirectional two-sample MR analyses were performed using several methods, including inverse variance weighting (IVW), weighted median, MR-Egger regression, simple mode, and weighted modal methods. We used the fixed-effects inverse-variance weighting (IVW) as the primary analytical method. However, when heterogeneity is observed, the random-effects IVW was used. The heterogeneity was quantified using the \u003cem\u003eP\u003c/em\u003e-value of Cochran's Q-statistics test, which quantifies the extent to which any differences in the individual effect sizes among the selected genetic variants are due to actual differences between SNPs rather than sampling error. A \u003cem\u003eP\u003c/em\u003e-value of less than 0.05 implies the presence of heterogeneity.\u003c/p\u003e \u003cp\u003eIn addition, we conducted a sensitivity analysis to evaluate the robustness of the association. To assess the influence of horizontal pleiotropy, the \u003cem\u003eP\u003c/em\u003e-value of the MR-Egger regression intercept was used to identify and adjust for bias resulting from directional pleiotropy. When \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, it indicated that there was significant pleiotropy bias. Then, the MR pleiotropy residual sum and outlier (MR-PRESSO) test was conducted to detect and rectify any horizontal pleiotropic outliers. This was done to obtain accurate results by removing any outliers.\u003c/p\u003e \u003cp\u003eThe associations between rheumatoid arthritis and APOs were presented using ORs along with their 95% confidence intervals (CIs). We adjusted for multiple testing using a Bonferroni-corrected threshold of \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.0063 (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05/8). The \u003cem\u003eP\u003c/em\u003e-values ranging from 0.0063 to 0.05 were considered to indicate suggestive associations. All analyses were performed using R statistical software (Version 4.2.3; \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.r-project.org/\u003c/span\u003e\u003cspan address=\"https://www.r-project.org/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). MR analyses were performed using the R-based \"TwoSampleMR\" and \"MRPROSSO\" packages, and forest plots were generated using the \"forestplot\" package.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eCausal effects of rheumatoid arthritis on APOs risk\u003c/h2\u003e \u003cp\u003eFor IVs used for rheumatoid arthritis, all the F-statistics were greater than 10, indicating no presence of weak instrumental bias. After removing linkage disequilibrium (LD) and anomalous outliers, we incorporated 78 SNPs with a significant \u003cem\u003eP\u003c/em\u003e-value less than 5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e as IVs for rheumatoid arthritis, Detailed information about exposure was listed in the Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eFigure \u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e illustrated the primary results of the causal relationship between rheumatoid arthritis and APOs. Among the main results of using IVW, we observed a causal association between rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery, with corresponding odds ratio (OR) =1.04 (95%CI: 1.02\u0026ndash;1.06; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;9.89\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e), 1.06 (95%CI: 1.01\u0026ndash;1.11; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;6.47\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e), 1.08 (95%CI: 1.04\u0026ndash;1.12; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;7.20\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;5\u003c/sup\u003e), 1.04 (95%CI: 1.01\u0026ndash;1.07; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001). respectively, none of them changed their significance levels after applying the Bonferroni correction. Detailed results of the MR analyses using different methods, such as MR Egger, weighted median, simple mode, weighted mode, were presented in the Table S2. The methods mentioned above are consistent with IVW, except for the Simple model. Furthermore, we found no evidence that rheumatoid arthritis was associated with the risk of gestational diabetes, hyperemesis gravidarum, ectopic pregnancy, or spontaneous abortion. In the sensitivity analyses (Table S3), heterogeneity was evaluated using Cochran's Q test, which was not found to be significant (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.5). The MR Egger intercept test did not observe a significant pleiotropy, with \u003cem\u003eP\u003c/em\u003e-values ranging from 0.053 to 0.891. And no outlier SNPs were identified by using MR-PRESSO in our study, with \u003cem\u003eP\u003c/em\u003e-values ranging from 0.088 to 0.444.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eCausal effects of APOs on rheumatoid arthritis risk\u003c/h2\u003e \u003cp\u003eBased on the same screening criteria, 25 SNPs were selected as IVs for gestational hypertension, 52 SNPs for gestational diabetes, 31 SNPs for pre-eclampsia, 19 SNPs for hyperemesis gravidarum, 9 SNPs for ectopic pregnancy, 10 SNPs for fetal growth restriction, 8 SNPs for preterm delivery, and 11 SNPs for spontaneous abortion. A summary and detailed information about the SNPs for each exposure were presented in the Table S4. In general, the primary analysis using IVW did not reveal a statistically significant relationship between an increase in the risk of having APOs and an increased risk of rheumatoid arthritis (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). The ORs of gestational hypertension, gestational diabetes, pre-eclampsia, hyperemesis gravidarum, ectopic pregnancy, fetal growth restriction, preterm delivery, and spontaneous abortion on rheumatoid arthritis were as follows: 1.04 (95%CI: 0.95\u0026ndash;1.13; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.397), 0.98 (95%CI: 0.93\u0026ndash;1.04; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.524), 1.04 (95%CI: 0.97\u0026ndash;1.11; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.292), 1.02 (95%CI: 0.97\u0026ndash;1.07; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.448), 1.00 (95%CI: 0.90\u0026ndash;1.10; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.936), 1.03 (95%CI: 0.95\u0026ndash;1.11; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.522), 1.12 (95%CI: 0.97\u0026ndash;1.29; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.116), 1.19 (95%CI: 1.00-1.43; \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.056). Neither the MR-Egger intercept test nor Cochran's Q statistic revealed any evidence of directional pleiotropy or heterogeneity. In addition, the MR-PRESSO global test did not reveal any evidence of horizontal pleiotropy (all \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.18). The results of the MR analyses, as well as the sensitivity analyses, were shown in Table S5, S6.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"DISCUSSION","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eMain Findings\u003c/h2\u003e \u003cp\u003eIn this study, we investigated the causal relationship between rheumatoid arthritis and adverse pregnancy outcomes using a bidirectional two-sample Mendelian randomization analysis. This study indicated that genetically predicted rheumatoid arthritis was associated with the increased risk of gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery. And these associations remained consistent even after multiple corrections were applied to the data. Furthermore, our study did not find evidence of causal associations of genetically predicted APOs on the increased risk of rheumatoid arthritis. It was also evident from the sensitivity analysis that the results of this study were robust and reliable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eInterpretation\u003c/h2\u003e \u003cp\u003eOur findings in bidirectional Mendelian randomization of the association of RA with gestational hypertension and preeclampsia are consistent with previous observational studies \u003csup\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e)\u003c/sup\u003e. A systematic review \u003csup\u003e(\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e)\u003c/sup\u003e also found that women with rheumatoid arthritis tended to have a higher risk of maternal and neonatal complications compared to the general pregnant population. There have been observational studies \u003csup\u003e(\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e)\u003c/sup\u003e and a meta-analysis \u003csup\u003e(\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e)\u003c/sup\u003e demonstrated that maternal rheumatoid arthritis during pregnancy was associated with a significantly increased risk of preterm birth and low birth weight in the fetus. The aforementioned studies provide support for our findings regarding the causal associations between genetically predicted rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction, and preterm delivery. There was certainly a good deal of evidence that rheumatoid arthritis was the risk factor for small for gestational age infants \u003csup\u003e(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/sup\u003e. However, due to the limited number of GWAS studies, we have been unable to find a suitable database.\u003c/p\u003e \u003cp\u003eSeveral possible mechanisms have been proposed to explain the association between rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery. First, in patients with rheumatoid arthritis, the CD4 protein on helper T lymphocytes is activated, which then stimulates monocytes, macrophages, and fibroblast-like synoviocytes. This activation can result in an increased release of proinflammatory cytokines, such as interleukin-1 (IL-1), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α). Additionally, it can lead to a decrease in the release of regulatory and anti-inflammatory cytokines \u003csup\u003e(\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e)\u003c/sup\u003e. High levels of proinflammatory cytokines, as well as chronic stress states, can reduce the activity of 11β-HSD2 and result in elevated maternal cortisol levels, which may have potentially deleterious effects on the placenta, leading to preterm birth, low birth weight, and small for gestational age \u003csup\u003e(\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e)\u003c/sup\u003e. Secondly, endothelial dysfunction is a common complication of active rheumatoid arthritis. Vasculopathy resulting from endothelial dysfunction may contribute to placental maldevelopment. Maldevelopment of the placenta is associated with unfavorable pregnancy outcomes, such as lower birth weight and hypertension \u003csup\u003e(\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e)\u003c/sup\u003e. Endothelial dysfunction is considered the initial stage of atherosclerosis \u003csup\u003e(\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e)\u003c/sup\u003e, and proinflammatory cytokines implicated in rheumatoid arthritis also contribute to the development of atherosclerosis \u003csup\u003e(\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e)\u003c/sup\u003e. Furthermore, in patients with rheumatoid arthritis, the upregulated expression of vascular endothelial growth factor (VEGF), a crucial regulator of endothelial dysfunction \u003csup\u003e(\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e)\u003c/sup\u003e, may lead to the development of pre-eclampsia during pregnancy \u003csup\u003e(\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e)\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eEpidemiologic data suggests that pregnancy-related hormones may influence the link between reproduction and the risk of rheumatoid arthritis. Excessive level of female hormones, such as estrogen and progesterone, may be protective against the development of rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e)\u003c/sup\u003e. During pregnancy, when estradiol and progesterone levels are high, women have a reduced risk of developing rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e)\u003c/sup\u003e. Hormone levels return to a non-pregnant state rapidly after delivery \u003csup\u003e(\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e)\u003c/sup\u003e, especially during the first 3 months, which appears to be a period of increased risk. A nationwide cohort study in Denmark found that women with hyperemesis gravidarum, gestational hypertension, or pre-eclampsia have a significantly higher risk of developing rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e)\u003c/sup\u003e. However, a population-based prospective study found that preterm delivery and small-for-gestational-age infants did not appear to have a significant association with subsequent rheumatoid arthritis \u003csup\u003e(\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e)\u003c/sup\u003e. Our study also did not find the causal relationship from the gene perspective. This may be due to the lack of individual-level information in the pooled data used, and the fact that the data on rheumatoid arthritis did not include data on its typing, due to which limitation it is difficult to determine a causal association of APOs on rheumatoid arthritis progression.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eStrengths and Limitations\u003c/h2\u003e \u003cp\u003eThis bidirectional two-sample MR study, which investigated the causal association between rheumatoid arthritis and APOs risk, had several strengths. First, the bidirectional two-sample Mendelian randomization analysis can reduce the effects of unknown confounders and small-sample selection bias. The bidirectional analysis ensures the inference of causality between rheumatoid arthritis and APOs in both directions. Furthermore, the study used a large sample size and SNPs from GWASs, which provided sufficient statistical validity to estimate causality. Finally, we applied a series of sensitivity analyses to ensure the consistency and the robustness of causal estimates.\u003c/p\u003e \u003cp\u003eInevitably, there were several limitations in our study. First, the summary data used in this study were all derived from individuals of European ancestry, which limited the generalizability of the findings to other ethnic groups. Therefore, there were limitations to extrapolation. Secondly, when examining the risk of rheumatoid arthritis associated with APOs, we set the \u003cem\u003eP\u003c/em\u003e-value threshold for SNPs at \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;5\u0026times;10\u003csup\u003e\u0026minus;\u0026thinsp;6\u003c/sup\u003e to ensure an adequate number of instrumental variables for heterogeneity and horizontal multivariate tests. This threshold may explain only a small portion of the variability in exposures and could affect the statistical efficacy of the causal estimates. Finally, we were unable to perform subgroup analyses due to the lack of specific information describing the severity of the disease and specific information at the individual level.\u003c/p\u003e \u003c/div\u003e"},{"header":"CONCLUSIONS","content":"\u003cp\u003eIn conclusion, this study confirmed the causal relationship between rheumatoid arthritis and adverse pregnancy outcomes, that is, rheumatoid arthritis is associated with an increased risk of gestational hypertension, pre-eclampsia, fetal growth restriction, and preterm delivery. It highlights the importance of more intensive prenatal care and early intervention among pregnant women with rheumatoid arthritis to prevent potential adverse obstetric outcomes. However, due to the limitations of the study, further research is warranted.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAPOs: Adverse Pregnancy Outcomes\u003c/p\u003e\n\u003cp\u003eLD: Linkage Disequilibrium\u003c/p\u003e\n\u003cp\u003eMR: Mendelian randomization\u003c/p\u003e\n\u003cp\u003eSNP: Single-nucleotide polymorphism\u003c/p\u003e\n\u003cp\u003eGWAS: Genome-Wide Association Studies\u003c/p\u003e\n\u003cp\u003eIV: Instrumental Variable\u003c/p\u003e\n\u003cp\u003eIVW: Inverse Variance-Weighted\u003c/p\u003e\n\u003cp\u003eMR-PRESSO: MR pleiotropy residual sum and outlier\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate: \u003c/strong\u003eAll the data were publicly available GWAS summary statistics, and therefore no additional ethical approval or informed consent was required. Ethical approval and participant consent were obtained in the original studies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication: \u003c/strong\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials: \u003c/strong\u003eThis study uses publicly available datasets, which can be found in the IEU Open Project (https://gwas.mrcieu.ac.uk/), and the FinnGen study (https://www.finngen.fi/en).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests:\u003c/strong\u003e The authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding: \u003c/strong\u003eThis work was supported by the Shandong Provincial Medical Association (YXH2022PT06001), the National Key Research and Development Program of China (2021YFF1201101) and ECCM Program of Clinical Research Center of Shandong University (2021SDUCRCE001).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contribution: \u003c/strong\u003eData collection, data curation, Methodology, Formal analysis, Software, and Visualization were performed by ZZ, TC, XL, XZ, JC, YZ, and XL. Writing original draft: ZZ, YZ. Funding acquisition: ML. Writing review and editing: YZ, XL, and ML. The corresponding authors attest that all listed authors meet authorship criteria and that no others meeting the criteria have been omitted.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments: \u003c/strong\u003eThe authors acknowledge the participants and investigators of the IEU Open Project study and FinnGen study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e \u003c/strong\u003e\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eIB M, G S. The pathogenesis of rheumatoid arthritis. N Engl J Med. 2011;365(23):2205-19.\u003c/li\u003e\n\u003cli\u003eSmith MH, Berman JR. What Is Rheumatoid Arthritis? Jama. 2022;327(12):1194.\u003c/li\u003e\n\u003cli\u003eSilman AJ, Pearson JE. Epidemiology and genetics of rheumatoid arthritis. Arthritis research. 2002;4 Suppl 3(Suppl 3):S265-72.\u003c/li\u003e\n\u003cli\u003ePennell LM, Galligan CL, Fish EN. 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Arthritis and rheumatism. 2004;50(11):3458-67.\u003c/li\u003e\n\u003cli\u003eSilman A, Kay A, Brennan P. Timing of pregnancy in relation to the onset of rheumatoid arthritis. Arthritis and rheumatism. 1992;35(2):152-5.\u003c/li\u003e\n\u003cli\u003eMastorakos G, Ilias I. Maternal hypothalamic-pituitary-adrenal axis in pregnancy and the postpartum period. Postpartum-related disorders. Annals of the New York Academy of Sciences. 2000;900:95-106.\u003c/li\u003e\n\u003cli\u003eMa KK, Nelson JL, Guthrie KA, Dugowson CE, Gammill HS. Adverse pregnancy outcomes and risk of subsequent rheumatoid arthritis. Arthritis \u0026amp; rheumatology (Hoboken, NJ). 2014;66(3):508-12.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"rheumatoid arthritis, adverse pregnancy outcomes, bidirectional two-sample Mendelian randomization","lastPublishedDoi":"10.21203/rs.3.rs-4120942/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4120942/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eThere is growing evidence of bidirectional associations between rheumatoid arthritis and adverse pregnancy outcomes (APOs) in observational studies, but little is known about the causal direction of these associations. Therefore, we explored the potential causal relationships between rheumatoid arthritis and APOs using a bidirectional two-sample Mendelian randomization (MR).\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eWe conducted a bidirectional two-sample Mendelian randomization analysis using available summary statistics from released genome-wide association studies. Summary statistics for instrument\u0026ndash;outcome associations were retrieved from two separate databases for rheumatoid arthritis and adverse pregnancy outcomes, respectively. The inverse-variance weighted method was used as the primary MR analysis. MR-Egger, MR pleiotropy residual sum and outlier (MR-PRESSO), and Cochran Q statistic method were implemented as sensitivity analyses approach to ensure the robustness of the results.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOur study showed that a higher risk of genetically predicted rheumatoid arthritis was associated with gestational hypertension (OR: 1.04, 95%CI: 1.02\u0026ndash;1.06), pre-eclampsia (OR: 1.06, 95%CI: 1.01\u0026ndash;1.11), fetal growth restriction (OR: 1.08, 95%CI: 1.04\u0026ndash;1.12), preterm delivery (OR:1.04, 95%CI: 1.01\u0026ndash;1.07). Furthermore, we found no evidence that APOs had causal effects on rheumatoid arthritis in the reverse MR analysis. There was no heterogeneity or horizontal pleiotropy.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThis MR analysis provides evidence of a positive causal association between rheumatoid arthritis and gestational hypertension, pre-eclampsia, fetal growth restriction and preterm delivery genetically. It highlights the importance of more intensive prenatal care and early intervention among pregnant women with rheumatoid arthritis to prevent potential adverse obstetric outcomes.\u003c/p\u003e","manuscriptTitle":"Rheumatoid Arthritis and Adverse Pregnancy Outcomes: A Bidirectional Two-Sample Mendelian Randomization Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-25 16:38:01","doi":"10.21203/rs.3.rs-4120942/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-17T04:38:54+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-05-16T13:45:22+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"79032732700968125829741428479205108724","date":"2024-04-28T13:56:41+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2024-04-19T15:42:53+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"62a28cd7-d734-4c72-bae4-90cc07824d06","date":"2024-03-30T13:37:13+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"8ee87bb9-8254-4634-9e1f-7d9b93f75cca_SNPRID","date":"2024-03-27T19:25:50+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2024-03-21T21:51:28+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-03-21T13:06:34+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-03-20T16:54:13+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Pregnancy and Childbirth","date":"2024-03-18T07:36:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-pregnancy-and-childbirth","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"prch","sideBox":"Learn more about [BMC Pregnancy and Childbirth](http://bmcpregnancychildbirth.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/prch/default.aspx","title":"BMC Pregnancy and Childbirth","twitterHandle":"@BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"28401618-aa1a-4cac-9367-455d3d6f34be","owner":[],"postedDate":"March 25th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2024-08-05T15:59:59+00:00","versionOfRecord":{"articleIdentity":"rs-4120942","link":"https://doi.org/10.1186/s12884-024-06698-3","journal":{"identity":"bmc-pregnancy-and-childbirth","isVorOnly":false,"title":"BMC Pregnancy and Childbirth"},"publishedOn":"2024-07-31 15:57:01","publishedOnDateReadable":"July 31st, 2024"},"versionCreatedAt":"2024-03-25 16:38:01","video":"","vorDoi":"10.1186/s12884-024-06698-3","vorDoiUrl":"https://doi.org/10.1186/s12884-024-06698-3","workflowStages":[]},"version":"v1","identity":"rs-4120942","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4120942","identity":"rs-4120942","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}