Multiple Sclerosis and risk of eight Adverse Events in Pregnancy: a Mendelian Randomization study

doi:10.21203/rs.3.rs-2006902/v1

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Multiple Sclerosis and risk of eight Adverse Events in Pregnancy: a Mendelian Randomization study

https://doi.org/10.21203/rs.3.rs-2006902/v1

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Background

Observational studies have found an association between multiple sclerosis (MS) and some adverse events in pregnancy, but the causal effect between them is unclear.

Methods

Using data from large-scale genome-wide association studies (GWAS), we performed two-sample Mendelian randomization (MR) analysis to comprehensively assess the causal relationship between MS and the risk of eight adverse events in pregnancy (gestational hypertension, diabetes mellitus in pregnancy, ectopic pregnancy, mental disorders, hemorrhage in pregnancy, intrahepatic cholestasis of pregnancy, infections of genitourinary tract in pregnancy, and postpartum hemorrhage).

Results

MR analysis found that MS significantly reduces the risk of diabetes mellitus in pregnancy [OR = 0.8718186, 95%CI (0.8298085, 0.9159556), P < 0.0001] and intrahepatic cholestasis of pregnancy [OR = 0.8813462, 95%CI (0.8052561, 0.9646262), P = 0.0061]. However, the causal effect of MS on the other six adverse events (gestational hypertension, ectopic pregnancy, mental disorders, hemorrhage in pregnancy, infections of genitourinary tract in pregnancy, and postpartum hemorrhage) was not statistically significant.

Conclusion

We found that MS significantly reduced the risk of diabetes mellitus in pregnancy and intrahepatic cholestasis of pregnancy, and the causal effect of MS on other six adverse events (gestational hypertension, ectopic pregnancy, mental disorders, hemorrhage in pregnancy, infections of genitourinary tract in pregnancy, and postpartum hemorrhage) is unclear.

multiple sclerosis

pregnancy

diabetes mellitus in pregnancy

intrahepatic cholestasis of pregnancy

Mendelian randomization

MS is a multifactorial chronic inflammatory disease affecting the central nervous system [1], and its incidence is increasing worldwide [2, 3]. This disease usually occurs between the ages of 20 and 50 years [4]. Moreover, it occurs more frequently in women [1]. Therefore, many MS patients are women of childbearing age, and there is a clinical need to study the impact of MS on the incidence of adverse events during pregnancy.

Currently, many studies [5–9] have been conducted on MS and adverse events during pregnancy. Which include the effect of MS on hypertension during pregnancy, diabetes during pregnancy, miscarriage, stillbirth, and other adverse events. Soler, B et al [10] found that women with MS have a higher risk of developing obstetric infections and preterm delivery, yet they do not have an elevated risk of other adverse pregnancy outcomes. A recent systematic review by Ahmed Arafa et al [11] suggests that pregnant women with MS had no increased risk of developing hypertension during pregnancy compared to pregnant women without MS. Other studies have also examined the relationship between MS and adverse events during pregnancy, but overall, the sample sizes of these studies [6, 9, 12–14] were generally small. Besides, some findings hardly prove a causal relationship between MS and adverse events during pregnancy.

MR analysis [15] is an epidemiological method that can be used to assess the causal relationship between exposure and outcome, which is unidirectional. In addition, this analytical approach is better able to circumvent the influence of confounding factors on the relationship between exposure and outcome, since genetic variants follow a strict random distribution at the time of conception and they usually act independently of environmental risk factors on the relationship between exposure and outcome [15]. Meanwhile, two-sample MR analyses can efficiently investigate disease causality based on data from open-access genome-wide association studies (GWASs). MR methods have been successful in explaining the causal relationship between exposure and outcome in many studies. However, there are no published MR studies between MS and the risk of adverse events during pregnancy.

In our study, genetic variants associated with MS were introduced as instrumental variables (IVs). By calculating the ratio of the effect of single nucleotide polymorphisms (SNPs) on the probability of eight adverse events during pregnancy to the effect of SNPs on MS, we attempted to explore the causal relationship between MS and eight adverse events during pregnancy.

2.1. Overall study design

Meeting three key assumptions is the basis of MR analysis. As shown in Fig. 1, in order to provide a valid interpretation of the MR analysis, the following three assumptions must hold. (1) IVs are significantly associated with MS (p < 5 × 10^− 8); (2) IVs affect the adverse events during pregnancy only through their effect on MS. (3) IVs are independent of any confounders of the “MS”- “adverse events during pregnancy” relationship. All SNPs and their associated information in this study were obtained from the GWAS (https://gwas.mrcieu.ac.uk/) website, which is a publicly available database. The latter analysis and graphing were achieved by R (version 4.1.1).

2.2. Data sources

The relevant information on the MS and eight adverse events during pregnancy studies included in the MR analysis and their corresponding GWAS database are shown in Table 1. All the data is publicly available and the original research was approved by the institute's institutional ethics approval committee. SNPs selected as IVs in our study needed to meet several conditions: p < 5 × 10^− 8, long physical distance in DNA (more than 10,000 kb), and no locus exceeding the limit in linkage disequilibrium (LD) analysis (R² < 0.001). This was to comply with the principles associated with MR analysis. In addition, these SNPs were required to exclude duplicate and echo SNPs.

Table 1

Details of the studies used in Mendelian Randomization. GWAS: genome-wide association studies (https://gwas.mrcieu.ac.uk/); SNP: single nucleotide polymorphism.
Disease	GWAS ID	Population	Sample size	Number of SNPs	Author
Multiple sclerosis	finn-b-G6_MS	European	218189	16380460	NA
Gestational hypertension	finn-b-O15_PREECLAMPS_CHRONIC_HYPERT	European	114818	16379587	NA
Diabetes mellitus in pregnancy	finn-b-O15_PREG_DM	European	116363	16379684	NA
Ectopic pregnancy	finn-b-O15_PREG_ECTOP	European	92451	16378923	NA
Mental disorders	finn-b-KRA_PSY_ANYMENTAL_SUICID_PREG_NERV	European	218792	16380466	NA
Hemorrhage in pregnancy	finn-b-O15_HAEMORRH_EARLY_PREG	European	113437	16379595	NA
Intrahepatic cholestasis of pregnancy	finn-b-O15_ICP	European	123579	16379784	NA
Infections of genitourinary tract in pregnancy	finn-b-O15_PREG_GU_INFECT	European	111731	16379553	NA
Postpartum hemorrhage	finn-b-O15_POSTPART_HEAMORRH	European	102296	16379289	NA

2.3. Mendelian randomization analysis

Statistical tests for MR analysis were performed using the “TwoSampleMR” (version 0.5.6) package in R (version 4.1.1). In the MR analysis, the inverse variance weighted (IVW) method was used as the main analysis to access each IV’s combined causal effects, supplemented by the weighted median, simple mode, weight mode and MR-Egger methods. The IVW approach was used to explore the causal relationship between genetically determined exposure factor (β_MS) and the outcomes (β_{gestational hypertension}, β_{diabetes mellitus in pregnancy}, β_{ectopic pregnancy}, β_{mental disorders}, β_{hemorrhage in pregnancy}, β_{intrahepatic cholestasis of pregnancy}, β_{infections of genitourinary tract in pregnancy}, β_{postpartum hemorrhage}). p < 0.05 was considered statistically significant. Complementary sensitivity analyses comprised of the MR-Egger were implemented to estimate the pleiotropy. The IVW and MR Egger methods were adopted to quantify the heterogeneity. Finally, a leave-one-out analysis was conducted to investigate the effect of a single SNP on the overall estimates.

Our final selection of SNPs met the basic conditions for Mendelian randomization analysis. We selected 5 eligible SNPs (rs141298848, rs149765808, rs55782725, rs9264277, and rs9271069) as IVs. We selected these SNPS because they satisfy three assumptions about MR mentioned in the method section. In addition, previous study [16] has found that some SNPs are associated with the pathogenesis of MS. The information of the 5 SNPs, including chromosome number, location, beta-value, P-value, is shown in Supplementary Table 1.

3.1. Results of MR analysis.

IVW analysis found that MS significantly decreases the risk of diabetes mellitus in pregnancy [OR = 0.8718186, 95%CI (0.8298085, 0.9159556), P < 0.0001] (Fig. 2, Table 2). Also, MS significantly decreases the risk of intrahepatic cholestasis of pregnancy [OR = 0.8813462, 95%CI (0.8052561, 0.9646262), P = 0.0061] (Fig. 3, Table 2).

Table 2

The causality of MS on gestational hypertension, diabetes mellitus in pregnancy, ectopic pregnancy, mental disorders, hemorrhage in pregnancy, intrahepatic cholestasis of pregnancy, infections of genitourinary tract in pregnancy, and postpartum hemorrhage. SNP: single nucleotide polymorphism; OR: odds ratio; CI: confidence interval.
Outcome	Methods	nSNP	OR (95%CI)	P
gestational hypertension	MR Egger	5	1.2884027 (0.5851502, 2.836847)	0.5738331
	Weighted median	5	1.0187770 (0.7159554, 1.449681)	0.9176718
	Inverse variance weighted	5	1.0438549 (0.7677295, 1.419293)	0.7842327
	Simple mode	5	0.9080038 (0.5646596, 1.460120)	0.7108246
	Weighted mode	5	1.0164300 (0.6832975, 1.511977)	0.9397576
Diabetes mellitus in pregnancy	MR Egger	5	0.8789535 (0.7597439, 1.0168680)	0.181
	Weighted median	5	0.8548085 (0.8151106, 0.8964398)	1.00654E-10
	Inverse variance weighted	5	0.8718186 (0.8298085, 0.9159556)	5.20927E-08
	Simple mode	5	0.8527942 (0.7869953, 0.9240944)	0.01773673
	Weighted mode	5	0.8517524 (0.8072843, 0.8986699)	0.004218641
Ectopic pregnancy	MR Egger	5	1.0419440 (0.9006957, 1.205343)	0.6189099
	Weighted median	5	0.9608597 (0.9053932, 1.019724)	0.1881254
	Inverse variance weighted	5	0.9605258 (0.9050052, 1.019453)	0.1849091
	Simple mode	5	1.0271824 (0.9114794, 1.157573)	0.682758
	Weighted mode	5	0.9521649 (0.8904085, 1.018205)	0.2252246
Mental disorders	MR Egger	5	0.9810233 (0.9333686, 1.031111)	0.5055754
	Weighted median	5	0.9937264 (0.9770090, 1.010730)	0.4671985
	Inverse variance weighted	5	0.9899978 (0.9730910, 1.007198)	0.2526806
	Simple mode	5	0.9907522 (0.9650177, 1.017173)	0.527056
	Weighted mode	5	0.9928264 (0.9753189, 1.010648)	0.4720893
Hemorrhage in pregnancy	MR Egger	5	0.9958032 (0.8749894, 1.133298)	0.9531918
	Weighted median	5	0.9822133 (0.9277929, 1.039826)	0.5371558
	Inverse variance weighted	5	0.9911560 (0.9424820, 1.042344)	0.729514
	Simple mode	5	0.9865255 (0.9125706, 1.066474)	0.7501053
	Weighted mode	5	0.9827823 (0.9240028, 1.045301)	0.6103635
Intrahepatic Cholestasis of Pregnancy	MR Egger	5	0.8301280 (0.6584494, 1.0465686)	0.213343731
	Weighted median	5	0.8938261 (0.8054126, 0.9919452)	0.034670357
	Inverse variance weighted	5	0.8813462 (0.8052561, 0.9646262)	0.006110375
	Simple mode	5	0.9244441 (0.7899171, 1.0818817)	0.382953342
	Weighted mode	5	0.8994042 (0.7936733, 1.0192204)	0.171922761
Infections of genitourinary tract in pregnancy	MR Egger	5	0.9734397 (0.8066868, 1.174663)	0.7971171
	Weighted median	5	1.0334392 (0.9520133, 1.121829)	0.4321317
	Inverse variance weighted	5	1.0289405 (0.9563478, 1.107043)	0.4446939
	Simple mode	5	1.0798389 (0.9332473, 1.249457)	0.3604223
	Weighted mode	5	0.9842624 (0.8959571, 1.081271)	0.7574301
Postpartum hemorrhage	MR Egger	5	1.0047251 (0.8914479, 1.132396)	0.9432976
	Weighted median	5	0.9845129 (0.9321733, 1.039791)	0.5754754
	Inverse variance weighted	5	0.9742588 (0.9299235, 1.020708)	0.2724447
	Simple mode	5	0.9761071 (0.9028856, 1.055267)	0.5761033
	Weighted mode	5	0.9832752 (0.9272333, 1.042704)	0.6032962

However, the causal effect of MS on the other six adverse events during pregnancy was not statistically significant (Table 2).

3.2. Sensitivity analysis

Heterogeneity was not significant in all SNPs among eight adverse events during pregnancy (all P > 0.05), which reduces the likelihood of bias (Supplementary Table 2). Besides, pleiotropy was not significant in our study (all P > 0.05), (Supplementary Table 3). Leave-one-out analysis revealed that no individual SNP could independently drive the overall results in the causal relationship of “MS- Diabetes mellitus in pregnancy” (P < 0.01) and “MS-ICP” (P < 0.05), (Supplementary Table 4).

In our study, the causal relationship between MS and eight adverse events during pregnancy (gestational hypertension, diabetes mellitus in pregnancy, ectopic pregnancy, mental disorders, hemorrhage in pregnancy, intrahepatic cholestasis of pregnancy, infections of genitourinary tract in pregnancy, and postpartum hemorrhage) was explored using a two-sample MR analysis. We found that MS can significantly decrease the risk of diabetes mellitus in pregnancy [OR = 0.8718186, 95%CI (0.8298085, 0.9159556), P < 0.0001]. Also, MS significantly decreases the risk of intrahepatic cholestasis of pregnancy [OR = 0.8813462, 95%CI (0.8052561, 0.9646262), P = 0.0061]. However, the causal effect of MS on the other six adverse events during pregnancy (gestational hypertension, ectopic pregnancy, mental disorders, hemorrhage in pregnancy, infections of genitourinary tract in pregnancy, and postpartum hemorrhage) was not statistically significant.

Many different studies[12, 13, 17, 18] have discussed the effects of MS on adverse events during pregnancy. Among them, some studies concluded that MS raises the risk of gestational hypertension, but others found no additional risk of preeclampsia in pregnant women with MS [11, 12]. A similar conclusion was reached in our study, with no significant causal effect of MS on hypertension during pregnancy [OR = 1.0438549, 95%CI (0.7677295, 1.419293), P = 0.7842327]. For the correlation between MS and diabetes, most studies [10, 12, 18] have found no significant association between them. However, according to the results we obtained, MS had a causal effect on the reduction of gestational diabetes [OR = 0.8718186, 95%CI (0.8298085, 0.9159556), P < 0.0001]. Besides, regarding genitourinary infections in pregnancy, previous studies have suggested that women with MS have a higher risk of genitourinary infections in pregnancy [13], while according to our results, a significant causal effect of MS on genitourinary infections in pregnancy was not supported [OR = 1.0289405, 95%CI (0.9563478, 1.107043), P = 0.4446939]. However, since genitourinary infections may be related to the type of pathogen, sanitary conditions in the area, and ethnicity, the specific relationship between MS and genitourinary infections may require more comprehensive analysis in larger sample studies. In addition, to the best of our knowledge, this study is the first to find that MS reduces the risk of intrahepatic cholestasis in pregnancy [OR = 0.8813462, 95%CI (0.8052561, 0.9646262), P < 0.01], but its exact mechanism is not clear. MS combined with intrahepatic cholestasis in pregnancy may be associated with intrahepatic cholestasis in pregnancy (ICP) caused by mutations in the ABCB4 [19]. Finally, regarding the relationship between MS and ectopic pregnancy, mental disorders, hemorrhage in pregnancy, and postpartum hemorrhage, previous studies [12, 13, 18] support that there is no significant association between MS and them. Our study suggests that there is no significant causal relationship between MS and ectopic pregnancy, mental disorders, hemorrhage in pregnancy, and postpartum hemorrhage.

Our study has several advantages. First, to the best of our knowledge, this study is the first MR study on the causal relationship between MS and adverse events during pregnancy. Second, we included the MS-related SNP dataset from the largest GWAS available, which contains 218189 samples and 16,380,460 SNPs, and the adverse events during pregnancy datasets were all obtained from the largest GWAS datasets, which can increase the statistical power of our study. Moreover, the MR approach allows us to obtain a simple causal relationship between them and reduce the influence of confounding factors on the relationship between them. This is because MR is based on the Mendelian correlation law of inheritance, where randomization among SNPs in different individuals is done at the time of gamete generation, and this randomization is similar to the randomized grouping in randomized controlled studies. It is also because individual SNP randomization is completed before an individual is born that the use of SNP as an instrumental variable to study exposure and disease causation is less likely to be confounded by acquired confounding factors.

However, some limitations of our study should not be overlooked. First, because of the limitation of datasets, the samples included in this study were all from European populations, so it is unknown whether our findings can be generalized to other ethnic groups. Besides, we did not analyze the relationship between some adverse events in pregnancy (preterm delivery, stillbirth, overdue delivery, etc.) and MS due to the lack of sufficient GWAS data.

In conclusion, the results of our MR study suggest that MS can significantly decrease the risk of diabetes mellitus in pregnancy and the risk of intrahepatic cholestasis of pregnancy in European ancestry. The causal effect of MS on the other six adverse events during pregnancy was not statistically significant. More studies about the causality between MS and adverse events during pregnancy are needed in the future to explore the relationship between them.

Declaration of interest: None

Acknowledgements: None.

Data Availability Statement: All data in this study are public and available through GWAS (https://gwas.mrcieu.ac.uk/)

Funding: This work is supported by “The special fund for the scientific and technological innovation strategy of Guangdong Province in 2022 (Special Fund for Climbing Plan)” [grant numbers pdjh2022a0581].

Competing interests: The authors declare no competing interests.

McGinley, M.P., C.H. Goldschmidt, and A.D. Rae-Grant, Diagnosis and Treatment of Multiple Sclerosis: A Review. Jama, 2021. 325(8): p. 765–779.
Kobelt, G., et al., New insights into the burden and costs of multiple sclerosis in Europe. Mult Scler, 2017. 23(8): p. 1123–1136.
Browne, P., et al., Atlas of Multiple Sclerosis 2013: A growing global problem with widespread inequity. Neurology, 2014. 83(11): p. 1022–4.
Runmarker, B. and O. Andersen, Pregnancy is associated with a lower risk of onset and a better prognosis in multiple sclerosis. Brain, 1995. 118 (Pt 1): p. 253–61.
Lu, E., et al., Birth hospitalization in mothers with multiple sclerosis and their newborns. Neurology, 2013. 80(5): p. 447–52.
Mueller, B.A., J. Zhang, and C.W. Critchlow, Birth outcomes and need for hospitalization after delivery among women with multiple sclerosis. Am J Obstet Gynecol, 2002. 186(3): p. 446–52.
Chen, Y.H., H.L. Lin, and H.C. Lin, Does multiple sclerosis increase risk of adverse pregnancy outcomes? A population-based study. Mult Scler, 2009. 15(5): p. 606–12.
Weber-Schoendorfer, C. and C. Schaefer, Multiple sclerosis, immunomodulators, and pregnancy outcome: a prospective observational study. Mult Scler, 2009. 15(9): p. 1037–42.
Jalkanen, A., A. Alanen, and L. Airas, Pregnancy outcome in women with multiple sclerosis: results from a prospective nationwide study in Finland. Mult Scler, 2010. 16(8): p. 950–5.
Soler, B., et al., Pregnancy outcomes in women with Multiple Sclerosis. Mult Scler Relat Disord, 2021. 48: p. 102682.
Arafa, A., et al., Does multiple sclerosis increase the risk of preeclampsia? A systematic review and meta-analysis. Hypertens Pregnancy, 2021. 40(3): p. 180–185.
Kelly, V.M., L.M. Nelson, and E.F. Chakravarty, Obstetric outcomes in women with multiple sclerosis and epilepsy. Neurology, 2009. 73(22): p. 1831–6.
Yalcin, S.E., et al., Maternal and perinatal outcomes in pregnancies with multiple sclerosis: a case-control study. J Perinat Med, 2017. 45(4): p. 455–460.
Goldacre, A., J. Pakpoor, and M. Goldacre, Perinatal characteristics and obstetric complications in mothers with multiple sclerosis: Record-linkage study. Mult Scler Relat Disord, 2017. 12: p. 4–8.
Lawlor, D.A., et al., Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med, 2008. 27(8): p. 1133–63.
Barnes, C.L.K., et al., Contribution of common risk variants to multiple sclerosis in Orkney and Shetland. Eur J Hum Genet, 2021. 29(11): p. 1701–1709.
Novo, A., et al., Pregnancy outcomes in Portuguese women with multiple sclerosis: The PREGNIMS study. Mult Scler Relat Disord, 2019. 28: p. 172–176.
Andersen, J.B., et al., Pregnancy-Related and Perinatal Outcomes in Women With Multiple Sclerosis: A Nationwide Danish Cross-sectional Study. Neurol Clin Pract, 2021. 11(4): p. 280–290.
De Masi, R., S. Orlando, and A. De Donno, Progressive familial intrahepatic cholestasis type-3 and multiple sclerosis: lessons from comorbidity. Ann Clin Transl Neurol, 2019. 6(11): p. 2347–2350.

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Multiple Sclerosis and risk of eight Adverse Events in Pregnancy: a Mendelian Randomization study

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Version 1

Abstract

Background

Methods

Results

Conclusion

Figures

1. Introduction

2. Material And Methods

2.1. Overall study design

2.2. Data sources

2.3. Mendelian randomization analysis

3. Results

3.1. Results of MR analysis.

3.2. Sensitivity analysis

4. Discussion

Declarations

References

Supplementary Files

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