RETRACTED: Kidney damage on fertility and pregnancy: A Mendelian randomization

Jin Ren; Qiuyan Huang; Xiaowei Lie; Xingli Tong; Qi Yao; Ge Zhou

doi:10.1371/journal.pone.0288788

Abstract

Background

Low fertility and adverse pregnancy outcomes are commonly observed in women with chronic kidney disease (CKD). However, a causal relationship between low fertility and adverse pregnancy outcomes with CKD remains unclear. Besides, whether mild kidney dysfunction can affect fertility and pregnancy still needs exploration. Hence, this study aimed to investigate the causal effect of kidney damage on fertility and pregnancy using Mendelian randomization (MR).

Methods

We first used two-sample MR to examine the effects of kidney damage on fertility and pregnancy. Next, we introduced the Bayesian model averaging MR analysis to detect major causal relationships and render the results robust. The genetic instruments and outcome data were derived from various large genome-wide association studies.

Results

Adverse pregnancy outcomes: Our analyses supported a suggestive causal effect of CKD and estimated glomerular filtration rate (eGFR) rapid on stillbirth, with CKD having an odds ratio (OR) of 1.020 [95% confidence interval (CI) 1.002 to 1.038] and eGFR rapid having an OR of 1.026 (95% CI 1.004–1.048). We also discovered a suggestive causal effect of eGFR on spontaneous abortion, with an OR of 2.63 (95% CI 1.269 to 5.450). Moreover, increased urinary albumin-to-creatinine ratio (UACR) was regarded as a potential risk factor for pre-eclampsia (OR = 1.936; 95% CI 1.065 to 3.517) and gestational hypertension (OR = 1.700; 95% CI 1.002 to 2.886). Fertility assessment: The results indicated that eGFR and UACR had a suggestive causal relationship with the anti-Müllerian hormone level (eGFR beta: 1.004; UACR beta: 0.405).

Conclusions

Our study used MR to demonstrate a suggestive causal relationship between kidney damage and fertility and pregnancy. We reported that mild kidney dysfunction might be a risk factor for reduced fertility and adverse pregnancy outcomes. Dynamic renal detection may help preserve fertility and reduce the risk of pregnancy loss.

Citation: Ren J, Huang Q, Lie X, Tong X, Yao Q, Zhou G (2023) RETRACTED: Kidney damage on fertility and pregnancy: A Mendelian randomization. PLoS ONE 18(7): e0288788. https://doi.org/10.1371/journal.pone.0288788

Editor: Antonio Simone Laganà, University of Palermo: Universita degli Studi di Palermo, ITALY

Received: May 6, 2023; Accepted: July 3, 2023; Published: July 21, 2023

Copyright: © 2023 Ren et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Data Availability: All data used in this article is available online at the following website. The code of MR-BMA is provided in github (https://github.com/verena-zuber/demo_AMD); CKD GEN (https://ckdgen.imbi.uni-freiburg.de/); UK biobank (HTTP://www.nealelab.is/uk-biobank); IEU(https://gwas.mrcieu.ac.uk/); FinnGen(https://www.finngen.fi/en); ReproGen(http://www.reprogen.org/data_download.html); PHENOSCANNER (http://www.phenoscanner.medschl.cam.ac.uk/) Statistical power (https://shiny.cnsgenomics.com/mRnd/).

Funding: Funding Statement: This study was supported by the National Natural Science Foundation of China (No. 82074479); the Natural Science Foundation of Jiangsu Province (No. BK20201503); the Special Foundation of Clinical Medicine of Jiangsu Provincial Bureau of Science and Technology (No. ZT202107); the Special funding for the training of outstanding young doctors (No. 2023QB0141). There was no additional external funding received for this study. The funding source did not have any influence on the study design, analyses, interpretation of data.

Competing interests: In our study, no conflict of interest exits in the submission of this manuscript.

Introduction

Pregnancy is one of the most crucial events in a woman’s life, and the ability to conceive within a specific time frame is of utmost importance. A woman’s innate maternal instinct fuels her desire for fertility [1]. However, several women of reproductive age suffer from chronic kidney disease (CKD), which deprives them of the golden period of childbearing. Additionally, cohort studies [2, 3] have demonstrated that women with CKD are more likely to experience reduced fertility and adverse pregnancy outcomes, such as pre-eclampsia, preterm delivery, and low birth weight.

Approximately 3%-5% of women of reproductive age in most developed countries suffer from CKD [4, 5]. Despite their condition, several women with CKD still desire the same reproductive rights as healthy women. Consequently, accurately assessing the fertility and pregnancy risk of women with CKD and helping them choose the optimal time to conceive are often challenging for physicians. However, several nephrologists hesitate to accept patients’ requests to become pregnant due to the limited availability of substantial evidence supporting the safety and feasibility of pregnancy in this population [6]. A few even recommend long-term contraception as a means of disease control and stability. Whether mild kidney dysfunction can affect fertility and pregnancy remains unclear. Therefore, exploring the causal relationship of kidney damage with fertility and pregnancy is of utmost importance.

Fewer sample sizes and retrospective designs limit most existing studies, introducing bias and confounding factors. Considering the ethical challenges of randomizing women with or without kidney damage, alternative methods are needed to address the causal effect of kidney damage on fertility and pregnancy. Our study aimed to assess the causal relationship between exposure and outcome using Mendelian randomization (MR), a method that leverages genetic variants [7]. This approach helps minimize confounding and reverse causality biases. The study used genome-wide association studies (GWAS) to identify genetic variants strongly associated with exposure factors but not associated with confounding factors. The analysis also relied on the assumption that genetic variants were associated with outcomes solely through the exposure of interest (MR critical assumptions). The calculations were performed as described in the Materials and Methods section. Fig 1 briefly describes the study procedure.

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Fig 1. Flowchart describing the research process.

https://doi.org/10.1371/journal.pone.0288788.g001

Materials and methods

Genetic summary data of kidney damage

We screened summary-level analyses from CKDGen to comprehensively assess kidney function and obtained 5 exposure factors: CKD, estimated glomerular filtration rate (eGFR), eGFR rapid, microalbuminuria (MA), and urinary albumin-to-creatinine ratio (UACR). Wuttke et al. conducted a meta-analysis of GWAS for CKD, involving 480,698 individuals of European ancestry (EA), and eGFR, involving 567,460 individuals of EA [8]. The values of eGFR were calculated from serum creatinine level using the Modification of Diet in Renal Disease study equation [9]. CKD was defined as an eGFR of less than 60 mL/(min ∙ 1.73 m²) [10]. Teumer et al. provided the GWAS data for MA and UACR [11]. MA was measured in primarily 96% of individuals of EA (N = 347,283). The UACR was identified in 547,361 individuals of EA, with the results calculated using creatinine-corrected MA. We also included the metric EGFR rapid, a small sample metric (N = 39,213), which was defined as a decline of 3 ml/(min.1.73 m²) per year [12], implying a rapid decline in renal function. We added this metric to provide a simple stratification of eGFR. All included studies were permitted by their academic ethics review committees, and each participant signed written informed consent. This study was a re-analysis based on publicly available GWAS data; therefore, no additional ethical approval was required.

Outcome GWAS data

For the fertility assessment, we used anti-Müllerian hormone (AMH) data obtained from the GWAS catalog for 7049 premenopausal women of EA [13]. Additionally, data related to the age at menarche and age at menopause were obtained from the ReproGen consortium. Age at menarche was imputed for genotype data from approximately 370,000 women of EA [14], whereas age at menopause was calculated for approximately 200,000 ancestrally European women who underwent natural menopause [15]. Both age at menopause and age menarche can provide insights into a woman’s ovarian function to a certain extent [16]. AMH has been widely used by clinicians for almost 20 years to predict fertility potential in women [17]. As for adverse pregnancy outcomes, the data were derived from the FinnGen consortium and the UK Biobank (UKBB). The aforementioned outcomes were selected based on published findings and clinical observations.

FinnGen

FinnGen is a large GWAS that aims to analyze genomic data from Finnish participants. For our study, we selected the outcomes in FinnGen R7 on June 1, 2022, which included a total sample size of 309,154 participants (173,746 women and 135,408 men). Cases of adverse pregnancy outcomes were identified based on the International Classification of Diseases 9th or 10th codes. The adverse pregnancy outcomes included spontaneous abortion (cases = 13,354/controls = 124,547), preterm birth (cases = 8108/controls = 135,806), gestational (pregnancy-induced) hypertension (cases = 6562/controls = 160,670), pre-eclampsia (cases = 5256/controls = 160,670), preterm rupture of membranes (cases = 5066/controls = 142,734), and poor fetal growth (cases = 2579/controls = 171,167). Preterm birth was defined as gestational age <37 weeks [18]. Gestational hypertension was defined as hypertension diagnosed after pregnancy, excluding women with a history of chronic hypertension that could potentially cause kidney damage [2].

UK Biobank.

UKBB is one of the most comprehensive publicly available GWAS repositories for data (recruited between 2006 and 2010 in the United Kingdom). It offers a rich dataset that includes detailed distinctions, such as the ability to differentiate between sexes. This feature makes it suitable for conducting single-sex data analysis. In our study, we chose only-female data (except birthweight) as the outcome so that the confounding factor of sex could be weakened. The adverse pregnancy outcomes included the number of stillbirths (cases = 87,974), pregnancy hypertension (cases = 194,174), pre-eclampsia or eclampsia (cases = 319/controls = 226,285), preterm delivery (cases = 646/controls = 419,885), and preterm rupture of membranes (cases = 1080/controls = 419,451). Low birth weight or small for gestational age are not reported in the UKBB; therefore, we chose birthweight (case = 155,242) as a proxy, with birth weight adjusted for maternal age at birth.

Selection of genetic instruments

We selected genome-wide single-nucleotide polymorphisms (SNPs) using GWAS correlated P values (P value < 5e-08) and linkage disequilibrium (LD) (SNPs: r² < 0.001 within a 1-Mb genomic region) to obtain strongly independent and correlated genetic variants [10]. Subsequently, we calculated the F-statistic of each SNP to determine its strength (S1 Table). In our rigorous estimation of MR, we carefully examined these SNPs using PhenoScanner to treat the phenotypes associated with each SNP and minimize confounding factors. We distinguished between 2 various sets of screening criteria to further reduce pleiotropy: one for the traits associated with fertility (such as ovarian cancer and diabetes) and another for the traits that lead to adverse pregnancy outcomes (such as body mass index, alcohol abuse, hypertension, and autoimmune diseases). We then removed SNPs that could have influenced the outcome (S1 Table).

MR analyses

For each exposure–outcome pair, we performed two-sample MR analyses using three different methods: inverse variance weighted (MR-IVW), the MR-Egger, and the weighted median (MR-WM) [19]. The MR-IVW method was considered the most informative outcome, which used a random-effects meta-analysis approach to combine the Wald ratio estimates of the causal effect obtained from each SNP [20]. MR-Egger and MR-WM were used as supplementary analyses to assess the robustness of the findings. We employed MR-PRESSO to detect pleiotropy and remove outliers. The MR-Egger intercept test was used for further detection of pleiotropy. We also used Cochran’s Q test to detect heterogeneity. In addition, we presented leave-one-out plots to determine whether a single SNP drove causality. Funnel plots assessed symmetry visually, and scatter plots visualized the causal effect. All statistical analyses were conducted using R version 4.2.2.

The significance threshold was a 2-tailed Bonferroni correction, with a P value < (.05/75) considered statistically significant. The P value < .05 also indicated a statistically significant difference. A high-correction P value might filter out positive results because several characteristics were not independent, and a few were verified more than once.

We also used Bayesian model averaging MR (MR-BMA) analysis, which is often used for high-throughput experiments to identify the most remarkable risk factors even when the candidate exposure factors are correlated [21]. MR-BMA can further verify the reliability and render the results robust. During the MR-BMA analysis, we prioritized the models based on the posterior probability (PP) values (PP >.02). To rank the exposure variables, we used the marginal inclusion probability (MIP) [22], which involved summing up the PP values across all models. The highest MIP rank indicated the true causal association candidates [23]. We also calculated the model-averaged causal estimate, which represented the average direct effect of each exposure on the outcomes. Furthermore, we excluded SNP outliers with both high heterogeneity (Q > 10) and large Cook’s D and repeated the aforementioned steps after removing the SNP outliers to obtain new values.

Results

Two-sample MR

Adverse pregnancy outcomes.

In this set of screening criteria, we reserved 21 index SNPs for the genetic prediction of CKD, 15 for MA, 178 for eGFR, 51 for UACR, and 3 for eGFR rapid. Our MR analyses supported suggestive causal effects of CKD and eGFR rapid on stillbirth [CKD: odds ratio (OR) = 1.02, 95% confidence interval (CI) 1.002 to1.038; P = .023; eGFR rapid: OR = 1.026; 95% CI 1.004 to 1.048; P = .016]. We also observed suggestive causal effects of eGFR on spontaneous abortion. The OR of eGFR per 10% lower IVW-predicted spontaneous abortion was 2.63 (95% CI 1.269 to 5.450; P = .009). In addition, increased UACR was regarded as a potential risk factor for pre-eclampsia and gestational hypertension from FinnGen (PE: OR = 1.936, 95% CI 1.065 to 3.517; P = .030; GHP: OR = 1.700, 95% CI 1.002 to 2.886; P = .048). Gestational hypertension and pre-eclampsia are pathologically related [24]. Hence, we considered the positive results to be mutually reinforcing. However, UACR was not causally associated with “gestational hypertension” and "pre-eclampsia or eclampsia" from UKBB, suggesting that this might be due to the differences in the disease boundary between the 2 GWAS groups (FinnGen database was more rigorous in defining the disease boundary). In addition, MA and hypertension had a potential causal effect on pregnancy from UKBB (OR = 1.004, 95% CI 1.004 to 1.008; P = .031). Our MR analyses reported no causal effect of kidney damage on preterm birth, preterm rupture of membranes, or low birth weight (S2 Table).

Fertility evaluation

In this set of screening criteria, 23 index SNPs were reserved for the genetic prediction of CKD, 16 for MA, 197 for eGFR, 55 for UACR, and 3 for eGFR rapid. The results from our analysis revealed suggestive evidence of a causal relationship between increased eGFR and higher levels of AMH (SE: 0.492, P = .041), as well as between increased eGFR and genetically predicted longer age at menopause (SE: 1.342, P = .047). Furthermore, increased UACR was suggestive of a causal effect with higher levels of AMH (SE: 0.200, P = .042). No relationship between kidney function and age at menarche was observed (S2 Table). Fig 2 presents the results of the two-sample MR.

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Fig 2. Heatmap showing the causal estimates of kidney function on fertility and pregnancy using 2-sample MR.

https://doi.org/10.1371/journal.pone.0288788.g002

Bayesian model averaging MR analysis

Table 1 presents the results of the MR-BMA. The MR-BMA was validated 3 times for various SNPs to render the results more robust and identify the most relevant exposures. We conducted the MR-BMA test for exposures where causality was previously reported in two-sample MR. The MR-BMA results indicated that eGFR played a dominant role in spontaneous abortion, and eGFR rapid played a crucial role in stillbirth. UACR was the major risk factor for gestational hypertension and adjusted pre-eclampsia. The MR-BMA analysis might suggest a stronger causal relationship between UACR and AMH compared with eGFR. The MR-BMA further identified the direct causal relationship based on the 2-sample MR.

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Table 1. Ranking of traits indicative of the level of kidney damage for adverse pregnancy outcomes and fertility evaluation using MR-BMA.

https://doi.org/10.1371/journal.pone.0288788.t001

Sensitivity analysis

The sensitivity analysis conducted in our study allowed us to detect and correct horizontal pleiotropy using MR-PRESSO. Additionally, the MR-Egger intercept test indicated a low probability of pleiotropy (P value intercept >.05). Although most of our results were robust, a few showed potential heterogeneity based on Cochran’s Q test (P < .05). However, since we employed a random-effects model, this heterogeneity could be disregarded. The leave-one-out sensitivity analysis, as displayed in the supplementary materials, did not reveal any abnormal SNPs. Further sensitivity results and plots are provided in S1 Fig and S3 Table. Finally, we performed an MR review against the STROBE-MR checklist to ensure adherence to reporting guidelines.

Discussion

Our study represented the first comprehensive MR analysis exploring the causal effects of kidney damage on fertility and pregnancy. Our findings indicated a potential relationship between renal and reproductive pathophysiology.

Although precisely assessing the pregnancy rates of women with CKD on a population level is challenging, the low fertility rate can still be predicted [24]. The underlying causes of low fertility in women with CKD are attributed to the failure of high LH levels to peak during ovulation, primarily due to decreased estrogen and/or increased prolactin [25] levels. This results in non-ovulation or sporadic ovulation. Kidney damage may also result in follicular atresia and increased follicular depletion. Cohort studies have demonstrated that women with CKD experience a 43% decrease in AMH levels and enter menopause 4–5 years earlier compared with the general population (P<0.001) [26, 27]. In our MR study, the results indicated that increased eGFR was suggestively causal with an increase in AMH and suggestively causal with the genetically predicted longer age at menopause, indicating that an increase in eGFR in women with CKD might serve as a protective factor for ovarian reserve and potentially extend their reproductive years. Our study also revealed a positive correlation between UACR and AMH. We preferred to interpret it as a compensatory increase in the AMH level in mild kidney dysfunction. A previous study reported that women with CKD undergoing hemodialysis or kidney transplantation might experience a slight increase in the AMH level [28]. The exact mechanism by which AMH is reversible remains uncertain, but a compensatory increase in the AMH level does not necessarily indicate normal ovulation and fertility.

A large number of studies reported conflicting results on stillbirth. A retrospective study (N = 502,186 singleton births) conducted in the United States demonstrated that women with CKD were more likely to experience stillbirth (6.4%) [29]. This relationship, however, did not reach a remarkable level (95% CI, 0.95–1.43) in the Swedish cohort study (N = 2,788,490 singleton births) [2]. According to our study, CKD had a suggestive causal effect on stillbirth. That is, for every 1 standard deviation (SD) increase in CKD, the risk of stillbirth increased by 2%. Rapidly declining eGFR might be a remarkable risk factor for stillbirth; the OR of stillbirth was 1.02 for 1 SD in the decrease of eGFR rapid. It followed that the rapid decline [more than 3 mL/(min ∙ 1.73 m²) per year] and persistent low levels [<60 mL/(min ∙ 1.73 m²)] of eGFR might be the key factors influencing the live birth rate. As a result, the dynamic monitoring of eGFR might be beneficial for predicting stillbirths, considering that eGFR is one of the most sensitive indicators of kidney function. Even mild kidney dysfunction may cause a decrease in eGFR due to the disruption of renal hyperfiltration that accompanies pregnancy. Our study revealed that mild kidney dysfunction might increase the risk of spontaneous abortion.

Previous studies have suggested that women with CKD are at an increased risk of experiencing complications such as pre-eclampsia, preterm birth, and small for gestational age infants [3, 30]. However, accurately assessing the rates of adverse pregnancy-related outcomes solely based on historical studies due to variations in the definition of CKD and differences in the thresholds used to identify the decrease. Our study revealed that increased UACR levels might contribute to the development of gestational hypertension and pre-eclampsia. For every 1 SD increase in UACR, the risk of gestational hypertension increased by 70% and the risk of pre-eclampsia increased by 90%. In the UKBB dataset, increased MA was also regarded as a suggestive causal factor in gestational hypertension. No correlation was observed between MA or UACR and "pre-eclampsia or eclampsia." This discrepancy might be due to the involvement of more organs and complex pathologic processes in the transition from pre-eclampsia to eclampsia.

Glomerular endothelial cell injury is a common pathophysiologic mechanism in both CKD and hypertensive disorders of pregnancy [31]. It plays a key role in the development of urinary protein abnormalities. Postpartum renal biopsies in women with pre-eclampsia reveal extensive glomerular endothelial cell injury, similar to the pathology observed in early gestational hypertension [32]. It is hypothesized that glomerular endothelial cell injury may occur early in pregnancy and lead to the destruction of the glomerular basement membrane. Urinary albumin serves as a sensitive indicator of systemic vascular endothelial cell injury and small-vessel spasms. Microalbuminuria may reflect glomerular endothelial cell injury at an earlier stage, and these pathologic changes can be captured by urine microalbumin or transient UACR tests [33]. Obstetricians no longer recommend proteinuria as a diagnostic criterion for pre-eclampsia because its presence signifies irreversible renal damage. UACR is a vital indicator for diagnosing and grading CKD and assessing diabetic nephropathy in nonpregnant individuals. However, its utility in predicting adverse pregnancy outcomes is not well understood. Our study suggested that the presence of MA and elevated UACR levels were associated with gestational hypertension and pre-eclampsia and might serve as more sensitive pathologic markers than "substantially elevated blood pressure" and "remarkable proteinuria." Consequently, the early detection of MA and UACR (before 12 weeks of gestation) could potentially help in the earlier diagnosis of gestational hypertension and pre-eclampsia.

This study had several limitations. First, the population studied was predominantly European, which limits the generalizability of the results to other populations. No overlap existed between CKDGen, FinnGen, and GWAS catalogs. However, some limited overlap might exist with CKDGen, UKBB, and ReproGen (less than 10%). Second, we used summary statistics, and hence were unable to stratify CKD by severity or subtype. This implied that we could only speculate regarding the impact of early-stage CKD on fertility and pregnancy outcomes based on the indicators of kidney function. However, the effects of various stages of CKD on fertility and pregnancy might vary. Hence, further studies are warranted to investigate these outcomes in patients with varying stages and subtypes of kidney disease. Finally, considering the limitations in statistical power, caution should be exercised when drawing conclusions. More rigorous statistical methods are needed for further investigation in the future.

Our study recommended expanded testing of renal function indicators, especially eGFR, UACR, and MA, in women during pre-pregnancy and pregnancy. Also, early UACR and MA testing is essential for women at risk of gestational hypertension and pre-eclampsia, and it should be performed prior to urine protein testing. Further, the dynamic testing of eGFR may be essential in women with CKD who have experienced spontaneous abortion and stillbirth. In a word, it is vital to monitor renal function in women with a history of adverse pregnancies and kidney damage because mild abnormalities are often overlooked and can be potential risk factors. Nephrologists should encourage preconception counseling and provide patients with clinical support for decision-making. The mechanisms linking kidney damage to reduced fertility and adverse pregnancy outcomes should also be further investigated.

Conclusions

This study was novel in demonstrating a suggestive causal relationship of kidney damage with fertility and pregnancy. We reported that mild kidney dysfunction might be a risk factor for reduced fertility and adverse pregnancy outcomes. The study emphasized that dynamic eGFR detection might help preserve fertility and reduce the risk of pregnancy loss. The early detection of UACR and MA during pregnancy may contribute to the early detection of gestational hypertension and pre-eclampsia, which has remarkable implications for mid- and late-pregnancy care.

Supporting information

S1 Checklist. STROBE-MR-checklist.

https://doi.org/10.1371/journal.pone.0288788.s001

(PDF)

S1 Table. Basic SNP information and F-statistic.

https://doi.org/10.1371/journal.pone.0288788.s002

(PDF)

S2 Table. The outcome of two-sample MR.

https://doi.org/10.1371/journal.pone.0288788.s003

(PDF)

S3 Table. The outcome of MR-PRESSO.

https://doi.org/10.1371/journal.pone.0288788.s004

(PDF)

S1 Fig. Sensitivity results and plots.

https://doi.org/10.1371/journal.pone.0288788.s005

(PDF)

Acknowledgments

All genetic summary data were obtained from CKD GEN, UKBB, FinnGen, GWAS catalog, and ReproGen consortium. We thank all participants and investigators for contributing GWAS data.

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RETRACTED: Kidney damage on fertility and pregnancy: A Mendelian randomization

RETRACTED: Kidney damage on fertility and pregnancy: A Mendelian randomization

Retraction

Correction

Figures

Abstract

Background

Methods

Results

Conclusions

Introduction

Materials and methods

Genetic summary data of kidney damage

Outcome GWAS data

FinnGen

UK Biobank.

Selection of genetic instruments

MR analyses

Results

Two-sample MR

Adverse pregnancy outcomes.

Fertility evaluation

Bayesian model averaging MR analysis

Sensitivity analysis

Discussion

Conclusions

Supporting information

S1 Checklist. STROBE-MR-checklist.

S1 Table. Basic SNP information and F-statistic.

S2 Table. The outcome of two-sample MR.

S3 Table. The outcome of MR-PRESSO.

S1 Fig. Sensitivity results and plots.

Acknowledgments

References