The Causal Effects of Primary Biliary Cholangitis on Thyroid Dysfunction: A Two-Sample Mendelian Randomization Study

Background: Primary biliary cholangitis (PBC) is an autoimmune disease and is often accompanied by thyroid dysfunction. Understanding the potential causal relationship between PBC and thyroid dysfunction is helpful to explore the pathogenesis of PBC and to develop strategies for the prevention and treatment of PBC and its complications.Methods: We used a two-sample Mendelian randomization (MR) method to estimate the potential causal effect of PBC on the risk of autoimmune thyroid disease (AITD), thyroid-stimulating hormone (TSH) and free thyroxine (FT4), hyperthyroidism, hypothyroidism, and thyroid cancer (TC) in the European population. We collected seven datasets of PBC and related traits to perform a series MR analysis and performed extensive sensitivity analyses to ensure the reliability of our results.Results: Using a sensitivity analysis, we found that PBC was a risk factor for AITD, TSH, hypothyroidism, and TC with odds ratio (OR) of 1.002 (95% CI: 1.000–1.005, p = 0.042), 1.016 (95% CI: 1.006–1.027, p = 0.002), 1.068 (95% CI: 1.022–1.115, p = 0.003), and 1.106 (95% CI: 1.019–1.120, p = 0.042), respectively. Interestingly, using reverse-direction MR analysis, we also found that AITD had a significant potential causal association with PBC with an OR of 0.021 (p = 5.10E−4) and that the other two had no significant causal relation on PBC.Conclusion: PBC causes thyroid dysfunction, specifically as AITD, mild hypothyroidism, and TC. The potential causal relationship between PBC and thyroid dysfunction provides a new direction for the etiology of PBC.

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No Causal Association Between Adiponectin and the Risk of Rheumatoid Arthritis: A Mendelian Randomization Study

Frontiers in Genetics ◽

10.3389/fgene.2021.670282 ◽

2021 ◽

Vol 12 ◽

Author(s):

Hanzhu Chen ◽

Shuai Mi ◽

Jiahao Zhu ◽

Weidong Jin ◽

Yasong Li ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Genetic Correlation ◽

Causal Relationship ◽

Large Scale ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Sensitivity Analyses ◽

Reverse Direction ◽

Genome Wide Association Studies

Background: Accumulating evidence from observational studies suggested that circulating adiponectin levels are associated with the risk of rheumatoid arthritis (RA), but the causality remains unknown. We aimed to assess the causal relationship of adiponectin with RA risk.Methods: Based on summary statistics from large-scale genome-wide association studies (GWAS), we quantified the genetic correlation between adiponectin and RA. Then bidirectional Mendelian randomization (MR) analysis was performed to assess the causal relationship. Twenty single-nucleotide polymorphisms (SNPs) associated with adiponectin were selected as instrumental variables from a recent GWAS (n = 67,739). We applied theses SNPs to a large-scale GWAS for RA (14,361 cases and 43,923 controls) with replication using RA data from the FinnGen consortium (6,236 cases and 147,221 controls) and the UK Biobank (5,201 cases and 457,732 controls). The inverse-variance weighted (IVW) and multiple pleiotropy-robust methods were used for two-sample MR analyses.Results: Our analyses showed no significant genetic correlation between circulating adiponectin levels and RA [rG = 0.127, 95% confidence interval (CI): –0.012 to 0.266, P = 0.074]. In MR analyses, genetically predicted adiponectin levels were not significantly associated with the RA risk (odds ratio: 0.98, 95% CI: 0.88–1.09, P = 0.669). In the reverse direction analysis, there is little evidence supporting an association of genetic susceptibility to RA with adiponectin (β: 0.007, 95% CI: –0.003 to 0.018, P = 0.177). Replication analyses and sensitivity analyses using different models yielded consistent results.Conclusions: Our findings provided no evidence to support the causal effect of adiponectin levels on RA risk and of RA on circulating adiponectin levels.

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Causal Effects of Life Course Adiposity on Chronic Kidney Disease: A Mendelian Randomization Study

10.21203/rs.3.rs-746367/v1 ◽

2021 ◽

Author(s):

Wanchun Yang ◽

Hongchun Chen ◽

Qiuyun Yuan ◽

Yang Zou

Keyword(s):

Chronic Kidney Disease ◽

Kidney Disease ◽

Life Course ◽

Causal Relationship ◽

Mendelian Randomization ◽

Causal Effect ◽

Sensitivity Analyses ◽

Body Fat Percentage ◽

Fat Percentage ◽

Hip Circumference

Abstract Background Obesity is reported to be tightly correlated the development of chronic kidney disease (CKD). However, whether there exists causation is unknown, and it remains controversial about the role of obesity in CKD is protective or destructive. In this study, we try to infer the causal relationship between life course adiposity and CKD, to provide a rationale for obesity management in CKD patients.Methods A two-sample Mendelian randomization (MR) analysis was conducted to explore the causal relationship of life course adiposity traits including including body mass index (BMI), childhood BMI, body fat percentage (BF), birth weight (BW), waist circumference, hip circumference and waist-to-hip ratio (WHR) to CKD. Significant single nucleotide polymorphisms from genome-wide association study on human adiposity traits were utilized as exposure instruments, and summary statistics of CKD as outcome. The causal relationship was evaluated by inverse variance weighted, MR Egger regression and weighted median methods, and further verified by extensive sensitivity analyses.Results Genetically determined one standard deviation increase in adult BMI was associated with higher risk of CKD in all four MR methods. And other indexes including childhood BMI, body fat percentage, and waist/hip circumference also have a causal effect on the risk of CKD. The results were robust under all sensitivity analyses.Conclusions There exist causal effect of life course adiposity on the risk of CKD. A genetic predisposition to higher adult BMI may increase the risk of CKD.

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Maternal polycystic ovary syndrome and offspring birth weight: a Mendelian randomization study

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/clinem/dgab843 ◽

2021 ◽

Author(s):

Yuexin Gan ◽

Donghao Lu ◽

Chonghuai Yan ◽

Jun Zhang ◽

Jian Zhao

Keyword(s):

Birth Weight ◽

Polycystic Ovary Syndrome ◽

Causal Relationship ◽

Mendelian Randomization ◽

Polycystic Ovary ◽

Causal Effect ◽

Sensitivity Analyses ◽

European Ancestry ◽

Ovary Syndrome ◽

Genetic Instruments

Abstract Background Observational associations between maternal polycystic ovary syndrome (PCOS) and offspring birth weight (BW) have been inconsistent and the causal relationship is still uncertain. Objective We conducted a two-sample Mendelian randomization (MR) study to estimate the causal effect of maternal PCOS on offspring BW. Methods We constructed genetic instruments for PCOS with 14 single nucleotide polymorphisms (SNPs) which were identified in the genome-wide association study (GWAS) meta-analysis including 10,074 PCOS cases and 103,164 controls of European ancestry from seven cohorts. The genetic associations of these SNPs with the offspring BW were extracted from summary statistics estimated by the Early Growth Genetics (EGG) consortium (n = 406,063 European-ancestry individuals) using the weighted linear model (WLM), an approximation method of structural equation model (SEM), which separated maternal genetic effects from fetal genetic effects. We used a two-sample MR design to examine the causal relationship between maternal PCOS and offspring BW. Sensitivity analyses were conducted to assess the robustness of the MR results. Results We found little evidence for a causal effect of maternal PCOS on offspring BW (-6.1 g, 95% confidence interval [CI]: -16.8 g, 4.6 g). Broadly consistent results were found in the sensitivity analyses. Conclusion Despite the large scale of this study, our results suggested little causal effect of maternal PCOS on offspring BW. MR studies with a larger sample size of women with PCOS or more genetic instruments that would increase the variation of PCOS explained are needed in the future.

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Elucidation of a Causal Relationship Between Platelet Count and Hypertension: A Bi-Directional Mendelian Randomization Study

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.743075 ◽

2021 ◽

Vol 8 ◽

Author(s):

Po-Chun Chiu ◽

Amrita Chattopadhyay ◽

Meng-Chun Wu ◽

Tzu-Hung Hsiao ◽

Ching-Heng Lin ◽

...

Keyword(s):

Platelet Count ◽

Causal Relationship ◽

Mendelian Randomization ◽

Causal Effect ◽

Sensitivity Analyses ◽

Exact Nature ◽

Nucleotide Polymorphisms ◽

Single Nucleotide ◽

Inverse Variance ◽

Weighted Median

Hypertension has been reported as a major risk factor for diseases such as cardiovascular disease, and associations between platelet activation and risk for hypertension are well-established. However, the exact nature of causality between them remains unclear. In this study, a bi-directional Mendelian randomization (MR) analysis was conducted on 15,996 healthy Taiwanese individuals aged between 30 and 70 years from the Taiwan Biobank, recorded between 2008 and 2015. The inverse variance weighted (IVW) method was applied to determine the causal relationship between platelet count and hypertension with single nucleotide polymorphisms as instrumental variables (IVs). Furthermore, to check for pleiotropy and validity of the IVs, sensitivity analyses were performed using the MR-Egger, weighted median and simple median methods. This study provided evidence in support of a positive causal effect of platelet count on the risk of hypertension (odds ratio: 1.149, 95% confidence interval: 1.131–1.578, P < 0.05), using the weighted median method. A significant causal effect of platelet count on hypertension was observed using the IVW method. No pleiotropy was observed. The causal effect of hypertension on platelet count was found to be non-significant. Therefore, the findings from this study provide evidence that higher platelet count may have a significant causal effect on the elevated risk of hypertension for the general population of Taiwan.

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Bias in two-sample Mendelian randomization when using heritable covariable-adjusted summary associations

International Journal of Epidemiology ◽

10.1093/ije/dyaa266 ◽

2021 ◽

Author(s):

Fernando Pires Hartwig ◽

Kate Tilling ◽

George Davey Smith ◽

Deborah A Lawlor ◽

Maria Carolina Borges

Keyword(s):

Waist Circumference ◽

Genetic Variants ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

Real Data ◽

Sensitivity Analyses ◽

Effect Estimate ◽

Genome Wide Association Studies ◽

Residual Confounding

Abstract Background Two-sample Mendelian randomization (MR) allows the use of freely accessible summary association results from genome-wide association studies (GWAS) to estimate causal effects of modifiable exposures on outcomes. Some GWAS adjust for heritable covariables in an attempt to estimate direct effects of genetic variants on the trait of interest. One, both or neither of the exposure GWAS and outcome GWAS may have been adjusted for covariables. Methods We performed a simulation study comprising different scenarios that could motivate covariable adjustment in a GWAS and analysed real data to assess the influence of using covariable-adjusted summary association results in two-sample MR. Results In the absence of residual confounding between exposure and covariable, between exposure and outcome, and between covariable and outcome, using covariable-adjusted summary associations for two-sample MR eliminated bias due to horizontal pleiotropy. However, covariable adjustment led to bias in the presence of residual confounding (especially between the covariable and the outcome), even in the absence of horizontal pleiotropy (when the genetic variants would be valid instruments without covariable adjustment). In an analysis using real data from the Genetic Investigation of ANthropometric Traits (GIANT) consortium and UK Biobank, the causal effect estimate of waist circumference on blood pressure changed direction upon adjustment of waist circumference for body mass index. Conclusions Our findings indicate that using covariable-adjusted summary associations in MR should generally be avoided. When that is not possible, careful consideration of the causal relationships underlying the data (including potentially unmeasured confounders) is required to direct sensitivity analyses and interpret results with appropriate caution.

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Using genetic variants to evaluate the causal effect of serum vitamin D concentration on COVID-19 susceptibility, severity and hospitalization traits: a Mendelian randomization study

Journal of Translational Medicine ◽

10.1186/s12967-021-02973-5 ◽

2021 ◽

Vol 19 (1) ◽

Author(s):

Zhiyong Cui ◽

Yun Tian

Keyword(s):

Vitamin D ◽

Fixed Effects ◽

Mendelian Randomization ◽

Causal Effect ◽

Serum Vitamin ◽

Vitamin D Supplementation ◽

Sensitivity Analyses ◽

Global Test ◽

Serum Vitamin D

Abstract Background The coronavirus disease 2019 (COVID-19) pandemic has struck globally and is exerting a devastating toll on humans. The pandemic has led to calls for widespread vitamin D supplementation in public. However, evidence supporting the role of vitamin D in the COVID-19 pandemic remains controversial. Methods We performed a two-sample Mendelian randomization (MR) analysis to analyze the causal effect of the 25-hydroxyvitamin D [25(OH)D] concentration on COVID-19 susceptibility, severity and hospitalization traits by using summary-level GWAS data. The causal associations were estimated with inverse variance weighted (IVW) with fixed effects (IVW-fixed) and random effects (IVW-random), MR-Egger, weighted edian and MR Robust Adjusted Profile Score (MR.RAPS) methods. We further applied the MR Steiger filtering method, MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) global test and PhenoScanner tool to check and remove single nucleotide polymorphisms (SNPs) that were horizontally pleiotropic. Results We found no evidence to support the causal associations between the serum 25(OH)D concentration and the risk of COVID-19 susceptibility [IVW-fixed: odds ratio (OR) = 0.9049, 95% confidence interval (CI) 0.8197–0.9988, p = 0.0473], severity (IVW-fixed: OR = 1.0298, 95% CI 0.7699–1.3775, p = 0.8432) and hospitalized traits (IVW-fixed: OR = 1.0713, 95% CI 0.8819–1.3013, p = 0.4878) using outlier removed sets at a Bonferroni-corrected p threshold of 0.0167. Sensitivity analyses did not reveal any sign of horizontal pleiotropy. Conclusions Our MR analysis provided precise evidence that genetically lowered serum 25(OH)D concentrations were not causally associated with COVID-19 susceptibility, severity or hospitalized traits. Our study did not provide evidence assessing the role of vitamin D supplementation during the COVID-19 pandemic. High-quality randomized controlled trials are necessary to explore and define the role of vitamin D supplementation in the prevention and treatment of COVID-19.

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Using a Two-Sample Mendelian Randomization Method in Assessing the Causal Relationships Between Human Blood Metabolites and Heart Failure

Frontiers in Cardiovascular Medicine ◽

10.3389/fcvm.2021.695480 ◽

2021 ◽

Vol 8 ◽

Author(s):

Zixian Wang ◽

Shiyu Chen ◽

Qian Zhu ◽

Yonglin Wu ◽

Guifeng Xu ◽

...

Keyword(s):

Heart Failure ◽

Human Blood ◽

Large Scale ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Meta Analysis ◽

Sensitivity Analyses ◽

Blood Metabolites ◽

Causal Relationships

Background: Heart failure (HF) is the main cause of morbidity and mortality worldwide, and metabolic dysfunction is an important factor related to HF pathogenesis and development. However, the causal effect of blood metabolites on HF remains unclear.Objectives: Our chief aim is to investigate the causal relationships between human blood metabolites and HF risk.Methods: We used an unbiased two-sample Mendelian randomization (MR) approach to assess the causal relationships between 486 human blood metabolites and HF risk. Exposure information was obtained from Sample 1, which is the largest metabolome-based genome-wide association study (mGWAS) data containing 7,824 Europeans. Outcome information was obtained from Sample 2, which is based on the results of a large-scale GWAS meta-analysis of HF and contains 47,309 cases and 930,014 controls of Europeans. The inverse variance weighted (IVW) model was used as the primary two-sample MR analysis method and followed the sensitivity analyses, including heterogeneity test, horizontal pleiotropy test, and leave-one-out analysis.Results: We observed that 11 known metabolites were potentially related to the risk of HF after using the IVW method (P < 0.05). After adding another four MR models and performing sensitivity analyses, we found a 1-SD increase in the xenobiotics 4-vinylphenol sulfate was associated with ~22% higher risk of HF (OR [95%CI], 1.22 [1.07–1.38]).Conclusions: We revealed that the 4-vinylphenol sulfate may nominally increase the risk of HF by 22% after using a two-sample MR approach. Our findings may provide novel insights into the pathogenesis underlying HF and novel strategies for HF prevention.

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Causal Association Between Heart Failure and Alzheimer’s Disease: A Two-Sample Bidirectional Mendelian Randomization Study

Frontiers in Genetics ◽

10.3389/fgene.2021.772343 ◽

2022 ◽

Vol 12 ◽

Author(s):

Chenglin Duan ◽

Jingjing Shi ◽

Guozhen Yuan ◽

Xintian Shou ◽

Ting Chen ◽

...

Keyword(s):

Heart Failure ◽

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Sensitivity Analysis ◽

Causal Relationship ◽

Observational Studies ◽

Mendelian Randomization ◽

Causal Effect ◽

Causal Relationships ◽

Simple Mode

Background: Traditional observational studies have demonstrated an association between heart failure and Alzheimer’s disease. The strengths of observational studies lie in their speed of implementation, cost, and applicability to rare diseases. However, observational studies have several limitations, such as uncontrollable confounders. Therefore, we employed Mendelian randomization of genetic variants to evaluate the causal relationships existing between AD and HF, which can avoid these limitations.Materials and Methods: A two-sample bidirectional MR analysis was employed. All datasets were results from the UK’s Medical Research Council Integrative Epidemiology Unit genome-wide association study database, and we conducted a series of control steps to select the most suitable single-nucleotide polymorphisms for MR analysis, for which five primary methods are offered. We reversed the functions of exposure and outcomes to explore the causal direction of HF and AD. Sensitivity analysis was used to conduct several tests to avoid heterogeneity and pleiotropic bias in the MR results.Results: Our MR studies did not support a meaningful causal relationship between AD on HF (MR-Egger, p = 0.634 > 0.05; weighted median (WM), p = 0.337 > 0.05; inverse variance weighted (IVW), p = 0.471 > 0.05; simple mode, p = 0.454 > 0.05; weighted mode, p = 0.401 > 0.05). At the same time, we did not find a significant causal relationship between HF and AD with four of the methods (MR-Egger, p = 0.195 > 0.05; IVW, p = 0.0879 > 0.05; simple mode, p = 0.170 > 0.05; weighted mode, p = 0.110 > 0.05), but the WM method indicated a significant effect of HF on AD (p = 0.025 < 0.05). Because the statistical powers of IVW and MR-Egger are more than that of WM, we think that there is no causal effect of HF on AD. Sensitivity analysis and horizontal pleiotropy were not detected in the MR analysis.Conclusion: Our results did not provide significant evidence indicating any causal relationships between HF and AD in the European population. Therefore, more large-scale datasets or datasets related to similar factors are expected for further MR analysis.

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Leukocyte telomere length and amyotrophic lateral sclerosis: a Mendelian randomization study

10.21203/rs.3.rs-522773/v2 ◽

2021 ◽

Author(s):

Kailin Xia ◽

Linjing Zhang ◽

Gan Zhang ◽

Yajun Wang ◽

Tao Huang ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Telomere Length ◽

Causal Relationship ◽

Mendelian Randomization ◽

Association Studies ◽

Sensitivity Analyses ◽

Genome Wide Association Studies ◽

Leukocyte Telomere Length ◽

Weighted Median ◽

Lateral Sclerosis

Abstract Background Observational studies have suggested that telomere length is associated with amyotrophic lateral sclerosis (ALS). However, it remains unclear whether this association is causal. We employed a two-sample Mendelian randomization (MR) approach to explore the causal relationship between leukocyte telomere length (LTL) and ALS based on the most cited and most recent and largest LTL genome-wide association studies (GWASs) that measured LTL with the Southern blot method (n = 9190) and ALS GWAS summary data (n = 80,610). We adopted the inverse variance weighted (IVW) method to examine the effect of LTL on ALS and used the weighted median method, simple median method, MR Egger method and MR PRESSO method to perform sensitivity analyses. Results We found that genetically determined longer LTL was inversely associated with the risk of ALS (OR = 0.846, 95% CI: 0.744–0.962, P = 0.011), which was mainly driven by rs940209 in the OBFC1 gene, suggesting a potential effect of OBFC1 on ALS. In sensitivity analyses, that was confirmed in MR Egger method (OR = 0.647,95% CI = 0.447–0.936, P = 0.050), and a similar trend was shown with the weighted median method (OR = 0.893, P = 0.201) and simple median method (OR = 0.935 P = 0.535). The MR Egger analyses did not suggest directional pleiotropy, showing an intercept of 0.025 (P = 0.168). Neither the influence of instrumental outliers nor heterogeneity was found. Conclusions Our results suggest that genetically predicted longer LTL has a causal relationship with a lower risk of ALS and underscore the importance of protecting against telomere loss in ALS.

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Using the MR-Base platform to investigate risk factors and drug targets for thousands of phenotypes

Wellcome Open Research ◽

10.12688/wellcomeopenres.15334.2 ◽

2019 ◽

Vol 4 ◽

pp. 113 ◽

Cited By ~ 12

Author(s):

Venexia M Walker ◽

Neil M Davies ◽

Gibran Hemani ◽

Jie Zheng ◽

Philip C Haycock ◽

...

Keyword(s):

Risk Factors ◽

Web Application ◽

Drug Targets ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

R Package ◽

Sensitivity Analyses ◽

Link Type ◽

Study Results

Mendelian randomization (MR) estimates the causal effect of exposures on outcomes by exploiting genetic variation to address confounding and reverse causation. This method has a broad range of applications, including investigating risk factors and appraising potential targets for intervention. MR-Base has become established as a freely accessible, online platform, which combines a database of complete genome-wide association study results with an interface for performing Mendelian randomization and sensitivity analyses. This allows the user to explore millions of potentially causal associations. MR-Base is available as a web application or as an R package. The technical aspects of the tool have previously been documented in the literature. The present article is complementary to this as it focuses on the applied aspects. Specifically, we describe how MR-Base can be used in several ways, including to perform novel causal analyses, replicate results and enable transparency, amongst others. We also present three use cases, which demonstrate important applications of Mendelian randomization and highlight the benefits of using MR-Base for these types of analyses.

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