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

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

Wellcome Open Research ◽

10.12688/wellcomeopenres.15334.1 ◽

2019 ◽

Vol 4 ◽

pp. 113 ◽

Cited By ~ 1

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 ◽

R Package ◽

Sensitivity Analyses ◽

Link Type ◽

Genome Wide ◽

Study Results

Mendelian randomization (MR) uses genetic information to strengthen causal inference concerning the effect of exposures on outcomes. 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 complimentary 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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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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Iron Status May Not Affect Amyotrophic Lateral Sclerosis: A Mendelian Randomization Study

Frontiers in Genetics ◽

10.3389/fgene.2021.617245 ◽

2021 ◽

Vol 12 ◽

Author(s):

Jiahao Cai ◽

Xiong Chen ◽

Hongxuan Wang ◽

Zixin Wei ◽

Mei Li ◽

...

Keyword(s):

Amyotrophic Lateral Sclerosis ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Iron Status ◽

Transferrin Saturation ◽

Outcome Data ◽

Sensitivity Analyses ◽

A Genome ◽

Lateral Sclerosis

BackgroundObservational studies have shown an association of increased iron status with a higher risk of amyotrophic lateral sclerosis (ALS). Iron status might be a novel target for ALS prevention if a causal relationship exists. We aimed to reveal the causality between iron status and ALS incidence using a large two-sample Mendelian randomization (MR).MethodsSingle nucleotide polymorphisms (SNPs) for iron status were identified from a genome-wide association study (GWAS) on 48,972 individuals. The outcome data came from the largest ALS GWAS to date (20,806 cases; 59,804 controls). We conducted conservative analyses (using SNPs with concordant change of biomarkers of iron status) and liberal analyses (using SNPs associated with at least one of the biomarkers of iron status), with inverse variance weighted (IVW) method as the main analysis. We then performed sensitivity analyses including weighted median, MR-Egger and MR-pleiotropy residual sum and outlier, as well as leave-one-out analysis to detect pleiotropy.ResultsIn the conservative analyses, we found no evidence of association between four biomarkers of iron status and ALS using IVW method with odds ratio (OR) 1.00 [95% confidence interval (CI): 0.90–1.11] per standard deviation (SD) increase in iron, 0.96 (95% CI: 0.77–1.21) in ferritin, 0.99 (95% CI: 0.92–1.07) in transferrin saturation, and 1.04 (95% CI: 0.93–1.16) in transferrin. Findings from liberal analyses were similar, and sensitivity analyses suggested no pleiotropy detected (all p > 0.05).ConclusionOur findings suggest no causal effect between iron status and risk of ALS. Efforts to change the iron status to decrease ALS incidence might be impractical.

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Inflammatory Cytokines and Risk of Ischemic Stroke: A Mendelian Randomization Study

Frontiers in Pharmacology ◽

10.3389/fphar.2021.779899 ◽

2022 ◽

Vol 12 ◽

Author(s):

Yalan Li ◽

Jun Lu ◽

Jie Wang ◽

Peizhi Deng ◽

Changjiang Meng ◽

...

Keyword(s):

Ischemic Stroke ◽

Inflammatory Cytokines ◽

Large Scale ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Meta Analysis ◽

Outcome Data ◽

Sensitivity Analyses ◽

A Genome

Background: Observational studies have revealed the association between some inflammatory cytokines and the occurrence of ischemic stroke, but the causal relationships remain unclear.Methods: We conducted a two-sample Mendelian randomization (MR) analysis to assess the causal effects of thirty inflammatory cytokines and the risk of ischemic stroke. For exposure data, we collected genetic variants associated with inflammatory cytokines as instrumental variables (IVs) from a genome-wide association study (GWAS) meta-analysis from Finland (sample size up to 8,293). For the outcome data, we collected summary data of ischemic stroke from a large-scale GWAS meta-analysis involved 17 studies (34,217 cases and 406,111 controls). We further performed a series of sensitivity analyses as validation of primary MR results.Results: According to the primary MR estimations and further sensitivity analyses, we established one robust association after Bonferroni correction: the odds ratio (95% CI) per unit change in genetically increased IL-4 was 0.84 (0.89–0.95) for ischemic stroke. The chemokine MCP3 showed a nominally significant association with ischemic stroke risk (OR: 0.93, 95% CI: 0.88–0.99, unadjusted p < 0.05). There was no evidence of a causal effect of other inflammatory cytokines and the risk of ischemic stroke.Conclusions: Our study suggested that genetically increased IL-4 levels showed a protective effect on the risk of ischemic stroke, which provides important new insights into the potential therapeutic target for preventing ischemic stroke.

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Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis

10.2337/figshare.13135781 ◽

2020 ◽

Author(s):

Tricia M. Peters ◽

Michael V. Holmes ◽

J. Brent Richards ◽

Tom Palmer ◽

Vincenzo Forgetta ◽

...

Keyword(s):

Type 2 Diabetes ◽

Coronary Heart Disease ◽

Heart Disease ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Sensitivity Analyses ◽

Chd Risk ◽

Unit Increase

Objective: Observational studies have demonstrated that type 2 diabetes is a stronger risk factor for coronary heart disease (CHD) in women compared with men. However, it is not clear whether this reflects a sex differential in the causal effect of diabetes on CHD risk or results from sex-specific residual confounding. Methods: Using 270 single nucleotide polymorphisms (SNPs) for type 2 diabetes identified in a type 2 diabetes genome-wide association study, we performed a sex-stratified Mendelian randomization (MR) study of type 2 diabetes and CHD using individual participant data in UK Biobank (N=251,420 women and 212,049 men). Weighted-median, MR Egger, MR-PRESSO and radial MR from summary-level analyses were used for pleiotropy assessment. Results: MR analyses showed that genetic risk of type 2 diabetes increased the odds of CHD for women (odds ratio [OR] 1.13, 95% confidence interval [CI] 1.08-1.18 per 1-log unit increase in odds of type 2 diabetes) and men (OR 1.21, 95% CI 1.17-1.26 per 1-log unit increase in odds of type 2 diabetes). Sensitivity analyses showed some evidence of directional pleiotropy, however, results were similar after correction for outlier SNPs. Conclusions: This MR analysis supports a causal effect of genetic liability to type 2 diabetes on risk of CHD that is not stronger for women than men. Assuming a lack of bias, these findings suggest that the prevention and management of type 2 diabetes for CHD risk reduction is of equal priority in both sexes.

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Mendelian randomization study shows no causal effects of serum urate levels on the risk of MS

Neurology Neuroimmunology & Neuroinflammation ◽

10.1212/nxi.0000000000000920 ◽

2020 ◽

Vol 8 (1) ◽

pp. e920

Author(s):

Adil Harroud ◽

J. Brent Richards ◽

Sergio E. Baranzini

Keyword(s):

Large Scale ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Meta Analysis ◽

Serum Urate ◽

Sensitivity Analyses ◽

Data Sets ◽

A Genome ◽

Mr Study

ObjectiveTo examine whether lifelong genetically increased serum urate levels, a potent antioxidant, contribute to MS susceptibility using Mendelian randomization (MR).MethodsThis 2-sample MR study included 25 independent genetic variants strongly associated with serum urate levels in a genome-wide association study meta-analysis of 140,949 individuals. Effects on the risk of MS were assessed with summary statistics from 3 large-scale MS genetic data sets totaling 61,667 MS cases and 86,806 controls from the International MS Genetic Consortium. Multiple sensitivity analyses were performed to evaluate the assumptions of MR and remove potentially pleiotropic variants.ResultsUsing inverse-variance weighted MR, we found no evidence for a causal effect of serum urate level on the risk of MS in any of the cohorts (MS1: OR 0.99 per each mg/dL unit increase in urate, 95% CI 0.89–1.08, p = 0.76; MS2: OR = 0.99, 95% CI 0.89–1.11, p = 0.90; MS3: OR = 1.00, 95% CI 0.98–1.2, p = 0.91). Pleiotropy robust MR methods yielded consistent estimates.ConclusionThis MR study does not support a clinically relevant causal effect of serum urate levels on the risk of MS.

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Causal Associations of Urate With Cardiovascular Risk Factors: Two-Sample Mendelian Randomization

Frontiers in Genetics ◽

10.3389/fgene.2021.687279 ◽

2021 ◽

Vol 12 ◽

Author(s):

Thitiya Lukkunaprasit ◽

Sasivimol Rattanasiri ◽

Boonsong Ongphiphadhanakul ◽

Gareth J. McKay ◽

John Attia ◽

...

Keyword(s):

Risk Factors ◽

Risk Factor ◽

Cardiovascular Risk ◽

Cardiovascular Risk Factors ◽

Instrumental Variables ◽

Mendelian Randomization ◽

Causal Effect ◽

Causal Effects ◽

Sensitivity Analyses ◽

Cardiac Risk Factor

BackgroundMendelian Randomization (MR) studies show conflicting causal associations of genetically predicted serum urate with cardiovascular risk factors (i.e., hypertension, diabetes, lipid profile, and kidney function). This study aimed to robustly investigate a causal relationship between urate and cardiovascular risk factors considering single nucleotide polymorphisms (SNPs) as instrumental variables using two-sample MR and various sensitivity analyses.MethodsData on SNP-urate associations were taken from the Global Urate Genetics Consortium and data on SNP-cardiovascular risk factor associations were taken from various consortia/UK Biobank. SNPs were selected by statistically and biologically driven approaches as instrumental variables. Various sensitivity analyses were performed using different MR methods including inverse variance weighted, MR-Egger, weighted median/mode, MR-PRESSO, and the contamination mixture method.ResultsThe statistically driven approach showed significant causal effects of urate on HDL-C and triglycerides using four of the six MR methods, i.e., every 1 mg/dl increase in genetically predicted urate was associated with 0.047 to 0.103 SD decrease in HDL-C and 0.034 to 0.207 SD increase in triglycerides. The biologically driven approach to selection of SNPs from ABCG2, SLC2A9, SLC17A1, SLC22A11, and SLC22A12 showed consistent causal effects of urate on HDL-C from all methods with 0.038 to 0.057 SD decrease in HDL-C per 1 mg/dl increase of urate, and no evidence of horizontal pleiotropy was detected.ConclusionOur study suggests a significant and robust causal effect of genetically predicted urate on HDL-C. This finding may explain a small proportion (7%) of the association between increased urate and cardiovascular disease but points to urate being a novel cardiac risk factor.

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Sex Differences in the Risk of Coronary Heart Disease Associated With Type 2 Diabetes: A Mendelian Randomization Analysis

10.2337/figshare.13135781.v1 ◽

2020 ◽

Author(s):

Tricia M. Peters ◽

Michael V. Holmes ◽

J. Brent Richards ◽

Tom Palmer ◽

Vincenzo Forgetta ◽

...

Keyword(s):

Type 2 Diabetes ◽

Coronary Heart Disease ◽

Heart Disease ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Sensitivity Analyses ◽

Chd Risk ◽

Unit Increase

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AB0210 ACREULAR: AN R PACKAGE FOR THE CALCULATION AND VISUALISATION OF ACR/EULAR RELATED RHEUMATOID ARTHRITIS MEASURES

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2020-eular.2326 ◽

2020 ◽

Vol 79 (Suppl 1) ◽

pp. 1405.1-1406

Author(s):

F. Morton ◽

J. Nijjar ◽

C. Goodyear ◽

D. Porter

Keyword(s):

Rheumatoid Arthritis ◽

Functional Status ◽

Rheumatic Diseases ◽

Web Application ◽

R Package ◽

Diagnostic Classification ◽

Microsoft Excel ◽

Link Type ◽

Large Joint ◽

Programming Skills

Background:The American College of Rheumatology (ACR) and the European League Against Rheumatism (EULAR) individually and collaboratively have produced/recommended diagnostic classification, response and functional status criteria for a range of different rheumatic diseases. While there are a number of different resources available for performing these calculations individually, currently there are no tools available that we are aware of to easily calculate these values for whole patient cohorts.Objectives:To develop a new software tool, which will enable both data analysts and also researchers and clinicians without programming skills to calculate ACR/EULAR related measures for a number of different rheumatic diseases.Methods:Criteria that had been developed by ACR and/or EULAR that had been approved for the diagnostic classification, measurement of treatment response and functional status in patients with rheumatoid arthritis were identified. Methods were created using the R programming language to allow the calculation of these criteria, which were incorporated into an R package. Additionally, an R/Shiny web application was developed to enable the calculations to be performed via a web browser using data presented as CSV or Microsoft Excel files.Results:acreular is a freely available, open source R package (downloadable fromhttps://github.com/fragla/acreular) that facilitates the calculation of ACR/EULAR related RA measures for whole patient cohorts. Measures, such as the ACR/EULAR (2010) RA classification criteria, can be determined using precalculated values for each component (small/large joint counts, duration in days, normal/abnormal acute-phase reactants, negative/low/high serology classification) or by providing “raw” data (small/large joint counts, onset/assessment dates, ESR/CRP and CCP/RF laboratory values). Other measures, including EULAR response and ACR20/50/70 response, can also be calculated by providing the required information. The accompanying web application is included as part of the R package but is also externally hosted athttps://fragla.shinyapps.io/shiny-acreular. This enables researchers and clinicians without any programming skills to easily calculate these measures by uploading either a Microsoft Excel or CSV file containing their data. Furthermore, the web application allows the incorporation of additional study covariates, enabling the automatic calculation of multigroup comparative statistics and the visualisation of the data through a number of different plots, both of which can be downloaded.Figure 1.The Data tab following the upload of data. Criteria are calculated by the selecting the appropriate checkbox.Figure 2.A density plot of DAS28 scores grouped by ACR/EULAR 2010 RA classification. Statistical analysis has been performed and shows a significant difference in DAS28 score between the two groups.Conclusion:The acreular R package facilitates the easy calculation of ACR/EULAR RA related disease measures for whole patient cohorts. Calculations can be performed either from within R or by using the accompanying web application, which also enables the graphical visualisation of data and the calculation of comparative statistics. We plan to further develop the package by adding additional RA related criteria and by adding ACR/EULAR related measures for other rheumatic disorders.Disclosure of Interests:Fraser Morton: None declared, Jagtar Nijjar Shareholder of: GlaxoSmithKline plc, Consultant of: Janssen Pharmaceuticals UK, Employee of: GlaxoSmithKline plc, Paid instructor for: Janssen Pharmaceuticals UK, Speakers bureau: Janssen Pharmaceuticals UK, AbbVie, Carl Goodyear: None declared, Duncan Porter: None declared

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A Preliminary Report on Alcohol-Associated DNA Methylation Changes and Suicidal Behavior: Evidence Using Mendelian Randomization

Illness Crisis & Loss ◽

10.1177/1054137320952246 ◽

2021 ◽

pp. 105413732095224

Author(s):

Charleen D. Adams

Keyword(s):

Public Health ◽

Dna Methylation ◽

Suicidal Behavior ◽

Genome Wide Association Study ◽

Mendelian Randomization ◽

Causal Effect ◽

Economic Stress ◽

Self Report ◽

Health Concern ◽

The Us

Suicide is a major public health concern. In 2015, it was the 10th leading cause of death in the US. The number of suicides increased by 30% in the US from 1999 to 2016, and a greater uptick in suicides is predicted to occur as a result of the COVID-19 crisis, for which the primary public-health strategy is physical distancing and during which alcohol sales have soared. Thus, current strategies for identifying at-risk individuals and preventing suicides, such as relying on self-reported suicidal ideation, are insufficient, especially under conditions of physical distancing, which exacerbate isolation, loneliness, economic stress, and possibly alcohol consumption. New strategies are urgent now and into the future. To that aim, here, a two-sample Mendelian randomization (an instrumental variables technique using public genome-wide association study data as data sources) was performed to determine whether alcohol-associated changes in DNA methylation mediate risk for suicidal behavior. The results suggest that higher alcohol-associated DNA methylation levels at cg18120259 confer a weak causal effect. Replication and triangulation of the results, both experimentally and with designs other than Mendelian randomization, are needed. If the findings replicate, the information might be utilized to raise awareness about the biological links between alcohol and suicide and possibly explored as a biomarker of risk, perhaps especially for early detection of those who may not self-report suicidal intent.

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