scholarly journals The Causal Effects of Insomnia on Bipolar Disorder, Depression, and Schizophrenia: A Two-Sample Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Peng Huang ◽  
Yixin Zou ◽  
Xingyu Zhang ◽  
Xiangyu Ye ◽  
Yidi Wang ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorder ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Treatment Strategies ◽  
European Population ◽  
Sensitivity Analyses ◽  
Causal Mechanism ◽  
Assumption Violations

Psychiatric disorder, including bipolar disorder (BD), major depression (MDD), and schizophrenia (SCZ), affects millions of persons around the world. Understanding the disease causal mechanism underlying the three diseases and identifying the modifiable risk factors for them hold the key for the development of effective preventative and treatment strategies. We used a two-sample Mendelian randomization method to assess the causal effect of insomnia on the risk of BD, MDD, and SCZ in a European population. We collected one dataset of insomnia, three of BD, one of MDD, and three of SCZ and performed a meta-analysis for each trait, further verifying the analysis through extensive complementarity and sensitivity analysis. Among the three psychiatric disorders, we found that only insomnia is causally associated with MDD and that higher insomnia increases the risk of MDD. Specifically, the odds ratio of MDD increase of insomnia is estimated to be 1.408 [95% confidence interval (CI): 1.210–1.640, p = 1.03E-05] in the European population. The identified causal relationship between insomnia and MDD is robust with respect to the choice of statistical methods and is validated through extensive sensitivity analyses that guard against various model assumption violations. Our results provide new evidence to support the causal effect of insomnia on MDD and pave ways for reducing the psychiatric disorder burden.

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

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.

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

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.

scholarly journals Depression and Osteoporosis: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Bin He ◽  
Qiong Lyu ◽  
Lifeng Yin ◽  
Muzi Zhang ◽  
Zhengxue Quan ◽  
...  
Keyword(s):  
Observational Studies ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Reverse Causality ◽  
Mineral Density

AbstractObservational studies suggest a link between depression and osteoporosis, but these may be subject to confounding and reverse causality. In this two-sample Mendelian randomization analysis, we included the large meta-analysis of genome-wide association studies for depression among 807,553 individuals (246,363 cases and 561,190 controls) of European descent, the large meta-analysis to identify genetic variants associated with femoral neck bone mineral density (FN-BMD), forearm BMD (FA-BMD) and lumbar spine BMD (LS-BMD) among 53,236 individuals of European ancestry, and the GWAS summary data of heel BMD (HE-BMD) and fracture among 426,824 individuals of European ancestry. The results revealed that genetic predisposition towards depression showed no causal effect on FA-BMD (beta-estimate: 0.091, 95% confidence interval [CI] − 0.088 to 0.269, SE:0.091, P value = 0.320), FN-BMD (beta-estimate: 0.066, 95% CI − 0.016 to 0.148, SE:0.042, P value = 0.113), LS-BMD (beta-estimate: 0.074, 95% CI − 0.029 to 0.177, SE:0.052, P value = 0.159), HE-BMD (beta-estimate: 0.009, 95% CI − 0.043 to 0.061, SE:0.027, P value = 0.727), or fracture (beta-estimate: 0.008, 95% CI − 0.071 to 0.087, SE:0.041, P value = 0.844). These results were also confirmed by multiple sensitivity analyses. Contrary to the findings of observational studies, our results do not reveal a causal role of depression in osteoporosis or fracture.

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

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.

scholarly journals Causal effect of renal function on venous thromboembolism: a two-sample Mendelian randomization investigation

2021 ◽  
Author(s):  
Shuai Yuan ◽  
Maria Bruzelius ◽  
Susanna C. Larsson
Keyword(s):  
Renal Function ◽  
Venous Thromboembolism ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Genome Wide ◽  
Increased Risk ◽  
Mr Study

AbstractWhether renal function is causally associated with venous thromboembolism (VTE) is not yet fully elucidated. We conducted a two-sample Mendelian randomization (MR) study to determine the causal effect of renal function, measured as estimated glomerular filtration rate (eGFR), on VTE. Single-nucleotide polymorphisms associated with eGFR were selected as instrumental variables at the genome-wide significance level (p < 5 × 10−8) from a meta-analysis of 122 genome-wide association studies including up to 1,046,070 individuals. Summary-level data for VTE were obtained from the FinnGen consortium (6913 VTE cases and 169,986 non-cases) and UK Biobank study (4620 VTE cases and 356,574 non-cases). MR estimates were calculated using the random-effects inverse-variance weighted method and combined using fixed-effects meta-analysis. Genetically predicted decreased eGFR was significantly associated with an increased risk of VTE in both FinnGen and UK Biobank. For one-unit decrease in log-transformed eGFR, the odds ratios of VTE were 2.93 (95% confidence interval (CI) 1.25, 6.84) and 4.46 (95% CI 1.59, 12.5) when using data from FinnGen and UK Biobank, respectively. The combined odds ratio was 3.47 (95% CI 1.80, 6.68). Results were consistent in all sensitivity analyses and no horizontal pleiotropy was detected. This MR-study supported a casual role of impaired renal function in VTE.

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

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.

scholarly journals 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

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.

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

2019 ◽  
Vol 4 ◽  
pp. 113 ◽  
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.

scholarly journals Effect of Basal Metabolic Rate on Cancer: A Mendelian Randomization Study

2021 ◽  
Vol 12 ◽  
Author(s):  
Jack C. M. Ng ◽  
C. Mary Schooling
Keyword(s):  
Growth Factor ◽  
Cancer Risk ◽  
Confidence Interval ◽  
Metabolic Rate ◽  
Basal Metabolic Rate ◽  
Odds Ratio ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Sensitivity Analyses ◽  
Insulin Like Growth Factor

Background: Basal metabolic rate is associated with cancer, but these observations are open to confounding. Limited evidence from Mendelian randomization studies exists, with inconclusive results. Moreover, whether basal metabolic rate has a similar role in cancer for men and women independent of insulin-like growth factor 1 increasing cancer risk has not been investigated.Methods: We conducted a two-sample Mendelian randomization study using summary data from the UK Biobank to estimate the causal effect of basal metabolic rate on cancer. Overall and sex-specific analysis and multiple sensitivity analyses were performed including multivariable Mendelian randomization to control for insulin-like growth factor 1.Results: We obtained 782 genetic variants strongly (p-value &lt; 5 × 10–8) and independently (r2 &lt; 0.01) predicting basal metabolic rate. Genetically predicted higher basal metabolic rate was associated with an increase in cancer risk overall (odds ratio, 1.06; 95% confidence interval, 1.02–1.10) with similar estimates by sex (odds ratio for men, 1.07; 95% confidence interval, 1.002–1.14; odds ratio for women, 1.06; 95% confidence interval, 0.995–1.12). Sensitivity analyses including adjustment for insulin-like growth factor 1 showed directionally consistent results.Conclusion: Higher basal metabolic rate might increase cancer risk. Basal metabolic rate as a potential modifiable target of cancer prevention warrants further study.

Effect of metabolites levels on type 2 diabetes mellitus and glycemic traits: a Mendelian randomization study

2021 ◽  
Author(s):  
Yue Sun ◽  
Ya-Ke Lu ◽  
Hao-Yu Gao ◽  
Yu-Xiang Yan
Keyword(s):  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Type 2 Diabetes Mellitus ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Significance Level ◽  
Inverse Variance ◽  
Meta Analyses

Abstract Objective To assess the causal associations of plasma levels of metabolites with type 2 diabetes mellitus (T2DM) and glycemic traits. Methods Two-sample mendelian randomization (MR) was conducted to assess the causal associations. Genetic variants strongly associated with metabolites at genome-wide significance level (P &lt; 5 × 10 −8) were selected from public GWAS, and SNPs of Outcomes were obtained from the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) consortium for T2DM and from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) for the fasting glucose, insulin and HbA1c. The Wald ratio and inverse-variance weighted methods were used for analyses, and MR-Egger was used for sensitivity analysis. Results The β estimates per 1 SD increasement of arachidonic acid (AA) level was 0.16 (95% CI: 0.078, 0.242; P&lt;0.001). Genetic predisposition to higher plasma AA levels were associated with higher FG levels (β 0.10 [95%CI: 0.064, 0.134], P&lt;0.001), higher HbA1c levels (β 0.04 [95%CI: 0.027, 0.061]) and lower FI levels (β -0.025 [95%CI: -0.047, -0.002], P=0.033). Besides, 2-hydroxybutyric acid (2-HBA) might have positive causal effect on glycemic traits. Conclusions Our findings suggest that AA and 2-HBA may have the causal associations on T2DM and glycemic traits. It is beneficial for clarifying the pathogenesis of T2DM, which would be valuable for early identification and prevention for T2DM.

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