scholarly journals Are psychiatric disorders risk factors for COVID-19 susceptibility and severity? a two-sample, bidirectional, univariable and multivariable Mendelian Randomization study

2020 ◽  
Author(s):  
Jurjen J. Luykx ◽  
Bochao D. Lin
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Neuropsychiatric Disorders ◽  
Sensitivity Analyses ◽  
Effect Estimate ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Increased Risk

AbstractImportanceObservational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome limitations of observational studies, e.g. unmeasured confounding and uncertainties about cause and effect.ObjectiveTo elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity.MethodIn November, 2020, we applied a two-sample, bidirectional, univariable and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released on 20 Oct. 2020). Our study population consisted of almost 2 million participants with either a (neuro)psychiatric disorder or data on COVID-19 status. Outcomes and exposures were anxiety, anxiety-and-stress related disorders, major depressive disorder, schizophrenia, bipolar disorder, schizophrenia-bipolar disorder combined (BIP-SCZ), and Alzheimer’s dementia on the one hand; and self-reported, confirmed, hospitalized, and very severe COVID-19 on the other.ResultsIn single-variable MR analysis the most significant and only Bonferroni-corrected significant result was found for BIP-SCZ (a combined anxiety of bipolar disorder and schizophrenia as cases vs. controls): the effect estimate was consistent with increased risk of COVID-19 (OR = 1.17, 95% CI, 1.06-1.28; p = 0.0012). Nominally significant univariable results were in line with slightly elevated risks of COVID-19 for genetic liabilities to bipolar disorder and schizophrenia. No COVID-19 phenotype consistently increased risk of (neuro)psychiatric disorders. In multivariable MR, bipolar disorder was the only phenotype showing a Bonferroni-corrected significant effect on a COVID-19 phenotype, namely severe COVID-19 (OR = 1.293; 95% CI, 1.095-1.527; p = 0.003). All sensitivity analyses confirmed the results.ConclusionsGenetic liability to bipolar disorder slightly increases COVID-19 susceptibility and severity. The contribution of bipolar disorder to these COVID-19 phenotypes was smaller than the odds ratios estimated by observational studies. Strength of association and direction of effect for genetic liability to schizophrenia were similar, albeit less significant. We found no consistent evidence of reverse effects, i.e. of genetic liability to COVID-19 on psychiatric disorders.

scholarly journals Are psychiatric disorders risk factors for COVID-19 susceptibility and severity? a two-sample, bidirectional, univariable, and multivariable Mendelian Randomization study

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jurjen J. Luykx ◽  
Bochao D. Lin
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Neuropsychiatric Disorders ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Genetic Liability ◽  
Bidirectional Associations

AbstractObservational studies have suggested bidirectional associations between psychiatric disorders and COVID-19 phenotypes, but results of such studies are inconsistent. Mendelian Randomization (MR) may overcome the limitations of observational studies, e.g., unmeasured confounding and uncertainties about cause and effect. We aimed to elucidate associations between neuropsychiatric disorders and COVID-19 susceptibility and severity. To that end, we applied a two-sample, bidirectional, univariable, and multivariable MR design to genetic data from genome-wide association studies (GWASs) of neuropsychiatric disorders and COVID-19 phenotypes (released in January 2021). In single-variable Generalized Summary MR analysis, the most significant and only Bonferroni-corrected significant result was found for genetic liability to BIP-SCZ (a combined GWAS of bipolar disorder and schizophrenia as cases vs. controls) increasing risk of COVID-19 (OR = 1.17, 95% CI, 1.06–1.28). However, we found a significant, positive genetic correlation between BIP-SCZ and COVID-19 of 0.295 and could not confirm causal or horizontally pleiotropic effects using another method. No genetic liabilities to COVID-19 phenotypes increased the risk of (neuro)psychiatric disorders. In multivariable MR using both neuropsychiatric and a range of other phenotypes, only genetic instruments of BMI remained causally associated with COVID-19. All sensitivity analyses confirmed the results. In conclusion, while genetic liability to bipolar disorder and schizophrenia combined slightly increased COVID-19 susceptibility in one univariable analysis, other MR and multivariable analyses could only confirm genetic underpinnings of BMI to be causally implicated in COVID-19 susceptibility. Thus, using MR we found no consistent proof of genetic liabilities to (neuro)psychiatric disorders contributing to COVID-19 liability or vice versa, which is in line with at least two observational studies. Previously reported positive associations between psychiatric disorders and COVID-19 by others may have resulted from statistical models incompletely capturing BMI as a continuous covariate.

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 The bidirectional causal relationships of insomnia with five major psychiatric disorders: A Mendelian randomization study

2019 ◽  
Vol 60 ◽  
pp. 79-85 ◽  
Author(s):  
Xue Gao ◽  
Ling-Xian Meng ◽  
Kai-Li Ma ◽  
Jie Liang ◽  
Hui Wang ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Bipolar Disorder ◽  
Confidence Interval ◽  
Psychiatric Disorders ◽  
Mendelian Randomization ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Outcome Variable ◽  
Genome Wide Association Studies ◽  
Causal Relationships

AbstractBackground:Several observational studies have investigated the association of insomnia with psychiatric disorders. Such studies yielded mixed results, and whether these associations are causal remains unclear. Thus, we aimed to identify the causal relationships between insomnia and five major psychiatric disorders.Methods:The analysis was implemented with six genome-wide association studies; one for insomnia and five for psychiatric disorders (attention-deficit/hyperactivity disorder, autism spectrum disorder, major depressive disorder, schizophrenia, and bipolar disorder). A heterogeneity in dependent instrument (HEIDI) approach was used to remove the pleiotropic instruments, Mendelian randomization (MR)-Egger regression was adopted to test the validity of the screened instruments, and bidirectional generalized summary data-based MR was performed to estimate the causal relationships between insomnia and these major psychiatric disorders.Results:We observed significant causal effects of insomnia on the risk of autism spectrum disorder and bipolar disorder, with odds ratios of 1.739 (95% confidence interval: 1.217–2.486, p = 0.002) and 1.786 (95% confidence interval: 1.396–2.285, p = 4.02 × 10−6), respectively. There was no convincing evidence of reverse causality for insomnia with these two disorders (p = 0.945 and 0.546, respectively). When insomnia was considered as either the exposure or outcome variable, causal estimates for the remaining three psychiatric disorders were not significant.Conclusions:Our results suggest a causal role of insomnia in autism spectrum disorder and bipolar disorder. Future disease models should include insomnia as a factor for these two disorders to develop effective interventions. More detailed mechanism studies may also be inspired by this causal inference.

scholarly journals Association of 25 hydroxyvitamin D concentration with risk of COVID-19: a Mendelian randomization study

2020 ◽  
Author(s):  
Di Liu ◽  
Qiuyue Tian ◽  
Jie Zhang ◽  
Haifeng Hou ◽  
Wei Wang ◽  
...  
Keyword(s):  
Causal Relationship ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Causal Association ◽  
Hydroxyvitamin D ◽  
Increased Risk ◽  
25Ohd Concentration ◽  
25 Hydroxyvitamin D

Background In observational studies, 25 hydroxyvitamin D (25OHD) concentration has been associated with an increased risk of Coronavirus disease 2019 (COVID-19). However, it remains unclear whether this association is causal. Methods We performed a two-sample Mendelian randomization (MR) to explore the causal relationship between 25OHD concentration and COVID-19, using summary data from the genome-wide association studies (GWASs) and using 25OHD concentration-related SNPs as instrumental variables (IVs). Results MR analysis did not show any evidence of a causal association of 25OHD concentration with COVID-19 susceptibility and severity (odds ratio [OR]=1.136, 95% confidence interval [CI] 0.988-1.306, P=0.074; OR=0.889, 95% CI 0.549-1.439, P=0.632). Sensitivity analyses using different instruments and statistical models yielded similar findings, suggesting the robustness of the causal association. No obvious pleiotropy bias and heterogeneity were observed. Conclusion The MR analysis showed that there might be no linear causal relationship of 25OHD concentration with COVID-19 susceptibility and severity.

scholarly journals Childhood obesity and multiple sclerosis: A Mendelian randomization study

2021 ◽  
pp. 135245852110017
Author(s):  
Adil Harroud ◽  
Ruth E Mitchell ◽  
Tom G Richardson ◽  
John A Morris ◽  
Vincenzo Forgetta ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Childhood Obesity ◽  
Mendelian Randomization ◽  
Pubertal Timing ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Increased Risk ◽  
Age At Puberty

Background: Higher childhood body mass index (BMI) has been associated with an increased risk of multiple sclerosis (MS). Objective: To evaluate whether childhood BMI has a causal influence on MS, and whether this putative effect is independent from early adult obesity and pubertal timing. Methods: We performed Mendelian randomization (MR) using summary genetic data on 14,802 MS cases and 26,703 controls. Large-scale genome-wide association studies provided estimates for BMI in childhood ( n = 47,541) and adulthood ( n = 322,154). In multivariable MR, we examined the direct effects of each timepoint and further adjusted for age at puberty. Findings were replicated using the UK Biobank ( n = 453,169). Results: Higher genetically predicted childhood BMI was associated with increased odds of MS (odds ratio (OR) = 1.26/SD BMI increase, 95% confidence interval (CI): 1.07–1.50). However, there was little evidence of a direct effect after adjusting for adult BMI (OR = 1.03, 95% CI: 0.70–1.53). Conversely, the effect of adult BMI persisted independent of childhood BMI (OR = 1.43; 95% CI: 1.01–2.03). The addition of age at puberty did not alter the findings. UK Biobank analyses showed consistent results. Sensitivity analyses provided no evidence of pleiotropy. Conclusion: Genetic evidence supports an association between childhood obesity and MS susceptibility, mediated by persistence of obesity into early adulthood but independent of pubertal timing.

scholarly journals Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Ify R Mordi ◽  
R Thomas Lumbers ◽  
Colin NA Palmer ◽  
Ewan R Pearson ◽  
Naveed Sattar ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Glycated Haemoglobin ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Fasting Insulin ◽  
Genetic Liability ◽  
Level Data

<b>Objective</b> <p>The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes, glycaemic traits and risk of HF.</p> <p><b>Research Design and Methods</b></p> <p>Summary-level data were obtained from genome-wide association studies (GWAS) of type 2 diabetes, insulin resistance (IR), glycated haemoglobin, fasting insulin and glucose and HF. MR was conducted using the inverse variance weighted (IVW) method. Sensitivity analyses included MR-Egger, weighted median and mode methods, and multivariable MR conditioning on potential mediators.</p> <p><b>Results</b></p> <p>Genetic liability to type 2 diabetes was causally related to higher risk of HF (OR: 1.13 per 1 log-unit higher risk of type 2 diabetes; 95% CI 1.11-1.14, p<0.001), however sensitivity analysis revealed evidence of directional pleiotropy. The relationship between type 2 diabetes and HF was attenuated when adjusted for coronary disease, body mass index, LDL-cholesterol and blood pressure. Genetically-instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1 log-unit higher risk of IR; 95% CI 1.00-1.41, p=0.041). There were no notable associations identified between fasting insulin, glucose or glycated haemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of type 2 diabetes (OR 1.49; 95% CI 1.01-2.19, p=0.042) though again with evidence of pleiotropy.</p> <p><b>Conclusions</b></p> These findings suggest a causal role of type 2 diabetes and IR in HF aetiology, though both the presence of bidirectional effects and directional pleiotropy highlight potential sources of bias that need to be considered.

Mendelian randomization highlights the causal role of normal thyroid function on blood lipid profiles

Endocrinology ◽  
2021 ◽  
Author(s):  
Yanjun Wang ◽  
Ping Guo ◽  
Lu Liu ◽  
Yanan Zhang ◽  
Ping Zeng ◽  
...  
Keyword(s):  
Correlation Analysis ◽  
Genetic Correlation ◽  
Thyroid Function ◽  
Observational Studies ◽  
Blood Lipids ◽  
Mendelian Randomization ◽  
Density Lipoprotein ◽  
Lipoprotein Cholesterol ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies

Abstract The association between thyroid function and dyslipidemia has been well documented in observational studies. However, observational studies are prone to confounding, making it difficult to conduct causal inference. We performed a two-sample bi-directional Mendelian randomization (MR) using summary statistics from large-scale genome-wide association studies (GWASs) of thyroid stimulating hormone (TSH), free thyroxine (FT4) and blood lipids. We chose inverse variance weighted (IVW) method as main analysis, and consolidated results through various sensitivity analyses involving six different MR methods under different model specifications. We further conducted genetic correlation analysis and colocalization analysis to deeply reflect the causality. The IVW method showed per one standard deviation (SD) increase in normal TSH was significantly associated with a 0.048 SD increase in total cholesterol (TC; P &lt; 0.001) and a 0.032 SD increase in low-density lipoprotein cholesterol (LDL; P = 0.021). Per one SD increase in normal FT4 was significantly associated with a 0.056 SD decrease in TC (P = 0.014) and a 0.072 SD decrease in LDL (P = 0.009). Neither TSH nor FT4 showed causal associations with high-density lipoprotein cholesterol (HDL) and triglycerides (TG). No significant causal effect of blood lipids on normal TSH or FT4 can be detected. All results were largely consistent when using several alternative MR methods, and were re-confirmed by both genetic correlation analysis and colocalization analysis. Our study suggested that even within reference range, higher TSH or lower FT4 are causally associated with increased TC and LDL, while no reverse causal association can be found.

scholarly journals Characterising the shared genetic determinants of bipolar disorder, schizophrenia and risk-taking

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Guy Hindley ◽  
Shahram Bahrami ◽  
Nils Eiel Steen ◽  
Kevin S. O’Connell ◽  
Oleksandr Frei ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Psychiatric Disorders ◽  
Risk Taking ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genome Wide Association Studies ◽  
Increased Risk ◽  
Risky Behaviours ◽  
Shared Risk ◽  
Shared Genetic

AbstractIncreased risk-taking is a central component of bipolar disorder (BIP) and is implicated in schizophrenia (SCZ). Risky behaviours, including smoking and alcohol use, are overrepresented in both disorders and associated with poor health outcomes. Positive genetic correlations are reported but an improved understanding of the shared genetic architecture between risk phenotypes and psychiatric disorders may provide insights into underlying neurobiological mechanisms. We aimed to characterise the genetic overlap between risk phenotypes and SCZ, and BIP by estimating the total number of shared variants using the bivariate causal mixture model and identifying shared genomic loci using the conjunctional false discovery rate method. Summary statistics from genome wide association studies of SCZ, BIP, risk-taking and risky behaviours were acquired (n = 82,315–466,751). Genomic loci were functionally annotated using FUMA. Of 8.6–8.7 K variants predicted to influence BIP, 6.6 K and 7.4 K were predicted to influence risk-taking and risky behaviours, respectively. Similarly, of 10.2–10.3 K variants influencing SCZ, 9.6 and 8.8 K were predicted to influence risk-taking and risky behaviours, respectively. We identified 192 loci jointly associated with SCZ and risk phenotypes and 206 associated with BIP and risk phenotypes, of which 68 were common to both risk-taking and risky behaviours and 124 were novel to SCZ or BIP. Functional annotation implicated differential expression in multiple cortical and sub-cortical regions. In conclusion, we report extensive polygenic overlap between risk phenotypes and BIP and SCZ, identify specific loci contributing to this shared risk and highlight biologically plausible mechanisms that may underlie risk-taking in severe psychiatric disorders.

scholarly journals Mendelian randomization highlights insomnia as a risk factor for pain diagnoses

SLEEP ◽  
2021 ◽  
Author(s):  
Martin Broberg ◽  
Juha Karjalainen ◽  
Hanna M Ollila ◽  
Keyword(s):  
Mendelian Randomization ◽  
Clinical Investigation ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Study Objective ◽  
Increased Risk ◽  
Icd 10 ◽  
Chronic Pain Conditions ◽  
Insomnia Symptoms

Abstract Study objective Insomnia has been linked to acute and chronic pain conditions; however, it is unclear whether such relationships are causal. Recently, a large number of genetic variants have been discovered for both insomnia and pain through genome-wide association studies (GWAS) providing a unique opportunity to examine evidence for causal relationships through the use of the Mendelian randomization paradigm. Methods To elucidate the causality between insomnia and pain we performed bidirectional Mendelian randomization analysis in FinnGen, where clinically diagnosed ICD-10 categories of pain had been evaluated. In addition, we used measures of self-reported insomnia symptoms. We used endpoints for pain in the FinnGen Release 5 (R5) (N=218,379), and a non-overlapping sample for insomnia (UK Biobank (UKBB) and 23andMe, N=1,331,010 or UKBB alone N=453,379). We assessed robustness of results through conventional MR sensitivity analyses. Results Genetic liability to insomnia symptoms increased the odds of reporting pain (odds ratio (OR) [95% confidence interval (CI)] = 1.47 [1.38–1.58], P = 4.12x10 -28). Manifested pain had a small effect on increased risk for insomnia (OR [95% CI] = 1.04 [1.01–1.07], P &lt; 0.05). Results were consistent in sensitivity analyses. Conclusions Our findings support a bidirectional causal relationship between insomnia and pain. These data support further clinical investigation into the utility of insomnia treatment as a strategy for pain management and vice versa.

scholarly journals Circulating Vitamin D Levels and Risk of Vitiligo: Evidence From Meta-Analysis and Two-Sample Mendelian Randomization

2021 ◽  
Vol 8 ◽  
Author(s):  
Jie Song ◽  
Ke Liu ◽  
Weiwei Chen ◽  
Bin Liu ◽  
Hong Yang ◽  
...  
Keyword(s):  
Vitamin D ◽  
Observational Studies ◽  
Mendelian Randomization ◽  
Meta Analysis ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Hydroxyvitamin D ◽  
Vitamin D Levels ◽  
Significant Difference ◽  
25 Hydroxyvitamin D

Background: The association between circulating vitamin D levels and risk of vitiligo was inconsistent among observational studies, and whether these observed associations were causal remained unclear. Therefore, we aimed to evaluate the effect of vitamin D on the risk of vitiigo using meta-analysis and Mendelian randomization (MR).Methods: At the meta-analysis stage, literature search was performed in PubMed and Web of Science to identify eligible observational studies examining the association of circulating 25-hydroxyvitamin D [25(OH)D] or 25-hydroxyvitamin D3 [25(OH)D3] levels with risk of vitiligo up to April 30, 2021. Standardized mean differences (SMDs) with 95% confidence intervals (CIs) of 25(OH)D and 25(OH)D3 in patients with vitiligo relative to controls were pooled. Then at the MR stage, genetic instruments for circulating 25(OH)D (N = 120,618) and 25(OH)D3 (N = 40,562) levels were selected from a meta-analysis of genome-wide association studies (GWAS) of European descent, and summary statistics of vitiligo were obtained from a meta-analysis of three GWASs including 4,680 cases and 39,586 controls. We used inverse-variance weighted (IVW) as main method, followed by weighted-median and likelihood-based methods. Pleiotropic and outlier variants were assessed by MR-Egger regression and MR Pleiotropy RESidual Sum and Outlier (MR-PRESSO) test.Results: In the meta-analysis, patients with vitiligo had a lower level of circulating 25(OH)D compared with controls [SMD = −1.40; 95% confidence interval (CI): −1.91, −0.89; P &lt; 0.001], while no statistically significant difference of 25(OH)D3 between vitiligo cases and controls was found (SMD = −0.63; 95% CI: −1.29, 0.04; P = 0.064). However, in the MR analyses, genetically predicted 25(OH)D [odds ratio (OR) = 0.93, 95% CI = 0.66–1.31, P = 0.66] and 25(OH)D3 levels (OR = 0.95, 95% CI = 0.80–1.14, P = 0.60) had null associations with risk of vitiligo using the IVW method. Sensitivity analyses using alternative MR methods and instrumental variables (IV) sets obtained consistent results, and no evidence of pleiotropy or outliers was observed.Conclusion: Our study provided no convincing evidence for a causal effect of 25(OH)D or 25(OH)D3 levels on the risk of vitiligo. Further longitudinal and experimental studies, as well as functional studies are warranted to elucidate the role of vitamin D in the development of vitiligo.

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