Cardiometabolic risk factors for COVID-19 susceptibility and severity: A Mendelian randomization analysis

Background Epidemiological studies report associations of diverse cardiometabolic conditions including obesity with COVID-19 illness, but causality has not been established. We sought to evaluate the associations of 17 cardiometabolic traits with COVID-19 susceptibility and severity using 2-sample Mendelian randomization (MR) analyses. Methods and findings We selected genetic variants associated with each exposure, including body mass index (BMI), at p < 5 × 10−8 from genome-wide association studies (GWASs). We then calculated inverse-variance-weighted averages of variant-specific estimates using summary statistics for susceptibility and severity from the COVID-19 Host Genetics Initiative GWAS meta-analyses of population-based cohorts and hospital registries comprising individuals with self-reported or genetically inferred European ancestry. Susceptibility was defined as testing positive for COVID-19 and severity was defined as hospitalization with COVID-19 versus population controls (anyone not a case in contributing cohorts). We repeated the analysis for BMI with effect estimates from the UK Biobank and performed pairwise multivariable MR to estimate the direct effects and indirect effects of BMI through obesity-related cardiometabolic diseases. Using p < 0.05/34 tests = 0.0015 to declare statistical significance, we found a nonsignificant association of genetically higher BMI with testing positive for COVID-19 (14,134 COVID-19 cases/1,284,876 controls, p = 0.002; UK Biobank: odds ratio 1.06 [95% CI 1.02, 1.10] per kg/m2; p = 0.004]) and a statistically significant association with higher risk of COVID-19 hospitalization (6,406 hospitalized COVID-19 cases/902,088 controls, p = 4.3 × 10−5; UK Biobank: odds ratio 1.14 [95% CI 1.07, 1.21] per kg/m2, p = 2.1 × 10−5). The implied direct effect of BMI was abolished upon conditioning on the effect on type 2 diabetes, coronary artery disease, stroke, and chronic kidney disease. No other cardiometabolic exposures tested were associated with a higher risk of poorer COVID-19 outcomes. Small study samples and weak genetic instruments could have limited the detection of modest associations, and pleiotropy may have biased effect estimates away from the null. Conclusions In this study, we found genetic evidence to support higher BMI as a causal risk factor for COVID-19 susceptibility and severity. These results raise the possibility that obesity could amplify COVID-19 disease burden independently or through its cardiometabolic consequences and suggest that targeting obesity may be a strategy to reduce the risk of severe COVID-19 outcomes.

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Causal effect of atrial fibrillation/flutter on chronic kidney disease: A bidirectional two-sample Mendelian randomization study

PLoS ONE ◽

10.1371/journal.pone.0261020 ◽

2021 ◽

Vol 16 (12) ◽

pp. e0261020

Author(s):

Masahiro Yoshikawa ◽

Kensuke Asaba ◽

Tomohiro Nakayama

Keyword(s):

Atrial Fibrillation ◽

Chronic Kidney Disease ◽

Kidney Disease ◽

Odds Ratio ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

European Population ◽

Genome Wide Association Studies ◽

The Uk

Chronic kidney disease (CKD) and atrial fibrillation are both major burdens on the health care system worldwide. Several observational studies have reported clinical associations between CKD and atrial fibrillation; however, causal relationships between these conditions remain to be elucidated due to possible bias by confounders and reverse causations. Here, we conducted bidirectional two-sample Mendelian randomization analyses using publicly available summary statistics of genome-wide association studies (the CKDGen consortium and the UK Biobank) to investigate causal associations between CKD and atrial fibrillation/flutter in the European population. Our study suggested a causal effect of the risk of atrial fibrillation/flutter on the decrease in serum creatinine-based estimated glomerular filtration rate (eGFR) and revealed a causal effect of the risk of atrial fibrillation/flutter on the risk of CKD (odds ratio, 9.39 per doubling odds ratio of atrial fibrillation/flutter; 95% coefficient interval, 2.39–37.0; P = 0.001), while the causal effect of the decrease in eGFR on the risk of atrial fibrillation/flutter was unlikely. However, careful interpretation and further studies are warranted, as the underlying mechanisms remain unknown. Further, our sample size was relatively small and selection bias was possible.

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Frequent Daytime Napping is Detrimental to Human Health: A phenotype-wide Mendelian Randomization Study

10.1101/2020.01.20.20017723 ◽

2020 ◽

Author(s):

Lanlan Chen ◽

Aowen Tian ◽

Zhipeng Liu ◽

Miaoran Zhang ◽

Xingchen Pan ◽

...

Keyword(s):

Health Outcomes ◽

Human Health ◽

Mendelian Randomization ◽

Wide Spectrum ◽

Association Studies ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Major Depressive ◽

Genome Wide ◽

The Uk

ABSTRACTBackgroundIt remains controversial whether daytime napping is beneficial for human health.ObjectiveTo examine the causal relationship between daytime napping and the risk for various human diseases.DesignPhenotype-wide Mendelian randomization study.SettingNon-UK Biobank cohorts reported in published genome-wide association studies (GWAS) provided the outcome phenotypes in the discovery stage. The UK Biobank cohort provided the outcome phenotypes in the validation stage.ParticipantsThe UK Biobank GWAS included 361,194 European-ancestry residents in the UK. Non-UKBB GWAS included various numbers of participants.ExposureSelf-reported daytime napping frequency.Main outcome measureA wide-spectrum of human health outcomes including obesity, major depressive disorder, and high cholesterol.MethodsWe examined the causal relationship between daytime napping frequency in the UK Biobank as exposure and a panel of 1,146 health outcomes reported in genome-wide association studies (GWAS), using a two-sample Mendelian randomization analysis. The significant findings were further validated in the UK Biobank health outcomes of 4,203 human traits and diseases. The causal effects were estimated using a fixed-effect inverse variance weighted model. MR-Egger intercept test was applied to detect horizontal pleiotropy, along with Cochran’s Q test to assess heterogeneity among the causal effects of IVs.FindingsThere were significant causal relationships between daytime napping frequency and a wide spectrum of human health outcomes. In particular, we validated that frequent daytime napping increased the risks of major depressive disorder, obesity and abnormal lipid profile.InterpretationThe current study showed that frequent daytime napping mainly had adverse impacts on physical and mental health. Cautions should be taken for health recommendations on daytime napping. Further studies are necessary to precisely define the best daytime napping strategies.

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Polygenic prediction of breast cancer: comparison of genetic predictors and implications for screening

10.1101/448597 ◽

2018 ◽

Author(s):

Kristi Läll ◽

Maarja Lepamets ◽

Marili Palover ◽

Tõnu Esko ◽

Andres Metspalu ◽

...

Keyword(s):

Breast Cancer ◽

Genetic Risk ◽

Odds Ratio ◽

Population Based ◽

Risk Scores ◽

Full Potential ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Genetic Risk Scores ◽

The Uk

AbstractBackgroundPublished genetic risk scores for breast cancer (BC) so far have been based on a relatively small number of markers and are not necessarily using the full potential of large-scale Genome-Wide Association Studies. This study aims to identify an efficient polygenic predictor for BC based on best available evidence and to assess its potential for personalized risk prediction and screening strategies.MethodsFour different genetic risk scores (two already published and two newly developed) and their combinations (metaGRS) are compared in the subsets of two population-based biobank cohorts: the UK Biobank (UKBB, 3157 BC cases, 43,827 controls) and Estonian Biobank (EstBB, 317 prevalent and 308 incident BC cases in 32,557 women). In addition, correlations between different genetic risk scores and their associations with BC risk factors are studied in both cohorts.ResultsThe metaGRS that combines two genetic risk scores (metaGRS2 - based on 75 and 898 Single Nucleotide Polymorphisms, respectively) has the strongest association with prevalent BC status in both cohorts. One standard deviation difference in the metaGRS2 corresponds to an Odds Ratio = 1.6 (95% CI 1.54 to 1.66, p = 9.7*10-135) in the UK Biobank and accounting for family history marginally attenuates the effect (Odds Ratio = 1.58, 95% CI 1.53 to 1.64, p = 9.1*10-129). In the EstBB cohort, the hazard ratio of incident BC for the women in the top 5% of the metaGRS2 compared to women in the lowest 50% is 4.2 (95% CI 2.8 to 6.2, p = 8.1*10-13). The different GRSs are only moderately correlated with each other and are associated with different known predictors of BC. The classification of genetic risk for the same individual may vary considerably depending on the chosen GRS.ConclusionsWe have shown that metaGRS2 that combines on the effects of more than 900 SNPs provides best predictive ability for breast cancer in two different population-based cohorts. The strength of the effect of metaGRS2 indicates that the GRS could potentially be used to develop more efficient strategies for breast cancer screening for genotyped women.

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Genetic liability to insomnia in relation to cardiovascular diseases: a Mendelian randomisation study

European Journal of Epidemiology ◽

10.1007/s10654-021-00737-5 ◽

2021 ◽

Author(s):

Shuai Yuan ◽

Amy M. Mason ◽

Stephen Burgess ◽

Susanna C. Larsson

Keyword(s):

Cardiovascular Diseases ◽

Association Studies ◽

European Ancestry ◽

Mendelian Randomisation ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Genetic Liability ◽

Genome Wide ◽

Increased Risk ◽

The Uk

AbstractThe present study aimed to determine the associations between insomnia and cardiovascular diseases (CVDs) using Mendelian randomisation (MR) analysis. As instrumental variables, we used 208 independent single-nucleotide polymorphisms associated with insomnia at the genome-wide significance threshold in a meta-analysis of genome-wide association studies in the UK Biobank and 23andMe including a total of 397 959 self-reported insomnia cases and 933 057 non-cases. Summary-level data for nine CVDs were obtained from the UK Biobank including 367 586 individuals of European ancestry. After correction for multiple testing, genetic liability to insomnia was associated with higher odds of six CVDs, including peripheral arterial disease (odd ratio (OR) 1.22; 95% confidence interval (CI), 1.21, 1.33), heart failure (OR 1.21; 95% CI, 1.13, 1.30), coronary artery disease (OR 1.19; 95% CI, 1.14, 1.25), ischaemic stroke (OR 1.15; 95% CI, 1.06, 1.25), venous thromboembolism (OR 1.13; 95% CI, 1.07, 1.19) and atrial fibrillation (OR 1.10; 95% CI, 1.05, 1.15). There were suggestive associations for aortic valve stenosis (OR, 1.17; 95% CI, 1.04, 1.32) and haemorrhagic stroke (OR 1.14; 95% CI, 1.00, 1.29) but no association for abdominal aortic aneurysm (OR, 1.14, 95% CI, 0.98, 1.33). The patterns of associations remained with mild attenuation in multivariable MR analyses adjusting for genetically correlated phenotypes and potential mediators, including sleep duration, depression, body mass index, type 2 diabetes and smoking. The present MR study suggests potential causal associations of genetic liability to insomnia with increased risk of a broad range of CVDs.

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Detecting and correcting for bias in Mendelian randomization analyses using gene-by-environment interactions

10.1101/187849 ◽

2017 ◽

Cited By ~ 3

Author(s):

Wes Spiller ◽

David Slichter ◽

Jack Bowden ◽

George Davey Smith

Keyword(s):

Mendelian Randomization ◽

Association Studies ◽

Pleiotropic Effects ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Mixed Ancestry ◽

Gene By Environment Interactions ◽

Gene Environment ◽

Using Data ◽

The Uk

Background: Mendelian randomization has developed into an established method for strengthening causal inference and estimating causal effects, largely due to the proliferation of genome-wide association studies. However, genetic instruments remain controversial as pleiotropic effects can introduce bias into causal estimates. Recent work has highlighted the potential of gene-environment interactions in detecting and correcting for pleiotropic bias in Mendelian randomization analyses. Methods: We introduce MR using Gene-by-Environment interactions (MRGxE) as a framework capable of identifying and correcting for pleiotropic bias, drawing upon developments in econometrics and epidemiology. If an instrument-covariate interaction induces variation in the association between a genetic instrument and exposure, it is possible to identify and correct for pleiotropic effects. The interpretation of MRGxE is similar to conventional summary Mendelian randomization approaches, with a particular advantage of MRGxE being the ability to assess the validity of an individual instrument. Results: We investigate the effect of BMI upon systolic blood pressure (SBP) using data from the UK Biobank and the GIANT consortium using a single instrument (a weighted allelic score). We find MRGxE produces findings in agreement with MR Egger regression in a two-sample summary MR setting, however, association estimates obtained across all methods differ considerably when excluding related participants or individuals of non-European ancestry. This could be a consequence of selection bias, though there is also potential for introducing bias by using a mixed ancestry population. Further, we assess the performance of MRGxE with respect to identifying and correcting for horizontal pleiotropy in a simulation setting, highlighting the utility of the approach even when the MRGxE assumptions are violated. Conclusions: By utilising instrument-covariate interactions within a linear regression framework, it is possible to identify and correct for pleiotropic bias, provided the average magnitude of pleiotropy is constant across interaction covariate subgroups.

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Adipokines and risk of rheumatoid arthritis: a Mendelian randomization study

10.21203/rs.3.rs-36474/v1 ◽

2020 ◽

Author(s):

Jiahao Zhu ◽

Haiyan Zheng ◽

Yasong Li ◽

Tianle Wang ◽

Yaohong Zhong ◽

...

Keyword(s):

Rheumatoid Arthritis ◽

Large Scale ◽

Mendelian Randomization ◽

Association Studies ◽

Statistical Significance ◽

Sensitivity Analyses ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Primary Analysis ◽

Genome Wide

Abstract Background: Circulating adipokines levels have been reported to be associated with the risk of rheumatoid arthritis (RA). However, it is still unclear whether these associations are causal or biased by reverse causation or residual confounding. This study aimed to assess potential causal roles of five adipokines (namely, adiponectin, leptin, resistin, chemerin, and retinol-blinding protein 4 [RBP4]) in the occurrence of RA.Methods: We conducted a two-sample Mendelian randomization analysis to investigate these associations. We used summary-level data from genome-wide association studies (GWASs) for adipokines in individuals of European ancestry as the exposure, and a separate large-scale meta-analysis of a GWAS which included 14,361 RA cases and 43,923 controls of European ancestry as the outcome. Genetic variants were selected as instrumental variables if robustly genome-wide significant in their associations with adipokines. The causal effects were estimated using the inverse-variance weighted method in the primary analysis. Sensitivity analyses were performed to warrant that bias due to genetic pleiotropy was unlikely.Results: The circulating resistin was found to be the only adipokinetic factor having statistical significance, with higher levels causally associated with the risk of RA (odds ratio: 1.28; 95% confidence interval: [1.07, 1.53] per unit increase in the natural log-transformed resistin). In contrast, associations of adiponectin, leptin, chemerin, and RBP4 with risk of RA were not statistically significant. The MR assumptions did not seem to be violated. Sensitivity analyses yielded consistent findings.Conclusions: Genetically predicted circulating resistin levels were positively associated with RA risk. Our analysis suggested that resistin may play a notable causal role in RA pathogenesis. It would be beneficial for the development of clinical as well as public health strategies that target appropriate levels of resistin for future RA intervention.

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Causal effect of adiposity on the risk of 19 gastrointestinal diseases: a Mendelian randomization study

10.1101/2021.11.19.21266578 ◽

2021 ◽

Author(s):

Min Seo Kim ◽

Minku Song ◽

Soyeon Kim ◽

Beomsu Kim ◽

Wonseok Kang ◽

...

Keyword(s):

Gastric Cancer ◽

Liver Disease ◽

Mendelian Randomization ◽

Causal Effect ◽

Association Studies ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Alcoholic Fatty Liver ◽

Increased Risk

Objectives: We applied Mendelian randomization (MR) to investigate the causal associations of body mass index (BMI) and waist circumference (WC) with 19 gastrointestinal (GI) disorders. Design: MR study. Setting: The UK Biobank, Genetic Investigation of Anthropometric Traits (GIANT) Consortium, FinnGen consortium, and genome-wide association studies. Participants: Overall, >400,000 UK Biobank participants, >170,000 participants of Finnish descent, and numerous consortia participants with predominantly European ancestry. Interventions: Single-nucleotide polymorphisms associated with BMI and WC were used as instrumental variables to estimate the causal associations with the GI conditions. Main outcome measures: Risk of developing 19 GI diseases Results: After correction for multiple testing (Bonferroni-corrected threshold of P<0.05/19) and testing for consistencies using several MR methods with varying assumptions (inverse variance weighted, weighted median, MR-Egger, and MR-PRESSO), genetically predicted BMI was associated with increased risks of non-alcoholic fatty liver disease (NAFLD), cholecystitis, cholelithiasis, and primary biliary cholangitis. The odds ratio (OR) per one standard deviation (SD) increased in genetically predicted BMI (4.77 kg/m2) from 1.22 (95% confidence interval [CI] 1.12 to 1.34; P<0.0001) for NAFLD to 1.65 (95% CI 1.31 to 2.06; P<0.0001) for cholecystitis. Genetically predicted WC was associated with increased risks of NAFLD, alcoholic liver disease (ALD), cholecystitis, cholelithiasis, colon cancer, and gastric cancer. ALD was associated with WC even after adjustment for alcohol consumption in multivariable MR analysis. The OR per 1 SD increased in genetically predicted WC (12.52 cm) from 1.41 (95% CI 1.17 to 1.70; P=0.0015) for gastric cancer to 1.74 (95% CI 1.21 to 1.78; P<0.0001) for cholelithiasis. Conclusions: Higher BMI and WC are causally associated with an increased risk of GI abnormalities, particularly of hepatobiliary organs (liver, biliary tract, and gallbladder) that are functionally related to fat metabolism. Abdominal obesity measured by WC might be more influential and relevant with a diverse span of GI diseases than BMI, highlighting a possible pathophysiological role of visceral abdominal fats in the development of GI disorders and cancers.

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Genetics of Height and Risk of Atrial Fibrillation: A Mendelian Randomization Study

10.1101/2019.12.23.19015743 ◽

2019 ◽

Author(s):

Michael G. Levin ◽

Renae Judy ◽

Dipender Gill ◽

Marijana Vujkovic ◽

Matthew C. Hyman ◽

...

Keyword(s):

Atrial Fibrillation ◽

Odds Ratio ◽

Mendelian Randomization ◽

Association Studies ◽

Genome Wide Association ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Standard Deviation Increase ◽

Genome Wide ◽

Predicted Height

ABSTRACTObjectiveTo determine whether height has a causal effect on risk of atrial fibrillationDesignMendelian randomization studySettingGenome-wide association studies of height and atrial fibrillation; Penn Medicine BiobankParticipantsMultiethnic (predominantly European ancestry) participants in genome-wide association studies of height (693,529 individuals) and atrial fibrillation (65,446 cases and 522,744 controls); 7,023 Penn Medicine Biobank participants of European ancestryExposuresHeight, cardiometabolic risk factors for atrial fibrillation, and randomly allocated genetic variants strongly associated with these traitsMain outcome measureRisk of atrial fibrillation (measured in odds ratio)ResultsAt the population level, a 1 standard deviation increase in genetically-predicted height was associated with increased odds of AF (Odds ratio [OR] 1.34; 95% Confidence Interval [CI] 1.29 to 1.40; p = 5×10−42). These findings remained consistent in sensitivity analyses that were robust to the presence of pleiotropic variants. Results from analyses considering individual-participant data were similar, even after adjustment for clinical covariates, including left atrial size.ConclusionGenetically predicted height is a positive causal risk factor for AF. This finding raises the possibility of investigating height/growth-related pathways as a means for gaining novel mechanistic insights to atrial fibrillation, as well as incorporating height into population screening strategies for atrial fibrillation.

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Comparison of Two Genome-Wide Association Studies for Heart Rate Response to Exercise from the UK Biobank

10.1101/2021.07.07.21259806 ◽

2021 ◽

Author(s):

Abhinav Thakral ◽

Andrew D Paterson

Keyword(s):

Heart Rate ◽

Association Studies ◽

Genome Wide Association ◽

European Ancestry ◽

Genome Wide Association Studies ◽

Uk Biobank ◽

Post Exercise ◽

Genome Wide ◽

The Difference ◽

The Uk

The short-term changes in heart rate (HR) during and after exercise are important physiologic traits mediated via the autonomic nervous system. Variations in these traits are associated with mortality from cardiovascular causes. We conducted a systematic review of genome-wide association studies for these traits (with >10,000 participants) with the aim of comparing Polygenic Risk Scores (PRS) from different studies. Additionally, we applied the STrengthening of Reporting of Genetic Association Studies (STREGA) statement for assessing the completeness of reporting of evidence. Our systematic search yielded two studies (Verweij et al. and Ramirez et al.) that met our inclusion criteria. Both were conducted on the UK Biobank. Both defined their exercise traits as the difference between resting HR and the maximum HR during exercise. Their recovery traits were defined differently. Verweij et al. defined 5 recovery traits as the differences between the peak HR during exercise and the HRs at 10-50 sec post exercise cessation. Ramirez et al. defined their recovery trait as the difference between peak HR during exercise and the minimum HR during the minute post exercise cessation. While Ramirez et al. divided their sample into discovery and replication subsets, Verweij et al. analyzed the whole sample together. In terms of results, there were several common SNPs identified between studies and traits. There was evidence for the phenomenon of winners curse operating for a SNP from the Ramirez studys HR recovery analysis. Many of the SNPs were mutually exclusive between the studies. However, there was a good agreement of PRS from the studies. The differences in the results could be attributed to the different exclusion criteria, analytic approaches, and definitions of traits used. Both studies had an under-representation of individuals of non-European ancestry compared to those of European ancestry. Further studies with proportionate representation of individuals of all ancestries would help address this gap.

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Genetic Contribution of Endometriosis to the Risk of Developing Hormone-Related Cancers

International Journal of Molecular Sciences ◽

10.3390/ijms22116083 ◽

2021 ◽

Vol 22 (11) ◽

pp. 6083

Author(s):

Aintzane Rueda-Martínez ◽

Aiara Garitazelaia ◽

Ariadna Cilleros-Portet ◽

Sergi Marí ◽

Rebeca Arauzo ◽

...

Keyword(s):

Mendelian Randomization ◽

Clear Cell ◽

Association Studies ◽

Epidemiological Data ◽

Epidemiological Studies ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Genomic Analyses ◽

Gynecological Disorder ◽

Robust Evidence

Endometriosis is a common gynecological disorder that has been associated with endometrial, breast and epithelial ovarian cancers in epidemiological studies. Since complex diseases are a result of multiple environmental and genetic factors, we hypothesized that the biological mechanism underlying their comorbidity might be explained, at least in part, by shared genetics. To assess their potential genetic relationship, we performed a two-sample mendelian randomization (2SMR) analysis on results from public genome-wide association studies (GWAS). This analysis confirmed previously reported genetic pleiotropy between endometriosis and endometrial cancer. We present robust evidence supporting a causal genetic association between endometriosis and ovarian cancer, particularly with the clear cell and endometrioid subtypes. Our study also identified genetic variants that could explain those associations, opening the door to further functional experiments. Overall, this work demonstrates the value of genomic analyses to support epidemiological data, and to identify targets of relevance in multiple disorders.

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