scholarly journals ADHD genetic liability and physical health outcomes - A two-sample Mendelian randomization study

2019 ◽  
Author(s):  
Beate Leppert ◽  
Lucy Riglin ◽  
Christina Dardani ◽  
Ajay Thapar ◽  
James R Staley ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Childhood Obesity ◽  
Health Outcomes ◽  
Physical Health ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Genetic Liability ◽  
Physical Health Outcomes ◽  
Artery Disease

AbstractObjectiveAttention-deficit/hyperactivity disorder (ADHD) has been associated with a broad range of physical health problems, including cardiometabolic, neurological and immunological conditions. Determining whether ADHD plays a causal role in these associations is of great importance for treatment and prevention but also because comorbid health problems further increase the serious social and economic impacts of ADHD on individuals and their families.MethodsWe used a two-sample Mendelian randomization (MR) approach to examine the causal relationships between genetic liability for ADHD and previously implicated physical health conditions. 11 genetic variants associated with ADHD were obtained from the latest summary statistics. Consistent effects obtained from IVW, weighted median and MR Egger methods were taken forward for sensitivity analysis, including bidirectional MR and multivariable MR (MVMR).ResultsWe found evidence of a causal effect of genetic liability for ADHD on childhood obesity (OR:1.29 (95% CI:1.02,1.63)) and coronary artery disease (CAD) (OR:1.11 (95% CI:1.03,1.19)) with consistent results across different MR approaches. There was further evidence for a bidirectional relationship between genetic liability for ADHD and childhood obesity. The effect of genetic liability for ADHD on CAD was independent of smoking heaviness but was attenuated when simultaneously controlling for childhood obesity. There was little evidence for a causal effect on other cardiometabolic, immunological, neurological disorders and lung cancer.ConclusionOur findings strengthen the argument for early treatment and support for children with ADHD and their families and especially promoting physical activity and providing them with dietary advice to reduce future risk for developing CAD.Key MessageEpidemiological studies have reported observational associations between ADHD and adult onset physical health outcomes.Mendelian Randomization can be used to assess causal associations for ADHD on health outcomes that would traditionally require long term follow-up and may suffer confoundingWe found that genetic liability for ADHD was associated with coronary artery disease and there was evidence for a bidirectional association between genetic liability for ADHD and childhood obesityMultivariable mendelian randomization suggests that the link between genetic liability and coronary artery disease might partially act through childhood obesity but was independent of smoking heavinessThere was little evidence of a causal of ADHD on other cardiometabolic and immunological diseases.

scholarly journals The Effect of ADHD on Physical Health Outcomes - A Two-Sample Mendelian Randomization Study

2020 ◽  
Author(s):  
Beate Leppert ◽  
Lucy Riglin ◽  
Robyn E Wootton ◽  
Christina Dardani ◽  
Ajay Thapar ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Childhood Obesity ◽  
Physical Health ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Neurological Diseases ◽  
Health Problems ◽  
Physical Health Problems ◽  
Artery Disease

Abstract Attention-deficit/hyperactivity disorder (ADHD) is associated with a broad range of physical health problems. Using different research designs to test whether ADHD has a causal role in these associations is of great importance because comorbid health problems further increase the serious social and economic impacts of ADHD. We used two-sample Mendelian randomization (MR) to infer causal relationships between ADHD and previously implicated physical health conditions. Different MR methods were used to test the robustness and plausibility of our findings. Consistent findings were taken forward for bidirectional and multivariable MR. We found evidence of ADHD having a causal effect on childhood obesity (OR (Odds Ratio):1.29 (95% CI (Confidence Intervals):1.02,1.63)) and coronary artery disease (OR:1.11(95% CI:1.03,1.19)) with consistent results across MR approaches. There was further MR evidence for a bidirectional relationship between ADHD and childhood obesity. The relationship with coronary artery disease attenuated when controlling for childhood obesity. There was little evidence for inferring a causal effect on other cardiometabolic, autoimmune, allergic and neurological diseases. Our findings strengthen the argument for effective treatment of children with ADHD. It also suggests that clinicians who manage ADHD need to be aware of the risk of childhood obesity to reduce future risks of coronary artery disease.

scholarly journals Mendelian randomization analyses reveal mediating factors of the causal effect of height on coronary artery disease

2021 ◽  
Author(s):  
Daniel Hui ◽  
Christopher S. Thom ◽  
Kimberly Lorenz ◽  
Scott M. Damrauer ◽  
Themistocles L. Assimes ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Lung Function ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Multivariable Analysis ◽  
Inverse Correlation ◽  
Artery Disease ◽  
Cad Risk

An inverse correlation between stature and risk of coronary artery disease (CAD) has been observed in several epidemiologic studies, and recent Mendelian randomization (MR) experiments have suggested evidence that this association may be causal. However, the extent to which the effect estimated by MR can be explained by established cardiovascular risk factors is unclear, with a recent report suggesting that lung function traits could fully explain the height-CAD effect. To clarify this relationship, we utilized the largest set of genetic instruments for human stature to date, comprising >2,000 genetic variants for height and CAD. In univariable analysis, we confirmed that a one standard deviation decrease in height (~6.5 cm) was associated with a 12.0% increase in the risk of CAD, consistent with previous reports. In multivariable analysis accounting for effects from up to 12 established risk factors, we observed a >3-fold attenuation in the causal effect of height on CAD susceptibility (3.7%, p = 2.1x10-2). We observed minimal effects of lung function traits on CAD risk in our analyses, indicating that these traits are unlikely to explain the residual association between height and CAD risk. In sum, these results suggest that height does not add meaningful clinical impact on CAD risk prediction beyond established risk factors.

scholarly journals A Mendelian randomization study of the role of lipoprotein subfractions in coronary artery disease

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Qingyuan Zhao ◽  
Jingshu Wang ◽  
Zhen Miao ◽  
Nancy R Zhang ◽  
Sean Hennessy ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Particle Size ◽  
Coronary Artery ◽  
Protective Effect ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Particle Diameter ◽  
Lipoprotein Subfractions ◽  
Artery Disease

Recent genetic data can offer important insights into the roles of lipoprotein subfractions and particle sizes in preventing coronary artery disease (CAD), as previous observational studies have often reported conflicting results. We used the LD score regression to estimate the genetic correlation of 77 subfraction traits with traditional lipid profile and identified 27 traits that may represent distinct genetic mechanisms. We then used Mendelian randomization (MR) to estimate the causal effect of these traits on the risk of CAD. In univariable MR, the concentration and content of medium high-density lipoprotein (HDL) particles showed a protective effect against CAD. The effect was not attenuated in multivariable analyses. Multivariable MR analyses also found that small HDL particles and smaller mean HDL particle diameter may have a protective effect. We identified four genetic markers for HDL particle size and CAD. Further investigations are needed to fully understand the role of HDL particle size.

scholarly journals MR-Clust: Clustering of genetic variants in Mendelian randomization with similar causal estimates

2019 ◽  
Author(s):  
Christopher N Foley ◽  
Paul D W Kirk ◽  
Stephen Burgess
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Risk Factor ◽  
Coronary Artery ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Disease Risk ◽  
Causal Effect ◽  
Coronary Artery Disease Risk ◽  
Artery Disease

AbstractMotivationMendelian randomization is an epidemiological technique that uses genetic variants as instrumental variables to estimate the causal effect of a risk factor on an outcome. We consider a scenario in which causal estimates based on each variant in turn differ more strongly than expected by chance alone, but the variants can be divided into distinct clusters, such that all variants in the cluster have similar causal estimates. This scenario is likely to occur when there are several distinct causal mechanisms by which a risk factor influences an outcome with different magnitudes of causal effect. We have developed an algorithm MR-Clust that finds such clusters of variants, and so can identify variants that reflect distinct causal mechanisms. Two features of our clustering algorithm are that it accounts for uncertainty in the causal estimates, and it includes ‘null’ and ‘junk’ clusters, to provide protection against the detection of spurious clusters.ResultsOur algorithm correctly detected the number of clusters in a simulation analysis, outperforming the popular Mclust method. In an applied example considering the effect of blood pressure on coronary artery disease risk, the method detected four clusters of genetic variants. A hypothesis-free search suggested that variants in the cluster with a negative effect of blood pressure on coronary artery disease risk were more strongly related to trunk fat percentage and other adiposity measures than variants not in this cluster.Availability and ImplementationMR-Clust can be downloaded from https://github.com/cnfoley/[email protected] or [email protected] InformationSupplementary Material is included in the submission.

scholarly journals MR-Clust: clustering of genetic variants in Mendelian randomization with similar causal estimates

2020 ◽  
Author(s):  
Christopher N Foley ◽  
Amy M Mason ◽  
Paul D W Kirk ◽  
Stephen Burgess
Keyword(s):  
Blood Pressure ◽  
Coronary Artery Disease ◽  
Risk Factor ◽  
Coronary Artery ◽  
Genetic Variants ◽  
Mendelian Randomization ◽  
Disease Risk ◽  
Causal Effect ◽  
Coronary Artery Disease Risk ◽  
Artery Disease

Abstract Motivation Mendelian randomization is an epidemiological technique that uses genetic variants as instrumental variables to estimate the causal effect of a risk factor on an outcome. We consider a scenario in which causal estimates based on each variant in turn differ more strongly than expected by chance alone, but the variants can be divided into distinct clusters, such that all variants in the cluster have similar causal estimates. This scenario is likely to occur when there are several distinct causal mechanisms by which a risk factor influences an outcome with different magnitudes of causal effect. We have developed an algorithm MR-Clust that finds such clusters of variants, and so can identify variants that reflect distinct causal mechanisms. Two features of our clustering algorithm are that it accounts for differential uncertainty in the causal estimates, and it includes ‘null’ and ‘junk’ clusters, to provide protection against the detection of spurious clusters. Results Our algorithm correctly detected the number of clusters in a simulation analysis, outperforming methods that either do not account for uncertainty or do not include null and junk clusters. In an applied example considering the effect of blood pressure on coronary artery disease risk, the method detected four clusters of genetic variants. A post hoc hypothesis-generating search suggested that variants in the cluster with a negative effect of blood pressure on coronary artery disease risk were more strongly related to trunk fat percentage and other adiposity measures than variants not in this cluster. Availability and implementation MR-Clust can be downloaded from https://github.com/cnfoley/mrclust. Supplementary information Supplementary data are available at Bioinformatics online.

Negative Effects of Age at Menarche on Risk of Cardiometabolic Diseases in Adulthood: A Mendelian Randomization Study

2019 ◽  
Vol 105 (2) ◽  
pp. 515-522 ◽  
Author(s):  
Min Cao ◽  
Bin Cui
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Meta Analysis ◽  
Age At Menarche ◽  
Model Assessment ◽  
Cardiometabolic Diseases ◽  
Genome Wide ◽  
Artery Disease

Abstract Context Observational studies have demonstrated that early menarche is associated with cardiometabolic diseases, but confounding factors make it difficult to infer causality. Objective We used Mendelian randomization (MR) to examine whether age at menarche (AAM) is causally associated with type 2 diabetes (T2D), coronary artery disease (CAD) and cardiometabolic traits. Design and Methods A 2-sample MR analysis was conducted using genome-wide association study (GWAS) summary statistics from the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) consortium (n = 159 208) for T2D and the Coronary Artery Disease Genome-wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics (CARDIoGRAMplusC4D) consortium (n = 184 305) for CAD. We used 122 instrumental variables (IVs) extracted from a published GWAS meta-analysis incorporating 182 416 women to determine the causal effect of AAM on cardiometabolic diseases, treating childhood and adult body mass index (BMI) as the confounders. Sensitivity analyses were also performed to detect the pleiotropy of the IVs. Results Employing the MR approach, we found that later AAM was associated with decreased risk of CAD (OR, 0.92 [95% CI, 0.88-0.96]; P = 2.06 × 10–4) in adults, as well as lower blood levels of log fasting insulin, log homeostatic model assessment of insulin resistance (HOMA-IR), log HOMA of β-cell function (HOMA-B), triglycerides, and diastolic blood pressure, but higher blood level of high-density lipoprotein. However, the associations were substantially attenuated after excluding BMI-related variants. MR analyses provide little evidence on the causal effect between AAM and T2D. Conclusions Our findings showed that AAM did not appear to have a causal effect on the risk of cardiometabolic diseases in adult life, as their associations observed in epidemiological studies might be largely mediated through excessive adiposity. We propose adiposity might be a primary target in future intervention strategy.

scholarly journals Genetics of Smoking and Risk of Atherosclerotic Cardiovascular Diseases: A Mendelian Randomization Study

2020 ◽  
Author(s):  
Michael G. Levin ◽  
Derek Klarin ◽  
Themistocles L. Assimes ◽  
Matthew S. Freiberg ◽  
Erik Ingelsson ◽  
...  
Keyword(s):  
Risk Factors ◽  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Peripheral Artery Disease ◽  
Mendelian Randomization ◽  
Large Artery ◽  
Peripheral Artery ◽  
Genetic Liability ◽  
Genome Wide ◽  
Artery Disease

ABSTRACTImportanceSmoking is associated with atherosclerotic cardiovascular disease, but the relative contribution to each subtype (coronary artery disease [CAD], peripheral artery disease [PAD], and large-artery stroke) remains less well understood.ObjectiveTo determine the effect of smoking on risk of coronary artery disease, peripheral artery disease, and large-artery stroke.DesignMendelian randomization study using summary statistics from genome-wide associations of smoking (up to 462,690 individuals), coronary artery disease (up to 60,801 cases, 123,504 controls), peripheral artery disease (up to 24,009 cases, 150,983 controls), and large-artery stroke (up to 4,373 cases, 406,111 controls)SettingPopulation-based study of primarily European-ancestry individualsParticipantsParticipants in genome-wide association studies of smoking, coronary artery disease, peripheral artery disease, and stroke.ExposuresGenetic liability to smoking defined by lifetime smoking index: an integrated measure of smoking status, age at initiation, age at cessation, number of cigarettes smoked per day, and declining effect of smoking on health outcomes).Main Outcome MeasureRisk of coronary artery disease, peripheral artery disease, and large-artery stroke.ResultsGenetic liability to smoking was associated with increased risk of PAD (OR 2.13; 95% CI 1.78-2.56; P = 3.6 × 10−16), CAD (OR 1.48; 95% CI 1.25-1.75; P = 4.4 × 10−6), and stroke (OR 1.4; 95% CI 1.02-1.92; P = 0.036). Risk of PAD in smokers was greater than risk of large-artery stroke (pdifference = 0.025) or CAD (pdifference = 0.0041). The effect of smoking on ASCVD remained independent from the effects of smoking on traditional cardiovascular risk factors.Conclusions and RelevanceGenetic liability to smoking is a strong, causal risk factor for CAD, PAD, and stroke, although the effect of smoking is strongest for PAD. The effect of smoking is independent of traditional cardiovascular risk factors.

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