scholarly journals TU35. INFLAMMATION AND OVERWEIGHT AS PUTATIVE RISK FACTORS FOR DEPRESSION: A MULTIVARIABLE MENDELIAN RANDOMIZATION STUDY

2021 ◽  
Vol 51 ◽  
pp. e113
Author(s):  
Vasileios Karageorgiou ◽  
Francesco Casanova ◽  
Jessica O'Loughlin ◽  
Jack Bowden ◽  
Jess Tyrrell
Keyword(s):  
Risk Factors ◽  
Mendelian Randomization

scholarly journals A Mendelian randomization analysis of the relationship between cardioembolic risk factors and ischemic stroke

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Danyang Tian ◽  
Linjing Zhang ◽  
Zhenhuang Zhuang ◽  
Tao Huang ◽  
Dongsheng Fan
Keyword(s):  
Risk Factors ◽  
Ischemic Stroke ◽  
Mendelian Randomization ◽  
P Wave ◽  
Cardioembolic Stroke ◽  
Large Artery ◽  
Weighted Analysis ◽  
Inverse Variance ◽  
Weighted Median ◽  
Genetically Determined

AbstractObservational studies have shown that several risk factors are associated with cardioembolic stroke. However, whether such associations reflect causality remains unknown. We aimed to determine whether established and provisional cardioembolic risk factors are causally associated with cardioembolic stroke. Genetic instruments for atrial fibrillation (AF), myocardial infarction (MI), electrocardiogram (ECG) indices and N-terminal pro-brain natriuretic peptide (NT-pro BNP) were obtained from large genetic consortiums. Summarized data of ischemic stroke and its subtypes were extracted from the MEGASTROKE consortium. Causal estimates were calculated by applying inverse-variance weighted analysis, weighted median analysis, simple median analysis and Mendelian randomization (MR)-Egger regression. Genetically predicted AF was significantly associated with higher odds of ischemic stroke (odds ratio (OR): 1.20, 95% confidence intervals (CI): 1.16–1.24, P = 6.53 × 10–30) and cardioembolic stroke (OR: 1.95, 95% CI: 1.85–2.06, P = 8.81 × 10–125). Suggestive associations were found between genetically determined resting heart rate and higher odds of ischemic stroke (OR: 1.01, 95% CI: 1.00–1.02, P = 0.005), large-artery atherosclerotic stroke (OR: 1.02, 95% CI: 1.00–1.04, P = 0.026) and cardioembolic stroke (OR: 1.02, 95% CI: 1.00–1.04, P = 0.028). There was no causal association of P‐wave terminal force in the precordial lead V1 (PTFVI), P-wave duration (PWD), NT-pro BNP or PR interval with ischemic stroke or any subtype.

scholarly journals Evaluating the effects of alcohol and tobacco use on cardiovascular disease using multivariable Mendelian randomization

2019 ◽  
Author(s):  
Daniel B. Rosoff ◽  
George Davey Smith ◽  
Nehal Mehta ◽  
Toni-Kim Clarke ◽  
Falk W. Lohoff
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Alcohol Use ◽  
Tobacco Use ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Cvd Risk ◽  
Increased Risk

ABSTRACTAlcohol and tobacco use, two major modifiable risk factors for cardiovascular disease (CVD), are often consumed together. Using large publicly available genome-wide association studies (results from > 940,000 participants), we conducted two-sample multivariable Mendelian randomization (MR) to simultaneously assess the independent effects of alcohol and tobacco use on CVD risk factors and events. We found genetic instruments associated with increased alcohol use, controlling for tobacco use, associated with increased high-density-lipoprotein-cholesterol (HDL-C), decreased triglycerides, but not with coronary heart disease (CHD), myocardial infarction (MI), nor stroke; and instruments for increased tobacco use, controlling for alcohol use, associated with decreased HDL-C, increased triglycerides, and increased risk of CHD and MI. Exploratory analysis found associations with HDL-C, LDL-C, and intermediate-density-lipoprotein metabolites. Consistency of results across complementary methods accommodating different MR assumptions strengthened causal inference, providing strong genetic evidence for the causal effects of modifiable lifestyle risk factors on CVD risk.

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 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.

Mendelian Randomization Analysis as a Tool to Gain Insights into Causes of Diseases: A Primer

2021 ◽  
pp. ASN.2020121760
Author(s):  
Adrienne Tin ◽  
Anna Köttgen
Keyword(s):  
Risk Factors ◽  
Chronic Kidney Disease ◽  
Kidney Disease ◽  
Mendelian Randomization ◽  
Mr Studies ◽  
Causal Relationships ◽  
Omics Technologies ◽  
Basic Concepts ◽  
Traditional Risk Factors ◽  
Randomization Analysis

Many Mendelian randomization (MR) studies have recently been published, with inferences on the causal relationships between risk factors and diseases that have potential implications for clinical research. In nephrology, MR methods have been applied to investigate potential causal relationships of traditional risk factors, lifestyle factors, and biomarkers from omics technologies with kidney function or chronic kidney disease. This primer summarizes the basic concepts of MR studies, highlighting methods employed in recent applications, and emphasizes key elements in conducting and reporting of MR studies that are important for interpreting the results.

A Mendelian randomization analysis of known and putative risk factors for pancreatic cancer

Pancreatology ◽  
2019 ◽  
Vol 19 ◽  
pp. S97-S98
Author(s):  
Ye Lu ◽  
Manuel Gentiluomo ◽  
Luca Morelli ◽  
Ofure Obazee ◽  
Federico Canzian ◽  
...  
Keyword(s):  
Risk Factors ◽  
Pancreatic Cancer ◽  
Mendelian Randomization ◽  
Mendelian Randomization Analysis ◽  
Randomization Analysis

scholarly journals CAUSES OF FRAILTY: GENETIC ANALYSIS IN 164,000 UK BIOBANK PARTICIPANTS

2019 ◽  
Vol 3 (Supplement_1) ◽  
pp. S222-S222
Author(s):  
Janice Atkins ◽  
Luke C Pilling ◽  
Dylan Williams ◽  
Juulia Jylhävä ◽  
David Melzer
Keyword(s):  
Risk Factors ◽  
Cardiovascular Disease ◽  
Mendelian Randomization ◽  
Frailty Index ◽  
Geriatric Syndrome ◽  
Uk Biobank ◽  
Genomewide Association Study ◽  
European Descent ◽  
Ongoing Work

Abstract Frailty is an important and common geriatric syndrome, yet the mechanisms are multifactorial and not well understood. The Frailty Index (FI) is based on the Rockwood Index for accumulation of deficits, and we aimed to use genetics to gain mechanistic insights for interventions to prevent and delay frailty in older people. We performed a genomewide association study in 60 to 70 year old UK Biobank participants of European descent (n=164,610). We identified 26 independent genetic signals at 24 loci associated with the FI. Several of these signals have previously been associated with traits such as cardiovascular disease, intelligence, and educational attainment, but 6 of the signals appear to be novel. We will also present the results of ongoing work both to identify causal risk factors for FI using Mendelian randomization methods, and replication and functional follow-up in the TwinGene cohort, at the meeting.

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