Abstract 15527: Association Between Adrenergic Receptor Modulation and the Risk of Heart Failure: A Two-sample Mendelian Randomization Study

Circulation ◽  
2020 ◽  
Vol 142 (Suppl_3) ◽  
Author(s):  
Claire Baudier ◽  
Françoise Fougerousse ◽  
Amand F Schmidt ◽  
Folkert W Asselbergs ◽  
Mickael Guedj ◽  
...  
Keyword(s):  
Heart Failure ◽  
Mendelian Randomization ◽  
Association Studies ◽  
P Value ◽  
Sample Population ◽  
Genome Wide Association Studies ◽  
Receptor Modulation ◽  
Genome Wide ◽  
Genes Encoding ◽  
The Impact

Introduction: The impact of the sympathetic nervous system (SNS) modulation on the risk of heart failure (HF) outside of ß1 receptor blockade remains controversial. Methods: We performed a two-sample Mendelian randomization (MR) study using common independent genetic variants located in the cis region of genes encoding the 9 SNS receptors (α1 A, B, D, α2 A, B, C and ß 1, 2 and 3) that were associated at genome-wide significance (P-value ≤ 5х10 –8 ) with blood pressure (BP) and/or heart rate (HR) in published genome-wide association studies (GWAS) available for BP and HR. Variants were filtered out by Linkage Disequilibrium clumping (LD R 2 > 0.1) and based on their minor allele frequency (MAF < 0.01). The effects of selected variants on the genetic risk of HF were extracted from a GWAS of HF from the HERMES consortium, based on a non-overlapping sample population. MR estimates were obtained using the Wald estimator for a single variant or the inverse variance weighted method for multiple variants. Results: 542,362 controls and 40,805 HF cases were evaluated. Independent variants in genes encoding 4 SNS receptors associated with BP or HR were identified as follows: α1A (diastolic BP), α2B (diastolic BP and HR), ß1 and ß2 (diastolic and systolic BP). MR analysis of α1A and ß1, weighted by their effects on diastolic BP, estimated an association with a higher risk of HF, while α2B variants were associated with a lower risk. We found no evidence for an effect of ß2. A similar relationship with systolic BP was found for ß1 and ß2. HR increasing effect of α2B variants was associated with a decreased odd of HF. Conclusions: Mindful of pleiotropic effects, these findings are consistent with the known benefits of ß1 blockade in HF and support a similar role for α1A blockade; conversely, they suggest a detrimental lowering effect of BP and HR through α2B modulation that deserves further studies. No evidence for a role of ß2 in HF was found.

scholarly journals What multiple Mendelian randomization approaches reveal about obesity and gout

2021 ◽  
Author(s):  
Charleen D. Adams ◽  
Brian Boutwell
Keyword(s):  
Observational Studies ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Hdl Cholesterol ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Cholesterol Levels ◽  
Genome Wide ◽  
The Impact ◽  
Apparent Ability

Background/Objectives: Gout is a painful arthritic disease. A robust canon of observational literature suggests strong relationships between obesity, high urate levels, and gout. But findings from observational studies can be fraught with confounding and reverse causation. They can conflict with findings from Mendelian randomization (MR), designed to tackle these biases. We aimed to determine whether the relationships between obesity, higher urate levels, and gout were causal using multiple MR approaches, including an investigation of how other closely related traits, LDL, HDL cholesterol, and triglyceride levels fit into the picture. Subjects/Methods: Summary results from genome-wide association studies of the five above-mentioned traits were extracted and used to perform two-sample (univariable, multivariable, and two-step) MR and MR mediation analysis. Results Obesity increased urate (beta=0.127; 95% CI=0.098, 0.157; P-value=1.2E-17) and triglyceride levels (beta=0.082; 95% CI=0.065, 0.099; P-value=1.2E-21) and decreased HDL cholesterol levels (beta=-0.083; 95% CI=-0.101, -0.065; P-value=2.5E-19). Higher triglyceride levels increased urate levels (beta=0.198; 95% CI=0.146, 0.251; P-value=8.9E-14) and higher HDL levels decreased them (beta=-0.109; 95% CI=-0.148, -0.071; P-value=2.7E-08). Higher urate levels (OR=1.030; 95% CI=1.028, 1.032; P-value=1.1E-130) and obesity caused gout (OR=1.003; 95% CI=1.001, 1.004; P-value=1.3E-04). The mediation MR of obesity on gout with urate levels as a mediator revealed, however, that essentially all of the effect of obesity on gout is mediated through urate. The impact of obesity on LDL cholesterol was null (beta=-0.011; 95% CI=-0.030, 0.008; P-value=2.6E-01), thus it was not included in the multivariable MR. The multivariable MR of obesity, HDL cholesterol, and triglycerides on urate levels revealed that obesity has an effect on urate levels even when accounting for HDL cholesterol and triglyceride levels. Conclusions: Obesity impacts gout indirectly by influencing urate levels and possibly other traits, such as triglycerides, that increase urate levels. Obesity's impact on urate is exacerbated by its apparent ability to decrease HDL cholesterol. 

scholarly journals The putative causal effect of type 2 diabetes in risk of cataract: a Mendelian randomization study in East Asian

2021 ◽  
Author(s):  
Haoyang Zhang ◽  
Xuehao Xiu ◽  
Angli Xue ◽  
Yuedong Yang ◽  
Yuanhao Yang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Correlation ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Population Based ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractBackgroundThe epidemiological association between type 2 diabetes and cataract has been well-established. However, it remains unclear whether the two diseases share a genetic basis, and if so, whether this reflects a causal relationship.MethodsWe utilized East Asian population-based genome-wide association studies (GWAS) summary statistics of type 2 diabetes (Ncase=36,614, Ncontrol=155,150) and cataract (Ncase=24,622, Ncontrol=187,831) to comprehensively investigate the shared genetics between the two diseases. We performed 1. linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (ρ-HESS) to estimate the genetic correlation and local genetic correlation between type 2 diabetes and cataract; 2. multiple Mendelian randomization (MR) analyses to infer the putative causality between type 2 diabetes and cataract; and 3. Summary-data-based Mendelian randomization (SMR) to identify candidate risk genes underling the causality.ResultsWe observed a strong genetic correlation (rg=0.58; p-value=5.60×10−6) between type 2 diabetes and cataract. Both ρ-HESS and multiple MR methods consistently showed a putative causal effect of type 2 diabetes on cataract, with estimated liability-scale MR odds ratios (ORs) at around 1.10 (95% confidence interval [CI] ranging from 1.06 to 1.17). In contrast, no evidence supports a causal effect of cataract on type 2 diabetes. SMR analysis identified two novel genes MIR4453HG (βSMR=−0.34, p-value=6.41×10−8) and KCNK17 (βSMR=−0.07, p-value=2.49×10−10), whose expression levels were likely involved in the putative causality of type 2 diabetes on cataract.ConclusionsOur results provided robust evidence supporting a causal effect of type 2 diabetes on the risk of cataract in East Asians, and posed new paths on guiding prevention and early-stage diagnosis of cataract in type 2 diabetes patients.Key MessagesWe utilized genome-wide association studies of type 2 diabetes and cataract in a large Japanese population-based cohort and find a strong genetic overlap underlying the two diseases.We performed multiple Mendelian randomization models and consistently disclosed a putative causal effect of type 2 diabetes on the development of cataract.We revealed two candidate genes MIR4453HG and KCNK17 whose expression levelss are likely relevant to the causality between type 2 diabetes and cataract.Our study provided theoretical fundament at the genetic level for improving early diagnosis, prevention and treatment of cataract in type 2 diabetes patients in clinical practice

scholarly journals Association Between Covid-19 and Heart Failure: Evidence From a Two-sample Mendelian Randomization Study

2021 ◽  
Author(s):  
Huachen Wang ◽  
Zheng Guo ◽  
Yulu Zheng ◽  
Bing Chen
Keyword(s):  
Heart Failure ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Meta Analysis ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Reverse Causality ◽  
Genome Wide ◽  
Weighted Median

Abstract Background: Current research observing inconsistent associations of Corona Virus Disease 2019 (COVID-19) with heart failure (HF) are prone to bias based on reverse causality and residual confounding factors. Our aim was to apply a two-sample Mendelian randomization method to investigate whether COVID-19 has a causal effect on HF. Methods: Twenty-nine single nucleotide polymorphisms (SNPs) were proposed as candidate instrumental variables (IVs). A total of 3,523 patients with COVID-19 and 36,634 control participants were included in the genome-wide meta-analysis. We analyzed the largest genome-wide association studies (GWAS) meta-analysis of heart failure in individuals of European ancestry consisting of 47,309 patients with HF and 930,014 controls. The inverse variance weighted (IVW), the Mendelian randomization-Egger (MR-Egger) regression, the simple mode (SM), weighted median, and weighted mode were utilized for the MR analysis to test the stability and a causal effect. Results: The IVW, MR-Egger regression, SM, weighted median and weighted mode demonstrated there was no association between the genetically predicted COVID-19 infection and HF risk (OR, 1.004; 95%CI, 0.994-1.014; P=0.467; OR, 1.008; 95%CI, 0.996-1.019; P=0.218; OR, 0.968; 95%CI, 0.924-1.015; P=0.186; OR, 1.001; 95%CI, 0.988-1.014; P=0.881; OR, 1.001; 95%CI, 0.989-1.014; P=0.836; respectively). Conclusion: This two-sample Mendelian randomization analysis provided no evidence to sustain the causality of COVID-19 on HF.

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

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.

scholarly journals Genomics-driven drug discovery based on disease-susceptibility genes

2021 ◽  
Vol 41 (1) ◽  
Author(s):  
Kyuto Sonehara ◽  
Yukinori Okada
Keyword(s):  
Drug Discovery ◽  
Drug Targets ◽  
Disease Susceptibility ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Drug Repurposing ◽  
Susceptibility Genes ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Disease Associations

AbstractGenome-wide association studies have identified numerous disease-susceptibility genes. As knowledge of gene–disease associations accumulates, it is becoming increasingly important to translate this knowledge into clinical practice. This challenge involves finding effective drug targets and estimating their potential side effects, which often results in failure of promising clinical trials. Here, we review recent advances and future perspectives in genetics-led drug discovery, with a focus on drug repurposing, Mendelian randomization, and the use of multifaceted omics data.

Stroke Genetics: Turning Discoveries into Clinical Applications

Stroke ◽  
2021 ◽  
Author(s):  
Martin Dichgans ◽  
Nathalie Beaufort ◽  
Stephanie Debette ◽  
Christopher D. Anderson
Keyword(s):  
Mendelian Randomization ◽  
Association Studies ◽  
Clinical Applications ◽  
Risk Scores ◽  
Genome Wide Association Studies ◽  
Neuroprotective Agents ◽  
Experimental Systems ◽  
Genome Wide ◽  
Rapid Pace

The field of medical and population genetics in stroke is moving at a rapid pace and has led to unanticipated opportunities for discovery and clinical applications. Genome-wide association studies have highlighted the role of specific pathways relevant to etiologically defined subtypes of stroke and to stroke as a whole. They have further offered starting points for the exploration of novel pathways and pharmacological strategies in experimental systems. Mendelian randomization studies continue to provide insights in the causal relationships between exposures and outcomes and have become a useful tool for predicting the efficacy and side effects of drugs. Additional applications that have emerged from recent discoveries include risk prediction based on polygenic risk scores and pharmacogenomics. Among the topics currently moving into focus is the genetics of stroke outcome. While still at its infancy, this field is expected to boost the development of neuroprotective agents. We provide a brief overview on recent progress in these areas.

PSVIII-10 Genome-wide CNV analysis unravels a deletion associated with parasite resistance in Florida native sheep

2021 ◽  
Vol 99 (Supplement_3) ◽  
pp. 243-244
Author(s):  
Brittany N Diehl ◽  
Andres A Pech-Cervantes ◽  
Thomas H Terrill ◽  
Ibukun M Ogunade ◽  
Owen Rae ◽  
...  
Keyword(s):  
Copy Number ◽  
Association Studies ◽  
Chromosome 21 ◽  
Trend Test ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Parasite Resistance ◽  
Association Testing ◽  
Genome Wide ◽  
Native Sheep

Abstract Florida Native sheep is an indigenous breed from Florida and expresses superior parasite resistance. Previous candidate and genome wide association studies with Florida Native sheep have identified single nucleotide polymorphisms with additive and non-additive effects associated with parasite resistance. However, the role of other potential DNA variants, such as copy number variants (CNVs), controlling this complex trait have not been evaluated. The objective of the present study was to investigate the importance of CNVs on resistance to natural Haemonchus contortus infections in Florida Native sheep. A total of 200 sheep were evaluated in the present study. Phenotypic records included fecal egg count (FEC, eggs/gram), FAMACHA score, and packed cell volume (PCV, %). Sheep were genotyped using the GGP Ovine 50K SNP chip. The copy number analysis was used to identify CNVs using the univariate method. A total of 170 animals with CNVs and phenotypic data were used for the association testing. Association tests were carried out using single linear regression and Principal Component Analysis (PCA) correction to identify CNVs associated with FEC, FAMACHA, and PCV. To confirm our results, a second association testing using the correlation-trend test with PCA correction was performed. Significant CNVs were detected when their adjusted p-value was &lt; 0.05 after FDR correction. A deletion CNV in chromosome 21 was associated with FEC. This DNA variant was located in intron 2 of RAB3IL gene and overlapped a QTL associated with changes in eosinophil number. Our study demonstrated for the first time that CNVs could be potentially involved with parasite resistance in this heritage sheep breed.

Abstract 233: Isoproterenol-induced Cardiac Hypertrophy And Failure In Mice: Gene Network Modeling

2013 ◽  
Vol 113 (suppl_1) ◽  
Author(s):  
Christoph D Rau ◽  
Jessica Wang ◽  
Shuxun Ren ◽  
Zhihua Wang ◽  
Hongmei Ruan ◽  
...  
Keyword(s):  
Heart Failure ◽  
Association Studies ◽  
Inbred Strains ◽  
Genome Wide Association Studies ◽  
Strong Correlations ◽  
Hotspot Analysis ◽  
Linear Relationships ◽  
Genome Wide ◽  
Echocardiographic Parameters ◽  
Hybrid Mouse Diversity Panel

Heart failure is highly heterogeneous and as a result, relatively few insights into the pathways and drivers of heart failure have been identified using system-wide methods such as genome-wide association studies (GWAS). We have developed a resource, the Hybrid Mouse Diversity Panel (HMDP) for high resolution GWAS and systems genetics in mice. Eight week old female mice from 93 unique inbred strains of the HMDP were given 20 μg/g/day of isoproterenol through an abdominally implanted Alzet micropump. Three weeks post-implantation, all mice were sacrificed, along with age-matched controls. The mice exhibited widely varying degrees of hypertrophy and heart functioning. A portion of the left ventricle was processed and arrayed on an Illumina Mouse Ref 8.0 platform. We used Maximal Information Component Analysis, a novel method of network construction which allows for non-linear relationships between genes as well as non-binary partitioning of genes into sub-networks to subdivide the expression data into a series of modules. In order to identify modules which may contribute to Isoproterenol-induced hypertrophy and failure, we examined the correlation of each module to clinically relevant cardiac traits traits such as organ weights and echocardiographic parameters. We identified several modules with strong correlations to multiple heart failure-related clinical traits, including one module of 41 genes which contained several genes of interest, including Lgals3, a diagnostic marker for heart failure. Utilizing eQTL hotspot analysis, we have identified a locus which is involved in the regulation of this module. A gene within this locus, Magi2, regulates the turnover of the β-adrenergic receptor and represents a likely candidate for the response to isoproterenol.

scholarly journals Genetic epidemiology and Mendelian randomization for informing disease therapeutics: conceptual and methodological challenges

2017 ◽  
Author(s):  
Lavinia Paternoster ◽  
Kate Tilling ◽  
George Davey Smith
Keyword(s):  
Genetic Epidemiology ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Disease Treatment ◽  
The Past ◽  
Genome Wide ◽  
Perceived Benefit ◽  
Progression Of Disease ◽  
High Yields

The past decade has been proclaimed as a hugely successful era of gene discovery through the high yields of many genome-wide association studies (GWAS). However, much of the perceived benefit of such discoveries lies in the promise that the identification of genes that influence disease would directly translate into the identification of potential therapeutic targets (1-4), but this has yet to be realised at a level reflecting expectation. One reason for this, we suggest, is that GWAS to date have generally not focused on phenotypes that directly relate to the progression of disease, and thus speak to disease treatment.

Sign in / Sign up

Export Citation Format

Share Document