Type 2 Diabetes, Metabolic traits and Risk of Heart Failure:a Mendelian Randomization study

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. 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 hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

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

OBJECTIVE: The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes (T2D), glycemic traits, and risk of heart failure (HF). RESEARCH DESIGN AND METHODS: Summary-level data were obtained from genome-wide association studies of T2D, insulin resistance (IR), glycated hemoglobin, fasting insulin and glucose, and HF. MR was conducted using the inverse-variance weighted method. Sensitivity analyses included the MR-Egger method, weighted median and mode methods, and multivariable MR conditioning on potential mediators. RESULTS: Genetic liability to T2D was causally related to higher risk of HF (odds ratio [OR] 1.13 per 1-log unit higher risk of T2D; 95% CI 1.11-1.14; P < 0.001); however, sensitivity analysis revealed evidence of directional pleiotropy. The relationship between T2D and HF was attenuated when adjusted for coronary disease, BMI, LDL cholesterol, and blood pressure in multivariable MR. 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 hemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of T2D (OR 1.49; 95% CI 1.01-2.19; P = 0.042), although again with evidence of pleiotropy. CONCLUSIONS: These findings suggest a possible causal role of T2D and IR in HF etiology, although the presence of both bidirectional effects and directional pleiotropy highlights potential sources of bias that must be considered

Genome-wide association study meta-analysis provides insights into the etiology of heart failure and its subtypes

Heart failure (HF) is a major contributor to global morbidity and mortality. While distinct clinical subtypes, defined by etiology and left ventricular ejection fraction, are well recognized, their genetic determinants remain inadequately understood. In this study, we report a genome-wide association study of HF and its subtypes in a sample of 1.9 million individuals. A total of 153,174 individuals had HF, of whom 44,012 had a nonischemic etiology (ni-HF). A subset of patients with ni-HF were stratified based on left ventricular systolic function, where data were available, identifying 5,406 individuals with reduced ejection fraction and 3,841 with preserved ejection fraction. We identify 66 genetic loci associated with HF and its subtypes, 37 of which have not previously been reported. Using functionally informed gene prioritization methods, we predict effector genes for each identified locus, and map these to etiologic disease clusters through phenome-wide association analysis, network analysis and colocalization. Through heritability enrichment analysis, we highlight the role of extracardiac tissues in disease etiology. We then examine the differential associations of upstream risk factors with HF subtypes using Mendelian randomization. These findings extend our understanding of the mechanisms underlying HF etiology and may inform future approaches to prevention and treatment

Genome-wide association analysis provides insights into the molecular etiology of dilated cardiomyopathy

Dilated cardiomyopathy (DCM) is a leading cause of heart failure and cardiac transplantation. We report a genome-wide association study and multi-trait analysis of DCM (14,256 cases) and three left ventricular traits (36,203 UK Biobank participants). We identified 80 genomic risk loci and prioritized 62 putative effector genes, including several with rare variant DCM associations (MAP3K7, NEDD4L and SSPN). Using single-nucleus transcriptomics, we identify cellular states, biological pathways, and intracellular communications that drive pathogenesis. We demonstrate that polygenic scores predict DCM in the general population and modify penetrance in carriers of rare DCM variants. Our findings may inform the design of genetic testing strategies that incorporate polygenic background. They also provide insights into the molecular etiology of DCM that may facilitate the development of targeted therapeutics

Genome-wide association study reveals mechanisms underlying dilated cardiomyopathy and myocardial resilience

Dilated cardiomyopathy (DCM) is a heart muscle disease that represents an important cause of morbidity and mortality, yet causal mechanisms remain largely elusive. Here, we perform a large-scale genome-wide association study and multitrait analysis for DCM using 9,365 cases and 946,368 controls. We identify 70 genome-wide significant loci, which show broad replication in independent samples and map to 63 prioritized genes. Tissue, cell type and pathway enrichment analyses highlight the central role of the cardiomyocyte and contractile apparatus in DCM pathogenesis. Polygenic risk scores constructed from our genome-wide association study predict DCM across different ancestry groups, show differing contributions to DCM depending on rare pathogenic variant status and associate with systolic heart failure across various clinical settings. Mendelian randomization analyses reveal actionable potential causes of DCM, including higher bodyweight and higher systolic blood pressure. Our findings provide insights into the genetic architecture and mechanisms underlying DCM and myocardial function more broadly

Cold dust and young starbursts: spectral energy distributions of Herschel SPIRE sources from the HerMES survey

13 pages, 13 figures. Accepted for publication by MNRASWe present spectral energy distributions (SEDs) for 68 Herschel sources detected at 5-sigma at 250, 350 and 500 mu in the HerMES SWIRE-Lockman field. We explore whether existing models for starbursts, quiescent star-forming galaxies and for AGN dust tori are able to model the full range of SEDs measured with Herschel. We find that while many galaxies (~ 56 %) are well fitted with the templates used to fit IRAS, ISO and Spitzer sources, for about half the galaxies two new templates are required: quiescent ('cirrus') models with colder (10-20 K) dust, and a young starburst model with higher optical depth than Arp 220. Predictions of submillimetre fluxes based on model fits to 4.5-24 mu data agree rather poorly with the observed fluxes, but the agreement is better for fits to 4.5-70 mu data. Herschel galaxies detected at 500 mu tend to be those with the very highest dust masses

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

&lt;b&gt;Objective&lt;/b&gt; &lt;p&gt;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.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Research Design and Methods&lt;/b&gt;&lt;/p&gt; &lt;p&gt;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.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Results&lt;/b&gt;&lt;/p&gt; &lt;p&gt;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&lt;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.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusions&lt;/b&gt;&lt;/p&gt; 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.</jats:p

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

&lt;b&gt;Objective&lt;/b&gt; &lt;p&gt;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.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Research Design and Methods&lt;/b&gt;&lt;/p&gt; &lt;p&gt;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.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Results&lt;/b&gt;&lt;/p&gt; &lt;p&gt;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&lt;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.&lt;/p&gt; &lt;p&gt;&lt;b&gt;Conclusions&lt;/b&gt;&lt;/p&gt; 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.</jats:p