Sleep Disordered Breathing, Obesity and Atrial Fibrillation: A Mendelian Randomisation Study.

Funder: National Institute for Health Research (NIHR)It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. We performed Mendelian randomisation (MR) to investigate the causal relationships between SDB, body mass index (BMI) and AF. Single-nucleotide polymorphisms associated with SDB (n = 29) and BMI (n = 453) were selected as instrumental variables to investigate the effects of SDB and BMI on AF, using genetic association data on 55,114 AF cases and 482,295 controls. Primary analysis was conducted using inverse-variance weighted MR. Higher genetically predicted SDB and BMI were associated with increased risk of AF (OR per log OR increase in snoring liability 2.09 (95% CI 1.10-3.98), p = 0.03; OR per 1-SD increase in BMI 1.33 (95% CI 1.24-1.42), p < 0.001). The association between SDB and AF was not observed in sensitivity analyses, whilst associations between BMI and AF remained consistent. Similarly, in multivariable MR, SDB was not associated with AF after adjusting for BMI (OR 0.68 (95% CI 0.42-1.10), p = 0.12). Higher BMI remained associated with increased risk of AF after adjusting for OSA (OR 1.40 (95% CI 1.30-1.51), p < 0.001). Elevated BMI appears causal for AF, independent of SDB. Our data suggest that the association between SDB, in general, and AF is attributable to mediation or confounding from obesity, though we cannot exclude that more severe SDB phenotypes (i.e., OSA) are causal for AF

Genome‐Wide Association Study of Pericardial Fat Area in 28 161 UK Biobank Participants

BACKGROUND: Pericardial adipose tissue (PAT) is the visceral adipose tissue compartment surrounding the heart. Experimental and observational research has suggested that greater PAT deposition might mediate cardiovascular disease, independent of general or subcutaneous adiposity. We characterize the genetic architecture of adiposity‐adjusted PAT and identify causal associations between PAT and adverse cardiac magnetic resonance imaging measures of cardiac structure and function in 28 161 UK Biobank participants. METHODS AND RESULTS: The PAT phenotype was extracted from cardiac magnetic resonance images using an automated image analysis tool previously developed and validated in this cohort. A genome‐wide association study was performed with PAT area set as the phenotype, adjusting for age, sex, and other measures of obesity. Functional mapping and Bayesian colocalization were used to understand the biologic role of identified variants. Mendelian randomization analysis was used to examine potential causal links between genetically determined PAT and cardiac magnetic resonance–derived measures of left ventricular structure and function. We discovered 12 genome‐wide significant variants, with 2 independent sentinel variants (rs6428792, P =4.20×10 −9 and rs11992444, P =1.30×10 −12 ) at 2 distinct genomic loci, that were mapped to 3 potentially causal genes: T‐box transcription factor 15 ( TBX15 ), tryptophanyl tRNA synthetase 2, mitochondrial ( WARS2 ) and early B‐cell factor‐2 ( EBF2 ) through functional annotation. Bayesian colocalization additionally suggested a role of RP4‐712E4.1. Genetically predicted differences in adiposity‐adjusted PAT were causally associated with adverse left ventricular remodeling. CONCLUSIONS: This study provides insights into the genetic architecture determining differential PAT deposition, identifies causal links with left structural and functional parameters, and provides novel data about the pathophysiological importance of adiposity distribution

Maternal Hypertension Increases Risk of Preeclampsia and Low Fetal Birthweight:Genetic Evidence From a Mendelian Randomization Study

BACKGROUND: Maternal cardiovascular risk factors have been associated with adverse maternal and fetal outcomes. Given the difficulty in establishing causal relationships using epidemiological data, we applied Mendelian randomization to explore the role of cardiovascular risk factors on risk of developing pre-eclampsia or eclampsia, and low fetal birthweight. METHODS: Uncorrelated single nucleotide polymorphisms associated systolic blood pressure, body mass index, type 2 diabetes mellitus, low-density lipoprotein with cholesterol, smoking, urinary albumin-to-creatinine ratio and estimated glomerular filtration rate at genome-wide significance in studies of 298,957 to 1,201,909 European ancestry participants were selected as instrumental variables. A two-sample Mendelian randomization study was performed with primary outcome of pre-eclampsia or eclampsia (PET). Risk factors associated with PET were further investigated for their association with low birthweight. RESULTS: Higher genetically-predicted systolic blood pressure was associated increased risk of PET [odds ratio (OR) per 1-SD systolic blood pressure increase 1.90 (95% confidence interval (CI)1.45-2.49;p=3.23x10(-6) and reduced birthweight (OR=0.83; 95%CI=0.79-0.86;p=3.96x10(-18)), and this was not mediated by PET. Body mass index and type 2 diabetes were also associated with PET (respectively, OR per 1-SD body mass index increase=1.67 95%CI=1.44-1.94,;p=7.45x10(-12); and OR per logOR increase type 2 diabetes=1.11 95%CI=1.04-1.19p;=1.19x10(-3)), but not with reduced birthweight. CONCLUSIONS: Our results provide evidence for causal effects of systolic blood pressure, body mass index and type 2 diabetes on PET, and identify that systolic blood pressure is associated with reduced birthweight independently of PET. The results provide insight into the pathophysiological basis of PET and identify hypertension as a potentially modifiable risk factor amenable to therapeutic intervention

Automated quality-controlled cardiovascular magnetic resonance pericardial fat quantification using a convolutional neural network in the UK Biobank

Background: Pericardial adipose tissue (PAT) may represent a novel risk marker for cardiovascular disease. However, absence of rapid radiation-free PAT quantification methods has precluded its examination in large cohorts.Objectives: We developed a fully automated quality-controlled tool for cardiovascular magnetic resonance (CMR) PAT quantification in the UK Biobank (UKB).Methods: Image analysis comprised contouring an en-bloc PAT area on four-chamber cine images. We created a ground truth manual analysis dataset randomly split into training and test sets. We built a neural network for automated segmentation using a Multi-residual U-net architecture with incorporation of permanently active dropout layers to facilitate quality control of the model's output using Monte Carlo sampling. We developed an in-built quality control feature, which presents predicted Dice scores. We evaluated model performance against the test set (n = 87), the whole UKB Imaging cohort (n = 45,519), and an external dataset (n = 103). In an independent dataset, we compared automated CMR and cardiac computed tomography (CCT) PAT quantification. Finally, we tested association of CMR PAT with diabetes in the UKB (n = 42,928).Results: Agreement between automated and manual segmentations in the test set was almost identical to inter-observer variability (mean Dice score = 0.8). The quality control method predicted individual Dice scores with Pearson r = 0.75. Model performance remained high in the whole UKB Imaging cohort and in the external dataset, with medium–good quality segmentation in 94.3% (mean Dice score = 0.77) and 94.4% (mean Dice score = 0.78), respectively. There was high correlation between CMR and CCT PAT measures (Pearson r = 0.72, p-value 5.3 ×10−18). Larger CMR PAT area was associated with significantly greater odds of diabetes independent of age, sex, and body mass index.Conclusions: We present a novel fully automated method for CMR PAT quantification with good model performance on independent and external datasets, high correlation with reference standard CCT PAT measurement, and expected clinical associations with diabetes.<br/

A Mendelian randomization study of genetic liability to post-traumatic stress disorder and risk of ischemic stroke.

Observational studies have shown an association between post-traumatic stress disorder (PTSD) and ischemic stroke (IS) but given the susceptibility to confounding it is unclear if these associations represent causal effects. Mendelian randomization (MR) facilitates causal inference that is robust to the influence of confounding. Using two sample MR, we investigated the causal effect of genetic liability to PTSD on IS risk. Ancestry-specific genetic instruments of PTSD and four quantitative sub-phenotypes of PTSD, including hyperarousal, avoidance, re-experiencing, and total symptom severity score (PCL-Total) were obtained from the Million Veteran Programme (MVP) using a threshold P value (P) of <5 × 10-7, clumping distance of 1000 kilobase (Mb) and r2 < 0.01. Genetic association estimates for IS were obtained from the MEGASTROKE consortium (Ncases = 34,217, Ncontrols = 406,111) for European ancestry individuals and from the Consortium of Minority Population Genome-Wide Association Studies of Stroke (COMPASS) (Ncases = 3734, Ncontrols = 18,317) for African ancestry individuals. We used the inverse-variance weighted (IVW) approach as the main analysis and performed MR-Egger and the weighted median methods as pleiotropy-robust sensitivity analyses. In European ancestry individuals, we found evidence of an association between genetic liability to PTSD avoidance, and PCL-Total and increased IS risk (odds ratio (OR)1.04, 95% Confidence Interval (CI) 1.007-1.077, P = 0.017 for avoidance and (OR 1.02, 95% CI 1.010-1.040, P = 7.6 × 10-4 for PCL total). In African ancestry individuals, we found evidence of an association between genetically liability to PCL-Total and reduced IS risk (OR 0.95 (95% CI 0.923-0.991, P = 0.01) and hyperarousal (OR 0.83 (95% CI 0.691-0.991, P = 0.039) but no association was observed for PTSD case-control, avoidance, or re-experiencing. Similar estimates were obtained with MR sensitivity analyses. Our findings suggest that specific sub-phenotypes of PTSD, such as hyperarousal, avoidance, PCL total, may have a causal effect on people of European and African ancestry's risk of IS. This shows that the molecular mechanisms behind the relationship between IS and PTSD may be connected to symptoms of hyperarousal and avoidance. To clarify the precise biological mechanisms involved and how they may vary between populations, more research is required

Sleep Disordered Breathing, Obesity and Atrial Fibrillation: A Mendelian Randomisation Study

It remains unclear whether the association between obstructive sleep apnoea (OSA), a form of sleep-disordered breathing (SDB), and atrial fibrillation (AF) is causal or mediated by shared co-morbidities such as obesity. Existing observational studies are conflicting and limited by confounding and reverse causality. We performed Mendelian randomisation (MR) to investigate the causal relationships between SDB, body mass index (BMI) and AF. Single-nucleotide polymorphisms associated with SDB (n = 29) and BMI (n = 453) were selected as instrumental variables to investigate the effects of SDB and BMI on AF, using genetic association data on 55,114 AF cases and 482,295 controls. Primary analysis was conducted using inverse-variance weighted MR. Higher genetically predicted SDB and BMI were associated with increased risk of AF (OR per log OR increase in snoring liability 2.09 (95% CI 1.10&ndash;3.98), p = 0.03; OR per 1-SD increase in BMI 1.33 (95% CI 1.24&ndash;1.42), p &lt; 0.001). The association between SDB and AF was not observed in sensitivity analyses, whilst associations between BMI and AF remained consistent. Similarly, in multivariable MR, SDB was not associated with AF after adjusting for BMI (OR 0.68 (95% CI 0.42&ndash;1.10), p = 0.12). Higher BMI remained associated with increased risk of AF after adjusting for OSA (OR 1.40 (95% CI 1.30&ndash;1.51), p &lt; 0.001). Elevated BMI appears causal for AF, independent of SDB. Our data suggest that the association between SDB, in general, and AF is attributable to mediation or confounding from obesity, though we cannot exclude that more severe SDB phenotypes (i.e., OSA) are causal for AF

Type 2 Diabetes and Atrial Fibrillation: Evaluating Causal and Pleiotropic Pathways Using Mendelian Randomization

Background Observational associations between type 2 diabetes (T2D) and atrial fibrillation (AF) have been established, but causality remains undetermined. We performed Mendelian randomization (MR) to study causal effects of genetically predicted T2D on AF risk, independent of cardiometabolic risk factors. Methods and Results Instrumental variables included 182 uncorrelated single nucleotide polymorphisms associated with T2D at genome‐wide significance (P <5×10−8). Genetic association estimates for cardiometabolic exposures were obtained from genome‐wide association studies including 188 577 individuals for low‐density lipoprotein‐C, 694 649 individuals for body mass index, and 757 601 for systolic blood pressure. Two‐sample, inverse‐variance weighted MR formed the primary analyses. The MR‐TRYX approach was used to dissect potential pleiotropic pathways, with multivariable MR performed to investigate cardiometabolic mediation. Genetically predicted T2D associated with increased AF liability in univariable MR (odds ratio [OR], 1.08 [95% CI, 1.02–1.13], P=0.003). Sensitivity analyses indicated potential pleiotropy, with radial MR identifying 4 outlier single nucleotide polymorphisms that were likely contributors. Phenomic scanning on MR‐base and subsequent least absolute shrinkage and selection operator regression allowed prioritization of 7 candidate traits. The outlier‐adjusted effect estimate remained consistent with the original inverse‐variance weighted estimate (OR, 1.07 [95% CI, 1.02–1.12], P=0.008). On multivariable MR, T2D remained associated with increased AF liability after adjustment for low‐density lipoprotein‐C and body mass index. Following adjustment for systolic blood pressure, the relationship between T2D and AF became nonsignificant (OR, 1.04 [95% CI, 0.95–1.13], P=0.40). Conclusions These data provide novel genetic evidence that while T2D likely causally associates with AF, mediation via systolic blood pressure exists. Endeavoring to lower systolic blood pressure alongside achieving normoglycemia may provide particular benefit on AF risk in patients with T2D