A new test for trait mean and variance detects unreported loci for blood-pressure variation.

Variability in quantitative traits has clinical, ecological, and evolutionary significance. Most genetic variants identified for complex quantitative traits have only a detectable effect on the mean of trait. We have developed the mean-variance test (MVtest) to simultaneously model the mean and log-variance of a quantitative trait as functions of genotypes and covariates by using estimating equations. The advantages of MVtest include the facts that it can detect effect modification, that multiple testing can follow conventional thresholds, that it is robust to non-normal outcomes, and that association statistics can be meta-analyzed. In simulations, we show control of type I error of MVtest over several alternatives. We identified 51 and 37 previously unreported associations for effects on blood-pressure variance and mean, respectively, in the UK Biobank. Transcriptome-wide association studies revealed 633 significant unique gene associations with blood-pressure mean variance. MVtest is broadly applicable to studies of complex quantitative traits and provides an important opportunity to detect novel loci.

Integration of genetic fine-mapping and multi-omics data reveals candidate effector genes for hypertension.

Genome-wide association studies of blood pressure (BP) have identified >1,000 loci, but the effector genes and biological pathways at these loci are mostly unknown. Using published association summary statistics, we conducted annotation-informed fine-mapping incorporating tissue-specific chromatin segmentation and colocalization to identify causal variants and candidate effector genes for systolic BP, diastolic BP, and pulse pressure. We observed 532 distinct signals associated with ≥2 BP traits and 84 with all three. For >20% of signals, a single variant accounted for >75% posterior probability, 65 were missense variants in known (SLC39A8, ADRB2, and DBH) and previously unreported BP candidate genes (NRIP1 and MMP14). In disease-relevant tissues, we colocalized >80 and >400 distinct signals for each BP trait with cis-eQTLs and regulatory regions from promoter capture Hi-C, respectively. Integrating mouse, human disorder, gene expression and tissue abundance data, and literature review, we provide consolidated evidence for 436 BP candidate genes for future functional validation and discover several potential drug targets.

LGR6 frameshift variant abrogates receptor expression on select leukocyte subsets and associates with viral infections.

The leucine-rich repeat-containing G-protein-coupled receptor 6 (LGR6) was recently identified as the cognate receptor for the pro-resolving mediator Maresin (MaR)1. To address the biological role of LGR6 in humans, we investigated the functional impact of a genetic variant in the gene encoding for LGR6, which is predicted to lead to a frameshift mutation in one of the receptor isoforms, on both receptor expression and immune cell responses. In neutrophils, monocytes, and NK cells from volunteers homozygous for this variant, we found a significant downregulation in the expression of LGR6 when compared with controls without the variant. Whereas LGR6 expression was essentially similar in monocyte-derived macrophages and CD8+ T-cells. Functionally loss of LGR6 expression was linked with a decreased ability of neutrophils and monocytes to phagocytose bacteria. We observed an increase in neutrophil chemotaxis and leukotriene B4 (LTB4) production, and increased expression of activation markers, including markers for platelet-leukocyte phagocyte heterotypic aggregates, such as CD41, in neutrophils and monocytes from the variant group. Using data from the UK Biobank we found that at a population level the rs4266947 variant which is in high linkage disequilibrium with rs74355478 was associated with a higher incidence of viral infections. Intriguingly, neutrophils, NK cells and CD8+ T-cells from volunteers with the LGR6 variant displayed altered viral responses when stimulated with Toll-like receptor (TLR)3, TLR7/TLR8 and TLR9 agonists. Together these findings shed new light on the cell type-specific regulation of LGR6 expression and the role of this receptor in directing host immune responses.

The ric-8b protein (resistance to inhibitors of cholinesterase 8b) is key to preserving contractile function in the adult heart.

Resistance to inhibitors of cholinesterases (ric-8 proteins) are involved in modulating G-protein function but little is known of their potential physiological importance in the heart. In the present study, we assessed the role of resistance to inhibitors of cholinesterase 8b (Ric-8b) in determining cardiac contractile function. We developed a murine model in which it was possible to conditionally delete ric-8b in cardiac tissue in the adult animal after the addition of tamoxifen. Deletion of ric-8b led to severely reduced contractility as measured using echocardiography days after administration of tamoxifen. Histological analysis of the ventricular tissue showed highly variable myocyte size, prominent fibrosis and an increase in cellular apoptosis. RNA sequencing revealed transcriptional remodelling in response to cardiac ric-8b deletion involving the extracellular matrix and inflammation. Phosphoproteomic analysis revealed substantial downregulation of phosphopeptides related to myosin light chain 2. At the cellular level, the deletion of ric-8b led to loss of activation of the L-type calcium channel through the ß-adrenergic pathways. Using fluorescence resonance energy transfer-based assays we showed ric-8b protein selectively interacts with the stimulatory G-protein, Gαs. We explored if deletion of Gnas (the gene encoding Gαs) in cardiac tissue using a similar approach in the mouse led to an equivalent phenotype. The conditional deletion of the Gαs gene in the ventricle led to comparable effects on contractile function and cardiac histology. We conclude that ric-8b is essential to preserve cardiac contractile function likely through an interaction with the stimulatory G-protein and downstream phosphorylation of myosin light chain 2.

Heteroplasmic mitochondrial DNA variants in cardiovascular diseases.

Mitochondria are implicated in the pathogenesis of cardiovascular diseases (CVDs) but the reasons for this are not well understood. Maternally-inherited population variants of mitochondrial DNA (mtDNA) which affect all mtDNA molecules (homoplasmic) are associated with cardiometabolic traits and the risk of developing cardiovascular disease. However, it is not known whether mtDNA mutations only affecting a proportion of mtDNA molecules (heteroplasmic) also play a role. To address this question, we performed a high-depth (~1000-fold) mtDNA sequencing of blood DNA in 1,399 individuals with hypertension (HTN), 1,946 with ischemic heart disease (IHD), 2,146 with ischemic stroke (IS), and 723 healthy controls. We show that the per individual burden of heteroplasmic single nucleotide variants (mtSNVs) increases with age. The age-effect was stronger for low-level heteroplasmies (heteroplasmic fraction, HF, 5-10%), likely reflecting acquired somatic events based on trinucleotide mutational signatures. After correcting for age and other confounders, intermediate heteroplasmies (HF 10-95%) were more common in hypertension, particularly involving non-synonymous variants altering the amino acid sequence of essential respiratory chain proteins. These findings raise the possibility that heteroplasmic mtSNVs play a role in the pathophysiology of hypertension.

Prognostic Significance of Different Ventricular Ectopic Burdens During Submaximal Exercise in Asymptomatic UK Biobank Subjects.

BACKGROUND: The consequences of exercise-induced premature ventricular contractions (PVCs) in asymptomatic individuals remain unclear. This study aimed to assess the association between PVC burdens during submaximal exercise and major adverse cardiovascular events (MI/HF/LTVA: myocardial infarction [MI], heart failure [HF], and life-threatening ventricular arrhythmia [LTVA]), and all-cause mortality. Additional end points were MI, LTVA, HF, and cardiovascular mortality. METHODS: A neural network was developed to count PVCs from ECGs recorded during exercise (6 minutes) and recovery (1 minute) in 48 315 asymptomatic participants from UK Biobank. Associations were estimated using multivariable Cox proportional hazard models. Explorative studies were conducted in subgroups with cardiovascular magnetic resonance imaging data (n=6290) and NT-proBNP (N-terminal Pro-B-type natriuretic peptide) levels (n=4607) to examine whether PVC burden was associated with subclinical cardiomyopathy. RESULTS: Mean age was 56.8±8.2 years; 51.1% of the participants were female; and median follow-up was 12.6 years. Low PVC counts during exercise and recovery were both associated with MI/HF/LTVA risk, independently of clinical factors: adjusted hazard ratio (HR), 1.2 (1-5 exercise PVCs, P<0.001) and HR, 1.3 (1-5 recovery PVCs, P<0.001). Risks were higher with increasing PVC count: HR, 1.8 (>20 exercise PVCs, P<0.001) and HR, 1.6 (>5 recovery PVCs, P<0.001). A similar trend was observed for all-cause mortality, although associations were only significant for high PVC burdens: HRs, 1.6 (>20 exercise PVCs, P<0.001) and 1.5 (>5 recovery PVCs, P<0.001). Complex PVC rhythms were associated with higher risk compared with PVC count alone. PVCs were also associated with incident HF, LTVA, and cardiovascular mortality, but not MI. In the explorative studies, high PVC burden was associated with larger left ventricular volumes, lower ejection fraction, and higher levels of NT-proBNP compared with participants without PVCs. CONCLUSIONS: In this cohort of middle-aged and older adults, PVC count during submaximal exercise and recovery were both associated with MI/HF/LTVA, all-cause mortality, HF, LTVAs, and cardiovascular mortality, independent of clinical and exercise test factors, indicating an incremental increase in risk as PVC count rises. Complex PVC rhythms were associated with higher risk compared with PVC count alone. Underlying mechanisms may include the presence of subclinical cardiomyopathy.

Frequency, Penetrance, and Variable Expressivity of Dilated Cardiomyopathy-Associated Putative Pathogenic Gene Variants in UK Biobank Participants.

BACKGROUND: There is a paucity of data regarding the phenotype of dilated cardiomyopathy (DCM) gene variants in the general population. We aimed to determine the frequency and penetrance of DCM-associated putative pathogenic gene variants in a general adult population, with a focus on the expression of clinical and subclinical phenotype, including structural, functional, and arrhythmic disease features. METHODS: UK Biobank participants who had undergone whole exome sequencing, ECG, and cardiovascular magnetic resonance imaging were selected for study. Three variant-calling strategies (1 primary and 2 secondary) were used to identify participants with putative pathogenic variants in 44 DCM genes. The observed phenotype was graded DCM (clinical or cardiovascular magnetic resonance diagnosis); early DCM features, including arrhythmia or conduction disease, isolated ventricular dilation, and hypokinetic nondilated cardiomyopathy; or phenotype-negative. RESULTS: Among 18 665 individuals included in the study, 1463 (7.8%) possessed ≥1 putative pathogenic variant in 44 DCM genes by the main variant calling strategy. A clinical diagnosis of DCM was present in 0.34% and early DCM features in 5.7% of individuals with putative pathogenic variants. ECG and cardiovascular magnetic resonance analysis revealed evidence of subclinical DCM in an additional 1.6% and early DCM features in an additional 15.9% of individuals with putative pathogenic variants. Arrhythmias or conduction disease (15.2%) were the most common early DCM features, followed by hypokinetic nondilated cardiomyopathy (4%). The combined clinical/subclinical penetrance was ≤30% with all 3 variant filtering strategies. Clinical DCM was slightly more prevalent among participants with putative pathogenic variants in definitive/strong evidence genes as compared with those with variants in moderate/limited evidence genes. CONCLUSIONS: In the UK Biobank, ≈1 of 6 of adults with putative pathogenic variants in DCM genes exhibited early DCM features potentially associated with DCM genotype, most commonly manifesting with arrhythmias in the absence of substantial ventricular dilation or dysfunction.

Genomic and pleiotropic analyses of resting QT interval identifies novel loci and overlap with atrial electrical disorders.

The resting QT interval, an electrocardiographic (ECG) measure of ventricular myocardial repolarization, is a heritable risk marker of cardiovascular mortality, but the mechanisms remain incompletely understood. Previously reported candidate genes have provided insights into the regulatory mechanisms of the QT interval. However, there are still important knowledge gaps. We aimed to gain new insights by (i) providing new candidate genes, (ii) identifying pleiotropic associations with other cardiovascular traits, and (iii) scanning for sexually dimorphic genetic effects. We conducted a genome-wide association analysis for resting QT interval with ~9.8 million variants in 52 107 individuals of European ancestry without known cardiovascular disease from the UK Biobank. We identified 40 loci, 13 of which were novel, including 2 potential sex-specific loci, explaining ~11% of the trait variance. Candidate genes at novel loci were involved in myocardial structure and arrhythmogenic cardiomyopathy. Investigation of pleiotropic effects of QT interval variants using phenome-wide association analyses in 302 000 unrelated individuals from the UK Biobank and pairwise genome-wide comparisons with other ECG and cardiac imaging traits revealed genetic overlap with atrial electrical pathology. These findings provide novel insights into how abnormal myocardial repolarization and increased cardiovascular mortality may be linked.

Genome-wide association study of cardiac troponin I in the general population.

Circulating cardiac troponin proteins are associated with structural heart disease and predict incident cardiovascular disease in the general population. However, the genetic contribution to cardiac troponin I (cTnI) concentrations and its causal effect on cardiovascular phenotypes are unclear. We combine data from two large population-based studies, the Trøndelag Health Study and the Generation Scotland Scottish Family Health Study, and perform a genome-wide association study of high-sensitivity cTnI concentrations with 48 115 individuals. We further use two-sample Mendelian randomization to investigate the causal effects of circulating cTnI on acute myocardial infarction (AMI) and heart failure (HF). We identified 12 genetic loci (8 novel) associated with cTnI concentrations. Associated protein-altering variants highlighted putative functional genes: CAND2, HABP2, ANO5, APOH, FHOD3, TNFAIP2, KLKB1 and LMAN1. Phenome-wide association tests in 1688 phecodes and 83 continuous traits in UK Biobank showed associations between a genetic risk score for cTnI and cardiac arrhythmias, metabolic and anthropometric measures. Using two-sample Mendelian randomization, we confirmed the non-causal role of cTnI in AMI (5948 cases, 355 246 controls). We found indications for a causal role of cTnI in HF (47 309 cases and 930 014 controls), but this was not supported by secondary analyses using left ventricular mass as outcome (18 257 individuals). Our findings clarify the biology underlying the heritable contribution to circulating cTnI and support cTnI as a non-causal biomarker for AMI in the general population. Using genetically informed methods for causal inference helps inform the role and value of measuring cTnI in the general population.

Common Genetic Variants Modulate the Electrocardiographic Tpeak-to-Tend Interval.

Sudden cardiac death is responsible for half of all deaths from cardiovascular disease. The analysis of the electrophysiological substrate for arrhythmias is crucial for optimal risk stratification. A prolonged T-peak-to-Tend (Tpe) interval on the electrocardiogram is an independent predictor of increased arrhythmic risk, and Tpe changes with heart rate are even stronger predictors. However, our understanding of the electrophysiological mechanisms supporting these risk factors is limited. We conducted genome-wide association studies (GWASs) for resting Tpe and Tpe response to exercise and recovery in ∼30,000 individuals, followed by replication in independent samples (∼42,000 for resting Tpe and ∼22,000 for Tpe response to exercise and recovery), all from UK Biobank. Fifteen and one single-nucleotide variants for resting Tpe and Tpe response to exercise, respectively, were formally replicated. In a full dataset GWAS, 13 further loci for resting Tpe, 1 for Tpe response to exercise and 1 for Tpe response to exercise were genome-wide significant (p ≤ 5 × 10-8). Sex-specific analyses indicated seven additional loci. In total, we identify 32 loci for resting Tpe, 3 for Tpe response to exercise and 3 for Tpe response to recovery modulating ventricular repolarization, as well as cardiac conduction and contraction. Our findings shed light on the genetic basis of resting Tpe and Tpe response to exercise and recovery, unveiling plausible candidate genes and biological mechanisms underlying ventricular excitability.

Genetic variants in TRPM7 associated with unexplained stillbirth modify ion channel function.

Stillbirth is the loss of a fetus after 22 weeks of gestation, of which almost half go completely unexplained despite post-mortem. We recently sequenced 35 arrhythmia-associated genes from 70 unexplained stillbirth cases. Our hypothesis was that deleterious mutations in channelopathy genes may have a functional effect in utero that may be pro-arrhythmic in the developing fetus. We observed four heterozygous, nonsynonymous variants in transient receptor potential melastatin 7 (TRPM7), a ubiquitously expressed ion channel known to regulate cardiac development and repolarization in mice. We used site-directed mutagenesis and single-cell patch-clamp to analyze the functional effect of the four stillbirth mutants on TRPM7 ion channel function in heterologous cells. We also used cardiomyocytes derived from human pluripotent stem cells to model the contribution of TRPM7 to action potential morphology. Our results show that two TRPM7 variants, p.G179V and p.T860M, lead to a marked reduction in ion channel conductance. This observation was underpinned by a lack of measurable TRPM7 protein expression, which in the case of p.T860M was due to rapid proteasomal degradation. We also report that human hiPSC-derived cardiomyocytes possess measurable TRPM7 currents; however, siRNA knockdown did not directly affect action potential morphology. TRPM7 variants found in the unexplained stillbirth population adversely affect ion channel function and this may precipitate fatal arrhythmia in utero.

Multi-ancestry genome-wide gene-sleep interactions identify novel loci for blood pressure.

Long and short sleep duration are associated with elevated blood pressure (BP), possibly through effects on molecular pathways that influence neuroendocrine and vascular systems. To gain new insights into the genetic basis of sleep-related BP variation, we performed genome-wide gene by short or long sleep duration interaction analyses on four BP traits (systolic BP, diastolic BP, mean arterial pressure, and pulse pressure) across five ancestry groups in two stages using 2 degree of freedom (df) joint test followed by 1df test of interaction effects. Primary multi-ancestry analysis in 62,969 individuals in stage 1 identified three novel gene by sleep interactions that were replicated in an additional 59,296 individuals in stage 2 (stage 1 + 2 Pjoint < 5 × 10-8), including rs7955964 (FIGNL2/ANKRD33) that increases BP among long sleepers, and rs73493041 (SNORA26/C9orf170) and rs10406644 (KCTD15/LSM14A) that increase BP among short sleepers (Pint < 5 × 10-8). Secondary ancestry-specific analysis identified another novel gene by long sleep interaction at rs111887471 (TRPC3/KIAA1109) in individuals of African ancestry (Pint = 2 × 10-6). Combined stage 1 and 2 analyses additionally identified significant gene by long sleep interactions at 10 loci including MKLN1 and RGL3/ELAVL3 previously associated with BP, and significant gene by short sleep interactions at 10 loci including C2orf43 previously associated with BP (Pint < 10-3). 2df test also identified novel loci for BP after modeling sleep that has known functions in sleep-wake regulation, nervous and cardiometabolic systems. This study indicates that sleep and primary mechanisms regulating BP may interact to elevate BP level, suggesting novel insights into sleep-related BP regulation.

Polygenic scores for schizophrenia and major depression are associated with psychosocial risk factors in children: evidence of gene-environment correlation.

BACKGROUND: Whilst genetic and environmental risk factors for schizophrenia (SCZ) and major depressive disorder (MDD) have been established, it is unclear whether exposure to environmental risk factors is genetically confounded by passive, evocative or active gene-environment correlation (rGE). STUDY OBJECTIVE: This study aims to investigate: (a) whether the genetic risk for SCZ/MDD in children is correlated with established environmental and psychosocial risk factors in two British community samples, the 1958 National Child Development Study (NCDS) and the Millennium Cohort Study (MCS), (b) whether these associations vary between both psychopathologies, and (c) whether findings differ across the two cohorts which were born 42 years apart. METHODS: Polygenic risk scores (PRS) from existing large genome-wide associations studies (GWAS) were applied to test the correlation between the child genetic risk for SCZ/MDD and known environmental risk factors. In addition, parental and child genetic data from MCS were used to distinguish between passive and evocative rGE. RESULTS: The child polygenic risk for SCZ and MDD was correlated with single parenthood in MCS. Moreover, the lack of father's involvement in child care was associated with the genetic risk for SCZ in NCDS. However, we also found associations between several indicators of low socioeconomic status and heightened genetic risk for MDD in children in both cohorts. Further, the genetic risk for MDD was associated with parental lack of interest in the child's education in NCDS as well as more maternal smoking and less maternal alcohol consumption during childhood in MCS. According to sensitivity analyses in MCS (controlling for parental genotype), more than half of our significant correlations reflected passive rGE. CONCLUSIONS: Findings suggest that several established environmental and psychosocial risk factors for SCZ and MDD are at least partially associated with children's genetic risk for these psychiatric disorders.

The role of resistance to inhibitors of cholinesterase 8b in the control of heart rate.

We have assessed the role of ric-b8 in the control of heart rate after the gene was implicated in a recent genome-wide association study of resting heart rate. We developed a novel murine model in which it was possible to conditionally delete ric-8b in the sinoatrial (SA) node after the addition of tamoxifen. Despite this, we were unable to obtain homozygotes and thus studied heterozygotes. Haploinsufficiency of ric-8b in the sinoatrial node induced by the addition of tamoxifen in adult animals leads to mice with a reduced heart rate. However, other electrocardiographic intervals (e.g., PR and QRS) were normal, and there was no apparent arrhythmia such as heart block. The positive chronotropic response to isoprenaline was abrogated, whereas the response to carbachol was unchanged. The pacemaker current If (funny current) has an important role in regulating heart rate, and its function is modulated by both isoprenaline and carbachol. Using a heterologous system expressing HCN4, we show that ric-8b can modulate the HCN4 current. Overexpression of ric-8b led to larger HCN4 currents, whereas silencing ric-8b led to smaller currents. Ric-8b modulates heart rate responses in vivo likely via its actions on the stimulatory G-protein.

Over 1000 genetic loci influencing blood pressure with multiple systems and tissues implicated.

High blood pressure (BP) remains the major heritable and modifiable risk factor for cardiovascular disease. Persistent high BP, or hypertension, is a complex trait with both genetic and environmental interactions. Despite swift advances in genomics, translating new discoveries to further our understanding of the underlying molecular mechanisms remains a challenge. More than 500 loci implicated in the regulation of BP have been revealed by genome-wide association studies (GWAS) in 2018 alone, taking the total number of BP genetic loci to over 1000. Even with the large number of loci now associated to BP, the genetic variance explained by all loci together remains low (~5.7%). These genetic associations have elucidated mechanisms and pathways regulating BP, highlighting potential new therapeutic and drug repurposing targets. A large proportion of the BP loci were discovered and reported simultaneously by multiple research groups, creating a knowledge gap, where the reported loci to date have not been investigated in a harmonious way. Here, we review the BP-associated genetic variants reported across GWAS studies and investigate their potential impact on the biological systems using in silico enrichment analyses for pathways, tissues, gene ontology and genetic pleiotropy.

Gut microbiome-based supervised machine learning for clinical diagnosis of inflammatory bowel diseases.

Despite the availability of various diagnostic tests for inflammatory bowel diseases (IBD), misdiagnosis of IBD occurs frequently, and thus, there is a clinical need to further improve the diagnosis of IBD. As gut dysbiosis is reported in patients with IBD, we hypothesized that supervised machine learning (ML) could be used to analyze gut microbiome data for predictive diagnostics of IBD. To test our hypothesis, fecal 16S metagenomic data of 729 subjects with IBD and 700 subjects without IBD from the American Gut Project were analyzed using five different ML algorithms. Fifty differential bacterial taxa were identified [linear discriminant analysis effect size (LEfSe): linear discriminant analysis (LDA) score > 3] between the IBD and non-IBD groups, and ML classifications trained with these taxonomic features using random forest (RF) achieved a testing area under the receiver operating characteristic curves (AUC) of ∼0.80. Next, we tested if operational taxonomic units (OTUs), instead of bacterial taxa, could be used as ML features for diagnostic classification of IBD. Top 500 high-variance OTUs were used for ML training, and an improved testing AUC of ∼0.82 (RF) was achieved. Lastly, we tested if supervised ML could be used for differentiating Crohn's disease (CD) and ulcerative colitis (UC). Using 331 CD and 141 UC samples, 117 differential bacterial taxa (LEfSe: LDA score > 3) were identified, and the RF model trained with differential taxonomic features or high-variance OTU features achieved a testing AUC > 0.90. In summary, our study demonstrates the promising potential of artificial intelligence via supervised ML modeling for predictive diagnostics of IBD using gut microbiome data.NEW & NOTEWORTHY Our study demonstrates the promising potential of artificial intelligence via supervised machine learning modeling for predictive diagnostics of different types of inflammatory bowel diseases using fecal gut microbiome data.

Hypertension genetics past, present and future applications.

Essential hypertension is a complex trait where the underlying aetiology is not completely understood. Left untreated it increases the risk of severe health complications including cardiovascular and renal disease. It is almost 15 years since the first genome-wide association study for hypertension, and after a slow start there are now over 1000 blood pressure (BP) loci explaining ∼6% of the single nucleotide polymorphism-based heritability. Success in discovery of hypertension genes has provided new pathological insights and drug discovery opportunities and translated to the development of BP genetic risk scores (GRSs), facilitating population disease risk stratification. Comparing highest and lowest risk groups shows differences of 12.9 mm Hg in systolic-BP with significant differences in risk of hypertension, stroke, cardiovascular disease and myocardial infarction. GRSs are also being trialled in antihypertensive drug responses. Drug targets identified include NPR1, for which an agonist drug is currently in clinical trials. Identification of variants at the PHACTR1 locus provided insights into regulation of EDN1 in the endothelin pathway, which is aiding the development of endothelin receptor EDNRA antagonists. Drug re-purposing opportunities, including SLC5A1 and canagliflozin (a type-2 diabetes drug), are also being identified. In this review, we present key studies from the past, highlight current avenues of research and look to the future focusing on gene discovery, epigenetics, gene-environment interactions, GRSs and drug discovery. We evaluate limitations affecting BP genetics, including ancestry bias and discuss streamlining of drug target discovery and applications for treating and preventing hypertension, which will contribute to tailored precision medicine for patients.

Vitamin D and coronavirus disease 2019 (COVID-19): rapid evidence review.

BACKGROUND: The rapid global spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus that causes coronavirus disease 2019 (COVID-19), has re-ignited interest in the possible role of vitamin D in modulation of host responses to respiratory pathogens. Indeed, vitamin D supplementation has been proposed as a potential preventative or therapeutic strategy. Recommendations for any intervention, particularly in the context of a potentially fatal pandemic infection, should be strictly based on clinically informed appraisal of the evidence base. In this narrative review, we examine current evidence relating to vitamin D and COVID-19 and consider the most appropriate practical recommendations. OBSERVATIONS: Although there are a growing number of studies investigating the links between vitamin D and COVID-19, they are mostly small and observational with high risk of bias, residual confounding, and reverse causality. Extrapolation of molecular actions of 1,25(OH)2-vitamin D to an effect of increased 25(OH)-vitamin D as a result of vitamin D supplementation is generally unfounded, as is the automatic conclusion of causal mechanisms from observational studies linking low 25(OH)-vitamin D to incident disease. Efficacy is ideally demonstrated in the context of adequately powered randomised intervention studies, although such approaches may not always be feasible. CONCLUSIONS: At present, evidence to support vitamin D supplementation for the prevention or treatment of COVID-19 is inconclusive. In the absence of any further compelling data, adherence to existing national guidance on vitamin D supplementation to prevent vitamin D deficiency, predicated principally on maintaining musculoskeletal health, appears appropriate.

Adverse cardiovascular magnetic resonance phenotypes are associated with greater likelihood of incident coronavirus disease 2019: findings from the UK Biobank.

BACKGROUND: Coronavirus disease 2019 (COVID-19) disproportionately affects older people. Observational studies suggest indolent cardiovascular involvement after recovery from acute COVID-19. However, these findings may reflect pre-existing cardiac phenotypes. AIMS: We tested the association of baseline cardiovascular magnetic resonance (CMR) phenotypes with incident COVID-19. METHODS: We studied UK Biobank participants with CMR imaging and COVID-19 testing. We considered left and right ventricular (LV, RV) volumes, ejection fractions, and stroke volumes, LV mass, LV strain, native T1, aortic distensibility, and arterial stiffness index. COVID-19 test results were obtained from Public Health England. Co-morbidities were ascertained from self-report and hospital episode statistics (HES). Critical care admission and death were from HES and death register records. We investigated the association of each cardiovascular measure with COVID-19 test result in multivariable logistic regression models adjusting for age, sex, ethnicity, deprivation, body mass index, smoking, diabetes, hypertension, high cholesterol, and prior myocardial infarction. RESULTS: We studied 310 participants (n = 70 positive). Median age was 63.8 [57.5, 72.1] years; 51.0% (n = 158) were male. 78.7% (n = 244) were tested in hospital, 3.5% (n = 11) required critical care admission, and 6.1% (n = 19) died. In fully adjusted models, smaller LV/RV end-diastolic volumes, smaller LV stroke volume, and poorer global longitudinal strain were associated with significantly higher odds of COVID-19 positivity. DISCUSSION: We demonstrate association of pre-existing adverse CMR phenotypes with greater odds of COVID-19 positivity independent of classical cardiovascular risk factors. CONCLUSIONS: Observational reports of cardiovascular involvement after COVID-19 may, at least partly, reflect pre-existing cardiac status rather than COVID-19 induced alterations.

Machine learning-based classification and diagnosis of clinical cardiomyopathies.

Dilated cardiomyopathy (DCM) and ischemic cardiomyopathy (ICM) are two common types of cardiomyopathies leading to heart failure. Accurate diagnostic classification of different types of cardiomyopathies is critical for precision medicine in clinical practice. In this study, we hypothesized that machine learning (ML) can be used as a novel diagnostic approach to analyze cardiac transcriptomic data for classifying clinical cardiomyopathies. RNA-Seq data of human left ventricle tissues were collected from 41 DCM patients, 47 ICM patients, and 49 nonfailure controls (NF) and tested using five ML algorithms: support vector machine with radial kernel (svmRadial), neural networks with principal component analysis (pcaNNet), decision tree (DT), elastic net (ENet), and random forest (RF). Initial ML classifications achieved ~93% accuracy (svmRadial) for NF vs. DCM, ~82% accuracy (RF) for NF vs. ICM, and ~80% accuracy (ENet and svmRadial) for DCM vs. ICM. Next, 50 highly contributing genes (HCGs) for classifying NF and DCM, 68 HCGs for classifying NF and ICM, and 59 HCGs for classifying DCM and ICM were selected for retraining ML models. Impressively, the retrained models achieved ~90% accuracy (RF) for NF vs. DCM, ~90% accuracy (pcaNNet) for NF vs. ICM, and ~85% accuracy (pcaNNet and RF) for DCM vs. ICM. Pathway analyses further confirmed the involvement of those selected HCGs in cardiac dysfunctions such as cardiomyopathies, cardiac hypertrophies, and fibrosis. Overall, our study demonstrates the promising potential of using artificial intelligence via ML modeling as a novel approach to achieve a greater level of precision in diagnosing different types of cardiomyopathies.