Defining left ventricular remodeling using lean body mass allometry: a UK Biobank study.

PURPOSE: The geometric patterns of ventricular remodeling are determined using indexed left ventricular mass (LVM), end-diastolic volume (LVEDV) and concentricity, most often measured using the mass-to-volume ratio (MVR). The aims of this study were to validate lean body mass (LBM)-based allometric coefficients for scaling and to determine an index of concentricity that is independent of both volume and LBM. METHODS: Participants from the UK Biobank who underwent both CMR and dual-energy X-ray absorptiometry (DXA) during 2014-2015 were considered (n = 5064). We excluded participants aged ≥ 70 years or those with cardiometabolic risk factors. We determined allometric coefficients for scaling using linear regression of the logarithmically transformed ventricular remodeling parameters. We further defined a multiplicative allometric relationship for LV concentricity (LVC) adjusting for both LVEDV and LBM. RESULTS: A total of 1638 individuals (1057 female) were included. In subjects with lower body fat percentage (< 25% in males, < 35% in females, n = 644), the LBM allometric coefficients for scaling LVM and LVEDV were 0.85 ± 0.06 and 0.85 ± 0.03 respectively (R2 = 0.61 and 0.57, P < 0.001), with no evidence of sex-allometry interaction. While the MVR was independent of LBM, it demonstrated a negative association with LVEDV in (females: r = - 0.44, P < 0.001; males: - 0.38, P < 0.001). In contrast, LVC was independent of both LVEDV and LBM [LVC = LVM/(LVEDV0.40 × LBM0.50)] leading to increased overlap between LV hypertrophy and higher concentricity. CONCLUSIONS: We validated allometric coefficients for LBM-based scaling for CMR indexed parameters relevant for classifying geometric patterns of ventricular remodeling.

Integration of genetic colocalizations with physiological and pharmacological perturbations identifies cardiometabolic disease genes.

BACKGROUND: Identification of causal genes for polygenic human diseases has been extremely challenging, and our understanding of how physiological and pharmacological stimuli modulate genetic risk at disease-associated loci is limited. Specifically, insulin resistance (IR), a common feature of cardiometabolic disease, including type 2 diabetes, obesity, and dyslipidemia, lacks well-powered genome-wide association studies (GWAS), and therefore, few associated loci and causal genes have been identified. METHODS: Here, we perform and integrate linkage disequilibrium (LD)-adjusted colocalization analyses across nine cardiometabolic traits (fasting insulin, fasting glucose, insulin sensitivity, insulin sensitivity index, type 2 diabetes, triglycerides, high-density lipoprotein, body mass index, and waist-hip ratio) combined with expression and splicing quantitative trait loci (eQTLs and sQTLs) from five metabolically relevant human tissues (subcutaneous and visceral adipose, skeletal muscle, liver, and pancreas). To elucidate the upstream regulators and functional mechanisms for these genes, we integrate their transcriptional responses to 21 relevant physiological and pharmacological perturbations in human adipocytes, hepatocytes, and skeletal muscle cells and map their protein-protein interactions. RESULTS: We identify 470 colocalized loci and prioritize 207 loci with a single colocalized gene. Patterns of shared colocalizations across traits and tissues highlight different potential roles for colocalized genes in cardiometabolic disease and distinguish several genes involved in pancreatic ß-cell function from others with a more direct role in skeletal muscle, liver, and adipose tissues. At the loci with a single colocalized gene, 42 of these genes were regulated by insulin and 35 by glucose in perturbation experiments, including 17 regulated by both. Other metabolic perturbations regulated the expression of 30 more genes not regulated by glucose or insulin, pointing to other potential upstream regulators of candidate causal genes. CONCLUSIONS: Our use of transcriptional responses under metabolic perturbations to contextualize genetic associations from our custom colocalization approach provides a list of likely causal genes and their upstream regulators in the context of IR-associated cardiometabolic risk.

A genome-wide association study in a large community-based cohort identifies multiple loci associated with susceptibility to bacterial and viral infections.

There is limited data on host-specific genetic determinants of susceptibility to bacterial and viral infections. Genome-wide association studies using large population cohorts can be a first step towards identifying patients prone to infectious diseases and targets for new therapies. Genetic variants associated with clinically relevant entities of bacterial and viral infections (e.g., abdominal infections, respiratory infections, and sepsis) in 337,484 participants of the UK Biobank cohort were explored by genome-wide association analyses. Cases (n = 81,179) were identified based on ICD-10 diagnosis codes of hospital inpatient and death registries. Functional annotation was performed using gene expression (eQTL) data. Fifty-seven unique genome-wide significant loci were found, many of which are novel in the context of infectious diseases. Some of the detected genetic variants were previously reported associated with infectious, inflammatory, autoimmune, and malignant diseases or key components of the immune system (e.g., white blood cells, cytokines). Fine mapping of the HLA region revealed significant associations with HLA-DQA1, HLA-DRB1, and HLA-DRB4 locus alleles. PPP1R14A showed strong colocalization with abdominal infections and gene expression in sigmoid and transverse colon, suggesting causality. Shared significant loci across infections and non-infectious phenotypes in the UK Biobank cohort were found, suggesting associations for example between SNPs identified for abdominal infections and CRP, rheumatoid arthritis, and diabetes mellitus. We report multiple loci associated with bacterial and viral infections. A better understanding of the genetic determinants of bacterial and viral infections can be useful to identify patients at risk and in the development of new drugs.

Alcohol use and cardiometabolic risk in the UK Biobank: A Mendelian randomization study.

Observational studies suggest alcohol use promotes the development of some adverse cardiometabolic traits but protects against others including outcomes related to coronary artery disease. We used Mendelian randomization (MR) to explore causal relationships between the degree of alcohol consumption and several cardiometabolic traits in the UK Biobank. Using the well-established ADH1B Arg47His variant (rs1229984) and up to 24 additional SNPs recently found to be associated with alcohol consumption in an independent dataset as instruments, we conducted two-stage least squares and inverse weighted variance MR analyses, both as one-sample analyses in the UK Biobank and as two-sample analyses in external consortia. In the UK Biobank inverse variance weighted analyses, we found that one additional drink of alcohol per day was positively associated with systolic blood pressure (beta = 2.65 mmHg [1.40, 3.89]), hemorrhagic stroke (OR = 2.25 [1.41, 3.60]), and atrial fibrillation (OR = 1.26 [1.07, 1.48]), which were replicated in multivariable analyses. Alcohol was also associated with all cardiovascular disease and all-cause death. A positive association with myocardial infarction did not replicate in multivariable analysis, with suggestive mediation through blood pressure; similarly, a positive association between alcohol use with type 2 diabetes was mitigated by BMI in multivariable analysis. Findings were generally null in replication with two-sample analyses. Alcohol was not protective for any disease outcome with any analysis method, dataset, or strata. Stratifications by sex and smoking in the UK Biobank revealed higher point estimates of risk for several outcomes for men and mixed results for smoking strata, but no statistically significant heterogeneity. Our results are consistent with an overall harmful and/or null effect of alcohol on cardiometabolic health at all levels of use and suggest that even moderate alcohol use should not be promoted as a part of a healthy diet and lifestyle.

Clinical Conditions and Their Impact on Utility of Genetic Scores for Prediction of Acute Coronary Syndrome.

BACKGROUND: Acute coronary syndrome (ACS) is a clinically significant presentation of coronary heart disease. Genetic information has been proposed to improve prediction beyond well-established clinical risk factors. While polygenic scores (PS) can capture an individual's genetic risk for ACS, its prediction performance may vary in the context of diverse correlated clinical conditions. Here, we aimed to test whether clinical conditions impact the association between PS and ACS. METHODS: We explored the association between 405 clinical conditions diagnosed before baseline and 9080 incident cases of ACS in 387 832 individuals from the UK Biobank. Results were replicated in 6430 incident cases of ACS in 177 876 individuals from FinnGen. RESULTS: We identified 80 conventional (eg, stable angina pectoris and type 2 diabetes) and unconventional (eg, diaphragmatic hernia and inguinal hernia) associations with ACS. The association between PS and ACS was consistent in individuals with and without most clinical conditions. However, a diagnosis of stable angina pectoris yielded a differential association between PS and ACS. PS was associated with a significantly reduced (interaction P=2.87×10-8) risk for ACS in individuals with stable angina pectoris (hazard ratio, 1.163 [95% CI, 1.082-1.251]) compared with individuals without stable angina pectoris (hazard ratio, 1.531 [95% CI, 1.497-1.565]). These findings were replicated in FinnGen (interaction P=1.38×10-6). CONCLUSIONS: In summary, while most clinical conditions did not impact utility of PS for prediction of ACS, we found that PS was substantially less predictive of ACS in individuals with prevalent stable coronary heart disease. PS may be more appropriate for prediction of ACS in asymptomatic individuals than symptomatic individuals with clinical suspicion for coronary heart disease.

Fatty Liver Index and Development of Cardiovascular Disease: Findings from the UK Biobank.

BACKGROUND: Nonalcoholic fatty liver disease is common and is associated with rising morbidity and mortality in the UK. Cardiovascular disease is the main cause of death in people with nonalcoholic fatty liver disease. AIMS: To determine the association between baseline cardiovascular risk factors with fatty liver index, and to investigate the association between fatty liver index and the incidence of cardiovascular disease in the UK. METHODS: This study is a population-based retrospective cohort study using the UK Biobank database. RESULTS: The mean fatty liver index in the study cohort was 44.9, and 33.7% met the criteria for nonalcoholic fatty liver disease. Fatty liver index was significantly associated with a wide range of cardiovascular risk factors at baseline. During a mean follow-up of 7.86 years, the combined incidence of cardiovascular disease was 6.92 per 1000-person years at risk. We found significant association between fatty liver index and incident cardiovascular disease in the fully adjusted model. We found significant association between fatty liver index and incident cardiovascular disease in subgroups stratified by BMI as well as subgroups with fatty liver index < 30, < 60, and ≥ 60. CONCLUSIONS: Fatty liver index not only predicts NAFLD diagnosis, but also indicates baseline and future development of cardiovascular disease on long-term follow-up across weight categories and fatty liver index spectrum. These findings can inform clinicians and other stakeholders on cardiovascular disease management and preventive efforts. Patients with high fatty liver index should be counseled on the increased future risk of developing cardiovascular disease.

Genetics of Smoking and Risk of Atherosclerotic Cardiovascular Diseases: A Mendelian Randomization Study.

Importance: Smoking is associated with atherosclerotic cardiovascular disease, but the relative contribution to each subtype (coronary artery disease [CAD], peripheral artery disease [PAD], and large-artery stroke) remains less well understood. Objective: To determine the association between genetic liability to smoking and risk of CAD, PAD, and large-artery stroke. Design, Setting, and Participants: Mendelian randomization study using summary statistics from genome-wide associations of smoking (UK Biobank; up to 462 690 individuals), CAD (Coronary Artery Disease Genome Wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics Consortium; up to 60 801 cases, 123 504 controls), PAD (VA Million Veteran Program; up to 24 009 cases, 150 983 controls), and large-artery stroke (MEGASTROKE; up to 4373 cases, 406 111 controls). This study was conducted using summary statistic data from large, previously described cohorts. Review of those publications does not reveal the total recruitment dates for those cohorts. Data analyses were conducted from August 2019 to June 2020. Exposures: Genetic liability to smoking (as proxied by genetic variants associated with lifetime smoking index). Main Outcomes and Measures: Risk (odds ratios [ORs]) of CAD, PAD, and large-artery stroke. Results: Genetic liability to smoking was associated with increased risk of PAD (OR, 2.13; 95% CI, 1.78-2.56; P = 3.6 × 10-16), CAD (OR, 1.48; 95% CI, 1.25-1.75; P = 4.4 × 10-6), and stroke (OR, 1.40; 95% CI, 1.02-1.92; P = .04). Genetic liability to smoking was associated with greater risk of PAD than risk of large-artery stroke (ratio of ORs, 1.52; 95% CI, 1.05-2.19; P = .02) or CAD (ratio of ORs, 1.44; 95% CI, 1.12-1.84; P = .004). The association between genetic liability to smoking and atherosclerotic cardiovascular diseases remained independent from the effects of smoking on traditional cardiovascular risk factors. Conclusions and Relevance: In this mendelian randomization analysis of data from large studies of atherosclerotic cardiovascular diseases, genetic liability to smoking was a strong risk factor for CAD, PAD, and stroke, although the estimated association was strongest between smoking and PAD. The association between smoking and atherosclerotic cardiovascular disease was independent of traditional cardiovascular risk factors.

Plasma proteomics and lung function in four community-based cohorts.

BACKGROUND: Underlying mechanism leading to impaired lung function are incompletely understood. OBJECTIVES: To investigate whether protein profiling can provide novel insights into mechanisms leading to impaired lung function. METHODS: We used four community-based studies (n = 2552) to investigate associations between 79 cardiovascular/inflammatory proteins and forced expiratory volume in 1 s percent predicted (FEV1%) assessed by spirometry. We divided the cohorts into discovery and replication samples and used risk factor-adjusted linear regression corrected for multiple comparison (false discovery rate of 5%). We performed Mendelian randomization analyses using genetic and spirometry data from the UK Biobank (n = 421,986) to assess causality. MEASUREMENTS AND MAIN RESULTS: In cross-sectional analysis, 22 proteins were associated with lower FEV1% in both the discovery and replication sample, regardless of stratification by smoking status. The combined proteomic data cumulatively explained 5% of the variation in FEV1%. In longitudinal analyses (n = 681), higher plasma levels of growth differentiation factor 15 (GDF-15) and interleukin 6 (IL-6) predicted a more rapid 5-year decline in lung function (change in FEV1% per standard deviation of protein level -1.4, (95% CI, -2.5 to -0.3) for GDF-15, and -0.8, (95% CI, -1.5 to -0.2) for IL-6. Mendelian randomization analysis in UK-biobank provided support for a causal effect of increased GDF-15 levels and reduced FEV1%. CONCLUSIONS: Our combined approach identified GDF-15 as a potential causal factor in the development of impaired lung function in the general population. These findings encourage additional studies evaluating the role of GDF-15 as a causal factor for impaired lung function.

Genetic Predisposition to Coronary Artery Disease in Type 2 Diabetes Mellitus.

BACKGROUND: Coronary artery disease (CAD) is accelerated in subjects with type 2 diabetes mellitus (T2D). METHODS: To test whether this reflects differential genetic influences on CAD risk in subjects with T2D, we performed a systematic assessment of genetic overlap between CAD and T2D in 66 643 subjects (27 708 with CAD and 24 259 with T2D). Variants showing apparent association with CAD in stratified analyses or evidence of interaction were evaluated in a further 117 787 subjects (16 694 with CAD and 11 537 with T2D). RESULTS: None of the previously characterized CAD loci was found to have specific effects on CAD in T2D individuals, and a genome-wide interaction analysis found no new variants for CAD that could be considered T2D specific. When we considered the overall genetic correlations between CAD and its risk factors, we found no substantial differences in these relationships by T2D background. CONCLUSIONS: This study found no evidence that the genetic architecture of CAD differs in those with T2D compared with those without T2D.

A phenome-wide association study of 26 mendelian genes reveals phenotypic expressivity of common and rare variants within the general population.

The clinical evaluation of a genetic syndrome relies upon recognition of a characteristic pattern of signs or symptoms to guide targeted genetic testing for confirmation of the diagnosis. However, individuals displaying a single phenotype of a complex syndrome may not meet criteria for clinical diagnosis or genetic testing. Here, we present a phenome-wide association study (PheWAS) approach to systematically explore the phenotypic expressivity of common and rare alleles in genes associated with four well-described syndromic diseases (Alagille (AS), Marfan (MS), DiGeorge (DS), and Noonan (NS) syndromes) in the general population. Using human phenotype ontology (HPO) terms, we systematically mapped 60 phenotypes related to AS, MS, DS and NS in 337,198 unrelated white British from the UK Biobank (UKBB) based on their hospital admission records, self-administrated questionnaires, and physiological measurements. We performed logistic regression adjusting for age, sex, and the first 5 genetic principal components, for each phenotype and each variant in the target genes (JAG1, NOTCH2 FBN1, PTPN1 and RAS-opathy genes, and genes in the 22q11.2 locus) and performed a gene burden test. Overall, we observed multiple phenotype-genotype correlations, such as the association between variation in JAG1, FBN1, PTPN11 and SOS2 with diastolic and systolic blood pressure; and pleiotropy among multiple variants in syndromic genes. For example, rs11066309 in PTPN11 was significantly associated with a lower body mass index, an increased risk of hypothyroidism and a smaller size for gestational age, all in concordance with NS-related phenotypes. Similarly, rs589668 in FBN1 was associated with an increase in body height and blood pressure, and a reduced body fat percentage as observed in Marfan syndrome. Our findings suggest that the spectrum of associations of common and rare variants in genes involved in syndromic diseases can be extended to individual phenotypes within the general population.

Commonly used clinical chemistry tests as mortality predictors: Results from two large cohort studies.

BACKGROUND: The normal ranges for clinical chemistry tests are usually defined by cut-offs given by the distribution in healthy individuals. This approach does however not indicate if individuals outside the normal range are more prone to disease. METHODS: We studied the associations and risk prediction of 11 plasma and serum biomarkers with all-cause mortality in two population-based cohorts: a Swedish cohort (X69) initiated in 1969, and the UK Biobank (UKB) initiated in 2006-2010, with up to 48- and 9-years follow-up, respectively. RESULTS: In X69 and in UKB, 18,529 and 425,264 individuals were investigated, respectively. During the follow-up time, 14,475 deaths occurred in X69 and 17,116 in UKB. All evaluated tests were associated with mortality in X69 (P<0.0001, except bilirubin P<0.005). For calcium, blood urea nitrogen, bilirubin, hematocrit, uric acid, and iron, U-shaped associations were seen (P<0.0001). For leukocyte count, gamma-glutamyl transferase, alkaline phosphatases and lactate dehydrogenase, linear positive associations were seen, while for albumin the association was negative. Similar associations were seen in UKB. Addition of all biomarkers to a model with classical risk factors improved mortality prediction (delta C-statistics: +0.009 in X69 and +0.023 in UKB, P<0.00001 in both cohorts). CONCLUSIONS: Commonly used clinical chemistry tests were associated with all-cause mortality both in the medium- and long-term perspective, and improved mortality prediction beyond classical risk factors. Since both linear and U-shaped relationships were found, we propose to define the normal range of a clinical chemistry test based on its association with mortality, rather than from the distribution.

Non-targeted urine metabolomics and associations with prevalent and incident type 2 diabetes.

Better risk prediction and new molecular targets are key priorities in type 2 diabetes (T2D) research. Little is known about the role of the urine metabolome in predicting the risk of T2D. We aimed to use non-targeted urine metabolomics to discover biomarkers and improve risk prediction for T2D. Urine samples from two community cohorts of 1,424 adults were analyzed by ultra-performance liquid chromatography/mass spectrometry (UPLC-MS). In a discovery/replication design, three out of 62 annotated metabolites were associated with prevalent T2D, notably lower urine levels of 3-hydroxyundecanoyl-carnitine. In participants without diabetes at baseline, LASSO regression in the training set selected six metabolites that improved prediction of T2D beyond established risk factors risk over up to 12 years' follow-up in the test sample, from C-statistic 0.866 to 0.892. Our results in one of the largest non-targeted urinary metabolomics study to date demonstrate the role of the urine metabolome in identifying at-risk persons for T2D and suggest urine 3-hydroxyundecanoyl-carnitine as a biomarker candidate.

Comprehensive Investigation of Circulating Biomarkers and Their Causal Role in Atherosclerosis-Related Risk Factors and Clinical Events.

BACKGROUND: Circulating biomarkers have been previously associated with atherosclerosis-related risk factors, but the nature of these associations is incompletely understood. METHODS: We performed multivariable-adjusted regressions and 2-sample Mendelian randomization analyses to assess observational and causal associations of 27 circulating biomarkers with 7 cardiovascular traits in up to 451 933 participants of the UK Biobank. RESULTS: After multiple-testing correction (alpha=1.3×10-4), we found a total of 15, 9, 21, 22, 26, 24, and 26 biomarkers strongly associated with coronary artery disease, ischemic stroke, atrial fibrillation, type 2 diabetes, systolic blood pressure, body mass index, and waist-to-hip ratio; respectively. The Mendelian randomization analyses confirmed strong evidence of previously suggested causal associations for several glucose- and lipid-related biomarkers with type 2 diabetes and coronary artery disease. Particularly interesting findings included a protective role of IGF-1 (insulin-like growth factor 1) in systolic blood pressure, and the strong causal association of lipoprotein(a) in coronary artery disease development (ß, -0.13; per SD change in exposure and outcome and odds ratio, 1.28; P=2.6×10-4 and P=7.4×10-35, respectively). In addition, our results indicated a causal role of increased ALT (alanine aminotransferase) in the development of type 2 diabetes and hypertension (odds ratio, 1.59 and ß, 0.06, per SD change in exposure and outcome; P=4.8×10-11 and P=6.0×10-5). Our results suggest that it is unlikely that CRP (C-reactive protein) and vitamin D play causal roles of any meaningful magnitude in development of cardiometabolic disease. CONCLUSIONS: We confirmed and extended known associations and reported several novel causal associations providing important insights about the cause of these diseases, which can help accelerate new prevention strategies.

Adults With Mild-to-Moderate Congenital Heart Disease Demonstrate Measurable Neurocognitive Deficits.

Background Neurocognitive impairment is a common complication of congenital heart disease (CHD) as well as acquired cardiovascular disease. Data are limited on neurocognitive function in adults with CHD (ACHD). Methods and Results A total of 1020 individuals with mild-to-moderate ACHD and 497 987 individuals without ACHD from the volunteer-based UK Biobank study underwent neurocognitive tests for fluid intelligence, reaction time, numeric memory, symbol-digit substitution, and trail making at enrollment and follow-up. Performance scores were compared before and after exclusion of preexisting stroke or coronary artery disease as measures of cerebro- and cardiovascular disease. Individuals with ACHD had significantly poorer performance on alpha-numeric trail making, a measure of visual attention and cognitive flexibility, spending 6.4 seconds longer on alpha-numeric trail making (95% CI, 3.0-9.9 seconds, P=0.002) and 2.5 seconds longer on numeric trail making (95% CI, 0.5-4.6 seconds, P=0.034), a measure of visual attention and processing speed. The ACHD cohort had modestly lower performance on symbol-digit substitution, a measure of processing speed, with 0.9 fewer correct substitutions (95% CI, - 1.5 to - 0.2 substitutions, P=0.021). After excluding preexisting stroke or coronary artery disease, individuals with ACHD continued to show poorer performance in all 6 domains (P=NS). Conclusions Individuals with mild-to-moderate ACHD had poorer neurocognitive performance, most significantly in tests of cognitive flexibility, analogous to deficits in children with CHD. These differences appear to be driven by increased burden of cerebro- and cardiovascular disease among individuals with ACHD.

Translating GWAS-identified loci for cardiac rhythm and rate using an in vivo image- and CRISPR/Cas9-based approach.

A meta-analysis of genome-wide association studies (GWAS) identified eight loci that are associated with heart rate variability (HRV), but candidate genes in these loci remain uncharacterized. We developed an image- and CRISPR/Cas9-based pipeline to systematically characterize candidate genes for HRV in live zebrafish embryos. Nine zebrafish orthologues of six human candidate genes were targeted simultaneously in eggs from fish that transgenically express GFP on smooth muscle cells (Tg[acta2:GFP]), to visualize the beating heart. An automated analysis of repeated 30 s recordings of beating atria in 381 live, intact zebrafish embryos at 2 and 5 days post-fertilization highlighted genes that influence HRV (hcn4 and si:dkey-65j6.2 [KIAA1755]); heart rate (rgs6 and hcn4); and the risk of sinoatrial pauses and arrests (hcn4). Exposure to 10 or 25 µM ivabradine-an open channel blocker of HCNs-for 24 h resulted in a dose-dependent higher HRV and lower heart rate at 5 days post-fertilization. Hence, our screen confirmed the role of established genes for heart rate and rhythm (RGS6 and HCN4); showed that ivabradine reduces heart rate and increases HRV in zebrafish embryos, as it does in humans; and highlighted a novel gene that plays a role in HRV (KIAA1755).

Development and validation of risk prediction models for multiple cardiovascular diseases and Type 2 diabetes.

Accurate risk assessment of an individuals' propensity to develop cardiovascular diseases (CVDs) is crucial for the prevention of these conditions. Numerous published risk prediction models used for CVD risk assessment are based on conventional risk factors and include only a limited number of biomarkers. The addition of novel biomarkers can boost the discriminative ability of risk prediction models for CVDs with different pathogenesis. The present study reports the development of risk prediction models for a range of heterogeneous CVDs, including coronary artery disease (CAD), stroke, deep vein thrombosis (DVT), and abdominal aortic aneurysm (AAA), as well as for Type 2 diabetes mellitus (DM2), a major CVD risk factor. In addition to conventional risk factors, the models incorporate various blood biomarkers and comorbidities to improve both individual and population stratification. An automatic variable selection approach was developed to generate the best set of explanatory variables for each model from the initial panel of risk factors. In total, up to 254,220 UK Biobank participants (ranging from 215,269 to 254,220 for different CVDs and DM2) were included in the analyses. The derived prediction models utilizing Cox proportional hazards regression achieved consistent discrimination performance (C-index) for all diseases: CAD, 0.794 (95% CI, 0.787-0.801); DM2, 0.909 (95% CI, 0.903-0.916); stroke, 0.778 (95% CI, 0.756-0.801); DVT, 0.743 (95% CI, 0.737-0.749); and AAA, 0.893 (95% CI, 0.874-0.912). When validated on various subpopulations, they demonstrated higher discrimination in healthier and middle-age individuals. In general, calibration of a five-year risk of developing the CVDs and DM2 demonstrated incremental overestimation of disease-related conditions amongst the highest decile of risk probabilities. In summary, the risk prediction models described were validated with high discrimination and good calibration for several CVDs and DM2. These models incorporate multiple shared predictor variables and may be integrated into a single platform to enhance clinical stratification to impact health outcomes.

Clonally expanding smooth muscle cells promote atherosclerosis by escaping efferocytosis and activating the complement cascade.

Atherosclerosis is the process underlying heart attack and stroke. Despite decades of research, its pathogenesis remains unclear. Dogma suggests that atherosclerotic plaques expand primarily via the accumulation of cholesterol and inflammatory cells. However, recent evidence suggests that a substantial portion of the plaque may arise from a subset of "dedifferentiated" vascular smooth muscle cells (SMCs) which proliferate in a clonal fashion. Herein we use multicolor lineage-tracing models to confirm that the mature SMC can give rise to a hyperproliferative cell which appears to promote inflammation via elaboration of complement-dependent anaphylatoxins. Despite being extensively opsonized with prophagocytic complement fragments, we find that this cell also escapes immune surveillance by neighboring macrophages, thereby exacerbating its relative survival advantage. Mechanistic studies indicate this phenomenon results from a generalized opsonin-sensing defect acquired by macrophages during polarization. This defect coincides with the noncanonical up-regulation of so-called don't eat me molecules on inflamed phagocytes, which reduces their capacity for programmed cell removal (PrCR). Knockdown or knockout of the key antiphagocytic molecule CD47 restores the ability of macrophages to sense and clear opsonized targets in vitro, allowing for potent and targeted suppression of clonal SMC expansion in the plaque in vivo. Because integrated clinical and genomic analyses indicate that similar pathways are active in humans with cardiovascular disease, these studies suggest that the clonally expanding SMC may represent a translational target for treating atherosclerosis.

Multi-ancestry GWAS of the electrocardiographic PR interval identifies 202 loci underlying cardiac conduction.

The electrocardiographic PR interval reflects atrioventricular conduction, and is associated with conduction abnormalities, pacemaker implantation, atrial fibrillation (AF), and cardiovascular mortality. Here we report a multi-ancestry (N = 293,051) genome-wide association meta-analysis for the PR interval, discovering 202 loci of which 141 have not previously been reported. Variants at identified loci increase the percentage of heritability explained, from 33.5% to 62.6%. We observe enrichment for cardiac muscle developmental/contractile and cytoskeletal genes, highlighting key regulation processes for atrioventricular conduction. Additionally, 8 loci not previously reported harbor genes underlying inherited arrhythmic syndromes and/or cardiomyopathies suggesting a role for these genes in cardiovascular pathology in the general population. We show that polygenic predisposition to PR interval duration is an endophenotype for cardiovascular disease, including distal conduction disease, AF, and atrioventricular pre-excitation. These findings advance our understanding of the polygenic basis of cardiac conduction, and the genetic relationship between PR interval duration and cardiovascular disease.

Proteomic profiles before and during weight loss: Results from randomized trial of dietary intervention.

Inflammatory and cardiovascular biomarkers have been associated with obesity, but little is known about how they change upon dietary intervention and concomitant weight loss. Further, protein biomarkers might be useful for predicting weight loss in overweight and obese individuals. We performed secondary analyses in the Diet Intervention Examining The Factors Interacting with Treatment Success (DIETFITS) randomized intervention trial that included healthy 609 adults (18-50 years old) with BMI 28-40 kg/m2, to evaluate associations between circulating protein biomarkers and BMI at baseline, during a weight loss diet intervention, and to assess predictive potential of baseline blood proteins on weight loss. We analyzed 263 plasma proteins at baseline and 6 months into the intervention using the Olink Proteomics CVD II, CVD III and Inflammation arrays. BMI was assessed at baseline, after 3 and 6 months of dietary intervention. At baseline, 102 of the examined inflammatory and cardiovascular biomarkers were associated with BMI (>90% with successful replication in 1,584 overweight/obese individuals from a community-based cohort study) and 130 tracked with weight loss shedding light into the pathophysiology of obesity. However, out of 263 proteins analyzed at baseline, only fibroblast growth factor 21 (FGF-21) predicted weight loss, and none helped individualize dietary assignment.

Global Plasma Metabolomics to Identify Potential Biomarkers of Blood Pressure Progression.

OBJECTIVE: The pathophysiology of hypertension remains incompletely understood. We investigated associations of circulating metabolites with longitudinal blood pressure (BP) changes in the Prospective Investigation of the Vasculature in Uppsala Seniors cohort and validated the findings in the Uppsala Longitudinal Study of Adult Men cohort. Approach and Results: Circulating metabolite levels were assessed with liquid- and gas-chromatography coupled to mass spectrometry among persons without BP-lowering medication at baseline. We studied associations of baseline levels of metabolites with changes in BP levels and the clinical BP stage between baseline and a follow-up examination 5 years later. In the discovery cohort, we investigated 504 individuals that contributed with 757 observations of paired BP measurements. The mean baseline systolic and diastolic BPs were 144 (19.7)/76 (9.7) mm Hg, and change in systolic and diastolic BPs were 3.7 (15.8)/-0.5 (8.6) mm Hg over 5 years. The metabolites associated with diastolic BP change were ceramide, triacylglycerol, total glycerolipids, oleic acid, and cholesterylester. No associations with longitudinal changes in systolic BP or BP stage were observed. Metabolites with similar structures to the 5 top findings in the discovery cohort were investigated in the validation cohort. Diacylglycerol (36:2) and monoacylglycerol (18:0), 2 glycerolipids, were associated with diastolic BP change in the validation cohort. CONCLUSIONS: Circulating baseline levels of ceramide, triacylglycerol, total glycerolipids, and oleic acid were positively associated with longitudinal diastolic BP change, whereas cholesterylester levels were inversely associated with longitudinal diastolic BP change. Two glycerolipids were validated in an independent cohort. These metabolites may point towards pathophysiological pathways of hypertension.