Muscle Sympathetic Nerve Activity Is Related to a Surrogate Marker of Endothelial Function in Healthy Individuals

BACKGROUND: Evidence from animal studies indicates the importance of an interaction between the sympathetic nervous system and the endothelium for cardiovascular regulation. However the interaction between these two systems remains largely unexplored in humans. The aim of this study was to investigate whether directly recorded sympathetic vasoconstrictor outflow is related to a surrogate marker of endothelial function in healthy individuals. METHODS AND RESULTS: In 10 healthy normotensive subjects (3 f/7 m), (age 37+/-11 yrs), (BMI 24+/-3 kg/m(2)) direct recordings of sympathetic action potentials to the muscle vascular bed (MSNA) were performed and endothelial function estimated with the Reactive Hyperaemia- Peripheral Arterial Tonometry (RH-PAT) technique. Blood samples were taken and time spent on leisure-time physical activities was estimated. In all subjects the rate between resting flow and the maximum flow, the Reactive Hyperemic index (RH-PAT index), was within the normal range (1.9-3.3) and MSNA was as expected for age and gender (13-44 burst/minute). RH-PAT index was inversely related to MSNA (r = -0.8, p = 0.005). RH-PAT index and MSNA were reciprocally related to time (h/week) spent on physical activity (p = 0.005 and p = 0.006 respectively) and platelet concentration (PLT) (p = 0.02 and p = 0.004 respectively). CONCLUSIONS: Our results show that sympathetic nerve activity is related to a surrogate marker of endothelial function in healthy normotensive individuals, indicating that sympathetic outflow may be modulated by changes in endothelial function. In this study time spent on physical activity is identified as a predictor of sympathetic nerve activity and endothelial function in a group of healthy individuals. The results are of importance in understanding mechanisms underlying sympathetic activation in conditions associated with endothelial dysfunction and emphasise the importance of a daily exercise routine for maintenance of cardiovascular health

The in vitro toxicology of Swedish snus

Three commercial brands of Swedish snus (SWS), an experimental SWS, and the 2S3 reference moist snuff were each tested in four in vitro toxicology assays. These assays were: Salmonella reverse mutation, mouse lymphoma, in vitro micronucleus, and cytotoxicity. Water extractions of each of the 5 products were tested using several different concentrations; the experimental SWS was also extracted using dimethyl sulfoxide (DMSO). Extraction procedures were verified by nicotine determinations. Results for SWS in the mutagenicity assays were broadly negative: there were occasional positive responses, but these were effectively at the highest concentration only (concentrations well above those suggested by regulatory guidelines), and were often associated with cytotoxicity. The 2S3 reference was unequivocally positive in one of the three conditions of the micronucleus assay (MNA), at the highest concentration only. Positive controls produced the expected responses in each assay. The SWS data are contrasted with data reported for combusted tobacco in the form of cigarettes, where strongly positive responses have been routinely reported for mutagenicity and cytotoxicity. These negative findings in a laboratory setting concur with the large amount of epidemiological data from Sweden, data showing that SWS are associated with considerably lower carcinogenic potential when compared with cigarettes

Bayesian methods for meta-analysis of causal relationships estimated using genetic instrumental variables.

Genetic markers can be used as instrumental variables, in an analogous way to randomization in a clinical trial, to estimate the causal relationship between a phenotype and an outcome variable. Our purpose is to extend the existing methods for such Mendelian randomization studies to the context of multiple genetic markers measured in multiple studies, based on the analysis of individual participant data. First, for a single genetic marker in one study, we show that the usual ratio of coefficients approach can be reformulated as a regression with heterogeneous error in the explanatory variable. This can be implemented using a Bayesian approach, which is next extended to include multiple genetic markers. We then propose a hierarchical model for undertaking a meta-analysis of multiple studies, in which it is not necessary that the same genetic markers are measured in each study. This provides an overall estimate of the causal relationship between the phenotype and the outcome, and an assessment of its heterogeneity across studies. As an example, we estimate the causal relationship of blood concentrations of C-reactive protein on fibrinogen levels using data from 11 studies. These methods provide a flexible framework for efficient estimation of causal relationships derived from multiple studies. Issues discussed include weak instrument bias, analysis of binary outcome data such as disease risk, missing genetic data, and the use of haplotypes.This is the accepted manuscript version. The final published version is available from Wiley at http://onlinelibrary.wiley.com/doi/10.1002/sim.3843/abstract;jsessionid=D83E836311AE8220A26CB4E7BFBF3DF1.f01t01

Genes Involved in Systemic and Arterial Bed Dependent Atherosclerosis - Tampere Vascular Study

BACKGROUND: Atherosclerosis is a complex disease with hundreds of genes influencing its progression. In addition, the phenotype of the disease varies significantly depending on the arterial bed. METHODOLOGY/PRINCIPAL FINDINGS: We characterized the genes generally involved in human advanced atherosclerotic (AHA type V-VI) plaques in carotid and femoral arteries as well as aortas from 24 subjects of Tampere Vascular study and compared the results to non-atherosclerotic internal thoracic arteries (n=6) using genome-wide expression array and QRT-PCR. In addition we determined genes that were typical for each arterial plaque studied. To gain a comprehensive insight into the pathologic processes in the plaques we also analyzed pathways and gene sets dysregulated in this disease using gene set enrichment analysis (GSEA). According to the selection criteria used (>3.0 fold change and p-value <0.05), 235 genes were up-regulated and 68 genes down-regulated in the carotid plaques, 242 genes up-regulated and 116 down-regulated in the femoral plaques and 256 genes up-regulated and 49 genes down-regulated in the aortic plaques. Nine genes were found to be specifically induced predominantly in aortic plaques, e.g., lactoferrin, and three genes in femoral plaques, e.g., chondroadherin, whereas no gene was found to be specific for carotid plaques. In pathway analysis, a total of 28 pathways or gene sets were found to be significantly dysregulated in atherosclerotic plaques (false discovery rate [FDR] <0.25). CONCLUSIONS: This study describes comprehensively the gene expression changes that generally prevail in human atherosclerotic plaques. In addition, site specific genes induced only in femoral or aortic plaques were found, reflecting that atherosclerotic process has unique features in different vascular beds

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

Background: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. Objectives: This study sought to systematically test if genetic variants identified for non-CAD diseases/traits also associate with CAD and to undertake a comprehensive analysis of the extent of pleiotropy of all CAD loci. Methods: In discovery analyses involving 42,335 CAD cases and 78,240 control subjects we tested the association of 29,383 common (minor allele frequency &gt;5%) single nucleotide polymorphisms available on the exome array, which included a substantial proportion of known or suspected single nucleotide polymorphisms associated with common diseases or traits as of 2011. Suggestive association signals were replicated in an additional 30,533 cases and 42,530 control subjects. To evaluate pleiotropy, we tested CAD loci for association with cardiovascular risk factors (lipid traits, blood pressure phenotypes, body mass index, diabetes, and smoking behavior), as well as with other diseases/traits through interrogation of currently available genome-wide association study catalogs. Results: We identified 6 new loci associated with CAD at genome-wide significance: on 2q37 (KCNJ13-GIGYF2), 6p21 (C2), 11p15 (MRVI1-CTR9), 12q13 (LRP1), 12q24 (SCARB1), and 16q13 (CETP). Risk allele frequencies ranged from 0.15 to 0.86, and odds ratio per copy of the risk allele ranged from 1.04 to 1.09. Of 62 new and known CAD loci, 24 (38.7%) showed statistical association with a traditional cardiovascular risk factor, with some showing multiple associations, and 29 (47%) showed associations at p &lt; 1 × 10−4 with a range of other diseases/traits. Conclusions: We identified 6 loci associated with CAD at genome-wide significance. Several CAD loci show substantial pleiotropy, which may help us understand the mechanisms by which these loci affect CAD risk

Pubertal high fat diet: effects on mammary cancer development

INTRODUCTION: Epidemiological studies linking dietary fat intake and obesity to breast cancer risk have produced inconsistent results. This may be due to the difficulty of dissociating fat intake from obesity, and/or the lack of defined periods of exposure in these studies. The pubertal mammary gland is highly sensitive to cancer-causing agents. We assessed how high fat diet (HFD) affects inflammation, proliferative, and developmental events in the pubertal gland, since dysregulation of these can promote mammary tumorigenesis. To test the effect of HFD initiated during puberty on tumorigenesis, we utilized BALB/c mice, for which HFD neither induces obesity nor metabolic syndrome, allowing dissociation of HFD effects from other conditions associated with HFD. METHODS: Pubertal BALB/c mice were fed a low fat diet (12% kcal fat) or a HFD (60% kcal fat), and subjected to carcinogen 7,12-dimethylbenz[a]anthracene (DMBA)-induced tumorigenesis. RESULTS: HFD elevated mammary gland expression of inflammatory and growth factor genes at 3 and 4 weeks of diet. Receptor activator of nuclear factor kappa-B ligand (RANKL), robustly induced at 4 weeks, has direct mitogenic activity in mammary epithelial cells and, as a potent inducer of NF-κB activity, may induce inflammatory genes. Three weeks of HFD induced a transient influx of eosinophils into the mammary gland, consistent with elevated inflammatory factors. At 10 weeks, prior to the appearance of palpable tumors, there were increased numbers of abnormal mammary epithelial lesions, enhanced cellular proliferation, increased growth factors, chemokines associated with immune-suppressive regulatory T cells, increased vascularization, and elevated M2 macrophages. HFD dramatically reduced tumor latency. Early developing tumors were more proliferative and were associated with increased levels of tumor-related growth factors, including increased plasma levels of HGF in tumor-bearing animals. Early HFD tumors also had increased vascularization, and more intra-tumor and stromal M2 macrophages. CONCLUSIONS: Taken together in this non-obesogenic context, HFD promotion of inflammatory processes, as well as local and systemically increased growth factor expression, are likely responsible for the enhanced tumorigenesis. It is noteworthy that although DMBA mutagenesis is virtually random in its targeting of genes in tumorigenesis, the short latency tumors arising in animals on HFD showed a unique gene expression profile, highlighting the potent overarching influence of HFD

Exome Chip Meta-analysis Fine Maps Causal Variants and Elucidates the Genetic Architecture of Rare Coding Variants in Smoking and Alcohol Use

BACKGROUND: Smoking and alcohol use have been associated with common genetic variants in multiple loci. Rare variants within these loci hold promise in the identification of biological mechanisms in substance use. Exome arrays and genotype imputation can now efficiently genotype rare nonsynonymous and loss of function variants. Such variants are expected to have deleterious functional consequences and to contribute to disease risk. METHODS: We analyzed similar to 250,000 rare variants from 16 independent studies genotyped with exome arrays and augmented this dataset with imputed data from the UK Biobank. Associations were tested for five phenotypes: cigarettes per day, pack-years, smoking initiation, age of smoking initiation, and alcoholic drinks per week. We conducted stratified heritability analyses, single-variant tests, and gene-based burden tests of nonsynonymous/loss-of-function coding variants. We performed a novel fine-mapping analysis to winnow the number of putative causal variants within associated loci. RESULTS: Meta-analytic sample sizes ranged from 152,348 to 433,216, depending on the phenotype. Rare coding variation explained 1.1% to 2.2% of phenotypic variance, reflecting 11% to 18% of the total single nucleotide polymorphism heritability of these phenotypes. We identified 171 genome-wide associated loci across all phenotypes. Fine mapping identified putative causal variants with double base-pair resolution at 24 of these loci, and between three and 10 variants for 65 loci. Twenty loci contained rare coding variants in the 95% credible intervals. CONCLUSIONS: Rare coding variation significantly contributes to the heritability of smoking and alcohol use. Fine-mapping genome-wide association study loci identifies specific variants contributing to the biological etiology of substance use behavior.Peer reviewe

Meta-analysis of up to 622,409 individuals identifies 40 novel smoking behaviour associated genetic loci

Smoking is a major heritable and modifiable risk factor for many diseases, including cancer, common respiratory disorders and cardiovascular diseases. Fourteen genetic loci have previously been associated with smoking behaviour-related traits. We tested up to 235,116 single nucleotide variants (SNVs) on the exome-array for association with smoking initiation, cigarettes per day, pack-years, and smoking cessation in a fixed effects meta-analysis of up to 61 studies (up to 346,813 participants). In a subset of 112,811 participants, a further one million SNVs were also genotyped and tested for association with the four smoking behaviour traits. SNV-trait associations withP <5 x 10(-8)in either analysis were taken forward for replication in up to 275,596 independent participants from UK Biobank. Lastly, a meta-analysis of the discovery and replication studies was performed. Sixteen SNVs were associated with at least one of the smoking behaviour traits (P <5 x 10(-8)) in the discovery samples. Ten novel SNVs, including rs12616219 nearTMEM182, were followed-up and five of them (rs462779 inREV3L, rs12780116 inCNNM2, rs1190736 inGPR101, rs11539157 inPJA1, and rs12616219 nearTMEM182) replicated at a Bonferroni significance threshold (P <4.5 x 10(-3)) with consistent direction of effect. A further 35 SNVs were associated with smoking behaviour traits in the discovery plus replication meta-analysis (up to 622,409 participants) including a rare SNV, rs150493199, inCCDC141and two low-frequency SNVs inCEP350andHDGFRP2. Functional follow-up implied that decreased expression ofREV3Lmay lower the probability of smoking initiation. The novel loci will facilitate understanding the genetic aetiology of smoking behaviour and may lead to the identification of potential drug targets for smoking prevention and/or cessation.Peer reviewe

Use of Repeated Blood Pressure and Cholesterol Measurements to Improve Cardiovascular Disease Risk Prediction: An Individual-Participant-Data Meta-Analysis

The added value of incorporating information from repeated measurements of blood pressure and cholesterol for cardiovascular disease (CVD) risk prediction has not been rigorously assessed. We used data from the Emerging Risk Factors Collaboration on 191,445 adults (38 cohorts from across 17 countries with data from 1962-2014) with > 1 million measurements of systolic blood pressure, total cholesterol and high-density lipoprotein cholesterol; over a median 12 years of follow-up, 21,170 CVD events occurred. Risk prediction models using cumulative means of repeated measurements and summary measures from longitudinal modelling of the repeated measurements were compared to models using measurements from a single time point. Risk discrimination (C-index) and net reclassification were calculated, and changes in C-indices were meta-analysed across studies. Compared to the single time point model, the cumulative means and the longitudinal models increased the C-index by 0.0040 (95% CI: 0.0023, 0.0057) and 0.0023 (0.0005, 0.0042), respectively. Reclassification was also improved in both models; compared to the single time point model, overall net reclassification improvements were 0.0369 (0.0303, 0.0436) for the cumulative means model and 0.0177 (0.0110, 0.0243) for the longitudinal model. In conclusion, incorporating repeated measurements of blood pressure and cholesterol into CVD risk prediction models slightly improves risk prediction