Quantifying the relative importance of genetics and environment on the comorbidity between mental and cardiometabolic disorders using 17 million Scandinavians.

Mental disorders are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders. Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and near-complete genealogies of Denmark and Sweden (n = 17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six mental disorders and 15 cardiometabolic disorders. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with cardiometabolic disorders, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with cardiometabolic disorders was mainly or fully driven by environmental factors. In this work we provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

Predictive machine learning models for ascending aortic dilatation in patients with bicuspid and tricuspid aortic valves undergoing cardiothoracic surgery: a prospective, single-centre and observational study.

OBJECTIVES: The objective of this study was to develop clinical classifiers aiming to identify prevalent ascending aortic dilatation in patients with bicuspid aortic valve (BAV) and tricuspid aortic valve (TAV). DESIGN AND SETTING: A prospective, single-centre and observational cohort. PARTICIPANTS: The study involved 543 BAV and 491 TAV patients with aortic valve disease and/or ascending aortic dilatation, excluding those with coronary artery disease, undergoing cardiothoracic surgery at the Karolinska University Hospital (Sweden). MAIN OUTCOME MEASURES: Predictors of high risk of ascending aortic dilatation (defined as ascending aorta with a diameter above 40 mm) were identified through the application of machine learning algorithms and classic logistic regression models. EXPOSURES: Comprehensive multidimensional data, including valve morphology, clinical information, family history of cardiovascular diseases, prevalent diseases, demographic details, lifestyle factors, and medication. RESULTS: BAV patients, with an average age of 60.4±12.4 years, showed a higher frequency of aortic dilatation (45.3%) compared with TAV patients, who had an average age of 70.4±9.1 years (28.9% dilatation, p <0.001). Aneurysm prediction models for TAV patients exhibited mean area under the receiver-operating-characteristic curve (AUC) values above 0.8, with the absence of aortic stenosis being the primary predictor, followed by diabetes and high-sensitivity C reactive protein. Conversely, prediction models for BAV patients resulted in AUC values between 0.5 and 0.55, indicating low usefulness for predicting aortic dilatation. Classification results remained consistent across all machine learning algorithms and classic logistic regression models. CONCLUSION AND RECOMMENDATION: Cardiovascular risk profiles appear to be more predictive of aortopathy in TAV patients than in patients with BAV. This adds evidence to the fact that BAV-associated and TAV-associated aortopathy involves different pathways to aneurysm formation and highlights the need for specific aneurysm preventions in these patients. Further, our results highlight that machine learning approaches do not outperform classical prediction methods in addressing complex interactions and non-linear relations between variables.

Quantifying the Relative Importance of Genetics and Environment on the Comorbidity between Mental- and Cardiometabolic Disorders: A Comprehensive Analysis of National Register Data from 17 million Scandinavians.

Mental disorders (MDs) are leading causes of disability and premature death worldwide, partly due to high comorbidity with cardiometabolic disorders (CMDs). Reasons for this comorbidity are still poorly understood. We leverage nation-wide health records and complete genealogies of Denmark and Sweden (n=17 million) to reveal the genetic and environmental contributions underlying the observed comorbidity between six MDs and 14 CMDs. Genetic factors contributed about 50% to the comorbidity of schizophrenia, affective disorders, and autism spectrum disorder with CMDs, whereas the comorbidity of attention-deficit/hyperactivity disorder and anorexia with CMDs was mainly or fully driven by environmental factors. These findings provide causal insight to guide clinical and scientific initiatives directed at achieving mechanistic understanding as well as preventing and alleviating the consequences of these disorders.

Sex and statin-related genetic associations at the PCSK9 gene locus: results of genome-wide association meta-analysis.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player of lipid metabolism with higher plasma levels in women throughout their life. Statin treatment affects PCSK9 levels also showing evidence of sex-differential effects. It remains unclear whether these differences can be explained by genetics. METHODS: We performed genome-wide association meta-analyses (GWAS) of PCSK9 levels stratified for sex and statin treatment in six independent studies of Europeans (8936 women/11,080 men respectively 14,825 statin-free/5191 statin-treated individuals). Loci associated in one of the strata were tested for statin- and sex-interactions considering all independent signals per locus. Independent variants at the PCSK9 gene locus were then used in a stratified Mendelian Randomization analysis (cis-MR) of PCSK9 effects on low-density lipoprotein cholesterol (LDL-C) levels to detect differences of causal effects between the subgroups. RESULTS: We identified 11 loci associated with PCSK9 in at least one stratified subgroup (p < 1.0 × 10-6), including the PCSK9 gene locus and five other lipid loci: APOB, TM6SF2, FADS1/FADS2, JMJD1C, and HP/HPR. The interaction analysis revealed eight loci with sex- and/or statin-interactions. At the PCSK9 gene locus, there were four independent signals, one with a significant sex-interaction showing stronger effects in men (rs693668). Regarding statin treatment, there were two significant interactions in PCSK9 missense mutations: rs11591147 had stronger effects in statin-free individuals, and rs11583680 had stronger effects in statin-treated individuals. Besides replicating known loci, we detected two novel genome-wide significant associations: one for statin-treated individuals at 6q11.1 (within KHDRBS2) and one for males at 12q24.22 (near KSR2/NOS1), both with significant interactions. In the MR of PCSK9 on LDL-C, we observed significant causal estimates within all subgroups, but significantly stronger causal effects in statin-free subjects compared to statin-treated individuals. CONCLUSIONS: We performed the first double-stratified GWAS of PCSK9 levels and identified multiple biologically plausible loci with genetic interaction effects. Our results indicate that the observed sexual dimorphism of PCSK9 and its statin-related interactions have a genetic basis. Significant differences in the causal relationship between PCSK9 and LDL-C suggest sex-specific dosages of PCSK9 inhibitors.

The protein "proprotein convertase subtilisin/kexin type 9" (PCSK9) regulates the levels of low-density lipoprotein cholesterol (LDL-C) in blood, and thus, contributes to the risk of cardio-vascular diseases. Women tend to have higher PCSK9 plasma levels throughout their life, although the difference is smaller in patients under LDL-C lowering medication (e.g., statins). We investigated the interplay of genetics, statin-treatment and sex, using combined data from six European studies. We detected 11 genetic regions associated with PCSK9 levels, of which one was specific for women (at SLCO1B3, a statin-transporter gene), and three were specific for men (e.g., ALOX5, encoding a protein linked to chronic inflammatory diseases such as atherosclerosis). We also tested if statin use changed the genetic effect and found five genes only associated with PCSK9 levels in untreated participants. Variants in the gene encoding PCSK9 were most strongly associated and had heterogeneous effects in dependence on statin treatment and sex: On one hand, there were genetic variants with stronger effects in men than women. Those variants are also linked to sex-differential gene expression of PCSK9. On the other hand, there were also variants with treatment-depending effects, linked to protein structure and functionality of PCSK9. This indicates that the observed sexual and treatment-related effects on PCSK9 levels have a genetic basis. In addition, we compared the causal effects of PCSK9 on LDL-C levels between men and women and found a different response to statin treatment. This highlights the need for sex-sensitive dosages of lipid-lowering medication.

Polygenic profiles define aspects of clinical heterogeneity in attention deficit hyperactivity disorder.

Attention deficit hyperactivity disorder (ADHD) is a complex disorder that manifests variability in long-term outcomes and clinical presentations. The genetic contributions to such heterogeneity are not well understood. Here we show several genetic links to clinical heterogeneity in ADHD in a case-only study of 14,084 diagnosed individuals. First, we identify one genome-wide significant locus by comparing cases with ADHD and autism spectrum disorder (ASD) to cases with ADHD but not ASD. Second, we show that cases with ASD and ADHD, substance use disorder and ADHD, or first diagnosed with ADHD in adulthood have unique polygenic score (PGS) profiles that distinguish them from complementary case subgroups and controls. Finally, a PGS for an ASD diagnosis in ADHD cases predicted cognitive performance in an independent developmental cohort. Our approach uncovered evidence of genetic heterogeneity in ADHD, helping us to understand its etiology and providing a model for studies of other disorders.

Meta-GWAS of PCSK9 levels detects two novel loci at APOB and TM6SF2.

BACKGROUND: Proprotein convertase subtilisin/kexin type 9 (PCSK9) is a key player in lipid metabolism, as it degrades low-density lipoprotein (LDL) receptors from hepatic cell membranes. So far, only variants of the PCSK9 gene locus were found to be associated with PCSK9 levels. Here we aimed to identify novel genetic loci that regulate PCSK9 levels and how they relate to other lipid traits. Additionally, we investigated to what extend the causal effect of PCSK9 on coronary artery disease (CAD) is mediated by low-density lipoprotein-cholesterol (LDL-C). METHODS AND RESULTS: We performed a genome-wide association study meta-analysis of PCSK9 levels in up to 12 721 samples of European ancestry. The estimated heritability was 10.3%, which increased to 12.6% using only samples from patients without statin treatment. We successfully replicated the known PCSK9 hit consisting of three independent signals. Interestingly, in a study of 300 African Americans, we confirmed the locus with a different PCSK9 variant. Beyond PCSK9, our meta-analysis detected three novel loci with genome-wide significance. Co-localization analysis with cis-eQTLs and lipid traits revealed biologically plausible candidate genes at two of them: APOB and TM6SF2. In a bivariate Mendelian Randomization analysis, we detected a strong effect of PCSK9 on LDL-C, but not vice versa. LDL-C mediated 63% of the total causal effect of PCSK9 on CAD. CONCLUSION: Our study identified novel genetic loci with plausible candidate genes affecting PCSK9 levels. Ethnic heterogeneity was observed at the PCSK9 locus itself. Although the causal effect of PCSK9 on CAD is mainly mediated by LDL-C, an independent direct effect also occurs.

Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability.

Differences between sexes contribute to variation in the levels of fasting glucose and insulin. Epidemiological studies established a higher prevalence of impaired fasting glucose in men and impaired glucose tolerance in women, however, the genetic component underlying this phenomenon is not established. We assess sex-dimorphic (73,089/50,404 women and 67,506/47,806 men) and sex-combined (151,188/105,056 individuals) fasting glucose/fasting insulin genetic effects via genome-wide association study meta-analyses in individuals of European descent without diabetes. Here we report sex dimorphism in allelic effects on fasting insulin at IRS1 and ZNF12 loci, the latter showing higher RNA expression in whole blood in women compared to men. We also observe sex-homogeneous effects on fasting glucose at seven novel loci. Fasting insulin in women shows stronger genetic correlations than in men with waist-to-hip ratio and anorexia nervosa. Furthermore, waist-to-hip ratio is causally related to insulin resistance in women, but not in men. These results position dissection of metabolic and glycemic health sex dimorphism as a steppingstone for understanding differences in genetic effects between women and men in related phenotypes.

Genomic and drug target evaluation of 90 cardiovascular proteins in 30,931 individuals.

Circulating proteins are vital in human health and disease and are frequently used as biomarkers for clinical decision-making or as targets for pharmacological intervention. Here, we map and replicate protein quantitative trait loci (pQTL) for 90 cardiovascular proteins in over 30,000 individuals, resulting in 451 pQTLs for 85 proteins. For each protein, we further perform pathway mapping to obtain trans-pQTL gene and regulatory designations. We substantiate these regulatory findings with orthogonal evidence for trans-pQTLs using mouse knockdown experiments (ABCA1 and TRIB1) and clinical trial results (chemokine receptors CCR2 and CCR5), with consistent regulation. Finally, we evaluate known drug targets, and suggest new target candidates or repositioning opportunities using Mendelian randomization. This identifies 11 proteins with causal evidence of involvement in human disease that have not previously been targeted, including EGF, IL-16, PAPPA, SPON1, F3, ADM, CASP-8, CHI3L1, CXCL16, GDF15 and MMP-12. Taken together, these findings demonstrate the utility of large-scale mapping of the genetics of the proteome and provide a resource for future precision studies of circulating proteins in human health.

Transcriptomic profiling of experimental arterial injury reveals new mechanisms and temporal dynamics in vascular healing response.

OBJECTIVE: Endovascular interventions cause arterial injury and induce a healing response to restore vessel wall homeostasis. Complications of defective or excessive healing are common and result in increased morbidity and repeated interventions. Experimental models of intimal hyperplasia are vital for understanding the vascular healing mechanisms and resolving the clinical problems of restenosis, vein graft stenosis, and dialysis access failure. Our aim was to systematically investigate the transcriptional, histologic, and systemic reaction to vascular injury during a prolonged time. METHODS: Balloon injury of the left common carotid artery was performed in male rats. Animals (n = 69) were euthanized before or after injury, either directly or after 2 hours, 20 hours, 2 days, 5 days, 2 weeks, 6 weeks, and 12 weeks. Both injured and contralateral arteries were subjected to microarray profiling, followed by bioinformatic exploration, histologic characterization of the biopsy specimens, and plasma lipid analyses. RESULTS: Immune activation and coagulation were key mechanisms in the early response, followed by cytokine release, tissue remodeling, and smooth muscle cell modulation several days after injury, with reacquisition of contractile features in later phases. Novel pathways related to clonal expansion, inflammatory transformation, and chondro-osteogenic differentiation were identified and immunolocalized to neointimal smooth muscle cells. Analysis of uninjured arteries revealed a systemic component of the reaction after local injury, underlined by altered endothelial signaling, changes in overall tissue bioenergy metabolism, and plasma high-density lipoprotein levels. CONCLUSIONS: We demonstrate that vascular injury induces dynamic transcriptional landscape and metabolic changes identifiable as early, intermediate, and late response phases, reaching homeostasis after several weeks. This study provides a temporal "roadmap" of vascular healing as a publicly available resource for the research community.

Comparison of quantitative trait loci methods: Total expression and allelic imbalance method in brain RNA-seq.

BACKGROUND: Of the 108 Schizophrenia (SZ) risk-loci discovered through genome-wide association studies (GWAS), 96 are not altering the sequence of any protein. Evidence linking non-coding risk-SNPs and genes may be established using expression quantitative trait loci (eQTL). However, other approaches such allelic expression quantitative trait loci (aeQTL) also may be of use. METHODS: We applied both the eQTL and aeQTL analysis to a biobank of deeply sequenced RNA from 680 dorso-lateral pre-frontal cortex (DLPFC) samples. For each of 340 genes proximal to the SZ risk-SNPs, we asked how much SNP-genotype affected total expression (eQTL), as well as how much the expression ratio between the two alleles differed from 1:1 as a consequence of the risk-SNP genotype (aeQTL). RESULTS: We analyzed overlap with comparable eQTL-findings: 16 of the 30 risk-SNPs known to have gene-level eQTL also had gene-level aeQTL effects. 6 of 21 risk-SNPs with known splice-eQTL had exon-aeQTL effects. 12 novel potential risk genes were identified with the aeQTL approach, while 55 tested SNP-pairs were found as eQTL but not aeQTL. Of the tested 108 loci we could find at least one gene to be associated with 21 of the risk-SNPs using gene-level aeQTL, and with an additional 18 risk-SNPs using exon-level aeQTL. CONCLUSION: Our results suggest that the aeQTL strategy complements the eQTL approach to susceptibility gene identification.

Correlation of computed tomography with carotid plaque transcriptomes associates calcification with lesion-stabilization.

BACKGROUND AND AIMS: Unstable carotid atherosclerosis causes stroke, but methods to identify patients and lesions at risk are lacking. We recently found enrichment of genes associated with calcification in carotid plaques from asymptomatic patients. Here, we hypothesized that calcification represents a stabilising feature of plaques and investigated how macro-calcification, as estimated by computed tomography (CT), correlates with gene expression profiles in lesions. METHODS: Plaque calcification was measured in pre-operative CT angiographies. Plaques were sorted into high- and low-calcified, profiled with microarrays, followed by bioinformatic analyses. Immunohistochemistry and qPCR were performed to evaluate the findings in plaques and arteries with medial calcification from chronic kidney disease patients. RESULTS: Smooth muscle cell (SMC) markers were upregulated in high-calcified plaques and calcified plaques from symptomatic patients, whereas macrophage markers were downregulated. The most enriched processes in high-calcified plaques were related to SMCs and extracellular matrix (ECM) organization, while inflammation, lipid transport and chemokine signaling were repressed. These findings were confirmed in arteries with high medial calcification. Proteoglycan 4 (PRG4) was identified as the most upregulated gene in association with plaque calcification and found in the ECM, SMA+ and CD68+/TRAP + cells. CONCLUSIONS: Macro-calcification in carotid lesions correlated with a transcriptional profile typical for stable plaques, with altered SMC phenotype and ECM composition and repressed inflammation. PRG4, previously not described in atherosclerosis, was enriched in the calcified ECM and localized to activated macrophages and smooth muscle-like cells. This study strengthens the notion that assessment of calcification may aid evaluation of plaque phenotype and stroke risk.

Effects of the coronary artery disease associated LPA and 9p21 loci on risk of aortic valve stenosis.

BACKGROUND: Aortic valve stenosis (AVS) and coronary artery disease (CAD) have a significant genetic contribution and commonly co-exist. To compare and contrast genetic determinants of the two diseases, we investigated associations of the LPA and 9p21 loci, i.e. the two strongest CAD risk loci, with risk of AVS. METHODS: We genotyped the CAD-associated variants at the LPA (rs10455872) and 9p21 loci (rs1333049) in the GeneCAST (Genetics of Calcific Aortic STenosis) Consortium and conducted a meta-analysis for their association with AVS. Cases and controls were stratified by CAD status. External validation of findings was undertaken in five cohorts including 7880 cases and 851,152 controls. RESULTS: In the meta-analysis including 4651 cases and 8231 controls the CAD-associated allele at the LPA locus was associated with increased risk of AVS (OR 1.37; 95%CI 1.24-1.52, p = 6.9 × 10-10) with a larger effect size in those without CAD (OR 1.53; 95%CI 1.31-1.79) compared to those with CAD (OR 1.27; 95%CI 1.12-1.45). The CAD-associated allele at 9p21 was associated with a trend towards lower risk of AVS (OR 0.93; 95%CI 0.88-0.99, p = 0.014). External validation confirmed the association of the LPA risk allele with risk of AVS (OR 1.37; 95%CI 1.27-1.47), again with a higher effect size in those without CAD. The small protective effect of the 9p21 CAD risk allele could not be replicated (OR 0.98; 95%CI 0.95-1.02). CONCLUSIONS: Our study confirms the association of the LPA locus with risk of AVS, with a higher effect in those without concomitant CAD. Overall, 9p21 was not associated with AVS.

Endothelial/Epithelial Mesenchymal Transition in Ascending Aortas of Patients With Bicuspid Aortic Valve.

Thoracic aortic aneurysm (TAA) is the progressive enlargement of the aorta due to destructive changes in the connective tissue of the aortic wall. Aneurysm development is silent and often first manifested by the drastic events of aortic dissection or rupture. As yet, therapeutic agents that halt or reverse the process of aortic wall deterioration are absent, and the only available therapeutic recommendation is elective prophylactic surgical intervention. Being born with a bicuspid instead of the normal tricuspid aortic valve (TAV) is a major risk factor for developing aneurysm in the ascending aorta later in life. Although the pathophysiology of the increased aneurysm susceptibility is not known, recent studies are suggestive of a transformation of aortic endothelium into a more mesenchymal state i.e., an endothelial-to-mesenchymal transition in these individuals. This process involves the loss of endothelial cell features, resulting in junction instability and enhanced vascular permeability of the ascending aorta that may lay the ground for increased aneurysm susceptibility. This finding differentiates and further emphasizes the specific characteristics of aneurysm development in individuals with a bicuspid aortic valve (BAV). This review discusses the possibility of a developmental fate shared between the aortic endothelium and aortic valves. It further speculates about the impact of aortic endothelium phenotypic shift on aneurysm development in individuals with a BAV and revisits previous studies in the light of the new findings.

Identification of a novel proinsulin-associated SNP and demonstration that proinsulin is unlikely to be a causal factor in subclinical vascular remodelling using Mendelian randomisation.

BACKGROUND AND AIMS: Increased proinsulin relative to insulin levels have been associated with subclinical atherosclerosis (measured by carotid intima-media thickness (cIMT)) and are predictive of future cardiovascular disease (CVD), independently of established risk factors. The mechanisms linking proinsulin to atherosclerosis and CVD are unclear. A genome-wide meta-analysis has identified nine loci associated with circulating proinsulin levels. Using proinsulin-associated SNPs, we set out to use a Mendelian randomisation approach to test the hypothesis that proinsulin plays a causal role in subclinical vascular remodelling. METHODS: We studied the high CVD-risk IMPROVE cohort (n = 3345), which has detailed biochemical phenotyping and repeated, state-of-the-art, high-resolution carotid ultrasound examinations. Genotyping was performed using Illumina Cardio-Metabo and Immuno arrays, which include reported proinsulin-associated loci. Participants with type 2 diabetes (n = 904) were omitted from the analysis. Linear regression was used to identify proinsulin-associated genetic variants. RESULTS: We identified a proinsulin locus on chromosome 15 (rs8029765) and replicated it in data from 20,003 additional individuals. An 11-SNP score, including the previously identified and the chromosome 15 proinsulin-associated loci, was significantly and negatively associated with baseline IMTmean and IMTmax (the primary cIMT phenotypes) but not with progression measures. However, MR-Eggers refuted any significant effect of the proinsulin-associated 11-SNP score, and a non-pleiotropic SNP score of three variants (including rs8029765) demonstrated no effect on baseline or progression cIMT measures. CONCLUSIONS: We identified a novel proinsulin-associated locus and demonstrated that whilst proinsulin levels are associated with cIMT measures, proinsulin per se is unlikely to have a causative effect on cIMT.

ClusterSignificance: a bioconductor package facilitating statistical analysis of class cluster separations in dimensionality reduced data.

SUMMARY: Multi-dimensional data generated via high-throughput experiments is increasingly used in conjunction with dimensionality reduction methods to ascertain if resulting separations of the data correspond with known classes. This is particularly useful to determine if a subset of the variables, e.g. genes in a specific pathway, alone can separate samples into these established classes. Despite this, the evaluation of class separations is often subjective and performed via visualization. Here we present the ClusterSignificance package; a set of tools designed to assess the statistical significance of class separations downstream of dimensionality reduction algorithms. In addition, we demonstrate the design and utility of the ClusterSignificance package and utilize it to determine the importance of long non-coding RNA expression in the identity of multiple hematological malignancies. AVAILABILITY AND IMPLEMENTATION: ClusterSignificance is an R package available via Bioconductor (https://bioconductor.org/packages/ClusterSignificance) under GPL-3. CONTACT: dan.grander@ki.se. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide association study with additional genetic and post-transcriptional analyses reveals novel regulators of plasma factor XI levels.

Coagulation factor XI (FXI) has become increasingly interesting for its role in pathogenesis of thrombosis. While elevated plasma levels of FXI have been associated with venous thromboembolism and ischemic stroke, its deficiency is associated with mild bleeding. We aimed to determine novel genetic and post-transcriptional plasma FXI regulators.We performed a genome-wide association study (GWAS) for plasma FXI levels, using novel data imputed to the 1000 Genomes reference panel. Individual GWAS analyses, including a total of 16,169 European individuals from the ARIC, GHS, MARTHA and PROCARDIS studies, were meta-analysed and further replicated in 2,045 individuals from the F5L family, GAIT2 and MEGA studies. Additional association with activated partial thromboplastin time (aPTT) was tested for the top SNPs. In addition, a study on the effect of miRNA on FXI regulation was performed using in silico prediction tools and in vitro luciferase assays.Three loci showed robust, replicating association with circulating FXI levels: KNG1 (rs710446, P-value = 2.07 × 10-302), F11 (rs4253417, P-value = 2.86 × 10-193), and a novel association in GCKR (rs780094, P-value = 3.56 ×10-09), here for the first time implicated in FXI regulation. The two first SNPs (rs710446 and rs4253417) also associated with aPTT. Conditional and haplotype analyses demonstrated a complex association signal, with additional novel SNPs modulating plasma FXI levels in both the F11 and KNG1 loci. Finally, eight miRNAs were predicted to bind F11 mRNA. Over-expression of either miR-145 or miR-181 significantly reduced the luciferase activity in cells transfected with a plasmid containing FXI-3'UTR.These results should open the door to new therapeutic targets for thrombosis prevention.

Perilipin 5 is protective in the ischemic heart.

BACKGROUND: Myocardial ischemia is associated with alterations in cardiac metabolism, resulting in decreased fatty acid oxidation and increased lipid accumulation. Here we investigate how myocardial lipid content and dynamics affect the function of the ischemic heart, and focus on the role of the lipid droplet protein perilipin 5 (Plin5) in the pathophysiology of myocardial ischemia. METHODS AND RESULTS: We generated Plin5(-/-) mice and found that Plin5 deficiency dramatically reduced the triglyceride content in the heart. Under normal conditions, Plin5(-/-) mice maintained a close to normal heart function by decreasing fatty acid uptake and increasing glucose uptake, thus preserving the energy balance. However, during stress or myocardial ischemia, Plin5 deficiency resulted in myocardial reduced substrate availability, severely reduced heart function and increased mortality. Importantly, analysis of a human cohort with suspected coronary artery disease showed that a common noncoding polymorphism, rs884164, decreases the cardiac expression of PLIN5 and is associated with reduced heart function following myocardial ischemia, indicating a role for Plin5 in cardiac dysfunction. CONCLUSION: Our findings indicate that Plin5 deficiency alters cardiac lipid metabolism and associates with reduced survival following myocardial ischemia, suggesting that Plin5 plays a beneficial role in the heart following ischemia.

Genetic loci on chromosome 5 are associated with circulating levels of interleukin-5 and eosinophil count in a European population with high risk for cardiovascular disease.

IL-5 is a Th2 cytokine which activates eosinophils and is suggested to have an atheroprotective role. Genetic variants in the IL5 locus have been associated with increased risk of CAD and ischemic stroke. In this study we aimed to identify genetic variants associated with IL-5 concentrations and apply a Mendelian randomisation approach to assess IL-5 levels for causal effect on intima-media thickness in a European population at high risk of coronary artery disease. We analysed SNPs within robustly associated candidate loci for immune, inflammatory, metabolic and cardiovascular traits. We identified 2 genetic loci for IL-5 levels (chromosome 5, rs56183820, BETA=0.11, P=6.73E(-5) and chromosome 14, rs4902762, BETA=0.12, P=5.76E(-6)) and one for eosinophil count (rs72797327, BETA=-0.10, P=1.41E(-6)). Both chromosome 5 loci were in the vicinity of the IL5 gene, however the association with IL-5 levels failed to replicate in a meta-analysis of 2 independent cohorts (rs56183820, BETA=0.04, P=0.2763, I(2)=24, I(2)-P=0.2516). No significant associations were observed between SNPs associated with IL-5 levels or eosinophil count and IMT measures. Expression quantitative trait analyses indicate effects of the IL-5 and eosinophil-associated SNPs on RAD50 mRNA expression levels (rs12652920 (r2=0.93 with rs56183820) BETA=-0.10, P=8.64E(-6) and rs11739623 (r2=0.96 with rs72797327) BETA=-0.23, P=1.74E(-29), respectively). Our data do not support a role for IL-5 levels and eosinophil count in intima-media thickness, however SNPs associated with IL-5 and eosinophils might influence stability of the atherosclerotic plaque via modulation of RAD50 levels.

AllelicImbalance: an R/bioconductor package for detecting, managing, and visualizing allele expression imbalance data from RNA sequencing.

BACKGROUND: One aspect in which RNA sequencing is more valuable than microarray-based methods is the ability to examine the allelic imbalance of the expression of a gene. This process is often a complex task that entails quality control, alignment, and the counting of reads over heterozygous single-nucleotide polymorphisms. Allelic imbalance analysis is subject to technical biases, due to differences in the sequences of the measured alleles. Flexible bioinformatics tools are needed to ease the workflow while retaining as much RNA sequencing information as possible throughout the analysis to detect and address the possible biases. RESULTS: We present AllelicImblance, a software program that is designed to detect, manage, and visualize allelic imbalances comprehensively. The purpose of this software is to allow users to pose genetic questions in any RNA sequencing experiment quickly, enhancing the general utility of RNA sequencing. The visualization features can reveal notable, non-trivial allelic imbalance behavior over specific regions, such as exons. CONCLUSIONS: The software provides a complete framework to perform allelic imbalance analyses of aligned RNA sequencing data, from detection to visualization, within the robust and versatile management class, ASEset.