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yocardial infarction and stroke, the leading causes of global morbidity and mortality, are caused by atherosclerosis, which originates from inflammatory, lipid, endocrine, metabolic and hemodynamic disturbances. Indeed, multiple and parallel malfunctions in metabolic organs are responsible for the complex molecular disease processes of cardiometabolic disorders (CMDs) leading to CAD 1 . For example, the liver plays a central role in determining plasma lipid levels by regulating lipoprotein synthesis and lipoprotein remnant uptake, whereas adipose tissues and skeletal muscle (SKLM) facilitate lipolysis. Similarly, blood glucose levels depend on a delicate interplay of hepatic glucose production, insulin production in pancreatic beta cells and insulin sensitivity in peripheral glycolytic tissues. Alterations in lipid or glucose metabolism may lead to obesity, which in turn may promote the development of type 2 diabetes mellitus, hypertension, systemic inflammation 2,3 and, eventually, CAD.Thus far, the role of these and other risk factors in causing the initiation and progression of CAD have typically only been considered in isolated pathways. A systemic view 4-7 of the combined high-dimensional, multiorgan metabolic processes that perturb the biology of the arterial wall has, however, not been described. Systems studies based on integrative analyses of DNA and RNA sequencing (RNA-seq) data, unlike studies focusing on DNA alone, such as genome-wide association studies (GWAS), hold promise to go beyond studies of individual genetic risk loci and candidate genes in isolated pathways by capturing the combined impact of exogenous and genetic risk factors 8-10 . To achieve this, RNA-seq data are typically first used to infer gene coexpression modules 5 ,

Key Points• FBXO11 loss in mice enhances GC B-cell formation and leads to increased BCL6 expression.• FBXO11 inactivation, mimicking genetic alterations identified in human lymphomas, represents an alternative mechanism of BCL6 deregulation.The BCL6 proto-oncogene encodes a transcriptional repressor that is required for the germinal center (GC) reaction and is implicated in lymphomagenesis. BCL6 protein stability is regulated by F-box protein 11 (FBXO11)-mediated ubiquitination and degradation, which is impaired in ∼6% of diffuse large B-cell lymphomas that carry inactivating genetic alterations targeting the FBXO11 gene. In order to investigate the role of FBXO11 in vivo, we analyzed GC-specific FBXO11 knockout mice. FBXO11 reduction or loss led to an increased number of GC B cells, to an altered ratio of GC dark zone to light zone cells, and to higher levels of BCL6 protein in GC B cells. B-cell receptor-mediated degradation of BCL6 was reduced in the absence of FBXO11, suggesting that FBXO11 contributes to the physiologic downregulation of BCL6 at the end of the GC reaction. Finally, FBXO11 inactivation was associated with the development of lymphoproliferative disorders in mice. (Blood. 2016;128(5):660-666)

Background: Hundreds of candidate genes have been associated with coronary artery disease (CAD) through genome-wide association studies. However, a systematic way to understand the causal mechanism(s) of these genes, and a means to prioritize them for further study, has been lacking. This represents a major roadblock for developing novel disease- and gene-specific therapies for patients with CAD. Recently, powerful integrative genomics analyses pipelines have emerged to identify and prioritize candidate causal genes by integrating tissue/cell-specific gene expression data with genome-wide association studies data sets. Methods: We aimed to develop a comprehensive integrative genomics analyses pipeline for CAD and to provide a prioritized list of causal CAD genes. To this end, we leveraged several complimentary informatics approaches to integrate summary statistics from CAD genome-wide association studies (from UK Biobank and CARDIoGRAMplusC4D) with transcriptomic and expression quantitative trait loci data from 9 cardiometabolic tissue/cell types in the STARNET study (Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task). Results: We identified 162 unique candidate causal CAD genes, which exerted their effect from between one and up to 7 disease-relevant tissues/cell types, including the arterial wall, blood, liver, skeletal muscle, adipose, foam cells, and macrophages. When their causal effect was ranked, the top candidate causal CAD genes were CDKN2B (associated with the 9p21.3 risk locus) and PHACTR1 ; both exerting their causal effect in the arterial wall. A majority of candidate causal genes were represented in cross-tissue gene regulatory co-expression networks that are involved with CAD, with 22/162 being key drivers in those networks. Conclusions: We identified and prioritized candidate causal CAD genes, also localizing their tissue(s) of causal effect. These results should serve as a resource and facilitate targeted studies to identify the functional impact of top causal CAD genes.

The aim of the study was to compare the results of ultrasonography (US) and laparoscopy in a series of 210 patients referred to our institution for the diagnosis of widespread liver diseases. Among 205 patients, laparoscopy revealed cirrhosis in 114, chronic widespread disease in 70 (chronic persistent hepatitis in 21, chronic active hepatitis in 28, steatosis in 14, acute hepatitis in 5, fibrosis in 2), and absence of liver disease in 21. Four of these cases had minor complications. A corroborative diagnosis was obtained in 122 patients (59.5%). Overall sensitivity of US was 84% with a low specificity due to the high rate of false negatives. From the results of this study we conclude that laparoscopy is a safe and essential diagnostic tool in the final diagnosis of widespread liver diseases and that US is not a reliable screening method because of its incidence of false negatives.

24 25 45 KEYWORDS 46 Atherosclerotic plaque, T cells, macrophages, cerebrovascular events, Stroke, CyTOF, 47 scRNA-seq, CITE-seq, cell-cell interactions, IL-1β, PD-1, T cell exhaustion. 48 49 alterations of individual immune cells that contribute to human disease and its CV 89 complications. 90 91 RESULTS 92 Single-Cell Immunophenotyping of Human Atherosclerosis: Study Design 93 To map the immune microenvironment of atherosclerotic lesions, identify mirroring 94 immune changes in blood and pinpoint cell-specific alterations associated with clinical CV 95 events (i.e. stoke and TIA), we performed a large-scale CyTOF mass-cytometry 96 analysis 41 combined with Cellular Indexing of Transcriptomes and Epitopes by 97 Sequencing (CITE-seq) 42 and single-cell scRNA-seq analysis of plaques from a total of 98 46 prospectively enrolled patients undergoing carotid endarterectomy (Fig.

In recent years, cardiovascular immuno-imaging by positron emission tomography (PET) has undergone tremendous progress in preclinical settings. Clinically, two approved PET tracers hold great potential for inflammation imaging in cardiovascular patients, namely FDG and DOTATATE. While the former is a widely applied metabolic tracer, DOTATATE is a relatively new PET tracer targeting the somatostatin receptor 2 (SST2). In the current study, we performed a detailed, head-to-head comparison of DOTATATE-based radiotracers and [18F]F-FDG in mouse and rabbit models of cardiovascular inflammation. For mouse experiments, we labeled DOTATATE with the long-lived isotope [64Cu]Cu to enable studying the tracer’s mode of action by complementing in vivo PET/CT experiments with thorough ex vivo immunological analyses. For translational PET/MRI rabbit studies, we employed the more widely clinically used [68Ga]Ga-labeled DOTATATE, which was approved by the FDA in 2016. DOTATATE’s pharmacokinetics and timed biodistribution were determined in control and atherosclerotic mice and rabbits by ex vivo gamma counting of blood and organs. Additionally, we performed in vivo PET/CT experiments in mice with atherosclerosis, mice subjected to myocardial infarction and control animals, using both [64Cu]Cu-DOTATATE and [18F]F-FDG. To evaluate differences in the tracers’ cellular specificity, we performed ensuing ex vivo flow cytometry and gamma counting. In mice subjected to myocardial infarction, in vivo [64Cu]Cu-DOTATATE PET showed higher differential uptake between infarcted (SUVmax 1.3, IQR, 1.2–1.4, N = 4) and remote myocardium (SUVmax 0.7, IQR, 0.5–0.8, N = 4, p = 0.0286), and with respect to controls (SUVmax 0.6, IQR, 0.5–0.7, N = 4, p = 0.0286), than [18F]F-FDG PET. In atherosclerotic mice, [64Cu]Cu-DOTATATE PET aortic signal, but not [18F]F-FDG PET, was higher compared to controls (SUVmax 1.1, IQR, 0.9–1.3 and 0.5, IQR, 0.5–0.6, respectively, N = 4, p = 0.0286). In both models, [64Cu]Cu-DOTATATE demonstrated preferential accumulation in macrophages with respect to other myeloid cells, while [18F]F-FDG was taken up by macrophages and other leukocytes. In a translational PET/MRI study in atherosclerotic rabbits, we then compared [68Ga]Ga-DOTATATE and [18F]F-FDG for the assessment of aortic inflammation, combined with ex vivo radiometric assays and near-infrared imaging of macrophage burden. Rabbit experiments showed significantly higher aortic accumulation of both [68Ga]Ga-DOTATATE and [18F]F-FDG in atherosclerotic (SUVmax 0.415, IQR, 0.338–0.499, N = 32 and 0.446, IQR, 0.387–0.536, N = 27, respectively) compared to control animals (SUVmax 0.253, IQR, 0.197–0.285, p = 0.0002, N = 10 and 0.349, IQR, 0.299–0.423, p = 0.0159, N = 11, respectively). In conclusion, we present a detailed, head-to-head comparison of the novel SST2-specific tracer DOTATATE and the validated metabolic tracer [18F]F-FDG for the evaluation of inflammation in small animal models of cardiovascular disease. Our results support further investigations on the use of DOTATATE to assess cardiovascular inflammation as a complementary readout to the widely used [18F]F-FDG.

Background Genetic loss-of-function variants (LoFs) associated with disease traits are increasingly recognized as critical evidence for the selection of therapeutic targets. We integrated the analysis of genetic and clinical data from 10,511 individuals in the Mount Sinai Bio Me Biobank to identify genes with loss-of-function variants (LoFs) significantly associated with cardiovascular disease (CVD) traits, and used RNA-sequence data of seven metabolic and vascular tissues isolated from 600 CVD patients in the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study for validation. We also carried out in vitro functional studies of several candidate genes, and in vivo studies of one gene. Results We identified LoFs in 433 genes significantly associated with at least one of 10 major CVD traits. Next, we used RNA-sequence data from the STARNET study to validate 115 of the 433 LoF harboring-genes in that their expression levels were concordantly associated with corresponding CVD traits. Together with the documented hepatic lipid-lowering gene, APOC3, the expression levels of six additional liver LoF-genes were positively associated with levels of plasma lipids in STARNET. Candidate LoF-genes were subjected to gene silencing in HepG2 cells with marked overall effects on cellular LDLR, levels of triglycerides and on secreted APOB100 and PCSK9. In addition, we identified novel LoFs in DGAT2 associated with lower plasma cholesterol and glucose levels in Bio Me that were also confirmed in STARNET, and showed a selective DGAT2-inhibitor in C57BL/6 mice not only significantly lowered fasting glucose levels but also affected body weight. Conclusion In sum, by integrating genetic and electronic medical record data, and leveraging one of the world’s largest human RNA-sequence datasets (STARNET), we identified known and novel CVD-trait related genes that may serve as targets for CVD therapeutics and as such merit further investigation. Electronic supplementary material The online version of this article (10.1186/s12920-019-0542-3) contains supplementary material, which is available to authorized users.