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The stress hormone cortisol modulates fuel metabolism, cardiovascular homoeostasis, mood, inflammation and cognition. The CORtisol NETwork (CORNET) consortium previously identified a single locus associated with morning plasma cortisol. Identifying additional genetic variants that explain more of the variance in cortisol could provide new insights into cortisol biology and provide statistical power to test the causative role of cortisol in common diseases. The CORNET consortium extended its genome-wide association meta-analysis for morning plasma cortisol from 12,597 to 25,314 subjects and from ~2.2 M to ~7 M SNPs, in 17 population-based cohorts of European ancestries. We confirmed the genetic association with SERPINA6/SERPINA1. This locus contains genes encoding corticosteroid binding globulin (CBG) and α1-antitrypsin. Expression quantitative trait loci (eQTL) analyses undertaken in the STARNET cohort of 600 individuals showed that specific genetic variants within the SERPINA6/SERPINA1 locus influence expression of SERPINA6 rather than SERPINA1 in the liver. Moreover, trans-eQTL analysis demonstrated effects on adipose tissue gene expression, suggesting that variations in CBG levels have an effect on delivery of cortisol to peripheral tissues. Two-sample Mendelian randomisation analyses provided evidence that each genetically-determined standard deviation (SD) increase in morning plasma cortisol was associated with increased odds of chronic ischaemic heart disease (0.32, 95% CI 0.06–0.59) and myocardial infarction (0.21, 95% CI 0.00–0.43) in UK Biobank and similarly in CARDIoGRAMplusC4D. These findings reveal a causative pathway for CBG in determining cortisol action in peripheral tissues and thereby contributing to the aetiology of cardiovascular disease.

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 study 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.

Coronary atherosclerosis results from the delicate interplay of genetic and exogenous risk factors, principally taking place in metabolic organs and the arterial wall. Here we show that 224 gene-regulatory coexpression networks (GRNs) identified by integrating genetic and clinical data from patients with (n = 600) and without (n = 250) coronary artery disease (CAD) with RNA-seq data from seven disease-relevant tissues in the Stockholm–Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) study largely capture this delicate interplay, explaining >54% of CAD heritability. Within 89 cross-tissue GRNs associated with clinical severity of CAD, 374 endocrine factors facilitated inter-organ interactions, primarily along an axis from adipose tissue to the liver (n = 152). This axis was independently replicated in genetically diverse mouse strains and by injection of recombinant forms of adipose endocrine factors (EPDR1, FCN2, FSTL3 and LBP) that markedly altered blood lipid and glucose levels in mice. Altogether, the STARNET database and the associated GRN browser (http://starnet.mssm.edu) provide a multiorgan framework for exploration of the molecular interplay between cardiometabolic disorders and CAD.

The majority of risk loci identified by genome-wide association studies (GWAS) are in non-coding regions, hampering their functional interpretation. Instead, transcriptome-wide association studies (TWAS) identify gene-trait associations, which can be used to prioritize candidate genes in disease-relevant tissue(s). Here, we aimed to systematically identify susceptibility genes for coronary artery disease (CAD) by TWAS. We trained prediction models of nine CAD-relevant tissues using EpiXcan based on two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these prediction models, we imputed gene expression of respective tissues from individual-level genotype data on 37,997 CAD cases and 42,854 controls for the subsequent gene-trait association analysis. Transcriptome-wide significant association (i.e. P RGS19 and KPTN, in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Our CAD TWAS work (i) prioritized candidate causal genes at known GWAS loci, (ii) identified 18 novel genes to be associated with CAD, and iii) suggested potential tissues and pathways of action for these TWAS CAD genes.

Transcriptome-wide association studies (TWAS) explore genetic variants affecting gene expression for association with a trait. Here we studied coronary artery disease (CAD) using this approach by first determining genotype-regulated expression levels in nine CAD relevant tissues by EpiXcan in two genetics-of-gene-expression panels, the Stockholm-Tartu Atherosclerosis Reverse Network Engineering Task (STARNET) and the Genotype-Tissue Expression (GTEx). Based on these data we next imputed gene expression in respective nine tissues from individual level genotype data on 37,997 CAD cases and 42,854 controls for a subsequent gene-trait association analysis. Transcriptome-wide significant association (P < 3.85e-6) was observed for 114 genes, which by genetic means were differentially expressed predominately in arterial, liver, and fat tissues. Of these, 96 resided within previously identified GWAS risk loci and 18 were novel (CAND1, EGFLAM, EZR, FAM114A1, FOCAD, GAS8, HOMER3, KPTN, MGP, NLRC4, RGS19, SDCCAG3, STX4, TSPAN11, TXNRD3, UFL1, WASF1, and WWP2). Gene set analyses showed that TWAS genes were strongly enriched in CAD-related pathways and risk traits. Associations with CAD or related traits were also observed for damaging mutations in 67 of these TWAS genes (11 novel) in whole-exome sequencing data of UK Biobank. Association studies in human genotype data of UK Biobank and expression-trait association statistics of atherosclerosis mouse models suggested that newly identified genes predominantly affect lipid metabolism, a classic risk factor for CAD. Finally, CRISPR/Cas9-based gene knockdown of RGS19 and KPTN in a human hepatocyte cell line resulted in reduced secretion of APOB100 and lipids in the cell culture medium. Taken together, our TWAS approach was able to i) prioritize genes at known GWAS risk loci and ii) identify novel genes which are associated with CAD.

Background Most of North and Western European countries recognized long ago the importance of specialized ACHD programmes and have today well-established Centre of excellence for management of ACHD patients. In contrast, even though Central and South-eastern (CESE) European region geographically comprise almost half of the European continent, little is known about ACHD status in vast majority of its countries. Purpose We aim to provide for the first time contemporary comprehensive overview of ACHD situation in CESE Europe. Methods We obtained data regarding current national ACHD status from 19 CESE European countries. Over the country national cardiac society, the ESC Working Group on ACHD has identified physician/s actively involved in ACHD care in these countries. Country's representative/s filled out an extensive survey regarding the provision of care for the year 2017 or/and 2018 comprised from five main questionnaires: country and hospital ACHD information, clinical activity information, interventional, and surgical cardiac procedures, infrastructure and staffing, health care system including funding, and education. Results The majority of countries have specialized ACHD centre; 13 out of 19 countries have a national tertiary centre. The median number of adult cardiologists and cardiologists specifically involved in ACHD care per country is 400 and 3, respectively. The median number of ACHD centres per country was one; year of establishment was 2007. Six countries have no dedicated centre. With the exception of Albania, these countries were relatively young, all have significantly lower GDP/capita in comparison with other CESE countries with an established service (p=0.005). The median number of outpatient visits and hospital admission per year was 900 and 135, respectively; cardiac catheter interventions and cardiac operations yearly were 49 and 40. Thirteen countries have a public health care system funded by their government, while six have also a small portion of private reimbursement. However, all countries have a financial cap imposed on ACHD care per hospital, leading to a patient waiting list and a restriction in the number of procedures. Conclusion In the past decades, the CESE European region has made significant progress in the state-of-the art ACHD care. The majority of countries nowadays have established ACHD services with a substantial patient workload comparable to the rest of Europe. Moreover, most centres are equipped with the necessary infrastructure. Contemporary provisions of ACHD care in the CESE European region is nevertheless challenged by generally lower financial resources, lower staffing levels and de-facto caps on the possibility to perform certain necessary procedures in comparison with Western European countries. These government healthcare financial constraints also restrict the required expansion in terms of numbers and complexity of surgical and interventional procedures locally. Funding Acknowledgement Type of funding source: None

To examine the current status of care and needs of adult congenital heart disease (ACHD) services in the Central and South Eastern European (CESEE) region.We obtained data regarding the national ACHD status for 19 CESEE countries from their ACHD representative based on an extensive survey for 2017 and/or 2018. Thirteen countries reported at least one tertiary ACHD centre with a median year of centre establishment in 2007 (interquartile range 2002-2013). ACHD centres reported a median of 2114 patients under active follow-up with an annual cardiac catheter and surgical intervention volume of 49 and 40, respectively. The majority (90%) of catheter or surgical interventions were funded by government reimbursement schemes. However, all 19 countries had financial caps on a hospital level, leading to patient waiting lists and restrictions in the number of procedures that can be performed. The median number of ACHD specialists per country was 3. The majority of centres (75%) did not have ACHD specialist nurses. The six countries with no dedicated ACHD centres had lower Gross Domestic Product per capita compared to the remainder (P = 0.005).The majority of countries in CESEE now have established ACHD services with adequate infrastructure and a patient workload comparable to the rest of Europe, but important gaps still exist. ACHD care is challenged or compromised by limited financial resources, insufficient staffing levels, and reimbursement caps on essential procedures compared to Western Europe. Active advocacy and increased resources are required to address the inequalities of care across the continent.

Background and aims Coronary artery disease (CAD) arises from the interaction of genetic and environmental factors. Although genome-wide association studies (GWAS) have identified multiple risk loci and single nucleotide polymorphisms (SNPs) associated with risk of CAD, they are predominantly located in non-coding or intergenic regions and their mechanisms of effect are largely unknown. Accordingly, our objective was to develop a data-driven informatics pipeline to understand complex CAD risk loci, and to apply this to a poorly understood cluster of SNPs in the vicinity of ZEB2. Methods We developed a unique informatics pipeline leveraging a multi-tissue CAD genetics-of-gene-expression dataset, GWAS datasets, and other resources. The pipeline first dissected SNP locations and their linkage disequilibrium relationships, and progressed through analyses of tissue-specific expression quantitative trait loci, and then gene-gene, gene-phenotype, SNP-phenotype relationships. The pipeline concluded by exploring CAD-relevant gene regulatory networks (GRNs). Results We identified three independent CAD risk SNPs in close proximity to the ZEB2 coding region (rs6740731, rs17678683 and rs2252641/rs1830321). Our pipeline determined that these SNPs likely act in concert via the atherosclerotic arterial wall and adipose tissues, by governing metabolic and lipid functions. In addition, ZEB2 is the top key driver of a liver-specific GRN that is related to lipid levels, metabolic and anthropometric measures, and CAD severity. Conclusions Using a novel informatics pipeline, we disclosed the multi-faceted mechanisms of action of the ZEB2-associated CAD risk SNPs. This pipeline can serve as a roadmap to dissect complex SNP-gene-tissue-phenotype relationships and to reveal targets for tissue- and gene-specific therapeutic interventions.

A genome wide meta-analysis by the CORtisol NETwork (CORNET) consortium(1) has identified genetic variants spanning the SERPINA6/SERPINA1 locus on chromosome 14, associated with morning plasma cortisol and predictive of cardiovascular disease (Crawford et al, Unpublished). SERPINA6 encodes Corticosteroid Binding Globulin (CBG), responsible for binding most cortisol in blood and putatively mediating delivery of cortisol to target tissues. We hypothesised that genetic variants in SERPINA6 influence CBG expression in liver and cortisol delivery to extra-hepatic tissues, influencing cortisol-regulated gene expression. The Stockholm Tartu Atherosclerosis Reverse Networks Engineering Task study (STARNET)(2) provides RNA sequencing data in 9 vascular and metabolic tissues from 600 genotyped individuals (mean age 65.8, 70.3% male) undergoing coronary artery bypass grafting. We used STARNET to identify SNPs associated with plasma cortisol at genome wide significance in CORNET as cis-eQTLs for SERPINA6 in liver and as trans-eQTLs for the expression of genes across STARNET tissues. Causal inference methodologies(3) were then employed for the network reconstruction of these trans-genes and their downstream targets. We identified 21 SNPs that both were associated with cortisol at genome wide significance in CORNET (p ≤ 5x10-8) and were cis-eQTLs for SERPINA6 expression in liver (q ≤ 0.05). Moreover, these SNPs were trans-eQTLs for sets of genes in liver, subcutaneous and visceral abdominal adipose tissue, with over-representation of known glucocorticoid-regulated genes in adipose. The highest confidence gene network identified was specific to subcutaneous adipose, with the interferon regulatory trans-gene, IRF2, controlling a putative glucocorticoid-regulated network. Targets in this network include LDB2 and LIPA, both associated with coronary artery disease. We conclude that variants in the SERPINA6/SERPINA1 locus mediate their effect on plasma cortisol through variation in SERPINA6 expression in liver, and in turn affect gene expression in extra-hepatic tissues through modulating cortisol delivery. This supports a dynamic role for CBG in modulating cortisol delivery to tissues. The cortisol-responsive gene networks identified here represent candidate pathways to mediate cardiovascular risk attributable to elevated cortisol. (1) Bolton, et al. (2014) PLOS Genet. 10:e1004474., (2) Franzén et al. (2016). Science 353:827., (3) Wang and Michoel. (2017). PLOS Comput. Biol. 13:e1005703.

Genome-wide association studies (GWAS) have identified hundreds of cardiometabolic disease (CMD) risk loci. However, they contribute little to genetic variance, and most downstream gene-regulatory mechanisms are unknown. We genotyped and RNA-sequenced vascular and metabolic tissues from 600 coronary artery disease patients in the Stockholm-Tartu Atherosclerosis Reverse Networks Engineering Task study (STARNET). Gene expression traits associated with CMD risk single-nucleotide polymorphism (SNPs) identified by GWAS were more extensively found in STARNET than in tissue- and disease-unspecific gene-tissue expression studies, indicating sharing of downstream cis-/trans-gene regulation across tissues and CMDs. In contrast, the regulatory effects of other GWAS risk SNPs were tissue-specific; abdominal fat emerged as an important gene-regulatory site for blood lipids, such as for the low-density lipoprotein cholesterol and coronary artery disease risk gene PCSK9 STARNET provides insights into gene-regulatory mechanisms for CMD risk loci, facilitating their translation into opportunities for diagnosis, therapy, and prevention.

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 BioMe 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 BioMe 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. Correction in: BMC MEDICAL GENOMICS, Volume: 12, Issue: 1, Article Number: 154, DOI: 10.1186/s12920-019-0573-9

RNA editing modifies transcripts and may alter their regulation or function. In humans, the most common modification is adenosine to inosine (A-to-I). We examined the global characteristics of RNA editing in 4,301 human tissue samples. More than 1.6 million A-to-I edits were identified in 62% of all protein-coding transcripts. mRNA recoding was extremely rare; only 11 novel recoding sites were uncovered. Thirty single nucleotide polymorphisms from genome-wide association studies were associated with RNA editing; one that influences type 2 diabetes (rs2028299) was associated with editing in ARPIN. Twenty-five genes, including LRP11 and PLIN5, had editing sites that were associated with plasma lipid levels. Our findings provide new insights into the genetic regulation of RNA editing and establish a rich catalogue for further exploration of this process.

Transcriptome-wide association studies (TWAS) integrate GWAS and gene expression datasets to find gene-trait associations. In this Perspective, we explore properties of TWAS as a potential approach to prioritize causal genes, using simulations and case studies of literature-curated candidate causal genes for schizophrenia, LDL cholesterol and Crohn’s disease. We explore risk loci where TWAS accurately prioritizes the likely causal gene, as well as loci where TWAS prioritizes multiple genes, some of which are unlikely to be causal, because they share the same variants as eQTLs. We illustrate that TWAS is especially prone to spurious prioritization when using expression data from tissues or cell types that are less related to the trait, due to substantial variation in both expression levels and eQTL strengths across cell types. Nonetheless, TWAS prioritizes candidate causal genes at GWAS loci more accurately than simple baselines based on proximity to lead GWAS variant and expression in trait-related tissue. We discuss current strategies and future opportunities for improving the performance of TWAS for causal gene prioritization. Our results showcase the strengths and limitations of using expression variation across individuals to determine causal genes at GWAS loci and provide guidelines and best practices when using TWAS to prioritize candidate causal genes.

Genome-wide association studies (GWAS) in coronary artery disease (CAD) had identified 66 loci at 'genome-wide significance' (P < 5 × 10(-8)) at the time of this analysis, but a much larger number of putative loci at a false discovery rate (FDR) of 5% (refs. 1,2,3,4). Here we leverage an interim release of UK Biobank (UKBB) data to evaluate the validity of the FDR approach. We tested a CAD phenotype inclusive of angina (SOFT; ncases = 10,801) as well as a stricter definition without angina (HARD; ncases = 6,482) and selected cases with the former phenotype to conduct a meta-analysis using the two most recent CAD GWAS. This approach identified 13 new loci at genome-wide significance, 12 of which were on our previous list of loci meeting the 5% FDR threshold, thus providing strong support that the remaining loci identified by FDR represent genuine signals. The 304 independent variants associated at 5% FDR in this study explain 21.2% of CAD heritability and identify 243 loci that implicate pathways in blood vessel morphogenesis as well as lipid metabolism, nitric oxide signaling and inflammation.

Inferring molecular networks can reveal how genetic perturbations interact with environmental factors to cause common complex diseases. We analyzed genetic and gene expression data from seven tissues relevant to coronary artery disease (CAD) and identified regulatory gene networks (RGNs) and their key drivers. By integrating data from genome-wide association studies, we identified 30 CAD-causal RGNs interconnected in vascular and metabolic tissues, and we validated them with corresponding data from the Hybrid Mouse Diversity Panel. As proof of concept, by targeting the key drivers AIP, DRAP1, POLR2I, and PQBP1 in a cross-species-validated, arterial-wall RGN involving RNA-processing genes, we re-identified this RGN in THP-1 foam cells and independent data from CAD macrophages and carotid lesions. This characterization of the molecular landscape in CAD will help better define the regulation of CAD candidate genes identified by genome-wide association studies and is a first step toward achieving the goals of precision medicine.