Community Research and Development Information Service - CORDIS

FP7

CVGENES-AT-TARGET Report Summary

Project ID: 601456
Funded under: FP7-HEALTH
Country: Germany

Final Report Summary - CVGENES-AT-TARGET (Exploitation of genomic variants affecting coronary artery disease and stroke risk for therapeutic intervention)

Executive Summary:
The scientific work of CVgenes-at-target was divided into 6 interrelated work packages (WP 1-6) organized in three programmes (programme 1-3):

Programme 1 aimed at identification of causal genetic variants and pathways affected by these while utilizing of before untapped resources and novel analytical technologies. Specifically, we applied in silico approaches to multiple layers of OMICs data to define the candidacy of genes and pathways affecting mechanisms leading to coronary artery disease (CAD) and stroke. Therefore, programme 1 contained of two work packages (WP), namely:

WP1: In silico identification and functional characterisation of druggable risk variants
WP2: Computations to identify and characterise networks/pathways surrounding CAD and stroke loci

In the course of programme 2 pathways affected by genetic variants causing CAD and/or stroke were functionally characterised – on cellular level, in whole animal disease models as well as in human atherosclerotic tissues. Specifically, we investigated pre-selected and newly confirmed causal genes and affected pathways in in vitro and in vivo models that allow studying their impact on the development of atherosclerosis and related traits. Once small molecules were identified interfering with CAD/stroke causing pathways, these (as well as indirectly the affected pathway) have been characterized in atherosclerosis-prone mice. In order to meet these objectives, programme 2 built on two work packages (WP), namely:

WP3: Molecular and cellular exploration of the causal mechanisms of CAD/stroke associated genetic loci
WP4: In vivo/ex vivo studies for target validation (a), and compound characterization (b)

Finally, in programme 3 assays were developed, enabling to monitor the activity of selected pathways and screened libraries to identify small molecules or antibodies that modulate the activity of respective pathways. This programme was divided in two work packages (WP):

WP5: Assay Development
WP6: Hit and tool discovery, lead identification

These three programmes presented a continuous process. After identifying promising genes and pathways in programme 1, predefined criteria supported decision-making steps addressing the options for such genes or pathways to be be further analysed on a functional level in programme 2 and on a pharmacological level in programme 3. However, we would like to emphasise that for several genes, we already had suffice evidence for their direct entry in programmes 2 and 3 at the starting point of CVgenes@target. In this way, the three programmes of CVgenes-at-target were able to run in parallel from the outset. We are convinced that this point was a particular strength of our project and allowed reaching our overall objectives optimally within the available time frame.
Project Context and Objectives:
In WP1, GWAS identified 16 novel risk loci for CAD represented by common SNPs implicating biological processes in vessel walls. Furthermore, a comprehensive analysis of the extent of pleiotropy of all CAD loci was undertaken, which helped us to understand the mechanisms how these loci affect CAD risk. Besides these major projects regarding common CAD risk variants, we contributed substantially to the identification of genes with rare, potentially functional, genetic variants with more profound effects on CAD risk; like ANGPTL4, SVEP1, ANGPTL3, CETP, LDLR and more. For stroke and small vessel disease additional low-frequency and common risk loci have been identified by a GWAS meta-analysis. Besides the identification of novel CAD and stroke risk variants/genes we successfully used circular chromatin conformation capturing followed by DNA sequencing (4C) to annotate susceptibility loci. As a consequence, novel candidate genes for human atherosclerotic disease within the associated gene regions were identified.

Within WP2 we have identified 171 co-expression networks/ modules in seven vascular and metabolic tissues from STAGE cohort. These were further supplemented with protein-protein interaction (PPI) from public databases and explored for their druggability potential. Within these networks CAD candidate genes and risk SNPs (provided by WP1) have been identified and used in the CVgenes-at-target evaluation pipeline. The next step was to prioritize modules containing at least one of the known CAD risk genes identified in GWAS. Among these, the most “promising” modules included LDLR, Col4A1, IL6R, ADM, and LRP1/FN1.

In WP3 a proteome-wide association study (PWAS) pipeline has been established. Of special interest was the genetic variant rs2107595 at the HDAC9 locus and its impact on vascular risk. Furthermore, in WP3 we have designed recombinant Adeno-Associated Virus (rAAV) targeting vectors and validated Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas9 for generating a specific knockout for a number of CAD risk loci, like HDAC9, ANRIL, ZC3HC1, KIAA1462, SVEP1, ARHGEF26, PHACTR1, MRAS, and LDB2. The vectors designed so far have been used for SNP insertion at the HDAC9 locus as well as a novel reporter and inducible expression system for ANRIL, a long noncoding RNA, at the 9p21 locus. The reporter cell line has been successfully used to screen for regulators of ANRIL expression and an inducible ANRIL line has been used to investigate the effects of ANRIL overexpression on gene regulation and cell phenotype.

In WP4 we could demonstrate a biological effect of candidate gene deficiency on atherogenesis, its progression and on plaque characteristics in a total of eight mouse models (HDAC9, ADAMTS7, KIA1462, ZC3HC1, LDB2, FES, HHIPL1, and PHACTR1). Furthermore, it was investigated in WP4 whether SNPs affect atherosclerotic plaque characteristics using data from the Athero-Express Biobank Study (AE, www.atheroexpress.nl). The most significant association was found for SNP rs12539895 (coded allele frequency = 0.75, odds ratio = 1.59 per C allele, p = 9.0 x 10-6). The same allele led to an increase of atheroma size as well as a raised CAD risk.

WP5 and WP6 were tightly interrelated and can report in silico high-thoughput screenings on homology models of HDAC9 and ADAMTS-7 and both molecules were also subjected to in vitro screens with hit compounds derived by this method and coming from in house libraries. Most importantly, this program led to new HDAC9 inhibitor structures that displayed good activity, stability, toxicity, and solubility properties. Two representative compound classes were successfully applied in a pharmacokinetic mouse model and one of these compounds will soon enter pre-clinical studies in a proof-of-concept atherosclerosis model.
Project Results:
WP1: In silico identification and functional characterization of druggable risk variants

While the duration of CVgenes-at-target we increased the number of coronary artery disease (CAD)/ myocardial infarction (MI) risk loci to more than 75. Furthermore, we could show that only one-third of these risk loci are associated with conventional cardiovascular risk factors, whereas at least one-half of the loci is associated with other diseases or traits (pleiotropy). These results lay the ground for future studies investigating the mechanisms that relate the observed pleiotropy to the pathogenesis of atherosclerosis and ischemic events.

Besides the identification of common CAD risk variants, we contributed substantially to the identification of genes with rare, potentially functional, genetic variants with more profound effects on CAD risk; like ANGPTL4, SVEP1, ANGPTL3, CETP, LDLR, APOA3 and more. These genes further complement the genetic architecture of CAD/MI, delivered new pathways and provided formidable starting points for functional studies and also revealed new targets for drug development. Likewise, for stroke and small vessel disease additional low-frequency and common risk loci have been identified by GWAS meta-analyses.

Our genome-wide sex-gene interaction analysis has initially revealed some interesting preliminary results, however we could not replicate all initial findings. Nonetheless, CAD has a sex-specific manifestation; therefore we conducted for the first time a comprehensive X-chromosome-wide meta-analysis including more than 43,000 CAD cases and 58,000 controls from 35 international study cohorts. Surprisingly, none of our investigated genetic models revealed genome-wide significant associations for any variant. Although we analysed the largest-to-date sample, currently available methods were not able to detect any associations of X-chromosomal variants with CAD.

Following the identification of novel risk loci/ candidate genes we successfully used circular chromatin conformation capturing followed by DNA sequencing (4C) to annotate susceptibility loci. As a consequence, novel candidate genes for human atherosclerotic disease within the associated gene regions were identified. In more detail, we identified physical 3D interaction with 326 candidate genes expressed in human monocytes or human coronary endothelial cells, of which 294 have not been reported before. We highlighted 16 genes based on expression quantitative trait loci. These candidate genes are of potential interest to better understand the complex pathophysiology of cardiovascular diseases.

Furthermore, a variant (rs12539895, risk allele A) at 7q22 that is associated with CAD, showed the strongest association with a single plaque characteristic (reduction of intraplaque fat, p < 5.0x10-6). We further characterised the 7q22 locus and provided evidence for its role in lipid metabolism and plaque fat content, possibly through the actions of HBP1 in plaques and COG5 in whole blood and liver.

Moreover, we were able to confirm many expected associations between cell and tissue types and common variants, such as the involvement of specific immune cell types in immune-related diseases and tissue types in diseases that affect specific organs, for example, inflammatory bowel disease and coronary artery disease. Other notable associations include adrenal glands in coronary artery disease, the immune system in Alzheimer’s disease, and the kidney for bone marrow density.

For complex diseases, like CAD and stroke, multi-locus association tests provide the opportunity to identify interacting causal loci (epistasis) contributing to the same trait and increase statistical power by reducing the FDR in the analyses. Here, all previously available datasets have underwent stringent QC and imputed based on the HRC reference genomes. In addition, we have collected and genotyped one more GWAS case-control study of coronary artery disease (CAD) at the DHM, i.e. GerMIFS VI, and have underwent the same analysis pipeline. As our focus analysis, statistical epistasis test was performed for each study separately within the broad-sense CAD susceptibility region and afterward fixed-effect meta-analysis were performed to combine the effects across studies. As a result of the achieved analysis, we have identified three SNP-pairs, which reached our stringent significance level: one trans-epistasis pair between FAM69A and HLA-DRA and two independent cis-epistasis pairs within chromosome 6 nearby LPA locus. As a next step, we expect further validation of our findings both statistically and biologically.


WP2: Computations (in silico) to identify and characterize networks and pathways surrounding CAD loci

During the course of CVgenes-at-target, we have successfully used sophisticated computational approaches, applied to a number of both open and unique datasets, such as STARNET to deepen our understanding of cardiovascular diseases including CAD, cardiometabolic diseases (CMDs) and stroke. These WP2 high-end publications are major achievements in themselves and have rendered strong international interest and attention for CVgenes-at-target.

For stroke, genome-wide association studies (GWAS) have progressed a bit slower and only recently (late 2016) we got access to the most updated list of lead SNPs that now has been comprehensive analysed using STARNET data - for the first time providing candidate genes in primarily arterial wall (AOR and IMA) and blood causally related to stroke. In addition, we found several stroke candidate genes also in metabolic tissues. These genes have now to be processed in a similar fashion to how we processed CAD and CMD genes in WP2 as outlined below.

For CAD and CMDs, we have gone beyond traditional eQTL network publications and used mainly the STAGE resource to create a first repository of network sub-modules containing risk genes established by GWAS lead risk SNPs and eQTLs for CAD as outlined above. In tissue-specific manner, these network modules offer both established and new biological processes and pathways serving as plausible insights into the biological mechanisms by which genetic risk is affecting CMDs and, CAD aetiologies. Furthermore, this network module repository also delivers new insights of both CAD-established, and novel drugs and drug targets that now can be further evaluated to reassess their effects on CAD and related risk factors. In sum, the identified network modules represent an unprecedented resource for tissue-specific gene–protein interactions directly affected by genetic variance in CAD risk loci that is essential for translation to GWAS risk lead SNPs and cardiovascular (CV) genes into new opportunities for CAD diagnostics and therapies.


WP3: Molecular and cellular exploration of the causal mechanisms of CAD/stroke associated genetic loci

A proteome-wide association study (PWAS) pipeline was established within CVgenes-at-target. The known 1456 lead and proxy SNPs of all 55 CAD/stroke risk loci (2013) were prioritized provided that they were in high linkage disequilibrium (r2≥0.8, according to 1000 Genomes phase 1 EUR panel) and an annotated DNAseI hypersensitive site at the SNP locus was measured in any cell line (ENCODE dataset). So far we have analysed the allele-specific binding of all 137 intergenic and the 211 intronic SNPs, which matched the prioritization criteria. In addition we included 50 SNPs as controls matching similar criteria except showing no association with CAD. In average we detect approx. 7 differentially bound proteins per intergenic or intronic SNP whereas control SNPs show only 3 differentially bound proteins on average. As expected, most measured proteins are involved in DNA or protein binding. Interestingly, factors involved in transcription are enriched in intergenic SNPs while intronic – as well as control SNPs – show a higher percentage of ATP-dependent processes (e.g. splicing).

We studied in more detail the mechanisms by which the genetic variant rs2107595 tagging the HDAC9 locus acts on vascular risk. We searched for allele-specific binding partners by proteome-wide analysis of SNPs (PWAS). We identified a preferential binding of the E2F3/TFDP1/Rb1 complex to the common allele, consistent with the disruption of a predicted E2F3 binding site by the risk allele. Interaction of the common allele with E2F3 was also demonstrated in vivo by chromatin immunoprecipitation. Gain- and loss-of-function studies together with cell synchronization experiments further revealed a role of E2F and Rb proteins in controlling cell cycle-dependent HDAC9 gene expression.

Moreover, we have designed 6 rAAV targeting vectors to support cell line engineering. The vectors designed have been for knock-in of each allele of the rs2107595 risk SNP at the HDAC9 locus and also the development of a novel reporter and inducible expression system for ANRIL, a long noncoding RNA at the 9p21 locus. In addition we have designed and validated CRISPR reagents for knockout generation for a number of loci including KIAA1462, SVEP1 ARGHEF26, LDB2, PHACTR1 and MRAS. Clustered regularly interspaced short palindromic repeats (CRISPR) is a nuclease genome editing technology in which the Cas9 nuclease is directed to a target locus by means of a synthetic gRNA. CRISPR benefits from increased efficiency and throughput when compared to rAAV, in particular for the generation of knockout models where multiple alleles can be modified simultaneously.

Furthermore, we have designed a siRNA library targeting genes in CAD associated loci. Genes were selected based on proximity to CAD associated loci, overlap with genomic features and expression in CAD relevant cell types. We have generated a second tier siRNA library to validate initial high-throughput screening results and allowed extended phenotyping.


WP4: In vivo / ex vivo studies for target validation (a), and compound characterization (b)

In WP4 we could demonstrate a biological effect of candidate gene deficiency on atherogenesis, its progression and on plaque characteristics in a total of eight mouse models (HDAC9, ADAMTS7, KIA1462, ZC3HC1, LDB2, FES, HHIPL1, and PHACTR1).

We created and investigated a mouse model lacking Adamts-7 via interruption of the Adamts7 gene. The mouse underwent large-scale phenotyping at the German Mouse Clinic. However, no relevant phenotypes were observed which strengthens the potential of targeting ADAMTS-7. Apoe-/-Adamts7-/- mice and Apoe-/- mice were fed a high cholesterol diet (HCD). Mass spectrometry analyses revealed increased protein levels of putative Adamts-7 targets, i.e., cartilage oligomeric matrix protein (Comp), and thrombospondin-1 (Tsp-1). Histological analyses of atherosclerotic plaques revealed mixed results. In mice fed a HCD, a clear effect of Adamts-7-deficiency was not observed. Aged Apoe-/-Adamts7-/- mice on chow diet tended to show less atherosclerotic plaques as compared to Apoe-/- mice. Bauer et al, however, demonstrated a reduction of atherosclerotic plaques in Adamts7-/- mice which was only weak on an Apoe-/- background but stronger on a Ldlr-/- background (Bauer et al, Circulation, 2015). Taken together, inhibition of ADAMTS-7 might be a promising strategy to reduce the burden of atherosclerosis without dramatic adverse effects on other organs.

The CAD associated variants at the chromosome 14q32 CAD locus fall in an uncharacterised gene called HHIPL1. We investigated the effect of Hhipl1 knockout on atherosclerosis in Apoe-/- and Ldlr-/- mice. Male double knockouts (Hhipl1-/-; Apoe-/- and Hhipl1-/-; Ldlr-/-) were fed a Western diet for 12 weeks and compared to littermates wild-type for Hhipl1 (Hhipl1+/+;Apoe-/- and Hhipl1+/+; Ldlr-/-). Atherosclerosis was assessed in the aorta by en face and in sections of the aortic root. Hhipl1-/-;Ldlr-/- mice exhibited a substantial reduction of 56% (±29%) (P=5x10-6) in lesion area compared to Hhipl1+/+;Ldlr-/- littermate controls as measured by en face and a 35% (±15%) reduction in lesion area (P=0.002) as measured in the root. Similar results were seen in Apoe-/- mice. We also investigated plaque composition in Hhipl1 knockout mice on Apoe-/- and Ldlr-/- backgrounds. We found no difference in lipid or macrophage content, however we saw a significant decrease in the proportion of smooth muscle cells within plaques and a trend towards reduced collagen. The plaques had a phenotype reminiscent of earlier stage lesions.

The Fes gene is located at the CAD-associated locus on chromosome 15q26. To investigate if FES gene has an effect on the development and characteristics of atherosclerotic lesions, we studied Fes wildtype and knockout mice that had been crossed with Apoe-/- mice or LDLR-/- mice, and fed a high fat diet. The study showed Fes knockout did not significantly affect atherosclerotic lesion formation and size, but did alter plaque composition. However, the atherosclerotic lesions in Fes knockout mice had significantly greater macrophage abundance than those in Fes wildtype mice. Additionally, the atherosclerotic lesions in Fes knockout mice had reduced collagen content but increased smooth muscle cell numbers. Thus, the study reveals that Fes does not significantly influence atherosclerotic lesion formation and size, but has a protective effect in the control of inflammation in the lesions.

Previous GWAS have revealed the HDAC9 gene region as the so far strongest risk locus for atherosclerotic stroke. rs2107595, the lead SNP in this region, resides in an intergenic region between HDAC9 and TWIST1. We recently demonstrated an attenuation of atheroprogression in Hdac-/-, Apoe-/- mice. The intergenic region is highly conserved across different species and comprises a cis-regulatory element marked by corresponding histone modifications. Based on the cell-type-specific regulatory nature of cis-elements, we hypothesized that mice lacking the respective element would provide information on the specific cell types mediating disease risk at the HDAC9 locus. Hence, we generated mice lacking the conserved cis-element. Our initial results point to a regulatory function of the cis-element in proinflammatory macrophages consistent with our functional data. Analysis of additional cell types is in progress. We are further exploring the effects of the cis-regulatory element on atheroprogression in Apoe-/- mice.

Furthermore, we investigated in WP4 whether SNPs affect atherosclerotic plaque characteristics using data from the Athero-Express Biobank Study (AE, www.atheroexpress.nl). The most significant association was found for SNP rs12539895 (coded allele frequency = 0.75, odds ratio = 1.59 per C allele, p = 9.0 x 10-6). The same allele led to an increase of atheroma size as well as a raised CAD risk.


WP5: Assay Development and
WP6: Hit and tool discovery, lead identification

WP5 and WP6 were tightly interrelated and can report in silico high-thoughput screenings on homology models of HDAC9 and ADAMTS-7 and both molecules were also subjected to in-vitro screens with hit compounds derived by this method and coming from in house libraries. Most importantly, this program led to new HDAC9 inhibitor structures that displayed good activity, stability, toxicity, and solubility properties. Two representative compound classes were successfully applied in a pharmacokinetic mouse model and one of these compounds will soon enter pre-clinical studies in a proof-of-concept atherosclerosis model.

In more detail, the main goal of WP5/WP6 was to identify lead molecules interfering with pathways leading to CAD and stroke. For this, the consortium followed two approaches: i) small molecule discovery programs for hit identification, validation and subsequent lead optimization, and ii) generation of monoclonal antibodies for the specific targets.

Concerning small molecules, hit identification and validation was performed on two targets already identified by members of the consortium (HDAC9 and ADAMTS7) and on three targets which were identified in other work packages during the first 18 months of the grant period; for these targets also a hit identification and validation campaign was performed (SLK, PHACTR1, and ANRIL).

The campaigns led to subsequent lead generation programs and resulted in at least 2 compound classes, which can be tested in proof-of-concept animal models.

With regard to monoclonal antibodies, mouse monoclonal antibodies against 2 target proteins identified by the consortium were generated. Batches of monoclonal antibodies were produced and tested for biological activity in assays developed in WP4. A candidate monoclonal antibody selected for biologic and therapeutic activity was humanized, however production processes in CHO cell lines were not possible in this case.

Furthermore, in silico high-throughput screenings were performed on homology models of HDAC9 and ADAMTS7 and both functional proteins were used for in vitro screens with the derived small molecule hit structures. Concerning ADAMTS7, a set of compounds has been selected, however could not be validated experimentally. For HDAC9, several hit compounds from two structural classes, derived from in silico screening (class 1) and an in house library by a “selective optimization of side activity” (SOSA) approach (class 2) were identified.

The small molecule drug development program for the inhibition of HDAC9 was successfully performed combining in silico screening, medicinal chemistry, and assay development expertise of the different project partners. This program led to new HDAC9 inhibitor structures that displayed good activity, stability, toxicity, and solubility properties. Two representative compound classes were successfully applied in a pharmacokinetic mouse model and one of these compounds will soon enter pre-clinical studies in a proof-of-concept atherosclerosis model.

As one of the secondary targets, the SLK / LDBD2 interaction was selected, as it is involved in transepithelial migration and might be important for macrophage infiltration in atherosclerotic lesions. Two hit structures for the serine-/threonine kinase SLK were found in a biochemical assay and could already be confirmed on a cellular level. Furthermore, more than 200 in silico hit structures are now available for screening and medicinal chemistry development.

A phenotypic screening assay based on cell migration was developed to investigate the association of Protein phosphatase and actin regulator protein 1 (PHACTR1) with cellular motility of SMCs. Measurement parameters for a multimode plate reader characterizing cell motility were established and validated. The developed assay system facilitated the screen of a library of known drugs containing 786 compounds in a fully automated process. As result of the small molecule screening general inhibitors and activators of SMC motility were identified. Vinorelbine, Ciclopirox, Fludarabine Phosphate, Mebendazole as well as Clobetasol Propionate were identified as inhibitors of SMC migration while Naloxone and Tolmetin activated SMC motility.

During the course of CVgenes-at-target we identified ANRIL as an additional target, here a firefly luciferase expressing reporter gene cell line for indirect monitoring of ANRIL expression and a counter cell line for identification of non-specific transcriptional regulators were generated and were utilised to generate high-throughput screening compatible assays. A fully automated screening of a library of 786 FDA-approved drugs against both reporter cell lines resulted in the identification of the ANRIL expression modulators Didanosine, 5-Fluoruracil, Myophenolate Mofetil, Mometasone Furoate, Nitazoxanide and Sertraline. These hits underwent further validation by qPCR to detect expression of various ANRIL isoforms. Two of the hit compounds were excluded from further examination following qPCR analysis. Didanosine had no effect on ANRIL expression by qPCR analysis, while Mycophenolate Mofetil was found to also induce expression of housekeeping genes. The three hit compounds found to down-regulate ANRIL expression in the reporter assay inhibited expression of the common linear ANRIL isoforms by approximately 50%. Nitazoxanide has recently been identified as an inhibitor of the cytoprotective protein NQO1. Treatment with dicumarol, another NQO1 inhibitor, also reduced expression of ANRIL. Ongoing analysis, outside of the program of work, will determine the mechanisms by which these compounds regulate ANRIL expression.
Potential Impact:
The CVgenes-at-target Consortium fully covers the requirements of the call topic “FP7-HEALTH-2013-INNOVATION-1, Discovery research to reveal novel targets for cardiovascular disease treatment”. We have delivered on the expected impact as described in the work programme.

CVgenes-at-target lifed a highly focused collaborative project to exploit our existing population genetic studies in order to fill in the gap with respect to identification, characterization and validation of therapeutically relevant targets for atherosclerotic disease. For decades, discovery research programs have been initiated in search for drug targets that will block progression of atherosclerotic disease. A multiple biomarkers have already been implicated in cardiovascular disease by epidemiologic association, however many therapeutic agents that have been developed to modulate their activities have failed to demonstrate safety and/or efficacy in suitably powered clinical trials. A major drawback in most of these cases has been a lack of target validation for a causal role. The strength of CVgenes-at-target was the successful initiation of a target identification and validation programme based on human genetic observations and potential validation using human plaque biobanks. The value chain, from discovery to application, was also strengthened by input of drug discovery, analytical and developmental experts that are operating within the SME participants.

CVgenes-at-target included the PIs of the largest and most widely recognised cardiovascular GWAS who have also explored further some of the targets for this project. So CVgenes-at-target started initially working on two targets, namely HDAC9 and ADAMTS-7 and as we have proposed in our grant application we can already deliver additional targets into the CVgenes-at-target target development pipeline (PHACTR1, KIAA1462, LDB2, ANRIL, MRAS, FES, and ZC3HC1).

The scientific impact of CVgenes-at-target relates to large-scale GWAS based on imputed data which resulted in a significant boosting of drug discovery research to explore the functional relevance of targets implicated in many disease areas, including cardiovascular disease. Based on the conducted studies, there is no doubt that the outcome of CVgenes-at-target has contributed to the understanding of cardiovascular disease.

CVgenes-at-target acknowledged its goals of discovering novel mechanisms leading to coronary atherosclerosis or stroke and therapeutic intervention in the underlying pathways are challenging. The identification of the responsible genes or regulatory mechanisms at the risk locus, the delineation of the subsequent mechanistic cascade leading to atherosclerosis, the search for therapeutically modifiable targets, as well as the identification of compounds that specifically modulate target activity were all ambitious. However, CVgenes-at-target was well equipped to meet these challenges and thus we reached our desired milestones, because:

• we had assembled unique resources of linked, large-scale GWA studies, transcriptomics, and proteomic databases to offer a solid foundation.
• the PIs of CVgenes-at-target offered synergistic and cutting-edge expertise to address the goals of this collaborative project. Indeed, the multidisciplinary nature of CVgenes-at-target spanned expertise from large-scale population studies and tissue sample collections, a leading bioinformatics SME specialized in genome-wide data analyses, sophisticated cell biological and in vivo expertise in atherosclerotic disease mechanisms, through an SME with advanced biotechnological tools that allowed the design and development of assays for drug discovery purposes and their use in assessing druggability against small molecules and antibody based therapeutics.

Significant progress has been made in explaining the effects of some of the genes at recently identified genomic risk loci, including the generation of transgenic and knock-out models that already offer new models for key disease processes in humans. Thereby, proof-of-principle targets have already been uncovered by the CVgenes-at-target PIs (ADAMTS7, HDAC9) and this allowed us a jump-start into the most demanding part of the project, i.e. identification of lead compounds for therapeutic intervention.


Main dissemination activities and exploitation of results

The dissemination of results arising from the work of the consortium has been particularly successful. Some of the key dissemination activities were as follows:

1. A joint meeting of three EU FP7 consortia was organised in Zandvoort near Amsterdam in September 2016 including a popular scientific component targeted at general public.
2. Approximately 40 manuscripts reporting results from the work of the consortium have already been published in high-ranking peer-reviewed scientific journals.
3. Dedicated scientific presentations outlining the work of the consortium took place.
4. A press release was prepared and disseminated at the beginning of the project.
5. A public website was created and successfully used to co-ordinate actions of the consortium and to disseminate its work.


Heart at Target - joint meeting of three EU FP7 consortia on cardiovascular research

On 27-28 September 2016, three consortia of EU FP7 projects which were focused on identification and validation of new targets for drugs in cardiovascular disease organized a joint meeting in Zandvoort, The Netherlands. The three projects started in October 2013.

The meeting started on Tuesday afternoon with a session opened by a representative of the European Commission, Dr. Grzegorz Owsianik. Dr. Owsianik stressed that CVD is still the main cause of death in Europe and therefore a very important research area supported by the EU in FP7 projects but also several projects under the H2020 funding. Demonstration of this support are the three project consortia that were presented by their coordinators and he called this joint meeting an excellent and unique initiative in which the important issue of knowledge sharing in R&D is shown in optima forma.

The introductions were followed by presentations of two highlights from each consortium. In addition, the second day was a networking event with pitches of the available technologies presented by the academia and SMEs. The three FP7 consortia seek further collaboration and aim to efficiently use the resources and expertise represented within the consortia.

With 60 participants from the three consortia, represented by researchers from academia, several SMEs and big pharma, from 15 European countries, the attendance exceeded the expectations. The Heart at Target meeting resulted in informal interactions, discussions and new collaborative initiatives. This open sharing of technologies and latest research results leads to optimal dissemination of latest developments supported by the EU and thus aids the increase of output from these research projects in a very relevant disease area.


Publications

A list of the key scientific publications published in high-ranking, peer-reviewed journals to date is included here:

• Fifteen new risk loci for coronary artery disease highlight arterial-wall-specific mechanisms.

Howson JMM, Zhao W, Barnes DR, Ho WK, Young R, Paul DS, Waite LL, Freitag DF, Fauman EB, Salfati EL, Sun BB, Eicher JD, Johnson AD, Sheu WHH, Nielsen SF, Lin WY, Surendran P, Malarstig A, Wilk JB, Tybjærg-Hansen A, Rasmussen KL, Kamstrup PR, Deloukas P, Erdmann J, Kathiresan S, Samani NJ, Schunkert H, Watkins H; CARDIoGRAMplusC4D., Do R, Rader DJ, Johnson JA, Hazen SL, Quyyumi AA, Spertus JA, Pepine CJ, Franceschini N, Justice A, Reiner AP, Buyske S, Hindorff LA, Carty CL, North KE, Kooperberg C, Boerwinkle E, Young K, Graff M, Peters U, Absher D, Hsiung CA, Lee WJ, Taylor KD, Chen YH, Lee IT, Guo X, Chung RH, Hung YJ, Rotter JI, Juang JJ, Quertermous T, Wang TD, Rasheed A, Frossard P, Alam DS, Majumder AAS, Di Angelantonio E, Chowdhury R; EPIC-CVD., Chen YI, Nordestgaard BG, Assimes TL, Danesh J, Butterworth AS, Saleheen D.

Nat Genet. 2017 published ahead of print.


• Functional Characterization of the GUCY1A3 Coronary Artery Disease Risk Locus.

Kessler T, Wobst J, Wolf B, Eckhold J, Vilne B, Hollstein R, von Ameln S, Dang TA, Sager HB, Rumpf PM, Aherrahrou R, Kastrati A, Bjoerkegren JLM, Erdmann J, Lusis AJ, Civelek M, Kaiser FJ, Schunkert H.

Circulation. 2017 published ahead of print.


• Loss of Cardio-Protective Effects at the ADAMTS7 Locus Due to Gene-Smoking Interactions.

Saleheen D, Zhao W, Young R, Nelson CP, Ho WK, Ferguson JF, Rasheed A, Ou K, Nurnberg ST, Bauer RC, Goel A, Do R, Stewart AFR, Hartiala J, Zhang W, Thorleifsson G, Strawbridge RJ, Sinisalo J, Kanoni S, Sedaghat S, Marouli E, Kristiansson K, Zhao JH, Scott R, Gauguier D, Shah SH, Smith AV, Van Zuydam N, Cox AJ, Willenborg C, Kessler T, Zeng L, Province MA, Ganna A, Lind L, Pedersen NL, White CC, Joensuu A, Kleber ME, Hall AS, März W, Salomaa V, O'Donnell C, Ingelsson E, Feitosa MF, Erdmann J, Bowden DW, Palmer CNA, Gudnason V, de Faire U, Zalloua P, Wareham N, Thompson JR, Kuulasmaa K, Dedoussis G, Perola M, Dehghan A, Chambers JC, Kooner J, Allayee H, Deloukas P, McPherson R, Stefansson K, Schunkert H, Kathiresan S, Farrall M, Frossard PM, Rader DJ, Samani N, Reilly MP; EPIC-CVD.; PROMIS.; CARDIoGRAMplusC4D.

Circulation. 2017 published ahead of print.


• Association of Rare and Common Variation in the Lipoprotein Lipase Gene With Coronary Artery Disease.

Khera AV, Won HH, Peloso GM, O'Dushlaine C, Liu D, Stitziel NO, Natarajan P, Nomura A, Emdin CA, Gupta N, Borecki IB, Asselta R, Duga S, Merlini PA, Correa A, Kessler T, Wilson JG, Bown MJ, Hall AS, Braund PS, Carey DJ, Murray MF, Kirchner HL, Leader JB, Lavage DR, Manus JN, Hartzel DN, Samani NJ, Schunkert H, Marrugat J, Elosua R, McPherson R, Farrall M, Watkins H, Lander ES, Rader DJ, Danesh J, Ardissino D, Gabriel S, Willer C, Abecasis GR, Saleheen D, Dewey FE, Kathiresan S; Myocardial Infarction Genetics Consortium, DiscovEHR Study Group, CARDIoGRAM Exome Consortium, and Global Lipids Genetics Consortium.

JAMA. 2017;317:937-946.


• Phenotypic Characterization of Genetically Lowered Human Lipoprotein(a) Levels.

Emdin CA, Khera AV, Natarajan P, Klarin D, Won HH, Peloso GM, Stitziel NO, Nomura A, Zekavat SM, Bick AG, Gupta N, Asselta R, Duga S, Merlini PA, Correa A, Kessler T, Wilson JG, Bown MJ, Hall AS, Braund PS, Samani NJ, Schunkert H, Marrugat J, Elosua R, McPherson R, Farrall M, Watkins H, Willer C, Abecasis GR, Felix JF, Vasan RS, Lander E, Rader DJ, Danesh J, Ardissino D, Gabriel S, Saleheen D, Kathiresan S; CHARGE–Heart Failure Consortium; CARDIoGRAM Exome Consortium.

J Am Coll Cardiol. 2016;68:2761-2772


• No Association of Coronary Artery Disease with X-Chromosomal Variants in Comprehensive International Meta-Analysis.

Loley C, Alver M, Assimes TL, Bjonnes A, Goel A, Gustafsson S, Hernesniemi J, Hopewell JC, Kanoni S, Kleber ME, Lau KW, Lu Y, Lyytikäinen LP, Nelson CP, Nikpay M, Qu L, Salfati E, Scholz M, Tukiainen T, Willenborg C, Won HH, Zeng L, Zhang W, Anand SS, Beutner F, Bottinger EP, Clarke R, Dedoussis G, Do R, Esko T, Eskola M, Farrall M, Gauguier D, Giedraitis V, Granger CB, Hall AS, Hamsten A, Hazen SL, Huang J, Kähönen M, Kyriakou T, Laaksonen R, Lind L, Lindgren C, Magnusson PK, Marouli E, Mihailov E, Morris AP, Nikus K, Pedersen N, Rallidis L, Salomaa V, Shah SH, Stewart AF, Thompson JR, Zalloua PA, Chambers JC, Collins R, Ingelsson E, Iribarren C, Karhunen PJ, Kooner JS, Lehtimäki T, Loos RJ, März W, McPherson R, Metspalu A, Reilly MP, Ripatti S, Sanghera DK, Thiery J, Watkins H, Deloukas P, Kathiresan S, Samani NJ, Schunkert H, Erdmann J, König IR.

Sci Rep. 2016;6:35278.


• Diagnostic Yield and Clinical Utility of Sequencing Familial Hypercholesterolemia Genes in Patients With Severe Hypercholesterolemia.

Khera AV, Won HH, Peloso GM, Lawson KS, Bartz TM, Deng X, van Leeuwen EM, Natarajan P, Emdin CA, Bick AG, Morrison AC, Brody JA, Gupta N, Nomura A, Kessler T, Duga S, Bis JC, van Duijn CM, Cupples LA, Psaty B, Rader DJ, Danesh J, Schunkert H, McPherson R, Farrall M, Watkins H, Lander E, Wilson JG, Correa A, Boerwinkle E, Merlini PA, Ardissino D, Saleheen D, Gabriel S, Kathiresan S.

J Am Coll Cardiol. 2016;67:2578-89.


• Cystatin C and Cardiovascular Disease: A Mendelian Randomization Study.

van der Laan SW, Fall T, Soumaré A, Teumer A, Sedaghat S, Baumert J, Zabaneh D, van Setten J, Isgum I, Galesloot TE, Arpegård J, Amouyel P, Trompet S, Waldenberger M, Dörr M, Magnusson PK, Giedraitis V, Larsson A, Morris AP, Felix JF, Morrison AC, Franceschini N, Bis JC, Kavousi M, O'Donnell C, Drenos F, Tragante V, Munroe PB, Malik R, Dichgans M, Worrall BB, Erdmann J, Nelson CP, Samani NJ, Schunkert H, Marchini J, Patel RS, Hingorani AD, Lind L, Pedersen NL, de Graaf J, Kiemeney LA, Baumeister SE, Franco OH, Hofman A, Uitterlinden AG, Koenig W, Meisinger C, Peters A, Thorand B, Jukema JW, Eriksen BO, Toft I, Wilsgaard T, Onland-Moret NC, van der Schouw YT, Debette S, Kumari M, Svensson P, van der Harst P, Kivimaki M, Keating BJ, Sattar N, Dehghan A, Reiner AP5, Ingelsson E, den Ruijter HM, de Bakker PI, Pasterkamp G, Ärnlöv J, Holmes MV, Asselbergs FW.

J Am Coll Cardiol. 2016;68:934-45.


• Cardiometabolic risk loci share downstream cis- and trans-gene regulation across tissues and diseases.

Franzén O, Ermel R, Cohain A, Akers NK, Di Narzo A, Talukdar HA, Foroughi-Asl H, Giambartolomei C, Fullard JF, Sukhavasi K, Köks S, Gan LM, Giannarelli C, Kovacic JC, Betsholtz C, Losic B, Michoel T, Hao K, Roussos P, Skogsberg J, Ruusalepp A, Schadt EE, Björkegren JL.

Science. 2016;353:827-830.


• Human Validation of Genes Associated With a Murine Atherosclerotic Phenotype.

Pasterkamp G, van der Laan SW, Haitjema S, Foroughi Asl H, Siemelink MA, Bezemer T, van Setten J, Dichgans M, Malik R, Worrall BB, Schunkert H, Samani NJ, de Kleijn DP, Markus HS, Hoefer IE, Michoel T, de Jager SC, Björkegren JL, den Ruijter HM, Asselbergs FW.

Arterioscler Thromb Vasc Biol. 2016;36:1240-1246.


• Coding Variation in ANGPTL4, LPL, and SVEP1 and the Risk of Coronary Disease.

Myocardial Infarction Genetics and CARDIoGRAM Exome Consortia Investigators, Stitziel NO, Stirrups KE, Masca NG, Erdmann J, Ferrario PG, König IR, Weeke PE, Webb TR, Auer PL, Schick UM, Lu Y, Zhang H, Dube MP, Goel A, Farrall M, Peloso GM, Won HH, Do R, van Iperen E, Kanoni S, Kruppa J, Mahajan A, Scott RA, Willenberg C, Braund PS, van Capelleveen JC, Doney AS, Donnelly LA, Asselta R, Merlini PA, Duga S, Marziliano N, Denny JC, Shaffer CM, El-Mokhtari NE, Franke A, Gottesman O, Heilmann S, Hengstenberg C, Hoffman P, Holmen OL, Hveem K, Jansson JH, Jöckel KH, Kessler T, Kriebel J, Laugwitz KL, Marouli E, Martinelli N, McCarthy MI, Van Zuydam NR, Meisinger C, Esko T, Mihailov E, Escher SA, Alver M, Moebus S, Morris AD, Müller-Nurasyid M, Nikpay M, Olivieri O, Lemieux Perreault LP, AlQarawi A, Robertson NR, Akinsanya KO, Reilly DF, Vogt TF, Yin W, Asselbergs FW, Kooperberg C, Jackson RD, Stahl E, Strauch K, Varga TV, Waldenberger M, Zeng L, Kraja AT, Liu C, Ehret GB, Newton-Cheh C, Chasman DI, Chowdhury R, Ferrario M, Ford I, Jukema JW, Kee F, Kuulasmaa K, Nordestgaard BG, Perola M, Saleheen D, Sattar N, Surendran P, Tregouet D, Young R, Howson JM, Butterworth AS, Danesh J, Ardissino D, Bottinger EP, Erbel R, Franks PW, Girelli D, Hall AS, Hovingh GK, Kastrati A, Lieb W, Meitinger T, Kraus WE, Shah SH, McPherson R, Orho-Melander M, Melander O, Metspalu A, Palmer CN, Peters A, Rader D, Reilly MP, Loos RJ, Reiner AP, Roden DM, Tardif JC, Thompson JR, Wareham NJ, Watkins H, Willer CJ, Kathiresan S, Deloukas P, Samani NJ, Schunkert H.

N Engl J Med. 2016;374:1134-44.


• Cross-Tissue Regulatory Gene Networks in Coronary Artery Disease.

Talukdar HA, Foroughi Asl H, Jain RK, Ermel R, Ruusalepp A, Franzén O, Kidd BA, Readhead B, Giannarelli C, Kovacic JC, Ivert T, Dudley JT, Civelek M, Lusis AJ, Schadt EE, Skogsberg J, Michoel T, Björkegren JL.

Cell Syst. 2016;2:196-208.


• Rare variant in scavenger receptor BI raises HDL cholesterol and increases risk of coronary heart disease.

Zanoni P, Khetarpal SA, Larach DB, Hancock-Cerutti WF, Millar JS, Cuchel M, DerOhannessian S, Kontush A, Surendran P, Saleheen D, Trompet S, Jukema JW, De Craen A, Deloukas P, Sattar N, Ford I, Packard C, Majumder Aa, Alam DS, Di Angelantonio E, Abecasis G, Chowdhury R, Erdmann J, Nordestgaard BG, Nielsen SF, Tybjærg-Hansen A, Schmidt RF, Kuulasmaa K, Liu DJ, Perola M, Blankenberg S, Salomaa V, Männistö S, Amouyel P, Arveiler D, Ferrieres J, Müller-Nurasyid M, Ferrario M, Kee F, Willer CJ, Samani N, Schunkert H, Butterworth AS, Howson JM, Peloso GM, Stitziel NO, Danesh J, Kathiresan S, Rader DJ; CHD Exome+ Consortium.; CARDIoGRAM Exome Consortium.; Global Lipids Genetics Consortium..

Science. 2016;351:1166-71.


• Systematic analysis of variants related to familial hypercholesterolemia in families with premature myocardial infarction.

Brænne I, Kleinecke M, Reiz B, Graf E, Strom T, Wieland T, Fischer M, Kessler T, Hengstenberg C, Meitinger T, Erdmann J, Schunkert H.

Eur J Hum Genet. 2016;24:191-7.


• A comprehensive 1000 Genomes-based genome-wide association meta-analysis of coronary artery disease.

Nikpay M, Goel A, Won HH, Hall LM, Willenborg C, Kanoni S, Saleheen D, Kyriakou T, Nelson CP, Hopewell JC, Webb TR, Zeng L, Dehghan A, Alver M, Armasu SM, Auro K, Bjonnes A, Chasman DI, Chen S, Ford I, Franceschini N, Gieger C, Grace C, Gustafsson S, Huang J, Hwang SJ, Kim YK, Kleber ME, Lau KW, Lu X, Lu Y, Lyytikäinen LP, Mihailov E, Morrison AC, Pervjakova N, Qu L, Rose LM, Salfati E, Saxena R, Scholz M, Smith AV, Tikkanen E, Uitterlinden A, Yang X, Zhang W, Zhao W, de Andrade M, de Vries PS, van Zuydam NR, Anand SS, Bertram L, Beutner F, Dedoussis G, Frossard P, Gauguier D, Goodall AH, Gottesman O, Haber M, Han BG, Huang J, Jalilzadeh S, Kessler T, König IR, Lannfelt L, Lieb W, Lind L, Lindgren CM, Lokki ML, Magnusson PK, Mallick NH, Mehra N, Meitinger T, Memon FU, Morris AP, Nieminen MS, Pedersen NL, Peters A, Rallidis LS, Rasheed A, Samuel M, Shah SH, Sinisalo J, Stirrups KE, Trompet S, Wang L, Zaman KS, Ardissino D, Boerwinkle E, Borecki IB, Bottinger EP, Buring JE, Chambers JC, Collins R, Cupples LA, Danesh J, Demuth I, Elosua R, Epstein SE, Esko T, Feitosa MF, Franco OH, Franzosi MG, Granger CB, Gu D, Gudnason V, Hall AS, Hamsten A, Harris TB, Hazen SL, Hengstenberg C, Hofman A, Ingelsson E, Iribarren C, Jukema JW, Karhunen PJ, Kim BJ, Kooner JS, Kullo IJ, Lehtimäki T, Loos RJ, Melander O, Metspalu A, März W, Palmer CN, Perola M, Quertermous T, Rader DJ, Ridker PM, Ripatti S, Roberts R, Salomaa V, Sanghera DK, Schwartz SM, Seedorf U, Stewart AF, Stott DJ, Thiery J, Zalloua PA, O'Donnell CJ, Reilly MP, Assimes TL, Thompson JR, Erdmann J, Clarke R, Watkins H, Kathiresan S, McPherson R, Deloukas P, Schunkert H, Samani NJ, Farrall M; CARDIoGRAMplusC4D Consortium.

Nat Genet. 2015;47:1121-30.


• Prediction of Causal Candidate Genes in Coronary Artery Disease Loci.

Brænne I, Civelek M, Vilne B, Di Narzo A, Johnson AD, Zhao Y, Reiz B, Codoni V, Webb TR, Foroughi Asl H, Hamby SE, Zeng L, Trégouët DA, Hao K, Topol EJ, Schadt EE, Yang X, Samani NJ, Björkegren JL, Erdmann J, Schunkert H, Lusis AJ; Leducq Consortium CAD Genomics.

Arterioscler Thromb Vasc Biol. 2015;35:2207-2217.


• Genetically Determined Height and Coronary Artery Disease.

Nelson CP, Hamby SE, Saleheen D, Hopewell JC, Zeng L, Assimes TL, Kanoni S, Willenborg C, Burgess S, Amouyel P, Anand S, Blankenberg S, Boehm BO, Clarke RJ, Collins R, Dedoussis G, Farrall M, Franks PW, Groop L, Hall AS, Hamsten A, Hengstenberg C, Hovingh GK, Ingelsson E, Kathiresan S, Kee F, König IR, Kooner J, Lehtimäki T, März W, McPherson R, Metspalu A, Nieminen MS, O'Donnell CJ, Palmer CN, Peters A, Perola M, Reilly MP, Ripatti S, Roberts R, Salomaa V, Shah SH, Schreiber S, Siegbahn A, Thorsteinsdottir U, Veronesi G, Wareham N, Willer CJ, Zalloua PA, Erdmann J, Deloukas P, Watkins H, Schunkert H, Danesh J, Thompson JR, Samani NJ; CARDIoGRAM+C4D Consortium.

N Engl J Med. 2015;372:1608-18.


• ADAMTS-7 inhibits re-endothelialization of injured arteries and promotes vascular remodeling through cleavage of thrombospondin-1.

Kessler T, Zhang L, Liu Z, Yin X, Huang Y, Wang Y, Fu Y, Mayr M, Ge Q, Xu Q, Zhu Y, Wang X, Schmidt K, de Wit C, Erdmann J, Schunkert H, Aherrahrou Z, Kong W.

Circulation. 2015;131:1191-201.


Presentations:

The following oral presentations present work done in the context of the CVgenes-at-target project and were presented for the first time during the reporting period:

• Implications of understanding the genetic basis of coronary artery disease.

Samani NJ, University of Leicester, United Kingdom

Oral presentation at ESHG, Copenhagen, Denmark, 29 May 2017.


• GWAS for Coronary Artery Disease; Novel Findings on Genetics and Mendelian Randomization.

Schunkert H, Deutsches Herzzentrum München, Germany

Oral presentations at the European Atherosclerosis Society (EAS) Congress, Innsbruck, Austria, 29 May - 01 June 2016.


• Athero-Express.

Pasterkamp G, Universitair Medisch Centrum Utrecht, The Netherlands

Oral presentations at European Atherosclerosis Society (EAS) Congress, Innsbruck, Austria, 29 May - 01 June 2016.


• Human Genetics as a Guide to new Therapies for Atherosclerosis.

Samani NJ, University of Leicester, United Kingdom

Oral presentation at American Heart Association (AHA) Scientific Sessions, Orlando, Florida, USA, 08 November 2015.


• Drug Discovery Outside The Pharmaceutical Industry: The Fraunhofer Experience.

Gul S, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V., Germany

Keynote presentation at Leibniz Research Alliance Bioactive Compounds and Biotechnology Bioactive Compounds Conference, Hamburg, Germany, 27-28 April 2015.


• Large-Scale Genomic Studies of Coronary Artery Disease/Myocardial Infarction.

Schunkert H, Deutsches Herzzentrum München, Germany

Oral presentation at the American Heart Association (AHA), Chicago, USA, 15-19 November 2014.


• What Have We Learned from Large-Scale Genomics in Cardiovascular Disease and Stroke?

Samani NJ, University of Leicester, United Kingdom

Oral presentation at American Heart Association (AHA), Chicago, USA, 17 November 2014.


• Epidemiology and Genetics - Using genetics to predict stroke risk: is it useful now and will it be in the future.

Dichgans M, Ludwig-Maximilians-Universität München, Germany

Oral presentations at the 9th World Stroke Congress, Istanbul, Turkey, 24 October 2014.
List of Websites:
http://cvgenesattarget.eu/

Related information

Reported by

DEUTSCHES HERZZENTRUM MUNCHEN
Germany

Subjects

Life Sciences
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