Toward Diagnostics and Therapies of Molecular Subcategories of CAD
CAD 分子亚类的诊断和治疗
基本信息
- 批准号:9497813
- 负责人:
- 金额:$ 79.88万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-09-01 至 2019-11-30
- 项目状态:已结题
- 来源:
- 关键词:AbdomenAchievementAddressAllelesAngiographyAnimal ModelAreaAtherosclerosisBenchmarkingBiochemical PathwayBiological MarkersBiological ModelsBiologyBiopsyBloodBlood VesselsCardiologyCardiovascular systemCause of DeathCell Differentiation processCell modelChestClinicalClinical ResearchComplexCoronary ArteriosclerosisCoronary Artery BypassDNADNA analysisDataData SetDevelopmentDiagnosisDiagnosticDiseaseDisease PathwayEngineeringEventFamilyFatty acid glycerol estersFoam CellsFoundationsFutureGenesGeneticGenetic DiseasesGenetic ModelsGenomicsGenotypeGoalsHeritabilityHospitalsIn VitroIndividualInheritedInstitutesInvestmentsLeadLinkLiverMachine LearningMapsMeta-AnalysisMetabolicMolecularMolecular DiseaseMyocardial InfarctionNew YorkOperative Surgical ProceduresOutcomePathway AnalysisPathway interactionsPatientsPharmacotherapyPhenotypePlasmaPlasma ProteinsPreventivePreventive carePreventive therapyProspective StudiesQuantitative Trait LociRNARNA SequencesRegulator GenesResearchResearch ProposalsRiskSamplingSingle Nucleotide PolymorphismSkeletal MuscleSubcategorySystemTechniquesTestingTissuesTranslatingTwin Multiple BirthTwin StudiesVariantWhole Bloodabdominal fatbiological systemsclinical predictorsclinical riskcomputer based statistical methodscoronary eventcoronary lesiondisorder riskfollow-upgenetic analysisgenome wide association studyin vivo Modelmacrophagemedical schoolsmolecular phenotypemonocytemultidisciplinarynovelnovel diagnosticsnovel therapeuticspercutaneous coronary interventionpersonalized carepersonalized diagnosticspersonalized medicinepredictive markerpredictive modelingprospectiveprotein biomarkerspublic health relevancerecruitrisk variantsubcutaneoustargeted biomarkertherapeutic targettraittranscriptome sequencing
项目摘要
DESCRIPTION (provided by applicant): Coronary artery disease (CAD) is a leading cause of death worldwide and in the US. While the genetics of this disease are intrinsically complex, thanks to huge research investments during the last 5-10 years, particularly in genome-wide association studies (GWAS), a more unbiased, data-driven and realistic view of CAD has been achieved. As part of this achievement, ~160 common risk loci for CAD/myocardial infarction (MI) have been identified. An important task is now to understand the molecular mechanisms/pathways by which these loci exert risk for CAD/MI allowing to translating the initial findings into new therapies and diagnostics. However, since the loci identified thus far explain only ~10% of variation in CAD/MI risk, it is also essential to define additional CAD pathways operating in parallel with GWA loci. In recent years, clinical studies that consider intermediate phenotypes (between DNA and disease) have greatly enhanced interpretations of risk loci identified in GWA datasets. In addition, disease networks that can be identified from intermediate molecular phenotypes provide an essential framework to identify novel CAD pathways and targets for new CAD therapies. Over the last 6 years, we have performed a clinical study considering many intermediate phenotypes in CAD patients (the STARNET study). In this proposal we intend to use newly generated DNA genotype and RNA sequence data from the STARNET study to identify atherosclerosis and metabolic networks underlying CAD. We then propose a new prospective study of CAD (the NGS-PREDICT study) with the main purpose of validating findings from the STARNET study. We hypothesize that the extent and stability of coronary lesions, thus clinical outcomes can be accurately assessed by defining the status of key atherosclerosis gene networks. In turn, metabolic networks active in liver, abdominal fat, and skeletal muscle influence the status of the atherosclerosis gene networks. In addition, molecular data isolated from easily obtainable tissues (e.g., blood, subcutaneous fat and plasma) can be used to identify biomarkers that can predict risk for clinical events caused by CAD. To test these hypotheses, we propose the following specific aims. Aim 1: To identify regulatory Bayesian gene networks causally linked to CAD and/or CAD sub-phenotypes using the STARNET datasets and the CARDIoGRAM meta-analysis GWA datasets. Aim 2: Identify biomarkers predicting clinical events of CAD (reflected in SYNTAX score) by applying machine learning on DNA genotype, RNA sequence and CAD plasma protein data from easily obtainable tissues of the STARNET cases. Aim 3: To validate the identified causal CAD eQTLs/networks and the biomarkers using the NGS-PREDICT study performed at the Mt. Sinai Hospital, the Swedish Twin study and CAD cell and animal models. We believe the proposed studies can lead to a significantly better molecular understanding of CAD and thus, serve the more long-term goal of preventive and personalized therapies of CAD patients diagnosed in well-defined molecular subcategories.
项目成果
期刊论文数量(8)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
An integrative multiomic network model links lipid metabolism to glucose regulation in coronary artery disease.
- DOI:10.1038/s41467-020-20750-8
- 发表时间:2021-01-22
- 期刊:
- 影响因子:16.6
- 作者:Cohain AT;Barrington WT;Jordan DM;Beckmann ND;Argmann CA;Houten SM;Charney AW;Ermel R;Sukhavasi K;Franzen O;Koplev S;Whatling C;Belbin GM;Yang J;Hao K;Kenny EE;Tu Z;Zhu J;Gan LM;Do R;Giannarelli C;Kovacic JC;Ruusalepp A;Lusis AJ;Bjorkegren JLM;Schadt EE
- 通讯作者:Schadt EE
Global analysis of A-to-I RNA editing reveals association with common disease variants.
- DOI:10.7717/peerj.4466
- 发表时间:2018
- 期刊:
- 影响因子:2.7
- 作者:Franzén O;Ermel R;Sukhavasi K;Jain R;Jain A;Betsholtz C;Giannarelli C;Kovacic JC;Ruusalepp A;Skogsberg J;Hao K;Schadt EE;Björkegren JLM
- 通讯作者:Björkegren JLM
Carbonyl reductase 1 catalyzes 20β-reduction of glucocorticoids, modulating receptor activation and metabolic complications of obesity.
- DOI:10.1038/s41598-017-10410-1
- 发表时间:2017-09-06
- 期刊:
- 影响因子:4.6
- 作者:Morgan RA;Beck KR;Nixon M;Homer NZM;Crawford AA;Melchers D;Houtman R;Meijer OC;Stomby A;Anderson AJ;Upreti R;Stimson RH;Olsson T;Michoel T;Cohain A;Ruusalepp A;Schadt EE;Björkegren JLM;Andrew R;Kenyon CJ;Hadoke PWF;Odermatt A;Keen JA;Walker BR
- 通讯作者:Walker BR
Network analysis of coronary artery disease risk genes elucidates disease mechanisms and druggable targets.
- DOI:10.1038/s41598-018-20721-6
- 发表时间:2018-02-21
- 期刊:
- 影响因子:4.6
- 作者:Lempiäinen H;Brænne I;Michoel T;Tragante V;Vilne B;Webb TR;Kyriakou T;Eichner J;Zeng L;Willenborg C;Franzen O;Ruusalepp A;Goel A;van der Laan SW;Biegert C;Hamby S;Talukdar HA;Foroughi Asl H;CVgenes@target consortium;Pasterkamp G;Watkins H;Samani NJ;Wittenberger T;Erdmann J;Schunkert H;Asselbergs FW;Björkegren JLM
- 通讯作者:Björkegren JLM
Loss of soluble guanylyl cyclase in platelets contributes to atherosclerotic plaque formation and vascular inflammation.
- DOI:10.1038/s44161-022-00175-w
- 发表时间:2022-12
- 期刊:
- 影响因子:0
- 作者:Mauersberger, Carina;Sager, Hendrik B;Wobst, Jana;Dang, Tan An;Lambrecht, Laura;Koplev, Simon;Stroth, Marlene;Bettaga, Noomen;Schlossmann, Jens;Wunder, Frank;Friebe, Andreas;Bjorkegren, Johan L M;Dietz, Lisa;Maas, Sanne L;van der Vorst, Emiel P C;Sandner, Peter;Soehnlein, Oliver;Schunkert, Heribert;Kessler, Thorsten
- 通讯作者:Kessler, Thorsten
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JOHAN M BJORKEGREN其他文献
JOHAN M BJORKEGREN的其他文献
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{{ truncateString('JOHAN M BJORKEGREN', 18)}}的其他基金
Network-driven drug repurposing approaches to treat coronary artery disease
网络驱动的药物再利用方法治疗冠状动脉疾病
- 批准号:
9205566 - 财政年份:2016
- 资助金额:
$ 79.88万 - 项目类别:
Toward Diagnostics and Therapies of Molecular Subcategories of CAD
CAD 分子亚类的诊断和治疗
- 批准号:
9278295 - 财政年份:2015
- 资助金额:
$ 79.88万 - 项目类别:
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