Toward Diagnostics and Therapies of Molecular Subcategories of CAD

CAD 分子亚类的诊断和治疗

• 批准号: 9497813
• 负责人: JOHAN M BJORKEGREN
• 金额: $ 79.88万
• 依托单位: ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
• 依托单位国家: 美国
• 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: https://reporter.nih.gov/project-details/9497813
• 关键词: Abdomen; Achievement; Address; Alleles; Angiography; Animal Model; Area; Atherosclerosis; Benchmarking; Biochemical Pathway; Biological Markers; Biological Models; Biology; Biopsy; Blood; Blood Vessels; Cardiology; Cardiovascular system; Cause of Death; Cell Differentiation process; Cell model; Chest; Clinical; Clinical Research; Complex; Coronary Arteriosclerosis; Coronary Artery Bypass; DNA; DNA analysis; Data; Data Set; Development; Diagnosis; Diagnostic; Disease; Disease Pathway; Engineering; Event; Family; Fatty acid glycerol esters; Foam Cells; Foundations; Future; Genes; Genetic; Genetic Diseases; Genetic Models; Genomics; Genotype; Goals; Heritability; Hospitals; In Vitro; Individual; Inherited; Institutes; Investments; Lead; Link; Liver; Machine Learning; Maps; Meta-Analysis; Metabolic; Molecular; Molecular Disease; Myocardial Infarction; New York; Operative Surgical Procedures; Outcome; Pathway Analysis; Pathway interactions; Patients; Pharmacotherapy; Phenotype; Plasma; Plasma Proteins; Preventive; Preventive care; Preventive therapy; Prospective Studies; Quantitative Trait Loci; RNA; RNA Sequences; Regulator Genes; Research; Research Proposals; Risk; Sampling; Single Nucleotide Polymorphism; Skeletal Muscle; Subcategory; System; Techniques; Testing; Tissues; Translating; Twin Multiple Birth; Twin Studies; Variant; Whole Blood; abdominal fat; biological systems; clinical predictors; clinical risk; computer based statistical methods; coronary event; coronary lesion; disorder risk; follow-up; genetic analysis; genome wide association study; in vivo Model; macrophage; medical schools; molecular phenotype; monocyte; multidisciplinary; novel; novel diagnostics; novel therapeutics; percutaneous coronary intervention; personalized care; personalized diagnostics; personalized medicine; predictive marker; predictive modeling; prospective; protein biomarkers; public health relevance; recruit; risk variant; subcutaneous; targeted biomarker; therapeutic target; trait; transcriptome sequencing

 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.

 描述（由申请人提供）：冠状动脉疾病 (CAD) 是全球和美国的主要死亡原因，但由于过去 5-10 年的巨大研究投入，这种疾病的遗传学本质上很复杂。全基因组关联研究 (GWAS) 已经实现了对 CAD 更加公正、数据驱动和现实的看法，作为这一成就的一部分，约 160 个 CAD/心肌梗死的常见风险位点已经实现。现在，一项重要的任务是了解这些位点对 CAD/MI 产生风险的分子机制/途径，从而将初步发现转化为新的治疗和诊断方法。仅约 10% 的 CAD/MI 风险变异，因此定义与 GWA 基因座并行运行的其他 CAD 途径也很重要。近年来，考虑中间表型（DNA 和疾病之间）的临床研究极大地增强了对风险的解释。确定的位点此外，可以从中间分子表型识别的疾病网络提供了一个重要的框架，用于确定新的 CAD 治疗途径和靶标。在过去 6 年中，我们进行了一项考虑 CAD 中许多中间表型的临床研究。在这项提案中，我们打算使用 STARNET 研究中新生成的 DNA 基因型和 RNA 序列数据来识别 CAD 的动脉粥样硬化和代谢网络。 NGS-PREDICT 研究）的主要目的是验证 STARNET 研究的结果，从而通过定义关键动脉粥样硬化基因网络和代谢网络的状态来准确评估冠状动脉病变的程度和稳定性。肝脏、腹部脂肪和骨骼肌中的活性会影响动脉粥样硬化基因网络的状态。此外，从容易获得的组织（例如血液、皮下脂肪和血浆）中分离出的分子数据可用于识别生物标志物。为了检验这些假设，我们提出以下具体目标：使用 STARNET 数据集和 CARDIoGRAM 识别与 CAD 和/或 CAD 亚表型因果相关的贝叶斯调控基因网络。荟萃分析 GWA 数据集 目标 2：通过对 DNA 基因型、RNA 序列和 CAD 血浆蛋白数据应用机器学习，识别预测 CAD 临床事件的生物标志物（反映在 SYNTAX 评分中）。目标 3：使用西奈山医院进行的 NGS-PREDICT 研究、瑞典双胞胎研究以及 CAD 细胞和动物模型来验证已确定的因果 CAD eQTL/网络和生物标志物。相信所提出的研究可以显着提高对 CAD 的分子理解，从而服务于在明确的分子亚类中诊断的 CAD 患者的预防性和个性化治疗的更长期目标。

项目成果

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: Nature communications
• 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

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: Scientific reports
• 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

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: PeerJ
• 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

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: Scientific reports
• 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: NATURE CARDIOVASCULAR RESEARCH
• 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