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（由适用提供）：冠状动脉疾病（CAD）是全球和美国死亡的主要原因。尽管该疾病的遗传学本质上是复杂的，但感谢您在过去的5 - 10年中，尤其是在全基因组协会研究（GWAS）中进行的大量研究投资，但已经实现了对CAD的公正，数据驱动和现实的观点。作为这一成就的一部分，已经确定了CAD/心肌梗塞（MI）的约160个常见风险基因座。现在，重要的任务是了解这些基因座的分子机制/途径，这些基因座对CAD/MI施加风险，可以将初始发现转化为新的疗法和诊断。但是，由于该基因座迄今仅确定了CAD/MI风险变化的约10％的解释，因此定义与GWA基因座并行运行的其他CAD途径也是必不可少的。近年来，考虑中间表型（DNA和疾病之间）的临床研究大大增强了对GWA数据集中鉴定的风险位置的解释。此外，可以从中间分子表型中鉴定出的疾病网络为识别新的CAD途径和新的CAD疗法的靶标提供了必不可少的框架。在过去的6年中，考虑到CAD患者的许多中间表型，我们进行了一项临床研究（Starnet研究）。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基础的动脉粥样硬化和代谢网络。然后，我们提出了一项对CAD（NGS-Predict研究）的新的前瞻性研究，其主要目的是验证Starnet研究中的发现。我们假设冠状动脉病变的程度和稳定性，因此可以通过定义关键动脉粥样硬化基因网络的状态来准确评估临床结果。反过来，活跃于肝脏，腹部脂肪和骨骼肌的代谢网络会影响动脉粥样硬化基因网络的状态。此外，可以使用从易于获得的时间（例如，血液，皮下脂肪和等离子体）中分离出来的分子数据来识别可以预测CAD引起的临床事件风险的生物标志物。为了检验这些假设，我们提出了以下特定目标。目标1：使用Starnet数据集和心脏图荟萃分析GWA数据集识别有时链接到CAD和/或CAD子表型的调节性贝叶斯基因网络。 AIM 2：通过将机器学习应用于Starnet病例的易于获得的时机上的DNA基因型，RNA序列和CAD等离子体蛋白数据，以确定预测CAD的临床事件（反映在语法评分中）的生物标志物。目标3：使用在西奈山医院，瑞典双胞胎研究以及CAD细胞和动物模型进行的NGS-Predict研究验证已确定的因果CAD EQTLS/网络和生物标志物。我们认为，拟议的研究可以导致对CAD的分子理解明显更好，因此可以实现在定义明确的分子子类别中诊断出的CAD患者的预防和个性化疗法的更长期目标。

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