From Variants to Mechanisms for Cardiac Arrhythmias
从心律失常的变异到机制
基本信息
- 批准号:10719850
- 负责人:
- 金额:$ 82.56万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2023
- 资助国家:美国
- 起止时间:2023-08-01 至 2028-06-30
- 项目状态:未结题
- 来源:
- 关键词:AddressAmericanAnatomyArchitectureAreaArrhythmiaAtrial FibrillationBiological AssayBiologyCRISPR/Cas technologyCalciumCandidate Disease GeneCardiacCardiac MyocytesCardiologyCell modelCell physiologyChromatinChromatin LoopClinicalClustered Regularly Interspaced Short Palindromic RepeatsCodeCompanionsComplementDataDiagnosticDiseaseElectrophysiology (science)EnhancersEventFollow-Up StudiesGene ExpressionGene ProteinsGene TargetingGenesGeneticGenetic RiskGenetic TranscriptionGenomicsGenotypeGoalsHeartHeart AtriumHeritabilityHi-CHumanIndividualKnowledgeLateralLeftLinkLocationMapsMeasurementMeasuresMembrane PotentialsMetadataModelingMolecular ConformationNaturePathologyPathway interactionsPhysical assessmentPhysiologyPositioning AttributeProteinsPublishingQuality of lifeQuantitative Trait LociRegulator GenesRegulatory ElementRepressionResolutionRetrospective cohortRiskSamplingSystemTechnologyTherapeuticTimeTissue SampleTissuesTranscriptional RegulationTranslational ResearchValidationVariantZFHX3 genebiobankcandidate identificationcell typeclinical practicecohortdetection limitdisorder riskevidence baseexpectationexperiencefollow-upgenetic associationgenetic variantgenome wide association studygenome-wide analysisgenomic locushuman stem cellshuman tissueimprovedmortality risknovel therapeutic interventionnovel therapeuticspower analysispromoterprospectiverisk variantsingle nucleus RNA-sequencingsuccesstherapeutic developmenttraittranscription factortranscriptome sequencingtranslational potentialtranslational therapeuticsvirtualwhole genome
项目摘要
Project summary
There are hundreds of genomic loci where common genetic variants associate with the risk of cardiac
arrhythmias, yet the slow rate of functional assessment severely limits our ability to unlock the unique biology
that they identify. Our long-term goal is to systematically link arrhythmia risk loci to their mechanisms, identifying
the unexpected mechanisms of arrhythmogenesis, and priming them for therapeutic translation. The key feature
of arrhythmia genetic association loci is their non-protein-coding nature, a finding which leads to our overarching
hypothesis that transcriptional misregulation underlies much of cardiac arrhythmia risk. To address this
hypothesis, we first examine the relationships between known arrhythmia target genes which encode
transcription factors and cardiomyocyte electrophysiology using inducible CRISPR-Cas9 modifiers of gene
expression. We will seek to understand the transcriptional changes underlying electrophysiological changes by
profiling gene expression and protein abundance. At the same time, we recognize that the vast majority of loci
remain entirely undefined, a limitation which serves as a great impediment to further translational research. To
address this, we will use two orthogonal approaches in human atrial tissue samples. First, our group has led
early large-scale implementations of single nucleus RNA sequencing on the human heart, experience which we
propose to extend to the goals of this proposal. We aim to link genotype to expression by performing single
nucleus RNA sequencing on a large biobank of non-diseased left atrial tissue with available genotypes and
clinical metadata. This will provide not only the target gene(s) for the association loci, but also the directionality
of effect and the pertinent cell type(s), greatly facilitating downstream validation by our team and others. To
complement the direct measurement of genotype to expression, we aim to supplement these analyses with
chromatin conformation analysis. While these assays do not resolve the effects of genotype, they measure
contact between regions of risk and target promoters to provide putative gene targets. Our preliminary high-
resolution contact map from the left atrial lateral wall greatly improved the number of candidate genes for atrial
fibrillation association loci. We recognize the importance of anatomically restricted events in the initiation and
propagation of arrhythmias, and thus propose to assess the physical proximity between regulatory elements
within association loci and their putative gene targets in prospectively sampled atrial tissues using micro-C, a
technology which assesses chromatin conformation across the entire genome. Ultimately, accomplishing these
aims could prove transformative for facilitating studies of cardiac arrhythmias, unlocking the mechanisms of
arrhythmia genetic risk to generate novel therapeutic approaches and guide clinical practices.
项目摘要
有数百个基因组基因座,共同的遗传变异与心脏风险相关
心律不齐,但是功能评估的缓慢速度严重限制了我们解锁独特生物学的能力
他们确定的。我们的长期目标是系统地将心律失常的风险基因座与其机制联系起来,确定
心律失常发生的意外机制,并为治疗翻译启动。关键功能
心律不齐的遗传关联基因座是他们的非蛋白质编码性质,这一发现导致了我们的总体
转录正调的假设是心律不齐的大部分风险。解决这个问题
假设,我们首先研究了已知的心律失常靶基因之间的关系
使用诱导的CRISPR-Cas9基因修饰剂的转录因子和心肌细胞电生理学
表达。我们将寻求了解电生理变化的转录变化
分析基因表达和蛋白质丰度。同时,我们认识到绝大多数基因座
保持完全不确定,这是进一步转化研究的极大障碍。到
解决这个问题,我们将在人心房组织样品中使用两种正交方法。首先,我们的小组领导
早期的大规模实施单核RNA测序在人心脏上,我们的经验我们
建议扩展到该提案的目标。我们的目的是通过执行单个将基因型与表达联系起来
核RNA的核RNA测序在不固定的左心组织的大生物库中,具有可用的基因型和
临床元数据。这不仅将为关联基因座提供目标基因,还将提供方向性
效果和相关细胞类型,极大地促进了我们团队和其他人的下游验证。到
我们旨在补充基因型的直接测量,我们旨在补充这些分析
染色质构象分析。虽然这些测定不能解析基因型的影响,但它们测量了
风险区域与目标启动子之间的接触以提供假定的基因靶标。我们的初步高级
从左图侧壁的分辨率接触图极大地改善了心房的候选基因数量
纤维化关联基因座。我们认识到解剖学上受限制事件在启动中的重要性,
心律不齐的传播,因此建议评估调节元件之间的物理接近性
在关联基因座及其推定基因靶标内,在前瞻性地采样的心房组织中,使用micro-c,a
评估整个基因组中染色质构象的技术。最终,完成这些
目的可能证明是促进心律不齐的研究的变革性,解锁了机制
心律不齐的风险产生新型的治疗方法并指导临床实践。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Nathan Tucker其他文献
Nathan Tucker的其他文献
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{{ truncateString('Nathan Tucker', 18)}}的其他基金
Defining the functional variation underlying atrial fibrillation risk
定义心房颤动风险背后的功能变异
- 批准号:
10421043 - 财政年份:2018
- 资助金额:
$ 82.56万 - 项目类别:
Defining the functional variation underlying atrial fibrillation risk
定义心房颤动风险的功能变异
- 批准号:
9930154 - 财政年份:2018
- 资助金额:
$ 82.56万 - 项目类别:
Defining the functional variation underlying atrial fibrillation risk
定义心房颤动风险背后的功能变异
- 批准号:
10115201 - 财政年份:2018
- 资助金额:
$ 82.56万 - 项目类别:
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