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Modeling gene x environment interactions in post-traumatic stress disorder.

Modeling gene x environment interactions in post-traumatic stress disorder.
创伤后应激障碍中基因与环境相互作用的建模。
批准号:
10750239
负责人:
Carina Seah
金额:
$5.19万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
未结题
起止时间:
2023-06-26 至 2027-06-25
关键词:
AdvocacyAffectAmygdaloid structureAreaAutopsyBiologyBloodBrainBrain regionCRISPR screenCatalogsCellular Indexing of Transcriptomes and Epitopes by SequencingClinical ResearchClustered Regularly Interspaced Short Palindromic RepeatsCognitiveComplexCore FacilityDataDetectionDevelopmentDiagnosisDiseaseDistalEarly DiagnosisEarly InterventionEarly treatmentElectronic Health RecordElementsEnvironmentEnvironmental ExposureEnvironmental Risk FactorEtiologyExposure toFellowshipFunctional disorderFutureGene ExpressionGene TargetingGenesGeneticGenetic RiskGenetic TranscriptionGenomicsGenotypeGlossaryGoalsHeritabilityHumanHydrocortisoneIn VitroIndividualInstitutionJointsLeadershipLinkMapsMeasuresMedialMediatingMentorshipMethodsModelingNatureNeuronsNeurosciencesOutcomePathway interactionsPatient riskPatientsPatternPhenotypePhysiciansPost-Traumatic Stress DisordersPredispositionPrefrontal CortexQuantitative Trait LociRegulationResearchResourcesRiskRisk EstimateRoleSamplingScholarshipScientistSingle Nucleotide PolymorphismStratificationStressTrainingTraining SupportTranslatingTraumaTraumatic Brain InjuryUniversitiesUntranslated RNAValidationVariantVisualWorkaccurate diagnosticsalgorithm developmentbiobankbiological adaptation to stressbiomarker discoverybrain cellbrain tissuecare deliverycell typeclinical practiceclinical riskclinically relevantcohortcomputing resourcesconditioned feardisorder riskexperimental studygene environment interactiongene interactiongenetic elementgenetic variantgenome wide association studygenome-widegenomic locusimprovedin vitro Modelmedical schoolsnoveloutcome predictionpatient stratificationpediatric traumapersonalized medicinephenomephysiologic modelprogramsresiliencerisk predictionrisk stratificationrisk variantscientific computingsingle-cell RNA sequencingstatisticstheoriestranscriptomicstranslational impacttranslational potentialtrauma exposuretraumatic eventvariant detection

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中文摘要
翻译
项目摘要 创伤后应激障碍(PTSD)是一种常见的,使人衰弱的疾病,由暴露于创伤性环境引发。 活动PTSD通常诊断不足,治疗不足,尽管早期发现和治疗 有利的结果。更好地识别疾病易感性或恢复力的要素对于 及时提供护理,以减轻疾病负担。由于创伤后应激障碍已被证明是可遗传的, 疾病易感性是遗传的大规模的全基因组关联研究(GWAS)揭示了一个 基于单核苷酸多态性(SNP)的遗传率估计为5- 20%。然而,环境因素,如 儿童创伤,也被证明可以独立预测PTSD的发展。全基因组整合 PTSD相关的基因位点与应激暴露可能阐明基因与环境的相互作用, 影响疾病易感性。在这个建议中,我将研究基因座与联合遗传和环境 PTSD风险的贡献,采用综合多层次的方法来检查和验证大脑区域 和细胞类型特异性调节。将GWAS研究结果与环境暴露相结合的一个主要问题是 GWAS鉴定的基因座的大部分非编码性质,模糊了明确的功能分支。为了克服这一点, 我将把识别出的变异与附近的表达变化联系起来,以揭示近端或远端的调控。 基因靶点这种具有转录组调控活性的变异体被称为表达数量性状基因座 (eQTL)。由于转录组调控依赖于环境,eQTL捕获遗传和环境 调节表达,使它们可用于破译PTSD的基因组调控。我做了初步的 在来自背外侧前额叶皮层(DLPFC)的死后脑样品中进行eQTL搜索,表明 应激交互eQTL在创伤暴露队列的脑中是可检测的。在目标1中,我将扩展这一分析 从DLPFC到内侧杏仁核,以揭示遗传应激反应的调控景观 穿过大脑在目标2中,我将检查这些变量的因果关系,以证明压力依赖性调节。 我已经开发了一种体外模型,捕捉PTSD特异性应激反应。在该模型中,候选效应器 将针对影响病症生物学的下游效应来询问变体。这将通过 培训大规模CRISPR筛选方法和收敛下游的计算探测 途径。这项工作将在西奈山伊坎医学院(ISMMS)和耶鲁大学进行 大学,目前排名#11和#10之间的全国最好的医学院的研究,分别。 在遗传学和神经科学系之间,我得到了超过100,000平方英尺研究的支持 计划和4500平方英尺的机构核心设施,以及超过2亿美元的科学计算 资源总之,这个奖学金利用了我的机构资源和我的合作伙伴的专业知识, 赞助商支持我在四个主要领域的培训:(1)科学卓越,(2)专业发展, 奖学金,(3)导师,领导和宣传,(4)和临床研究整合。
英文摘要
PROJECT SUMMARY Posttraumatic stress disorder (PTSD) is a common, debilitating disorder, triggered by exposure to a traumatic event. PTSD is often under-diagnosed and undertreated, despite early detection and treatment governing favorable outcomes. Better identification of elements of disorder susceptibility or resilience is important for prompt delivery of care to mitigate disorder burden. As PTSD has shown to be heritable, a prevailing theory of disorder susceptibility is genetic. Large-scale genome wide association studies (GWAS) have revealed an estimated single-nucleotide polymorphism (SNP)-based heritability of 5-20%. Yet, environmental factors, such as childhood trauma, have also shown to independently predict PTSD development. Genome-wide integration of PTSD-associated genetic loci with stressful exposures may elucidate gene by environment interactions that influence disorder susceptibility. In this proposal, I will investigate loci with joint genetic and environmental contributions to PTSD risk, employing an integrative multi-level approach to examine and validate brain region and cell type-specific regulation. One major issue integrating GWAS findings with environmental exposures is the largely non-coding nature of GWAS-identified loci, obscuring clear functional ramifications. To overcome this, I will associate identified variants with nearby expression changes to uncover regulation of proximal or distal gene targets. Such variants with transcriptomic regulatory activity are termed expression quantitative trait loci (eQTLs). As transcriptomic regulation is context-dependent, eQTLs capture genetically and environmentally regulated expression, making them useful for deciphering genomic regulation of PTSD. I performed a preliminary eQTL search in post-mortem brain samples from the dorsolateral pre-frontal cortex (DLPFC), demonstrating that stress-interactive eQTLs are detectable in brains of trauma-exposed cohorts. In Aim 1, I will extend this analysis beyond the DLPFC to the medial amygdala, to uncover the regulatory landscape of genetic stress response across the brain. In Aim 2, I will examine causality of these variants to demonstrate stress-dependent regulation. I have developed an in vitro model capturing PTSD-specific stress response. In this model, candidate effector variants will be interrogated for downstream effects impacting disorder biology. This will be accomplished via training in large scale CRISPR-screening methods and in computational probing of convergent downstream pathways. This work will take place within the Icahn School of Medicine at Mount Sinai (ISMMS) and Yale University, currently ranked #11 and #10 among the nation’s best medical schools for research, respectively. Between the Departments of Genetics and Neuroscience, I am supported by over 100,000 ft2 of research programs and 4500 ft2 of institutional core facilities, in addition to over $200 million in scientific computing resources. Together, this fellowship leverages the resources of my institutional and the expertise of my co- sponsors to support my training in four major areas: (1) Scientific excellence, (2) professional development and scholarship, (3) mentorship, leadership, and advocacy, (4) and clinical-research integration.
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