Cellular Phenotypes of Genetic Variants in Mucopolysaccharidosis
Cellular Phenotypes of Genetic Variants in Mucopolysaccharidosis
批准号:
10638709
负责人:
William J Buchser
金额:
$45.15万
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
项目状态:
未结题
起止时间:
2023-04-01 至 2028-03-31
关键词:
A549AffectAttenuatedBenignBiochemicalBiological AssayBiopsyBirthCell LineCellsCellular MorphologyChimeric ProteinsClassificationClinicalComplementary DNAConsentDNADataDermatan SulfateDiagnosisDiagnosticDiagnostic testsDiscriminationDiseaseEnzymesGenerationsGenesGenetic DiseasesGenetic VariationGenome engineeringGenomicsGlycosaminoglycansGoalsHeparitin SulfateHumanImageImpairmentIn VitroIndividualInheritedIntellectual functioning disabilityKnock-outLaboratoriesLibrariesLinkLysosomesMachine LearningMeasurementMeasuresMedicalMedical RecordsMembraneMethodsMolecularMorphologyMucopolysaccharidosesMucopolysaccharidosis IINeonatal ScreeningNeuronsPathogenicityPatientsPhenotypePopulationReportingResearchResolutionSamplingSeveritiesSkinSystemTechnologyTest ResultTestingTransmembrane DomainUniversitiesVariantWashingtonWhole Bloodcell typediagnostic accuracydisorder riskexperimental studygenetic testinggenetic variantiduronate-2-sulfataseimprovedinduced pluripotent stem cellmolecular diagnosticsnovelphenotypic datapolysulfated glycosaminoglycanpreventrisk predictionsingle cell sequencingstem cellsvariant of unknown significance
中文摘要
摘要
目前迫切需要发展方法学的方法来评估基因组变异的功能。
蚂蚁。临床基因组测试正在迅速增长,随之而来的是比以往任何时候都更多的基因变异
既不能定义为致病也不能定义为良性。这个问题影响到临床医生和他们的患者,他们
努力理解和解释分子诊断报告、结果的含义以及如何
在没有明确信息的情况下管理他们的病人。涉及要生成的单个单元的系统
高含量、高分辨率的函数数据对于解决VaR提出的问题至关重要。
不确定意义的Iants。在这里,我们建议利用一种新的基于细胞的平台,它使用机器学习-
以确定定义致病性的形态表型的组合。我们将应用
全面评估入侵检测系统变异功能的技术--亨特的致病基因
综合症。这一建议中概述的核心假设是,测量直接函数的实验数据-
变异的影响将为准确的疾病风险预测提供信息。此外,我们假设在体外,
与现有的基于形态特征的细胞检测方法相比,基于细胞的检测方法将更准确地检测疾病
使用人造底物进行生化检测。我们将在变异库中使用
Buchser实验室的RaftSeq管道,在那里将建立细胞表型,然后测试我们-
与救援实验相结合的第二组变种。结果将通知不同的分类
IDS分子检测和改进对个人的诊断,包括那些被低艾杜酸-2-磺酸鉴定的人.
TASE在新生儿筛查中的活性。
英文摘要
ABSTRACT
There is presently an urgent need to develop methodical approaches to evaluate the function of genomic vari-
ants. Clinical genomic testing is growing rapidly, and with it a larger-than-ever number of genetic variants that
cannot be defined as either disease-causing or benign. The problem affects clinicians and their patients, who
struggle to understand and interpret molecular diagnostic reports, the implications of the results, and how to
manage their patients in the absence of definitive information. Systems that involve single cells to generate
high-content, high-resolution functional data are of paramount importance to solving the problem posed by var-
iants of uncertain significance. Here, we propose to utilize a novel cell-based platform that uses machine learn-
ing to determine the combination of morphological phenotypes that define pathogenicity. We will apply the
technology to the comprehensive functional assessment of variants in IDS, the gene responsible for Hunter
syndrome. The core hypothesis outlined in this proposal is that experimental data measuring the direct func-
tional effects of variants will inform accurate disease risk prediction. In addition, we hypothesize that an in vitro,
cell-based assay based on morphological features will more accurately detect disease compared to existing
biochemical testing using artificial substrates. We will perform a functional assay in a variant library using the
RaftSeq pipeline in the Buchser laboratory, where a cellular phenotype will be established and then tested us-
ing a second set of variants combined with rescue experiments. The results will inform variant classification in
IDS molecular testing and improve diagnosis of individuals including those identified by low iduronate-2-sulfa-
tase activity on newborn screening.
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会议论文
Cellular phenotype of mucopolysaccharidosis II for studies of genomic variants
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批准号:10442244
-
项目类别:
-
资助金额:$7.88万
-
财政年份:2022
-
负责人:William J Buchser
-
依托单位:
Cellular phenotype of mucopolysaccharidosis II for studies of genomic variants
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批准号:10589929
-
项目类别:
-
资助金额:$7.88万
-
财政年份:2022
-
负责人:William J Buchser
-
依托单位:
海外基金