Phenotyping Skeletal QTLs in a DO Mouse Population
Phenotyping Skeletal QTLs in a DO Mouse Population
批准号:
8829756
负责人:
David W. Rowe
金额:
$17.84万
依托单位国家:
美国
项目类别:
财政年份:
2014
资助国家:
美国
项目状态:
已结题
起止时间:
2014-04-01 至 2016-03-31
关键词:
AffectAgeAge-MonthsAgingAlgorithmsAnimal ModelAnimalsBioinformaticsBiologicalBiologyBiomedical ResearchBone remodelingBudgetsCandidate Disease GeneCartilageCellsChondrocytesChromosome MappingClinical ResearchCommunitiesComplexComplex Genetic TraitComputersCore FacilityCoupledDataDegenerative polyarthritisDevelopmentDiseaseElderlyEnvironmentEnvironmental Risk FactorFemaleFundingGenerationsGenesGeneticGenetic VariationGenetic studyGenomeGenomicsGoalsGrantHealthHereditary DiseaseHistologicHistological TechniquesHistologyHousingHumanHuman BiologyImageImage AnalysisInbred MouseInbreedingIndividualInterventionInvestmentsJointsLactationLinkMaintenanceMapsMeasurementMedicalMedicineMethodsMineralsMorphologyMultiparityMultiple PregnancyMusOnline SystemsOsteoporosisPathway interactionsPatientsPhenotypePhysiologicalPopulationPregnancyQuantitative Trait LociRecoveryRegulationRelative (related person)ResearchResolutionResourcesSamplingScanningServicesSeverity of illnessShockSkeletonStudy modelsSumSurfaceTechnologyThe Jackson LaboratoryThickTimeTissuesVariantage effectarticular cartilagebasebonebone healthbone masscohortcostdensitydesigndigitaldisorder riskempoweredfluorescence microscopegene interactionimaging modalitymalemeetingsmineralizationnovelpersonalized medicineskeletaltooltrait
中文摘要
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英文摘要
DESCRIPTION (provided by applicant): The genomic revolution promises major medical advances by tailoring interventions to an individual's unique genetic constellation. This hope is predicated on understanding the contribution to human health of each gene and its interaction with the environment. This essential information will have to come from model organisms that replicate human biology. The mouse genetics community has responded to this challenge by developing genetically defined and highly polymorphic (diversity outbreed, DO) mouse lines for quantitative trait linkage (QTL) studies capable of directly identifying the genetic unit underlyin a phenotypic extreme. The skeletal biology field is not yet taking advantage of this advance in part because of the relative insensitivity of affordable tools used for bone/cartilage phenotyping,
and the expensive and time consuming effort required to establish the mouse colonies and to perform a QTL study. Given the shrinking budget for biomedical research, the skeletal biology community has to reinvent how it conducts a QTL study if it wants to participate in promise of personalized medicine. This grant proposes one avenue for skeletal medicine to participate in identifying genetic loci that contribute to complex medical diseases such as osteoporosis or degenerative arthritis. It has two objectives. The first is a histological approach for assessing dynamic and cellular histomorphology of bone and articular cartilage that is compatible with a computer-based QTL study. The method is relatively low cost and high through put and the quantitation of the images is observer independent. The second is ability to append a skeletal QTL study to an ongoing and funded project designed for another biological question that is compatible with the skeletal question. In Aim 1, a well-developed computer driven bone histomorphogical method will be used to assess the skeleton status in two DO studies. (1) In 9 month old multiparous female mice. Unlike all previous QTL studies that use virgin females, this study may identify genes that are needed to recover bone mineral after lactation is competed. (2) In male and female mice at 6, 12 and 18 months of age. Aging studies of the skeleton have been particularly difficult to perform and partnering with a NIA supported Shock core facility makes this opportunity possible. In both cases, the major fixed costs for conducting the study are covered. In Aim 2, the histological/imaging methods and image analysis algorithms will be refined to provide a computer based histomorphometric assessment of articular cartilage health that is compatible with the same sections used for the bone studies. The method will be validated using existing sections from 5 different inbred mouse lines before it is applied to the two DO studies. The demonstration that our digital histological technology can be coupled with multipurpose DO study to identify genetic loci linked to extreme skeletal variation in a format that is web-based data-ready should empower the skeletal biology research community to participate in the personalized medicine revolution.
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