Enriching medical phenotypes and environmental traits in the large DS360 Down syndrome cohort
Enriching medical phenotypes and environmental traits in the large DS360 Down syndrome cohort
批准号:
10427601
负责人:
TRACIE C ROSSER
金额:
$31.3万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2022
资助国家:
美国
项目状态:
未结题
起止时间:
2022-05-01 至 2025-04-30
关键词:
Acute Lymphocytic LeukemiaAddressAgeAlopeciaAutoimmune DiseasesAwardBiologicalBirthBirth RecordsCaregiversCeliac DiseaseChildChromosome 21ClinicalClinical DataCollectionCommunitiesCongenital AbnormalityCongenital Heart DefectsConsentDNADataData CollectionData Coordinating CenterData ReportingData SetDementiaDiagnosisDiseaseDocumentationDown SyndromeEnsureEnvironmental ExposureEnvironmental Risk FactorEvaluationFamilyFundingFutureGeneral PopulationGeneticGenetic RiskGenotypeGoalsHealthImpaired cognitionIndividualInterviewInvestmentsMalignant Childhood NeoplasmMapsMedicalMedical HistoryMedical RecordsMothersOnset of illnessOntologyParticipantPathway interactionsPersonsPhenotypePregnancyPregnancy HistoriesProviderQuestionnairesRecontactsRecording of previous eventsReportingResearchResearch PersonnelResourcesRiskRisk FactorsSamplingServicesSeveritiesSourceStandardizationStructural Congenital AnomaliesStructural defectTimeTranslatingUpdateWorkbaseclinically significantcohortdata harmonizationdata resourcedata sharingdatabase of Genotypes and Phenotypesearly onsetgastrointestinalgenome sequencinggenomic dataphenotypic dataprobandprogramssuccesstraitwhole genome
中文摘要
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英文摘要
Summary
Down syndrome (DS) leads to a significant risk for structural birth defects and health conditions, all presenting
with substantial variability in severity. We have obtained whole genome sequencing (WGS) on approximately
1700 probands with Down syndrome (DS) via three service awards. In this R03, we request funds to enrich the
available phenotype data on this established DS-WGS cohort (KF-X01-DS-CHD dbGaP accession number
phs002330) and harmonize these data with other resources to ensure maximum impact of this first-of-its kind
genotype/phenotype investment in DS research. These samples were contributed by four research groups,
with Emory’s DS360 study contributing the largest cohort. For most participants, phenotype evaluation was
done at one time point only, although we do have substantial information provided by our interviews around the
time of birth with mothers of the probands. We propose two aims to expand, enrich and harmonize this first-of-
its-kind WGS resource for the DS research community.
We will expand medical phenotyping data on participants from Emory’s DS360 program on whom WGS
is available. We will recontact participants where we have WGS data to complete an updated medical history
questionnaire. These data will be used as a guide for subsequent medical record collection. Caregiver report
data may be the sole source of information; thus, these reports are vital to identify presence of birth defects
along with later-onset disorders. Where caregivers have indicated medical conditions in the medical history
questionnaire, we will attempt to obtain medical records from those providers. These medical records will be
abstracted into a standardized medical record summary form.
We will curate existing phenotype and maternal environmental variables on participants in DS360 on
whom WGS is available and map diagnoses to ontology terms to expand potential identification of DS-
associated genetic and environmental risk factors. We have extensive questionnaire data from interviews
conducted with mothers of probands with DS. We will work with the data coordinating centers of Kids First and
INCLUDE to harmonize these comprehensive data and map them onto standard ontology terms to promote
cross-disease analyses in the Kids First large set of cohorts and to allow new genotype/phenotype studies in
the DS research community.
The proposed new data collection, along with our existing data that include clinical and environmental
variables, will be curated, harmonized and shared. This expanded data will enhance research on DS as well as
promote cross-disease analyses.
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