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Risk Clustering and Stratification in Genetically High-Risk Individuals Using Electronic Medical Records and Biomarkers

Risk Clustering and Stratification in Genetically High-Risk Individuals Using Electronic Medical Records and Biomarkers
使用电子病历和生物标记对遗传高危个体进行风险聚类和分层
批准号:
9180312
负责人:
Girish Nitin Nadkarni
金额:
$17.79万
依托单位国家:
美国
项目类别:
财政年份:
2016
资助国家:
美国
项目状态:
已结题
起止时间:
2016-08-15 至 2021-05-31
关键词:
AddressAdmixtureAdvisory CommitteesAffectAfricanAfrican AmericanApolipoproteinsAreaAtherosclerosisBig DataBiochemical MarkersBioinformaticsBiological AssayBiological MarkersBiometryBlood VesselsChronic Kidney FailureChronic Kidney InsufficiencyClinicalClinical ResearchClinical TrialsCocaCommunitiesComputerized Medical RecordDataDevelopmentDiscriminationDiseaseDisease ProgressionEarly DiagnosisEarly InterventionEarly identificationEnd stage renal failureEndostatinsEndothelin-1EnrollmentEnvironmentEpidemiologyFibrosisFrequenciesFundingFutureGenesGeneticGenetic MarkersGenetic RiskGenetic screening methodGenomicsGlomerular Filtration RateGoalsHispanicsIndividualInflammationInjuryInstitutesInterleukin-18InterventionK-Series Research Career ProgramsKidneyKidney DiseasesKidney FailureLaboratoriesLatinoLife StyleLinkLiteratureMeasurementMedicineMentored Patient-Oriented Research Career Development AwardMentorsMentorshipMethodologyMethodsMinorityMonocyte Chemoattractant Protein-1NamesNephrologyNot Hispanic or LatinoParticipantPathway interactionsPatient Self-ReportPatientsPharmacologyPlasmaPlasma ProteinsPopulationPopulation GeneticsPrevalenceProcessProtocols documentationPublishingRandomized Controlled TrialsRenal functionResearchResearch InfrastructureResearch PersonnelRiskRisk EstimateRisk FactorsSamplingSpecimenStratificationSystemTNF geneTNFR-Fc fusion proteinTNFRSF1A geneTestingTherapeuticTrainingTubular formationUnited StatesUnited States National Institutes of HealthValidationVariantWorkbasebiobankbiomarker panelcareercareer developmentclinical predictorscohortcomputing resourcesdisorder riskethnic minority populationfollow-upfunctional declinegenetic variantgenomic biomarkerhigh riskimprovedinnovationlifestyle factorslongitudinal analysismedical schoolsmid-career facultynovelnovel therapeutic interventionpatient orientedpatient stratificationpatient subsetspersonalized medicineprofessorprogramsrat KIM-1 proteinrisk varianttranslational genetics

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PROJECT SUMMARY/ABSTRACT This is a revised submission for a K23 award by Dr. Girish Nadkarni at the Icahn School of Medicine at Mount Sinai. Dr. Nadkarni is establishing himself as a young investigator in patient oriented clinical research of chronic kidney disease. This project will try to improve risk prediction and stratification for kidney disease progression in minority populations at baseline high genetic risk due to Apolipoprotein1 (APOL1) variants. Candidate: The primary objective of this application is to support Dr. Girish Nadkarni's career development into an independent investigator in the field of leveraging biomarkers, genomics and “big data” approaches for renal research. Dr. Nadkarni's career goal is to accurately risk stratify patients for renal functional decline for future targeted enrolment into clinical trials evaluating novel interventions. To achieve these goals, Dr. Nadkarni has assembled a mentoring and advisory team led by a primary mentor, Dr. Steven Coca, Associate Professor and Director of Clinical Research at the Icahn School of Medicine at Mount Sinai, and a co-mentor Dr. Erwin Bottinger, Professor of Medicine and former Director of The Charles Bronfman Institute of Personalized Medicine. His advisory team consists of Dr. Emilia Bagiella, Professor in the Division of Biostatistics at Mount Sinai and an expert in longitudinal analysis; Dr. Eimear Kenny, Assistant Professor in the Department of Genetics and Genomics and an expert in statistical and population genetics; Dr. Avi Ma'ayan, an Associate Professor in the Department of Pharmacology and Systems Therapeutics and an expert in bioinformatics and Dr. Judy Cho, the incoming director of the Charles Bronfman Institute of Personalized Medicine and an expert in translational genetics. His proposed training plan focuses on four areas (1) Advanced Statistical and Epidemiological Methodology; (2) Biomarker Methodology; (3) Computational Bioinformatics and Programming and (4) Focused mentorship and career development. Environment: Icahn School of Medicine at Mount Sinai is a national leader in research and is one of the top 20 medical schools in NIH funding. ISMMS was also named as one of the "The World's Top 10 Most Innovative Companies In Big Data" due to its computing resources and the BioMe Biobank, whose primary architect is Dr.Bottinger and is currently led by Dr. Cho. Research: Ethnic minorities are at higher risk of both development and progression of chronic kidney disease. This has been linked in part to risk variants in the APOL1 gene that are present in up to 14% in populations of African descent (including African Americans [AAs] and Hispanic Latinos [HLas]) but are absent in non- Hispanic Whites. Although APOL1 high-risk genotype is, in general, associated with faster eGFR decline, only about 50% progress to ESRD and patients within this group have differing rates of renal functional decline. Thus, risk stratification within this group is poor, limiting early intervention. With a large proportion of vulnerable ethnic minorities at increased risk, innovative methods for predicting renal function decline within this genetically high-risk group are urgently needed. Therefore, our specific aims are: (1) Establish associations of clinical predictors, lifestyle factors and laboratory parameters with longitudinal eGFR decline in AA/HLas with APOL1 high-risk genotype; (2) To develop a novel plasma biomarker panel assessing inflammation, injury, vascular insult and fibrosis, for risk prognostication of longitudinal eGFR decline in self-reported AA/HLas with APOL1 high-risk genotype; and (3) To conduct comprehensive, external validation of the highest performing plasma biomarkers and traditional predictors and derive risk clusters using validated predictors for longitudinal eGFR decline in self-reported AA/HLa's with APOL1 high-risk genotype. Aims 1 and 2 will be conducted using the largest cohort of participants with APOL1 risk variants ever assembled (n=809). Aim 3 will be conducted using four external cohorts, the Vanderbilt BioVU cohort, the Genetic testing to Understand and Address Renal Disease Disparities (GUARDD) study, the Atherosclerosis Risk in Communities (ARIC) study and the Chronic Renal Insufficiency Cohort (CRIC). These approaches integrating genetic, biomarker and electronic medical record clinical information, will form the basis for future work investigating targeted enrolment of high-risk patients in pragmatic, randomized controlled trials for early interventions, which will be proposed in an R01 application before the end of the K award period.
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Artificial Intelligence to Predict Outcomes in Patients with Acute Kidney Injury on Continuous Renal Replacement Therapy
Elucidating Genetic and Environmental Second Hits in Racial and Ethnic Minorities with APOL1 High-Risk Genotypes
Artificial Intelligence to Predict Outcomes in Patients with Acute Kidney Injury on Continuous Renal Replacement Therapy
  • 批准号:
    10261059
  • 项目类别:
  • 资助金额:
    $10.0万
  • 财政年份:
    2020
  • 负责人:
    Girish Nitin Nadkarni
  • 依托单位:
Elucidating Genetic and Environmental Second Hits in Racial and Ethnic Minorities with APOL1 High-Risk Genotypes
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