Pharmacogenetics of the Response to a GLP1R Agonist
Pharmacogenetics of the Response to a GLP1R Agonist
批准号:
10387898
负责人:
AMBER L BEITELSHEES
金额:
$67.2万
依托单位国家:
美国
项目类别:
财政年份:
2021
资助国家:
美国
项目状态:
未结题
起止时间:
2021-12-01 至 2026-11-30
关键词:
AccelerationAftercareAgonistAmericanAmishAmputationAntidiabetic DrugsBiological MarkersBlindnessBlood CirculationBody Weight decreasedBolus InfusionCardiovascular systemClinicalClinical TrialsCountyDNA SequenceDataDiabetes MellitusDiabetic AngiopathiesDoseDrug PrescriptionsEnd stage renal failureEnvironmental Risk FactorEuropeanEvaluationEventFrequenciesGLP-I receptorGeneral PopulationGeneticGenetic MarkersGenetic studyGenotypeGlucoseGlycosylated hemoglobin AHeadIndividualLiteratureMeasurementMeasuresMediatingMediationNational Heart, Lung, and Blood InstituteNon-Insulin-Dependent Diabetes MellitusObesityOutcomeOverweightParticipantPatientsPharmaceutical PreparationsPharmacodynamicsPharmacogeneticsPharmacogenomicsPharmacologyPhasePhysiciansPhysiologicalPlasmaPopulationPrincipal InvestigatorPropertyPublishingReportingResearchResearch SubjectsRiskSamplingTrans-Omics for Precision MedicineType 2 diabeticVariantbaseclinical predictorsclopidogrelcostdensitydesigndiabetic patientdiet and exerciseexperiencegenetic variantgenome wide association studyglucose metabolismglycemic controlhealthy volunteerimprovedindividual patientindividual responseinsulin secretionintravenous administrationintravenous glucose tolerance testliraglutidelogarithmnon-diabeticoptimal treatmentspatient populationpatient responseprecision medicinepredictive markerprimary endpointprogramsrecruitresponseside effectsubcutaneousvolunteerwhole genome
中文摘要
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英文摘要
Glucagon-like peptide 1 receptor (GLP1R) agonists are an important class of antidiabetic drugs with an
attractive clinical profile – including improved glycemic control, weight loss, and decreased risk of major
adverse cardiovascular events. While there is substantial variation in the magnitude of individual patients’
responses to these drugs, there are no validated approaches to identify patients most likely to have the largest
responses and derive the most clinical benefit. This application proposes a genome-wide association study in
the Old Order Amish population to identify genetic variants that predict individuals’ pharmacodynamic
responses to GLP1R agonists. Based on preliminary data from the Principal Investigators’ research, the
proposed project will measure pharmacodynamic endpoints related to beneficial effects of GLP1R agonists.
Overweight/obese otherwise healthy volunteers will be recruited from the Old Order Amish population in
Lancaster County, PA. In order to assess pharmacodynamic responses, research participants will undergo two
frequently sampled intravenous glucose tolerance tests (FSIGT). The first FSIGT will be conducted at baseline
prior to administration of drug. The second FSIGT will be conducted after six weeks of treatment with
semaglutide (0.25 mg/wk X 4 wks; 0.5 mg/sk X 2 wks). The proposal proposes two specific aims:
• Specific Aim #1. To identify genetic variants associated with effects of a GLP1R agonist to enhance glucose-
stimulated first phase insulin secretion in the two FSIGTs (before and after administration of drug).
• Specific Aim #2. To identify genetic variants associated with the effect of a GLP1R agonist to accelerate the
rate of glucose disappearance as assessed in the two FSIGTs (before and after administration of drug).
Genotyping will be conducted using a high-density array with comprehensive coverage of DNA sequence
variants. The project will leverage a global imputation panel generated from whole genome sequence data on
~ 100K subjects including 1,025 Amish individuals obtained through the NHLBI-sponsored Trans-Omics for
Precision Medicine (TOPMed) program. Previous genetic studies conducted in the Old Order Amish population
have been highly predictive of observations in the general population and relevant patient populations. Based
on these precedents, we anticipate that genetic variants in this study are very likely to be predictive of clinical
responses of GLP1R agonist-treated type 2 diabetic patients. The proposed study is a step toward the long-
term objective of identifying genetic biomarkers to predict an individual patient’s response to GLP1R agonists.
Availability of predictive biomarkers would enable physicians to prescribe optimal therapies for each individual
patient based on predictors of beneficial response. This type of Precision Medicine approach, based on
predictive pharmacogenomic biomarkers, would be a transformational advance in the way diabetes drugs are
prescribed.
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