grant

Identifying Genes for Type 2 Diabetes: FUSION

Organization UNIVERSITY OF MICHIGAN AT ANN ARBORLocation ANN ARBOR, UNITED STATESPosted 1 Jul 2002Deadline 31 Jul 2026
NIHUS FederalResearch GrantFY202565 and older65 or older65 years of age and older65 years of age or more65 years of age or older65+ years65+ years oldAKT2AKT2 KinaseAKT2 geneAKT2 protein kinaseAccelerationAchievementAchievement AttainmentAddressAdult-Onset Diabetes MellitusAffectAged 65 and OverAkt-beta proteinAmericanB9 endocrine pancreasBase SequenceBeta CellCallbackCausalityCell Communication and SignalingCell NucleusCell SignalingChromatinChromosome MappingCodeCoding SystemCollaborationsComputing MethodologiesD-GlucoseDNA MethylationDataData SourcesDevelopmentDextroseDiabetes MellitusEndocrine PancreasEnvironmentEpidemicEtiologyEuropeanFinlandFosteringFrequenciesGWA studyGWASGene ExpressionGene LocalizationGene MappingGene Mapping GeneticsGene variantGenesGeneticGenetic studyGenomeGenomicsGenotypeGlucoseGoalsHeadHealth Care CostsHealth CostsHeritabilityHistoryHuman Gene MappingHuman Gene Mapping DNA SequencingHuman genetic mappingIncidenceIndividualInsulin CellInsulin ResistanceInsulin Secreting CellIntracellular Communication and SignalingInvestigationInvestigatorsIslands of LangerhansIslets of LangerhansKetosis-Resistant Diabetes MellitusKnowledge PortalKnowledge base PortalKnowledgebase PortalLeadLife StyleLifestyleLinkage MappingMapsMaturity-Onset Diabetes MellitusMeasuresMedical Care CostsMeta-AnalysisMetabolic DiseasesMetabolic DisorderMetabolic syndromeMethodsMethylationMichiganMolecularMorbidityMorbidity - disease rateMuscleMuscle TissueNIDDMNesidioblastsNon-Insulin Dependent DiabetesNon-Insulin-Dependent Diabetes MellitusNoninsulin Dependent DiabetesNoninsulin Dependent Diabetes MellitusNucleotide SequenceNucleusOrganPKBbetaPRKBBPancreatic IsletsPars endocrina pancreatisPb elementPersonsPhenotypePhysiologicPhysiologicalPlayPopulationPredicting RiskPrevalencePreventionProductivityProtein Kinase B BetaPublic HealthQTLQuantitative Trait LociRAC-BETARAC-Beta Protein KinaseRAC-Beta Serine/Threonine KinaseRecording of previous eventsResearchResearch PersonnelResearch ResourcesResearchersResolutionResourcesRiskRoleSample SizeSamplingSignal TransductionSignal Transduction SystemsSignalingSiteSkeletal MuscleSlow-Onset Diabetes MellitusStable Diabetes MellitusStatistical MethodsT2 DMT2DT2DMTestingThesaurismosisTotal Human and Non-Human Gene MappingType 2 Diabetes MellitusType 2 diabetesType II Diabetes MellitusType II diabetesUnited StatesVariantVariationVisualizationVoluntary MuscleWorkabove age 65adult onset diabetesafter age 65age 65 and greaterage 65 and olderage 65 or olderageage of 65 years onwardaged 65 and greateraged 65+aged ≥65allelic variantbasebasesbiological signal transductioncardiometaboliccardiometabolismcausal allelecausal genecausal mutationcausal variantcausationcausative mutationcausative variantcell typeclinical phenotypeclinical translationclinically translatablecohortcomputational methodologycomputational methodscomputer based methodcomputer methodscomputing methodcustomized therapycustomized treatmentdata diversitydata sharingdata visualizationdatabase of Genotypes and PhenotypesdbGaPdevelopmentaldiabetesdiabetes geneticsdiabetes mellitus geneticsdiabetes riskdisease causationdisease preventiondisorder preventiondisparity in healthdiverse dataentire genomeexomeforecasting riskfull genomegene locusgenetic associationgenetic locusgenetic mappinggenetic variantgenome wide associationgenome wide association scangenome wide association studygenomewide association scangenomewide association studygenomic locationgenomic locusgenomic varianthealth disparityheavy metal Pbheavy metal leadhistorieshuman diseasehuman old age (65+)iPSiPSCiPSCsimprovedindividualized medicineindividualized patient treatmentindividualized therapeutic strategyindividualized therapyindividualized treatmentinduced pluripotent cellinduced pluripotent stem cellinducible pluripotent cellinducible pluripotent stem cellinsulin resistantinsulin toleranceinterestketosis resistant diabeteslow-frequency mutationmaturity onset diabetesmedical costsmedical expensesmenmetabolism disordermolecular phenotypemortalitymuscularnew drug treatmentsnew drugsnew pharmacological therapeuticnew therapeuticsnew therapynext generation therapeuticsnovelnovel drug treatmentsnovel drugsnovel pharmaco-therapeuticnovel pharmacological therapeuticnovel therapeuticsnovel therapynucleic acid sequenceopen source toolopen source toolkitover 65 yearspatient specific therapiespatient specific treatmentphenotypic datapredict riskpredict riskspredicted riskpredicted riskspredicting riskspredictive riskpredicts riskrac-PK betarac-PK beta proteinrare allelerare mutationrare variantresolutionsrisk predictionrisk predictionssex related variationsex variablesex variationsex-related variablesocial rolestatistic methodssuccesstailored medical treatmenttailored therapytailored treatmenttargeted drug therapytargeted drug treatmentstargeted therapeutictargeted therapeutic agentstargeted therapytargeted treatmenttooltraittype 2 DMtype II DMtype two diabetesunique treatmentvaries by sexwhole genomewhole genome association analysiswhole genome association studyβ-cellβ-cellsβCell≥65 years
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Full Description

Project Summary / Abstract
Type 2 diabetes (T2D) is a major cause of morbidity and mortality, affecting >450M people worldwide and

>34M in the US alone; >26% of Americans aged ≥65 years have T2D. T2D incidence and prevalence are

increasing rapidly. In the US, direct medical costs of diabetes in 2017 were estimated at $237 billion, ~15% of

all US health-care costs. The goals of the Finland-United States Investigation of NIDDM Genetics (FUSION)

study are to identify genetic variants, genes, and mechanisms that influence T2D risk and variability in T2D-

related quantitative traits (QTs), and to foster clinical translation of these findings. Improved understanding of

the genetic bases of T2D and related QTs has the potential to reduce the impact of the T2D epidemic by

supporting identification of novel therapies, enabling better targeting of therapies, providing more accurate risk

prediction, and advising lifestyle changes in at-risk individuals. In this competing renewal, we will

a. discover and fine map genetic loci that influence T2D risk and QT variability using array- and sequence-

based GWAS in our FUSION, METSIM, and MGI cohorts, and through meta-analysis of Finnish, European,

and diverse multi-ancestry samples;

b. select individuals with and without high-interest T2D- and QT-associated variants for genotype-based

callback and targeted phenotyping to test for association and identify physiological mechanisms;

c. use skeletal muscle data (bulk and single-nucleus) to understand how cell-type composition, chromatin

accessibility, DNA methylation, gene expression, and metabolites vary by sex, T2D, QTs, and genetic

variants, and to identify cell-type molecular QTLs that colocalize with T2D and QT GWAS;

d. use iPSC-derived beta cells to understand how chromatin accessibility and gene expression vary by

developmental stage and glucose stimulation, and identify stage-specific, accessible-chromatin enrichment

for T2D and QT GWAS signals; and

e. accelerate advances in T2D genetics through enhanced data sharing and support for easy exploration and

visualization of our study results by any investigator.

Successful completion of these aims will improve our understanding of T2D etiology, point the way to novel

methods of prevention and treatment, and help address the public health crisis posed by T2D. The

longstanding, productive collaboration of our FUSION study team makes achievement of these aims feasible.

Methods developed and lessons learned here will be useful in the study of other human diseases and traits.

Grant Number: 5R01DK062370-22
NIH Institute/Center: NIH

Principal Investigator: MICHAEL BOEHNKE

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