Analysis of Type 1 Diabetes Polygenic Scores in Atypical Forms of Diabetes
Analysis of Type 1 Diabetes Polygenic Scores in Atypical Forms of Diabetes
批准号:
10750644
负责人:
Aaron Jonathan Deutsch
金额:
$8.22万
依托单位国家:
美国
项目类别:
财政年份:
2023
资助国家:
美国
项目状态:
已结题
起止时间:
2023-08-01 至 2024-07-31
关键词:
AdultAutoantibodiesAutoimmune DiabetesAutoimmunityBeta CellBody mass indexCaringCell physiologyChildChildhoodChildhood diabetesClassificationClinicalComputational BiologyComputing MethodologiesDiabetes MellitusDiagnosisDiagnosticEnsureEnvironmentEuropean ancestryFoundationsFunctional disorderFundingGeneral HospitalsGeneticGenetic DeterminismGenetic ResearchGenetic RiskGenomeGoalsGrantHuman GeneticsHyperglycemiaImmune checkpoint inhibitorIndividualInsulinInsulin ResistanceInsulin deficiencyInsulin-Dependent Diabetes MellitusK-Series Research Career ProgramsLifeMassachusettsMeasuresMethodsNon-Insulin-Dependent Diabetes MellitusOutcomePancreasPhenotypePhysiciansPopulationPopulation HeterogeneityResearchResearch PersonnelRiskScientistTimeTrainingUncertaintyVariantWorkautoimmune pathogenesischeckpoint therapycomputing resourcesdiabetes mellitus geneticsdiabetes riskdisease heterogeneitydisorder riskearly onsetgenetic architecturegenetic informationgenetic risk factorgenetic varianthealth care disparityimprovedinnovationinsulin dependent diabetes mellitus onsetinsulin secretionnovelprecision medicineprogramsrisk predictionskillstherapy developmenttooltype I and type II diabeteswaiver
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PROJECT SUMMARY/ABSTRACT
Diabetes is traditionally classified as type 1 diabetes (T1D) or type 2 diabetes (T2D). T1D is caused by
autoimmune destruction of beta cells and insulin deficiency, while T2D is characterized by increased body mass
and insulin resistance. However, some atypical forms of diabetes are not easily classified as T1D or T2D, and
they share overlapping features with both conditions.
In this project, we propose to use genetic information to enhance the diagnosis of atypical forms of diabetes. In
particular, we will use polygenic scores, a promising tool that combines the effects of multiple variants across
the genome to predict the risk of disease. T1D polygenic scores have been validated to predict the onset of T1D
in children and to help discriminate between T1D and T2D in adults. Here, we will apply T1D polygenic scores
in novel contexts.
In Aim 1, we will examine ketosis-prone diabetes, which phenotypically resembles T2D but nevertheless involves
ketoacidosis. In Aim 2, we will investigate latent autoimmune diabetes in adults, which phenotypically resembles
T1D but presents later in life and has slower progression compared to classic, childhood-onset T1D. Finally, in
Aim 3, we will study immune checkpoint inhibitor-induced diabetes, in which individuals treated with immune
checkpoint inhibitors develop variable phenotypes and may or may not require insulin.
In each of these aims, we will implement T1D polygenic scores to better characterize disease heterogeneity and
to identify diabetes subtypes with distinct clinical outcomes. By using ancestry-specific and multi-ancestry
polygenic scores, we will ensure that diverse populations are well-represented. This is particularly important
because most existing polygenic scores have been developed in populations with European ancestry, whereas
certain atypical forms of diabetes are more common in other populations.
The proposed project will provide advanced training in computational biology and statistical genetics. The
research setting represents an ideal environment for junior investigators, combining the world-class clinical
expertise of Massachusetts General Hospital with the innovative computational resources of the Broad Institute.
This project will provide a foundation for the candidate to apply for a career development award and ultimately
to become an independent physician scientist.
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