Analysis of Type 1 Diabetes Polygenic Scores in Atypical Forms of Diabetes

非典型糖尿病 1 型糖尿病多基因评分分析

• 批准号: 10750644
• 负责人: Aaron Jonathan Deutsch
• 金额: $ 8.22万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10750644
• 关键词: Adult; Autoantibodies; Autoimmune Diabetes; Autoimmunity; Beta Cell; Body mass index; Caring; Cell physiology; Child; Childhood; Childhood diabetes; Classification; Clinical; Computational Biology; Computing Methodologies; Diabetes Mellitus; Diagnosis; Diagnostic; Ensure; Environment; European ancestry; Foundations; Functional disorder; Funding; General Hospitals; Genetic; Genetic Determinism; Genetic Research; Genetic Risk; Genome; Goals; Grant; Human Genetics; Hyperglycemia; Immune checkpoint inhibitor; Individual; Insulin; Insulin Resistance; Insulin deficiency; Insulin-Dependent Diabetes Mellitus; K-Series Research Career Programs; Life; Massachusetts; Measures; Methods; Non-Insulin-Dependent Diabetes Mellitus; Outcome; Pancreas; Phenotype; Physicians; Population; Population Heterogeneity; Research; Research Personnel; Risk; Scientist; Time; Training; Uncertainty; Variant; Work; autoimmune pathogenesis; checkpoint therapy; computing resources; diabetes mellitus genetics; diabetes risk; disease heterogeneity; disorder risk; early onset; genetic architecture; genetic information; genetic risk factor; genetic variant; health care disparity; improved; innovation; insulin dependent diabetes mellitus onset; insulin secretion; novel; precision medicine; programs; risk prediction; skills; therapy development; tool; type I and type II diabetes; waiver

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.

项目摘要/摘要 糖尿病传统上分为1型糖尿病（T1 D）或2型糖尿病（T2 D）。T1 D是由 β细胞的自身免疫性破坏和胰岛素缺乏，而T2 D的特征是体重增加 和胰岛素抵抗。然而，一些非典型形式的糖尿病不容易分类为T1 D或T2 D， 它们与这两种情况具有重叠的特征。 在本项目中，我们建议使用遗传信息来增强非典型糖尿病的诊断。在 特别是，我们将使用多基因评分，这是一种很有前途的工具，它结合了多个变异的影响， 基因组来预测疾病的风险。已验证T1 D多基因评分可预测T1 D的发作 并帮助区分T1 D和T2 D成人。在这里，我们将应用T1 D多基因评分 in novel新contexts上下文. 在目标1中，我们将检查酮症倾向性糖尿病，其表型类似于T2 D，但仍然涉及 酮症酸中毒在目标2中，我们将研究成人隐匿性自身免疫性糖尿病， T1 D，但在生命后期出现，与经典的儿童期发作的T1 D相比，进展较慢。最后在 目的3，我们将研究免疫检查点通道诱导的糖尿病，其中个体接受免疫治疗， 检查点抑制剂产生可变的表型，并且可能需要或可能不需要胰岛素。 在这些目标中，我们将实施T1 D多基因评分，以更好地表征疾病异质性， 以确定具有不同临床结果的糖尿病亚型。通过使用特定祖先和多祖先 多基因评分，我们将确保不同的人群得到充分代表。这一点尤其重要 因为大多数现有的多基因评分都是在欧洲血统的人群中开发的，而 某些非典型形式的糖尿病在其他人群中更为常见。 拟议的项目将提供计算生物学和统计遗传学方面的高级培训。的 研究环境为初级研究人员提供了理想的环境，结合了世界一流的临床研究， 马萨诸塞州总医院的专业知识与布罗德研究所的创新计算资源。 该项目将为候选人申请职业发展奖奠定基础，并最终 成为一名独立的医学科学家。