Multi-omics integration to characterize genetic influences on metabotypes of type 1 diabetes progression

多组学整合表征遗传对 1 型糖尿病进展代谢型的影响

• 批准号: 10264080
• 负责人: Randi Kay Johnson
• 金额: $ 15.55万
• 依托单位: UNIVERSITY OF COLORADO DENVER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-15 至 2023-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10264080
• 关键词: Affect; Amino Acids; Appearance; Autoantibodies; Autoimmunity; Automobile Driving; Biochemical Reaction; Child; Citric Acid Cycle; Colorado; Communities; Complex; Data; Detection; Development; Diabetes Mellitus; Disease; Disease Progression; Enzymes; Finland; Foundations; Functional disorder; Future; Genes; Genetic; Genetic Variation; Genotype; Germany; Heritability; Incidence; Individual; Insulin-Dependent Diabetes Mellitus; Investigation; Islet Cell; Islets of Langerhans; Mediation; Metabolic; Pathogenesis; Phase; Phospholipids; Positioning Attribute; Process; Quantitative Trait Loci; Research; Research Design; Resources; Risk; Sweden; Technology; Testing; Time; Variant; chronic autoimmune disease; cohort; data repository; endocrine pancreas development; genetic approach; genetic variant; genome-wide; genomic locus; high risk population; improved; infancy; insight; islet autoimmunity; metabolic phenotype; metabolome; metabolomics; multiple omics; non-genetic; novel; pre-clinical; prevent; programs; prospective; repository; seroconversion; tool; trait

PROJECT SUMMARY Type 1 diabetes (T1D) is a chronic, autoimmune disease that affects 1.4 million people in the U.S, and its incidence is increasing. The preclinical period of T1D is called islet autoimmunity (IA) and is characterized by the detection of autoantibodies to pancreatic islet cells. Genetic and non-genetic factors contribute to the risk of T1D, though factors affecting the progression from preclinical IA to symptomatic T1D remain unclear. Metabolomics and associated genetic loci controlling metabolite levels (mtQTLs) can be powerful tools for understanding disease pathophysiology that have been underutilized in T1D research. Genes encode enzymes, and the downstream effect of genetic variation on enzymatic activity is captured by ratios between metabolites participating in biochemical reactions. Although several studies have identified individual metabolites associated with risk of T1D (T1D metabotypes), functional understanding of these compounds remains elusive since metabolites reflect both genetic and environmental influences. Characterization of T1D metabotype ratios and related genetic drivers therefore promises to deliver new insights into progression to T1D. The Environmental Determinants of Diabetes in the Young (TEDDY) consortium is the largest prospective T1D study in the world, following 8,676 children in Finland, Germany, Sweden, and the U.S. for the development of IA and T1D. In this initiative, we will leverage TEDDY’s robust multi-omics repository to: 1) Identify ratios of T1D metabotypes associated with progression from IA to T1D; 2) Estimate T1D metabotype and ratio heritability to elucidate the genetic vs. environmental contribution to metabolite variation at the time of seroconversion to IA and from infancy to seroconversion; 3) Perform mtQTL mapping to identify the genotypes that affect T1D-associated or highly heritable metabotypes and ratios, and quantify the relationship between mtQTLs, T1D metabotypes and ratios, and progression to T1D in a mediation analysis. Our team is uniquely positioned to replicate results in the Diabetes Autoimmunity Study in the Young (DAISY), which follows 2,547 children in Colorado for T1D using similar study design, case definitions, and genetics and metabolomics technologies as TEDDY. Findings from these aims will provide critical data for a future application to refine and pinpoint environmental contributions to metabolomics changes in T1D using multi-omics approaches. Furthermore, this study improves on previous metabolomics studies in T1D by incorporating cutting-edge approaches that integrate metabolomics and genetics to elucidate underlying processes in disease progression. Our characterization of genetic influences on metabolomics disturbances at this stage of disease will lay a foundation for the ongoing search for strategies to prevent or delay T1D progression in high-risk populations.

项目总结 1型糖尿病(T1D)是一种慢性自身免疫性疾病，影响着美国140万人，其 发病率正在增加。T1D的临床前阶段称为胰岛自身免疫期(IA)，其特征是 胰岛细胞自身抗体的检测。遗传性和非遗传性因素会增加患糖尿病的风险。 T1D，尽管影响从临床前IA进展到症状性T1D的因素仍不清楚。 代谢组学和相关的控制代谢物水平的遗传基因座(MtQTL)可以作为强大的工具 了解在T1D研究中未得到充分利用的疾病病理生理学。基因编码酶， 基因变异对酶活性的下游影响是通过代谢产物之间的比率来捕捉的 参与生化反应。尽管有几项研究已经确定了与 由于存在T1D(T1D代谢型)的风险，这些化合物的功能了解仍然难以捉摸，因为 代谢物既能反映遗传影响，也能反映环境影响。T1D代谢型比率的表征和 因此，相关的基因驱动因素有望为T1D的进展提供新的见解。环境保护 The Young(Teddy)财团的糖尿病决定因素是世界上最大的前瞻性T1D研究， 芬兰、德国、瑞典和美国的8,676名儿童参与了IA和T1D的开发。在这 计划，我们将利用Teddy强大的多组学存储库：1)确定T1D代谢型的比率 2)估计T1D代谢型和比率遗传力，以阐明 在血清转换为IA时和从婴儿期开始，遗传和环境对代谢物变化的贡献 进行mtQTL定位，以确定影响T1D相关或高度相关的基因类型 可遗传代谢型和比率，并量化mtQTL、T1D代谢型和比率之间的关系， 并在中介分析中进行到T1D。我们的团队处于独特的地位，可以在 青年糖尿病自身免疫研究(DAISY)，跟踪调查科罗拉多州2547名儿童使用T1D 与Teddy相似的研究设计、病例定义以及遗传学和代谢组学技术。调查结果来自 这些目标将为未来的应用程序提供关键数据，以完善和准确地确定环境贡献 用多组学方法研究T1D的代谢组学变化。此外，本研究在前人的基础上有所改进 T1D中的代谢组学研究通过整合代谢组学和 阐明疾病发展的潜在过程的遗传学。我们对遗传影响的描述 在疾病的这个阶段，代谢组学的紊乱将为正在进行的寻找策略奠定基础 预防或延缓高危人群的T1D进展。