Multi-trait genome-wide characterization of non-traditional glycemic biomarkers and type 2 diabetes

非传统血糖生物标志物和 2 型糖尿病的多特征全基因组表征

基本信息

批准号：
10215925
负责人：
Debashree Ray
金额：
$ 24.56万
依托单位：
JOHNS HOPKINS UNIVERSITY
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-04-01 至 2023-03-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10215925
关键词：
Atherosclerosis Risk in Communities Biological Biological Assay Biological Markers Biology Caring Clinical Coronary Artery Risk Development in Young Adults Study DNA Methylation Data Databases Development Diabetes Mellitus Diagnosis Environmental Risk Factor Epidemic Epidemiology Ethnic group Family Study Fasting Female Fructosamine Future Gene Frequency Genes Genetic Genetic Determinism Genetic Predisposition to Disease Genetic study Genotype Glucose Glycosylated Hemoglobin Glycosylated hemoglobin A Guidelines Heritability Hour Hyperglycemia Impaired fasting glycaemia Impairment Insulin Investigation Joints Knowledge Lead Maps Measurement Mendelian randomization Methods Modernization Monitor National Heart, Lung, and Blood Institute Non-Insulin-Dependent Diabetes Mellitus OGTT Obesity Participant Pathway interactions Patients Pattern Pharmacotherapy Physiology Plasma Predisposition Preparation Prevention strategy Proteomics Research Role Sampling Sex Differences Signal Transduction Smoking Statistical Methods Stress Time Trans-Omics for Precision Medicine Twin Studies Variant base causal variant clinically relevant cohort diabetes mellitus genetics diabetes risk exome fasting glucose follow-up genetic architecture genetic association genetic risk factor genetic variant genome wide association study genome-wide glycemic control glycosylated serum albumin improved individual variation innovation insight male multi-ethnic multiple omics novel novel strategies novel therapeutics pleiotropism programs rare variant risk stratification screening sedentary lifestyle sex targeted treatment trait translational impact whole genome

项目摘要

PROJECT SUMMARY Type 2 diabetes (T2D) and its long-term complications has reached epidemic proportions worldwide. Currently, there are major gaps in the knowledge of T2D genetics and its underlying mechanisms, which is critical for identifying novel therapies and strategies that can reduce the impact of T2D. Genetic studies of clinically relevant biomarkers in relation to T2D, beyond the classical glycemic biomarkers (e.g. glucose, HbA1c, and insulin- related traits), can help us get a wholesome view of T2D mechanisms. There is growing epidemiologic evidence that nontraditional biomarkers of hyperglycemia – fructosamine, glycated albumin, and 1,5-anhydroglucitol – improve risk stratification of diabetes and its long-term complications, provide information beyond the classical glycemic biomarkers, and hold promise in providing unique insights into hyperglycemia and diabetes physiology. A limited number of previous genome-wide association studies (GWAS) have examined genetic determinants of these newer biomarkers using data from the Atherosclerosis Risk in Communities (ARIC) Study. Thus far, ARIC (or any other study) has not been fully exploited to unravel genetic associations of these newer biomarkers or investigate underlying causal mechanisms using more advanced statistical methods that can leverage overlapping genetic architecture of these biomarkers, among themselves and with traditional glycemic biomarkers and T2D taking into account sex-specific differences. In this proposal, we will use modern statistical approaches to exploit the unique data available on these newer glycemic biomarkers, in two major ethnic groups (Black and White) in the ARIC Study to identify genetic associations across the entire allele-frequency spectrum (Aims 1, 3); to explore genetic overlap with traditional biomarkers (Aim 2) and with known T2D-relevant genes (Aims 2, 3); to investigate independent causal role of all biomarkers on T2D by leveraging genetic overlap (Aim 2); and characterize sex-specific and ancestry-specific differences if any (Aims 1-3). We will attempt to replicate our findings in the Coronary Artery Risk Development in Young Adults (CARDIA) study. Our innovations include going beyond the current paradigm of T2D locus discovery using classical biomarkers; novel use of modern multi-trait approaches on existing data; novel follow-up analysis of pleiotropic loci to better characterize underlying causal mechanisms using Mendelian Randomization; use of trans-ethnic analysis to boost GWAS power; and exploring rare variant associations of fructosamine and glycated albumin for the first time. Successful completion of these aims will provide preliminary data for a subsequent multi-omics proposal to study these biomarkers using DNA methylation, proteomic, and whole genome sequence data in ARIC. Thus, our pipeline for systematic examination of unique and shared genetics of these newer glycemic biomarkers with classical biomarkers and T2D can lead to a better understanding of the mechanisms by which they act in concert in delineating T2D risk, and can impact clinical guidelines and diabetes care. Intriguing results from this proposal will encourage other cohorts to do assays of these newer biomarkers that will increase power of future GWAS.

项目概要目前，2 型糖尿病（T2D）及其长期并发症已在全球范围内流行。对 T2D 遗传学及其潜在机制的了解存在重大差距，这对于可以减少 T2D 临床相关影响的新疗法和策略。与 T2D 相关的生物标志物，超出了经典的血糖生物标志物（例如葡萄糖、HbA1c 和胰岛素）相关特征），可以帮助我们对 T2D 机制有一个全面的认识。越来越多的流行病学证据。高血糖的非传统生物标志物——果糖胺、糖化白蛋白和 1,5-脱水葡萄糖醇—— 改善糖尿病及其长期并发症的风险分层，提供经典之外的信息血糖生物标志物，并有望为高血糖和糖尿病生理学提供独特的见解。之前有限数量的全基因组关联研究（GWAS）已经检查了这些较新的生物标志物使用了迄今为止社区动脉粥样硬化风险 (ARIC) 研究的数据。（或任何其他研究）尚未被充分利用来揭示这些新生物标志物的遗传关联或使用更先进的统计方法来研究潜在的因果机制这些生物标志物之间以及与传统血糖的遗传结构重叠生物标志物和 T2D 考虑到性别特异性差异在本提案中，我们将使用现代统计。在两个主要种族群体中利用这些新的血糖生物标志物的独特数据的方法 ARIC 研究中的（黑白）识别整个等位基因频谱的遗传关联（目标 1、3）；探索与传统生物标志物（目标 2）和已知 T2D 相关基因的遗传重叠（目标 2、3）；利用遗传重叠研究所有生物标志物对 T2D 的独立因果作用（目标 2)；并描述性别特异性和血统特异性差异（如果有）（我们将尝试复制）。我们在年轻人冠状动脉风险发展 (CARDIA) 研究中的发现我们的创新包括。超越当前使用经典生物标志物发现 T2D 基因座的范例；对现有数据进行多性状方法；对多效性基因座进行新颖的后续分析，以更好地表征使用孟德尔随机化的潜在因果机制；使用跨种族分析来促进 GWAS 力量；并首次探索果糖胺和糖化白蛋白的罕见变异关联。这些目标的成功完成将为后续的多组学提案提供初步数据使用 ARIC 中的 DNA 甲基化、蛋白质组和全基因组序列数据来研究这些生物标志物。我们对这些新的血糖生物标志物的独特和共享遗传学进行系统检查的管道经典生物标志物和 T2D 可以更好地理解它们协同作用的机制描述 T2D 风险，并且可以影响临床指南和糖尿病护理。将鼓励其他队列对这些新的生物标志物进行分析，这将增强未来 GWAS 的力量。