Examining Susceptibility and Resistance Phenotypes to Enhance Understanding of the Genetic Basis of Major Coronary Artery Disease in Type 1 Diabetes

检查易感性和耐药表型以增强对 1 型糖尿病主要冠状动脉疾病遗传基础的了解

• 批准号: 10506443
• 负责人: Rachel Grace Miller
• 金额: $ 64.88万
• 依托单位: UNIVERSITY OF PITTSBURGH AT PITTSBURGH
• 依托单位国家: 美国
• 财政年份: 2022
• 资助国家: 美国
• 起止时间: 2022-07-27 至 2027-06-30
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10506443
• 关键词: 17 year old; Address; Age-Years; Biological; Biological Markers; Blood Pressure; Blood Vessels; Candidate Disease Gene; Cardiovascular system; Cessation of life; Childhood; Clinical Data; Complications of Diabetes Mellitus; Coronary; Coronary Arteriosclerosis; Coupling; DNA Methylation; Data; Development; Diabetes Mellitus; Disease; Disease Pathway; Disease Resistance; Disease susceptibility; Electrocardiogram; Epidemiology; Etiology; Event; Future; Genes; Genetic; Genetic Code; Genetic Predisposition to Disease; Genetic study; Goals; Heterogeneity; Immune Response Genes; Immune response; Inflammation; Inflammatory; Inflammatory Response; Insulin-Dependent Diabetes Mellitus; Intervention; Ischemia; Kidney Diseases; Lipids; Measurement; Measures; Mediating; Mediation; Mendelian randomization; Myocardial Infarction; Natural History; Network-based; Outcome; Pathway interactions; Persons; Phenotype; Population; Predisposition; Prevalence; Proteins; Proteomics; Reporting; Resistance; Risk; Risk Factors; Sample Size; Sampling; Specimen; Subgroup; Testing; Variant; Vascular Diseases; base; burden of illness; case control; clinical risk; cohort; design; disease phenotype; disorder risk; follow-up; gene discovery; genetic variant; genome sequencing; genome wide association study; high risk; insulin dependent diabetes mellitus onset; multiple omics; novel; novel marker; novel therapeutic intervention; prevent; prospective; response biomarker; risk variant; targeted biomarker; trend; whole genome

ABSTRACT People with type 1 diabetes (T1D) are at dramatically increased risk of developing coronary artery disease (CAD), but the reasons for this excess risk compared to the background population are not fully understood. There is a critical need to identify people at risk of major CAD events early in their T1D natural history and to develop new therapeutic interventions to reduce CAD risk and burden. While prior studies have examined associations between genetic variants and CAD in T1D, a lack of strong candidate genes remains. This lack is at least partially due to the fact that case-control designs using low-precision phenotypes to maximize sample size and which disregard within-phenotype heterogeneity have been the most common approach to studying the genetic basis of vascular complications in T1D to date. Likewise, while it is well established that inflammatory and immune response biomarkers are associated with CAD risk in general and that levels of these biomarkers are elevated in T1D, the association between such markers and CAD has not been comprehensively studied in T1D. Inflammatory and immune response biomarkers are intermediate phenotypes that hold potential to help uncover novel pathways to CAD in T1D and may be promising treatment targets. Thus, our hypotheses are that unidentified genetic variants associated with CAD susceptibility or resistance exist and that networks of inflammatory and immune response biomarkers are associated with CAD and may mediate inflammatory/immune response gene-CAD associations. Our approach will be to first refine the CAD phenotype definition to one that better reflects the genetic etiology of CAD susceptibility and resistance in T1D. Specifically, studying highly specific “discordant” risk factor-CAD phenotype subgroups may help uncover novel pathways to CAD development in T1D. Our approach will increase precision of both genetic sequencing (by using whole genome sequencing) and CAD phenotype definitions. We will also measure a comprehensive proteomic panel of 92 targeted biomarkers and derive networks of related markers to assess their associations with CAD and the degree to which those networks mediate associations between CAD and genes involved in inflammation/immune response. We will utilize data and specimens from the Epidemiology of Diabetes Complications (EDC) study, a well-characterized T1D cohort with >30 years of follow-up and deep phenotyping, allowing us to comprehensively examine many intermediate phenotypes (i.e., traditional risk factors and novel biomarkers) in gene-to-CAD pathways. Furthermore, we will replicate the findings from this discovery analyses in external cohorts. With this approach we expect to uncover evidence of novel pathways that account for a proportion of unexplained CAD risk in T1D and point to new intervention targets.

抽象的 1 型糖尿病 (T1D) 患者患冠状动脉疾病的风险显着增加 （CAD），但与背景人群相比，这种超额风险的原因尚不完全清楚。 迫切需要在 T1D 自然史早期识别出有重大 CAD 事件风险的人群，并 开发新的治疗干预措施以降低 CAD 风险和负担。 尽管 T1D 基因变异与 CAD 之间存在关联，但仍缺乏强有力的候选基因。 至少部分是由于病例对照设计使用低精度表型来最大化样本 大小和忽视表型异质性是最常见的研究方法 迄今为止，T1D 血管并发症的遗传基础也同样如此，但这一点已得到充分证实。 炎症和免疫反应生物标志物总体上与 CAD 风险相关，并且炎症和免疫反应生物标志物的水平 这些生物标志物在 T1D 中升高，但这些标志物与 CAD 之间的关联尚未确定 在 T1D 中进行全面研究的炎症和免疫反应生物标志物是中间表型。 它们有可能帮助发现 T1D 中 CAD 的新途径，并可能成为有希望的治疗目标。 因此，我们的假设是，未识别的遗传变异与 CAD 易感性或抵抗力相关 存在，并且炎症和免疫反应生物标志物网络与 CAD 相关，并且可能 介导炎症/免疫反应基因-CAD 关联我们的方法是首先完善 CAD。 表型定义能够更好地反映 1 型糖尿病 (T1D) 中 CAD 易感性和耐药性的遗传病因。 具体来说，研究高度特异性的“不一致”风险因素 - CAD 表型亚组可能有助于揭示 T1D 中 CAD 开发的新途径将提高基因测序的精度。 （通过使用全基因组测序）和 CAD 表型定义。 由 92 个目标生物标志物组成的蛋白质组组，并衍生相关标志物网络以评估其关联 CAD 以及这些网络介导 CAD 与相关基因之间关联的程度 我们将利用糖尿病流行病学的数据和标本。 并发症 (EDC) 研究，一项经过 30 年以上随访和深入研究的特征明确的 T1D 队列 表型分析，使我们能够全面检查许多中间表型（即传统的风险 此外，我们将复制此研究结果。 通过这种方法，我们期望发现新途径的证据。 这解释了 1 型糖尿病中无法解释的 CAD 风险的一部分，并指出了新的干预目标。