Chronic Inflammation and Type 2 Diabetes: A Multi-omics Approach

慢性炎症和 2 型糖尿病：多组学方法

• 批准号: 10592436
• 负责人: Jun Li
• 金额: $ 24.42万
• 依托单位: BRIGHAM AND WOMEN'S HOSPITAL
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-09-01 至 2025-03-14
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10592436
• 关键词: Adult; Affect; Applications Grants; Area; Bioinformatics; Biological; C-reactive protein; Cardiometabolic Disease; Cardiovascular Diseases; Chronic; Clinical; Complex; Data; Data Analytics; Development; Diabetes Mellitus; Diabetes prevention; Diet; Dietary Assessment; Dimensions; Disease; Early Diagnosis; Environmental Risk Factor; Epidemiologist; Epidemiology; Etiology; Follow-Up Studies; Food; Future; Genes; Genetic; Genetic Predisposition to Disease; Genomics; Genotype-Tissue Expression Project; Goals; Health Professional; Hispanic Community Health Study/Study of Latinos; IL6 gene; Inflammation; Inflammatory; Intake; Interleukin-6; Kidney Diseases; Knowledge; Mediating; Mentors; Metabolic; Methodology; Methods; Multiomic Data; National Institute of Diabetes and Digestive and Kidney Diseases; Nested Case-Control Study; Non-Insulin-Dependent Diabetes Mellitus; Nurses' Health Study; Nutritional; Pathogenicity; Pathway interactions; Patient Self-Report; Pattern; Phenotype; Physiological; Pilot Projects; Plasma; Positioning Attribute; Predisposition; Prevention; Prospective, cohort study; Proteins; Proteome; Proteomics; Public Health; Qi; Regulator Genes; Regulatory Element; Research; Research Design; Research Personnel; Resources; Retinal Diseases; Risk; Risk Factors; Role; System; Systems Biology; TNFRSF1A gene; Technology; Training; White Blood Cell Count procedure; Work; adiponectin; biobank; biomarker development; career; case control; cohort; cytokine; diabetes risk; dietary; disorder prevention; genetic architecture; genomic data; genomic locus; high dimensionality; improved; indexing; inflammatory marker; innovation; machine learning model; metabolome; metabolomics; mortality; multidimensional data; multiple omics; novel; novel marker; prospective; response; skills; systemic inflammatory response; therapeutic target; training opportunity; transcriptome; transcriptomics; whole genome

ABSTRACT The etiology of type 2 diabetes (T2D) likely involves a complex interaction of polygenic, metabolic, and environmental factors including diet. Accumulating experimental, epidemiological, and clinical evidence supports a pathogenic role of chronic inflammation in T2D development. However, the precise mechanisms underlying these findings are largely unknown, and current evidence on the causal relationships between specific inflammatory pathways and T2D risk is inconclusive. Advances in omics technologies have led to the identification of genes and metabolites associated with T2D risk, but data on mechanisms and causality are still very limited. Multi-omics integration in the framework of systems epidemiology may provide new avenues to enhance our understanding of disease mechanisms. To systematically investigate the relation between chronic inflammation and T2D, I propose to examine 3 Specific Aims by leveraging the rich resources in the UK Biobank, Nurses’ Health Studies (NHS), Health Professional Follow-up Study (HPFS), Hispanic Community Health Study/Study of Latinos (SOL), and Genotype-Tissue Expression project (GTEx). In Aim 1 [K99], I will integrate existing genomic data from the UK Biobank, NHS/HPFS, SOL, and transcriptomic data in the GTEx to examine shared genetic architectures between systemic inflammatory markers and T2D and whether polygenic susceptibility to chronic inflammation confers T2D risk. Meanwhile, I will receive extensive training in T2D systems biology and cutting-edge high-dimensional data analytics and bioinformatics. In Aim 2 [R00], I will integrate dietary and metabolomic data to examine metabolomic profiles mediating the association between dietary inflammatory potentials and T2D risk in the prospective NHS/HPFS and the SOL. In Aim 3 [R00], I will conduct plasma proteomic profiling in a nested case-control study within the NHS to identify inflammatory protein networks in relation to T2D risk, and as a Secondary Aim, integrate findings from Aim 1-3 to explore T2D-related pathways co-regulating at multiple biological dimensions. Findings from this project may improve the understanding of inflammatory mechanisms underlying T2D and identify novel targets/pathways suitable for early detection and prevention. I will be mentored/advised by an interdisciplinary team that includes Dr. JoAnn Manson (diabetes epidemiologist), Dr. Liming Liang (expert in statistical omics methodologies), Dr. Frank Hu (nutritional epidemiologist), Dr. Peter Kraft, (statistical geneticist), Dr. Qibin Qi (genetic epidemiologist), Dr. Towia Libermann (expert in proteomics), and Dr. Clary Clish (expert in metabolomics). The outstanding training opportunities with key leaders in these areas will provide me advanced knowledge and skills, positioning me for a successful, independent career as a diabetes epidemiologist with expertise in systems biology and integrated-omics. This project aligns with the NIDDK’s goal of integrating multi-omics technologies into diabetes research.

摘要 2型糖尿病（T2 D）的病因可能涉及多基因、代谢和遗传的复杂相互作用。 环境因素包括饮食。积累实验、流行病学和临床证据 支持慢性炎症在T2 D发展中的致病作用。然而，精确的机制 这些发现的基础在很大程度上是未知的，目前的证据表明， 具体的炎症途径和T2 D风险是不确定的。组学技术的进步导致了 识别与T2 D风险相关的基因和代谢物，但有关机制和因果关系的数据 仍然非常有限。系统流行病学框架下的多组学整合可能提供新的 这有助于我们更好地了解疾病的机制。为了系统地研究 在慢性炎症和T2 D之间，我建议通过利用丰富的 英国生物银行的资源，护士健康研究（NHS），健康专业随访研究（HPFS）， 西班牙裔社区健康研究/拉丁美洲人研究（SOL）和基因型-组织表达项目 （GTEx）。在目标1 [K99]中，我将整合来自英国生物库、NHS/HPFS、SOL和 GTEx中的转录组学数据，以检查全身性炎症性疾病之间共享的遗传结构。 标记物和T2 D以及对慢性炎症的多基因易感性是否赋予T2 D风险。同时， 我将接受T2 D系统生物学和尖端高维数据分析方面的广泛培训 和生物信息学。在目标2 [R 00]中，我将整合饮食和代谢组学数据，以检查代谢组学 在前瞻性研究中， NHS/HPFS和SOL。在目标3 [R 00]中，我将在巢式病例对照中进行血浆蛋白质组学分析 NHS内的研究，以确定与T2 D风险相关的炎症蛋白网络，并作为次要研究， 目的，整合目的1-3的发现，探索T2 D相关通路在多种生物学行为中的共调节作用。 尺寸.该项目的发现可能会提高对炎症机制的理解 T2 D的潜在原因，并确定适合早期检测和预防的新靶点/途径。我将 由包括JoAnn曼森博士（糖尿病流行病学家）在内的跨学科团队指导/建议， 博士梁黎明（统计组学方法学专家），胡福兰博士（营养流行病学家）， Peter Kraft，（统计遗传学家），Qibin Qi博士（遗传流行病学家），Towia Libermann博士（ 蛋白质组学）和Clary Clish博士（代谢组学专家）。出色的培训机会， 这些领域的领导者将为我提供先进的知识和技能，使我成为一个成功的， 作为一名糖尿病流行病学家，拥有系统生物学和集成组学方面的专业知识。 该项目符合NIDDK将多组学技术整合到糖尿病研究中的目标。