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: 9805982
• 负责人: Jun Li
• 金额: $ 9.15万
• 依托单位: HARVARD SCHOOL OF PUBLIC HEALTH
• 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 2021-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9805982
• 关键词: Adult; Affect; Applications Grants; Area; Bioinformatics; Biological; C-reactive protein; 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; Gene Proteins; 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; Limes; Machine Learning; Mediating; Mentors; Metabolic; Methodology; Methods; Modeling; 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; Study of Latinos; System; Systems Biology; TNFRSF1A gene; Technology; Training; White Blood Cell Count procedure; Work; adiponectin; base; biobank; biomarker development; cardiometabolism; career; case control; cohort; cytokine; diabetes risk; disorder prevention; genetic architecture; genomic data; high dimensionality; i(19); improved; indexing; inflammatory marker; innovation; metabolome; metabolomics; mortality; multidimensional data; multiple omics; novel; novel marker; prospective; protein metabolite; response; skills; 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.

抽象的 2 型糖尿病 (T2D) 的病因可能涉及多基因、代谢和代谢因素的复杂相互作用。 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 T2D 发展中的致病作用。然而，精确的机制 这些发现的背后很大程度上是未知的，目前关于两者之间因果关系的证据 具体的炎症途径和 T2D 风险尚无定论。组学技术的进步导致 识别与 T2D 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。系统流行病学框架中的多组学整合可能提供新的 增强我们对疾病机制的了解的途径。系统地研究关系 在慢性炎症和 T2D 之间，我建议利用丰富的资源来研究 3 个具体目标 英国生物银行、护士健康研究 (NHS)、健康专业随访研究 (HPFS) 的资源， 西班牙裔社区健康研究/拉丁裔研究 (SOL) 和基因型组织表达项目 （GTEx）。在目标 1 [K99] 中，我将整合来自 UK Biobank、NHS/HPFS、SOL 和 GTEx 中的转录组数据可检查系统性炎症之间的共享遗传结构 标记物和 T2D 以及对慢性炎症的多基因易感性是否会带来 T2D 风险。同时， 我将接受 T2D 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 [R00] 中，我将整合饮食和代谢组数据来检查代谢组 前瞻性地介导膳食炎症潜力与 T2D 风险之间关联的概况 NHS/HPFS 和 SOL。在目标 3 [R00] 中，我将在嵌套病例对照中进行血浆蛋白质组分析 NHS 内的一项研究旨在识别与 T2D 风险相关的炎症蛋白网络，并将其作为次要研究 目标，整合目标 1-3 的发现，探索 T2D 相关通路在多个生物体上的共同调节 方面。该项目的研究结果可能会增进对炎症机制的理解 潜在的 T2D 并确定适合早期检测和预防的新靶标/途径。我会的 由包括 JoAnn Manson 博士（糖尿病流行病学家）在内的跨学科团队指导/建议， 梁黎明博士（统计组学方法学专家）、Frank Hu 博士（营养流行病学家）、 Peter Kraft（统计遗传学家）、齐其斌博士（遗传流行病学家）、Towia Libermann 博士（专家） 蛋白质组学）和 Clary Clish 博士（代谢组学专家）。杰出的培训机会与关键 这些领域的领导者将为我提供先进的知识和技能，使我能够取得成功， 作为一名独立的糖尿病流行病学家，拥有系统生物学和综合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。