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: 10552803
• 负责人: Jun Li
• 金额: $ 24.9万
• 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/10552803
• 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; 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; 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; Study of Latinos; System; Systems Biology; TNFRSF1A gene; Technology; Training; White Blood Cell Count procedure; Work; adiponectin; base; biobank; biomarker development; career; case control; cohort; cytokine; diabetes risk; dietary; disorder prevention; genetic architecture; genomic data; genomic locus; high dimensionality; i(19); improved; indexing; inflammatory marker; innovation; machine learning model; metabolome; metabolomics; mortality; multidimensional data; multiple omics; novel; novel marker; prospective; protein metabolite; 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.

抽象的 2型糖尿病（T2D）的病因可能涉及多基因，代谢和 环境因素，包括饮食。累积实验，流行病学和临床证据 支持慢性感染在T2D发育中的致病作用。但是，精确的机制 这些发现的基础是未知的，并且目前有关因果关系的证据 特定的炎症途径和T2D风险尚无定论。 OMICS技术的进步已导致 与T2D风险相关的基因和代谢产物的鉴定，但有关机制和因果关系的数据 仍然非常有限。在系统流行病学框架中的多词集成可能会提供新的 增强我们对疾病机制的理解的途径。系统地研究这种关系 在慢性炎症和T2D之间，我建议通过利用富人来检查3个特定目标 英国生物库的资源，护士健康研究（NHS），卫生专业后续研究（HPFS）， 西班牙裔社区健康研究/拉丁裔（SOL）和基因型 - 组织表达项目 （GTEX）。在AIM 1 [K99]中，我将整合来自英国Biobank，NHS/HPFS，SOL和SOL和 GTEX中的转录组数据检查系统性炎症之间的共享遗传体系结构 标记和T2D以及对慢性炎症贡献T2D风险的多基因敏感性是否存在。同时， 我将接受T2D系统生物学和尖端高维数据分析的广泛培训 和生物信息学。在AIM 2 [R00]中，我将整合饮食和代谢组数据以检查代谢组学 介导饮食炎症潜力与T2D风险之间的关联的概况 NHS/HPFS和SOL。在AIM 3 [r00]中，我将在嵌套的病例对照中进行等离子体蛋白质组学分析 在NHS中进行研究，以鉴定与T2D风险有关的炎症蛋白网络，并作为次要 AIM，AIM 1-3的集成发现，以探索与T2D相关的途径在多个生物学上共同调节 方面。该项目的发现可能会改善对炎症机制的理解 基础T2D并确定适合早期检测和预防的新型目标/途径。我会的 由包括乔恩·曼森（Joann Manson）博士（糖尿病流行病学家）在内的跨学科团队的指导/建议 Liming Liang博士（统计学方法的专家），Frank Hu博士（营养流行病学家），博士 彼得·卡夫（Peter Kraft），（统计遗传学家），Qibin Qi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）。钥匙的出色培训机会 这些领域的领导者将为我提供高级知识和技能，为我定位成功， 独立职业作为糖尿病的独立职业，仅是系统生物学和集成词专家的流行病学家。 该项目符合NIDDK的目标，即将多派技术集成到糖尿病研究中。