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.

摘要