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

摘要

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.