Chronic Inflammation and Type 2 Diabetes: A Multi-omics Approach
Chronic Inflammation and Type 2 Diabetes: A Multi-omics Approach
批准号:
9805982
负责人:
Jun Li
金额:
$9.15万
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-09-01 至 2021-08-31
关键词:
AdultAffectApplications GrantsAreaBioinformaticsBiologicalC-reactive proteinCardiovascular DiseasesChronicClinicalComplexDataData AnalyticsDevelopmentDiabetes MellitusDiabetes preventionDietDietary AssessmentDimensionsDiseaseEarly DiagnosisEnvironmental Risk FactorEpidemiologistEpidemiologyEtiologyFollow-Up StudiesFoodFutureGene ProteinsGenesGeneticGenetic Predisposition to DiseaseGenomicsGenotype-Tissue Expression ProjectGoalsHealth ProfessionalHispanic Community Health Study/Study of LatinosIL6 geneInflammationInflammatoryIntakeInterleukin-6Kidney DiseasesKnowledgeLimesMachine LearningMediatingMentorsMetabolicMethodologyMethodsModelingMultiomic DataNational Institute of Diabetes and Digestive and Kidney DiseasesNested Case-Control StudyNon-Insulin-Dependent Diabetes MellitusNurses&apos Health StudyNutritionalPathogenicityPathway interactionsPatient Self-ReportPatternPhenotypePhysiologicalPilot ProjectsPlasmaPositioning AttributePredispositionPreventionProspective cohort studyProteinsProteomeProteomicsPublic HealthQiRegulator GenesRegulatory ElementResearchResearch DesignResearch PersonnelResourcesRetinal DiseasesRiskRisk FactorsRoleStudy of LatinosSystemSystems BiologyTNFRSF1A geneTechnologyTrainingWhite Blood Cell Count procedureWorkadiponectinbasebiobankbiomarker developmentcardiometabolismcareercase controlcohortcytokinediabetes riskdisorder preventiongenetic architecturegenomic datahigh dimensionalityi(19)improvedindexinginflammatory markerinnovationmetabolomemetabolomicsmortalitymultidimensional datamultiple omicsnovelnovel markerprospectiveprotein metaboliteresponseskillstherapeutic targettraining opportunitytranscriptometranscriptomicswhole genome
中文摘要
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英文摘要
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.
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