Influence of genetic variation, genetic ancestry, and obesity on gestational diabetes mellitus risk

遗传变异、遗传血统和肥胖对妊娠期糖尿病风险的影响

• 批准号: 10113596
• 负责人: Ayush Giri
• 金额: $ 14.03万
• 依托单位: VANDERBILT UNIVERSITY MEDICAL CENTER
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-03-01 至 2023-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10113596
• 关键词: Academic Medical Centers; Affect; African; African American; Algorithms; American; Area; Asian Americans; Asians; Award; Bioinformatics; Biology; Body mass index; Candidate Disease Gene; Categories; Central obesity; Classification; Clinical Data; Complications of Diabetes Mellitus; Country; Data; Databases; Development; Development Plans; Diabetes Mellitus; Diet; Electronic Health Record; Environmental Risk Factor; Ethnic Origin; Etiology; European; Functional disorder; Future; Gene Expression; Genes; Genetic; Genetic Predisposition to Disease; Genetic Variation; Genetic study; Genome; Gestational Diabetes; Glucose; Goals; High Prevalence; Hispanic Americans; Hispanics; Hyperglycemia; Individual; Insulin; Insulin Resistance; Investigation; Kidney Diseases; Knowledge; Koreans; Lead; Light; Link; Low Prevalence; Measures; Mendelian randomization; Mentored Research Scientist Development Award; Mentors; Methods; National Institute of Diabetes and Digestive and Kidney Diseases; Native American Ancestry; Native Americans; Neuropathy; Non-Insulin-Dependent Diabetes Mellitus; Obesity; Patient Self-Report; Phenotype; Physiology; Plant Roots; Population; Predictive Value; Pregnancy; Pregnancy Complications; Pregnancy Outcome; Pregnant Women; Prevalence; Prevention; Quantitative Trait Loci; Race; Regulation; Reporting; Reproducibility; Research; Research Personnel; Research Priority; Resources; Retinal Diseases; Risk; Risk Factors; Role; Sampling; Stream; Structure of beta Cell of islet; Testing; Thinness; Time; Tissue-Specific Gene Expression; Tissues; Training; Training Programs; United Kingdom; Variant; Waist-Hip Ratio; Weight; Woman; Women' s Health; biobank; biomedical informatics; case control; causal variant; cost effective; genetic architecture; genetic epidemiology; genetic variant; genome wide association study; high risk; innovation; instrument; multidisciplinary; personalized approach; personalized intervention; personalized strategies; population based; portability; prevent; racial disparity; repository; screening; trait

PROJECT SUMMARY/ABSTRACT Gestational diabetes mellitus (GDM), is among the most common pregnancy complications in the US. Shared pathophysiology with type-2 diabetes (T2D), evidence of familial aggregation, and evidence of racial disparity all support a role for genetic predisposition. Asian American (AAM) and Hispanic American (HA) women have lower prevalence of obesity on average than African American (AA) women, yet have higher GDM prevalence: 10.2%, 6.8%, 4.5% and 4.4% in AAM, HA, European American (EA) and AA women, respectively. Current studies are limited to candidate gene investigations with most investigating five to ten known T2D loci and only one genome-wide association study (GWAS) (468 cases; 1242 controls), in a South-Korean population. AAMs and HAs are the fastest growing populations in the US. Despite evident racial disparity suggesting a genetic etiology, no study has evaluated whether this is in part is rooted in differences associated with genetic ancestry. The overall goals of this proposal are to expand comprehensive genetic investigations of GDM and related traits by leveraging electronic health records (EHR) and bio-repositories to better understand the etiology which may inform personalized strategies for screening and prevention. We aim to develop, refine and validate reproducible and portable bioinformatics-algorithms to identity GDM cases and controls using de- identified EHR data at Vanderbilt. We will evaluate whether reported race/ethnicity modifies the association between maternal BMI and GDM in the Vanderbilt EHR database, the synthetic derivative (SD) (>8000 cases; Aim 1.1). In approximately 2,200 cases and 4,400 controls with genetic data, we will perform a Mendelian randomization study to test whether genetic instruments of central obesity (waist to hip ratio) or overall obesity (BMI) are more strongly associated with GDM (Aim 1.2). We will perform the first two-stage trans-ethnic GWAS of GDM in the US in EA, AA, HA, and AAM women from the SD and replicate associated variants (P < 1x10-6) in over 1000 GDM cases and many controls from the UK Biobank and Mount Sinai BioME EHR-linked bio- repository (Aim 2.1). By integrating GWAS data and expression quantitative trait loci (eQTL) data from various tissues with methods such as S-PrediXcan, we will prioritize candidate causal genes for GDM (Aim 2.2). Finally, we will explore whether genetically inferred Asian/Native American ancestry proportion is associated with increased risk of GDM (Aim 3.1) and T2D (Aim 3.2) in HAs. The well-tailored mentored training program supports the stated research aims and provides the candidate with the protected time to gain appropriate training in areas in which he lacks fully independent expertise, including phenotyping in the EHR setting, biomedical informatics and knowledge of gestational diabetes and classification of pregnancy outcomes. Successful completion of this award will facilitate the candidate's development into an independent multi- disciplinary researcher ideally prepared to contribute significantly to the fields of gestational diabetes, diabetes and associated complications, genetic epidemiology, racial disparity and women's health research.

项目总结/文摘