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.

项目概要/摘要 妊娠糖尿病（GDM）是美国最常见的妊娠并发症之一。共享 2 型糖尿病 (T2D) 的病理生理学、家族聚集的证据以及种族差异的证据 所有这些都支持遗传倾向的作用。亚裔美国人 (AAM) 和西班牙裔美国人 (HA) 女性 平均肥胖患病率低于非裔美国 (AA) 女性，但 GDM 患病率较高： AAM、HA、欧洲裔美国人 (EA) 和 AA 女性的比例分别为 10.2%、6.8%、4.5% 和 4.4%。当前的 研究仅限于候选基因调查，大多数调查五到十个已知的 T2D 位点，并且仅 一项针对韩国人群的全基因组关联研究 (GWAS)（468 例病例；1242 名对照）。空空导弹 HA 和 HA 是美国增长最快的人口。尽管明显的种族差异表明遗传因素 病因学方面，尚无研究评估这是否部分源于与遗传相关的差异 祖先。该提案的总体目标是扩大 GDM 的全面遗传研究和 通过利用电子健康记录 (EHR) 和生物存储库来更好地了解相关特征 病因学可为筛查和预防的个性化策略提供信息。我们的目标是开发、完善和 验证可重复且可移植的生物信息学算法，以使用 de- 来识别 GDM 病例和对照 确定了范德比尔特大学的 EHR 数据。我们将评估所报告的种族/民族是否会改变关联 范德比尔特 EHR 数据库中母亲 BMI 和 GDM 之间的合成衍生物 (SD)（>8000 例； 目标 1.1)。在大约 2,200 个病例和 4,400 个具有遗传数据的对照中，我们将进行孟德尔分析 随机化研究，测试遗传工具是否影响中心性肥胖（腰臀比）或整体肥胖 (BMI) 与 GDM 的相关性更强（目标 1.2）。我们将进行首个两阶段跨种族 GWAS 美国 EA、AA、HA 和 AAM 女性中来自 SD 的 GDM 的发生率以及复制相关变异 (P < 1x10-6) 在超过 1000 个 GDM 病例以及来自 UK Biobank 和 Mount Sinai BioME EHR 相关生物的许多对照中 存储库（目标 2.1）。通过整合 GWAS 数据和来自不同国家的表达数量性状位点 (eQTL) 数据 通过 S-PrediXcan 等方法对组织进行分析，我们将优先考虑 GDM 的候选致病基因（目标 2.2）。 最后，我们将探讨基因推断的亚洲/美洲原住民血统比例是否相关 HA 中 GDM（目标 3.1）和 T2D（目标 3.2）的风险增加。精心定制的指导培训计划 支持既定的研究目标，并为候选人提供受保护的时间来获得适当的研究成果 在他缺乏完全独立专业知识的领域接受培训，包括电子病历环境中的表型分析， 妊娠糖尿病的生物医学信息学和知识以及妊娠结局的分类。 成功完成该奖项将有助于候选人发展成为独立的多学科人士 学科研究员理想地准备为妊娠糖尿病、糖尿病领域做出重大贡献 及相关并发症、遗传流行病学、种族差异和妇女健康研究。