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

项目摘要/摘要 妊娠期糖尿病(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、家族聚集的证据和种族差异的证据 所有人都支持遗传易感性的作用。亚裔(AAM)和西班牙裔(HA)女性 肥胖率平均低于非裔美国人(AA)女性，但GDM患病率较高： AAM、HA、欧美(EA)和AA女性分别为10.2%、6.8%、4.5%和4.4%。当前 研究仅限于候选基因研究，大多数研究5到10个已知的T2D基因座，并且仅 在韩国人群中进行的一项全基因组关联研究(GWAS)(468例；1242例对照)。AAM 哈马斯是美国人口增长最快的国家。尽管明显的种族差异表明 病因学方面，还没有研究评估这是否部分根源于与遗传相关的差异 血统。这项提议的总体目标是扩大对妊娠期糖尿病和妊娠期糖尿病的全面遗传研究。 通过利用电子健康记录(EHR)和生物信息库更好地了解 病因学，可为个性化的筛查和预防策略提供信息。我们的目标是开发、完善和 验证可重现和便携的生物信息学-识别GDM病例和对照的算法 确认了范德比尔特的电子病历数据。我们将评估所报告的种族/民族是否会修改该关联 在Vanderbilt EHR数据库中，母亲BMI和GDM之间的合成导数(SD)(&gt；8000例； 目标1.1)。在大约2,200个病例和4,400个有基因数据的对照中，我们将进行孟德尔 一项随机研究，以检验中心性肥胖(腰臀比)或总体肥胖的遗传指标 体重指数(BMI)与妊娠期糖尿病的相关性更强(AIM 1.2)。我们将表演第一个跨种族的两个阶段的 在美国的妊娠期糖尿病中，来自SD的EA、AA、HA和AAM女性以及复制相关变异(P&lt；1x10-6) 在1000多例妊娠期糖尿病病例和来自英国生物库和西奈山生物群的许多对照中，EHR连接的生物- 存储库(目标2.1)。通过整合Gwas数据和来自不同地区的表达数量性状基因座(EQTL)数据 利用S-PrediXcan等方法，我们将优先考虑妊娠期糖尿病的候选致病基因(目标2.2)。 最后，我们将探索从基因上推断的亚裔/美洲原住民血统比例是否相关 HAS中GDM(目标3.1)和T2D(目标3.2)的风险增加。量身定做的导师培训计划 支持规定的研究目标，并为应聘者提供适当的时间 在他缺乏完全独立专业知识的领域接受培训，包括在电子病历环境中进行表型分析， 妊娠期糖尿病的生物医学信息学和知识以及妊娠结局的分类。 成功完成这一奖项将有助于候选人发展成为一个独立的多学科 理想的学科研究人员准备在妊娠期糖尿病、糖尿病领域做出重大贡献 以及相关的并发症、遗传流行病学、种族差异和妇女健康研究。

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.