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

项目总结/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（T2 D）的病理生理学、家族聚集性证据和种族差异证据 都支持遗传易感性的作用。亚裔美国人（AAM）和西班牙裔美国人（HA）女性 肥胖的平均患病率低于非洲裔美国人（AA）妇女，但GDM的患病率较高： AAM、HA、EA和AA妇女的阳性率分别为10.2%、6.8%、4.5%和4.4%。电流 研究仅限于候选基因调查，大多数调查五到十个已知的T2 D基因座， 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）。个aam 而HA是美国增长最快的人群。尽管明显的种族差异表明 病因学，没有研究评估这是否部分植根于与遗传相关的差异， 祖先该提案的总体目标是扩大GDM的全面遗传学研究， 通过利用电子健康记录（EHR）和生物储存库来更好地了解 病因学，可以为筛查和预防提供个性化策略。我们的目标是开发、完善和 验证可重复和便携式生物信息学算法，以识别GDM病例和对照， 在范德比尔特确认了电子病历数据我们将评估报告的人种/种族是否改变了相关性 在范德比尔特EHR数据库中，母亲BMI与GDM之间的合成衍生物（SD）（>8000例; 目标1.1）。在大约2,200例病例和4,400例有遗传数据的对照中，我们将进行孟德尔遗传分析。 随机研究，以测试是否遗传工具的中心性肥胖（腰臀比）或整体肥胖 (BMI)与GDM的相关性更强（目标1.2）。我们将进行第一个两阶段的跨种族GWAS 来自SD和重复相关变异的EA、AA、HA和AAM女性中美国GDM的比例（P <1x 10 -6） 在超过1000例GDM病例和许多来自英国生物库和西奈山生物医学EHR相关生物的对照中， （目标2.1）。通过整合GWAS数据和来自不同群体的表达数量性状基因座（eQTL）数据， 组织的方法，如S-PrediXcan，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与 HAs中GDM（目标3.1）和T2 D（目标3.2）的风险增加。量身定制的指导培训计划 支持声明的研究目标，并为候选人提供受保护的时间，以获得适当的 在他缺乏完全独立专业知识的领域进行培训，包括EHR环境中的表型分析， 生物医学信息学和妊娠糖尿病知识以及妊娠结局分类。 成功完成此奖项将促进候选人的发展成为一个独立的多- 学科研究人员理想地准备作出重大贡献的领域妊娠糖尿病，糖尿病 和相关并发症，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.