Genetic determinants of puberty and later life health outcomes

青春期和晚年健康结果的遗传决定因素

• 批准号: 9805815
• 负责人: Diana Cousminer
• 金额: $ 13.17万
• 依托单位: CHILDREN'S HOSP OF PHILADELPHIA
• 依托单位国家: 美国
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-07-17 至 2020-07-01
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9805815
• 关键词: Address; Adolescence; Adolescent; Adult; Affect; Age; Age at Menarche; Area; Award; Bioinformatics; Child; Childhood; Clinical; Collaborations; Data; Development; Disease; Early Intervention; Elderly; Electronic Health Record; Ensure; Etiology; Female; Foundations; Genetic; Genetic Determinism; Genetic Risk; Genetic Variation; Genome; Genomics; Goals; Growth; Health; Height; Heritability; Individual; Informatics; International; Investigation; Knowledge; Lead; Leadership; Life; Link; Machine Learning; Malignant Neoplasms; Measurement; Medical; Menarche; Mentors; Mentorship; Meta-Analysis; Methods; Mission; Modeling; Molecular; National Institute of Child Health and Human Development; Non-Insulin-Dependent Diabetes Mellitus; Onset of illness; Osteoporosis; Outcome; Pathway interactions; Patients; Phase; Phenotype; Positioning Attribute; Postdoctoral Fellow; Prevention strategy; Puberty; Public Health; Regulation; Reporting; Research; Research Personnel; Research Training; Risk Factors; Secure; Signal Transduction; Speed; Techniques; Testing; Traction; Training; Translating; Variant; Voice; Work; biobank; biomedical informatics; boys; cardiometabolism; career; career development; clinical care; clinical risk; clinically relevant; cohort; data resource; experience; genetic variant; genome wide association study; girls; informatics training; insight; longitudinal analysis; male; men; novel; phenome; population based; pubertal timing; sex; sexual dimorphism; skills; tool; trait; virtual

My long-term objective is to build on my existing track record in understanding the genetic mechanisms that influence differences in pubertal developmental timing and how they impact associated adverse health outcomes. Puberty is a key adolescent developmental milestone that is strongly associated with later life health outcomes, such as poor cardiometabolic health, type 2 diabetes, cancer, and osteoporosis. Hundreds of genetic variants across the genome are known to affect the timing of puberty (assessed by age at menarche in girls and age at voice break in boys), but the sex-specific impact of this genetic variation on health outcomes in adolescence and adulthood remain poorly characterized, particularly for boys. Furthermore, another key puberty trait, the pubertal height growth spurt, is less well characterized genetically, but reflects influences from pubertal timing, height growth potential, and body mass, and deeper investigation may reveal novel insights into the links between puberty and health outcomes. During the mentored K99 phase of this proposal, I will use a machine learning approach to choose the best variants across the genome that predict pubertal timing to build optimized polygenic scores (Aim 1a). These male and female-specific polygenic scores will then be tested for association across hundreds of clinical outcomes in biobanks composed of electronic health records (EHR) in tens of thousands of children and adults (Aim 1b). Subsequently, in the independent R00 phase, I will use causal inference analyses to understand the causal impact of genetically determined pubertal timing on identified health outcomes (Aim 1c). Meanwhile, I will combine what I have learned during Aim 1 with my previous expertise to lead a genome-wide association study of the pubertal height growth spurt in the Early Growth Genetics (EGG) consortium, combining longitudinal data from ~35,000 children across multiple cohorts, followed by trans-ethnic fine-mapping (Aim 2a). Finally, I will apply the pipeline developed in Aim 1 to derive PGS for pubertal growth and determine clinically relevant health outcomes linked to differences in pubertal growth trajectories (Aims 2b-d). In this Pathway to Independence proposal, I will complete training in computational and biomedical informatics techniques to capitalize on large-scale data resources, including linked genetic and EHR data from medical and population-based biobanks and longitudinal adolescent cohorts in the EGG consortium. My mentorship committee is composed of a team of world-renowned experts in genomics, informatics, and computational approaches, who have a strong track record in transitioning postdoctoral fellows into independent researchers. Combining my previous expertise with the proposed research and training objectives, together with a strong mentorship team, the securing of EGG leadership in this phenotypic area, and career development activities, I will be uniquely poised to achieve my goal of transitioning to an independent researcher with the skills needed to advance our understanding of the genetic underpinnings of pubertal development and its linked adult outcomes.

我的长期目标是建立在我现有的跟踪记录，了解遗传机制， 影响青春期发育时间的差异以及它们如何影响相关的不良健康 结果。青春期是一个关键的青少年发展里程碑，与以后的生活健康密切相关 结果，如心脏代谢健康不良，2型糖尿病，癌症和骨质疏松症。数百名 已知基因组中的遗传变异会影响青春期的时间（根据月经初潮年龄评估， 女孩和男孩的声音中断年龄），但这种遗传变异对健康结果的性别特异性影响， 青春期和成年期的特征仍然不明确，尤其是男孩。此外，另一个关键 青春期特征，即青春期身高生长突增，在遗传学上不太清楚，但反映了 青春期的时间，身高增长潜力和体重，更深入的研究可能会揭示新的见解 青春期和健康结果之间的联系。在本建议书的辅导K99阶段，我将使用 一种机器学习方法来选择整个基因组中预测青春期时间的最佳变体， 构建优化的多基因评分（目标1a）。然后将这些男性和女性特异性多基因评分 在由电子健康记录组成的生物库中测试数百种临床结果之间的关联 (EHR)成千上万的儿童和成人（目标1b）。随后，在独立R 00阶段，我将 使用因果推理分析，以了解基因决定的青春期时间对 确定的健康结果（目标1c）。同时，我将把我在目标1中学到的联合收割机与我的 以前的专业知识，领导一项全基因组关联研究的青春期身高生长突增在早期 生长遗传学（EGG）联盟，结合来自多个国家约35，000名儿童的纵向数据， 队列，然后进行跨种族精细绘图（目标2a）。最后，我将把目标1中开发的管道应用于 得出青春期生长的PGS，并确定与以下差异相关的临床相关健康结果： 青春期生长轨迹（目标2b-d）。在这个独立之路的建议，我将完成培训， 计算和生物医学信息学技术，以利用大规模的数据资源，包括 来自医学和基于人口的生物库以及纵向青少年队列的关联遗传和EHR数据 在EGG联盟。我的导师委员会由一群世界知名的专家组成， 基因组学，信息学和计算方法，谁有一个强大的记录，在过渡 博士后研究员转变为独立研究人员。结合我以前的专业知识和提议的 研究和培训目标，加上强大的导师团队，确保EGG的领导地位， 这个表型领域，和职业发展活动，我将独特地准备实现我的目标， 过渡到一个独立的研究人员与所需的技能，以促进我们对遗传的理解， 青春期发育的基础及其与成人相关的结果。