Phosphatidylcholine and cholesterol ester biomarkers of type 2 diabetes and preventive treatment effects

项目摘要/摘要 背景：2型糖尿病(T2D)发病率和患病率的增加可以通过以下方法来缓解 在高危人群中，通过行为改变或药物治疗成功预防。 确定特定个人患糖尿病的风险，以及哪种预防性治疗将最有效， 然而，这仍然是一个临床难题。代谢物生物标志物代表了一种解决这些问题的新方法 临床挑战，也可能揭示疾病发展的机制。这五年的指导生涯 开发提案详细说明了生物标记物发现和临床方面的翻译研究培训计划 研究实施，目的是确定糖尿病的代谢物预测因素和预防治疗 效果。应聘者：应聘者是贝思以色列分校最近任命的内分泌学教员 女执事医疗中心的长期目标是成为一名研究新陈代谢的内科科学家 参与T2D发展和进展的通路。她在分子方面有两年半的经验 大型人体研究中的概况分析和概述的建议建立在这一背景下，以提供 专业知识包括预测建模、遗传学和临床研究设计。培训：申请人的 发展将通过实验室培训、教学课程(包括持续的公共卫生小时)、 和科学会议。这位候选人的导师是分子图谱方面公认的领导者， “组学”和心脏代谢性疾病。她的共同导师是T2D遗传学领域的领军人物，她的成员 咨询委员会在非目标T2D方面拥有卓越的指导记录和丰富的专业知识 代谢组学、统计建模和临床试验。研究：最近，申请者确定了独特的 一项大型随机对照试验中与T2D相关的代谢物分布，该试验比较了生活方式的改变和 二甲双胍治疗预防糖调节受损个体的T2D。这些协会， 包括特定的磷脂酰胆碱和胆固醇酯，在调整传统的 临床危险因素提示它们可以作为T2D的预测因子。此外，这些代谢物是 与生活方式或二甲双胍治疗后不同的T2D进展相关，并可能有助于指导 T2D预防决策。申请人提议通过(目标1)创建 评估这些代谢物前瞻性预测能力的代谢物多标记物预测模型 糖尿病的发展，(目标2A)将这些发现与遗传学相结合，以揭示代谢途径 在这些关联下，如果它们导致糖尿病，(目标2B)利用遗传学也完全识别 与T2D相关的新的循环小分子，以及(目标3)进行一项小型前瞻性队列研究 在现实世界的临床环境中，外部验证这些代谢物作为预测生物标记物。这项工作将奠定基础 NIH R01应用于临床试验以评估代谢物的预测效用的基础 糖尿病预防的生物标记物和向研究独立性过渡的候选者。

PROJECT SUMMARY/ABSTRACT Background: The increasing incidence and prevalence of type 2 diabetes (T2D) can be mitigated by successful prevention with behavioral changes or pharmacotherapy in individuals that are at high risk. Identifying a specific individual’s risk for diabetes and which preventive treatment will be most effective, however, remains a clinical dilemma. Metabolite biomarkers represent a novel approach to addressing these clinical challenges and may also reveal mechanisms of disease development. This five-year mentored career development proposal details a translational research training program in biomarker discovery and clinical study implementation with a goal of identifying metabolite predictors of diabetes and preventive treatment effect. Candidate: The applicant is a recently appointed Endocrinology faculty member at Beth Israel Deaconess Medical Center with a long-term goal to become a physician-scientist who investigates metabolic pathways involved in T2D development and progression. She has 2.5 years of experience in molecular profiling in large human studies and the outlined proposal builds on this background to provide new domains of expertise including prediction modeling, genetics, and clinical study design. Training: The applicant’s development will occur through a blend of laboratory training, didactic courses (including an ongoing MPH), and scientific conferences. The candidate’s mentor is a recognized leader in molecular profiling, integrative “omics”, and cardiometabolic diseases. Her co-mentor is a leader in T2D genetics, and the members of her advisory committee have a distinguished mentoring record and vast expertise in T2D, non-targeted metabolomics, statistical modeling, and clinical trials. Research: Recently, the applicant identified unique metabolite profiles associated with T2D in a large, randomized control trial that compared lifestyle changes and metformin therapy for T2D prevention in individuals with impaired glucose regulation. These associations, including specific phosphatidylcholines and cholesterol esters, remained after adjustments for traditional clinical risk factors suggesting they could serve as predictors of T2D. Furthermore, these metabolites were associated with different rates of T2D progression after lifestyle or metformin treatment and may help guide T2D prevention decisions. The applicant proposes to further extend these findings by (Aim 1) creating metabolite multi-marker prediction models to assess the ability of these metabolites to prospectively predict diabetes development, (Aim 2A) integrate these findings with genetics to uncover metabolic pathways that underly these associations and if they cause diabetes, (Aim 2B) leverage genetics to also identify completely novel circulating small molecules associated with T2D, and (Aim 3) conduct a small prospective cohort study to externally validate these metabolites as predictive biomarkers in a real-world clinical setting. This work will lay the foundation for an NIH R01 application for a clinical trial to assess the predictive utility of metabolite biomarkers for diabetes prevention and transition the candidate to research independence.