Leveraging Proteomics to Understand the Link Between Chronic Kidney Disease and Cognitive Impairment

项目总结 这是林赛·米勒博士在约阿希姆九世的指导下首次提交的K01申请 加州大学圣地亚哥分校医学博士。这项提案将使米勒博士成为 独立的研究人员，将利用大规模蛋白质组学来了解这种关联和预测性 阿尔茨海默病及其相关临床症状--认知障碍的蛋白质组能力 患有慢性肾脏疾病(CKD)的老年人的痴呆(ADRD)。 候选人：米勒博士通过这个计划的培训目标和职业目标包括：1)成为 老年人CKD和CI方面的专家2)发展应用于蛋白质组学的先进方法的技能 数据，以及3)发展拨款撰写、实验室管理和职业发展方面的技能。米勒医生会 通过指导、课程作业和研讨会来实现这些目标。她已经组建了一支 她的多学科导师团队由她的主要导师，肾脏病领域公认的领导者IX博士组成， 和以下共同导师：Marquine博士，神经心理学专家；Scherzer博士， 加州大学旧金山分校肾脏健康研究合作的生物统计学。 研究：CI是ADRD的临床症状，轻度CI通常是ADRD发生的前兆 阿德勒。CI在CKD患者中很常见；然而，CI接受的研究远远少于 心血管疾病和终末期肾病等并发症。研究主要使用估计的肾小球 滤过率(EGFR)和尿白蛋白/肌酐比值(ACR)评价慢性肾功能不全与肾功能损害的关系 线人。然而，在最近的工作中，申请人证明了一组反映肾小管健康的标志物 在老年人中与CI相关，独立于EGFR和ACR，表明这些肾脏标志物 健康并没有完全解释它与CI的联系。尽管如此，这种关系可能比可能发生的事情更复杂 用几个目标生物标记物进行鉴定。因此，米勒博士建议利用大规模蛋白质组数据来 理解CKD和认知之间的多因素关系，长期目标是这些 洞察力可能会导致新的方法和治疗方法来预防或改善脑梗塞的发展 CKD人群。下一步，虽然大规模蛋白质组学最适合于了解生物途径 在慢性肾脏病和脑梗塞之间，在临床实践中利用它来识别罹患慢性肾脏病风险最高的个体是不可行的。 线人。因此，需要可变选择方法来识别和验证将允许 认知功能障碍的临床预测。在目标1中，她将确定蛋白质簇和生物途径 与CI关联。这一目标将在3419名患有慢性肾功能不全的CKD成人中进行 队列研究(CRIC)。在目标2中，她将测试不同的惩罚变量选择方法，以确定 在同一CRIC队列中预测CI的蛋白质。在目标3中，米勒博士将确定簇和蛋白质是否 在心血管健康研究中对1076名患有CKD的老年人进行CRIC外部验证。

PROJECT SUMMARY This is the initial submission of a K01 application by Lindsay Miller Ph.D., under the mentorship of Joachim Ix M.D., at the University of California, San Diego (UCSD). This proposal will establish Dr. Miller as an independent investigator and will leverage large-scale proteomics to understand the association and predictive ability of the proteome with cognitive impairment (CI), a clinical symptom of Alzheimer’s Disease and Related Dementias (ADRD) in older adults with chronic kidney disease (CKD). Candidate: Dr. Miller’s training objectives and career goals through this proposal include: 1) to become an expert in CKD and CI in older adults 2) to develop skills in advanced methods for the application to proteomic data, and 3) to develop skills in grant writing, lab management and career development. Dr. Miller will accomplish these objectives through mentorship, coursework, and workshops. She has assembled a multidisciplinary mentorship team comprised of her primary mentor, Dr. Ix, an established leader in nephrology, and the following co-mentors: Dr. Marquine, an expert in neuropsychology; Dr. Scherzer, the Director of Biostatistics at the Kidney Health Research Collaboration at the University of California, San Francisco. Research: CI is a clinical symptom of ADRD, with mild CI being often a precursor to the development of ADRD. CI is common among patients with CKD; however, CI has received much less investigation than complications such as CVD and end-stage kidney disease. Studies have primarily used estimated glomerular filtration rate (eGFR) and urine albumin to creatinine ratio (ACR) to evaluate the relationship between CKD and CI. However, in recent work the applicant demonstrated that a panel of markers reflecting kidney tubule health was associated with CI independent of eGFR and ACR in older adults, indicating that these markers of kidney health do not fully explain its link with CI. Still, the relationship is likely more complex that what can be identified using a few targeted biomarkers. Thus, Dr. Miller proposes to utilize large-scale proteomic data to understand the multifactorial relationship between CKD and cognition with the long-term objective that these insights might lead to novel approaches and therapies to prevent or ameliorate the development of CI in the CKD population. Next, while large-scale proteomics is optimally suited to understand biological pathways between CKD and CI, it will not be feasible to utilize in clinical practice to identify individuals at highest risk for CI. As such, variable selection methods are needed to identify and validate subsets of proteins that will allow clinical prediction of cognitive impairment. In aim 1, she will identify protein clusters and biological pathways that associate with CI. This aim will be conducted in 3419 adults with CKD in the Chronic Renal Insufficiency Cohort Study (CRIC). In aim 2 she will test different penalized variable selection methods to identify a panel of proteins that predict CI in the same CRIC cohort. In aim 3, Dr. Miller will determine if the clusters and proteins identified in CRIC externally validate among 1076 older adults with CKD in the Cardiovascular Health Study.