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

项目摘要 这是林赛米勒博士首次提交的K 01申请，在约阿希姆九世的指导下 医学博士，在加州大学圣地亚哥分校（UCSD）。这份提案将使米勒博士成为 独立调查员，并将利用大规模蛋白质组学来了解关联和预测 蛋白质组与认知障碍（CI），阿尔茨海默病的临床症状和相关的能力 老年慢性肾病（CKD）患者的痴呆（ADRD）。 候选人：米勒博士的培训目标和职业目标，通过这一建议包括：1）成为一个 老年人CKD和CI专家2）培养应用于蛋白质组学的先进方法的技能 数据，和3）发展在拨款写作，实验室管理和职业发展的技能。米勒医生会 通过指导，课程和研讨会来实现这些目标。她已经组装了一个 多学科导师团队由她的主要导师，博士伊克斯，在肾脏病学的既定领导者， 和以下共同导师：Marquine博士，神经心理学专家; Scherzer博士， 加州大学旧金山弗朗西斯科肾脏健康研究合作组织的生物统计学。 研究：CI是ADRD的一种临床症状，轻度CI通常是ADRD发展的前兆。 ADRD。CI在CKD患者中很常见;然而，CI接受的研究远少于 并发症，如CVD和终末期肾病。研究主要使用估计的肾小球 滤过率（eGFR）和尿白蛋白与肌酐比值（ACR），以评估CKD与 CI.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，与eGFR和ACR无关，表明这些肾脏标志物 健康并不能完全解释它与CI之间联系。尽管如此，这种关系可能比 使用一些有针对性的生物标志物进行鉴定。因此，米勒博士建议利用大规模的蛋白质组学数据， 了解CKD和认知之间的多因素关系，长期目标是， 这些见解可能会导致新的方法和疗法，以预防或改善CI的发展， CKD人群。其次，虽然大规模蛋白质组学最适合于了解生物途径， 在CKD和CI之间，在临床实践中利用它来识别具有最高风险的个体是不可行的。 CI.因此，需要可变选择方法来鉴定和验证蛋白质的子集， 认知障碍的临床预测。在aim 1中，她将识别蛋白质簇和生物途径 与CI相关的信息。本研究将在3419例慢性肾功能不全的CKD成人患者中进行 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，以确定一组 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 CRIC在心血管健康研究的1076名CKD老年人中进行了外部验证。

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.