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

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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.