All ETDs from UAB

Advisory Committee Chair

Marguerite R Irvin

Advisory Committee Members

William Geisler

Bertha Hidalgo

Nita A Limdi

Hermant K Tiwari

Document Type


Date of Award


Degree Name by School

Doctor of Philosophy (PhD) School of Public Health


Kidney disease is the tenth-leading cause of death in the United States (US). There are significant racial disparities within kidney disease: African Americans (AAs) have the highest rates of CKD and carry a four-fold higher risk of developing end-stage renal disease (ESRD). They are also less likely to undergo kidney transplants, and among those who do, are more likely to experience graft rejection. Additionally, until 2021, kidney function equations were shown to underestimate the severity of kidney disease in AA due to the use of race coefficients. Among all populations, genetic and epigenetic factors contribute to kidney disease. However, AAs are underrepresented in these studies, which is likely to exacerbate existing disparities. For example, polygenic risk scores (PRS) are being developed to predict kidney traits but are heavily Eurocentric in their curation. Due to differences in allele frequencies and linkage disequilibrium, these PRS demonstrate diminished accuracy in non-European and admixed populations. Similarly, methylation risk scores (MRS), which have the potential to capture biological implications of environmental exposures, are underutilized in AAs and kidney disease overall. Measures to improve precision medicine must have an equity-informed approach. The goal of this dissertation was to optimize PRS and MRS for CKD, considering AA from the outset. We first showed that a PRS using exclusively African ancestry genomic data outperformed European-ancestry derived PRS, but not multi-ancestry PRS. iii We also showed that risk estimates were more precise when using the race-free estimators of kidney function. Next, we showed that a MRS was associated with CKD in both AA and non-AA populations. Finally, we evaluated the capacity of these scores to predict incident kidney outcomes, including ESRD, in comparison to and in conjunction with the gold-standard clinical risk score. Findings demonstrate that 1) including AAs at the development stage of PRS/MRS improve risk prediction and 2) PRS/MRS can further refine risk stratification when integrated with clinical algorithms

Available for download on Monday, September 01, 2025

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