Abstract: TH-PO1087
Genome-Wide Association Study of eGFR Using Repeated Measurements in the Asian Population
Session Information
- CKD: Epidemiology, Risk Factors, and Other Conditions
November 06, 2025 | Location: Exhibit Hall, Convention Center
Abstract Time: 10:00 AM - 12:00 PM
Category: CKD (Non-Dialysis)
- 2301 CKD (Non-Dialysis): Epidemiology, Risk Factors, and Prevention
Authors
- Lai, Tai-Shuan, National Taiwan University Hospital Department of Internal Medicine, Taipei City, Taiwan
- Tsao, Hsiao-Mei, National Taiwan University Hospital Department of Internal Medicine, Taipei City, Taiwan
Background
Genetic factors play a substantial role in kidney function. Although genome-wide association studies (GWAS) have identified numerous loci associated with estimated glomerular filtration rate (eGFR), most studies relied on a single measurement, limiting the ability to account for individual variability over time. Notably, individuals of Asian ancestry have been underrepresented in existing studies.
Methods
We aimed to identify genetic loci associated with eGFR by using trajectory GWAS, an approach based on linear mixed-effect models, to incorporate repeated measurements of eGFR. The data from the Taiwan Biobank of 25,004 participants with repeated eGFR measurements were utilized. The identified loci were subjected to comprehensive biological function annotation, including analysis of expression quantitative trait loci (eQTL), predictions of deleteriousness, and assessments of epigenetic markers. Results were compared with conventional GWAS using a single measurement.
Results
Six loci associated with eGFR were identified, including four previously reported loci (1q22, 4q21.1, 11p14.1, and 17q21.2) and two novel loci (6p21.32 and 15q24.2). By contrast, conventional GWAS identified only four loci associated with eGFR. Functional annotation implicated several candidate genes, such as MUC1/EFNA1, SHROOM3, HLA-DQB1, MPPED2, NRG4, and PGAP3/FBXL20, in kidney function regulation.
Conclusion
Incorporating repeated eGFR measurements in GWAS provides deeper insights into the genetic determinants of kidney function. This study identifies novel loci and highlights promising candidate genes for further investigation, paving the way for improved understanding and management of CKD.
Figure 1. Study flow diagram.
Figure 2. Manhattan plots of trajectory GWAS