Kidney Week

Abstract: TH-PO0105

Genetic Landscape of Kidney Failure in a Korean Transplant Cohort: Genome-Wide Association and Multipolygenic Risk Score Analyses

Session Information

• Integrative Genomics and Multi-Omics in Noncystic Genetic Kidney Disease
  October 22, 2026 | Location: Exhibit Hall A, Convention Center
  Abstract Time: 10:00 AM - 12:00 PM

Category: Genetic Diseases of the Kidneys

• 1202 Genetic Diseases of the Kidneys: Non-Cystic (Complex and Non-Cystic Monogenic)

Authors

• Na, Omi, Division of Nephrology, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Korea (the Republic of)

Omi Na, MD

• Koh, Hee Byung, Division of Nephrology, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Korea (the Republic of)

Hee Byung Koh, MD

• Jeon, Hee Jung, Department of Internal Medicine, Kangdong Sacred Heart Hospital, Hallym University College of Medicine, Seoul, Korea (the Republic of)

Hee Jung Jeon, MD, PhD

• Jang, Hye-Mi, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea (the Republic of)

Hye-Mi Jang

• Park, Yi Seul, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea (the Republic of)

Yi Seul Park

• Kim, Sung Min, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea (the Republic of)

Sung Min Kim

• Kim, Bong-Jo, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea (the Republic of)

Bong-Jo Kim, PhD

• Kim, Hyung Woo, Division of Nephrology, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Korea (the Republic of)

Hyung Woo Kim, MD

• Jeong, Jong Cheol, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Korea (the Republic of)

Jong Cheol Jeong, MD, PhD

• Park, Seokwoo, Department of Internal Medicine, Seoul National University Bundang Hospital, Seongnam-si, Korea (the Republic of)

Seokwoo Park, MD, PhD

• Park, Borae G., Korea Organ Donation Agency Laboratory, Seoul, Korea (the Republic of)

Borae G. Park, MD, PhD

• Kim, Myoung soo, Department of Surgery, Yonsei University College of Medicine, Severance Hospital, Seoul, Korea (the Republic of)

Myoung soo Kim, MD, PhD

• Park, Hyun-Young, National Institute of Health, Cheongju-si, Korea (the Republic of)

Hyun-Young Park, MD, PhD

• Kim, Young Jin, Division of Genome Science, Department of Precision Medicine, National Institute of Health, Cheongju-si, Korea (the Republic of)

Young Jin Kim, PhD

• Yang, Jaeseok, Division of Nephrology, Department of Internal Medicine, Yonsei University College of Medicine, Severance Hospital, Seoul, Korea (the Republic of)

Jaeseok Yang, MD, PhD

Background

Kidney failure is the final stage of chronic kidney disease (CKD), but its genetic architecture remains incompletely defined compared to CKD. While prior studies focused on kidney function traits, the genetic determinants of kidney failure are poorly understood. This study aimed to identify genetic loci and evaluate the predictability of polygenic risk score (PRS) on kidney failure and its subtypes.

Methods

We performed a large-scale genome-wide association study (GWAS) using a dataset of 2,355 kidney failure patients across three subtypes defined by primary disease from the KOTRY cohort, along with 152,131 controls from the KoGES cohort. PRSs for type 2 diabetes, hypertension, estimated glomerular filtration rate (eGFR), and CKD were calculated, and a multi-PRS model was derived.

Results

The GWAS identified multiple kidney failure-associated loci, including HLA-DRB1 for all kidney failure and glomerulonephritis as the primary disease, and COL24A1 for hypertensive kidney failure at genome-wide significance (P<5×10^-8), implicating distinct immune and hypertension-related pathways in kidney failure pathogenesis. PRS analysis revealed that genetically distinct components of type 2 diabetes, hypertension, CKD, and eGFR were significantly linked to kidney failure risk across subtypes (OR=1.1–2.5). A combined multi-PRS model demonstrated superior predictive performance (OR=1.5–2.5) (Figure 1A). Comparison with CKD cohorts, predominantly influenced by eGFR-related genetics, uncovered unique kidney failure-specific genetic signatures, highlighting kidney failure as a genetically heterogeneous and multifactorial disease beyond CKD (Figure 1B).

Conclusion

This study identified novel subtype-specific loci and demonstrated that multi-PRS models substantially improve kidney failure risk prediction beyond clinical factors.

Funding

• Government Support – Non-U.S.