Using Large Genomic Biobanks to Generate Insights into Genetic Kidney Disease
Issued Date
2025-01-01
Resource Type
ISSN
02709295
eISSN
15584488
Scopus ID
2-s2.0-105010329605
Journal Title
Seminars in Nephrology
Rights Holder(s)
SCOPUS
Bibliographic Citation
Seminars in Nephrology (2025)
Suggested Citation
Chang A.R., Wongboonsin J., Mallett A.J., Morales A., Retterer K., Mirshahi T., Sayer J.A. Using Large Genomic Biobanks to Generate Insights into Genetic Kidney Disease. Seminars in Nephrology (2025). doi:10.1016/j.semnephrol.2025.151651 Retrieved from: https://repository.li.mahidol.ac.th/handle/123456789/111286
Title
Using Large Genomic Biobanks to Generate Insights into Genetic Kidney Disease
Author's Affiliation
The University of Queensland
Brigham and Women's Hospital
Newcastle University
Boston Children's Hospital
James Cook University
University of Newcastle upon Tyne, Faculty of Medical Sciences
Siriraj Hospital
The Newcastle Upon Tyne Hospitals NHS Foundation Trust
Townsville University Hospital
Geisinger
Bumrungrad International Hospital
Brigham and Women's Hospital
Newcastle University
Boston Children's Hospital
James Cook University
University of Newcastle upon Tyne, Faculty of Medical Sciences
Siriraj Hospital
The Newcastle Upon Tyne Hospitals NHS Foundation Trust
Townsville University Hospital
Geisinger
Bumrungrad International Hospital
Corresponding Author(s)
Other Contributor(s)
Abstract
Chronic kidney disease (CKD) affects approximately 9% of the global population, leading to increased risks of end-stage kidney disease (ESKD), cardiovascular disease (CVD), and mortality. Patients with CKD are a huge burden on health care resources globally. CKD is a complex condition influenced by a combination of genetic, environmental, and traditional risk factors. Family studies have suggested heritability rates for CKD ranging from 30% to 75%, and large genomic biobank studies have proven essential in identifying genes with substantial effects on CKD risk and in capturing cumulative genetic risk through polygenic risk scores. These biobanks are crucial for discovering new genes associated with kidney health and disease, and their growing size enhances the power to detect novel genetic associations. Integrating multi-omics technologies such as transcriptomics, metabolomics, and proteomics further enriches our understanding of CKD, while advanced computational tools continue to expand our insights into genetic data. Polygenic risk scores, derived from hundreds of genetic variants with small effect sizes, can help identify individuals at high risk of CKD. Genomic biobanks offer valuable opportunities for early identification and personalized treatment of monogenic kidney disorders, such as autosomal dominant polycystic kidney disease and Alport syndrome. These biobanks help fill knowledge gaps, particularly in individuals with milder or asymptomatic presentations who are often underrepresented in traditional studies. Expanding genomic biobank efforts globally, especially in diverse populations, is vital to enhancing our understanding of the genetic underpinnings of kidney disease. This review highlights the significant contributions of genomic biobanks to advancing our comprehension of the genetics of CKD. Semin Nephrol 36:x-xx © 20XX Elsevier Inc. All rights reserved.