| Title: | A genetic and clinical risk factor algorithm to aid in identifying new cases of chronic kidney disease from the general population |
| Journal: | Frontiers in Genetics |
| Published: | 9 Jul 2026 |
| DOI: | https://doi.org/10.3389/fgene.2026.1799312 |
| URL: | https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2026.1799312/pdf |
Publication 20332
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Abstract
The purpose of this study is to develop a genetic test to aid in diagnosing chronic kidney disease (CKD). One challenge in treating CKD is that 80%-90% of people with it are undiagnosed and thus do not access healthcare promptly. The problem arises because early-stage CKD has no overt symptoms, and the current policy is to perform diagnostic tests only when accompanied by risk factors such as old age, hypertension, and diabetes. This study describes the development of the RICK (RIsk for Chronic Kidney disease) algorithm that employs a polygenic risk score for CKD plus clinical risk factors to identify people at risk. In data from the United Kingdom biobank, those in the top decile of RICK have a ten-fold increased risk of CKD, and approximately 49% of all those with CKD are included in this decile. Furthermore, targeted creatinine testing for those in the highest RICK decile would potentially increase the number of individuals diagnosed with CKD by 7.4%. However, the RICK algorithm adds little value for detecting CKD defined by elevated uACR (albuminuria). Using RICK to selectively test those in the general population with highest risk may help in the early identification of CKD and facilitate early access to renal healthcare. The effectiveness and cost-effectiveness of such testing require further study.</p>
3 Authors
- Graham Rodwell
- John P. A. Ioannidis
- Stuart K. Kim
1 Application
| Application ID | Title |
|---|---|
| 17847 | GWAS for risk for sports injuries |
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