A genetic and clinical risk factor algorithm to aid in identifying new cases of chronic kidney disease from the general population

Abstract One of the biggest challenges in treating chronic kidney disease (CKD) is that 80 – 90% of people with this disease 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 (e.g. glomerular filtration rate and urinary albumin to creatinine ratio) only when accompanied by risk factors such as old age, hypertension and diabetes. Genetic testing may be useful to identify those most likely to have CKD and who therefore may benefit from screening. This work describes the development of an algorithm termed RICK (for RIsk for Chronic Kidney disease) that employs a polygenic risk score for CKD plus clinical risk factors to identify people at risk. In data from the UK biobank, those in the top decile of RICK have a 4.4-fold increased risk of CKD, and about 34% of all those with CKD are included in this decile. Using RICK to selectively test those in the general population with highest risk may help in early identification of CKD and thereby facilitate early access to renal healthcare. Lay Summary One of the biggest challenges in renal health is that 80 – 90% of people with Chronic Kidney Disease (CKD) 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 (e.g. glomerular filtration rate and urinary albumin to creatinine ratio) only when accompanied by risk factors such as old age, hypertension and diabetes. This work describes the development of an algorithm termed RICK (for RIsk for Chronic Kidney disease) that employs a genetic test for CKD plus clinical risk factors to identify people at risk and who therefore may benefit from screening. Those in the top ten percentile of RICK have a 15-fold increased risk of stage 3 CKD. Diagnostic testing of the top decile would capture about 43% of the undiagnosed stage 3 CKD cases. Thus, using RICK to selectively test those with highest risk could have an immense impact on renal health by facilitating early identification of CKD and thereby enabling access to healthcare.