Large-Scale Proteomics Improve Prediction of CKD in the General Population without Diabetes

Background: To develop a protein risk score (PRS) for predicting chronic kidney disease (CKD) and compare its predictive capability with a validated clinical risk model (CKD Prediction Consortium [CKD-PC]) and CKD genetic risk score (GRS) in the general population without diabetes. Methods: The development cohort included 36,307 participants from England area in the UK biobank. Participants in the development cohort were randomly divided into a training set and a testing set in a 7:3 ratio. The validation cohort included 4,813 participants from Scotland and Wales area in the UK biobank. Results: In the training set, a PRS for CKD risk was constructed using 86 out of 2,911 proteins. In the testing set, the CKD PRS was significantly positively associated with incident CKD (per SD increment, HR, 1.88; 95%CI: 1.67, 2.12). The C-index of the CKD PRS in predicting CKD risk was 0.838 (95%CI: 0.814-0.861), which was significantly better than that of CKD GRS (C-index,0.749; 95%CI, 0.721-0.777). Adding CKD PRS to CKD-PC risk factors significantly increased the C-index (from 0.825 to 0.853; difference,0.029; 95%CI, 0.018-0.040), the continuous 10-year net reclassification (0.162; 95%CI, 0.074-0.259) and integrated discrimination index (0.009; 95%CI, 0.001-0.026). The C-index for the alternative CKD PRS, compromising only the top 5 proteins (CD59, COL6A3, HRC, ITGB2, and KIM-1), was 0.810 (95%CI: 0.785-0.836), contributing most of the prediction power of original CKD PRS. These results were verified in the validation cohort. Conclusion: The CKD PRS was a potent predictor for CKD risk in the general population without diabetes. When incorporated into a validated clinical risk model, the CKD PRS significantly improved CKD risk discrimination and reclassification. Funding: Government Support – Non-U.S.Table 1. The chronic kidney disease (CKD) risk prediction performance of protein risk score for CKD risk in the testing set of the development cohort and validation cohort. CKD-PC risk factors represent those variables included in the CKD-PC model, including age, sex, race, eGFR, history of cardiovascular disease, never smoking, hypertension, body mass index, and albuminuria