One of the biggest challenges in treating chronic kidney disease (CKD) is that 80 to 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.

SKK is CEO of AxGen, Inc.

No funding was used.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

The study used ONLY openly available human data that were originally located at UK Biobank (https://www.ukbiobank.ac.uk/).

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

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I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

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Data used in the published polygenic risk scores described in this paper are available at https://www.pgscatalog.org/ using the PGS codes shown in Supplemental Table 1. Coefficients for the RICK algorithm are shown in Supplemental Table 2.