Abstract
BACKGROUND: Genome-wide association studies (GWAS) have identified >50 single nucleotide polymorphisms (SNP) in association with estimated glomerular filtration rate (eGFR) and chronic kidney disease (CKD) but little is known about whether the combination of these SNPs may aid in prediction of future incidence of CKD in the population. METHODS: We included 2301 participants with baseline eGFR ≥60 mL/min per 1.73 m(2) from the Malmö Diet and Cancer Study-Cardiovascular Cohort. The eGFR was estimated during baseline (1991-1996) and after a mean follow-up of 16.6 years using the CKD-Epidemiology Collaboration 2009 creatinine equation. We combined 53 SNPs into a genetic risk score weighted by the effect size (wGRS(CKD)), and examined its association with incidence of CKD stage 3A (eGFR ≤60 mL/min per 1.73 m(2)). RESULTS: At follow-up, 453 study participants were defined as having CKD stage 3A. We observed a strong association between wGRS(CKD) and eGFR at baseline (P = 6.5 × 10(-8)) and at the follow-up reexamination (P = 5.0 × 10(-10)). The odds ratio (OR) for incidence of CKD stage 3A was 1.25 per 1 SD increment in the wGRS(CKD) (95% confidence interval [CI]: 1.12-1.39) adjusting for potential confounders (sex, age, body mass index [BMI], baseline eGFR, fasting glucose, systolic blood pressure (SBP), antihypertensive treatment, smoking, follow-up time). Adding wGRS(CKD) on the top of traditional risk factors did not improve the C-statistics (P = 0.12), but the Net Reclassification-Improvement-Index was significantly improved (cNRI = 21.3%; 95% CI: 21.2-21.4; P < 0.0001). CONCLUSION: wGRS(CKD) was associated with a 25% increased incidence of CKD per 1 SD increment. Although the wGRS(CKD) did not improve the prediction model beyond clinical risk factors per se, the information of genetic predisposition may aid in reclassification of individuals into correct risk direction.