Identification of novel genetic susceptibility loci for calcium-containing kidney stone disease by genome-wide association study and polygenic risk score in a Taiwanese population.

Approximately 80% of kidney stone diseases contain calcium. Inherited genetic factors are among the variables that influence the development of calcium-containing kidney stone diseases (CKSD). Previous genome-wide association studies (GWAS) on stone diseases have been reported worldwide; however, these are not focused on calcium-containing stones. We conducted a GWAS to identify germline genetic polymorphisms associated with CKSD in a Medical Center in Taiwan; hence, this study was based primarily on a hospital-based database. CKSD was diagnosed using the chart records. Patients infected with urea-splitting-microorganisms and those with at least two urinary pH value below 5.5 were excluded. None of the patients had cystic stones based on stone analysis. Those over 40 years of age with no history of CKSD and no microscopic hematuria on urinalysis were considered as controls. The DNA isolated from the blood of 14,934 patients (63.7% male and 36.3% female) with CKSD and 29,868 controls (10,830 men and 19,038 women) at a medical center was genotyped for approximately 714,457 single nucleotide polymorphisms (SNPs) with minor allele frequency of ≥ 0.05. We used PLINK 1.9 to calculate the polygenic risk score (PRS) to investigate the association between CKSD and controls. The accuracy of the PRS was verified by dividing it into the training and testing groups. The statistical analyses were calculated with the area under the curve (AUC) using IBM SPSS version 22. We identified 432 susceptibility loci that reached a genome-wide threshold of P < 1.0 × 10^- 5. A total of 132 SNPs reached a threshold of P < 5 × 10^- 8 using a stricter definition of significance on chromosomes 4, 13, 16, 17, and 18. At the top locus of our study, SNPs in DGKH, PDILT, BCAS3, and ABCG2 have been previously reported. RN7SKP27, HDAC4, PCDH15, AP003068.2, and NFATC1 were novel findings in this study. PRS was adjusted for sex and age, resulting in an AUC of 0.65. The number of patients in the top quartile of PRS was 1.39 folds in the risk of CKSD than patients in the bottom quartile. Our data identified the significance of GWAS for patients with CKSD in a hospital-based study. The PRS also had a high AUC for discriminating patients with CKSD from controls. A total of 132 SNP loci of SNPs significantly associated with the development of CKSD. This first survey, which focused on patients with CKSD, will provide novel insights specific to CKSD and its potential clinical biomarkers.