High-Resolution Melting Curve Analysis for High-Throughput Genotyping of NOD2/CARD15 Mutations and Distribution of These Mutations in Slovenian Inflammatory Bowel Diseases Patients

Inflammatory bowel diseases (IBD) are usually classified into Crohn's disease (CD) and ulcerative colitis (UC). NOD2/CARD15 was the first identified CD-susceptibility gene and was confirmed as the most potent disease gene in CD pathogenesis. Three NOD2/CARD15 variants, namely two missense polymorphisms R702W (rs2066844) and G908R (rs2066845), and a frame shift polymorphism L1007fs (rs2066847), were associated with CD in Caucasian populations. High resolution melting analysis (HRMA) with saturation LCGreen dyes was previously reported as a simple, inexpensive, accurate and sensitive method for genotyping and/or scanning of rare variants. For this reasons we used qPCR-HRMA for genotyping NOD2/CARD15 variants in 588 Slovenian IBD patients and 256 healthy controls. PCR-RFLP was used as a reference method for genotyping of clinical samples. The optimization of an HRM experiment required careful design and adjustment of main parameters, such as primer concentration, MgCl(2) concentration, probe design and template DNA concentration. Different HRMA approaches were tested and used to develop a reliable and low-cost SNP genotyping assays for polymorphisms in NOD2/CARD15 gene. Direct HRMA was the fastest and cheapest HRMA approach for L1007fs and R702W polymorphisms, yet for G908R polymorphism sufficient reliability was achieved after introduction of unlabeled probe. In association analysis, we found statistically significant association of L1007fs (p = 0.001, OR = 3.011, CI95%=1.494–6.071) and G908R (p = 2.62 × 10(-4), OR = 14.117, CI95% = 1.884–105.799) polymorphisms with CD patients. At least one of NOD2/CARD15 polymorphisms was found in 78/354 (22.03%) in CD patients, 25/197 (12.69%) in UC patients and in 26/256 (10.15%) in healthy controls. We have successfully implemented NOD2/CARD15 HRMA assays, which may contribute to the development of genetic profiles for risk prediction of developing CD and for differential diagnosis of CD vs. UC.