BackgroundSingle nucleotide polymorphisms (SNPs) of interleukin-28B (IL28B) have received considerable interest for their association with sustained virological response (SVR) when treating patients of genotype-1 hepatitis C virus (GT1-HCV) chronic infection with pegylated interferon and ribavirin (PegIFN/RBV). This study was to investigate the predictive power of IL28B SNPs for on-treatment responses and SVR in treatment-naïve patients with GT1-HCV chronic infection.Methodology/Principal FindingsWe analyzed ten SNPs of IL28B in 191 treatment-naïve patients with GT1-HCV chronic infection who received PegIFN/RBV. In these patients, rapid virological response (RVR), early virological response (EVR) and SVR were achieved in 69.6%, 95.8% and 68.6% of the patients, respectively. Multivariate analysis (odds ratio; 95% confidence interval; P value) indicated age (0.96; 0.93–0.99; 0.012), low baseline viral load (4.65; 2.23–9.66; <0.001) and CC genotype of rs12979860 (7.74; 2.55–23.53; <0.001) but no other SNPs were independent predictors for SVR. In addition, none of the ten SNPs examined were associated with baseline viral load and stages of liver fibrosis. Regarding RVR, low baseline viral load (2.83; 1.40–5.73; 0.004) and CC genotype of rs12979860 (10.52; 3.45–32.04; <0.001) were two critical predictors. As for EVR, only CC genotype of rs12979860 (36.21; 6.68–196.38; <0.001) was the predictor. Similarly, for end of treatment response (ETR), CC genotype of rs12979860 (15.42; 4.62–51.18; <0.001) was the only predictor. For patients with RVR, only low baseline viral load (3.90; 1.57–9.68; 0.003) could predict the SVR. For patients without RVR, only rs12979860 (4.60; 1.13–18.65; 0.033) was the predictor for SVR.Conclusions/Significancers12979860 is the critical predictor for RVR, EVR, ETR and SVR in treatment-naïve patients of GT1-HCV chronic infection. Furthermore, this SNP is the only predictor for SVR in patients without RVR. These results have provided evidence that rs12979860 is the ideal IL28B SNP for genetic testing in treating patients of GT1-HCV chronic infection.

BackgroundGraves' disease (GD) is the leading cause of hyperthyroidism and thyroid eye disease inherited as a complex trait. Although geoepidemiology studies showed relatively higher prevalence of GD in Asians than in Caucasians, previous genetic studies were contradictory concerning whether and/or which human leukocyte antigen (HLA) alleles are associated with GD in Asians.Methodology/Principal FindingsWe conducted a case-control association study (499 unrelated GD cases and 504 controls) and a replication in an independent family sample (419 GD individuals and their 282 relatives in 165 families). To minimize genetic and phenotypic heterogeneity, we included only ethnic Chinese Han population in Taiwan and excluded subjects with hypothyroidism. We performed direct and comprehensive genotyping of six classical HLA loci (HLA-A, -B, -C, -DPB1, -DQB1 and -DRB1) to 4-digit resolution. Combining the data of two sample populations, we found that B*46:01 (odds ratio under dominant model [OR]  = 1.33, Bonferroni corrected combined P [PBc]  = 1.17×10−2), DPB1*05:01 (OR  = 2.34, PBc = 2.58×10−10), DQB1*03:02 (OR  = 0.62, PBc  = 1.97×10−2), DRB1*15:01 (OR  = 1.68, PBc = 1.22×10−2) and DRB1*16:02 (OR  = 2.63, PBc  = 1.46×10−5) were associated with GD. HLA-DPB1*05:01 is the major gene of GD in our population and singly accounts for 48.4% of population-attributable risk.Conclusions/SignificanceThese GD-associated alleles we identified in ethnic Chinese Hans, and those identified in other Asian studies, are totally distinct from the known associated alleles in Caucasians. Identification of population-specific association alleles is the critical first step for individualized medicine. Furthermore, comparison between different susceptibility/protective alleles across populations could facilitate generation of novel hypothesis about GD pathophysiology and indicate a new direction for future investigation.

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Haplotype-based approaches may have greater power than single-locus analyses when the SNPs are in strong linkage disequilibrium with the risk locus. To overcome potential complexities owing to large numbers of haplotypes in genetic studies, we evaluated two data mining approaches, multifactor dimensionality reduction (MDR) and classification and regression tree (CART), with the concept of haplotypes considering their haplotype uncertainty to detect haplotype-haplotype (HH) interactions. In evaluation of performance for detecting HH interactions, MDR had higher power than CART, but MDR gave a slightly higher type I error. Additionally, we performed an HH interaction analysis with a publicly available dataset of Parkinson's disease and confirmed previous findings that the RET proto-oncogene is associated with the disease. In this study, we showed that using HH interaction analysis is possible to assist researchers in gaining more insight into identifying genetic risk factors for complex diseases.