Although the genetic component in the etiology of rheumatoid arthritis (RA) has been consistently suggested, many novel genetic loci remain to uncover. To identify RA risk loci, we performed a genome-wide association study (GWAS) with 100 RA cases and 600 controls using Affymetrix SNP array 5.0. The candidate risk locus (APOM gene) was re-sequenced to discover novel promoter and coding variants in a group of the subjects. Replication was performed with the independent case-control set comprising of 578 RAs and 711 controls. Through GWAS, we identified a novel SNP associated with RA at the APOM gene in the MHC class III region on 6p21.33 (rs805297, odds ratio (OR) = 2.28, P = 5.20 × 10 -7). Three more polymorphisms were identified at the promoter region of the APOM by the re-sequencing. For the replication, we genotyped the four SNP loci in the independent case-control set. The association of rs805297 identified by GWAS was successfully replicated (OR = 1.40, P = 6.65 × 10 -5). The association became more significant in the combined analysis of discovery and replication sets (OR = 1.56, P = 2.73 × 10 -10). The individuals with the rs805297 risk allele (A) at the promoter region showed a significantly lower level of APOM expression compared with those with the protective allele (C) homozygote. In the logistic regressions by the phenotype status, the homozygote risk genotype (A/A) consistently showed higher ORs than the heterozygote one (A/C) for the phenotype-positive RAs. These results indicate that APOM promoter polymorphisms are significantly associated with the susceptibility to RA.
BackgroundThe full extent of chromosomal alterations and their biological implications in early breast carcinogenesis has not been well examined. In this study, we aimed to identify chromosomal alterations associated with poor prognosis in early-stage breast cancers (EBC).MethodsA total of 145 EBCs (stage I and II) were examined in this study. We analyzed copy number alterations in a discovery set of 48 EBCs using oligoarray-comparative genomic hybridization. In addition, the recurrently altered regions (RARs) associated with poor prognosis were validated using an independent set of 97 EBCs.ResultsA total of 23 RARs were defined in the discovery set. Six were commonly detected in both stage I and II groups (> 50%), suggesting their connection with early breast tumorigenesis. There were gains on 1q21.2-q21.3, 8q24.13, 8q24.13-21, 8q24.3, and 8q24.3 and a loss on 8p23.1-p22. Among the 23 RARs, copy number gains on 16p11.2 (NUPR1) and 17q12 (ERBB2) showed a significant association with poor survival (P = 0.0186 and P = 0.0186, respectively). The patients simultaneously positive for both gains had a significantly worse prognosis (P = 0.0001). In the independent replication, the patients who were double-positive for NUPR1-ERBB2 gains also had a significantly poorer prognosis on multivariate analysis (HR = 7.31, 95% CI 2.65-20.15, P = 0.0001).ConclusionsThe simultaneous gain of NUPR1 and ERBB2 can be a significant predictor of poor prognosis in EBC. Our study will help to elucidate the molecular mechanisms underlying early-stage breast cancer tumorigenesis. This study also highlights the potential for using combinations of copy number alterations as prognosis predictors for EBC.
Lung cancer in never-smokers ranks as the seventh most common cause of cancer death worldwide, and the incidence of lung cancer in non-smoking Korean women appears to be steadily increasing. To identify the effect of genetic polymorphisms on lung cancer risk in non-smoking Korean women, we conducted a genome-wide association study of Korean female non-smokers with lung cancer. We analyzed 440,794 genotype data of 285 cases and 1,455 controls, and nineteen SNPs were associated with lung cancer development (P < 0.001). For external validation, nineteen SNPs were replicated in another sample set composed of 293 cases and 495 controls, and only rs10187911 on 2p16.3 was significantly associated with lung cancer development (dominant model, OR of TG or GG, 1.58, P = 0.025). We confirmed this SNP again in another replication set composed of 546 cases and 744 controls (recessive model, OR of GG, 1.32, P = 0.027). OR and P value in combined set were 1.37 and < 0.001 in additive model, 1.51 and < 0.001 in dominant model, and 1.54 and < 0.001 in recessive model. The effect of this SNP was found to be consistent only in adenocarcinoma patients (1.36 and < 0.001 in additive model, 1.49 and < 0.001 in dominant model, and 1.54 and < 0.001 in recessive model). Furthermore, after imputation with HapMap data, we found regional significance near rs10187911, and five SNPs showed P value less than that of rs10187911 (rs12478012, rs4377361, rs13005521, rs12475464, and rs7564130). Therefore, we concluded that a region on chromosome 2 is significantly associated with lung cancer risk in Korean non-smoking women.
Together with single nucleotide polymorphism (SNP), copy number variations (CNV) are recognized to be the major component of human genetic diversity and used as a genetic marker in many disease association studies. Affymetrix Genome-wide SNP 5.0 is one of the commonly used SNP array platforms for SNP-GWAS as well as CNV analysis. However, there has been no report that validated the accuracy and reproducibility of CNVs identified by Affymetrix SNP array 5.0. In this study, we compared the characteristics of CNVs from the same set of genomic DNAs detected by three different array platforms; Affymetrix SNP array 5.0, Agilent 2X244K CNV array and NimbleGen 2.1M CNV array. In our analysis, Affymetrix SNP array 5.0 seems to detect CNVs in a reliable manner, which can be applied for association studies. However, for the purpose of defining CNVs in detail, Affymetrix Genome-wide SNP 5.0 might be relatively less ideal than NimbleGen 2.1M CNV array and Agilent 2X244K CNV array, which outperform Affymetrix array for defining the small-sized single copy variants. This result will help researchers to select a suitable array platform for CNV analysis.
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