How genome-wide SNP-SNP interactions relate to nasopharyngeal carcinoma susceptibility

A Large-Scale Genome-Wide Gene-Gene Interaction Study of Lung Cancer Susceptibility in Europeans With a Trans-Ethnic Validation in Asians

INTRODUCTION

Although genome-wide association studies have been conducted to investigate genetic variation of lung tumorigenesis, little is known about gene-gene (G × G) interactions that may influence the risk of non-small cell lung cancer (NSCLC).

METHODS

Leveraging a total of 445,221 European-descent participants from the International Lung Cancer Consortium OncoArray project, Transdisciplinary Research in Cancer of the Lung and UK Biobank, we performed a large-scale genome-wide G × G interaction study on European NSCLC risk by a series of analyses. First, we used BiForce to evaluate and rank more than 58 billion G × G interactions from 340,958 single-nucleotide polymorphisms (SNPs). Then, the top interactions were further tested by demographically adjusted logistic regression models. Finally, we used the selected interactions to build lung cancer screening models of NSCLC, separately, for never and ever smokers.

RESULTS

With the Bonferroni correction, we identified eight statistically significant pairs of SNPs, which predominantly appeared in the 6p21.32 and 5p15.33 regions (e.g., rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.17, p = 6.57 × 10-13; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.17, p = 2.43 × 10-13; rs2858859HLA-DQA1 and rs9275572HLA-DQA2, ORinteraction = 1.15, p = 2.84 × 10-13; rs2853668TERT and rs62329694CLPTM1L, ORinteraction = 0.73, p = 2.70 × 10-13). Notably, even with much genetic heterogeneity across ethnicities, three pairs of SNPs in the 6p21.32 region identified from the European-ancestry population remained significant among an Asian population from the Nanjing Medical University Global Screening Array project (rs521828C6orf10 and rs204999PRRT1, ORinteraction = 1.13, p = 0.008; rs3135369BTNL2 and rs2858859HLA-DQA1, ORinteraction = 1.11, p = 5.23 × 10-4; rs3135369BTNL2 and rs9271300HLA-DQA1, ORinteraction = 0.89, p = 0.006). The interaction-empowered polygenetic risk score that integrated classical polygenetic risk score and G × G information score was remarkable in lung cancer risk stratification.

CONCLUSIONS

Important G × G interactions were identified and enriched in the 5p15.33 and 6p21.32 regions, which may enhance lung cancer screening models.

Associations between ALDH Genetic Variants, Alcohol Consumption, and the Risk of Nasopharyngeal Carcinoma in an East Asian Population

Nasopharyngeal carcinoma (NPC) and alcohol flush syndrome are thought to be strongly influenced by genetic factors and are highly prevalent amongst East Asians. Diminished activity of aldehyde dehydrogenase (ALDH), a major enzyme in the alcohol-metabolizing pathway, causes the flushing syndrome associated with alcoholic consumption. The genetic effect of ALDH isoforms on NPC is unknown. We therefore investigated the association between the genetic polymorphisms of all 19 ALDH isoforms and NPC among 458 patients with NPC and 1672 age- and gender-matched healthy controls in Taiwan. Single-nucleotide polymorphisms (SNPs) located between the 40,000 base pairs upstream and downstream of the 19 ALDH isoform coding regions were collected from two genome-wise association studies conducted in Taiwan and from the Taiwan Biobank. Thirteen SNPs located on ALDH4A1, ALDH18A1, ALDH3B2, ALDH1L2, ALDH1A2, and ALDH2 Glu487Lys (rs671) were associated with NPC susceptibility. Stratification by alcohol status revealed a cumulative risk effect for NPC amongst drinkers and non-drinkers, with odds ratios of 4.89 (95% confidence interval 2.15–11.08) and 3.57 (1.97–6.47), respectively. A synergistic effect was observed between SNPs and alcohol. This study is the first to report associations between genetic variants in 19 ALDH isoforms, their interaction with alcohol consumption and NPC in an East Asian population.

MetaPhat: Detecting and Decomposing Multivariate Associations From Univariate Genome-Wide Association Statistics

Background

Multivariate testing tools that integrate multiple genome-wide association studies (GWAS) have become important as the number of phenotypes gathered from study cohorts and biobanks has increased. While these tools have been shown to boost statistical power considerably over univariate tests, an important remaining challenge is to interpret which traits are driving the multivariate association and which traits are just passengers with minor contributions to the genotype-phenotypes association statistic.

Results

We introduce MetaPhat, a novel bioinformatics tool to conduct GWAS of multiple correlated traits using univariate GWAS results and to decompose multivariate associations into sets of central traits based on intuitive trace plots that visualize Bayesian Information Criterion (BIC) and P-value statistics of multivariate association models. We validate MetaPhat with Global Lipids Genetics Consortium GWAS results, and we apply MetaPhat to univariate GWAS results for 21 heritable and correlated polyunsaturated lipid species from 2,045 Finnish samples, detecting seven independent loci associated with a cluster of lipid species. In most cases, we are able to decompose these multivariate associations to only three to five central traits out of all 21 traits included in the analyses. We release MetaPhat as an open source tool written in Python with built-in support for multi-processing, quality control, clumping and intuitive visualizations using the R software.

Conclusion

MetaPhat efficiently decomposes associations between multivariate phenotypes and genetic variants into smaller sets of central traits and improves the interpretation and specificity of genome-phenome associations. MetaPhat is freely available under the MIT license at: https://sourceforge.net/projects/meta-pheno-association-tracer.

Application of simulation-based CYP26 SNP-environment barcodes for evaluating the occurrence of oral malignant disorders by odds ratio-based binary particle swarm optimization: A case-control study in the Taiwanese population

Introduction

Genetic polymorphisms and social factors (alcohol consumption, betel quid (BQ) usage, and cigarette consumption), both separately or jointly, play a crucial role in the occurrence of oral malignant disorders such as oral and pharyngeal cancers and oral potentially malignant disorders (OPMD).

Material and methods

Simultaneous analyses of multiple single nucleotide polymorphisms (SNPs) and environmental effects on oral malignant disorders are essential to examine, albeit challenging. Thus, we conducted a case-control study (N = 576) to analyze the risk of occurrence of oral malignant disorders by using binary particle swarm optimization (BPSO) with an odds ratio (OR)-based method.

Results

We demonstrated that a combination of SNPs (CYP26B1 rs887844 and CYP26C1 rs12256889) and socio-demographic factors (age, ethnicity, and BQ chewing), referred to as the combined effects of SNP-environment, correlated with maximal risk diversity of occurrence observed between the oral malignant disorder group and the control group. The risks were more prominent in the oral and pharyngeal cancers group (OR = 10.30; 95% confidence interval (CI) = 4.58–23.15) than in the OPMD group (OR = 5.42; 95% CI = 1.94–15.12).

Conclusions

Simulation-based “SNP-environment barcodes” may be used to predict the risk of occurrence of oral malignant disorders. Applying simulation-based “SNP-environment barcodes” may provide insight into the importance of screening tests in preventing oral and pharyngeal cancers and OPMD.

CREB5 promotes cell proliferation and correlates with poor prognosis in hepatocellular carcinoma

CAMP responsive element binding protein 5 (CREB5) has been reported to be overexpressed in several types of human cancers and has crucial roles in regulating cell growth, proliferation, differentiation, and the cell cycle. However, the expression and function of CREB5 in hepatocellular carcinoma (HCC) remains unclear. The purpose of this study was to investigate the role of CREB5 in HCC, and its prognostic significance. We measured the expression of CREB5 in 91 specimens of paraffin-embedded HCC tissue by immunohistochemistry and performed a clinicopathological analysis. Gain of function and loss of function assays were used to evaluate the effect of CREB5 on cell proliferation in vitro. We found that up-regulation of CREB5 was associated with a poor prognosis, and CREB5 status was an independent prognostic factor. The overexpression of CREB5 increased the proliferation of SMMC-7721 cells, but the knockdown of CREB5 had the opposite effect. The results indicate that CREB5 may be useful when determining a treatment strategy for patients with HCC.

Ferguson L. SNP-SNP interactions as risk factors for aggressive prostate cancer

Prostate cancer (PCa) is one of the most significant male health concerns worldwide. Single nucleotide polymorphisms (SNPs) are becoming increasingly strong candidate biomarkers for identifying susceptibility to PCa. We identified a number of SNPs reported in genome-wide association analyses (GWAS) as risk factors for aggressive PCa in various European populations, and then defined SNP-SNP interactions, using PLINK software, with nucleic acid samples from a New Zealand cohort. We used this approach to find a gene x environment marker for aggressive PCa, as although statistically gene x environment interactions can be adjusted for, it is highly impossible in practicality, and thus must be incorporated in the search for a reliable biomarker for PCa. We found two intronic SNPs statistically significantly interacting with each other as a risk for aggressive prostate cancer on being compared to healthy controls in a New Zealand population.

SNP interaction pattern identifier (SIPI): an intensive search for SNP-SNP interaction patterns

Motivation

Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped.

Results

We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns.

Availability and Implementation

The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ .

Contact

hlin1@lsuhsc.edu.

Supplementary information

Supplementary data are available at Bioinformatics online.

Identification of Genetic and Epigenetic Variants Associated with Breast Cancer Prognosis by Integrative Bioinformatics Analysis

INTRODUCTION

Breast cancer being a multifaceted disease constitutes a wide spectrum of histological and molecular variability in tumors. However, the task for the identification of these variances is complicated by the interplay between inherited genetic and epigenetic aberrations. Therefore, this study provides an extrapolate outlook to the sinister partnership between DNA methylation and single-nucleotide polymorphisms (SNPs) in relevance to the identification of prognostic markers in breast cancer. The effect of these SNPs on methylation is defined as methylation quantitative trait loci (meQTL).

MATERIALS AND METHODS

We developed a novel method to identify prognostic gene signatures for breast cancer by integrating genomic and epigenomic data. This is based on the hypothesis that multiple sources of evidence pointing to the same gene or pathway are likely to lead to reduced false positives. We also apply random resampling to reduce overfitting noise by dividing samples into training and testing data sets. Specifically, the common samples between Illumina 450 DNA methylation, Affymetrix SNP array, and clinical data sets obtained from the Cancer Genome Atlas (TCGA) for breast invasive carcinoma (BRCA) were randomly divided into training and test models. An intensive statistical analysis based on log-rank test and Cox proportional hazard model has established a significant association between differential methylation and the stratification of breast cancer patients into high- and low-risk groups, respectively.

RESULTS

The comprehensive assessment based on the conjoint effect of CpG–SNP pair has guided in delaminating the breast cancer patients into the high- and low-risk groups. In particular, the most significant association was found with respect to cg05370838–rs2230576, cg00956490–rs940453, and cg11340537–rs2640785 CpG–SNP pairs. These CpG–SNP pairs were strongly associated with differential expression of ADAM8, CREB5, and EXPH5 genes, respectively. Besides, the exclusive effect of SNPs such as rs10101376, rs140679, and rs1538146 also hold significant prognostic determinant.

CONCLUSIONS

Thus, the analysis based on DNA methylation and SNPs have resulted in the identification of novel susceptible loci that hold prognostic relevance in breast cancer.

Influences of XDH genotype by gene-gene interactions with SUCLA2 for thiopurine-induced leukopenia in Korean patients with Crohn's disease

BACKGROUND

The impact of genetic variation in the thiopurine S-methyltransferase (TPMT) gene on thiopurine-induced leukopenia has been well demonstrated. Although xanthine dehydrogenase (XDH) is the second major contributor to azathioprine breakdown, polymorphisms in XDH have rarely been studied in IBD patients. We aim to access association between XDH variants and thiopurine-induced leukopenia by gene-gene interaction in a Crohn's disease (CD) population.

STUDY

A total of 964 CD patients treated with thiopurines were recruited from a tertiary referral center. The association between four XDH variants (p.Gly172Arg, p.Asn1109Thr, p.Arg149Cys, and p.Thr910Lys) and thiopurine-induced leukopenia was analyzed in cases with early leukopenia (n = 66), late leukopenia (n = 264), and in controls without leukopenia (n = 632). Three non-synonymous SNPs, which we previously reported association with thiopurine-induced leukopenia, NUDT15 (p.Arg139Cys), SUCLA2 (p.Ser199Thr), and TPMT *3C were selected for epistasis analysis with the XDH variants.

RESULTS

There was no significant association for two variants of XDH and thiopurine-induced leukopenia. In the epistasis analysis, only XDH (p.Asn1109Thr) * SUCLA2 (p.Ser199Thr) showed a statistically significant association with early leukopenia [odds ratio (OR) = 0.16; p = 0.03]. After genotype stratification, a positive association on the background of SUCLA2 wild-type (199Ser) between the XDH (p.Asn1109Thr) and early leukopenia (OR = 4.39; p = 0.01) was detected.

CONCLUSION

Genes associated with thiopurine-induced leukopenia can act in a complex interactive manner. Further studies are warranted to explore the mechanisms underlying the effects of the combination of XDH (p.Asn1109Thr) and SUCLA2 (199Ser) on thiopurine-induced leukopenia.

The Combinational Polymorphisms of ORAI1 Gene Are Associated with Preventive Models of Breast Cancer in the Taiwanese

The ORAI calcium release-activated calcium modulator 1 (ORAI1) has been proven to be an important gene for breast cancer progression and metastasis. However, the protective association model between the single nucleotide polymorphisms (SNPs) of ORAI1 gene was not investigated. Based on a published data set of 345 female breast cancer patients and 290 female controls, we used a particle swarm optimization (PSO) algorithm to identify the possible protective models of breast cancer association in terms of the SNPs of ORAI1 gene. Results showed that the PSO-generated models of 2-SNP (rs12320939-TT/rs12313273-CC), 3-SNP (rs12320939-TT/rs12313273-CC/rs712853-(TT/TC)), 4-SNP (rs12320939-TT/rs12313273-CC/rs7135617-(GG/GT)/rs712853-(TT/TC)), and 5-SNP (rs12320939-TT/rs12313273-CC/rs7135617-(GG/GT)/rs6486795-CC/rs712853-(TT/TC)) displayed low values of odds ratios (0.409–0.425) for breast cancer association. Taken together, these results suggested that our proposed PSO strategy is powerful to identify the combinational SNPs of rs12320939, rs12313273, rs7135617, rs6486795, and rs712853 of ORAI1 gene with a strongly protective association in breast cancer.

Heterogeneity revealed through meta-analysis might link geographical differences with nasopharyngeal carcinoma incidence in Han Chinese populations

Background

Nasopharyngeal carcinoma (NPC) is an epithelial malignancy highly prevalent in southern China, and incidence rates among Han Chinese people vary according to geographic region. Recently, three independent genome-wide association studies (GWASs) confirmed that HLA-A is the main risk gene for NPC. However, the results of studies conducted in regions with dissimilar incidence rates contradicted the claims that HLA-A is the sole risk gene and that the association of rs29232 is independent of the HLA-A effect in the chromosome 6p21.3 region.

Methods

We performed a meta-analysis, selecting five single-nucleotide polymorphisms (SNPs) in chromosome 6p21.3 mapped in three published GWASs and four case–control studies. The studies involved 8994 patients with NPC and 11,157 healthy controls, all of whom were Han Chinese.

Results

The rs2517713 SNP located downstream of HLA-A was significantly associated with NPC (P = 1.08 × 10⁻⁹¹, odds ratio [OR] = 0.58, 95 % confidence interval [CI] = 0.55–0.61). The rs29232 SNP exhibited a moderate level of heterogeneity (I² = 47 %) that disappeared (I² = 0 %) after stratification by moderate- and high-incidence NPC regions.

Conclusions

Our results suggested that the HLA-A gene is strongly associated with NPC risk. In addition, the heterogeneity revealed by the meta-analysis of rs29232 might be associated with regional differences in NPC incidence among Han Chinese people. The higher OR of rs29232 and the fact that rs29232 was independent of the HLA-A effect in the moderate-incidence population suggested that rs29232 might have greater relevance to NPC incidence in a moderate-incidence population than in a high-incidence population.

Electronic supplementary material

The online version of this article (doi:10.1186/s12885-015-1607-0) contains supplementary material, which is available to authorized users.