Gene-gene Interaction Analysis Research Articles

Previous miscarriages and GLI2 are associated with anorectal malformations in offspring.

Are anorectal malformations (ARMs) associated with previous miscarriages or single nucleotide polymorphisms (SNPs) in the Bone Morphogenetic Protein 4 (BMP4) and GLI family zinc finger 2 (GLI2) genes? The SNP rs3738880 in GLI2 and miscarriages were associated with ARM, especially in patients with multiple congenital anomalies (MCA). ARM are one of the most common birth defects of the gastrointestinal tract. The etiology is likely to be multifactorial, involving both environmental and genetic factors. SNPs in BMP4 and GLI2 genes were associated with ARM in non-Caucasian populations. During a patient information day, several mothers of ARM patients reported their concerns about previous miscarriages. A case-control study was performed among 427 ARM patients and 663 population-based controls. We examined the associations of ARM with SNPs in GLI2 and BMP4 using DNA samples of the children and associations with previous miscarriages using parental questionnaires. In addition, gene-gene and gene-environment interaction analyses were performed. The SNP rs3738880 in GLI2 was associated with ARM, especially in patients with MCA (homozygous GG-genotype: odds ratio (OR): 2.1; 95% CI: 1.2, 3.7). We identified previous miscarriages as a new risk factor for ARM, especially when occurring in the pregnancy directly preceding the index pregnancy and in patients with MCA (OR: 2.1; 95% CI: 1.3, 3.5). No association with rs17563 in BMP4, nor gene-gene or gene-environment interactions were found. The possibility of recall errors for previous miscarriage, but we expect these errors to be limited, as a miscarriage is a major life event. In addition, potential misclassification regarding miscarriages and stillbirth, but sensitivity analyses showed that this did not influence our results. This study showed associations of ARM with rs3738880 in GLI2 and with previous miscarriages. Both associations were stronger in patients with MCA, showing the importance of stratifying the analyses by patients with isolated ARM or MCA. This study was funded by the Radboudumc. The authors have no conflict of interest to disclose.

New insights from GWAS for the cleft palate among han Chinese population.

BackgroundGenome wide association studies (GWAS) already have identified tens of susceptible loci for nonsyndromic cleft lip with or without cleft palate (NSCL/P). However, whether these loci associated with nonsyndromic cleft palate only (NSCPO) remains unknown.Material and MethodsIn this study, we replicated 38 SNPs (Single nucleotide polymorphisms) which has the most significant p values in published GWASs, genotyping by using SNPscan among 144 NSCPO trios from Western Han Chinese. We performed the transmission disequilibrium test (TDT) on individual SNPs and gene-gene (GxG) interaction analyses on the family data; Parent-of-Origin effects were assessed by separately considering transmissions from heterozygous fathers versus heterozygous mothers to affected offspring.ResultsAllelic TDT results showed that T allele at rs742071 (PAX7) (p=0.025, ORtransmission=3.00, 95%CI: 1.09-8.25) and G allele at rs2485893 (10kb 3’ of SYT14) were associated with NSCPO (p=0.0036, ORtransmission= 0.60, 95%CI: 0.42-0.85). Genotypic TDT based on 3 pseudo controls further confirmed that rs742071 (p-value=0.03, ORtransmission=3.00, 95%CI: 1.09-8.25) and rs2485893 were associated with NSCPO under additive model (p-value= 0.02, ORtransmission= 0.66, 95%CI: 0.47-0.92). Genotypic TDT for epistatic interactions showed that rs4844913 (37kb 3’ of DIEXF) interacted with rs11119388 (SYT14) (p-value=1.80E-08) and rs6072081 (53kb 3’ of MAFB) interacted with rs6102085 (33kb 3’ of MAFB) (p-value=3.60E-04) for NSCPO, suggesting they may act in the same pathway in the etiology of NSCPO.ConclusionsIn this study, we found that rs742071 and rs2485893 were associated NSCPO from Han Chinese population; also, interactions of rs4844913:rs11119388 and rs6072081:rs6102085 for NSCPO were identified, gene-gene interactions have been proposed as a potential source of the remaining heritability, these findings provided new insights of the previous GWAS. Key words:GWAS, NSCPO, TDT, parent-of-origin effects, epistatic interactions.

An Exploration of Gene-Gene Interactions and Their Effects on Hypertension.

Hypertension tends to perpetuate in families and the heritability of hypertension is estimated to be around 20–60%. So far, the main proportion of this heritability has not been found by single-locus genome-wide association studies. Therefore, the current study explored gene-gene interactions that have the potential to partially fill in the missing heritability. A two-stage discovery-confirmatory analysis was carried out in the Framingham Heart Study cohorts. The first stage was an exhaustive pairwise search performed in 2320 early-onset hypertensive cases with matched normotensive controls from the offspring cohort. Then, identified gene-gene interactions were assessed in an independent set of 694 subjects from the original cohort. Four unique gene-gene interactions were found to be related to hypertension. Three detected genes were recognized by previous studies, and the other 5 loci/genes (MAN1A1, LMO3, NPAP1/SNRPN, DNAL4, and RNA5SP455/KRT8P5) were novel findings, which had no strong main effect on hypertension and could not be easily identified by single-locus genome-wide studies. Also, by including the identified gene-gene interactions, more variance was explained in hypertension. Overall, our study provides evidence that the genome-wide gene-gene interaction analysis has the possibility to identify new susceptibility genes, which can provide more insights into the genetic background of blood pressure regulation.

Gene-gene Interaction Analyses for Atrial Fibrillation.

Atrial fibrillation (AF) is a heritable disease that affects more than thirty million individuals worldwide. Extensive efforts have been devoted to the study of genetic determinants of AF. The objective of our study is to examine the effect of gene-gene interaction on AF susceptibility. We performed a large-scale association analysis of gene-gene interactions with AF in 8,173 AF cases, and 65,237 AF-free referents collected from 15 studies for discovery. We examined putative interactions between genome-wide SNPs and 17 known AF-related SNPs. The top interactions were then tested for association in an independent cohort for replication, which included more than 2,363 AF cases and 114,746 AF-free referents. One interaction, between rs7164883 at the HCN4 locus and rs4980345 at the SLC28A1 locus, was found to be significantly associated with AF in the discovery cohorts (interaction OR = 1.44, 95% CI: 1.27–1.65, P = 4.3 × 10–8). Eight additional gene-gene interactions were also marginally significant (P < 5 × 10–7). However, none of the top interactions were replicated. In summary, we did not find significant interactions that were associated with AF susceptibility. Future increases in sample size and denser genotyping might facilitate the identification of gene-gene interactions associated with AF.

Genetic Biomarker Selection for Obsessive-Compulsive Disorder by Sparse Representation Based Variable Selection Method

Background:Obsessive-compulsive disorder (OCD) is a debilitating neuropsychiatric condition estimated to afflict 1-3 % of the world population. Dozens of OCD candidate genes have been reported by an increased number of articles. Nevertheless, each patient/patient group may demonstrate unique etiologic characteristics that need personalized treatment. Methods:We integrated a sparse representation based variable selection (SRVS) approach with an OCD-gene ResNet relation data analysis to select top genes for a specific group of 118 subjects, including 16 OCD cases and 102 healthy controls. The gene expression profile were acquired from the dorsolateral prefrontal cortex (DLPFC) of postmortem tissue of these subjects. A 77 OCD candidate genes were acquired from ResNet relation data analysis. Pathway enrichment analysis (PEA), sub-network enrichment analysis (SNEA) and gene-gene Interaction analysis (GGI) were conducted to study the functional profile of the top genes selected by SRVS, and compared with previous reported genetic markers. Results:A significantly high classification accuracy (CR) of 79.66 % was acquired (permutation p-value = 0.0046) using the top 9 genes selected by SRVS, including HOXB8, HTR2C, CRHR2, GRIK3, HGF, OXT, TPH2, DRD2 and ADRA1A. These genes were enriched within multiple pathways and sub-networks that were previously implicated with OCD. In contrast, using the same number of most frequently reported, a CR of only 65.5 % is achieved. Moreover, GGI results showed that these genes demonstrated a strong functional correlation with the frequently reported OCD genes. Conclusion:Our study suggests that SRVS is an effective method for data driven variable selection for OCD, and that the genes that were frequently reported to associate with OCD might not be the best biomarkers for a specific OCD patient/ patient group

Epistatic Gene-Based Interaction Analyses for Glaucoma in eMERGE and NEIGHBOR Consortium.

Primary open angle glaucoma (POAG) is a complex disease and is one of the major leading causes of blindness worldwide. Genome-wide association studies have successfully identified several common variants associated with glaucoma; however, most of these variants only explain a small proportion of the genetic risk. Apart from the standard approach to identify main effects of variants across the genome, it is believed that gene-gene interactions can help elucidate part of the missing heritability by allowing for the test of interactions between genetic variants to mimic the complex nature of biology. To explain the etiology of glaucoma, we first performed a genome-wide association study (GWAS) on glaucoma case-control samples obtained from electronic medical records (EMR) to establish the utility of EMR data in detecting non-spurious and relevant associations; this analysis was aimed at confirming already known associations with glaucoma and validating the EMR derived glaucoma phenotype. Our findings from GWAS suggest consistent evidence of several known associations in POAG. We then performed an interaction analysis for variants found to be marginally associated with glaucoma (SNPs with main effect p-value <0.01) and observed interesting findings in the electronic MEdical Records and GEnomics Network (eMERGE) network dataset. Genes from the top epistatic interactions from eMERGE data (Likelihood Ratio Test i.e. LRT p-value <1e-05) were then tested for replication in the NEIGHBOR consortium dataset. To replicate our findings, we performed a gene-based SNP-SNP interaction analysis in NEIGHBOR and observed significant gene-gene interactions (p-value <0.001) among the top 17 gene-gene models identified in the discovery phase. Variants from gene-gene interaction analysis that we found to be associated with POAG explain 3.5% of additional genetic variance in eMERGE dataset above what is explained by the SNPs in genes that are replicated from previous GWAS studies (which was only 2.1% variance explained in eMERGE dataset); in the NEIGHBOR dataset, adding replicated SNPs from gene-gene interaction analysis explain 3.4% of total variance whereas GWAS SNPs alone explain only 2.8% of variance. Exploring gene-gene interactions may provide additional insights into many complex traits when explored in properly designed and powered association studies.

Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study

ObjectiveGenome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. MethodsOur analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. ResultsSingle-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. ConclusionsOur study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes.

2-amino-1-methyl-6-phenylimidazo(4,5-b) pyridine (PhIP) induces gene expression changes in JAK/STAT and MAPK pathways related to inflammation, diabetes and cancer.

Background2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine (PhIP), a heterocyclic aromatic amine (HCA) formed in meat that is cooked at high temperatures and then ingested, can potentially be retained in human adipose tissues.MethodsTo determine if PhIP is bioactive in the adipocyte, we exposed a human adipocyte cell line,HepG2 and Caco-2 cells to low dose PhIP. Uptake and retention of PhIP was determined and cytotoxicity was assessed by the TUNEL assay. Relative expression of PhIP-activating genes (CYP1A1, CYP1A2, SULT1A1 and UGT1A1) was determined by RT-PCR and global expression changes were also examined.ResultsThe percent retention of 0.1 μCi [14C]-PhIP over a 24 h period was significantly higher in the adipocyte than the HepG2 (p = 0.0001) and Caco-2 (p = 0.0007) cell lines. Cytotoxicity rates were 14.4 and 2.6 % higher compared to controls in Caco-2 and HepG2 cells (p < 0.001 and 0.054, respectively); no significant differences were detected in adipocyte cells (p = 0.18). Caco-2 and HepG2 cells, respectively, had significantly higher basal expression of CYP1A1 (p = 0.001, p = 0.003), SULT1A1 (p = 0.04, p < 0.001) and UGT1A1 (p < 0.001, p = 0.01) compared to the adipocyte. Exposure to 5nM PhIP did not significantly induce expression of these genes in any of the cell lines. Global gene expression analysis of mature adipocytes exposed to 5nM PhIP for 72 h resulted in statistically significant changes in 8 genes (ANGPTL2, CD14, CIDEA, EGR1, FOS, IGFBP5, PALM and PSAT1). Gene-gene interaction and pathway analysis indicates that PhIP modulates genes controlled by the STAT3 transcriptional factor and initiates leptin signaling via the JAK/STAT and MAPK pathway cascades. Early growth response 1 (EGR1) and prostaglandin synthase 2 (COX-2) were down-regulated via c-Fos, while insulin binding protein 5 (IBP5) was up regulated. Expression of transcription factors (ANGPTL2, HP, LEP, SAA1, SAA2), genes related to inflammation (SAA1, LEP), diabetes (IGFBP5) and cancer risk (SAA2) were also elevated upon exposure to 5 nM PhIP..ConclusionsPhIP mediates gene expression changes within the adipocyte, and the pathways most affected are related to cancer and other chronic diseases. Further studies are needed on the relationship between dietary carcinogens such as PhIP with cancer, obesity and diabetes.Electronic supplementary materialThe online version of this article (doi:10.1186/s12986-016-0111-0) contains supplementary material, which is available to authorized users.

GCORE-sib: An efficient gene-gene interaction tool for genome-wide association studies based on discordant sib pairs.

BackgroundA computationally efficient tool is required for a genome-wide gene-gene interaction analysis that tests an extremely large number of single-nucleotide polymorphism (SNP) interaction pairs in genome-wide association studies (GWAS). Current tools for GWAS interaction analysis are mainly developed for unrelated case-control samples. Relatively fewer tools for interaction analysis are available for complex disease studies with family-based design, and these tools tend to be computationally expensive.ResultsWe developed a fast gene-gene interaction test, GCORE-sib, for discordant sib pairs and implemented the test into an efficient tool. We used simulations to demonstrate that the GCORE-sib has correct type I error rates and has comparable power to that of the regression-based interaction test. We also showed that the GCORE-sib can run more than 10 times faster than the regression-based test. Finally, the GCORE-sib was applied to a GWAS dataset with approximately 2,000 discordant sib pairs, and the GCORE-sib finished testing 19,368,078,382 pairs of SNPs within 6 days.ConclusionsAn efficient gene-gene interaction tool for discordant sib pairs was developed. It will be very useful for genome-wide gene-gene interaction analysis in GWAS using discordant sib pairs. The tool can be downloaded for free at http://gcore-sib.sourceforge.net.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-016-1145-z) contains supplementary material, which is available to authorized users.

Prediction of susceptible biomarkers for end stage renal disease among North Indians.

Involvement of pro-inflammatory genes has been correlated with basic kidney diseases and end stage renal disease (ESRD). However, results at odds were often noted from such independent association studies. This study proposes a genome wide analysis approach to predict ESRD risk associated genes. We included 42 single nucleotide polymorphisms (SNPs) showing association among north Indian ESRD cases and controls. ESRD cases comprised chronic glomerulonephritis (CGN), chronic interstitial nephritis (CIN), hypertension (HTN) and autosomal dominant polycystic kidney disease (ADPKD). Genotyping data obtained from our prior published reports were compared with Genome-Wide Association Studies (GWAS) SNPs retrieved from HapMap and GWASCentral databases using R-statistical package SNPAssoc. Linkage disequilibrium (LD), gene-gene interaction, classification and regression tree (CART) and pathway analysis were carried out in the present study supplemented with IL-6 and TNF-α levels estimation using enzyme linked immunosorbent assay (ELISA). Comparison of genotyping data with GWAS SNPs revealed significant associations for interleukin (IL)1-RN, IL-6, MTHFR, tumour necrosis factor-α (TNF-α) and CCR3 genes with ESRD. Nine SNPs were commonly associated with CGN, CIN, HTN, ADPKD and ESRD. LD (D = 0.9) and gene-gene interaction (P = 0.0002) analyses revealed significant associations for IL-6 and TNF-α genes. In a consistent manner, CART analysis and functional analysis servers predict predisposing effects for TNF-α and IL-6 with ESRD. Finally, higher body circulating levels were observed for mutant TNF-α and IL-6 alleles among ESRD. The study indicates significance for IL-6 and TNF-α gene with basic kidney diseases and ESRD. Extensive statistical tests, pathway analysis and functional assays also reflect attenuated level of significance for these SNPs. In future these may be brought from bench side to clinical practice as diagnostic biomarkers upon external and prospective replication and confirmation among other cohorts.

Exploring the Effects of Genetic Variants on Clinical Profiles of Parkinson's Disease Assessed by the Unified Parkinson's Disease Rating Scale and the Hoehn-Yahr Stage.

Many genetic variants have been linked to familial or sporadic Parkinson’s disease (PD), among which those identified in PARK16, BST1, SNCA, LRRK2, GBA and MAPT genes have been demonstrated to be the most common risk factors worldwide. Moreover, complex gene-gene and gene-environment interactions have been highlighted in PD pathogenesis. Compared to studies focusing on the predisposing effects of genes, there is a relative lack of research investigating how these genes and their interactions influence the clinical profiles of PD. In a cohort consisting of 2,011 Chinese Han PD patients, we selected 9 representative variants from the 6 above-mentioned common PD genes to analyze their main and epistatic effects on the Unified Parkinson’s Disease Rating Scale (UPDRS) and the Hoehn and Yahr (H-Y) stage of PD. With multiple linear regression models adjusting for medication status, disease duration, gender and age at onset, none of the variants displayed significant main effects on UPDRS or the H-Y scores. However, for gene-gene interaction analyses, 7 out of 37 pairs of variants showed significant or marginally significant associations with these scores. Among these, the GBA rs421016 (L444P)×LRRK2 rs33949390 (R1628P) interaction was consistently significant in relation to UPDRS III and UPDRS total (I+II+III), even after controlling for the family-wise error rate using False Discovery Rate (FDR-corrected p values are 0.0481 and 0.0070, respectively). Although the effects of the remaining pairs of variants did not survive the FDR correction, they showed marginally significant associations with either UPDRS or the H-Y stage (raw p<0.05). Our results highlight the importance of epistatic effects of multiple genes on the determination of PD clinical profiles and may have implications for molecular classification and personalized intervention of the disease.

The Genetic Variability of UCP4 Affects the Individual Susceptibility to Late-Onset Alzheimer's Disease and Modifies the Disease's Risk in APOE-ɛ4 Carriers.

Uncoupling proteins (UCPs) are a group of five mitochondrial inner membrane transporters with a tissue specific expression that uncouple biofuel oxidation from ATP synthesis and function as regulators of energy homeostasis and antioxidants. Previous data suggested that neuronal UCPs (UCP2, UCP4, and UCP5) can directly influence synaptic plasticity, neurotransmission, and neurodegenerative processes, and have a crucial role in the function and protection of the central nervous system. In fact, it has been observed that the expression of neuronal UCPs significantly decreases in Alzheimer's disease (AD) patients. Here we analyzed the variability of UCP2, -3, -4, and 5 genes in sporadic and familial cases (n = 465) of late-onset AD (LOAD) with respect to healthy controls (n = 442). We showed that a genetic variant in the human UCP4, rs9472817, not only significantly affects the individual susceptibility to LOAD, but also modulates the effect of APOE-ɛ4 on AD risk. In fact, rs9472817-C allele was significantly more frequent in both groups of patients with respect to the control group (p = 6.934*10-4 for familial and p = 1.033*10-3 for sporadic cases). In addition, gene-gene interaction analysis revealed that the effect of APOE-ɛ4 allele on LOAD risk was doubled in homozygote CC subjects; conversely, the risk conferred by the APOE-ɛ4 allele was annulled in subjects with two copies of the G allele. Our findings are further evidence that the efficiency in mitochondrial energy metabolism and oxidative stress are important factors in AD pathogenesis.

Genetic Association and Gene-Gene Interaction Reveal Genetic Variations in ADH1B, GSTM1 and MnSOD Independently Confer Risk to Alcoholic Liver Diseases in India.

Genetic susceptibility is an important modifier of clinical outcome and natural history of progression in Alcoholic liver disease (ALD). While the significance of ethnicity in this evolution is very clear, subtle inter-individual genetic variant(s) might be important and thus we investigated those in an Indian population. Fourteen markers were genotyped within two alcohol metabolism genes [Alcohol dehydrogenase (ADH) gene clusters (ADH1B and ADH1C) and Aldehyde dehydrogenase (ALDH2)], one microsomal ethanol oxidizing enzyme cytochrome p450 (CYP2E1) and three oxidative stress response (OSR) genes (MnSOD, GSTT1 and GSTM1) among 490 Bengali individuals (322 ALD and 168 control) from Eastern and North-Eastern India and validation was performed in a new cohort of 150 Bengali patients including 100 ALD and 50 advanced non-alcoholic steatohepatitis (NASH). Out of 14 genetic variants, carriage of 5 genotypes (rs2066701CC in ADH1B, rs1693425TT in ADH1C, rs4880TT in MnSOD and GSTT1/GSTM1 null, p-value <0.05) were noted significantly higher among ALD patients while inter or intra group gene-gene interaction analysis revealed that addition of risk genotype of any OSR gene enhanced the possibility of ALD synergistically. Multiple logistic regression analysis showed independent association of rs2066701CC, rs4880TT and GSTM1 null genotype with ALD while lower frequencies of those genotypes in advanced NASH patients further confirmed their causal relation to ALD. Thus these findings suggest that the three variants of ADH1C, MnSOD and GSTM1 can be used to identify individuals who are at high risk to develop ALD and may be helpful in proper management of Indian alcoholics.

Efficient Strategy to Identify Gene-Gene Interactions and Its Application to Type 2 Diabetes.

Over the past decade, the detection of gene-gene interactions has become more and more popular in the field of genome-wide association studies (GWASs). The goal of the GWAS is to identify genetic susceptibility to complex diseases by assaying and analyzing hundreds of thousands of single-nucleotide polymorphisms. However, such tests are computationally demanding and methodologically challenging. Recently, a simple but powerful method, named “BOolean Operation-based Screening and Testing” (BOOST), was proposed for genome-wide gene-gene interaction analyses. BOOST was designed with a Boolean representation of genotype data and is approximately equivalent to the log-linear model. It is extremely fast, and genome-wide gene-gene interaction analyses can be completed within a few hours. However, BOOST can not adjust for covariate effects, and its type-1 error control is not correct. Thus, we considered two-step approaches for gene-gene interaction analyses. First, we selected gene-gene interactions with BOOST and applied logistic regression with covariate adjustments to select gene-gene interactions. We applied the two-step approach to type 2 diabetes (T2D) in the Korea Association Resource (KARE) cohort and identified some promising pairs of single-nucleotide polymorphisms associated with T2D.

Further Evidence of GWAS Signals in Non-Syndromic Orofacial Clefts from Western Han Chinese

Background Non-syndromic orofacial clefts (NSOCs) are the major human congenital defects with a complex etiology. Several candidate genes and environmental factors, and their interactions were assumed for the susceptibility to NSOCs. Previous GWAS have identified numerous susceptible loci from different populations. However, few loci have been replicated among Western Han Chinese yet. This study aimed to validate this findings in NSOCs from Western Han Chinese population. Methods We selected two SNPs (rs4147811 and rs481931) on 1p22 and recruited 440 case-parent trios with NSOCs for this study. The SNPs were genotyped by using SNPscan method. To evaluate the association, we performed transmission disequilibrium test (TDT), parent-of-origin effect and gene-gene interaction analysis. Results Rs481931 G allele (Z=2.05, P=0.016) and G/G homozygotes (Z=2.62, P=0.009) were over-transmitted for NSCL/P. Rs4147811 C allele (Z=2.16, P=0.030) and C/C homozygotes (Z=2.29, P=0.020) were over-transmitted for NSCL/P. Rs481931 G allele was also paternal over-transmitted for NSCL/P (P=0.030) and maternal over-transmitted for NSCPO (P=0.036). Conclusions Our results confirmed the previous GWAS findings of these two SNPs in the etiology of NSOCs among Western Han Chinese.

Assessment of the Effects of IL9, IL9R, IL17A, and IL17F Gene Polymorphisms on Women with Allergic Rhinitis in Shahrekord, Iran.

Background:The genes encoding IL9, IL9R, IL17A, and IL17F have recently been implicated in the genetic basis of rhinitis and allergy.Aim:The purpose of this study was to assess the association of the single nucleotide polymorphisms (SNPs) of IL9, IL9R, IL17A, and IL17F and potential interaction of these genes with the determination of IgE levels in women with allergic rhinitis (AR) in Shahrekord, Iran.Subjects and Methods:In a case–control study, SNPs from the IL9, IL9R, IL17A, and IL17F were genotyped in 394 random samples including 195 AR patients and 199 normal controls. Enzyme-linked immunosorbent assay was performed for the determination of serum total IgE levels. The Student's t-test was used to compare the differences. The Chi-square test was performed to compare proportions of cases with different clinical features among cases with different genotypes. The genotype and allele frequencies were obtained by direct counting. Hardy–Weinberg equilibrium was tested between cases and controls separately. The relative risk associated with rare alleles was estimated as an odds ratio with 95% confidence interval. P ≤ 0.05 was considered statistically significant.Results:The rs731476 SNP in the IL9R was significantly associated with the AR phenotype in women. No association was found between any of the other SNPs in IL9, IL17A, and IL17F genes and AR. In the gene–gene interaction analysis, we found that IL9R/IL9 genotype rs731476 T-/rs2069885 G conferred a higher risk for AR phenotype development. We also did not find a significant association in terms of IgE levels between cases and controls.Conclusion:Our result suggests that the rs731476 SNP located in the IL9R is associated with an increased susceptibility to AR in females. In a subsequent gene–gene interaction analysis, the rs731476 T-/rs2069885 G-genotype combination (IL9R/IL9) has significantly been associated with the development of the AR phenotype.

Gene-Gene Interaction Analysis for the Accelerated Failure Time Model Using a Unified Model-Based Multifactor Dimensionality Reduction Method.

Although a large number of genetic variants have been identified to be associated with common diseases through genome-wide association studies, there still exits limitations in explaining the missing heritability. One approach to solving this missing heritability problem is to investigate gene-gene interactions, rather than a single-locus approach. For gene-gene interaction analysis, the multifactor dimensionality reduction (MDR) method has been widely applied, since the constructive induction algorithm of MDR efficiently reduces high-order dimensions into one dimension by classifying multi-level genotypes into high- and low-risk groups. The MDR method has been extended to various phenotypes and has been improved to provide a significance test for gene-gene interactions. In this paper, we propose a simple method, called accelerated failure time (AFT) UM-MDR, in which the idea of a unified model-based MDR is extended to the survival phenotype by incorporating AFT-MDR into the classification step. The proposed AFT UM-MDR method is compared with AFT-MDR through simulation studies, and a short discussion is given.

Contribution of Common Variants in GABRG2, RELN and NRG3 and Interaction Networks to the Risk of Hirschsprung Disease

Background: Hirschsprung disease (HSCR) is a complex and heterogeneous disorder, characterized by a deficit in enteric nervous system. Genome-wide studies implied GABRG2, RELN and NRG3 might be involved in HSCR etiology. Here, we aimed to assess genetic variants in GABRG2, RELN and NRG3 that may confer susceptibility to HSCR and explore genetic interaction networks in HSCR. Methods: Using a strategy that combined case-control study and gene-gene interaction analysis with the MassArray system, we evaluated 24 polymorphisms within GABRG2, RELN and NRG3 in 104 HSCR cases and 151 normal controls of Han Chinese origin. Results: We observed that seven polymorphisms showed statistically significant differences between HSCR subjects and normal controls. For each of the three genes, the haplotypes which combined eight markers were the most significant. Moreover, we recruited SNPsyn, GO enrichment and MDR analyses to interrogate the interactions among GABRG2, RELN, NRG3 and our previous identified PTCH1 gene. Significant interaction networks were found among GABRG2, RELN, and PTCH1. Conclusion: We provide a first indication that common variants of GABRG2, RELN and NRG3 and the GABRG2-RELN-PTCH1 interaction networks might confer altered susceptibility to HSCR in the Han Chinese population, suggesting a potential mechanism underlying HSCR pathogenesis.

Polymorphic variants in the vitamin D pathway genes and the risk of ovarian cancer among non-carriers of BRCA1/BRCA2 mutations.

Previous studies have produced inconsistent results regarding the contribution of single-nucleotide polymorphisms (SNPs) in the vitamin D receptor (VDR) gene to ovarian cancer (OC) in various ethnicities. Additionally, little has been established with regard to the role of SNPs located in the retinoid X receptor α (RXRA), vitamin D-binding protein [also know as group-specific component (GC)] and VDR genes in non-carriers of the breast cancer 1/2 early onset (BRCA1/BRCA2) gene mutations. All participating individuals in the present study were evaluated for BRCA1 mutations (5382incC, C61G and 4153delA) with HybProbe assays, and for BRCA2 mutation (5946delT) using high-resolution melting (HRM) analysis. The associations of 8 SNPs located in RXRA, GC and VDR were investigated in OC patients without the BRCA1/BRCA2 mutations (n=245) and healthy controls (n=465). Genotyping of RXRA rs10881578 and rs10776909, and GC rs1155563 and rs2298849 SNPs was conducted by HRM analysis, while RXRA rs749759, GC rs7041, VDR BsmI rs1544410 and FokI rs2228570 genotyping was performed by polymerase chain reaction-restriction fragment length polymorphism analysis. In addition, the gene-gene interactions among all tested SNPs were studied using the epistasis option in PLINK software. The lowest P-values of the trend test were identified for VDR rs1544410 and GC rs2298849 as Ptrend=0.012 and Ptrend=0.029, respectively. It was also found that, in the dominant inheritance model, VDR BsmI contributed to an increased risk of OC [odds ratio (OR), 1.570; 95% confidence interval (CI), 1.136-2.171; P=0.006; Pcorr=0.048]. The gene-gene interaction analysis indicated a significant interaction between RXRA rs749759 and VDR FokI rs2228570 (OR for interaction, 1.687; χ2=8.278; asymptotic P-value=0.004; Pcorr=0.032). In conclusion, this study demonstrated that certain VDR and RXRA SNPs may be risk factors for OC in non-carriers of BRCA1/BRCA2 mutations in the Polish population.

Inherited Inflammatory Response Genes Are Associated with B-Cell Non-Hodgkin's Lymphoma Risk and Survival.

BackgroundMalignant B-cell clones are affected by both acquired genetic alterations and by inherited genetic variations changing the inflammatory tumour microenvironment.MethodsWe investigated 50 inflammatory response gene polymorphisms in 355 B-cell non-Hodgkin’s lymphoma (B-NHL) samples encompassing 216 diffuse large B cell lymphoma (DLBCL) and 139 follicular lymphoma (FL) and 307 controls. The effect of single genes and haplotypes were investigated and gene-expression analysis was applied for selected genes. Since interaction between risk genes can have a large impact on phenotype, two-way gene-gene interaction analysis was included.ResultsWe found inherited SNPs in genes critical for inflammatory pathways; TLR9, IL4, TAP2, IL2RA, FCGR2A, TNFA, IL10RB, GALNT12, IL12A and IL1B were significantly associated with disease risk and SELE, IL1RN, TNFA, TAP2, MBL2, IL5, CX3CR1, CHI3L1 and IL12A were, associated with overall survival (OS) in specific diagnostic entities of B-NHL. We discovered noteworthy interactions between DLBCL risk alleles on IL10 and IL4RA and FL risk alleles on IL4RA and IL4. In relation to OS, a highly significant interaction was observed in DLBCL for IL4RA (rs1805010) * IL10 (rs1800890) (HR = 0.11 (0.02–0.50)). Finally, we explored the expression of risk genes from the gene-gene interaction analysis in normal B-cell subtypes showing a different expression of IL4RA, IL10, IL10RB genes supporting a pathogenetic effect of these interactions in the germinal center.ConclusionsThe present findings support the importance of inflammatory genes in B-cell lymphomas. We found association between polymorphic sites in inflammatory response genes and risk as well as outcome in B-NHL and suggest an effect of gene-gene interactions during the stepwise oncogenesis.