Interactions among Variants in Eicosanoid Genes Increase Risk of Atherothrombotic Stroke in Chinese Populations.

BACKGROUND: Eicosanoids are lipid mediators that may play a role in ischemic stroke (IS). However, the association of variants in eicosanoid genes and these interactions with IS risk has not been investigated. The aim of the present study was to investigate the association of 11 variants in eicosanoid genes with IS and to determine whether these gene-gene interactions increase the risk of IS. METHODS: Eleven variants in prostaglandin H synthase-1 (PTGS1), PTGS2, thromboxane A2 synthase (TBXAS1), prostacyclin synthase (PTGIS), and prostaglandin E synthase (PTGES) genes were examined using mass spectrometry method in 297 patients with atherothrombotic stroke and 291 controls. Gene-gene interactions were analyzed using generalized multifactor dimensionality reduction (GMDR) method. Platelet aggregation and platelet-leukocyte aggregates were measured on admission. RESULTS: There were no significant differences in the genotype distributions of the 11 variants between patients and controls. However, GMDR analysis showed a significant gene-gene interaction among rs20417, rs5602, and rs41708, which scored 10 for cross-validation consistency and 9 for the sign test (P = .014). Logistic regression analysis showed that high-risk interaction among rs20417, rs5602, and rs41708 was an independent risk factor for atherothrombotic stroke (OR = 2.45, 95% CI: 1.33-3.27, P = .019). The high-risk interactive genotypes were associated with higher platelet aggregation and platelet-leukocyte aggregates. CONCLUSIONS: PTGS2 rs20417, PTGIS rs5602, and TBXAS1 rs41708 three-locus interactions may confer a higher risk for atherothrombotic stroke. The combinatorial analysis used in this study may be helpful to elucidate complex genetic risk for IS.

Association of Wnt signaling pathway genetic variants in gallbladder cancer susceptibility and survival.

Gallbladder cancer (GBC) is the most common malignancy of the biliary tract with adverse prognosis and poor survival. Wnt signaling plays an important role in embryonic development and regeneration of tissues in all the species. Deregulation of expression and mutations in this pathway may lead to disease state such as cancer. In this study, we assessed the association of common germline variants of Wnt pathway genes (SFRP2, SFRP4, DKK2, DKK3, WISP3, APC, ß-catenin, AXIN-2, GLI-1) to evaluate their contribution in predisposition to GBC and treatment outcomes. The study included 564 GBC patients and 250 controls. Out of 564, 200 patients were followed up for treatment response and survival. Tumor response (RECIST 1.1) was recorded in 116 patients undergoing non-adjuvant chemotherapy (NACT). Survival was assessed by Kaplan-Meier curve and Cox-proportional hazard regression. Single locus analysis showed significant association of SFRP4 rs1802073G > T [p value = 0.0001], DKK2 rs17037102C > T [p value = 0.0001], DKK3 rs3206824C > T [p value = 0.012], APC rs4595552 A/T [p value = 0.021], APC rs11954856G > T [p value = 0.047], AXIN-2 rs4791171C > T [p value = 0.001], ß-catenin rs4135385A > G [p value = 0.031], and GLI-1 rs222826C > G [p value = 0.001] with increased risk of GBC. Gene-gene interaction using GMDR analysis predicted APC rs11954856 and AXIN2 rs4791171 as significant in conferring GBC susceptibility. Cox-proportional hazard model showed GLI-1 rs2228226 CG/GG and AXIN-2 rs4791171 TT genotype higher hazard ratio. In recursive partitioning, AXIN-2 rs4791171 TT genotype showed higher mortality and hazard. Most of studied genetic variants influence GBC susceptibility. APC rs11954856, GLI-1 rs2228226, and AXIN-2 rs4791171 were found to be associated with poor survival in advanced GBC patients.

GMDR: Versatile Software for Detecting Gene-Gene and Gene-Environ- ment Interactions Underlying Complex Traits.

Identification of multifactor gene-gene (G×G) and gene-environment (G×E) interactions underlying complex traits poses one of the great challenges to today's genetic study. Development of the generalized multifactor dimensionality reduction (GMDR) method provides a practicable solution to problems in detection of interactions. To exploit the opportunities brought by the availability of diverse data, it is in high demand to develop the corresponding GMDR software that can handle a breadth of phenotypes, such as continuous, count, dichotomous, polytomous nominal, ordinal, survival and multivariate, and various kinds of study designs, such as unrelated case-control, family-based and pooled unrelated and family samples, and also allows adjustment for covariates. We developed a versatile GMDR package to implement this serial of GMDR analyses for various scenarios (e.g., unified analysis of unrelated and family samples) and large-scale (e.g., genome-wide) data. This package includes other desirable features such as data management and preprocessing. Permutation testing strategies are also built in to evaluate the threshold or empirical p values. In addition, its performance is scalable to the computational resources. The software is available at http://www.soph.uab.edu/ssg/software or http://ibi.zju.edu.cn/software.

Higher order genes interaction in DNA repair and cytokine genes polymorphism and risk to lung cancer in North Indians.

Context: Lung cancer pathological process involves cumulative effects exerted by gene polymorphism(s), epigenetic modifications, and alterations in DNA repair machinery. Further, DNA damage due to oxidative stress, chronic inflammation, and the interplay between genetic and environmental factors is also an etiologic milieu of this malignant disease. Aims: The present study aims to assess the prognostic value of DNA repair, cytokines, and GST gene polymorphism in lung cancer patients who had not received any neoadjuvant therapy. Materials and Methods: In this case-control study, 127 cases and 120 controls were enrolled. DNA from the blood samples of both patients and controls was used to genotype XRCC1Arg399Gln, XPDLys751Gln, and interleukin-1 (IL-1ß) genes by polymerase chain reaction (PCR)-restriction fragment length polymorphism method, whereas multiplex PCR was performed to genotype GSTT1 and GSTM1. Results: Binary logistic regression analysis showed that XRCC1Arg399Gln-mutant genotype (Gln/Gln, odds ratio [OR] = 4.6, 95% confidence interval [CI]: 2.2-9.6) and GSTT1 null (OR = 2.7, 95% CI: 1.6-4.5) were linked to cancer susceptibility. Generalized multidimensional reduction analysis of higher order gene-gene interaction using cross-validation testing (CVT) accuracy showed that GSTT1 (CVT 0.62, P = 0.001), XPD751 and IL-1ß (CVT 0.6, P = 0.001), and XRCC1399, XPD751, and interleukin-1 receptor antagonists (IL-1RN) (CVT 0.98, P = 0.001) were single-, two-, and three-factor best model predicted, respectively, for lung cancer risk. Classification and regression tree analysis results showed that terminal nodes which contain XRCC1399-mutant genotype (AA) had increased the risk to lung cancer. Conclusion: The present study demonstrated that XRCC1399 (Gln/Gln), GSTT1, and IL-1RN allele I, I/II served as the risk genotypes. These genes could serve as the biomarkers to predict lung cancer risk.

Gene-Gene Interactions of Gemcitabine Metabolizing-Enzyme Genes hCNT3 and WEE1 for Preventing Severe Gemcitabine-Induced Hematological Toxicity.

Most patients experience severe hematological toxicity during treatment with gemcitabine; thus, preventing such toxicity would improve the treatment effects and patient quality of life. We analyzed 13 polymorphisms in the transporters, metabolizing enzymes, targets, and genes involved in DNA damage and the folate pathway among 132 patients treated with gemcitabine and studied their association with the severity of the hematological toxicities. Single-locus analysis showed that the single-nucleotide polymorphisms (SNPs) RRM1 rs12806698 and rs11031918 and DCTD rs7663494 were significantly associated with severe neutropenia, hENT1 rs760370 and hCNT3 rs7867504 and rs4877831 were associated with severe leukopenia, CDA rs2072671, DCTD rs7663494, and WEE1 rs3910384 were associated with severe anemia, and MTHFR rs1801133 was associated with severe thrombocytopenia after stringent Bonferroni correction (P < .0038). The gene-gene interaction analysis identified the overall best models, including a 2-way interaction model (hCNT3 rs7867504 and dCK rs12648166) for severe leukopenia (P = .0022) and a 3-locus model (CDA rs207671, DCTD rs7663494, and WEE1 rs3910384) for severe anemia with a strong synergistic effect (P = .0001). The association with hematological toxicity was further strengthened by the results of a haplotype analysis, in which the homozygous genotype combination of rs3910384 CC, rs2072671 AA, rs12648166 GG, rs7867504 CC, and rs7663494 TT conferred high genetic susceptibility to severe thrombocytopenia. Our results suggest that the gene-gene interaction of gemcitabine metabolic pathway genes and WEE1 contributes to susceptibility to gemcitabine-induced hematological toxicity. Moreover, we propose a promising data-mining analysis approach (generalized multifactor dimensionality reduction) to detect and characterize gene-gene interactions.

NRN1 and CAT Gene Polymorphisms, Complex Noise, and Lifestyles interactively Affect the Risk of Noise-induced Hearing Loss.

OBJECTIVE: The effects of interactions between genetic and environmental factors on the noise-induced hearing loss (NIHL) are still unclear. This study aimed to assess interactions among gene polymorphisms, noise metrics, and lifestyles on the risk of NIHL. METHODS: A case-control study was conducted using 307 patients with NIHL and 307 matched healthy individuals from five manufacturing industries. General demographic data, lifestyle details, and noise exposure levels were recorded. The Kompetitive allele-specific polymerase chain reaction (KASP) was used to analyze the genotypes of 18 SNPs. RESULTS: GMDR model demonstrated a relevant interaction between NRN1 rs3805789 and CAT rs7943316 (P = 0.0107). Subjects with T allele of rs3805789 or T allele of rs7943316 had higher risks of NIHL than those with the SNP pair of rs3805789-CC and rs7943316-AA (P < 0.05). There was an interaction among rs3805789, rs7943316, and kurtosis (P = 0.0010). Subjects exposed to complex noise and carrying both rs3805789-CT and rs7943316-TT or rs3805789-CT/TT and rs7943316-AA had higher risks of NIHL than those exposed to steady noise and carrying both rs3805789-CC and rs7943316-AA (P < 0.05). The best six-locus model involving NRN1 rs3805789, CAT rs7943316, smoking, video volume, physical exercise, and working pressure for the risk of NIHL was found to be the interaction (P = 0.0010). An interaction was also found among smoking, video volume, physical exercise, working pressure, and kurtosis (P = 0.0107). CONCLUSION: Concurrence of NRN1 and CAT constitutes a genetic risk factor for NIHL. Complex noise exposure significantly increases the risk of NIHL in subjects with a high genetic risk score. Interactions between genes and lifestyles as well as noise metrics and lifestyles affect the risk of NIHL.

Susceptibility to Plasmodium falciparum Malaria: Influence of Combined Polymorphisms of IgG3 Gm Allotypes and Fc Gamma Receptors IIA, IIIA, and IIIB.

The binding of immunoglobulin (Ig) to Fc gamma receptors (FcgR) at the immune cell surface is an important step to initiate immunological defense against malaria. However, polymorphisms in receptors and/or constant regions of the IgG heavy chains may modulate this binding. Here, we investigated whether polymorphisms located in FcgR and constant regions of the heavy chain of IgG are associated with susceptibility to P. falciparum malaria. For this purpose, a clinical and parasitological follow-up on malaria was conducted among 656 infants in southern Benin. G3m allotypes (from total IgG3) were determined by a serological method of hemagglutination inhibition. FcgRIIA 131R/H and FcgRIIIA 176F/V genotypes were determined using the TaqMan method and FcgRIIIB NA1/NA2 genotypes were assessed by polymerase chain reaction using allele-specific primers. Association analyses between the number of malaria infections during the follow-up and polymorphisms in IgG G3m allotypes and FcgR were studied independently by zero inflated binomial negative regression. The influence of combinations of G3m allotypes and FcgRIIA/FcgRIIIA/FcgRIIIB polymorphisms on the number of P. falciparum infections, and their potential interaction with environmental exposure to malaria was assessed by using the generalized multifactor dimensionality reduction (GMDR) method. Results showed that individual carriage of G3m24 single allotype and of G3m5,6,10,11,13,14,24 phenotype was independently associated with a high risk of malaria infection. A risk effect for G3m6 was observed only under high environmental exposure. FcgRIIIA 176VV single genotype and combined carriage of FcgRIIA 131RH/FcgRIIIA 176VV/FcgRIIIB NA1NA2, FcgRIIA 131HH/FcgRIIIA 176FF/FcgRIIIB NA1NA1, FcgRIIA 131HH/FcgRIIIA 176VV/FcgRIIIB NA2NA2 and FcgRIIA 131HH/FcgRIIIA 176VV/FcgRIIIB NA1NA2 genotypes were related to a high number of malaria infections. The risk was accentuated for FcgRIIIA 176VV when considering the influence of environmental exposure to malaria. Finally, the GMDR analysis including environmental exposure showed strengthened associations with a malaria risk when FcgRIIA/FcgRIIIA/FcgRIIIB genotypes were combined to G3m5,6,11,24 and G3m5,6,10,11,13,15,24 phenotypes or G3m10 and G3m13 single allotypes. Our results highlight the relevance of studying IgG heavy chain and FcgR polymorphisms, independently as well as in combination, in relation to the individual susceptibility to P. falciparum infection. The intensity of individual exposure to mosquito bites was demonstrated to impact the relationships found.

Association of the NCAN-TM6SF2-CILP2-PBX4-SUGP1-MAU2 SNPs and gene-gene and gene-environment interactions with serum lipid levels.

This study investigated the association of the NCAN-TM6SF2-CILP2-PBX4-SUGP1-MAU2 SNPs and gene-gene and gene-environment interactions with serum lipid levels in the population of Southwest China. Genotyping of 12 SNPs (i.e., rs2238675, rs2228603, rs58542926, rs735273, rs16996148, rs968525, rs17216525, rs12610185, rs10401969, rs8102280, rs73001065 and rs150268548) was performed in 1248 hyperlipidemia patients and 1248 normal subjects. The allelic and genotypic frequencies of the detected SNPs differed substantially between the normal and hyperlipidemia groups (P < 0.05-0.001), and the association of the 12 SNPs and hyperlipidemia was also observed (P < 0.004-0.0001). Four haplotypes (i.e., NCAN C-C, CILP2 G-T, PBX4-SUGP1 G-C, and MAU2 C-A-G-T) and 5 gene-gene interaction haplotypes (i.e., rs2238675C-rs2228603C, rs16996148G-rs17216525T, rs12610185G-rs10401969C, rs73001065G-rs8102280A-rs150268548G-rs968525C and rs73001065C-rs8102280A-rs150268548G-rs96852）showed a protective effect, whereas four other haplotypes (i.e., TM6SF2 T-A, TM6SF2 C-A, MAU2 G-G-G-C and MAU2 C-G-A-T), as well as 4 gene-gene interaction haplotypes (i.e., rs58542926C-rs735273A, rs58542926T-rs735273A, rs73001065G-rs8102280G-rs150268548G-rs968525C, and rs73001065C-rs8102280G-rs150268548A-rs968525T), exhibited an inverse effect on hyperlipidemia (P < 0.05-0.0001). There were notable three-locus models comprising SNP-SNP, SNP-environment, and haplotype-haplotype interactions (P < 0.05-0.0001). The individuals with some genotypes and haplotypes reduced the prevalence of hyperlipidemia, whereas the individuals with some other genotypes and haplotypes augmented the prevalence of hyperlipidemia. The NCAN-TM6SF2-CILP2-PBX4-SUGP1-MAU2 SNPs and gene-gene and gene-environment interactions on hyperlipidemia were observed in the population of Southwest China.

Pro-inflammatory cytokine polymorphisms in ONECUT2 and HNF4A and primary colorectal carcinoma: a post genome-wide gene-lifestyle interaction study.

Immune-related molecular and genetic pathways that are connected to colorectal cancer (CRC) and lifestyles in postmenopausal women are incompletely characterized. In this study, we examined the role of pro-inflammatory biomarkers such as C-reactive protein (CRP) and interleukin-6 (IL-6) in those pathways. Through selection of the best predictive single-nucleotide polymorphisms (SNPs) and lifestyles, our goal was to improve the prediction accuracy and ability for CRC risk. Using large cohort data of postmenopausal women from the Women's Health Initiative Database for Genotypes and Phenotypes Study, we previously conducted a genome-wide association (GWA) for a CRP and IL-6 gene-behavioral interaction study. For the present study, we added GWA-SNPs from outside GWA studies, resulting in a total of 152 SNPs. Together with 41 selected lifestyles, we performed a 2-stage multimodal random survival forest analysis with generalized multifactor dimensionality reduction approach to construct CRC risk profiles. Overall and in obesity strata (by body mass index, waist circumference, waist-to-hip ratio, exercise, and dietary fat intake), we identified the best predictive genetic markers in inflammatory cytokines and lifestyles. Across the strata, 2 SNPs (ONECUT2 rs4092465 and HNF4A rs1800961) and 1 lifestyle factor (relatively short-term past use of oral contraceptives) were the most common and strongest predictive markers for CRC risk. The risk profile that combined those variables exhibited synergistically increased risk for CRC; this pattern appeared more strongly in obese and inactive subgroups. Our results may contribute to improved predictability for CRC and suggest genetically targeted lifestyle interventions for women carrying the inflammatory-risk genotypes, reducing CRC risk.

Variants in matrix metalloproteinase-9 gene are associated with hemorrhagic transformation in acute ischemic stroke patients with atherothrombosis, small artery disease, and cardioembolic stroke.

OBJECTIVE: The potential effect of matrix metalloproteinase-9 (MMP-9) variants and these variants interactions on hemorrhagic transformation (HT) risk after ischemic stroke (IS) remain unclear. The aims of present study were to investigate the associations of six variants in MMP-9 with HT, and these variants interactions whether related to increased HT risk. METHOD: A total of 705 patients with IS who were admitted to the participating hospitals within 48 hr of symptom onset were consecutively enrolled between March 2014 and December 2016. HT was confirmed by brain computed tomography (CT) scan during 14 days from stroke onset. Six variants of MMP-9 gene were measured by mass spectrometry. Interactions of gene variant-gene variant were assessed through generalized multifactor dimensionality reduction method (GMDR). RESULTS: HT occurred in 104 (14.8%) patients. There were no differences in genotypes for the six variants between patients with and without HT using univariate analysis (all p > 0.05). GMDR analysis revealed that there was a synergistic effect of gene variant-gene variant interactions between rs3918242 and rs3787268 in MMP-9 gene. Cox regression analysis showed that high-risk interactions of rs3918242 and rs3787268 were associated with increased risk of HT after adjusting for covariates (hazard ratio: 2.08; 95% confidence interval: 1.34-7.85; p = 0.016). CONCLUSION: Incidence of HT is common in acute IS in Chinese population. The mechanisms leading to HT are most likely multifactorial. Two-loci interactions of rs3918242 and rs3787268 in MMP-9 gene may confer a higher risk for HT.

Single Nucleotide Polymorphisms in the Acylphosphatase 2 Gene and The SNP-SNP Interactions on the Risk of Breast Cancer in Chinese Han Women.

INTRODUCTION: The purpose of this study was to investigate the impact of single nucleotide polymorphisms (SNPs) in the acylphosphatase 2 gene and the SNP-SNP interactions on breast cancer (BC) risk in Chinese Han women. PATIENTS AND METHODS: A logistic regression model was used to examine the association between SNPs and BC risk. Odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Generalized multifactor dimensionality reduction was employed to analyze the SNP-SNP interaction. RESULTS: Logistic regression analysis showed that BC risk was significantly higher in carriers with the rs1682111-A allele than those with the TT genotype (TA + AA vs. TT; adjusted OR, 1.47; 95% CI, 1.21-1.92). In addition, we also found that BC risk was significantly higher in carriers with the rs10439478-C allele than those with the AA genotype (AC + CC vs. AA); adjusted OR, 1.67; 95% CI, 1.29-2.11. We found a significant 2-locus model (P = .0010) involving rs1682111 and rs10439478; the cross-validation consistency of this model was 10 of 10, and the testing accuracy was 60.11%. Participants with the TA or AA of rs1682111 and the AC or CC of rs10439478 genotype have the highest BC risk, compared with subjects with the TT of rs1682111 and the AA of rs10439478 genotype (OR, 2.52; 95% CI, 1.67-3.44), after covariate adjustment for gender, age, age at menarche, number of children, and body mass index. CONCLUSIONS: Minor allele of rs1682111 and rs10439478 and its interaction were associated with increased BC risk.

Interaction between polymorphisms in cell-cycle genes and environmental factors in regulating cholinesterase activity in people with exposure to omethoate.

Cholinesterase activity (ChA), the effective biomarker for organophosphate pesticide exposure, is possibly affected by single nucleotide polymorphisms (SNPs) in cell-cycle-related genes. One hundred and eighty workers with long-term exposure to omethoate and 115 healthy controls were recruited to explore the gene-gene and gene-environment interactions. The acetylthiocholine and dithio-bis-(nitrobenzoic acid) method was used to detect the cholinesterase activities in whole blood, erythrocytes and plasma. Genetic polymorphisms were determined by the PCR-RFLP and direct PCR electrophoresis methods. Statistical results showed that the cholinesterase activities of whole blood, erythrocytes and plasma in the exposure group were significantly lower than those in the control group (p < 0.001), and erythrocyte cholinesterase activities were associated with gender, smoking and drinking in the exposure group (p < 0.05). Single-locus analyses showed that there is a statistically significant difference in the ChA among the genotypes CC, CA and AA of the p21 rs1801270 locus in the control group (p = 0.033), but not in the exposure group. A significant interaction between genes and environmental factors (i.e. p53, p21, mdm2, gender, smoking and drinking) affecting ChA was found through a generalized multifactor dimensionality reduction analysis. These obtained markers will be useful in further marker-assisted selection in workers with exposure to omethoate.

Interactions among the variants of insulin-related genes and nutrients increase the risk of type 2 diabetes.

Asians easily develops type 2 diabetes (T2DM) since they have insufficient glucose-stimulated insulin secretion (GSIS) in insulin resistant states. Since this may be associated with genetic background, the hypothesis of this study was that inter-genetic and gene-nutrient interactions may explain the low insulin secretory capacity of Asians. Accordingly, we identified the best gene-gene and gene-nutrient interactions using generalized multifactor dimensionality reduction (GMDR) in a large Korean cohort (n=8,842). Initially, we used 105 genetic variants associated with GSIS to identify the best gene-gene interaction model using the GMDR method. The best model included six SNPs, FNBP1L-rs4847428, FNBP1L-rs23766, GLIS3-rs2027393, GLIS3-rs3892354, GLIS3-rs486163 and DLC1-rs17093957. For each individual, we obtained the genetic risk scores based on the best model (GRSBM) to predict the GSIS levels. The GRSBM were divided into low, medium and high groups, and the association between T2DM and the GRSBM was measured using logistic regression. We analyzed the interaction between the GRSBM and the nutrition intakes. The adjusted odds ratios for T2DM risk increased by 1.701 fold in the high-score group compared to the low-score group. HOMA-B, an index of insulin secretion capacity, but not insulin resistance index was much lower in the high-score group than the low-score group. The association between the GRSBM and T2DM risk was greater in subjects with high energy intakes and low Ca intake, than those with low energy intake and high Ca intake. The high-score group was susceptible to T2DM incidence due to lower GSIS than the low-score group especially in subjects with high energy intake. In conclusion, the hypothesis of the study was accepted. These findings suggested that individuals with high GRSBM of the 6 genes in the model should avoid diets in high energy and low in calcium (<500 mg/day) to protect against T2DM.

The interaction of NOS1AP, DISC1, DAOA, and GSK3B confers susceptibility of early-onset schizophrenia in Chinese Han population.

Although many major breakthrough had identificated potential susceptibility genes for schizophrenia, the aetiology of schizophrenia is still unknown. In the present study, we focused on the N-methyl-Daspartate receptors related genes nitric oxide synthase 1 adaptor gene (NOS1AP), disrupted in schizophrenia 1 gene (DISC1), d-amino acid oxidase activator gene (DAOA), and glycogen synthase kinase 3-beta gene (GSK3B). A family-based genetic association study (459 Han Chinese subjects in 153 nuclear families) using 3 single nucleotide polymorphisms in NOS1AP, 2 in DISC1, 1 in DAOA and 1 in GSK3B was conducted. We found rs12742393 have just positive trend with schizophrenia (SCZ) (p=0.07) after FDR correction. NOS1AP mRNA and serum levels were significantly elevated in SCZ patients (p<0.001; p<0.001) compared with healthy control. However, expression Quantitative Trait Loci (eQTL) analysis have demonstrated that rs12742393 genotype were not significantly associated with the NOS1AP mRNA expression. GMDR identified a significant seven-locus interaction model involving (NOS1AP-rs348624, rs12742393, rs1415263, DISC1-rs821633, rs1000731, DAOA-rs2391191and GSK3B- rs6438552) with a good testing accuracy (0.72). Our finding suggested statistically significant role of interaction of NOS1AP, DISC1, DAOA, and GSK3B polymorphisms (NOS1AP-rs348624, rs12742393, rs1415263, DISC1-rs821633, rs1000731, DAOA-rs2391191and GSK3B-rs6438552) in EOS susceptibility.

[Gene-gene interaction on central obesity in school-aged children in China].

Objective: To investigate possible effect of 6 obesity-associated SNPs in contribution to central obesity and examine whether there is an interaction in the 6 SNPs in the cause of central obesity in school-aged children in China. Methods: A total of 3 502 school-aged children who were included in Beijing Child and Adolescent Metabolic Syndrome (BCAMS) Study were selected, and based on the age and sex specific waist circumference (WC) standards in the BCAMS study, 1 196 central obese cases and 2 306 controls were identified. Genomic DNA was extracted from peripheral blood white cells using the salt fractionation method. A total of 6 single nucleotide polymorphisms (FTO rs9939609, MC4R rs17782313, BDNF rs6265, PCSK1 rs6235, SH2B1 rs4788102, and CSK rs1378942) were genotyped by TaqMan allelic discrimination assays with the GeneAmp 7900 sequence detection system (Applied Biosystems, Foster City, CA, USA). Logistic regression model was used to investigate the association between 6 SNPs and central obesity. Gene-gene interactions among 6 polymorphic loci were analyzed by using the Generalized Multifactor Dimensionality Reduction (GMDR) method, and then logistic regression model was constructed to confirm the best combination of loci identified in the GMDR. Results: After adjusting gender, age, Tanner stage, physical activity and family history of obesity, the FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity under additive genetic model (OR=1.24, 95%CI: 1.06-1.45, P=0.008; OR=1.26, 95%CI: 1.11-1.43, P=2.98×10(-4); OR=1.18, 95% CI: 1.06-1.32, P=0.003). GMDR analysis showed a significant gene-gene interaction between MC4R rs17782313 and BDNF rs6265 (P=0.001). The best two-locus combination showed the cross-validation consistency of 10/10 and testing accuracy of 0.539. This interaction showed the maximum consistency and minimum prediction error among all gene-gene interaction models evaluated. Moreover, the combination of MC4R rs17782313-C and BDNF rs6265-G was associated with an increased risk of central obesity after adjustment for gender, age, Tanner stage, physical activity and family history of obesity. Conclusions: Our study showed that FTO rs9939609-A, MC4R rs17782313-C and BDNF rs6265-G alleles were associated with central obesity, and statistical interaction between MC4R rs17782313-C and BDNF rs6265-G increased risk of central obesity in school-aged children in China.

[Association and effects of gene-gene interactions between peroxisome proliferator-activated receptor and pulse pressure].

Objective: To investigate the association between ten single nucleotide polymorphisms (SNPs) in the peroxisome proliferator-activated receptors and pulse pressure (PP) as well as the relationships between gene-gene interaction between PPARα/δ/γ genes and PP. Methods: A total of 820 subjects, with 550 females and 270 males, were recruited from a cohort study of "Prevention of Metabolic Syndrome and Multi-metabolic Disorders in Jiangsu Province of China Study (PMMJS)" . Ten SNPs of PPARα/δ/γ genes were selected. GMDR software (version 1.0.1) was used to evaluate the gene-gene interactions among PPARs SNPs associated with PP. Results: The mean levels of PP in people with mutant genotype of rs1805192 in PPARγ genes (PA+AA) showed a significant increase by 1.341 mmHg (95%CI: 0.431-2.252 mmHg) when compared to the persons with wild genotype (PP). In the subgroup of subjects with more than 30 mmHg levels of PP, a six-locus model comprised rs135539 of PPARα, rs2016520 of PPARδ, rs10865710, rs1805192, rs709158 and rs3856806 of PPARγ showed a highest level of prediction accuracy (0.577) and displayed a better cross-validation consistency (10/10). In the subgroup of subjects with less than 40 mmHg levels of PP, a two-locus model was statistically associated with PP with 0.628 of prediction accuracy and 10/10 of cross-validation consistency. Conclusion: PPARγ rs1805192 was associated with the occurrence of PP. Gene-gene interactions among rs135539 of PPARα, rs2016520 of PPARδ, rs10865710, rs1805192, rs709158 and rs3856806 of PPARγ were all significantly related to PP.

Impact of Interaction Between PPAR Alpha and PPAR Gamma on Breast Cancer Risk in the Chinese Han Population.

BACKGROUND: Several studies have been conducted to investigate the association of the peroxisome proliferator-activated receptor (PPAR) alpha (PPAR A) and PPAR gamma (PPAR G) polymorphism and breast cancer (BC) risk, but the results were inconsistent, and, until now, no study focused on the impact of gene-gene interactions between PPAR A and PPAR G on BC risk; thus, the aim of this study was to investigate the impact of interaction between PPAR A and PPAR G on BC risk in the Chinese Han population. METHODS: A total of 862 participants with a mean age of 63.0 ± 15.7 years were selected, including 432 patients with BC and 430 controls. A logistic regression model was used to examine the association between single-nucleotide polymorphisms and BC risk. The odds ratios (ORs) and 95% confidence intervals (95% CIs) were calculated. Generalized multifactor dimensionality reduction was employed to analyze the gene-gene interaction. RESULTS: Logistic regression analysis showed that BC risk was significantly higher in carriers of G allele of rs1800206 polymorphism than those with CC (CG + GG vs. CC) (adjusted OR, 1.50; 95% CI, 1.20-1.93). In addition, we found that BC risk was also significantly higher in carriers of the G allele of the rs1805192 polymorphism than those with the CC genotype (CG + GG vs. CC) (adjusted OR, 1.78; 95% CI, 1.34-2.26). There was a significant gene-gene interaction between rs1805192 and rs1800206. Overall, the 2-locus models had a cross-validation consistency of 10 of 10, and had a testing accuracy of 60.11%. Patients with CG or GG of rs1805192 and CG or GG of rs1800206 genotype have the highest BC risk, compared with patients with CC of rs1805192 and CC of rs1800206 genotype (OR, 2.59; 95% CI, 1.70-3.48, after covariates adjustment for gender, age, age at menarche, number of children, body mass index, and waist circumference). CONCLUSIONS: The minor allele of rs1800206 and rs1805192 and its interaction were associated with increased BC risk.

CYP2C8 rs17110453 and EPHX2 rs751141 two-locus interaction increases susceptibility to ischemic stroke.

AIMS: Ischemic stroke (IS) is a multifactorial disease caused by a combination of environmental risk factors and genetic susceptibilities. However, few studies have assessed the effects of gene-gene interactions among cytochrome P450 (CYP) pathway genes on the risk of stroke. The present study investigated the association of seven variants of six CYP pathway genes with IS in a Chinese population. MAIN METHODS: A total of 396 patients with IS and 378 controls were genotyped for seven variants from six CYP pathway genes, including CYP2J2 rs10889160, CYP2C8 rs17110453, CYP2C8 rs1934980, CYP2C9 rs1799853, CYP2C9 rs1057910, and CYP3A5 rs776746, as well as epoxide hydrolase 2 (EPHX2) rs751141, using matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) methods. Gene-gene interactions were analyzed using generalized multifactor dimensionality reduction (GMDR) methods. KEY FINDINGS: Single-gene variant analysis showed no significant differences in the genotype distributions of the seven variants between IS patients and healthy volunteers. However, GMDR analysis showed a significant gene-gene interaction between rs17110453 and rs751141, with scores of 10 and 9 for the cross-validation consistency and sign test, respectively (P=0.0167). A 1.86-fold increased risk for IS was detected in individuals carrying the genotypes of rs17110453CC and rs751141GG (adjusted for age, hypertension, and diabetes mellitus; 95% CI: 1.216-2.896, P=0.005). SIGNIFICANCE: The CYP2C8 rs17110453 and EPHX2 rs751141 two-locus interaction confers a significantly higher risk for IS. The combinational analysis used in this study may be helpful in the elucidation of genetic risk factors for common and complex diseases such as IS.

Hidden risk genes with high-order intragenic epistasis in Alzheimer's disease.

Meta-analysis of data from genome-wide association studies (GWAS) of Alzheimer's disease (AD) has confirmed the high risk of APOE and identified twenty other risk genes/loci with moderate effect size. However, many more risk genes/loci remain to be discovered to account for the missing heritability. The contributions from individual singe-nucleotide polymorphisms (SNPs) have been thoroughly examined in traditional GWAS data analysis, while SNP-SNP interactions can be explored by a variety of alternative approaches. Here we applied generalized multifactor dimensionality reduction to the re-analysis of four publicly available GWAS datasets for AD. When considering 4-order intragenic SNP interactions, we observed high consistency of discovered potential risk genes among the four independent GWAS datasets. Ten potential risk genes were observed across all four datasets, including PDE1A, RYR3, TEK, SLC25A21, LOC729852, KIRREL3, PTPN5, FSHR, PARK2, and NR3C2. These potential risk genes discovered by generalized multifactor dimensionality reduction are highly relevant to AD pathogenesis based on multiple layers of evidence. The genetic contributions of these genes warrant further confirmation in other independent GWAS datasets for AD.

Network graph analysis of gene-gene interactions in genome-wide association study data.

Most common complex traits, such as obesity, hypertension, diabetes, and cancers, are known to be associated with multiple genes, environmental factors, and their epistasis. Recently, the development of advanced genotyping technologies has allowed us to perform genome-wide association studies (GWASs). For detecting the effects of multiple genes on complex traits, many approaches have been proposed for GWASs. Multifactor dimensionality reduction (MDR) is one of the powerful and efficient methods for detecting high-order gene-gene (GxG) interactions. However, the biological interpretation of GxG interactions identified by MDR analysis is not easy. In order to aid the interpretation of MDR results, we propose a network graph analysis to elucidate the meaning of identified GxG interactions. The proposed network graph analysis consists of three steps. The first step is for performing GxG interaction analysis using MDR analysis. The second step is to draw the network graph using the MDR result. The third step is to provide biological evidence of the identified GxG interaction using external biological databases. The proposed method was applied to Korean Association Resource (KARE) data, containing 8838 individuals with 327,632 single-nucleotide polymorphisms, in order to perform GxG interaction analysis of body mass index (BMI). Our network graph analysis successfully showed that many identified GxG interactions have known biological evidence related to BMI. We expect that our network graph analysis will be helpful to interpret the biological meaning of GxG interactions.