Efecto combinado de la interacción genética sobre el desarrollo del bocio nodular con tiroiditis autoinmune y adenoma tiroideo en los habitantes de Bucovina del Norte / Combined effect of gene-gene interaction on the development of nodular goiter with autoimmune thyroiditis and thyroid adenoma in the inhabitants of Northern Bukovyna

ABSTRAC This article presents the results of a comprehensive analysis of the combined influence of genetic polymorphisms associated with various links of apoptosis regulation (BCL-2, CTLA-4 and APO-1/Fas) on the development of nodular goiter with autoimmune thyroiditis and thyroid adenoma in the studied population. The analysis was performed using the Multifactor Dimensionality Reduction (MDR) method by calculating the prediction potential. Graphic models of gene-gene interaction with the highest cross-validation consistency created by the MDR method showed complex "synergistic or independent" impact of polymorphic loci of the CTLA-4 (+49G/A), Fas (-1377G/A) and BCL-2 (63291411 A>G) genes on the onset of thyroid pathology in general, or its individual types (nodular goiter with autoimmune thyroiditis and thyroid adenoma) in the population of Northern Bukovyna.

RESUMEN Este artículo presenta los resultados de un análisis exhaustivo de la influencia combinada de polimorfismos genéticos asociados a diversos enlaces en la regulación de la apoptosis (BCL-2, CTLA-4 y APO-1/FAS) sobre el desarrollo de bocio nodular con tiroiditis autoinmune y adenoma tiroideo en la población estudiada. Para ello, se utilizó el método de reducción de dimensionalidad multifactorial (MDR) mediante el cálculo de los potenciales de predicción. Los modelos gráficos de interacción gen-gen con la mayor consistencia de validación cruzada creada por el método MDR mostraron un complejo impacto «sinérgico o independiente¼ de los loci polimórficos de los genes CTLA-4 (+49G/A), FAS (-1377G/A) y BCL-2 (63291411A>G) en el inicio de la patología tiroidea en general, o sus tipos individuales (bocio nodular con tiroiditis autoinmune y adenoma tiroideo) en la población de Bucovina septentrional.

EFMDR-Fast: An Application of Empirical Fuzzy Multifactor Dimensionality Reduction for Fast Execution

Gene-gene interaction is a key factor for explaining missing heritability. Many methods have been proposed to identify gene-gene interactions. Multifactor dimensionality reduction (MDR) is a well-known method for the detection of gene-gene interactions by reduction from genotypes of single-nucleotide polymorphism combinations to a binary variable with a value of high risk or low risk. This method has been widely expanded to own a specific objective. Among those expansions, fuzzy-MDR uses the fuzzy set theory for the membership of high risk or low risk and increases the detection rates of gene-gene interactions. Fuzzy-MDR is expanded by a maximum likelihood estimator as a new membership function in empirical fuzzy MDR (EFMDR). However, EFMDR is relatively slow, because it is implemented by R script language. Therefore, in this study, we implemented EFMDR using RCPP (c++ package) for faster executions. Our implementation for faster EFMDR, called EMMDR-Fast, is about 800 times faster than EFMDR written by R script only.

The FOXO1 Gene-Obesity Interaction Increases the Risk of Type 2 Diabetes Mellitus in a Chinese Han Population

Here, we aimed to study the effect of the forkhead box O1-insulin receptor substrate 2 (FOXO1-IRS2) gene interaction and the FOXO1 and IRS2 genes-environment interaction for the risk of type 2 diabetes mellitus (T2DM) in a Chinese Han population. We genotyped 7 polymorphism sites of FOXO1 gene and IRS2 gene in 780 unrelated Chinese Han people (474 cases of T2DM, 306 cases of healthy control). The risk of T2DM in individuals with AA genotype for rs7986407 and CC genotype for rs4581585 in FOXO1 gene was 2.092 and 2.57 times higher than that with GG genotype (odds ratio [OR] = 2.092; 95% confidence interval [CI] = 1.178–3.731; P = 0.011) and TT genotype (OR = 2.571; 95% CI = 1.404–4.695; P = 0.002), respectively. The risk of T2DM in individuals with GG genotype for Gly1057Asp in IRS2 gene was 1.42 times higher than that with AA genotype (OR = 1.422; 95% CI = 1.037–1.949; P = 0.029). The other 4 single nucleotide polymorphisms (SNPs) had no significant association with T2DM (P > 0.05). Multifactor dimensionality reduction (MDR) analysis showed that the interaction between SNPs rs7986407 and rs4325426 in FOXO1 gene and waist was the best model confirmed by interaction analysis, closely associating with T2DM. There was an increased risk for T2DM in the case of non-obesity with genotype combined AA/CC, AA/AC or AG/AA for rs7986407 and rs4325426, and obesity with genotype AA for rs7986407 or AA for rs4325426 (OR = 3.976; 95% CI = 1.156–13.675; P value from sign test [P(sign)] = 0.025; P value from permutation test [P(perm)] = 0.000–0.001). Together, this study indicates an association of FOXO1 and IRS2 gene polymorphisms with T2DM in Chinese Han population, supporting FOXO1-obesity interaction as a key factor for the risk of T2DM.

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.

Gene-Gene Interaction Between CCR3 and Eotaxin Genes: The Relationship With Blood Eosinophilia in Asthma

PURPOSE: Eosinophils function as an effector cell in the development of asthma and allergic disease. Eotaxins are cytokines that promote pulmonary eosinophilia via the receptor CCR3. Single-nucleotide polymorphisms (SNPs) in CCR3 and eotaxin genes are associated with asthma. In this study, genetic interactions among SNPs of several eotaxin genes and CCR3 were assessed and their relationship with blood eosinophilia in asthma was examined. METHODS: A total of 533 asthmatics were enrolled in this study. Asthmatics with eosinophilia (>0.5x109/L) were compared with those without eosinophilia (A (29L>I) was significantly associated with 3 of the 4 CCR3 SNPs among asthmatics with eosinophilia (P=0.037-0.009). EOT2+304C>A (29L>I) and the CCR3 SNPs were also significantly associated with blood eosinophilia in an interaction model constructed by logistic regression (P=0.0087). GMDR analysis showed that the combination of EOT2+304C>A (29L>I) and CCR3-174C>T was the best model (accuracy=0.536, P=0.005, CVC 9/10). CONCLUSIONS: The epistatic influence of CCR3 on eotaxin gene variants indicates that these variants may be candidate markers for eosinophilia in asthma.

Multifactor dimensionality reduction analysis of the correlation of Chinese medicine syndrome evolvement and cardiovascular events in patients with stable coronary heart disease / 中国结合医学杂志

<p><b>OBJECTIVE</b>To analyze the correlation of Chinese medicine syndrome evolvement and cardiovascular: events in patients with stable coronary heart disease (CHD).</p><p><b>METHODS</b>This prospective cohort study investigated and: collected the clinical information of patients with stable CHD and observed the syndrome type at the baseline and 6-month at follow-up, as well as the cardiovascular events during the 6-month and 12-month follow-up. The patients were divided into the event group and the non-event group. The interaction and the impact of syndrome evolvement on cardiovascular events were examined through multifactor dimensionality reduction (MDR) analysis and the results were verified by Chi-square test.</p><p><b>RESULTS</b>Totally 1,333 of 1,503 stable CHD patients enrolled met the inclusion criteria: of MDR analysis. Among them, 959 (71.9%) cases were males and 374 (28.1%) cases were females. Thirty seven cases had cardiovascular events during 6 to 12 months after the study began. The results of the MDR analysis and verification using Chi-square test showed that the development of cardiovascular events was positively correlated with interaction between blood stasis and toxic syndrome at the baseline, blood stasis at the baseline and qi deficiency at the 6-month follow-up, toxic syndrome at the baseline and qi deficiency at the 6-month follow-up, toxic syndrome at the base line and blood stasis at the 6-month follow-up, qi deficiency and blood stasis at the 6-month follow-up (P<0.05 for all).</p><p><b>CONCLUSIONS</b>Blood stasis, toxic syndrome and qi deficiency are important factors of stable CHD. There: are positive correlation between cardiovascular events and syndrome evolution from blood stasis to qi deficiency, from toxic syndrome to qi deficiency and from toxic syndrome to blood stasis, indicating the pathogenesis of toxin consuming qi, toxin leading to blood-stasis in stable CHD patients prone to recurrent cardiovascular events.</p>

The Interaction Between Allelic Variants of CD86 and CD40LG: A Common Risk Factor of Allergic Asthma and Rheumatoid Arthritis

PURPOSE: Allergic asthma (AA) and rheumatoid arthritis (RA) are immune tolerance-related diseases, and immune tolerance is known to be influenced by costimulatory molecules. In this study, we sought to identify common genetic susceptibility in AA and RA. METHODS: Two hundred cases of AA, 184 cases of RA, and 182 healthy controls were recruited at the Seoul National University Hospital, Seoul, Korea. Eight single nucleotide polymorphisms (SNPs) in five genes coding costimulatory molecules, namely, -318C>T, +49A>G, and 6230G>A in CTLA4, IVS3+17T>C in CD28, -3479T>G and I179V in CD86, -1C>T in CD40, and -3458A>G in CD40LG were scored, and genetic interactions were evaluated by multifactor dimensionality reduction (MDR) analysis. RESULTS: MDR analysis revealed a significant gene-gene interaction between -3479T>G CD86 and -3458A>G CD40LG for AA. Subjects with the T/T genotype of -3479T>G CD86 and the A/A genotype of -3458A>G CD40LG were found to be significantly more likely to develop AA than those with the T/T genotype of -3479T>G CD86 and A/- genotype of -3458A>G CD40LG (adjusted OR, 6.09; 95% CI, 2.89-12.98; logistic regression analysis controlled by age). Similarly those subjects showed a significant risk of developing RA (adjusted OR, 39.35; 95% CI, 15.01-107.00, logistic regression analysis controlled by age). CONCLUSIONS: Our findings suggest that a genetic interaction between CD86 and CD40LG favors the development of both AA and RA.

Epistatic interactions in idiopathic pulmonary arterial hypertension.

BACKGROUND: Idiopathic pulmonary arterial hypertension (IPAH) is a poorly understood complex disorder, which results in progressive remodeling of the pulmonary artery that ultimately leads to right ventricular failure. A two-hit hypothesis has been implicated in pathogenesis of IPAH, according to which the vascular abnormalities characteristic of PAH are triggered by the accumulation of genetic and/or environmental insults in an already existing genetic background. The multifactor dimensionality reduction (MDR) analysis is a statistical method used to identify gene–gene interaction or epistasis and gene–environment interactions that are associated with a particular disease. The MDR method collapses high-dimensional genetic data into a single dimension, thus permitting interactions to be detected in relatively small sample sizes. AIM: To identify and characterize polymorphisms/genes that increases the susceptibility to IPAH using MDR analysis. MATERIALS AND METHODS: A total of 77 IPAH patients and 100 controls were genotyped for eight polymorphisms of five genes (5HTT, EDN1, NOS3, ALK-1, and PPAR-γ2). MDR method was adopted to determine gene–gene interactions that increase the risk of IPAH. RESULTS: With MDR method, the single-locus model of 5HTT (L/S) polymorphism and the combination of 5HTT(L/S), EDN1(K198N), and NOS3(G894T) polymorphisms in the three-locus model were attributed to be the best models for predicting susceptibility to IPAH, with a P value of 0.05. CONCLUSION: MDR method can be useful in understanding the role of epistatic and gene–environmental interactions in pathogenesis of IPAH.

Association between H-ras and L-myc gene polymorphisms and susceptibility to colorectal cancer / 中华肿瘤杂志

<p><b>OBJECTIVE</b>To explore the association between the polymorphisms of oncogenes H-ras and L-myc and colorectal cancer risk, and the interaction of those genes.</p><p><b>METHODS</b>The genotypes of H-ras and L-myc genes were determined by polymerase chain reaction-based restriction fragment length polymorphism analysis. Stratified analysis and logistic model were used to detect the gene-gene interaction. The gene-gene interaction was validated by multifactor dimensionality reduction (MDR) analysis.</p><p><b>RESULTS</b>The single SNP model showed that the polymorphisms of H-ras and L-myc genes were not significantly related with colorectal cancer risk (P > 0.05). Stratified analysis revealed that among the L-myc LS + SS genotype carriers, those with H-ras TC + CC genotype showed significantly increased risk of rectal cancer than those with TT genotype (OR = 1.81, P = 0.005). The positive interaction between L-myc and H-ras was detected by logistic regression model. The OR of the interaction effect was 2.74 (P = 0.024). This result was confirmed in the MDR model, with 54.83% testing balanced accuracy and 10/10 cross-validation consistency, and the model was still significant after the 1000 times permutation test (P = 0.001).</p><p><b>CONCLUSION</b>Our findings suggest that the polymorphism of H-ras and L-myc genes is not related to colorectal cancer risk, but there is a synergy between H-ras and L-myc polymorphisms in the development of rectal cancer.</p>

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.

Genome-Wide Association Scan of Korean Autism Spectrum Disorders with Language Delay: A Preliminary Study

OBJECTIVE: Communication problems are a prevalent symptom of autism spectrum disorders (ASDs), which have a genetic background. Although several genome-wide studies on ASD have suggested a number of candidate genes, few studies have reported the association or linkage of specific endophenotypes to ASDs. METHODS: Forty-two Korean ASD patients who showed a language delay were enrolled in this study with their parents. We performed a genome-wide scan by using the Affymetrix SNP Array 5.0 platform to identify candidate genes responsible for language delay in ASDs. RESULTS: We detected candidate single-nucleotide polymorphisms (SNPs) in chromosome 11, rs11212733 (p-value=9.76x10(-6)) and rs7125479 (p-value=1.48x10(-4)), as a marker of language delay in ASD using the transmission disequilibrium test and multifactor dimensionality reduction test. CONCLUSION: Although our results suggest that several SNPs are associated with language delay in ASD, rs11212733 we were not able to observe any significant results after correction of multiple comparisons. This may imply that more samples may be required to identify genes associated with language delay in ASD.

Association analysis of polymorphisms of metabolizing enzyme genes with chronic benzene poisoning based on logistic regression and multifactor dimensionality reduction / 中华劳动卫生职业病杂志

<p><b>OBJECTIVE</b>To explore the association of polymorphisms of metabolizing enzyme genes with chronic benzene poisoning (CBP) comprehensively by case-control design.</p><p><b>METHODS</b>152 CBP patients and 152 workers occupationally exposed to benzene without poisoning manifestations were investigated. 30 single nucleotide polymorphisms (SNPs) in 13 genes such as CYP2E1 were tested by PCR-RFLP, sequencing approaches. Logistic regression model was used to detect main effects and 2-order interaction effects of gene and/or environment. Multifactor dimensionality reduction (MDR) was used to detect high-order gene-gene or gene-environment interactions.</p><p><b>RESULTS</b>Based on logistic regression, the main effects of GSTP1 rs947894, EPHX1 rs1051740, CYP1A1 rs4646903, CYP2D6 rs1065852 and rs1135840 were found to be significant (P < 0.05) while the confounding factors of sex, cigarette smoking, alcohol consumption and the intensity of benzene exposure were controlled. EPHX1 rs1051740 might be associated with CBP (P = 0.06). There existed 3 types of interactions were as followed: interactions of GSTP1 rs947894 with alcohol consumption, CYP2E1 rs3813867 with EPHX1 rs3738047, EPHX1 rs3738047 with alcohol consumption(P < 0.05), while the main effects of CYP2E1 rs3813867 and EPHX1 rs3738047 were not significant (P > 0.05). The other SNPs did not show any significant associations with CBP. According to MDR, a 3-order interaction with the strongest combined effect was found, i.e. the 3-factor combination of CYP1A1 rs4646903, CYP2D6 rs1065852 and CYP2D6 rs1135840.</p><p><b>CONCLUSION</b>Gene-gene, gene-environment interactions are important mechanism to genetic susceptibility of CBP.</p>

Lack of Association between Glutathione S-Transferase-M1, -T1, and -P1 Polymorphisms and Olanzapine-Induced Weight Gain in Korean Schizophrenic Patients

OBJECTIVE: Oxidative stress may be an important pathogenic mechanism in the obesity and metabolic syndrome. The aims of this study was to assess the possible association between the oxidative stress related Glutathione S-Transferase genes (GST-M1, GST-T1, and GST-P1) variants and the olanzapine-induced weight gain in Korean schizophrenic patients. METHODS: We categorized 78 schizophrenic patients into two groups the more than 7% weight gain from baseline (weight gain > or =7%) and the less weight gain (weight gain or =7% compared to subjects with body weight gain 0.05). No significant difference in GST-P1 genotype and allele frequencies were observed between the groups (p>0.05). MDR analysis did not show a significant interaction between the three GST gene variants and susceptibility to weight gain (p>0.05). CONCLUSION: These findings do not support a relationship between the genetic variants of three GST genes (GST-M1, -T1 and -P1) and weight gain in Korean schizophrenic patients receiving olanzapine treatment.