Gene-gene interaction analysis for age at onset of bipolar disorder in a Korean population.

BACKGROUND: Multiple genes might interact to determine the age at onset of bipolar disorder. We investigated gene-gene interactions related to age at onset of bipolar disorder in the Korean population, using genome-wide association study (GWAS) data. METHODS: The study population consisted of 303 patients with bipolar disorder. First, the top 1000 significant single-nucleotide polymorphisms (SNPs) associated with age at onset of bipolar disorder were selected through single SNP analysis by simple linear regression. Subsequently, the QMDR method was used to find gene-gene interactions. RESULTS: The best 10 SNPs from simple regression were located in chromosome 1, 2, 3, 10, 11, 14, 19, and 21. Only five SNPs were found in several genes, such as FOXN3, KIAA1217, OPCML, CAMSAP2, and PTPRS. On QMDR analyses, five pairs of SNPs showed significant interactions with a CVC exceeding 1/5 in a two-locus model. The best interaction was found for the pair of rs60830549 and rs12952733 (CVC = 1/5, P < 1E-07). In three-locus models, four combinations of SNPs showed significant associations with age at onset, with a CVC of >1/5. The best three-locus combination was rs60830549, rs12952733, and rs12952733 (CVC = 2/5, P < 1E-6). The SNPs showing significant interactions were located in the KIAA1217, RBFOX3, SDK2, CYP19A1, NTM, SMYD3, and RBFOX1 genes. CONCLUSIONS: Our analysis confirmed genetic interactions influencing the age of onset for bipolar disorder and identified several potential candidate genes. Further exploration of the functions of these promising genes, which may have multiple roles within the neuronal network, is necessary.

Association between Gene Polymorphisms and SNP-SNP Interactions of the Matrix Metalloproteinase 2 Signaling Pathway and the Risk of Vascular Senescence.

Objective: This study aimed to explore the association of single nucleotide polymorphisms (SNP) in the matrix metalloproteinase 2 (MMP-2) signaling pathway and the risk of vascular senescence (VS). Methods: In this cross-sectional study, between May and November 2022, peripheral venous blood of 151 VS patients (case group) and 233 volunteers (control group) were collected. Fourteen SNPs were identified in five genes encoding the components of the MMP-2 signaling pathway, assessed through carotid-femoral pulse wave velocity (cfPWV), and analyzed using multivariate logistic regression. The multigene influence on the risk of VS was assessed using multifactor dimensionality reduction (MDR) and generalized multifactor dimensionality regression (GMDR) modeling. Results: Within the multivariate logistic regression models, four SNPs were screened to have significant associations with VS: chemokine (C-C motif) ligand 2 (CCL2) rs4586, MMP2 rs14070, MMP2 rs7201, and MMP2 rs1053605. Carriers of the T/C genotype of MMP2 rs14070 had a 2.17-fold increased risk of developing VS compared with those of the C/C genotype, and those of the T/T genotype had a 19.375-fold increased risk. CCL2 rs4586 and MMP-2 rs14070 exhibited the most significant interactions. Conclusion: CCL2 rs4586, MMP-2 rs14070, MMP-2 rs7201, and MMP-2 rs1053605 polymorphisms were significantly associated with the risk of VS.

ARID5B, IKZF1, GATA3, CEBPE, and CDKN2A germline polymorphisms and predisposition to childhood acute lymphoblastic leukemia.

Acute lymphoblastic leukemia (ALL) is the most frequent type of pediatric cancer. Germline single nucleotide polymorphisms (SNPs), including ARID5B (rs10821936 T/C), IKZF1 (rs4132601 T/G), GATA3 (rs3824662 G/T), CEBPE (rs2239633 G/A), and CDKN2A (rs3731217 A/C) have been linked to pediatric ALL in different populations. Hitherto, no previous studies have tested the relationship between these SNPs and pediatric ALL in Gaza strip. Therefore, we investigated the association between these polymorphisms and the occurrence of childhood ALL in this part of Palestine. This case-control study recruited 100 healthy controls and 78 ALL patients. Allele-specific PCR (AS-PCR) technique was used for SNPs genotyping. Relevant statistical tests were used and the multifactor dimensionality reduction (MDR) approach was applied in the analysis of gene-gene interactions. Minor alleles of ARID5B rs10821936 T/C (p = 0.007) and IKZF1 rs4132601 T/G (p = 0.045) were significantly higher in ALL patients. The homozygous (TT) genotype of GATA3 rs3824662 G/T (p = 0.038), (CC) of ARID5B rs10821936 T/C (p = 0.008), and (AC and CC) genotypes of CDKN2A rs3731217 A/C (p < 0.0001) were significantly higher in ALL cases. On MDR analysis, the best model for ALL risk was the five-factor model combination of the examined SNPs (CVC = 10/10; TBA = 0.632; p < 0.0001). This work demonstrates the association of ARID5B rs10821936 T/C, IKZF1 rs4132601 T/G, GATA3 rs3824662 G/T, and CDKN2A rs3731217 A/C polymorphisms with increased risk of pediatric ALL among a patient cohort from Gaza Strip. Further studies with a larger sample size are needed in order to confirm these findings and test the value of these SNPs in prognosis and treatment sensitivity.

Interaction between maintenance variables of medical ultrasound scanners through multifactor dimensionality reduction.

BACKGROUND: Proper maintenance of electro-medical devices is crucial for the quality of care to patients and the economic performance of healthcare organizations. This research aims to identify the interaction between Ultrasound scanners (US) maintenance variables as a function of maintenance indicators: US in service or decommissioned, excessive number of failures, and failure rate. Knowing those interactions, specific maintenance measures will be developed to improve the reliability of the US. RESEARCH DESIGN AND METHODS: Multifactor Dimensionality Reduction (MDR) method was eployed to analyze data from 222 US and their four-year maintenance history. Models were developed based on the variables with the greatest influence on maintenance indicators, where US were classified according to the associated risk. RESULTS: US with more than one major failure or at least one major component replacement had up to 496.4% more failures than the average. Failure rate increased by up to 188.7% over the average for those US with more than three moderate failures, three replacements, or both. CONCLUSIONS: This study identifies and quantifies the causes of risk to establish a specific maintenance plan for US. It helps to better understand the degradation of US to optimize their operation and maintenance.

Multifactor dimensionality reduction method identifies novel SNP interactions in the WNT protein interaction networks that are associated with recurrence risk in colorectal cancer.

Background: Interactions among genetic variants are rarely studied but may explain a part of the variability in patient outcomes. Objectives: In this study, we aimed to identify 1 to 3 way interactions among SNPs from five Wnt protein interaction networks that predict the 5-year recurrence risk in a cohort of stage I-III colorectal cancer patients. Methods: 423 patients recruited to the Newfoundland Familial Colorectal Cancer Registry were included. Five Wnt family member proteins (Wnt1, Wnt2, Wnt5a, Wnt5b, and Wnt11) were selected. The BioGRID database was used to identify the proteins interacting with each of these proteins. Genotypes of the SNPs located in the interaction network genes were retrieved from a genome-wide SNP genotype data previously obtained in the patient cohort. The GMDR 0.9 program was utilized to examine 1-, 2-, and 3-SNP interactions using a 5-fold cross validation step. Top GMDR 0.9 models were assessed by permutation testing and, if significant, prognostic associations were verified by multivariable logistic regression models. Results: GMDR 0.9 has identified novel 1, 2, and 3-way SNP interactions associated with 5-year recurrence risk in colorectal cancer. Nine of these interactions were multi loci interactions (2-way or 3-way). Identified interaction models were able to distinguish patients based on their 5-year recurrence-free status in multivariable regression models. The significance of interactions was the highest in the 3-SNP models. Several of the identified SNPs were eQTLs, indicating potential biological roles of the genes they were associated with in colorectal cancer recurrence. Conclusions: We identified novel interacting genetic variants that associate with 5-year recurrence risk in colorectal cancer. A significant portion of the genes identified were previously linked to colorectal cancer pathogenesis or progression. These variants and genes are of interest for future functional and prognostic studies. Our results provide further evidence for the utility of GMDR models in identifying novel prognostic biomarkers and the biological importance of the Wnt pathways in colorectal cancer.

Impact of NOTCH1 polymorphisms on liver cancer in a Chinese Han population.

NOTCH1, a member of the Notch family, is up-expression in advanced liver cancer (LC) patients and is associated with tumor sizes, tumor stage, metastasis, and invasion. A few studies have discovered the contribution of NOTCH1 variants to LC risk. Our purpose was to assess the relationship of NOTCH1 rs10521, rs2229971, and rs4489420 to LC risk. We enrolled 709 LC patients and 708 healthy controls. Genotyping was determined through the Agena MassARRAY system. Multiple genetic models by logistic regression were useful for odds ratios (ORs) with 95% confidence intervals (CIs). Rs10521-G (p = 0.009, OR = 0.75, 95% CI: 0.61-0.93), rs2229971-A (p = 0.023, OR = 0.81, 95% CI: 0.67-0.97), and rs4489420-A (p = 0.014, OR = 0.38, 95% CI: 0.16-0.85) might be protective factors for LC occurrence in the Chinese Han population, especially rs10521 and rs2229971 (false-positive report probability (FPRP) <0.2 and statistical power >90%). Interestingly, stratified analysis displayed that the contribution of NOTCH1 polymorphisms to LC risk might be associated with gender, age, smoking, and drinking. Our data first determined that NOTCH1 rs10521-G, rs2229971-A, and rs4489420-A might be protective factors for LC susceptibility.

The interplay between XPG-Asp1104His polymorphism and reproductive risk factors elevates risk of breast cancer in Tanzanian women: A multiple interaction analysis.

BACKGROUND: Reproductive history and genetics are well-known risk factors of breast cancer (BC). Little is known about how these factors interact to effect BC. This study investigated the association of ten polymorphisms in DNA repair genes with BC susceptibility in the Tanzanian samples and further analyzed the association between reproductive risk factors and disease risk METHODS: A hospital-based case-control study in 263 histopathological confirmed BC patients and 250 age-matched cancer-free controls was carried out. Allelic, genotypic, and haplotype association analyses were executed. Also, multifactor dimensionality reduction (MDR), and interaction dendrogram approaches were performed. RESULTS: The frequency of genotypic and allelic variants of XRCC1-Arg399Gln (rs25487), XRCC2-Arg188His (rs3218536), XRCC3-Thr241Met (rs861539), XPG-Asp1104His (rs17655), and MSH2-Gly322Asp (rs4987188) were significantly different between the groups (p < 0.05). Moreover, XRCC1-Arg399Gln (rs25487), XRCC3-Thr241Met (rs861539), and XPG-Asp1104His (rs17655) were associated with the increased risk of BC in co-dominant, dominant, recessive, and additive genetic-inheritance models (p < 0.05). XRCC1-Arg/Gln genotype indicated a 3.1-fold increased risk of BC in pre-menopausal patients (p = 0.001) while XPG-His/His genotype showed a 1.2-fold increased risk in younger BC patients (<40 years) (p = 0.028). Asp/His+His/His genotypes indicated a 1.3-fold increased risk of BC in PR+ patients and a 1.1-fold decreased risk of BC in luminal-A patients (p = 0.014, p = 0.020, respectively). MDR analysis revealed a positive interaction between BC and the XPG-Asp1104His (rs17655) together with family history of cancer in the first-degree relatives. Dendrogram analysis indicated that the XPG-Asp1104His (rs17655) and family history of cancer in first-degree relatives were significantly synergistic and might be associated with an elevated risk of BC in Tanzania. CONCLUSIONS: The XPG-Asp1104His (rs17655) might exert both independent and interactive effects on BC development in the Tanzanian women.

Genetic polymorphisms in CYP2B6 may be associated with lung cancer risk in the Chinese Han population.

BACKGROUND: Our study aimed to elucidate the association between single nucleotide polymorphisms (SNPs) in CYP2B6 gene and susceptibility to lung cancer (LC). METHODS: Five SNPs in CYP2B6 were genotyped in Chinese Han population (507 cases and 505 controls) utilizing Agena MassARRAY. The relationship between these SNPs and LC susceptibility was assessed using odds ratios, 95% confidence intervals, and χ2 tests. Additionally, multifactor dimensionality reduction was employed to analyze SNP-SNP interactions. Bioinformatics methods were applied to investigate the function of these SNPs. RESULTS: We found that rs2099361 was associated with an increased susceptibility to LC in the codominant model (OR = 1.31, p = 0.045). Stratification analysis revealed the allele G at rs4803418 and the allele T at rs4803420 of CYP2B6 (BMI >24 kg/m2) were significantly linked to decreased susceptibility of LC. Conversely, the allele C at rs12979270 (BMI >24 kg/m2) showed increased susceptibility to LC. Moreover, a robust redundant relationship between rs12979270 and rs4803420 was identified in the study. According to the VannoPortal database, we found that rs4803420, rs12979270 and rs2099361 may modulate the binding affinity of LMNB1, SP1 and HDAC2, respectively. CONCLUSIONS: Our results suggest that SNPs in the CYP2B6 gene play crucial roles in LC susceptibility.

The Enigmatic Etiology of Oculo-Auriculo-Vertebral Spectrum (OAVS): An Exploratory Gene Variant Interaction Approach in Candidate Genes.

The clinical diagnosis of oculo-auriculo-vertebral spectrum (OAVS) is established when microtia is present in association with hemifacial hypoplasia (HH) and/or ocular, vertebral, and/or renal malformations. Genetic and non-genetic factors have been associated with microtia/OAVS. Although the etiology remains unknown in most patients, some cases may have an autosomal dominant, autosomal recessive, or multifactorial inheritance. Among the possible genetic factors, gene−gene interactions may play important roles in the etiology of complex diseases, but the literature lacks related reports in OAVS patients. Therefore, we performed a gene−variant interaction analysis within five microtia/OAVS candidate genes (HOXA2, TCOF1, SALL1, EYA1 and TBX1) in 49 unrelated OAVS Mexican patients (25 familial and 24 sporadic cases). A statistically significant intergenic interaction (p-value < 0.001) was identified between variants p.(Pro1099Arg) TCOF1 (rs1136103) and p.(Leu858=) SALL1 (rs1965024). This intergenic interaction may suggest that the products of these genes could participate in pathways related to craniofacial alterations, such as the retinoic acid (RA) pathway. The absence of clearly pathogenic variants in any of the analyzed genes does not support a monogenic etiology for microtia/OAVS involving these genes in our patients. Our findings could suggest that in addition to high-throughput genomic approaches, future gene−gene interaction analyses could contribute to improving our understanding of the etiology of microtia/OAVS.

Multifactor dimensionality reduction reveals the effect of interaction between ERAP1 and IFIH1 polymorphisms in psoriasis susceptibility genes.

Background: Psoriasis is a common immune-mediated hyperproliferative skin dysfunction with known genetic predisposition. Gene-gene interaction (e.g., between HLA-C and ERAP1) in the psoriasis context has been reported in various populations. As ERAP1 has been recognized as a psoriasis susceptibility gene and plays a critical role in antigen presentation, we performed this study to identify interactions between ERAP1 and other psoriasis susceptibility gene variants. Methods: We validated psoriasis susceptibility gene variants in an independent cohort of 5,414 patients with psoriasis and 5,556 controls. Multifactor dimensionality reduction (MDR) analysis was performed to identify the interaction between variants significantly associated with psoriasis in the validation cohort and ERAP1 variants. We then conducted a meta-analysis of those variants with datasets from exome sequencing, target sequencing, and validation analyses and used MDR to identify the best gene-gene interaction model, including variants that were significant in the meta-analysis and ERAP1 variants. Results: We found that 19 of the replicated variants were identified with p < 0.05 and detected six single-nucleotide polymorphisms of psoriasis susceptibility genes in the meta-analysis. MDR analysis revealed that the best predictive model was that between the rs27044 polymorphism of ERAP1 and the rs7590692 polymorphism of IFIH1 (cross-validation consistency = 9/10, test accuracy = 0.53, odds ratio = 1.32 (95% CI, 1.09-1.59), p < 0.01). Conclusion: Our findings suggest that the interaction between ERAP1 and IFIH1 affects the development of psoriasis. This hypothesis needs to be tested in basic biological studies.

Suggestive evidence of the genetic association of TMOD1 and PTCSC2 polymorphisms with thyroid carcinoma in the Chinese Han population.

BACKGROUND: The purpose of this study was to survey the associations of six single nucleotide polymorphisms (SNPs) in the TMOD1 and PTCSC2 genes with thyroid carcinoma (TC). METHOD: Peripheral blood samples were obtained from 510 patients with TC and 509 normal controls. Six SNPs were genotyped by the Agena MassARRAY platform. Logistic regression was used to evaluate the association between SNPs and TC susceptibility by calculating odds ratios (ORs) and 95% confidence intervals (CIs). SNP-SNP interactions were analyzed by multifactor dimensionality reduction (MDR). RESULTS: Our study showed that rs925489 (OR = 1.45, p = 0.011) and rs965513 (OR = 1.40, p = 0.021) were significantly associated with an increased risk of TC. Rs10982622 decreased TC risk (OR = 0.74, p = 0.025). Further stratification analysis showed that rs10982622 reduced the susceptibility to TC in patients aged ≤ 45 years (OR = 0.69, p = 0.019) and in females (OR = 0.61, p = 0.014). Rs925489 increased TC risk in people aged > 45 years (OR = 1.54, p = 0.044) and in males (OR = 2.34, p = 0.003). In addition, rs965513 was related to an increased risk of TC in males (OR = 2.14, p = 0.007). Additionally, haplotypes in the block (rs925489|rs965513) significantly increased TC risk (p < 0.05). The best predictive model for TC was the combination of rs1052270, rs10982622, rs1475545, rs16924016, and rs925489. CONCLUSION: TMOD1 and PTCSC2 polymorphisms were separately correlated with a remarkable decrease and increase in TC risk based on the analysis.

Genetic Variants in MIR3142HG Contribute to the Predisposition of IgA Nephropathy in a Chinese Han Population.

BACKGROUND: The study aimed to evaluate the association of genetic variants in MIR3142HG with the predisposition of IgA nephropathy (IgAN) in a Chinese Han population. METHODS: Six single-nucleotide polymorphisms (SNPs) in MIR3142HG were chosen for genotyping among 417 IgAN cases and 424 healthy controls using Agena MassARRAY technique. Logistic regression models adjusted for age and gender were used to calculate odds ratios (ORs) and 95% confidence intervals (CI). Haploview and multifactor dimensionality reduction analysis were used to analyze the role of combined SNPs in IgAN risk. RESULTS: Rs17057846-AA genotype (OR = 2.11, 95% CI: 1.04-4.27, p = 0.039) and rs58747524-CC genotype (OR = 1.89, 95% CI: 1.06-3.38, p = 0.032) had the higher risk for IgAN developing in the overall. Interestingly, rs7727115 had a reduced risk for IgAN in females, while rs17057846, rs2961920, and rs58747524 were related to the increased susceptibility to IgAN in females and the subjects with age ≤35 years; moreover, rs17057846 and rs58747524 conferred to the higher risk for Lee's grade ≥III IgAN (p < 0.05 for all). Besides, the combination of rs1582417, rs7727115, and rs2961920 was the best model (testing accuracy = 0.5468, CVC = 10/10, p < 0.001) to predict IgAN predisposition compared to the single SNP alone. CONCLUSIONS: Our study firstly indicated that rs17057846 and rs58747524 in MIR3142HG contributed to the elevated risk for IgAN in a Chinese Han population. These results might provide a new insight for the molecular mechanism in the progression of IgAN.

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.

Melatonin Receptor 1B Genetic Variants on Susceptibility to Gestational Diabetes Mellitus: A Hospital-Based Case-Control Study in Wuhan, Central China.

Purpose: The aim of the study was to find out the associations of Melatonin receptor 1B (MTNR1B) genetic variants with gestational diabetes mellitus (GDM) in Wuhan of central China. Patients and Methods: A hospital-based case-control study that included 1679 women was carried out to explore the associations of MTNR1B single nucleotide polymorphisms (SNPs) with GDM risk, which were analyzed through logistic regression analysis by adjusting age, pre-pregnancy BMI and family history of diabetes. Multifactor dimensionality reduction was applied to determine gene-gene interactions between SNPs. Results: MTNR1B SNPs rs10830962, rs10830963, rs1387153, rs7936247 and rs4753426 were significantly associated with GDM risk (P<0.05). The rs10830962/G, rs10830963/G, rs1387153/T, and rs7936247/T were risk variants, whereas rs4753426/T was protective variant for GDM development. Fasting plasma glucose (FPG) and 1h-plasma glucose (PG) were significantly different among genotypes at rs10830962 and rs10830963, whereas 2h-PG levels were not. Gene-gene interactions were not found among the five SNPs on GDM risk. Conclusion: MTNR1B genetic variants have significant associations but no gene-gene interactions with GDM risk in central Chinese population. Furthermore, MTNR1B SNPs have significant relationships with glycemic traits.

Possible Association Between Polymorphisms in ESR1, COL1A2, BGLAP, SPARC, VDR, and MMP2 Genes and Dental Fluorosis in a Population from an Endemic Region of West Bengal.

Dental fluorosis (DF) is the most prevalent form of fluorosis in India affecting millions of people all over the country. As estrogen receptor 1 (ESR1), collagen type 1 alpha 2 (COL1A2), bone γ-carboxyglutamic acid protein (BGLAP), secreted protein acidic and cysteine-rich (SPARC), vitamin D receptor (VDR), and matrix metallopeptidase 2 (MMP2) genes play critical roles in bone metabolism, bone formation, mineral metabolism, and mineralization, variants in these genes could influence susceptibility to DF. The present study was aimed at evaluating the association between 15 single-nucleotide polymorphisms (SNPs) in the six candidate genes (namely, ESR1, COL1A2, BGLAP, SPARC, VDR, and MMP2) and DF among 132 individuals (case = 71 and control = 61) living in a fluoride endemic region of West Bengal, India. No statistically significant association with disease risk was found when the genotypes and allele frequencies of each of the 15 SNPs was analyzed individually using odd's ratio with 95% confidence interval. "CC" and "AG" haplotypes of the COL1A2 gene showed a borderline association with DF. The present study is the first in India to use multifactor dimensionality reduction (MDR) analysis for identifying gene-gene and gene-environment interactions in fluorosis. The biomarker of serum fluoride showed a significant association with the disease state among the 17 attributes (15 SNPs and 2 biomarkers of urine fluoride and serum fluoride) (P value = 0.011). The best model of MDR analysis with maximized testing accuracy involved two SNPs from the ESR1 gene (rs9340799 and rs2077647) and one SNP from BGLAP gene (rs1543294) (P value < 0.0001).

Associations between WNT signaling pathway-related gene polymorphisms and risks of osteoporosis development in Chinese postmenopausal women: a case-control study.

BACKGROUND: The WNT signaling pathway is involved in the regulation of bone homeostasis, and the effect of WNT signaling pathway-related gene (WNT16 and LRP5) polymorphisms on osteoporosis risk among Chinese postmenopausal women is still unknown. Hence, we performed a case-control study to assess the association of WNT signaling pathway-related gene polymorphisms and osteoporosis risk. METHODS: A total of 1026 women (515 osteoporosis patients and 511 controls) of postmenopausal age who were randomly sampled from Xi'an 630 Hospital (Shaanxi Province, China) were involved in this study. Seven genetic polymorphisms in WNT16 (rs3779381, rs3801387, rs917727 and rs7776725) and LRP5 (rs2291467, rs11228240 and rs12272917) were selected and genotyped using the Agena MassARRAY iPLEX system. The association of the genetic polymorphisms and osteoporosis risk was assessed by odds ratios and 95% confidence intervals. The multifactor dimensionality reduction (MDR) method was conducted to analyze single nucleotide polymorphism (SNP)-SNP interaction. RESULTS: We found that LRP5 polymorphisms (rs2291467, rs11228240 and rs12272917) were significantly associated with a decreased risk of osteoporosis in homozygote, recessive and additive models (p < 0.05). Stratification analysis showed that LRP5 polymorphisms (rs2291467, rs11228240 and rs12272917) significantly decreased the osteoporosis risk in the subgroup of body mass index (BMI) ≤ 24 (p < 0.05) and that individuals carrying a heterozygote genotype of WNT16 polymorphisms (rs3779381, rs3801387, rs917727 and rs7776725) had a higher osteoporosis risk in the subgroup of BMI > 24 (p < 0.05). Two haplotypes (haplotype 1: rs3779381, rs3801387, rs917727 and rs7776725; haplotype 2: rs2291467 and rs11228240) were observed, yet only Trs2291467Trs11228240 and Crs2291467Crs11228240 had a strong association with a decreased risk of osteoporosis (p < 0.05). Additionally, MDR analysis revealed that LRP5 rs2291467 was the best model in single-locus MDR analysis. A seven-locus model including rs3779381-AG, rs7776725-TC, rs3801387-GA and rs917727-TC in WNT16 and rs11228240-CC, rs12272917-TC and rs2291467-CC in LRP5 was the best model in multiple-loci MDR analysis (p < 0.001). These two best models were the most significantly associated with osteoporosis risk. CONCLUSIONS: Our findings suggested that WNT16 and LRP5 genetic polymorphisms are associated with osteoporosis risk among Chinese postmenopausal women.

Spatial rank-based multifactor dimensionality reduction to detect gene-gene interactions for multivariate phenotypes.

BACKGROUND: Identifying interaction effects between genes is one of the main tasks of genome-wide association studies aiming to shed light on the biological mechanisms underlying complex diseases. Multifactor dimensionality reduction (MDR) is a popular approach for detecting gene-gene interactions that has been extended in various forms to handle binary and continuous phenotypes. However, only few multivariate MDR methods are available for multiple related phenotypes. Current approaches use Hotelling's T2 statistic to evaluate interaction models, but it is well known that Hotelling's T2 statistic is highly sensitive to heavily skewed distributions and outliers. RESULTS: We propose a robust approach based on nonparametric statistics such as spatial signs and ranks. The new multivariate rank-based MDR (MR-MDR) is mainly suitable for analyzing multiple continuous phenotypes and is less sensitive to skewed distributions and outliers. MR-MDR utilizes fuzzy k-means clustering and classifies multi-locus genotypes into two groups. Then, MR-MDR calculates a spatial rank-sum statistic as an evaluation measure and selects the best interaction model with the largest statistic. Our novel idea lies in adopting nonparametric statistics as an evaluation measure for robust inference. We adopt tenfold cross-validation to avoid overfitting. Intensive simulation studies were conducted to compare the performance of MR-MDR with current methods. Application of MR-MDR to a real dataset from a Korean genome-wide association study demonstrated that it successfully identified genetic interactions associated with four phenotypes related to kidney function. The R code for conducting MR-MDR is available at https://github.com/statpark/MR-MDR . CONCLUSIONS: Intensive simulation studies comparing MR-MDR with several current methods showed that the performance of MR-MDR was outstanding for skewed distributions. Additionally, for symmetric distributions, MR-MDR showed comparable power. Therefore, we conclude that MR-MDR is a useful multivariate non-parametric approach that can be used regardless of the phenotype distribution, the correlations between phenotypes, and sample size.

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.

Germline Variants and Genetic Interactions of Several EMT Regulatory Genes Increase the Risk of HBV-Related Hepatocellular Carcinoma.

Epithelial-mesenchymal transition (EMT) plays an important role in the development of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC). We hypothesized that germline variants in the major EMT regulatory genes (SNAIL1, ZEB1, ZEB2, TWIST1) may influence the development of HBV-related HCC. We included 421 cases of HBsAg-positive patients with HCC, 1371 cases of HBsAg-positive subjects without HCC [patients with chronic hepatitis B (CHB) or liver cirrhosis (LC)] and 618 cases of healthy controls in the case-control study. Genotype, allele, and haplotype associations in the major EMT regulatory genes were tested. Environment-gene and gene-gene interactions were analysed using the non-parametric model-free multifactor dimensionality reduction (MDR) method. The SNAIL1rs4647958T>C was associated with a significantly increased risk of both HCC (CT+CC vs. TT: OR=1.559; 95% confidence interval [CI], 1.073-2.264; P=0.020) and CHB+LC (CT+CC vs. TT: OR=1.509; 95% CI, 1.145-1.988; P=0.003). Carriers of the TWIST1rs2285681G>C (genotypes CT+CC) had an increased risk of HCC (CG+CC vs. GG: OR=1.407; 95% CI, 1.065-1.858; P=0.016). The ZEB2rs3806475T>C was associated with significantly increased risk of both HCC (P recessive =0.001) and CHB+LC (P recessive<0.001). The CG haplotype of the rs4647958/rs1543442 haplotype block was associated with significant differences between healthy subjects and HCC patients (P=0.0347). Meanwhile, the CT haplotype of the rs2285681/rs2285682 haplotype block was associated with significant differences between CHB+LC and HCC patients (P=0.0123). In MDR analysis, the combination of TWIST1rs2285681, ZEB2rs3806475, SNAIL1rs4647958 exhibited the most significant association with CHB+LC and Health control in the three-locus model. Our results suggest significant single-gene associations and environment-gene/gene-gene interactions of EMT-related genes with HBV-related HCC.

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.