Gene-Gene Interaction Analysis in Alzheimer

The COL1A1 and COL5A1 variants have been associated with the risk of musculoskeletal injuries. Therefore, the main aim of the study was to investigate the association between three polymorphisms within two genes (rs1800012 in COL1A1, as well as rs12722 and rs13946 in COL5A1) and the reported, yet rarely described in the literature, injuries of the joint and muscle area in a physically active Caucasian population. Polish students (n = 114) were recruited and divided into the following two groups: students with (n = 53) and without (n = 61) injures. Genotyping was carried out using real-time PCR. The results obtained revealed a statistically significant association between rs1800012 COL1A1 and injury under an overdominant model. Specifically, when adjusted for age and sex, the GT heterozygotes had a 2.2 times higher chance of being injured compared with both homozygotes (TT and GG, 95% CI 0.59–5.07, p = 0.040). However, no significant interaction between the COL5A1 variants, either individually or in haplotype combination, and susceptibility to injury were found. In addition, the gene–gene interaction analysis did not reveal important relationships with the musculoskeletal injury status. It was demonstrated that rs1800012 COL1A1 may be positively associated with physical activity-related injuries in a Caucasian population. Harboring the specific GT genotype may be linked to a higher risk of being injured.

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Graphical modeling based gene interaction analysis for microarray data

ACM SIGKDD Explorations Newsletter ◽

10.1145/980972.980984 ◽

2003 ◽

Vol 5 (2) ◽

pp. 91-100 ◽

Cited By ~ 3

Author(s):

Xintao Wu ◽

Yong Ye ◽

Liying Zhang

Keyword(s):

Microarray Data ◽

Interaction Analysis ◽

Gene Interaction ◽

Graphical Modeling

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A circular RNAs dataset landscape reveals potential signatures for the detection and prognosis of early-stage lung adenocarcinoma

BMC Cancer ◽

10.1186/s12885-021-08293-7 ◽

2021 ◽

Vol 21 (1) ◽

Author(s):

Zhiying Chen ◽

Jiahui Wei ◽

Min Li ◽

Yongjuan Zhao

Keyword(s):

Functional Analysis ◽

Survival Analysis ◽

Lung Adenocarcinoma ◽

Target Genes ◽

Interaction Analysis ◽

Early Stage ◽

Gene Interaction ◽

Gene Expression Omnibus ◽

Circular Rnas ◽

Cerna Network

Abstract Background This study aimed to identify potential circular ribonucleic acid (circRNA) signatures involved in the pathogenesis of early-stage lung adenocarcinoma (LAC). Methods The circRNA sequencing dataset of early-stage LAC was downloaded from the Gene Expression Omnibus database. First, the differentially expressed circRNAs (DEcircRNAs) between tumour and non-tumour tissues were screened. Then, the corresponding miRNAs and their target genes were predicted. In addition, prognosis-related genes were identified using survival analysis and further used to build a network of competitive endogenous RNAs (ceRNAs; DEcircRNA–miRNA–mRNA). Finally, the functional analysis and drug–gene interaction analysis of mRNAs in the ceRNA network was performed. Results A total of 35 DEcircRNAs (30 up-regulated and 5 down-regulated circRNAs) were identified. Moreover, 135 DEcircRNA–miRNA and 674 miRNA–mRNA pairs were predicted. The survival analysis of these target mRNAs revealed that 60 genes were significantly associated with survival outcomes in early-stage LAC. Of these, high levels of PSMA 5 and low levels of NAMPT, CPT 2 and TNFSF11 exhibited favourable prognoses. In addition, the DEcircRNA–miRNA–mRNA network was constructed, containing 5 miRNA–circRNA (hsa_circ_0092283/hsa-miR-762/hsa-miR-4685-5p; hsa_circ_0070610/hsa-let-7a-2-3p/hsa-miR-3622a-3p; hsa_circ_0062682/hsa-miR-4268) and 60 miRNA–mRNA pairs. Functional analysis of the genes in the ceRNA network showed that they were primarily enriched in the Wnt signalling pathway. Moreover, PSMA 5, NAMPT, CPT 2 and TNFSF11 had strong correlations with different drugs. Conclusion Three circRNAs (hsa_circ_0062682, hsa_circ_0092283 and hsa_circ_0070610) might be potential novel targets for the diagnosis of early-stage LAC.

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

Genomics & Informatics ◽

10.5808/gi.2016.14.4.166 ◽

2016 ◽

Vol 14 (4) ◽

pp. 166 ◽

Cited By ~ 4

Author(s):

Seungyeoun Lee ◽

Donghee Son ◽

Wenbao Yu ◽

Taesung Park

Keyword(s):

Failure Time ◽

Interaction Analysis ◽

Gene Interaction ◽

Accelerated Failure Time Model ◽

Accelerated Failure Time ◽

Time Model ◽

Multifactor Dimensionality Reduction Method ◽

Accelerated Failure ◽

Dimensionality Reduction Method ◽

Failure Time Model

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Unified Cox model based multifactor dimensionality reduction method for gene-gene interaction analysis of the survival phenotype

BioData Mining ◽

10.1186/s13040-018-0189-1 ◽

2018 ◽

Vol 11 (1) ◽

Cited By ~ 1

Author(s):

Seungyeoun Lee ◽

Donghee Son ◽

Yongkang Kim ◽

Wenbao Yu ◽

Taesung Park

Keyword(s):

Dimensionality Reduction ◽

Multifactor Dimensionality Reduction ◽

Reduction Method ◽

Interaction Analysis ◽

Cox Model ◽

Gene Interaction ◽

Model Based ◽

Multifactor Dimensionality Reduction Method ◽

Dimensionality Reduction Method

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Interaction of miR-181b and IFNA1 Polymorphisms on the Risk of Systemic Lupus Erythematosus

BioMed Research International ◽

10.1155/2020/4757065 ◽

2020 ◽

Vol 2020 ◽

pp. 1-7

Author(s):

Yong-Ling He ◽

Jun Yang ◽

Zhi-Neng Zeng ◽

Xiang Shi

Keyword(s):

Systemic Lupus Erythematosus ◽

Quantitative Pcr ◽

Lupus Erythematosus ◽

Interaction Analysis ◽

Gene Interaction ◽

Systemic Lupus ◽

Locus Model ◽

Increased Risk ◽

Phenotype Analysis ◽

Combined Genotypes

Introduction. A previous work has discovered that chromosome 1q32 locus linked to the risk of systemic lupus erythematosus (SLE) and miR-181b located on the susceptibility site with downregulation inversely correlating to its target molecular interferon alpha 1 (IFNA1). The purpose of this study was to investigate the association of miR-181b and IFNA1 polymorphisms with IS risk. Methods. The miR-181b rs322931, IFNA1 rs1332190, and rs10811543 were genotyped using a Multiplex SNaPshot assay. miR-181b expression levels in plasma of SLE patients and controls were analyzed using quantitative PCR. Results. The rs322931 CT, CT/TT, and T allele exerted an increased trend of SLE risk (CT vs. CC: adjusted OR=1.71, 95% CI 1.16-2.50, P=0.01; CT/TT vs. CC: adjusted OR=1.45, 95% CI 1.08-1.95, P=0.01; T vs. C: adjusted OR=1.38, 95% CI 1.07-1.79, P=0.01). Combined genotypes of the rs322931 CT/TT+rs1332190 TT and the rs322931 CC+rs10811543 AG/AA also revealed an increased risk of SLE. Gene-gene interaction analysis showed that a three-locus model consisting of rs322931, rs1332190, and rs10811543 attributed an increased risk of SLE. Further genotype-phenotype analysis revealed that rs322931 CT/TT carriers displayed lower levels of miR-181b. Conclusions. These findings indicate that the miR-181b rs322931 may be singly and jointly responsible for the etiology of SLE by altering miR-181b expression.

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

International Journal of Genomics ◽

10.1155/2017/7208318 ◽

2017 ◽

Vol 2017 ◽

pp. 1-9 ◽

Cited By ~ 7

Author(s):

Ying Meng ◽

Susan Groth ◽

Jill R. Quinn ◽

John Bisognano ◽

Tong Tong Wu

Keyword(s):

Interaction Analysis ◽

Association Studies ◽

Independent Set ◽

Gene Interaction ◽

Single Locus ◽

Gene Interactions ◽

Genome Wide Association Studies ◽

Original Cohort ◽

Genome Wide ◽

Heart Study

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

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