Gene-gene Interaction Analysis Research Articles

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

BackgroundMultiple 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. MethodsThe 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. ResultsThe 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. ConclusionsOur 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.

LncRNA RP11-10E18.7 cooperates with lncRNA RP11-481C4.2 to affect the overall survival of breast cancer patients: a TCGA-based retrospective study.

As either oncogenes or tumor suppressor genes, long non-coding RNAs (lncRNAs) have a major role in both tumorigenesis and progression of human cancers, including breast cancer (BC). However, the statistical correlation between the lncRNA-lncRNA interaction and prognosis of BC remains unclear. We analyzed the fragments per kilobase per million (FPKM) lncRNA expression data in tumor tissue samples from 890 female patients with BC in The Cancer Genome Atlas (TCGA) between May 2021 and October 2022. The Cox proportional hazards model adjusted for age, race, clinical stage, neoadjuvant therapy, estrogen receptor (ER), and progesterone receptor (PR) was adopted to evaluate the lncRNA-lncRNA interaction regarding overall survival (OS) of BC. The multiple comparison was corrected by Bonferroni method. RP11-10E18.7×RP11-481C4.2 was significantly associated with OS of BC patients [hazard ratio (HR)interaction =1.04, 95% confidence interval (CI): 1.03-1.06, P=3.35×10-9]. Then, gene-gene interaction analysis was performed for genes co-expressed with lncRNAs. FOXA1×U2SURP (HRinteraction =1.49, 95% CI: 1.28-1.73, P=2.16×10-7) was found to have a similar interactive pattern to RP11-10E18.7×RP11-481C4.2. after classifying the patients by intersection (3.47), we observed that the effect of FOXA1 opposite in patients with different U2SURP expression level (HRhigh vs. low =0.58, 95% CI: 0.34-0.99, P=0.046 in low expression of U2SURP; HRhigh vs. low =1.56, 95% CI: 1.18-2.87, P=0.029 in high expression of U2SURP). Our comprehensive study identified RP11-10E18.7×RP11-481C4.2 as a potential biomarker of BC prognosis. The results play an essential role in the impact of lncRNA-lncRNA interaction on BC survival. Our findings elucidated potential molecular mechanisms of BC progression under complex association patterns and provided potential dynamic and reversible therapeutic targets for BC patients.

Association of MMP1 gene polymorphisms with breast cancer risk: A narrative review.

Breast cancer is a multifactorial malignancy with different clinicopathological and molecular characteristics. It is the most frequent cancer in women in terms of both incidence and mortality. Matrix metallopeptidase 1 or MMP1 is a zinc-dependent endopeptidase associated with several physiological processes through the modification of the extracellular matrix and tumor microenvironment. However, previous results did not suggest any concluding remarks on the correlation between MMP1 gene polymorphisms and the risk of breast cancer. A comprehensive literature search was performed in PubMed database to retrieve relevant articles and extract data from suitable ones. The literature written only in English was selected for this review. A total of 26 articles were included in the present narrative review. From the available studies, it is observed that MMP1 is upregulated in breast cancer tissues and found to be correlated with metastasis and invasion. The expression of MMP1 gene is mediated by numerous factors, including polymorphisms which act as a potential risk factor for the progression of breast cancer. To establish the correlation between genetic polymorphisms in MMP1 and the risk of breast cancer, several case-control studies, as well as genetic analyses, have been carried out in different ethnicities. The association of genetic polymorphisms in MMP1 with the risk and survival of breast cancer in different populations has been reviewed in this study. Moreover, the structural domain of MMP1 and the role of MMP1 in breast cancer metastasis and invasion are also discussed which will help to understand the potential impact of MMP1 as a genetic biomarker. This review provides an overview of the MMP1 gene polymorphisms in breast cancer. However, we recommend future studies concentrating on combined analysis of multiple SNPs, gene-gene interactions, and analysis of epigenetics, proteomics, and posttranscriptional modifications that will provide the best outcome.

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.

Genome-wide case-only analysis of gene-gene interactions with known Parkinson’s disease risk variants reveals link between LRRK2 and SYT10

The effects of one genetic factor upon Parkinson’s disease (PD) risk may be modified by other genetic factors. Such gene-gene interaction (G×G) could explain some of the ‘missing heritability’ of PD and the reduced penetrance of known PD risk variants. Using the largest single nucleotide polymorphism (SNP) genotype data set currently available for PD (18,688 patients), provided by the International Parkinson’s Disease Genomics Consortium, we studied G×G with a case-only (CO) design. To this end, we paired each of 90 SNPs previously reported to be associated with PD with one of 7.8 million quality-controlled SNPs from a genome-wide panel. Support of any putative G×G interactions found was sought by the analysis of independent genotype-phenotype and experimental data. A total of 116 significant pairwise SNP genotype associations were identified in PD cases, pointing towards G×G. The most prominent associations involved a region on chromosome 12q containing SNP rs76904798, which is a non-coding variant of the LRRK2 gene. It yielded the lowest interaction p-value overall with SNP rs1007709 in the promoter region of the SYT10 gene (interaction OR = 1.80, 95% CI: 1.65–1.95, p = 2.7 × 10−43). SNPs around SYT10 were also associated with the age-at-onset of PD in an independent cohort of carriers of LRRK2 mutation p.G2019S. Moreover, SYT10 gene expression during neuronal development was found to differ between cells from affected and non-affected p.G2019S carriers. G×G interaction on PD risk, involving the LRRK2 and SYT10 gene regions, is biologically plausible owing to the known link between PD and LRRK2, its involvement in neural plasticity, and the contribution of SYT10 to the exocytosis of secretory vesicles in neurons.

A novel prognostic biomarker: GINS3 is correlated with methylation and immune escape in liver hepatocellular carcinoma.

Liver cancer remains one of the tricky malignancies nowadays. GINS complex subunit 3 (GINS3), part of the GINS tetrameric complex, is significantly upregulated in many cancers, including liver hepatocellular carcinoma (LIHC). With the development of liver cancer treatment, immune and molecular targeted therapy gradually becomes a promising treatment. However, the key target for liver cancer is still indistinct. Herein, the underneath mechanism of GINS3 was investigated to verify its role as a biomarker in LIHC. Genomic expression, genetic alteration, and methylation analyses were obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTAC), The University of Alabama at Birmingham CANcer (UALCN), and Human Protein Atlas (HPA), cBioPortal, and MethSurv databases. Subsequently, the diagnostic and prognostic role of GINS3 in LIHC were analyzed based on data from receiver operating characteristic (ROC), Kaplan-Meier plotter (KM-plotter), and univariate and multivariate cox regression analyses. The functional analyses were conducted with GeneMANIA and STRING databases, gene-gene, and protein-protein interaction (PPI) networks, Gene Ontology (GO) term, and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses. Tumor Immune Estimation Resource (TIMER), Tumor-Immune System Interaction Database (TISIDB), and Gene Expression Profiling Interactive Analysis (GEPIA) were utilized to explore the internal connection with the immune escape. Through the analyses of genomic expression, GINS3 was significantly upregulated in LIHC and positively correlated with higher T classification. ROC analysis indicated GINS3 as a potential biomarker in the diagnosis of LIHC. KM-plotter, univariate and multivariate cox regression analyses both associated GINS3 with poor prognosis in LIHC patients. GINS3 genetic alteration, gene-gene interaction, PPI networks, and enrichment analysis further revealed that GINS3 played a pivotal role in the progression of LIHC. Furthermore, hypermethylation of GINS3 at different cytosine-guanine (CpG) sites was correlated with better or worse overall survival (OS) in LIHC and GINS3 was also closely correlated with m6A modification. Moreover, results supported that GINS3 could influence the tumor microenvironment and relate to the immune checkpoints. Taken together, comprehensive analyses from this study supported GINS3 as a novel targeted biomarker in LIHC.

Genetic polymorphisms of pri-let-7f, gene-environment and gene-gene interactions, and associations with ischemic stroke risk in Liaoning Province.

The incidence of stroke has been rising annually and investigations into traditional risk factors have led to increased attention on genetic factors. In this study, we focused on the pri-let-7f gene, and investigated the association between pri-let-7f gene polymorphisms and ischemic stroke (IS). This case-control study included 1803 patients and 1456 healthy controls of Han ethnicity living in Liaoning Province. We carried out genotyping analysis of two loci, pri-let-7f-1 rs10739971 and pri-let-7f-2 rs17276588, and performed statistical analysis controlling for confounding factors by logistic regression. The A alleles and AA genotypes of both loci were significantly associated with an increased risk of IS. Variant genotypes of rs17276588 may also increase the risk of IS in females with alcohol intake. Gene-gene interaction analysis showed combined effects of mutations in both these single nucleotide polymorphisms (SNPs). This study demonstrated an association between pri-let-7f SNPs and IS, providing potential latent biomarkers for the risk of IS. However, more detailed studies are needed to clarify these results.

Revolutionizing DNA repair research and cancer therapy with CRISPR-Cas screens.

All organisms possess molecular mechanisms that govern DNA repair and associated DNA damage response (DDR) processes. Owing to their relevance to human disease, most notably cancer, these mechanisms have been studied extensively, yet new DNA repair and/or DDR factors and functional interactions between them are still being uncovered. The emergence of CRISPR technologies and CRISPR-based genetic screens has enabled genome-scale analyses of gene-gene and gene-drug interactions, thereby providing new insights into cellular processes in distinct DDR-deficiency genetic backgrounds and conditions. In this Review, we discuss the mechanistic basis of CRISPR-Cas genetic screening approaches and describe how they have contributed to our understanding of DNA repair and DDR pathways. We discuss how DNA repair pathways are regulated, and identify and characterize crosstalk between them. We also highlight the impacts of CRISPR-based studies in identifying novel strategies for cancer therapy, and in understanding, overcoming and even exploiting cancer-drug resistance, for example in the contexts of PARP inhibition, homologous recombination deficiencies and/or replication stress. Lastly, we present the DDR CRISPR screen (DDRcs) portal , in which we have collected and reanalysed data from CRISPR screen studies and provide a tool for systematically exploring them.

Identification of RALA as a Therapeutic Target and Prognostic Predictor of Osteosarcoma.

Osteosarcoma (OS) is the most common primary aggressive sarcoma of bone, with massive aberrant expression of oncogenes related to the development of OS. RALA, a kind of small Ras-like guanosine triphosphatases, has been identified as a potential therapeutic target in several types of tumor, but its role in OS remains largely unknown. Abnormal expression of RALA was proven in the Cancer Genome Atlas (TCGA), Genotype-Tissue Expression (GTEx), Therapeutically Applicable Research to Generate Effective Treatments (TARGET), and RNA-sequence of samples and cell lines. The role of RALA in OS was analyzed in terms of DNA methylation, immune cell infiltration, and patient survival. The cancer-promoting effect of RALA was demonstrated in cell lines and xenograft osteosarcoma models. A prognostic scoring model incorporating RALA as an indicator was established with the clinical samples that we collected. The results showed that RALA was highly expressed in human OS tissues and cell lines. Survival analysis demonstrated that RALA was the sole independent risk factor for poor overall survival and disease-free survival in OS patients and impacted the proportion of infiltrating immune cells and DNA methylation in the OS tumor microenvironment. By gene-gene interaction analysis, we found that the expression of RALA was highly correlated to the expression of ABCE1. Similar to RALA, upregulated ABCE1 is correlated with poor survival outcome of OS patients. In addition, the functional experiment demonstrated that higher expression of RALA promoted the proliferation, migration, and invasion of OS cells. In vivo results were similar with the in vitro results. We examined m6a methylation-related genes and found that m6A methylation is responsible for the abnormal expression of RALA. Finally, the prognostic prediction model of RALA could be used to predict the long-term outcome of OS patients. We identified RALA as an oncogene in OS, and RALA upregulation in a concerted manner with ABCE1 was significantly associated with worse outcomes of OS patients. Targeting RALA may prove to be a novel target for OS immunotherapy in future clinical practice.

DBDPE upregulates NOD-like receptor signaling to induce NLRP3 inflammasome-mediated HAECs pyroptosis

Decabromodiphenyl ethane (DBDPE), a typical new brominated flame retardant (BFR), is a widespread new pollutant in the environment. Several studies and our previous studies have found that DBDPE can cause aortic endothelial injury and aortic endothelial cell pyroptosis, whereas the molecular mechanism involved has not been elucidated. In this study, we exposed human aortic endothelial cells (HAECs) to 25 μmol/L of DBDPE and analyzed the gene expression profiles by Affymetrix PrimeView™ Human Gene Expression Chip. The results showed that 886 genes were differentially expressed in the DBDPE exposure group. Enrichment analyses revealed that differentially expressed genes were mainly enriched in the inflammatory response and NOD-like receptor signal pathway. Gene-gene functional interaction analyses and crossover genes and pathways analyses found that the NOD-like receptor signal pathway may be involved in regulating NLRP3 and IL-18. We found that NOD2 cannot interact with NLRP3 directly through an immunoprecipitation experiment. Thus, we construct the RIPK2 knockdown HAECs cell line to repress the NOD-like receptor signaling and further study the mechanism of DBDPE-activated NLRP3 inflammasome to induce HAECs pyroptosis. The results showed that RIPK2 knockdown could repress DBDPE-induced NOD-like receptor signaling pathway upregulation, inhibit NLRP3 inflammasome activation, and decrease HAECs pyroptosis. In addition, RIPK2 knockdown decreased the ROS generation in HAECs induced by DBDPE. And NAC pretreated HAECs inhibited DBDPE-induced NLRP3 inflammasome activation and HAECs pyroptosis. These results demonstrated that DBDPE upregulated NOD-like receptor signaling to induce ROS generation and, in turn, activated NLRP3 inflammasome, leading to HAECs pyroptosis.

Two-level Bayesian interaction analysis for survival data incorporating pathway information.

Genetic interactions play an important role in the progression of complex diseases, providing explanation of variations in disease phenotype missed by main genetic effects. Comparatively, there are fewer studies on survival time, given its challenging characteristics such as censoring. In recent biomedical research, two-level analysis of both genes and their involved pathways has received much attention and been demonstrated as more effective than single-level analysis. However, such analysis is usually limited to main effects. Pathways are not isolated, and their interactions have also been suggested to have important contributions to the prognosis of complex diseases. In this paper, we develop a novel two-level Bayesian interaction analysis approach for survival data. This approach is the first to conduct the analysis of lower-level gene-gene interactions and higher-level pathway-pathway interactions simultaneously. Significantly advancing from the existing Bayesian studies based on the Markov Chain Monte Carlo (MCMC) technique, we propose a variational inference framework based on the accelerated failure time model with effective priors to accommodate two-level selection as well as censoring. Its computational efficiency is much desirable for high-dimensional interaction analysis. We examine performance of the proposed approach using extensive simulation. The application to TCGA melanoma and lung adenocarcinoma data leads to biologically sensible findings with satisfactory prediction accuracy and selectionstability.

Association of Polymorphisms in NHEJ Pathway Genes with HIV-1 Infection and AIDS Progression in a Northern Chinese MSM Population.

Background and Aims Men who have sex with men (MSM) are at high risk of HIV infection. The nonhomologous end joining (NHEJ) pathway is the main way of double-stranded DNA break (DSB) repair in the higher eukaryotes and can repair the DSB timely at any time in cell cycle. It is also indicated that the NHEJ pathway is associated with HIV-1 infection since the DSB in host genome DNA occurs in the process of HIV-1 integration. The aim of the present investigation was to evaluate associations of single-nucleotide polymorphisms (SNPs) in NHEJ pathway genes with susceptibility to HIV-1 infection and AIDS progression among MSM residing in northern China. Methods A total of 481 HIV-1 seropositive men and 493 HIV-1 seronegative men were included in this case-control study. Genotyping of 22 SNPs in NHEJ pathway genes was performed using the SNPscan™ Kit. Results Positive associations were observed between XRCC6 rs132770 and XRCC4 rs1056503 genotypes and the susceptibility to HIV-1 infection. In gene-gene interaction analysis, significant SNP-SNP interactions of XRCC6 and XRCC4 genetic variations were found to play a potential role in the risk of HIV-1 infection. In stratified analysis, XRCC5 rs16855458 was significantly associated with CD4+ T cell counts in AIDS patients, whereas LIG4 rs1805388 was linked to the clinical phases of AIDS patients. Conclusions NHEJ gene polymorphisms can be considered to be risk factors of HIV-1 infection and AIDS progression in the northern Chinese MSM population.

Cytokine gene variants of TNF-α and IL-10 in the propensity of type 2 diabetes in south Indian population

Chronic inflammation plays an important role in type 2 diabetes mellitus (T2DM), a common endocrinological pro-inflammatory disorder associated with insulin resistance. The objective of the present study is to see individual and combined effect of TNF-α (rs361525, rs1800629) and IL-10 (rs1800872, rs1800896) genes on T2DM susceptibility The genotyping was carried out in 200 T2DM patients and 200 healthy controls by polymerase chain reaction–restriction fragment length polymorphism (PCR–RFLP) using suitable primers. The results shown that TNF-α (GA of rs361525 & rs1800629) and IL-10 (AA of rs1800872 & GA of rs1800896) genes are significantly linked with T2DM development. The presence of AA-GA genotype combination for both TNF-α and IL-10 genes were elevating the risk of T2DM. Moreover, individuals bearing haplotypes AAAA, AACA and AAAG experience the increased risk of T2DM. Furthermore, gene-gene interaction analysis shown that TNF-α (GA of rs361525 & rs1800896) gene redundantly confer 3.4-fold elevated risk for T2DM. In gene-environment interaction, GA of TNF-α −1800896, W/H ratio and TG/HDL ratio were redundantly interacted each other and increase the risk of T2DM by 67-times. In conclusion, our results reveal that there is a significant association between foresaid TNF-α, IL-10 gene promoter polymorphisms and T2DM development. To the best of our knowledge this study is the first of its kind in the literature reporting the epistatic association of TNF-α (rs1800629G/A) gene with TG/HDL ratio and W/H ratio over IL-10 gene polymorphisms for T2DM susceptibility among south Indians.

Association of maternal MTHFD1 and MTHFD2 gene polymorphisms with congenital heart disease in offspring

To study the association of maternal methylenetetrahydrofolate dehydrogenase 1 (MTHFD1) and methylenetetrahydrofolate dehydrogenase 2 (MTHFD2) gene polymorphisms with congenital heart disease (CHD) in offspring. A hospital-based case-control study was conducted. The mothers of 683 children with CHD alone who attended Hunan Children's Hospital, from November 2017 to March 2020 were enrolled as the case group, and the mothers of 740 healthy children who attended the same hospital during the same period and did not have any deformity were enrolled as the control group. A questionnaire survey was performed to collect related exposure data, and then venous blood samples (5 mL) were collected from the mothers to detect MTHFD1 and MTHFD2 gene polymorphisms. A multivariate logistic regression analysis was used to evaluate the association of MTHFD1 and MTHFD2 gene polymorphisms with CHD. The four-gamete test in Haploview 4.2 software was used to construct haplotypes and evaluate the association between haplotypes and CHD. The generalized multifactor dimensionality reduction method and logistic regression analysis were used to examine gene-gene interaction and its association with CHD. The multivariate logistic regression analysis showed that maternal MTHFD1 gene polymorphisms at rs11849530 (GA vs AA: OR=1.49; GG vs AA: OR=2.04) andat rs1256142 (GA vs GG: OR=2.34; AA vs GG: OR=3.25) significantly increased the risk of CHD in offspring (P<0.05), while maternal MTHFD1 gene polymorphisms at rs1950902 (AA vs GG: OR=0.57) and MTHFD2 gene polymorphisms at rs1095966 (CA vs CC: OR=0.68) significantly reduced the risk of CHD in offspring (P<0.05). The haplotypes of G-G-G (OR=1.86) and G-A-G (OR=1.35) in mothers significantly increased the risk of CHD in offspring (P<0.05). The gene-gene interaction analyses showed that the first-order interaction between MTHFD1 rs1950902 and MTHFD1 rs2236222 and the second-order interaction involving MTHFD1 rs1950902, MTHFD1 rs1256142, and MTHFD2 rs1095966 might be associated with risk of CHD (P<0.05). Maternal MTHFD1 and MTHFD2 gene polymorphisms and their haplotypes, as well as the interaction between MTHFD1 rs1950902 and MTHFD1 rs2236222 and between MTHFD1 rs1950902, MTHFD1 rs1256142, and MTHFD2 rs1095966, are associated with the risk of CHD in offspring.

Association of Maternal Betaine-Homocysteine Methyltransferase (BHMT) and BHMT2 Genes Polymorphisms with Congenital Heart Disease in Offspring.

To systematically explore the association of single nucleotide polymorphisms (SNPs) of maternal BHMT and BHMT2 genes with the risk of congenital heart disease (CHD) and its three subtypes including atrial septal defect (ASD), ventricular septal defect (VSD), and patent ductus arteriosus (PDA) in offspring. A hospital-based case-control study involving 683 mothers of CHD children and 740 controls was performed. Necessary exposure information was captured through epidemiological investigation. Totally twelve SNPs of maternal BHMT and BHMT2 genes were detected and analyzed systematically. The study showed that maternal BHMT gene polymorphisms at rs1316753 (CG vs. CC: OR = 1.96 [95% CI 1.41-2.71]; GG vs. CC: OR = 1.99 [95% CI 1.32-3.00]; dominant model: OR = 1.97 [95% CI 1.44-2.68]) and rs1915706 (TC vs. TT: OR = 1.93 [95% CI 1.44-2.59]; CC vs. TT: OR = 2.55 [95% CI 1.38-4.72]; additive model: OR = 1.77 [95% CI 1.40-2.24]) were significantly associated with increased risk of total CHD in offspring. And two haplotypes were observed to be significantly associated with risk of total CHD, including C-C haplotype involving rs1915706 and rs3829809 in BHMT gene (OR = 1.30 [95% CI 1.07-1.58]) and C-A-A-C haplotype involving rs642431, rs592052, rs626105, and rs682985 in BHMT2 gene (OR = 0.71 [95% CI 0.58-0.88]). Besides, a three-locus model involving rs1316753 (BHMT), rs1915706 (BHMT), and rs642431 (BHMT2) was identified through gene-gene interaction analyses (P < 0.01). As for three subtypes including ASD, VSD, and PDA, significant SNPs and haplotypes were also identified. The results indicated that maternal BHMT gene polymorphisms at rs1316753 and rs1915706 are significantly associated with increased risk of total CHD and its three subtypes in offspring. Besides, significant interactions between different SNPs do exist on risk of CHD. Nevertheless, studies with larger sample size in different ethnic populations and involving more SNPs in more genes are expected to further define the genetic contribution underlying CHD and its subtypes.

Interaction of CCND2, CDKN1A, and POLD3 Variants in Mexican Patients with Colorectal Cancer.

Colorectal cancer is the second cause of death by cancer around the world. Sporadic colorectal cancer is the most frequent (75%), and it is produced by the interaction of environmental, epigenetic, and genetic factors. The accumulation of single-nucleotide variants in genes associated with cell proliferation, DNA repair, and/or apoptosis could confer a risk to cancer. The aim of this study was to analyze the gene-gene interactions among CCND2 (rs3217901), CDKN1A (rs1059234 and rs1801270), and POLD3 (rs3824999) variants in Mexican patients with colorectal cancer. We collected peripheral blood samples from 185 patients with sporadic colorectal cancer before treatment and from 185 unrelated blood donors as the reference group; all participants signed an informed consent form. DNA extraction was performed by Miller and Cetyltrimethylammonium bromide (CTAB)/ Dodecyltrimethylammonium bromide (DTAB) methods. Polymerase chain reaction- restriction fragment length polymorphism followed by polyacrylamide gel electrophoresis stained with AgNO3 methods were used to identify the variants rs3217901, rs1059234, rs1801270, and rs3824999. Odds ratio and single-nucleotide variant interaction were determined by single-locus analysis and Multifactorial Dimensionality Reduction software, respectively. No association was found for CCND2 and CDKN1A variants; yet, a significant association for the GG genotype, G allele, and recessive and additive models for the POLD3 variant was observed (P < .05). The single-nucleotide variant-single-nucleotide variant interaction revealed the combination rs1059234, rs3217901, and rs3824999 as the best model and the comparison showed an increased risk (P < .05). Single-locus and gene-gene interaction analyses disclosed that both the rs3824999 (POLD3) variant and the combination of rs3217901 (CCND2), rs1059234 (CDKN1A), and rs3824999 (POLD3) genotypes increase the risk for colorectal cancer in Mexican population.

ZNF384: A Potential Therapeutic Target for Psoriasis and Alzheimer's Disease Through Inflammation and Metabolism.

BackgroundPsoriasis is an immune-related skin disease notable for its chronic inflammation of the entire system. Alzheimer’s disease (AD) is more prevalent in psoriasis than in the general population. Immune-mediated pathophysiologic processes may link these two diseases, but the mechanism is still unclear. This article aimed to explore potential molecular mechanisms in psoriasis and AD.MethodsGene expression profiling data of psoriasis and AD were acquired in the Gene Expression Omnibus (GEO) database. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were first applied in two datasets. Differentially expressed genes (DEGs) of two diseases were identified, and common DEGs were selected. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed to explore common biological pathways. Signature transcription factors (STFs) were identified and their diagnostic values was calculated by receiver operating characteristic (ROC) curve analysis in the exploration cohort and verified in the validation cohort. The expression levels of STFs were further investigated in the validation cohort and the GTEx Portal Database. Additionally, four kinds of interaction analysis were performed: correlation analysis among STFs, gene-gene, chemical-protein, and protein-ligand interaction analyses. In the end, we predicted the transcription factor that potentially regulates STFs.ResultsBiosynthesis and metabolic pathways were enriched in GSEA analysis. In ssGSEA analysis, most immunoreaction gene lists exhibited differential enrichment in psoriasis cases, whereas three receptor-related gene lists did in AD. The KEGG analysis of common DEGs redetermined inflammatory and metabolic pathways essential in both diseases. 5 STFs (PPARG, ZFPM2, ZNF415, HLX, and ANHX) were screened from common DEGs. The ROC analysis indicated that all STFs have diagnostic values in two diseases, especially ZFPM2. The correlation analysis, gene-gene, chemical-protein, and protein-ligand interaction analyses suggested that STFs interplay and involve inflammation and aberrant metabolism. Eventually, ZNF384 was the predicted transcription factor regulating PPARG, ZNF415, HLX, and ANHX.ConclusionsThe STFs (PPARG, ZFPM2, ZNF415, HLX, and ANHX) may increase the morbidity rate of AD in psoriasis by initiating a positive feedback loop of excessive inflammation and metabolic disorders. ZNF384 is a potential therapeutic target for psoriasis and AD by regulating PPARG, ZNF415, HLX, and ANHX.

Expression of CCL2, FOS, and JUN May Help to Distinguish Patients With IgA Nephropathy From Healthy Controls.

BackgroundIgA nephropathy (IgAN), the most common type of glomerulonephritis worldwide, can only be diagnosed mainly by renal biopsy owing to lack of effective biomarkers. It is urgent to explore and identify the potential diagnostic biomarkers through assessing the gene expression profiles of patients with IgAN.MethodsTwo datasets were obtained from the Gene Expression Omnibus (GEO) database, including GSE115857 (55 IgAN, 7 living healthy donors) and GSE35487 (25 IgAN, 6 living healthy donors), then underwent differentially expressed genes (DEGs) and function enrichment analyses utilizing R packages. The common gene list was screened out between DEGs and immune-associated genes by Venn diagram, then performed gene-gene interaction, protein-protein interaction (PPI) and function enrichment analyses. Top three immune-associated hub genes were selected by Maximal Clique Centrality (MCC) method, then the expression and diagnostic value of these hub genes were determined. Consensus clustering algorithm was applied to conduct the unsupervised cluster analysis of the immune-associated hub gene list in IgAN. Finally, the Nephroseq V5 tool was applied to identify the expression level of CCL2, FOS, JUN in kidney diseases, as well as the correlation between CCL2, FOS, JUN expression and renal function in the patients with IgAN.ResultsA total of 129 DEGs were obtained through comparing IgAN with healthy controls via the GSE115857 and GSE35487 datasets. Then, we screened out 24 immune-associated IgAN DEGs. CCL2, JUN, and FOS were identified as the top three hub genes, and they were all remarkably downregulated in IgAN. More importantly, CCL2, JUN, and FOS had a high accuracy [area under the curve (AUC) reached almost 1] in predicting IgAN, which could easily distinguish between IgAN patients and healthy individuals. Three distinct subgroups of IgAN were determined based on 24 immune-associated DEGs, with significant differences in the expression of CCL2, JUN, and FOS genes. Finally, CCL2, FOS, JUN were manifested a meaningful association with proteinuria, glomerular filtration rate (GFR), and serum creatinine level.ConclusionIn summary, our study comprehensively uncovers that CCL2, JUN, and FOS may function as promising biomarkers for diagnosis of IgAN.

Structural, molecular hybridization and network based identification of miR-373-3p and miR-520e-3p as regulators of NR4A2 human gene involved in neurodegeneration

MicroRNAs (miRNAs) are short non-coding RNAs with a 22 nucleotide sequence length and docks to the 3′UTR/5’UTR of the gene to regulate their mRNA translation to play a vital role in neurodegenerative diseases. The Nuclear Receptor gene (NR4A2), a transcription factor, and a steroid-thyroid hormone retinoid receptor is involved in neural development, memory formation, dopaminergic neurotransmission, and cellular protection from inflammatory damage. Therefore, recognizing the miRNAs is essential to efficiently target the 3′UTR/5’UTR of the NR4A2 gene and regulate neurodegeneration. Highly stabilized top miRNA-mRNA hybridized structures, their homologs, and identification of the best structures based on their least free energy were evaluated using in silico techniques. The miR-gene, gene-gene network analysis, miR-disease association, and transcription factor binding sites were also investigated. Results suggest top 166 miRNAs targeting the NR4A2 mRNA, but with a total of 10 miRNAs bindings with 100% seed sequence identity (both at 3’ and 5’UTR) at the same position on the NR4A2 mRNA region. The miR-373-3p and miR-520e-3p are considered the best candidate miRNAs hybridizing with high efficiency at both 3’ and 5’UTR of NR4A2 mRNA. This could be due to the most significant seed sequence length complementary, supplementary pairing, and absence of non-canonical base pairs. Furthermore, the miR-gene network, target gene-gene interaction analysis, and miR-disease association provide an understanding of the molecular, cellular, and biological processes involved in various pathways regulated by four transcription factors (PPARG, ZNF740, NRF1, and RREB1). Therefore, miR-373-3p, 520e-3p, and four transcription factors can regulate the NR4A2 gene involved in the neurodegenerative process.

Molecular prognostic indicators in HPV-positive oropharyngeal cancer: an updated review.

Infection with HPV virus and exposure to extrinsic carcinogens are the main causative factors for oropharyngeal squamous cell carcinoma (OPSCC). While HPV-related OPSCC typically shows a better prognosis and may be a candidate for de-intensification therapy, there is a subset of HPV-related cancers that show aggressive phenotype with frequent metastatic spread. The identification and refinement of molecular markers can better serve for prediction of prognosis and thus improve treatment decisions and outcome. We conducted a systematic review according to the PRISMA guidelines of all relevant studies addressing novel biomarkers in publications prior to July 2021. We identified studies that evaluated the association between molecular markers and prognosis in HPV-positive OPSCC. Full-text publications were entirely reviewed, classified, and selected if a clear predictive/prognostic value was seen in patients with HPV-positive OPSCC. Furthermore, a functional analysis of the target genes was conducted to understand biological processes and molecular pathways impacting on HPV-positive OPSCC outcomes. The systematic review yielded a total of 14 studies that matched the inclusion and exclusion criteria. Differential expression was identified for 31 different biomarkers. The first common pattern identified was the association of HPV-related circulating antibodies to activated immune function. Second, gene-gene interaction analysis further identified interacting gene networks tightly implicated in hypoxia tumor metabolism including the Warburg effect. Survival in HPV-positive OPSCC can be predicted by distinct selective biomarkers mainly indicative of immune host response and oxidative metabolism. Among these markers, some were identified to be unsuitable for HPV-positive de-escalation trials aimed at improving patients' quality of life.