Development and validation of a coagulation-related genes prognostic model for hepatocellular carcinoma.

BACKGROUND: Hepatocellular carcinoma (HCC) has a high incidence and mortality worldwide, which seriously threatens people's physical and mental health. Coagulation is closely related to the occurrence and development of HCC. Whether coagulation-related genes (CRGs) can be used as prognostic markers for HCC remains to be investigated. METHODS: Firstly, we identified differentially expressed coagulation-related genes of HCC and control samples in the datasets GSE54236, GSE102079, TCGA-LIHC, and Genecards database. Then, univariate Cox regression analysis, LASSO regression analysis, and multivariate Cox regression analysis were used to determine the key CRGs and establish the coagulation-related risk score (CRRS) prognostic model in the TCGA-LIHC dataset. The predictive capability of the CRRS model was evaluated by Kaplan-Meier survival analysis and ROC analysis. External validation was performed in the ICGC-LIRI-JP dataset. Besides, combining risk score and age, gender, grade, and stage, a nomogram was constructed to quantify the survival probability. We further analyzed the correlation between risk score and functional enrichment, pathway, and tumor immune microenvironment. RESULTS: We identified 5 key CRGs (FLVCR1, CENPE, LCAT, CYP2C9, and NQO1) and constructed the CRRS prognostic model. The overall survival (OS) of the high-risk group was shorter than that of the low-risk group. The AUC values for 1 -, 3 -, and 5-year OS in the TCGA dataset were 0.769, 0.691, and 0.674, respectively. The Cox analysis showed that CRRS was an independent prognostic factor for HCC. A nomogram established with risk score, age, gender, grade, and stage, has a better prognostic value for HCC patients. In the high-risk group, CD4+T cells memory resting, NK cells activated, and B cells naive were significantly lower. The expression levels of immune checkpoint genes in the high-risk group were generally higher than that in the low-risk group. CONCLUSIONS: The CRRS model has reliable predictive value for the prognosis of HCC patients.

Lipoxin A4 attenuates MSU-crystal-induced NLRP3 inflammasome activation through suppressing Nrf2 thereby increasing TXNRD2.

Gout is a common inflammatory disease. The activation of NLRP3 inflammasome induced by monosodium urate (MSU) crystals has a critical role in gout, and its prevention is beneficial for patients. Lipoxin A4 (LXA4) is an endogenous lipoxygenase-derived eicosanoid mediator with powerful anti-inflammatory properties. However, whether LXA4 can suppress NLRP3 inflammasome activation induced by MSU crystals remains unclear. This study aimed to investigate the protective effect of LXA4 on MSU-crystal-induced NLRP3 inflammasome activation and its underlying molecular mechanisms. We found that LXA4 inhibited MSU-crystal-induced NLRP3 inflammasome activation, interleukin (IL)-1ß maturation, and pyroptosis. More specifically, LXA4 suppressed the assembly of the NLRP3 inflammasome, including oligomerization and speck formation of ASC, and ASC-NLRP3 interaction. Furthermore, LXA4 suppressed oxidative stress, the upstream events for NLRP3 inflammasome activation, as evidenced by the fact that LXA4 eliminated total reactive oxygen species (ROS) generation and alleviated nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activation and mitochondrial dysfunction. However, LXA4 also depressed the Nrf2 activation, a critical molecule in the antioxidant pathway, and then exerted an inhibitory impact on Klf9 expression and promotional impact on TXNRD2 expression, two molecules located downstream of Nrf2 in sequence. Knockdown of TXNRD2 reversed the LXA4-induced depression of ROS and NLRP3 inflammasome. Moreover, LXA4 alleviated joint inflammation and decreased the production of cleaved caspase-1 and matured IL-1ß in gouty arthritis rats. Taken together, our findings demonstrate that LXA4 can attenuate MSU-crystal-induced NLRP3 inflammasome activation, probably through suppressing Nrf2 activation to increase TXNRD2 expression. The present study highlights the potential of LXA4 as an attractive new gout treatment candidate.

Comparison of ischemic stroke diagnosis models based on machine learning.

Background: The incidence, prevalence, and mortality of ischemic stroke (IS) continue to rise, resulting in a serious global disease burden. The prediction models have a great value in the early prediction and diagnosis of IS. Methods: The R software was used to screen the differentially expressed genes (DEGs) of IS and control samples in the datasets GSE16561, GSE58294, and GSE37587 and analyze DEGs for enrichment analysis. The feature genes of IS were obtained by several machine learning algorithms, including the least absolute shrinkage and selector operation (LASSO) logistic regression, the support vector machine-recursive feature elimination (SVM-RFE), and the Random Forest (RF). The IS diagnostic models were constructed based on transcriptomics by machine learning and artificial neural network (ANN). Results: A total of 69 DEGs, mainly involved in immune and inflammatory responses, were identified. The pathways enriched in the IS group were complement and coagulation cascades, lysosome, PPAR signaling pathway, regulation of autophagy, and toll-like receptor signaling pathway. The feature genes selected by LASSO, SVM-RFE, and RF were 17, 10, and 12, respectively. The area under the curve (AUC) of the LASSO model in the training dataset, GSE22255, and GSE195442 was 0.969, 0.890, and 1.000. The AUC of the SVM-RFE model was 0.957, 0.805, and 1.000, respectively. The AUC of the RF model was 0.947, 0.935, and 1.000, respectively. The models have good sensitivity, specificity, and accuracy. The AUC of the LASSO+ANN, SVM-RFE+ANN, and RF+ANN models was 1.000, 0.995, and 0.997, respectively, in the training dataset. However, the AUC of LASSO+ANN, SVM-RFE+ANN, and RF+ANN models was 0.688, 0.605, and 0.619, respectively, in the GSE22255 dataset. The AUC of the LASSO+ANN and RF+ANN models was 0.740 and 0.630, respectively, in the GSE195442 dataset. In the training dataset, the sensitivity, specificity, and accuracy of the LASSO+ANN model were 1.000, 1.000, and 1.000, respectively; of the SVM-RFE+ANN model were 0.946, 0.982, and 0.964, respectively; and of the RF+ANN model were 0.964, 1.000, and 0.982, respectively. In the test datasets, the sensitivity was very satisfactory; however, the specificity and accuracy were not good. Conclusion: The LASSO, SVM-RFE, and RF models have good prediction abilities. However, the ANN model is efficient at classifying positive samples and is unsuitable at classifying negative samples.

Susceptibility genes of hyperuricemia and gout.

Gout is a chronic metabolic disease that seriously affects human health. It is also a major challenge facing the world, which has brought a heavy burden to patients and society. Hyperuricemia (HUA) is the most important risk factor for gout. In recent years, with the improvement of living standards and the change of dietary habits, the incidence of gout in the world has increased dramatically, and gradually tends to be younger. An increasing number of studies have shown that gene mutations may play an important role in the development of HUA and gout. Therefore, we reviewed the existing literature and summarized the susceptibility genes and research status of HUA and gout, in order to provide reference for the early diagnosis, individualized treatment and the development of new targeted drugs of HUA and gout.

Lipoxin alleviates oxidative stress: a state-of-the-art review.

OBJECTIVE: This review aims to summarize the capability of lipoxin in regulating oxidative stress. BACKGROUND: Oxidative stress is defined as an imbalance between the production of free radicals and the antioxidant system, and it is associated with the existence of a large number of oxidation products, such as reactive oxygen species (ROS) and reaction nitrogen species (RNS), causing damage to human tissues through immunoinflammatory responses. Therefore, reducing oxidative stress is vital to alleviate pathological damage. Lipoxin, an acronym for lipoxygenase interaction product, is a bioactive autacoid metabolite of arachidonic acid made by various cell types. Previous studies have shown that lipoxin is associated with a variety of biological functions, including anti-inflammatory, regulating immune responses, promoting the repair of damaged cells, etc. The deficiency of lipoxin is a critical pathological mechanism in different diseases. Moreover, the ability of lipoxin to attenuate oxidative stress is noteworthy, thereby protecting the human body from diverse diseases. METHODS: We searched papers from PubMed database using search terms, such as lipoxin, lipoxin A4, oxidative stress, and other relevant terms. RESULTS: A total of 103 articles published over the past 20 years were identified for inclusion. We summarized the capability of lipoxin in regulating oxidative stress and mechanism. CONCLUSION: Lipoxin is provided with a protective role in attenuating oxidative stress.

Immunological analysis and differential genes screening of venous thromboembolism.

PURPOSE: To explore the pathogenesis of venous thromboembolism (VTE) and provide bioinformatics basis for the prevention and treatment of VTE. METHODS: The R software was used to obtain the gene expression profile data of GSE19151, combining with the CIBERSORT database, obtain immune cells and differentially expressed genes (DEGs) of blood samples of VTE patients and normal control, and analyze DEGs for GO analysis and KEGG pathway enrichment analysis. Then, the protein-protein interaction (PPI) network was constructed by using the STRING database, the key genes (hub genes) and immune differential genes were screened by Cytoscape software, and the transcription factors (TFs) regulating hub genes and immune differential genes were analyzed by the NetworkAnalyst database. RESULTS: Compared with the normal group, monocytes and resting mast cells were significantly expressed in the VTE group, while regulatory T cells were significantly lower. Ribosomes were closely related to the occurrence of VTE. 10 hub genes and immune differential genes were highly expressed in VTE. MYC, SOX2, XRN2, E2F1, SPI1, CREM and CREB1 can regulate the expressions of hub genes and immune differential genes. CONCLUSIONS: Ribosomal protein family genes are most relevant to the occurrence and development of VTE, and the immune differential genes may be the key molecules of VTE, which provides new ideas for further explore the pathogenesis of VTE.

Sex Difference of Ribosome in Stroke-Induced Peripheral Immunosuppression by Integrated Bioinformatics Analysis.

Ischemic stroke (IS) greatly threatens human health resulting in high mortality and substantial loss of function. Recent studies have shown that the outcome of IS has sex specific, but its mechanism is still unclear. This study is aimed at identifying the sexually dimorphic to peripheral immune response in IS progression, predicting potential prognostic biomarkers that can lead to sex-specific outcome, and revealing potential treatment targets. Gene expression dataset GSE37587, including 68 peripheral whole blood samples which were collected within 24 hours from known onset of symptom and again at 24-48 hours after onset (20 women and 14 men), was downloaded from the Gene Expression Omnibus (GEO) datasets. First, using Bioconductor R package, two kinds of differentially expressed genes (DEGs) (nonsex-specific- and sex-specific-DEGs) were screened by follow-up (24-48 hours) vs. baseline (24 hours). 30 nonsex-specific DEGs (1 upregulated and 29 downregulated), 79 female-specific DEGs (25 upregulated and 54 downregulated), and none of male-specific DEGs were obtained finally. Second, bioinformatics analysis of female-specific DEGs was performed. Gene Ontology (GO) functional annotation analysis shows that DEGs were mainly enriched in translational initiation, cytosolic ribosome, and structural constituent of ribosome. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis shows that the top 6 enrichment pathways are ribosome, nuclear factor--kappa B (NF-kappa B) signaling pathway, apoptosis, mineral absorption, nonalcoholic fatty liver disease, and pertussis. Three functional modules were clustered in the protein-protein interaction (PPI) network of DEGs. The top 10 key genes of the PPI network constructed were selected, including RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2. Sex difference of ribosome in stroke-induced peripheral immunosuppression may be the potential mechanism of sex disparities in outcome after IS, and women are more likely to have stroke-induced immunosuppression. RPS14, RPS15A, RPS24, FAU, RPL27, RPL31, RPL34, RPL35A, RSL24D1, and EEF1B2 may be novel prognostic biomarkers and potential therapeutic targets for IS.

The Potential Role of Gut Microbiota in the Prevention and Treatment of Lipid Metabolism Disorders.

Due to changes in lifestyle, diet structure, and aging worldwide, the incidence of metabolic syndromes such as hyperlipidemia, hypertension, diabetes, and obesity is increasing. Metabolic syndrome is considered to be closely related to cardiovascular disease and severely affects human health. In recent years, researchers have revealed that the gut microbiota, through its own or interacting metabolites, has a positive role in regulating metabolic syndrome. Therefore, the gut microbiota has been a new "organ" for the treatment of metabolic syndrome. The role has not been clarified, and more research is necessary to prove the specific role of specific strains. Probiotics are also believed to regulate metabolic syndromes by regulating the gut microbiota and are expected to become a new preparation for treating metabolic syndromes. This review focuses on the regulation of lipid metabolism disorders by the gut microbiota through the effects of bile acids (BA), short-chain fatty acids (SCFAs), bile salt hydrolase (BSH), and genes such as ABCG5 and ABCG8, FXR, NPC1L, and LDL-R.

Clinical Application Values of Neutrophil to Lymphocyte and Platelet to Lymphocyte Ratios in Multiple Cancers.

BACKGROUND: As the mechanism of systemic inflammatory response in the course of cancer progression is gradually revealed, research has begun to focus on the two indictors of neutrophil to lymphocyte ratio (NLR) and the platelet to lymphocyte ratio (PLR) which may be associated with clinical disease development, treatment, and prognosis in patients who are undergoing surgery, chemotherapy, targeted therapy, and immunotherapy. We aim to define the clinical application values of those two biomarkers in multiple cancers. METHODS: PubMed and Web of Science are used to perform the systematic literature research. Related articles and references were identified for analyzing the association of between NLR and PLR with treatment outcome, as well as progression of cancers. RESULTS: NLR and PLR are convenient, easy to calculate, economical, and practical biomarkers, effectively predicting treatment outcome and risk of death based on inflammatory cells. Elevated NLR and PLR are significantly in line with worse clinical pathological characteristics, deeper invasiveness, more lymph node metastasis and advanced TNM stage. A significant association was observed that high NLR and PLR predict poor overall survival and disease-free survival. CONCLUSIONS: NLR and PLR can be used as available biomarkers in prognostic survival and formulation of treatment strategy of multiple cancers.

Integrated Analysis of the Functions and Prognostic Values of RNA Binding Proteins in Lung Squamous Cell Carcinoma.

Lung cancer is the leading cause of cancer-related deaths worldwide. Dysregulation of RNA binding proteins (RBPs) has been found in a variety of cancers and is related to oncogenesis and progression. However, the functions of RBPs in lung squamous cell carcinoma (LUSC) remain unclear. In this study, we obtained gene expression data and corresponding clinical information for LUSC from The Cancer Genome Atlas (TCGA) database, identified aberrantly expressed RBPs between tumors and normal tissue, and conducted a series of bioinformatics analyses to explore the expression and prognostic value of these RBPs. A total of 300 aberrantly expressed RBPs were obtained, comprising 59 downregulated and 241 upregulated RBPs. Functional enrichment analysis indicated that the differentially expressed RBPs were mainly associated with mRNA metabolic processes, RNA processing, RNA modification, regulation of translation, the TGF-beta signaling pathway, and the Toll-like receptor signaling pathway. Nine RBP genes (A1CF, EIF2B5, LSM1, LSM7, MBNL2, RSRC1, TRMU, TTF2, and ZCCHC5) were identified as prognosis-associated hub genes by univariate, least absolute shrinkage and selection operator (LASSO), Kaplan-Meier survival, and multivariate Cox regression analyses, and were used to construct the prognostic model. Further analysis demonstrated that high risk scores for patients were significantly related to poor overall survival according to the model. The area under the time-dependent receiver operator characteristic curve of the prognostic model was 0.712 at 3 years and 0.696 at 5 years. We also developed a nomogram based on nine RBP genes, with internal validation in the TCGA cohort, which showed a favorable predictive efficacy for prognosis in LUSC. Our results provide novel insights into the pathogenesis of LUSC. The nine-RBP gene signature showed predictive value for LUSC prognosis, with potential applications in clinical decision-making and individualized treatment.

Development and validation of a RNA binding protein-associated prognostic model for lung adenocarcinoma.

RNA binding proteins (RBPs) dysregulation have been reported in various malignant tumors and associated with the occurrence and development of cancer. However, the role of RBPs in lung adenocarcinoma (LUAD) is poorly understood. We downloaded the RNA sequencing data of LUAD from the Cancer Genome Atlas (TCGA) database and determined the differently expressed RBPs between normal and cancer tissues. The study then systemically investigated the expression and prognostic value of these RBPs by a series of bioinformatics analysis. A total of 223 differently expressed RBPs were identified, including 101 up-regulated and 122 down-regulated RBPs. Eight RBPs (IGF2BP1, IFIT1B, PABPC1, TLR8, GAPDH, PIWIL4, RNPC3, and ZC3H12C) were identified as prognosis related hub gene and used to construct a prognostic model. Further analysis indicated that the patients in the high-risk subgroup had poor overall survival(OS) compared to those in low-risk subgroup based on the model. The area under the curve of the time-dependent receiver operator characteristic curve of the prognostic model are 0.775 in TCGA cohort and 0.814 in GSE31210 cohort, confirming a good prognostic model. We also established a nomogram based on eight RBPs mRNA and internal validation in the TCGA cohort, which displayed a favorable discriminating ability for lung adenocarcinoma.

CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 May Be Potential Therapeutic Targets for Hepatocellular Carcinoma Using Integrated Bioinformatic Analysis.

Hepatocellular carcinoma (HCC) is a malignant tumor with high mortality. The abnormal expression of genes is significantly related to the occurrence of HCC. The aim of this study was to explore the differentially expressed genes (DEGs) of HCC and to provide bioinformatics basis for the occurrence, prevention and treatment of HCC. The DEGs of HCC and normal tissues in GSE102079, GSE121248, GSE84402 and GSE60502 were obtained using R language. The GO function analysis and KEGG pathway enrichment analysis of DEGs were carried out using the DAVID database. Then, the protein-protein interaction (PPI) network was constructed using the STRING database. Hub genes were screened using Cytoscape software and verified using the GEPIA, UALCAN, and Oncomine database. We used HPA database to exhibit the differences in protein level of hub genes and used LinkedOmics to reveal the relationship between candidate genes and tumor clinical features. Finally, we obtained transcription factor (TF) of hub genes using NetworkAnalyst online tool. A total of 591 overlapping up-regulated genes were identified. These genes were related to cell cycle, DNA replication, pyrimidine metabolism, and p53 signaling pathway. Additionally, the GEPIA database showed that the CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 were associated with the poor survival of HCC patients. UALCAN, Oncomine, and HPA databases and qRT-PCR confirmed that these genes were highly expressed in HCC tissues. LinkedOmics database indicated these genes were correlated with overall survival, pathologic stage, pathology T stage, race, and the age of onset. TF analysis showed that MYBL2, KDM5B, MYC, SOX2, and E2F4 were regulators to these nine hub genes. Overexpression of CDK1, CCNB1, CDC20, BUB1, MAD2L1, MCM3, BUB1B, MCM2, and RFC4 in tumor tissues predicted poor survival in HCC. They may be potential therapeutic targets for HCC.

Exploring the Pathological Mechanism of Bladder Cancer Based on Tumor Mutational Burden Analysis.

Although immunotherapy has progressed in the treatment of bladder cancer, some patients still have poor prognosis. New therapeutic targets are eager to be discovered to improve the outcomes of bladder cancer. With the development of high-throughput sequencing and tumor profiling, potential tumor biomarkers were identified. Through the interpretation of related data from the Cancer Genome Atlas database (TCGA), some key genes have been discovered to drive the development and prognosis of urinary bladder neoplasm. On account of the success of immunotherapy in many cancer types, we established the relationship between tumor mutation burden and immune microenvironment of bladder cancer and found the changes of several immune cells in this disease. Based on the understanding of the bladder tumor genome and immune environment, this study is supposed to provide new therapies for the treatment of bladder neoplasm.

Prevalence of Hyperuricemia and its Correlation with Serum Lipids and Blood Glucose in Physical Examination Population in 2015 - 2018: a Retrospective Study.

BACKGROUND: Hyperuricemia (HUA) is a metabolic disease caused by a disorder of purine metabolism, which increases the risk of cardio-cerebrovascular disease. Serum lipids and blood glucose are risk factors for metabolic syndrome. Thus, this study aimed to assess the prevalence of HUA and its relationship with serum lipids and blood glucose. METHODS: A total of 59,074 cases (32,623 males and 26,451 females) from three hospitals in Lanzhou city from January 2015 to December 2018 were grouped according to serum uric acid (SUA) level to analyze the differences in age, total cholesterol (TC), triacylglycerol (TG), low density lipoprotein (LDL), high density lipoprotein (HDL), fasting blood glucose (FBG), creatinine (Cr), and blood urea nitrogen (BUN). The changes of prevalence of HUA among different age and gender groups was analyzed. Pearson's correlation analysis was used to analyze the correlation of SUA level with clinical indicators. The risk factors of HUA were analyzed by using binary logistic regression analysis. ROC curve was used to analyze the independent risk factors of elevated SUA. RESULTS: The overall prevalence rate of HUA was 19.87% and the prevalence rate of males was significantly higher than that of females (28.35% vs. 9.41%, χ2 = 3,289.143, p < 0.01). The prevalence rates of HUA from 2015 - 2018 were 19.54%, 19.31%, 18.64%, and 21.81%, respectively. Compared with the normal SUA group, TC, TG, and LDL significantly increased in the HUA group. The correlation analysis showed that SUA was negatively correlated with gender and HDL, and positively correlated with age, FBG, TC, TG, and LDL. The logistic regression analysis revealed that TG, TC, and LDL were risk factors for HUA. The ROC curve analysis showed that the risk of HUA significantly increased when TG was above 1.645 mmol/L. CONCLUSIONS: The overall prevalence of HUA in physical examination population has generally been at a high level in the past 4 years. Serum lipids and blood glucose may be independent risk factors for predicting HUA.

Hypertriglyceridemia and hyperuricemia: a retrospective study of urban residents.

BACKGROUND: The aim of this study was to determine the association between hypertriglyceridemia and hyperuricemia (HUA). METHODS: The study was conducted in 3884 subjects who had not received medication enrolled as a baseline. Each participant received at least three annual health check-ups between 2011 and 2017. The risk of hyperuricemia was assessed in four Quartiles (Q1 to Q4) according to TG levels using multivariate-adjusted logistic regression models. RESULTS: The total incidence rate of HUA was 62.3/1000 person-years. In the univariate analysis, the risk of hyperuricemia in people with hypertriglyceridemia was 2.353 times that of normal triglycerides, with a 95% confidence interval of (2.011, 2.754), and the risk of hyperuricemia in men was 1.86 times of female, and the 95% confidence interval is (1.634, 2.177). After adjusting the potential confounders, the relative risk RR of TG at Q2 Q3 Q4 was 1.445 (95%CI:1.114, 1.901), 2.075 (1.611, 2.674), 2.972 (2.322, 3.804). CONCLUSIONS: TG is an independent risk factor for hyperuricemia. As the level of TG increases, the risk of HUA increases.

Development and application of a PCR-HRM molecular diagnostic method of SNPs linked with TNF inhibitor efficacy.

Background Clinical evidence indicates that genetic variations may interfere with the mechanism of drug action. Recently, it has been reported that the single nucleotide polymorphisms (SNPs) of STAT4, PTPN2, PSORS1C1 and TRAF3IP2RA genes are associated with the clinical efficacy of tumor necrosis factor (TNF) inhibitors in the treatment of rheumatoid arthritis (RA) patients. Therefore, the detection of the SNPs linked with TNF inhibitor efficacy may provide an important basis for the treatment of RA. This study intended to establish molecular diagnostic methods for genotyping the linked SNPs based on high resolution melting (HRM) curve analysis. Methods The polymerase chain reaction-HRM (PCR-HRM) curve analysis detecting systems were established by designing the primers of the four SNPs, rs7574865G>T, rs7234029A>G, rs2233945C>A and rs33980500C>T, and the performance and clinical applicability of which were evaluated by using the Sanger sequencing method and genotyping test for 208 clinical samples. Results The self-developed molecular diagnostic methods of PCR-HRM were confirmed to be able to correctly genotype the four SNPs, the sensitivity and specificity of which were 100% in this study. The repeatability and reproducibility tests showed that there is little variable in intra-assay and inter-assay (the coefficient of variation ranged from 0.01% to 0.07%). The slight changes of DNA template and primer concentrations, PCR cycle number and reaction system volume had no significant effect on the genotyping performance of the method. The PCR-HRM assays were also applied to other PCR thermocyclers with HRM function and use different saturation fluorescent dyes. Conclusions The PCR-HRM genotyping method established in this study can be applied to the routine molecular diagnosis of rs7574865, rs7234029, rs2233945 and rs33980500.

High-Throughput and Rapid Melting Curve Analysis.

BACKGROUND: High-resolution melting curve analysis has been widely applied as one of the mainstream technologies used for scanning and detecting genetic mutations. After having realized the integration of PCR amplification and HRM detection on the same instrument, researchers have begun to focus on the throughput and speed of PCR-HRM detection. METHODS: A systematic literature search was conducted with the use of PubMed and ScienceDirect for articles on high resolution melting curve and microfluidic technologies. The focus is on the manufacture and application of microfluidic devices in medical diagnostic. A further review of the references identified from these articles was also performed. RESULTS: Based on the characteristics of microfluidic integration and rapid detection of microfluidic technology, a new high-throughput PCR-HRM genotyping and scanning detection mode combining microfluidic technology has not only achieved closed Tube high-throughput rapid detection, but also meets the needs of portability and lowcost. CONCLUSIONS: The new PCR-HRM detection platform based on the microfluidic technology can achieve high throughput and high speed.

Correlation analysis of gene polymorphisms and ß-lactam allergy.

A total of 64 patients with ß-lactam allergy and 30 control subjects were enrolled in a case-control study. This study is aimed to analyze the relationship between ß-lactam allergy and 10 single nucleotide polymorphisms (SNPs) in interleukin-10 (IL-10), IL-13, IL-4Rα, high-affinity immunoglobulin E-receptor ß chain (FcεRIß), interferon γ receptor 2 (IFNGR2), and CYP3A4, and within the Han Chinese population of Northwest China. Genotyping for the SNPs was conducted using the Sequenom MassARRAY(®) platform. SPSS 17.0 was employed to analyze the statistical data and SHEsis was used to perform the haplotype reconstruction and analyze linkage disequilibrium of SNPs of IL-10 and IL-13. The results showed that the genotype distribution of CYP3A4 rs2242480/CT differed significantly between case and control groups of males (P=0.022; odds ratio (OR)=0.167, 95% confidence interval (CI): 0.032-0.867). Further analysis showed that CCA, CCG, and TAA haplotypes of IL-10 had no significant correlation in patients with ß-lactam allergy. The correlation between CCT and CAC haplotypes of IL-13 and ß-lactam allergy needs to be further studied. The analysis did not reveal any differences in the distribution of others gene polymorphisms between cases and controls.

Association analysis of single nucleotide polymorphisms of proinflammatory cytokine and their receptors genes with rheumatoid arthritis in northwest Chinese Han population.

OBJECTIVE: To analyze the relationship of genetic polymorphisms in IL1ß, IL6, TNF-α genes and their receptors genes with rheumatoid arthritis (RA) for northwest Han Chinese. This study also explores whether there are gene-gene interactions among these genetic polymorphisms. METHODS: A total of 452 patients with RA and 373 matched healthy controls were enrolled to carry out a case-control study for 16 SNPs of IL1B-511 C>T, IL1B-31 T>C, IL1B+3954 C>T, IL1RN T>C, IL6-597 G>A, IL6-572 G>C, IL6-174 G>C, IL6R-183 G>A, IL6R exon2 T>A, IL6R exon1 A>C, TNFA-863 C>A, TNFA-857 C>T, TNFA-308 G>A, TNFA-238 G>A, TNFR1-383 A>C and TNFR2 T676G T>G from seven genes. Genotyping for the SNPs was conducted on the RotorGene 6000 PCR platform using in-house high resolution melting (HRM) approaches. Detection correctness was validated through direct sequencing. Generalized multifactor dimensionality reduction (GMDR) analysis was applied to discover likely gene-gene interaction model among the SNPs. RESULTS: The results showed that the genotype distributions of TNFA-308, TNFA-857 and TNFA-863 are significantly different between case and control groups (P=0.016, P=0.048 and P=0.016, respectively). Carriers of TNFA-857 mutant allele conferred risk to RA (OR=1.525, 95% CI=1.157-2.009) while those of TNFA-308 and TNFA-863 mutant alleles conferred protection to RA (OR=0.459, 95% CI=0.286-0.739; OR=0.490, 95% CI=0.329-0.732). GMDR analysis for the SNPs indicated that gene-gene interaction existed among IL1B-31, IL1RN, IL6-572, IL6R-183, IL6R-exon1 and TNFA-857. Thirteen of all genotypes of the six SNPs combination were discovered to have significant distribution difference between RA group and the control. CONCLUSIONS: This study demonstrated that PCR-HRM assay is a highly efficient SNP genotyping method especially for the detection of large-scale samples. The SNPs of TNFA-308 and TNFA-863 are closely associated with RA susceptibility and that gene-gene interactions may occur among the six SNPs of IL1B-31, IL1RN, IL6-572, IL6R-183, IL6R-exon1 and TNFA-857 in RA patients from northwest Chinese Han population, especially these SNPs' combination genotypes CT/TT/CC/GG/AC/CC, CT/TT/GC/AA/AC/CT and CT/CT/CC/GA/AC/CC to show high risk of RA susceptibility in our study.