Development and analysis of a comprehensive diagnostic model for aortic valve calcification using machine learning methods and artificial neural networks.

Background: Although advanced surgical and interventional treatments are available for advanced aortic valve calcification (AVC) with severe clinical symptoms, early diagnosis, and intervention is critical in order to reduce calcification progression and improve patient prognosis. The aim of this study was to develop therapeutic targets for improving outcomes for patients with AVC. Materials and methods: We used the public expression profiles of individuals with AVC (GSE12644 and GSE51472) to identify potential diagnostic markers. First, the R software was used to identify differentially expressed genes (DEGs) and perform functional enrichment analysis. Next, we combined bioinformatics techniques with machine learning methodologies such as random forest algorithms and support vector machines to screen for and identify diagnostic markers of AVC. Subsequently, artificial neural networks were employed to filter and model the diagnostic characteristics for AVC incidence. The diagnostic values were determined using the receiver operating characteristic (ROC) curves. Furthermore, CIBERSORT immune infiltration analysis was used to determine the expression of different immune cells in the AVC. Finally, the CMap database was used to predict candidate small compounds as prospective AVC therapeutics. Results: A total of 78 strong DEGs were identified. The leukocyte migration and pid integrin 1 pathways were highly enriched for AVC-specific DEGs. CXCL16, GPM6A, BEX2, S100A9, and SCARA5 genes were all regarded diagnostic markers for AVC. The model was effectively constructed using a molecular diagnostic score system with significant diagnostic value (AUC = 0.987) and verified using the independent dataset GSE83453 (AUC = 0.986). Immune cell infiltration research revealed that B cell naive, B cell memory, plasma cells, NK cell activated, monocytes, and macrophage M0 may be involved in the development of AVC. Additionally, all diagnostic characteristics may have varying degrees of correlation with immune cells. The most promising small molecule medicines for reversing AVC gene expression are Doxazosin and Terfenadine. Conclusion: It was identified that CXCL16, GPM6A, BEX2, S100A9, and SCARA5 are potentially beneficial for diagnosing and treating AVC. A diagnostic model was constructed based on a molecular prognostic score system using machine learning. The aforementioned immune cell infiltration may have a significant influence on the development and incidence of AVC.

Bioinformatics and Machine Learning Methods to Identify FN1 as a Novel Biomarker of Aortic Valve Calcification.

Aim: The purpose of this study was to identify potential diagnostic markers for aortic valve calcification (AVC) and to investigate the function of immune cell infiltration in this disease. Methods: The AVC data sets were obtained from the Gene Expression Omnibus. The identification of differentially expressed genes (DEGs) and the performance of functional correlation analysis were carried out using the R software. To explore hub genes related to AVC, a protein-protein interaction network was created. Diagnostic markers for AVC were then screened and verified using the least absolute shrinkage and selection operator, logistic regression, support vector machine-recursive feature elimination algorithms, and hub genes. The infiltration of immune cells into AVC tissues was evaluated using CIBERSORT, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. Finally, the Connectivity Map database was used to forecast the candidate small molecule drugs that might be used as prospective medications to treat AVC. Results: A total of 337 DEGs were screened. The DEGs that were discovered were mostly related with atherosclerosis and arteriosclerotic cardiovascular disease, according to the analyses. Gene sets involved in the chemokine signaling pathway and cytokine-cytokine receptor interaction were differently active in AVC compared with control. As the diagnostic marker for AVC, fibronectin 1 (FN1) (area the curve = 0.958) was discovered. Immune cell infiltration analysis revealed that the AVC process may be mediated by naïve B cells, memory B cells, plasma cells, activated natural killer cells, monocytes, and macrophages M0. Additionally, FN1 expression was associated with memory B cells, M0 macrophages, activated mast cells, resting mast cells, monocytes, and activated natural killer cells. AVC may be reversed with the use of yohimbic acid, the most promising small molecule discovered so far. Conclusion: FN1 can be used as a diagnostic marker for AVC. It has been shown that immune cell infiltration is important in the onset and progression of AVC, which may benefit in the improvement of AVC diagnosis and treatment.

Gene variation in IL10 and susceptibility to chronic hepatitis B.

OBJECTIVES: To evaluate the correlation between IL-10 gene polymorphisms and hepatitis B infection. METHODS: Tag single nucleotide polymorphisms (SNPs) were used to investigate the relationship between IL-10 gene polymorphisms and susceptibility to chronic hepatitis B virus (HBV) infection by comparing 996 chronic HBV infection cases to 301 acute infection controls. RESULTS: This study found that rs3024490 G/T allele, located in the intron 1 region and highly prevalent in Chinese populations, was significantly different between the chronic HBV infection cases and the acute infection controls in single allele analysis, genetic models analysis, and haplotypes analysis. CONCLUSIONS: This suggested that the rs3024490 within IL-10 was associated with susceptibility to chronic hepatitis B in a Chinese Han population.

Single nucleotide polymorphisms rs2120131, rs4935047, and rs7095891 in the MBL2 gene show no association with susceptibility to chronic hepatitis B in a Chinese Han population.

Thus far, many studies have evaluated the correlation between MBL2 gene polymorphisms and hepatitis B infection. Tag single nucleotide polymorphisms (SNPs) were used to investigate the relationship between MBL2 gene polymorphisms and susceptibility to chronic hepatitis B virus (HBV) infection by comparing 996 chronic HBV infection cases to 301 acute infection controls. There was no significant correlation between rs2120131, rs4935047, and rs7095891 and chronic HBV infection. This suggested that the new SNPs within MBL2 were not associated with susceptibility to chronic hepatitis B in a Chinese Han population.

Relationship between interleukin 18 polymorphisms and susceptibility to chronic hepatitis B virus infection.

AIM: To identify the relationship between the tagging single nucleotide polymorphism sites (tagSNPs) of the Interleukin-18 (IL-18) gene and genetic susceptibility to chronic hepatitis B virus infection in Chinese patients. METHODS: Five hundred and one cases of chronic hepatitis B virus (HBV) infection and 301 HBV natural clearance controls were studied. Two tagSNPs in the IL-18 gene (rs1946518A/C and rs574424C/G) were genotyped by the Multiplex Snapshot technique. The genotype and allele frequencies were calculated and analyzed. RESULTS: In the genotypes of rs1946518, the AA type was present at a higher frequency in the patients compared to those in the controls. Odds ratio (OR) of the AA genotype for the comparison with that of the AC and the CC genotype was 1.537 (95% confidence intervals (CI): 1.116-2.218, P = 0.009 < 0.025). In phenotypes, the allele C at rs1946518 was of a significantly lower frequency in the patients with chronic hepatitis B than that in the controls (P = 0.017 < 0.025). OR of the allele A for the comparison with that of the allele C was 1.279 (95% CI: 1.045-1.567). As for the rs574424 genotypes, no significant difference in this genotype distribution or in this allele frequency between the patients and the control subjects was observed. No significant difference in the haplotype frequencies between the patients with chronic hepatitis B and HBV natural clearance individuals was displayed. CONCLUSION: The data suggest that genotype AA and the allele A of the IL-18 at position rs1946518 are closely associated with the resistance to chronic hepatitis B and may be the dangerous gene. However, no statistical association was found between polymorphisms of rs574424 for IL-18 and hepatitis B.

No association between IRF3 polymorphism and susceptibility to hepatitis B virus infection in Chinese patients.

AIM: To investigate the association between three tag single nucleotide polymorphisms (tagSNPs) in interferon regulatory factors (IRF3) and the genetic susceptibility to chronic hepatitis B virus (HBV) infection. METHODS: We performed a case-control study of 985 Chinese cases of chronic HBV infection and 294 self-limiting HBV-infected individuals as controls. Three tagSNPs in IRF3 (rs10415576, rs2304204, rs2304206) were genotyped with the Multiplex SNaPshot technique. The genotype and allele frequencies were calculated and analyzed. RESULTS: The three SNPs showed no significant genotype/allele associations with chronic HBV infection. Overall allele P values were: rs10415576, P = 0.0908, odds ratio (OR) [95% confidence interval (CI)] = 1.1798 (0.9740-1.4291); rs2304204, P = 0.5959, OR (95% CI) = 1.0597 (0.8552-1.3133); rs2304206, P = 0.8372, OR (95% CI) = 1.0250 (0.8097-1.2976). Overall genotype P values were: rs10415576, P = 0.2106; rs2304204, P = 0.8458; rs2304206, P = 0.8315. There were no statistically significant differences between patients with chronic HBV infection and controls. Haplotypes generated by these three SNPs were also not significantly different between the two groups. CONCLUSION: The three tagSNPs of IRF3 are not associated with HBV infection in the Han Chinese population.

Polymorphisms in programmed death-1 gene are not associated with chronic HBV infection in Chinese patients.

AIM: To investigate the association between the programmed death-1(PD-1) polymorphisms and genetic susceptibility of chronic hepatitis B virus (HBV) infection in Chinese patients. METHODS: Two single nucleotide polymorphisms (SNPs), PD-1.1 G > A and PD-1.2 G > A, were genotyped in 539 patients with chronic HBV infection and 353 other family members (HbsAg-) from 256 nuclear families using polymerase chain reactiorestriction fragment length polymorphisms assay. The associations between PD-1 polymorphisms and genetic susceptibility of chronic HBV infection were analyzed usng the family-based association analysis method. RESULTS: No association or linkage was detected among 539 patients. Univariate (single-marker) family-based association tests demonstrated that PD-1 genotypes, alleles and transmitted haplotypes are not associated with chronic HBV infection (all with P value more than 0.05). Transmission/disequilibrium test and sibship disequilibrium test analysis showed no excess of the alleles from heterozygous parents to affected offspring (P = 0.688880, P = 1.000000 respectively). CONCLUSION: The data demonstrated that PD-1.1 and PD-1.2 polymorphisms are not associated with chronic HBV infection in Chinese patients.

Interleukin-10 gene polymorphisms in association with susceptibility to chronic hepatitis C virus infection: a meta-analysis study.

A relationship between chronic hepatitis C virus (HCV) infection and interleukin-10 (IL-10) gene polymorphisms has been reported with controversial results in different studies. In an effort to solve this controversy, we quantitatively summarized ten studies on this relationship by means of meta-analysis. Our analysis included ten case-control studies with 992 cases of chronic HCV infection and 1,123 controls. Analyses were performed with STATA version 9.0. The results showed that the IL-10 -1082GG genotype significantly increased the risk for persistent HCV infection (AA vs. GG: OR = 0.680, 95% CI = 0.489-0.947, P = 0.022; AG vs. GG: OR = 0.608, 95% CI = 0.439-0.840, P = 0.003; GG vs. AG + AA: OR = 1.570, 95% CI = 1.160-2.123, P = 0.003), but no statistically significant differences were observed between cases and controls for IL-10 -819C/T and IL-10 -592C/A polymorphisms (P > 0.05). In conclusion, this meta-analysis suggested that the IL-10 -1082GG genotype was associated with increased susceptibility for chronic HCV infection.