Immune- and Ribosome-Related Genes were Associated with Systemic Vasculitis

Severe, but not moderate asthmatics share blood transcriptomic changes with post-traumatic stress disorder and depression

Asthma, an inflammatory disorder of the airways, is one of the most common chronic illnesses worldwide and is associated with significant morbidity. There is growing recognition of an association between asthma and mood disorders including post-traumatic stress disorder (PTSD) and major depressive disorder (MDD). Although there are several hypotheses regarding the relationship between asthma and mental health, there is little understanding of underlying mechanisms and causality. In the current study we utilized publicly available datasets of human blood mRNA collected from patients with severe and moderate asthma, MDD, and PTSD. We performed differential expression (DE) analysis and Gene Set Enrichment Analysis (GSEA) on diseased subjects against the healthy subjects from their respective datasets, compared the results between diseases, and validated DE genes and gene sets with 4 more independent datasets. Our analysis revealed that commonalities in blood transcriptomic changes were only found between the severe form of asthma and mood disorders. Gene expression commonly regulated in PTSD and severe asthma, included ORMDL3 a gene known to be associated with asthma risk and STX8, which is involved in TrkA signaling. We also identified several pathways commonly regulated to both MDD and severe asthma. This study reveals gene and pathway regulation that potentially drives the comorbidity between severe asthma, PTSD, and MDD and may serve as foci for future research aimed at gaining a better understanding of both the relationship between asthma and PTSD, and the pathophysiology of the individual disorders.

Discovery of potential biomarkers for human atherosclerotic abdominal aortic aneurysm through untargeted metabolomics and transcriptomics

Abdominal aortic aneurysm (AAA) and atherosclerosis (AS) have considerable similarities in clinical risk factors and molecular pathogenesis. The aim of our study was to investigate the differences between AAA and AS from the perspective of metabolomics, and to explore the potential mechanisms of differential metabolites via integration analysis with transcriptomics. Plasma samples from 32 AAA and 32 AS patients were applied to characterize the metabolite profiles using untargeted liquid chromatography-mass spectrometry (LC-MS). A total of 18 remarkably different metabolites were identified, and a combination of seven metabolites could potentially serve as a biomarker to distinguish AAA and AS, with an area under the curve (AUC) of 0.93. Subsequently, we analyzed both the metabolomics and transcriptomics data and found that seven metabolites, especially 2'-deoxy-D-ribose (2dDR), were significantly correlated with differentially expressed genes. In conclusion, our study presents a comprehensive landscape of plasma metabolites in AAA and AS patients, and provides a research direction for pathogenetic mechanisms in atherosclerotic AAA.

Application of Genetic Algorithm-Based Support Vector Machine in Identification of Gene Expression Signatures for Psoriasis Classification: A Hybrid Model

BACKGROUND

Psoriasis is a chronic autoimmune disease impairing significantly the quality of life of the patient. The diagnosis of the disease is done via a visual inspection of the lesional skin by dermatologists. Classification of psoriasis using gene expression is an important issue for the early and effective treatment of the disease. Therefore, gene expression data and selection of suitable gene signatures are effective sources of information.

METHODS

We aimed to develop a hybrid classifier for the diagnosis of psoriasis based on two machine learning models of the genetic algorithm and support vector machine (SVM). The method also conducts gene signature selection. A publically available gene expression dataset was used to test the model.

RESULTS

A number of 181 probe sets were selected among the original 54,675 probes using the hybrid model with a prediction accuracy of 100% over the test set. A number of 10 hub genes were identified using the protein-protein interaction network. Nine out of 10 identified genes were found in significant modules.

CONCLUSIONS

The results showed that the genetic algorithm improved the SVM classifier performance significantly implying the ability of the proposed model in terms of detecting relevant gene expression signatures as the best features.

Genetic Variants of RPL5 and RPL9 Genes among Saudi Patients Diagnosed with Thrombosis

BACKGROUND

Thrombosis directly affects the quality of life with increased mortality. The RPL5 (L5) gene on intron 6 on chromosome 1p22, rs6604026 is associated with multiple sclerosis risk, whereas RPL9 (L9) on 8 exons on chromosome 4p14 has been documented so far as being an essential involvement in the proliferation of protein synthesized cells mostly by gene products.

OBJECTIVE

The aim of this work was to assess genetic variants of RPL5 and RPL9 and thrombosis to characterize their role in the diagnosis of thrombosis among the Saudi population.

METHODS

The cross-sectional study involved 100 Saudi patients diagnosed with thrombosis (arterial or venous) in 50 healthy individuals as controls in the same age and sex groups. Primers were designed RPL5 and RPL9 for molecular analysis. The Sanger System ABI-3730xL (Hong Kong) automatic sequencing was used for DNA sequencing. Statistical analysis was performed using the Prism 5 and SPSS version-21 programs.

RESULTS

The male / female age ratio was 66.7 / 57.4, and the mean age was 61.2 years. Most of the patients were self-identifiable and without a previous history of thrombosis (61.0%). Most of the patients had just been diagnosed, that is, in the last five years (74.0%), about 43% of the patients underwent treatment using combination therapy (Aspirin and oral anticoagulants). New gene variants of RPL5 (5 SNPs) and RPL9 (9 SNPs) were detected in Saudi thrombotic patients.

CONCLUSION

Mutations in RPL5 and RPL9 were reported in all thrombotic patients, represented by a new variant of the ribosomal protein gene and correlated with thrombosis in the Saudi population. These results may reflect an association between the ribosomal protein SNP gene and the incidence and progression of thrombosis in the Saudi population.

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.

Human gene expression microarray analysis of the HPV 6bE7-HaCaT stable cell line

OBJECTIVE

Human papillomavirus (HPV) is the most common sexually transmitted agent in the world. HPV6b is a low-risk type of HPVs that causes benign verrucous hyperplastic lesions of the skin and anal genital mucosa. Previous research has indicated that HPV genotype 6 is sometimes associated with high-grade lesions and anal cancer. The pathogenesis of low-risk HPV infection and its relationship to high-risk HPV is not clear at present. The E7 protein, which is encoded by HPV early -expressing genes, plays an important role in HPV infection. The aim of this study is to investigate the human gene expression signature of the HPV6b E7-transfected HaCaT stable cell line. The identification of differentially expressed genes might provide a more comprehensive understanding of HPV6b infection and will allow us to explore the specific role of E7 protein.

METHODS

We established a stable cell line transfected with the HPV6b E7 gene and analyzed the line's genome-wide expression profile by microarray. Quantitative real-time PCR (qRT-PCR) was used to verify the differentially expressed genes. GO enrichment analysis was applied for gene annotation according to functions. KEGG analysis, a system for analyzing gene function and genome information, was used to help us integrate differentially expressed genes into pathways.

RESULTS

A total of 3519 genes were identified to be significantly differentially expressed between the HPV 6bE7-HaCaT stable cell line and a control cell line, among which 1884 genes were up-regulated and 1635 genes were down-regulated with a fold-change > 2.0 between the two groups. The expression profiles of the top 20 up-regulated and the top 20 down-regulated genes in the HPV 6bE7-HaCaT stable cell line as analyzed by qRT-PCR were consistent with the microarray data. The most significantly enhanced genes HPV 6bE7-HaCaT cells were SIMC1, S100A8 and S100A9, whereas PXDN expression was markedly down-regulated. GO analysis showed that HPV 6bE7 primarily affected biological processes and that the most significant difference was in heart induction (GO:0003129). Many differentially expressed genes were linked to histone H4-K20 demethylation (GO:0035574). KEGG analysis showed that the most significant changes in gene expression were related to primary bile acid biosynthesis, and the most diverse biological processes were related to systemic lupus erythematosus pathogenesis.

CONCLUSIONS

The global gene expression profile of the HPV 6bE7-HaCaT stable cell line was analyzed, revealing the genes regulated by E7 protein and providing insight into the pathogenesis of HPV6b infection.

First report on HLA-DPA1 gene allelic distribution in the general Lebanese population

Aims

HLA-DPA1 is an important marker in bone marrow and organ transplantation and a highly emerging screening parameter in histocompatibility laboratories. Being highly polymorphic, it has another significant value in detecting population origins and migrations. This is the first study to assess DPA1 allele frequencies in an Arab population.

Methods

The HLA DPA1 alleles were identified using the One-Lambda assays on a Luminex reverse SSO DNA typing system. Our study included 101 individuals coming from different Lebanese geographical areas representing the different communities and religious sects of the country.

Results

We compared the results of this study to 16 different populations and found very interesting similarities and differences between Lebanese people and individuals of European ancestry.

Conclusion

This study is the first to describe the different allelic frequencies of HLA-DPA1 in the Lebanese population and will serve as a template that can be later used for disease association studies both at the level of the country and internationally.