Genetics research最新文献

Idiopathic pulmonary fibrosis (IPF) is a disease of progressive lung fibrosis with a high mortality rate. This study aimed to uncover the underlying molecular features for different types of IPF. IPF microarray datasets were retrieved from GEO databases. Weighted gene co-expression analysis (WGCNA) was used and identified subgroup-specific WGCNA modules. Infiltration-level immune cells in different subgroups of microenvironments were analyzed with CIBERSORT algorithms. The result is we classified 173 IPF cases into two subgroups based on gene expression profiles, which were retrieved from the GEO databases. The SGRQ score and age were significantly higher in C2 than in C1. Using WGCNA, five subgroup-specific modules were identified. M4 was mainly enriched by MAPK signaling, which was mainly expressed in C2; M1, M2, and M3 were mainly enriched by metabolic pathways and Chemokine signaling, and the pathway of M5 was phagosome inflammation; M1, M2, M3, and M5 were mainly expressed in C1. Utilizing the CIBERSORT, we showed that the number of M1 macrophage cells, CD8 T cells, regulatory T cells (Tregs), and Plasma cells was significantly different between C1 and C2. We found the molecular subgroups of IPF revealed that cases from different subgroups may have their unique patterns and provide novel information to understand the mechanisms of IPF itself.

A literature review showed some discrepancies regarding the association of -592C/A with the risk of cervical cancer. To allow more precise analysis of the data by increasing the number of cases studied and more acceptable generalization by considering results from different sources, the present meta-analysis was performed on available published studies that explored the relationship between SNP-592C/A of the IL-10 gene and the risk of cervical cancer. Eleven available studies, including 4187 cases and 3311 controls, were included in this study investigating the relationship between the -592C/A polymorphism of IL-10 and cervical cancer risk. Fixed-effects or random-effects models were performed with pooled odds ratios (ORs). Heterogeneity and bias tests were performed by the inconsistency test and funnel plot, respectively. The overall analysis showed an increased susceptibility to cervical cancer with the -592C/A polymorphism of the IL-10 gene for the recessive model (OR = 1.30, 95% CI = 1.14-1.49), dominant model (OR = 1.36, 95% CI = 1.09-1.70), and additive model (OR = 1.25, 95% CI = 1.09-1.44). Regarding ethnicity, a significant association of the -592C/A polymorphism of the IL-10 gene was linked to an elevated risk of cervical cancer for all genetic models (recessive, dominant, and additive) in the Asian populations and for the recessive and additive models in Caucasians with P < 0.05. The -592C/A polymorphism of the IL-10 gene may be considered a risk factor for cervical cancer.

This study aimed to screen miRNA biomarkers for melanoma progression. Raw melanoma data were downloaded from the Gene Expression Omnibus (GSE34460, GSE35579, GSE18509, and GSE24996) and the Cancer Genome Atlas (TCGA). Then, all differentially expressed miRNAs (DEmiRNAs) between benign vs. primary, metastatic vs. benign, and metastatic vs. primary groups were obtained in the GSE34460 and GSE35579 datasets, and the miRNAs related to disease progression were further screened. Then, the miRNA-gene network was constructed, followed by enrichment, survival, and cluster analyses. Differentially expressed genes (DEGs), tumor-infiltrating immune cells, and tumor mutation burden (TMB) between subtypes were analyzed. miRNAs were verified in the GSE18509 and GSE24996 datasets. A total of 132 and 209 DEmiRNAs were obtained in the GSE34460 and GSE35579 datasets, respectively, and 27 DEmiRNAs related to disease progression were screened. hsa-miR-106b-5p, hsa-miR-27b-3p, and hsa-miR-141-3p had a higher degree and were regulated by numerous genes in the miRNA-gene network. Moreover, four miRNAs were associated with prognosis: hsa-let-7c-5p, hsa-miR-130b-3p, hsa-miR-142-3p, and hsa-miR-509-3p. Furthermore, the bidirectional hierarchical clustering of 27 miRNAs was classified into three subtypes, and TMB and four types of immune cells, including activated dendritic cells, naïve CD4 T cells, M1 macrophages, and plasma cells, showed significant differences among the three subtypes. The expression levels of most miRNAs in the GSE18509 and GSE24996 datasets were consistent with those in the training dataset. These miRNAs, including hsa-let-7c-5p, hsa-miR-130b-3p, and hsa-miR-142-3p, and activated dendritic cells, naïve CD4 T cells, M1 macrophages, and plasma cells may play vital roles in the pathogenesis of melanoma.

Background: Exercise is a regular behavioral activity that not only helps to lose weight but also reduces the risk of cardiovascular and cerebrovascular diseases. Diabetes is a common disease that plagues human health. It is shown that regular exercise can improve the insulin sensitivity of diabetic patients and have an important function in adjuvant therapy.

Methods: We downloaded the GSE101931 dataset from the Gene Expression Omnibus (GEO) database, 10 samples were obtained from the GSE101931 dataset, including 5 before exercise and 5 postexercise samples, and GEO2R was used to screen the differentially expressed genes (DEGs) exhibited by a heat map. Then, the enrichment analysis of DEGs in Gene Ontology (GO) function was analyzed by Metascape, and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway of DEGs was also analyzed by gene set enrichment analysis (GSEA). Next, the protein-protein interaction (PPI) network maps were drawn, and the hub genes were identified through Metascape. Finally, the expressions of the hub genes in the dataset were analyzed.

Results: Totally, 116 upregulated DEGs and 1017 downregulated DEGs were identified from these data. These DEGs were mainly enriched in the platelet-derived growth factor receptor signaling pathway and mRNA processing. Then, the GSEA analysis showed that 6 KEGG pathways were associated with postexercise prediabetic samples, namely, ABC transporters, focal adhesion, MAPK signaling pathway, prion diseases, melanogenesis, and gap junction. Afterward, three hub genes (HSPA8, STIP1, and HSPH1) were highly expressed after exercise through the box plot analysis.

Conclusion: A myriad of research results confirms that there is a certain connection between exercise and diabetes, which provides a favorable basis for emerging exercise into the treatment of diabetic patients.