Autophagy-mediated regulation patterns contribute to the alterations of the immune microenvironment in periodontitis

Integrated bioinformatics analysis identifies autophagy-associated genes as candidate biomarkers and reveals the immune infiltration landscape in psoriasis

Autophagy is implicated in the pathogenesis of psoriasis. We aimed to identify autophagy-related biomarkers in psoriasis via an integrated bioinformatics approach. We downloaded the gene expression profiles of GSE30999 dataset, and the "limma" package was applied to identify differentially expressed genes (DEGs). Then, differentially expressed autophagy-related genes (DEARGs) were identified via integrating autophagy-related genes with DEGs. CytoHubba plugin was used for the identification of hub genes and verified by the GSE41662 dataset. Subsequently, a series of bioinformatics analyses were employed, including protein-protein interaction network, functional enrichment, spearman correlation, receiver operating characteristic, and immune infiltration analyses. One hundred and one DEARGs were identified, and seven DEARGs were identified as hub genes and verified using the GSE41662 dataset. These validated genes had good diagnostic value in distinguishing psoriasis lesions. Immune infiltration analysis indicated that ATG5, SQSTM1, EGFR, MAPK8, MAPK3, MYC, and PIK3C3 were correlated with infiltration of immune cells. Seven DEARGs, namely ATG5, SQSTM1, EGFR, MAPK8, MAPK3, MYC, and PIK3C3, may be involved in the pathogenesis of psoriasis, which expanded the understanding of the development of psoriasis and provided important clinical significance for treatment of this disease.

Leveraging human-mouse studies to advance the genetics of hearing impairment in Africa

Mouse models are used extensively to understand human pathobiology and mechanistic functions of disease-associated loci. However, in this review, we investigate the potential of using genetic mouse models to identify genetic markers that can disrupt hearing thresholds in mice and then target the hearing-enriched orthologues and loci in humans. Currently, little is known about the real prevalence of genes that cause hearing impairment (HI) in Africa. Pre-screening mouse cell lines to identify orthologues of interest has the potential to improve the genetic diagnosis for HI in Africa to a significant percentage, for example, 10-20%. Furthermore, the functionality of a candidate gene derived from mouse screening with heterogeneous genetic backgrounds and multi-omic approaches can shed light on the molecular, genetic heterogeneity and plausible mode of inheritance of a gene in hearing-impaired individuals especially in the absence of large families to investigate.

Analysis of m6A regulators related immune characteristics in ankylosing spondylitis by integrated bioinformatics and computational strategies

N6-methyladenosine (m6A) modification, as a common epigenetic modification, has been widely studied in autoimmune diseases. However, the role of m6A in the regulation of the immune microenvironment of ankylosing spondylitis (AS) remains unclear. Therefore, we aimed to investigate the effect of m6A modification on the immune microenvironment of AS. We first evaluated RNA modification patterns mediated by 26 m6A regulators in 52 AS samples and 20 healthy samples. Thereafter, an m6A related classifier composed of seven genes was constructed and could effectively distinguish healthy and AS samples. Then, the correlation between m6A regulators and immune characteristics were investigated, including infiltrating immunocytes, immune reactions activity, and human leukocyte antigen (HLA) genes expression. The results indicated that m6A regulators was closely correlated with immune characteristics. For example, EIF3A was significantly related to infiltrating immunocytes; IGF2BP2 and EIF3A were significant regulators in immune reaction of TGF-β family member, and the expression of HLA-DPA1 and HLA-E were affected by EIF3A and ALKBH5. Next, two distinct m6A expression patterns were identified through unsupervised clustering analysis, and diverse immune characteristics were found between them. A total of 5889 m6A phenotype-related genes were obtained between the two expression patterns, and their biological functions were revealed. Finally, we validated the expression status of m6A modification regulators using two additional datasets. Our findings illustrate that m6A modifications play a critical role in the diversity and complexity of the AS immune microenvironment.

Identification and validation of a classifier based on hub aging-related genes and aging subtypes correlation with immune microenvironment for periodontitis

BACKGROUND

Periodontitis (PD), an age-related disease, is characterized by inflammatory periodontal tissue loss, and with the general aging of the global population, the burden of PD is becoming a major health concern. Nevertheless, the mechanism underlying this phenomenon remains indistinct. We aimed to develop a classification model for PD and explore the relationship between aging subtypes and the immune microenvironment for PD based on bioinformatics analysis.

MATERIALS AND METHODS

The PD-related datasets were acquired from the Gene Expression Omnibus (GEO) database, and aging-related genes (ARGs) were obtained from the Human Aging Genomic Resources (HAGR). Four machine learning algorithms were applied to screen out the hub ARGs. Then, an artificial neural network (ANN) model was constructed and the accuracy of the model was validated by receiver operating characteristic (ROC) curve analysis. The clinical effect of the model was evaluated by decision curve analysis (DCA). Consensus clustering was employed to determine the aging expression subtypes. A series of bioinformatics analyses were performed to explore the PD immune microenvironment and its subtypes. The hub aging-related modules were defined using weighted correlation network analysis (WGCNA).

RESULTS

Twenty-seven differentially expressed ARGs were dysregulated and a classifier based on four hub ARGs (BLM, FOS, IGFBP3, and PDGFRB) was constructed to diagnose PD with excellent accuracy. Subsequently, the mRNA levels of the hub ARGs were validated by quantitative real-time PCR (qRT-PCR). Based on differentially expressed ARGs, two aging-related subtypes were identified. Distinct biological functions and immune characteristics including infiltrating immunocytes, immunological reaction gene sets, the human leukocyte antigen (HLA) gene, and immune checkpoints were revealed between the subtypes. Additionally, the black module correlated with subtype-1 was manifested as the hub aging-related module and its latent functions were identified.

CONCLUSION

Our findings highlight the critical implications of aging-related genes in modulating the immune microenvironment. Four hub ARGs (BLM, FOS, IGFBP3, and PDGFRB) formed a classification model, and accompanied findings revealed the essential role of aging in the immune microenvironment for PD, providing fresh inspiration for PD etiopathogenesis and potential immunotherapy.

Autophagy-Related Genes Predict the Progression of Periodontitis Through the ceRNA Network

Purpose

The goal of this study was to identify the crucial autophagy-related genes (ARGs) in periodontitis and construct mRNA-miRNA-lncRNA networks to further understand the pathogenesis of periodontitis.

Methods

We used the Gene Expression Omnibus (GEO) database and Human Autophagy Database (HADb) to identify differentially expressed mRNAs, miRNAs, and ARGs. These ARGs were subjected to Gene Ontology (GO), KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway, and PPI (protein–protein interaction) network analysis. Two databases (miRDB and StarBase v2.0) were used to reverse-predict miRNAs while the miRNA-lncRNA interaction was predicted using the StarBase v2.0 and LncBase Predicted v.2 databases. After excluding the lncRNAs only present in the nucleus, a competing endogenous RNA (ceRNA) network was built. Finally, we used quantitative real-time PCR (qRT-PCR) to confirm the levels of mRNA expression in the ceRNA network.

Results

The differential expression analysis revealed 10 upregulated and 10 downregulated differentially expressed ARGs. After intersecting the reverse-predicted miRNAs with the differentially expressed miRNAs, a ceRNA network consisting of 4 mRNAs (LAMP2, NFE2L2, NCKAP1, and EGFR), 3 miRNAs (hsa-miR-140-3p, hsa-miR-142-5p, and hsa-miR-671-5p), and 30 lncRNAs was constructed. In addition, qRT-PCR results revealed that EGFR expression was downregulated in diseased gingival tissue of periodontitis patients.

Conclusion

Four autophagy-related genes, especially EGFR, may play a key role in periodontitis progression. The novel ceRNA network may aid in elucidating the role and the mechanism of autophagy in periodontitis, which could be important in developing new therapeutic options.

Identification of an Autophagy-Related lncRNA Prognostic Signature and Related Tumor Immunity Research in Lung Adenocarcinoma

Autophagy is closely associated with the tumor immune microenvironment (TIME) and prognosis of patients with lung adenocarcinoma (LUAD). In the present study, we established a signature on the basis of long noncoding RNAs (lncRNAs) related to autophagy (ARlncRNAs) to investigate the TIME and survival of patients with LUAD. We selected ARlncRNAs associated with prognosis to construct a model and divided each sample into different groups on the basis of risk score. The ARlncRNA signature could be recognized as an independent prognostic factor for patients with LUAD, and patients in the low-risk group had a greater survival advantage. Kyoto Encyclopedia of Genes and Genomes and Gene Ontology enrichment analysis suggested that several immune functions and pathways were enriched in different groups. A high-risk score correlated significantly negatively with high abundance of immune cells and stromal cells around the tumor and high tumor mutational burden. Low-risk patients had a higher PD-1, CTLA-4, and HAVCR2 expression and had a better efficacy of immune checkpoint inhibitors, including PD-1/CTLA-4 inhibitor. A reliable signature on the basis of ARlncRNAs was constructed to explore the TIME and prognosis of patients with LUAD, which could provide valuable information for individualized LUAD treatment.

Nicotine regulates autophagy of human periodontal ligament cells through α7 nAchR that promotes secretion of inflammatory factors IL-1β and IL-8

Background

Nicotine is an important risk factor and the main toxic component associated with periodontitis. However, the mechanism of nicotine induced periodontitis is not clear. To investigated the mechanism through which nicotine regulates autophagy of human periodontal ligament cells (hPDLCs) through the alpha7 nicotinic acetylcholine receptor (α7 nAChR) and how autophagy further regulates the release of IL-1β and IL-8 secretion in hPDLCs.

Methods

HPDLCs were obtained from root of extracted teeth and pre-incubated in alpha-bungarotoxin (α-BTX) or 3-Methyladenine (3-MA), followed by culturing in nicotine. We used a variety of experimental detection techniques including western blotting, immunofluorescence, enzyme-linked immunosorbent assay (ELISA), transmission electron microscopy (TEM) and RT-qPCR to assess the expression of the LC3 protein, autolysosome, and release of IL-1β and IL-8 from hPDLCs.

Results

Western blots, immunofluorescence and TEM results found that the nicotine significantly increased the autophagy expression in hPDLCs that was time and concentration dependent and reversed by α-BTX treatment (p < 0.05). RT-qPCR and ELISA results revealed a noticeable rise in the release of inflammatory factors IL-1β and IL-8 from hPDLCs in response to nicotine. RT-qPCR and ELISA results showed that nicotine can significantly up-regulate the release of inflammatory factors IL-1β and IL-8 in hPDLCs, and this effect can be inhibited by 3-MA (p < 0.05).

Conclusions

Nicotine regulated autophagy of hPDLCs through α7 nAChR and in turn the regulation of the release of inflammatory factors 1L-1β and 1L-8 by hPDLCs.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12903-021-01894-5.

Crosstalk between RNA-Binding Proteins and Immune Microenvironment Revealed Two RBP Regulatory Patterns with Distinct Immunophenotypes in Periodontitis

Periodontitis is an inflammatory disease whose pathogenesis is closely related with immunology. RNA-binding proteins (RBPs) were found to play crucial roles in immunity. Therefore, we aimed to investigate the potential impact of RBPs in the immune microenvironment in periodontitis. The differential expressions of RBPs in periodontitis and healthy samples were determined and were used to construct an RBP-based classifier for periodontitis using logistic regression. The correlations between RBPs and immune characteristics were investigated by the Spearman correlation. Unsupervised clustering was conducted to identify the RBP regulatory patterns. RBP-related genes were identified by WGCNA, while biological distinctions were revealed by GSVA and GO. 24 dysregulated RBPs were identified, from which a 12-RBP classifier was established to distinguish periodontitis with AUC of 0.942. Close protein-protein interactions and expression correlations were observed especially between SPATS2 and ISG20. ISG20 and ESRP1 were found to be highly correlated with immunocyte infiltration, immune signaling activation, and HLA expressions in periodontitis. Two distinct RBP regulatory patterns were identified with different immune and other biological characteristics in periodontitis. Our findings indicate a significant impact of RBPs in shaping the immune microenvironment in periodontitis, which might bring new insights into the understanding of immune mechanisms in the pathogenesis of periodontitis.

m6A regulator-mediated RNA methylation modification patterns are involved in immune microenvironment regulation of periodontitis

The role of epigenetic regulation in immunity is emerging, especially for RNA N6‐methyladenosine (m6A) modification. However, little is known about the role of m6A in the regulation of the immune microenvironment of periodontitis. Thus, we aim to investigate the impact of m6A modification in periodontitis immune microenvironment. The RNA modification patterns mediated by 23 m6A‐regulators were systematically evaluated in 310 periodontitis samples. The impact of m6A modification on immune microenvironment characteristics was explored, including infiltrating immunocytes, immune reaction gene‐sets and HLAs (human leukocyte antigen) gene. m6A phenotype‐related immune genes were also identified. 17 m6A regulators were dysregulated and a 15‐m6A regulator signature can well distinguish periodontitis and control samples. ALKBH5 and FMR1 are closely related to infiltrating monocyte abundance. ELAVL1 and CBLL1 are significant regulators in immune reaction of TNF_Family_Members_Receptors and Cytokine. The expression of HLA‐B and HLA‐DOA is affected by ALKBH5 and LRPPRC. 3 distinct RNA modification patterns mediated by 23 m6A regulators were identified. They differ from immunocyte abundance, immune reaction and HLA gene. 1631 m6A phenotype‐related genes and 70 m6A‐mediated immune genes were identified, and the biological functions of these were explored. Our finding demonstrated the m6A modification plays a crucial role in the diversity and complexity of the immune microenvironment of periodontitis.