TLR-Induced IL-12 and CCL2 Production by Myeloid Cells Is Dependent on Adenosine A3 Receptor-Mediated Signaling

Identification of biomarkers associated with diagnosis of postmenopausal osteoporosis patients based on bioinformatics and machine learning

Background: Accumulating evidence suggests that postmenopausal osteoporosis (PMOP) is a common chronic systemic metabolic bone disease, but its specific molecular pathogenesis remains unclear. This study aimed to identify novel genetic diagnostic markers for PMOP. Methods: In this paper, we combined three GEO datasets to identify differentially expressed genes (DEGs) and performed functional enrichment analysis of PMOP-related differential genes. Key genes were analyzed using two machine learning algorithms, namely, LASSO and the Gaussian mixture model, and candidate biomarkers were found after taking the intersection. After further ceRNA network construction, methylation analysis, and immune infiltration analysis, ACACB and WWP1 were finally selected as diagnostic markers. Twenty-four clinical samples were collected, and the expression levels of biomarkers in PMOP were detected by qPCR. Results: We identified 34 differential genes in PMOP. DEG enrichment was mainly related to amino acid synthesis, inflammatory response, and apoptosis. The ceRNA network construction found that XIST-hsa-miR-15a-5p/hsa-miR-15b-5p/hsa-miR-497-5p and hsa-miR-195-5p-WWP1/ACACB may be RNA regulatory pathways regulating PMOP disease progression. ACACB and WWP1 were identified as diagnostic genes for PMOP, and validated in datasets and clinical sample experiments. In addition, these two genes were also significantly associated with immune cells, such as T, B, and NK cells. Conclusion: Overall, we identified two vital diagnostic genes responsible for PMOP. The results may help provide potential immunotherapeutic targets for PMOP.

Experimental animal models of chronic inflammation

Inflammation is a general term for a wide variety of both physiological and pathophysiological processes in the body which primarily prevents the body from diseases and helps to remove dead tissues. It has a crucial part in the body immune system. Tissue damage can recruit inflammatory cells and cytokines and induce inflammation. Inflammation can be classified as acute, sub-acute, and chronic. If it remained unresolved and lasted for prolonged periods, it would be considered as chronic inflammation (CI), which consequently exacerbates tissue damage in different organs. CI is the main pathophysiological cause of many disorders such as obesity, diabetes, arthritis, myocardial infarction, and cancer. Thus, it is critical to investigate different mechanisms involved in CI to understand its processes and to find proper anti-inflammatory therapeutic approaches for it. Animal models are one of the most useful tools for study about different diseases and mechanisms in the body, and are important in pharmacological studies to find proper treatments. In this study, we discussed the various experimental animal models that have been used to recreate CI which can help us to enhance the understanding of CI mechanisms in human and contribute to the development of potent new therapies.

Identification of early biomarkers of transcriptomics in alveolar macrophage for the prognosis of intubated ARDS patients

Background

Currently, the rate of morbidity and mortality in acute respiratory distress syndrome (ARDS) remains high. One of the potential reasons for the poor and ineffective therapies is the lack of early and credible indicator of risk prediction that would help specific treatment of severely affected ARDS patients. Nevertheless, assessment of the clinical outcomes with transcriptomics of ARDS by alveolar macrophage has not been performed.

Methods

The expression data GSE116560 was obtained from the Gene Expression Omnibus databases (GEO) in NCBI. This dataset consists of 68 BAL samples from 35 subjects that were collected within 48 h of ARDS. Differentially expressed genes (DEGs) of different outcomes were analyzed using R software. The top 10 DEGs that were up- or down-regulated were analyzed using receiver operating characteristic (ROC) analysis. Kaplan–Meier survival analysis within two categories according to cut-off and the value of prediction of the clinical outcomes via DEGs was verified. GO enrichment, KEGG pathway analysis, and protein–protein interaction were also used for functional annotation of key genes.

Results

24,526 genes were obtained, including 235 up-regulated and 292 down-regulated DEGs. The gene ADORA3 was chosen as the most obvious value to predict the outcome according to the ROC and survival analysis. For functional annotation, ADORA3 was significantly augmented in sphingolipid signaling pathway, cGMP-PKG signaling pathway, and neuroactive ligand-receptor interaction. Four genes (ADORA3, GNB1, NTS, and RHO), with 4 nodes and 6 edges, had the highest score in these clusters in the protein–protein interaction network.

Conclusions

Our results show that the prognostic prediction of early biomarkers of transcriptomics as identified in alveolar macrophage in ARDS can be extended for mechanically ventilated critically ill patients. In the long term, generalizing the concept of biomarkers of transcriptomics in alveolar macrophage could add to improving precision-based strategies in the ICU patients and may also lead to identifying improved strategy for critically ill patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12890-022-02130-8.

NAD+-consuming enzymes in immune defense against viral infection

The COVID-19 pandemic reminds us that in spite of the scientific progress in the past century, there is a lack of general antiviral strategies. In analogy to broad-spectrum antibiotics as antibacterial agents, developing broad spectrum antiviral agents would buy us time for the development of vaccines and treatments for future viral infections. In addition to targeting viral factors, a possible strategy is to understand host immune defense mechanisms and develop methods to boost the antiviral immune response. Here we summarize the role of NAD⁺-consuming enzymes in the immune defense against viral infections, with the hope that a better understanding of this process could help to develop better antiviral therapeutics targeting these enzymes. These NAD⁺-consuming enzymes include PARPs, sirtuins, CD38, and SARM1. Among these, the antiviral function of PARPs is particularly important and will be a focus of this review. Interestingly, NAD⁺ biosynthetic enzymes are also implicated in immune responses. In addition, many viruses, including SARS-CoV-2 contain a macrodomain-containing protein (NSP3 in SARS-CoV-2), which serves to counteract the antiviral function of host PARPs. Therefore, NAD⁺ and NAD⁺-consuming enzymes play crucial roles in immune responses against viral infections and detailed mechanistic understandings in the future will likely facilitate the development of general antiviral strategies.

Identification of Potential Risk Genes and the Immune Landscape of Idiopathic Pulmonary Arterial Hypertension via Microarray Gene Expression Dataset Reanalysis

Gene dysfunction and immune cell infiltration play an essential role in the pathogenesis of idiopathic pulmonary arterial hypertension (IPAH). We aimed to investigate the immune landscape and novel differentially expressed genes (DEGs) of IPAH. In addition, potential druggable molecular targets for IPAH were also explored. In this study, the GSE117261 dataset was reanalyzed to explore the immune landscape and hub DEGs of IPAH. Lasso Cox regression analysis and receiver operating characteristic curve analysis were performed to detect the predictive value of IPAH. Additionally, the underlying drug targets for IPAH treatment were determined by drug-gene analysis. IPAH was significantly associated with the transforming growth factor-β (TGF-β) signaling pathway and Wnt signaling pathway as well as energetic metabolism dysfunction. We identified 31 upregulated and 39 downregulated DEGs in IPAH patients. Six hub genes, namely, SAA1, CCL5, CXCR1, CXCR2, CCR1, and ADORA3, were related to IPAH pathogenesis regardless of sex differences. Prediction model analysis showed that the area under the curve values of the hub DEGs except CXCR2 were all above 0.9 for distinguishing IPAH patients. In addition, the relative proportions of 5 subtypes of immune cells, namely, CD₈ ⁺ T cells, CD₄ ⁺ memory resting T cells, γ delta T cells, M1 macrophages, and resting mast cells, were significantly upregulated in the IPAH samples, while 6 subtypes of immune cells, namely, CD₄ ⁺ naive T cells, resting NK cells, monocytes, M0 macrophages, activated mast cells, and neutrophils, were downregulated. Additionally, a total of 17 intersecting drugs targeting 5 genes, CCL5, CXCR1, CXCR2, CCR1, and ADORA3, were generated as potential druggable molecular targets for IPAH. Our study revealed the underlying correlations between genes and immune cells in IPAH and demonstrated for the first time that SAA1, CCL5, CXCR1, CCR1, and ADORA3 may be novel genetic targets for IPAH.

Direct Comparison of (N)-Methanocarba and Ribose-Containing 2-Arylalkynyladenosine Derivatives as A3 Receptor Agonists

A side-by-side pharmacological comparison of ribose and (N)-methanocarba (bicyclo[3.1.0]hexane) nucleosides as A₃AR agonists indicated that the bicyclic pseudoribose ring constraint provided higher affinity/selectivity at human and mouse A₃AR. The mean affinity enhancement for 5 pairs of 5'-methylamides was 11-fold at hA₃AR and 42-fold at mA₃AR. Novel C2-(5-fluorothien-2-ylethynyl) substitution enhanced affinity in the methanocarba but not ribose series, with highly hA₃AR-selective 16 (MRS7334) displaying K_i 280 pM and favorable pharmacokinetics and off-target activity profile. Molecular dynamics comparison of 16 and its corresponding riboside 8 suggested a qualitative entropic advantage of 16 in hA₃AR binding. The 5-F substitution tended to increase hA₃AR affinity (cf. 5-Cl) for methanocarba but not ribose derivatives. A representative methanocarba agonist 4 was shown to interact potently exclusively with A₃AR, among 240 GPCRs and 466 kinases. Thus, despite added synthetic difficulty, the (N)-methanocarba modification has distinct advantages for A₃AR agonists, which have translational potential for chronic disease treatment.

Modulation of myeloid cells by adenosine signaling

Hypoxia, metabolic activity, cell death and immune responses influence the adenosine concentrations in the extracellular space. Cellular responses to hypoxia and inflammation in myeloid cells promote activation of adenosine sensing circuit, which involves increased expression of ectoenzymes that converts phospho-nucleotides such as ATP to adenosine and increased expression of G protein-coupled adenosine receptors. Adenosine sensing circuitry also involves feedforward signaling, which leads to increased expression of hypoxia-inducible factor 1-alpha (HIF1 and feedback signaling, which leads to the suppression of inflammatory transcription factor, the nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) activation. In this review we will discuss how different subsets of myeloid cells sense adenosine accumulation and how adenosine sensing by myeloid cells influence progression of different immune-related conditions including cancer.