The Association between Obstructive Sleep Apnea and Venous Thromboembolism: A Bidirectional Two-Sample Mendelian Randomization Study.

Background Despite previous observational studies linking obstructive sleep apnea (OSA) to venous thromboembolism (VTE), these findings remain controversial. This study aimed to explore the association between OSA and VTE, including pulmonary embolism (PE) and deep vein thrombosis (DVT), at a genetic level using a bidirectional two-sample Mendelian randomization (MR) analysis. Methods Utilizing summary-level data from large-scale genome-wide association studies (GWAS) in European individuals, we designed a bidirectional two-sample MR analysis to comprehensively assess the genetic association between OSA and VTE. The inverse variance weighting (IVW) was used as the primary method for MR analysis. In addition, MR-Egger, weighted median, and MR pleiotropy residual sum and outlier (MR-PRESSO) were used for complementary analyses. Furthermore, a series of sensitivity analyses were performed to ensure the validity and robustness of the results. Results The initial and validation MR analyses indicated that genetically predicted OSA had no effects on the risk of VTE (including PE and DVT). Likewise, the reverse MR analysis did not find substantial support for a significant association between VTE (including PE and DVT) and OSA. Supplementary MR methods and sensitivity analyses provided additional confirmation of the reliability of the MR results. Conclusion Our bidirectional two-sample MR analysis did not find genetic evidence supporting a significant association between OSA and VTE in either direction.

The multifaceted role of placental growth factor in the pathogenesis and progression of bronchial asthma and pulmonary fibrosis: Therapeutic implications.

Placental growth factor (PlGF) is a glycosylated dimeric protein that is homologous to vascular endothelial growth factor (VEGF). PlGF expression is upregulated in patients with bronchial asthma, suggesting that it plays a role in the pathogenesis of asthma. Bronchial asthma is characterized by chronic airway inflammation and airway hyperresponsiveness (AHR). After recurrent asthma attacks, pulmonary fibrosis develops and leads to airway remodeling and a further decline in lung function. In this review, we focused on the pivotal role of PlGF in chronic airway inflammation, AHR, and airway remodeling during bronchial asthma. Furthermore, we summarized data showing that PlGF may be a potential therapeutic target in bronchial asthma.

Development and validation of a genomic nomogram based on a ceRNA network for comprehensive analysis of obstructive sleep apnea.

Objectives: Some ceRNA associated with lncRNA have been considered as possible diagnostic and therapeutic biomarkers for obstructive sleep apnea (OSA). We intend to identify the potential hub genes for the development of OSA, which will provide a foundation for the study of the molecular mechanism underlying OSA and for the diagnosis and treatment of OSA. Methods: We collected plasma samples from OSA patients and healthy controls for the detection of ceRNA using a chip. Based on the differential expression of lncRNA, we identified the target genes of miRNA that bind to lncRNAs. We then constructed lncRNA-related ceRNA networks, performed functional enrichment analysis and protein-protein interaction analysis, and performed internal and external validation of the expression levels of stable hub genes. Then, we conducted LASSO regression analysis on the stable hub genes, selected relatively significant genes to construct a simple and easy-to-use nomogram, validated the nomogram, and constructed the core ceRNA sub-network of key genes. Results: We successfully identified 282 DElncRNAs and 380 DEmRNAs through differential analysis, and we constructed an OSA-related ceRNA network consisting of 292 miRNA-lncRNAs and 41 miRNA-mRNAs. Through PPI and hub gene selection, we obtained 7 additional robust hub genes, CCND2, WT1, E2F2, IRF1, BAZ2A, LAMC1, and DAB2. Using LASSO regression analysis, we created a nomogram with four predictors (CCND2, WT1, E2F2, and IRF1), and its area under the curve (AUC) is 1. Finally, we constructed a core ceRNA sub-network composed of 74 miRNA-lncRNA and 7 miRNA-mRNA nodes. Conclusion: Our study provides a new foundation for elucidating the molecular mechanism of lncRNA in OSA and for diagnosing and treating OSA.

A Case Report of Burkholderia mallei Infection Leading to Pneumonia.

BACKGROUND: Glanders is a rare zoonotic disease caused by Burkholderia mallei. Humans can be infected by B. mallei, which causes cutaneous lymphadenitis and pneumonia, leading to sepsis and death in severe cases. CASE PRESENTATION: We report a case of a 60-year-old male who was diagnosed with glanders. The patient who had a history of diabetes presented with cough, expectoration, and fever. Computed tomography (CT) imaging showed B. mallei infection in the right upper lobe of the lung with mediastinal lymph node involvement and the lingual segment of the left lung. Moreover, the posterior basal segment of the lower lobe of both lungs had inflammation. Subsequently, B. mallei infection was confirmed by lymph node biopsy and bronchoalveolar lavage multiplex PCR-based targeted gene sequencing. After meropenem treatment, the patient was discharged, and CT imaging showed reduced absorption of pulmonary inflammatory lesions. CONCLUSIONS: Glanders is a rare disease that can cause skin infection, lymphadenitis, and pneumonia, and in severe cases, it can be life-threatening. The diagnosis of this disease mainly relies on microbiological culture and pathological biopsy. Diagnosis is also facilitated by multiplex PCRbased targeted gene sequencing. Glanders is treated with cephalosporins, carbapenems, and other sensitive antibiotics.

Erratum: "Baicalin prevents pulmonary arterial remodeling in vivo via the AKT/ERK/NF-κB signaling pathways".

[This corrects the article DOI: 10.1177/2045894019878599.].

Development and validation of a simple clinical nomogram for predicting obstructive sleep apnea.

Obstructive sleep apnea is the most common type of sleep breathing disorder. Therefore, the purpose of our research is to construct and verify an objective and easy-to-use nomogram that can accurately predict a patient's risk of obstructive sleep apnea. In this study, we retrospectively collected the data of patients undergoing polysomnography at the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University. Participants were randomly assigned to a training cohort (50%) and a validation cohort (50%). Logistic regression and Lasso regression models were used to reduce data dimensions, select factors and construct the nomogram. C-index, calibration curve, decision curve analysis and clinical impact curve analysis were used to evaluate the identification, calibration and clinical effectiveness of the nomogram. Nomograph validation was performed in the validation cohort. The study included 1035 people in the training cohort and 1078 people in the validation cohort. Logistic and Lasso regression analysis identified age, gender, diastolic blood pressure, body mass index, neck circumference and Epworth Sleepiness Scale as the predictive factors included in the nomogram. The training cohort (C-index = 0.741) and validation cohort (C-index = 0.745) had better identification and calibration effects. The areas under the curve of the nomogram and STOP-Bang were 0.741 (0.713-0.767) and 0.728 (0.700-0.755), respectively. Decision curve analysis and clinical impact curve analysis showed that the nomogram is clinically useful. We have established a concise and practical nomogram that will help doctors better determine the priority of patients referred to the sleep centre.

The influence of sex on anthropometric methods and four scales for screening obstructive sleep apnea.

OBJECTIVES: Obstructive Sleep Apnea (OSA) is a kind of respiratory disease that occurs apnea repeatedly during sleep. The purpose of this study was to investigate the influence of sex on anthropometric methods and four scales for screening OSA. METHODS: The basic data and PSG data of 2108 patients who underwent PSG examination at the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University from July 2017 to December 2020 were continuously included. Then the sensitivity, specificity, positive predictive value, negative predictive value, AUC and DOR of the anthropometric method and the four scales were calculated. RESULTS: 2108 OSA patients were enrolled from the Sleep Medicine Center, including 1644 males (78.0%). The average neck circumference and waist circumference of male and female patients were respectively (39.4±3.4) cm and (96.7±13.8) cm,(34.6±3.5) cm and (90.1±11.6) cm. In female patients. the AUC of NoSAS was the largest. When AHI was 5, 15, and 30 evens/h as the cut-off point, in male patients, the sensitivity of NHR was the highest,in female patients, the sensitivity of WHR was the highest. CONCLUSIONS: NHR and WHR are good tools for screening OSA in male and female patients respectively. They are worthy of promotion.

Exploring the Potential Targets and Mechanisms of Huang Lian Jie Du Decoction in the Treatment of Coronavirus Disease 2019 Based on Network Pharmacology.

BACKGROUND: In December 2019, coronavirus disease 2019 (COVID-19) caused by a novel coronavirus (severe acute respiratory syndrome coronavirus 2, SARS-CoV-2; previously known as 2019-nCoV) emerged in Wuhan, China, and caused many infections and deaths. At present, there are no specific drugs for the etiology and treatment of COVID-19. A combination of traditional Chinese and western medicine is proposed to treat COVID-19, in which Huang Lian Jie Du decoction (HLJDD) is recommended for the treatment of COVID-19 in many provinces in China and has been widely used in the clinic. This study explored the potential targets of HLJDD in the treatment of COVID-19 based on network pharmacology. METHODS: First, the chemical composition and targets of HLJDD and COVID-19-related targets were obtained through the TCMSP, UniProt, GeneCards and OMIM databases. Second, HLJDD target and HLJDD-COVID-19 target networks were constructed via the STRING database and Cytoscape software. Finally, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the HLJDD-COVID-19 targets was applied via the DAVID database. RESULTS: Our study identified a total of 67 active ingredients of HLJDD and 204 targets of HLJDD. A total of 502 COVID-19-related targets were obtained, of which 47 were intersecting targets of HLJDD and COVID-19. A total of 179 GO terms and 77 KEGG terms, including the TNF signaling pathway, NF-κB signaling pathway and HIF-1 signaling pathway, were identified. CONCLUSION: The present study explored the potential targets and signaling pathways of HLJDD during the treatment of COVID-19, which may provide a basis for the research and development of drugs for the treatment of COVID-19.

HB-EGF-induced IL-8 secretion from airway epithelium leads to lung fibroblast proliferation and migration.

BACKGROUND: We have reported that heparin-binding epidermal growth factor (HB-EGF) is increased in patients with chronic obstructive pulmonary disease (COPD) and associated with collagen deposition, but the mechanisms remain unclear. In the present study, we aimed to investigated the inflammatory cytokines secreted by bronchial epithelial cells following exposure to HB-EGF that promoted proliferation and migration of human lung fibroblast. METHODS: HB-EGF-induced inflammatory cytokines were assayed in two airway epithelial cells (primary human bronchial epithelial cells [HBECs] and BEAS-2B cells). Moreover, the culture supernatants derived from HB-EGF-treated HBECs and BEAS-2B cells were added to human primary lung fibroblasts. The effect of culture supernatants on proliferation and migration of fibroblasts was assessed. RESULTS: IL-8 expression was significantly increased in bronchial epithelial cells treated with HB-EGF, which was at least partially dependent on NF-kB pathways activation. HB-EGF-induced IL-8 was found to further promote lung fibroblasts proliferation and migration, and the effects were attenuated after neutralizing IL-8. CONCLUSIONS: These findings suggest that HB-EGF may be involved in the pathology of airway fibrosis by induction of IL-8 from airway epithelium, subsequently causing lung fibroblasts proliferation and migration. Thus, inhibition of HBEGF and/or IL-8 production could prevent the development of airway fibrosis by modulating fibroblast activation.

A Pan-Cancer Analysis of the Prognostic Value and Expression of Adenylate Cyclase 7 (ADCY7) in Human Tumors.

BACKGROUND: The role of adenylate cyclase 7 (ADCY7) in cancer is still unclear. This study analyzed the interrelationship between the expression and immune function of ADCY7. METHODS: ADCY7 expression in multiple human cancers was analyzed using the databases of Genotype-Tissue Expression Project (GTEx), Cancer Cell Line Encyclopedia (CCLE), and The Cancer Genome Atlas (TCGA). Correlations among ADCY7 gene expression, mismatch repair (MMR) gene expression, and DNA methyltransferase (DNMT) expression were assessed using Spearman correlation analysis. Univariate survival analysis and Kaplan-Meier (KM) curve were used to examine the effect of ADCY7 expression on prognosis. The Tumor Immune Estimation Resource (TIMER) database was used to evaluate the relationship between ADCY7 gene expression and tumor immune invasion or immune checkpoint gene (ICG) expression. RESULTS: ADCY7 was abnormally expressed in multiple human cancers and was correlated with MMR genes and DNMT expression. Univariate survival analysis and KM curve showed that ADCY7 expression influences the overall survival (OS) of six types of cancer, disease-specific survival (DSS) of eight, and progression-free interval (PFI) of three. The high expression of ADCY7 in OS, DSS, and PFI was strongly associated with poor outcomes in patients with breast cancer and lung squamous cell carcinoma. ADCY7 expression was strongly associated with immune cell infiltration and ICG expression. CONCLUSION: The results of this study indicated that ADCY7 may be a prognostic biomarker of tumorigenesis. The study may also provide a new perspective on the role of ADCY7 in human cancers.

Comparison of six assessment tools to screen for obstructive sleep apnea in patients with hypertension.

BACKGROUND: Obstructive sleep apnea (OSA) is often accompanied by other complications, especially hypertension. HYPOTHESIS: The purpose of this study is to compare the application value of six tools in the screening of OSA in patients with hypertension. Compared with other questionnaires, we hypothesized that Berlin performed better in screening hypertensive patients suspected of OSA. METHODS: In this study, we collected the basic data and polysomnography (PSG) data of patients diagnosed with hypertension who underwent PSG at the Sleep Medicine Center of the First Affiliated Hospital of Guangzhou Medical University from April 2012 to March 2021. The sensitivity, specificity, positive predictive value, negative predictive value, area under the curv (AUC) and diagnostic odds ratio (DOR) of the six screening tools were then calculated, and their correlation with the sleep apnea hypopnea index (AHI) analyzed. RESULTS: There were 303 males (303/398, 76.1%) out of 398 hypertension patients suspected of OSA. The area under the curve of the Berlin questionnaire's receiver operating characteristic (ROC) curve reached 0.753 (95%CI: 0.707-0.794). When the AHI was 5, 15 and 30 times/h as the cut-off points, the sensitivity and negative predictive value of Berlin were the highest at 0.947 and 0.630, 0.970 and 0.851, and 0.988 and 0.957 respectively, while the specificity and positive predictive value of the Epworth Sleepiness Scale (ESS) were the highest at 0.696 and 0.729, 0.750 and 0.887, and 0.674 and 0.575 respectively. The DOR value of the Berlin questionnaire could reach 18.333 when the AHI cut-off point was 30 times/h. Berlin had the largest rank correlation coefficient with AHI at 0.466. CONCLUSION: The Berlin questionnaire can be considered a priority for the screening and stratifying of hypertensive patients suspected of OSA.

Screening of key biomarkers and immune infiltration in Pulmonary Arterial Hypertension via integrated bioinformatics analysis.

This study aimed to screen key biomarkers and investigate immune infiltration in pulmonary arterial hypertension (PAH) based on integrated bioinformatics analysis. The Gene Expression Omnibus (GEO) database was used to download three mRNA expression profiles comprising 91 PAH lung specimens and 49 normal lung specimens. Three mRNA expression datasets were combined, and differentially expressed genes (DEGs) were obtained. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses and the protein-protein interaction (PPI) network of DEGs were performed using the STRING and DAVID databases, respectively. The diagnostic value of hub gene expression in PAH was also analyzed. Finally, the infiltration of immune cells in PAH was analyzed using the CIBERSORT algorithm. Total 182 DEGs (117 upregulated and 65 downregulated) were identified, and 15 hub genes were screened. These 15 hub genes were significantly associated with immune system functions such as myeloid leukocyte migration, neutrophil migration, cell chemotaxis, Toll-like receptor signaling pathway, and NF-κB signaling pathway. A 7-gene-based model was constructed and had a better diagnostic value in identifying PAH tissues compared with normal controls. The immune infiltration profiles of the PAH and normal control samples were significantly different. High proportions of resting NK cells, activated mast cells, monocytes, and neutrophils were found in PAH samples, while high proportions of resting T cells CD4 memory and Macrophages M1 cell were found in normal control samples. Functional enrichment of DEGs and immune infiltration analysis between PAH and normal control samples might help to understand the pathogenesis of PAH.

Screening of Hub Genes Associated with Pulmonary Arterial Hypertension by Integrated Bioinformatic Analysis.

BACKGROUND: Pulmonary arterial hypertension (PAH) is a disease or pathophysiological syndrome which has a low survival rate with abnormally elevated pulmonary artery pressure caused by known or unknown reasons. In addition, the pathogenesis of PAH is not fully understood. Therefore, it has become an urgent matter to search for clinical molecular markers of PAH, study the pathogenesis of PAH, and contribute to the development of new science-based PAH diagnosis and targeted treatment methods. METHODS: In this study, the Gene Expression Omnibus (GEO) database was used to downloaded a microarray dataset about PAH, and the differentially expressed genes (DEGs) between PAH and normal control were screened out. Moreover, we performed the functional enrichment analyses and protein-protein interaction (PPI) network analyses of the DEGs. In addition, the prediction of miRNA and transcriptional factor (TF) of hub genes and construction miRNA-TF-hub gene network were performed. Besides, the ROC curve was used to evaluate the diagnostic value of hub genes. Finally, the potential drug targets for the 5 identified hub genes were screened out. RESULTS: 69 DEGs were identified between PAH samples and normal samples. GO and KEGG pathway analyses revealed that these DEGs were mostly enriched in the inflammatory response and cytokine-cytokine receptor interaction, respectively. The miRNA-hub genes network was conducted subsequently with 131 miRNAs, 7 TFs, and 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) which screened out via constructing the PPI network. 17 drugs interacted with 5 hub genes were identified. CONCLUSIONS: Through bioinformatic analysis of microarray data sets, 5 hub genes (CCL5, CXCL12, VCAM1, CXCR1, and SPP1) were identified from DEGs between control samples and PAH samples. Studies showed that the five hub genes might play an important role in the development of PAH. These 5 hub genes might be potential biomarkers for diagnosis or targets for the treatment of PAH. In addition, our work also indicated that paying more attention on studies based on these 5 hub genes might help to understand the molecular mechanism of the development of PAH.

Analyses of expressions and prognostic values of Polo-like kinases in non-small cell lung cancer.

BACKGROUND: Despite great advances in its early diagnosis and treatment, lung cancer is still an intractable disease and the second leading cause of cancer-related deaths and morbidity in the world. The family of Polo-like kinases (PLKs) consists of five serine/threonine kinases, which have been reported to participate in various human diseases. However, the expression and prognostic value of each PLK in human lung cancer have not been fully understood. This study analyzed mRNA expression and prognostic value of different PLKs in human non-small cell lung cancer (NSCLC). METHODS: First, mRNA expression of PLKs in patients with NSCLC from the Oncomine and the Gene Expression Profiling Interactive Analysis (GEPIA) database was investigated. Then, a Kaplan-Meier plotter was employed for survival analysis. The sequence alteration for PLKs was analyzed using The Cancer Genome Atlas (TCGA) and the cBioPortal database. Additionally, we analyzed the association among different PLKs using the LinkedOmics database. Finally, the enrichment analysis of PLKs was achieved using the DAVID database. RESULTS: The mRNA expression levels of PLK1 and PLK4 were significantly overexpressed, while mRNA expression level of PLK3 was underexpressed in patients with NSCLC. mRNA expressions of PLK1 and PLK4 were significantly and positively related to the tumor stage of NSCLC. Increased expressions of PLK1, PLK4, and PLK5 and decreased expression of PLK2 were attributed to limited overall survival time in NSCLC. PLK1 was positively correlated with PLK4 via the LinkedOmics database. CONCLUSIONS: PLKs are relevant targets for NSCLC treatment, especially PLK1 and PLK4.

Screening of hub genes associated with prognosis in non-small cell lung cancer by integrated bioinformatics analysis.

BACKGROUND: Lung cancer is an intractable disease and the second leading cause of cancer-related deaths and morbidity in the world. This study conducted a bioinformatics analysis to identify critical genes associated with poor prognosis in non-small cell lung cancer (NSCLC). METHODS: We downloaded three datasets (GSE33532, GSE27262, and GSE18842) from the gene expression omnibus (GEO), and used the GEO2R online tools to identify the differentially expressed genes (DEGs). We then used the Search Tool for Retrieval of Interacting Genes (STRING) database to establish a protein-protein interaction (PPI) network and used the Cytoscape software to perform a module analysis of the PPI network. A Kaplan-Meier plotter was used to perform the overall survival (OS) analysis, and the Gene Expression Profiling Interactive Analysis (GEPIA) database was used for expression level analysis of hub genes. Further, the UALCAN database was used to validate the relationship between the gene expression level of each hub gene and clinical characteristics. RESULTS: We identified 254 DEGs, which were composed of 66 up-regulated genes and 188 down-regulated genes. Out of these, five DEGs were identified as hub genes (CDC20, BUB1, CCNB2, CCNB1, UBE2C) by constructing a PPI network. The use of a Kaplan-Meier plotter to generate patient survival curves suggested a strong relationship between the five hub genes with worse OS. Validation of the above results using the GEPIA database showed that all the hub genes were highly expressed in NSCLC tissues. Using the UALACN data mining platform, we found that the five hub genes are correlated with tumor stage and the status of node metastasis in NSCLC patients. CONCLUSIONS: We identified five hub DEGs that might provide perspectives in the explorations of pathogenesis and treatments for NSCLC.

The No-apnea score vs. the other five questionnaires in screening for obstructive sleep apnea-hypopnea syndrome in patients with cerebral infarction.

BACKGROUND: Given the growing number of patients suspected of having obstructive sleep apnea-hypopnea syndrome (OSAHS), screening methods have become increasingly important for sleep clinics. We analyzed the clinical value of the No-apnea score which is used to diagnose OSAHS in patients with cerebral infarction, and compared the accuracy of the No-apnea score with the accuracy of the NoSAS score, the STOP-Bang questionnaire (SBQ), the Epworth Sleepiness Scale (ESS), the STOP questionnaire (STOP) and the Berlin questionnaire (BQ). METHODS: Between January 2014 and December 2018, a total of 221 cerebral infarction patients, suspected of having OSAHS, underwent the polysomnography (PSG) for one night at the sleep medical center of Guangdong Medical University Affiliated Second Hospital. The PSG data were collected and analyzed with the NoSAS score, the SBQ, the ESS, the STOP, the BQ, and patients' demographic information. Based on the apnea-hypopnea index (AHI), the patients were classified into four groups: the normal group (<5 events/h), mild OSAHS group (5-15 events/h), moderate OSAHS group (15-30 events/h) and severe OSAHS group (≥30 events/h). The sensitivity, specificity, positive predictive value, negative predictive value and areas under the curve (AUC) of the Receiver Operating Curve (ROC) were calculated for the five questionnaires to compare their relative efficacies for diagnosing OSAHS. RESULTS: When using the standard of AHI ≥5 for diagnosing OSAHS, the NoSAS score had an AUC of 0.831; the SBQ had an AUC of 0.730; the BQ had an AUC of 0.698; and the STOP had an AUC of 0.735, so these techniques are relatively accurate in diagnosing OSAHS. On the other hand, the No-apnea score and the ESS score are relatively less accurate comparing to the rest: the No-apnea had an AUC of 0.626, and the ESS had an AUC of 0.650. Using the NoSAS score to predict AHI ≥5 events/h, AHI ≥15 events/h and AHI ≥30 events/h, the sensitivity and specificity were 0.867 and 0.731, 0.888 and 0.476, 0.889 and 0.369, respectively; Using the SBQ to predict AHI ≥5 events/h, AHI 15 events/h and AHI ≥30 events/h, the sensitivity and specificity were 0.903 and 0.268, 0.914 and 0.200, 0.903 and 0.268, respectively; Using the STOP to predict AHI ≥5 events/h, AHI ≥15 events/h and AHI ≥30 events/h, the values were 0.830 and 0.500, 0.871 and 0.390, 0.875 and 0.302, respectively; and using the BQ to predict AHI ≥5 events/h, AHI ≥15 events/h and AHI ≥30 events/h, the values were 0.758 and 0.482, 0.810 and 0.429, 0.819 and 0.362, respectively. CONCLUSIONS: The study concludes that the NoSAS score and the SBQ had a better predictive value for cerebral infarction patients suspected with OSAHS disease. These questionnaires can also effectively help clinicians quickly address nocturnal hypoxia in patients with cerebral infarction to control subsequent complications in patients with cerebral infarction. More studies are needed to evaluate the efficacy of the NoSAS score in screening for OSAHS in patients with cerebral infarction.