Visualization of the individual blood microbiome to study the etiology of sarcoidosis.

Introduction: Single microbial pathogens or host-microbiome dysbiosis are the causes of lung diseases with suspected infectious etiology. Metagenome sequencing provides an overview of the microbiome content. Due to the rarity of most granulomatous lung diseases collecting large systematic datasets is challenging. Thus, single-patient data often can only be summarized visually. Objective: To increase the information gain from a single-case metagenome analysis we suggest a quantitative and qualitative approach. Results: The 16S metagenomic results of 7 patients with pulmonary sarcoidosis were compared with those of 22 healthy individuals. From lysed blood, total microbial DNA was extracted and sequenced. Cleaned data reads were identified taxonomically using Kraken 2 software. Individual metagenomic data were visualized with a Sankey diagram, Krona chart, and a heat-map. We identified five genera that were exclusively present or significantly enhanced in patients with sarcoidosis - Veillonella, Prevotella, Cutibacterium, Corynebacterium, and Streptococcus. Conclusions: Our approach can characterize the blood microbiome composition and diversity in rare diseases at an individual level. Investigation of the blood microbiome in patients with granulomatous lung diseases of unknown etiology, such as sarcoidosis could enhance our comprehension of their origin and pathogenesis and potentially uncover novel personalized therapeutics.

Left ventricular diastolic dysfunction in non-severe chronic obstructive pulmonary disease - a step forward in cardiovascular comorbidome.

Chronic obstructive pulmonary disease (COPD) augments the likelihood of having left ventricular diastolic dysfunction (LVDD)-precursor of heart failure with preserved ejection fraction (HFpEF). LVDD shares overlapping symptomatology (cough and dyspnea) with COPD. Stress induced LVDD is indicative of masked HFpEF. Our aim was to evaluate the predictive value of inflammatory, oxidative stress, cardio-pulmonary and echocardiographic parameters at rest for the diagnosis of stress LVDD in non-severe COPD patients, who complain of exertional dyspnea and are free of overt cardiovascular diseases. A total of 104 COPD patients (26 patients with mild and 78 with moderate COPD) underwent echocardiography before cardio-pulmonary exercise testing (CPET) and 1-2 minutes after peak exercise. Patients were divided into two groups based on peak average E/e': patients with stress induced left ventricular diastolic dysfunction (LVDD)-E/e' > 15 masked HFpEF and patients without LVDD-without masked HFpEF. CPET and echocardiographic parameters at rest were measured and their predictive value for stress E/e' was analysed. Markers for inflammation (resistin, prostaglandine E2) and oxidative stress (8-isoprostanes) were also determined. Stress induced LVDD occurred in 67/104 patients (64%). Those patients showed higher VE/VCO2 slope. None of the CPET parameters was an independent predictor for stress LVDD.Except for prostglandine E2, none of the inflammatory or oxidative stress markers correlated to stress E/e'. The best independent predictors for stress LVDD (masked HFpEF) were RAVI, right ventricular parasternal diameter and RV E/A >0.75. Their combination predicted stress LVDD with the accuracy of 91.2%. There is a high prevalence of masked HFpEF in non-severe COPD with exertional dyspnea, free of overt cardiovascular disease. RAVI, right ventricular parasternal diameter and RV E/A >0.75 were the only independent clinical predictors of masked HFpEF. 288.

Immunohistochemical characteristics of brain metastases and corresponding primary lung cancer.

PURPOSE: to study brain metastases (BM) and their corresponding primary lung cancers (LCs). METHODS: Surgically resected BMs and their corresponding primary LCs from 30 patients (25 men, 83%; age 55±9 years) were studied: 21 adenocarcinomas (ACs), 5 squamous cell carcinomas (SCCs), 4 small cell lung carcinomas (SCLCs). The histological subtype, immunohistochemical expression of TTF1, p63, Ki67 (proliferative activity), CD31, number of intratumoral microvessels, (NIM) and survival were evaluated. RESULTS: There was a different histological structure in 47% of the cases of ACs of the lung in comparison with the corresponding metastasis, but none in SCC and SCLC. TTF-1 was expressed in a greater number of ACs (n=20; 95%), with lower mean expression levels, while the corresponding BM expressed the marker less frequently (n=16;76%) with higher mean expression values (p=0.011). P63 was expressed in all SCCs (p=0.68). Cytokeratin 7 was expressed equally in all ACs. Ki-67 proliferative index (PI) was higher in SCLC than in AC (p=0.008), in SCLC BM than in AC BM (p<0.001), and in SCLC BM than in SCC BM (p=0.008). The Ki-67 PI in BM was higher than in AC (p=0.003), SCC (p=0.048), but without difference in SCLC (p=0.141). CD31 NIM was higher in AC than in SCLC (p=0.003), in SCC than in SCLC (p=0.009), while no difference between AC and SCC was found (p=0.467). There were no differences between LC/BM in the NIM. Survival after surgery for LC was significantly longer in AC than in SCLC (p=0.017). SCLC histology and Ki67>18% were established as negative prognostic factors after surgery for LC. Such factors were not found after surgery for BM. CONCLUSION: There are differences between primary LC and corresponding BM - in histology, immunohistochemical expression and proliferative activity, but there are no significant differences in vascularization. SCLC histology and Ki67>8% may represent negative prognostic factors after surgery for LC with BM.

Serum levels of IL-5, IL-6, IL-8, IL-13 and IL-17A in pre-defined groups of adult patients with moderate and severe bronchial asthma.

BACKGROUND: Bronchial asthma (BA) is a complex disease characterised by persistent inflammation. Exhaled nitric oxide (FeNO) and blood eosinophil count (b-Eos) are biomarkers for type 2 endotype of BA. OBJECTIVE: To analyse a panel of serum interleukins and total IgE in predefined by FeNO and b-Eos groups of moderate and severe BA patients. METHODS: Serum levels of IL-5, IL-6, IL-8, IL-13 and IL-17A (ELISA) were measured in 30 healthy controls (HC) and 80 adult BA patients. BA patients were split into 4 groups. Group 1:Low FeNO/Low b-Eos (n = 23; 28.8%); Group 2:Low FeNO/High b-Eos (n = 17; 21.3%); Group 3:High FeNO/Low b-Eos (n = 15; 18.8%); Group 4:High FeNO/High b-Eos (n = 25; 31.3%). RESULTS: All interleukins and total IgE were significantly higher in patients with BA as compared with HC. IL-5 levels were highest in Group 2 (p < 0.05). IL-6, IL-13 and IL-17A levels were elevated in Groups 2, 3 and 4 as compared with HC (p < 0.05). Higher IL-8 levels were associated with a pattern of current smokers. Highest IL-17A levels were found in type 2 high groups with frequent exacerbations, mostly uncontrolled and severe BA. We have found a distinct pattern for each group based on demographic, clinical, functional, immunological and inflammatory characteristics. CONCLUSION: FeNO and b-Eos are useful in the identification of severe type 2 BA subgroups with frequent exacerbations. IL-5, IL-6, IL-13 and IL-17A are involved in the persistent type 2 immune response in moderate and severe BA. We have identified a pattern of refractory, severe type 2/IL-17A high BA in the real clinical practice.

Phenotypes Determined by Cluster Analysis in Moderate to Severe Bronchial Asthma.

BACKGROUND: Bronchial asthma is a heterogeneous disease that includes various subtypes. They may share similar clinical characteristics, but probably have different pathological mechanisms. AIM: To identify phenotypes using cluster analysis in moderate to severe bronchial asthma and to compare differences in clinical, physiological, immunological and inflammatory data between the clusters. PATIENTS AND METHODS: Forty adult patients with moderate to severe bronchial asthma out of exacerbation were included. All underwent clinical assessment, anthropometric measurements, skin prick testing, standard spirometry and measurement fraction of exhaled nitric oxide. Blood eosinophilic count, serum total IgE and periostin levels were determined. Two-step cluster approach, hierarchical clustering method and k-mean analysis were used for identification of the clusters. RESULTS: We have identified four clusters. Cluster 1 (n=14) - late-onset, non-atopic asthma with impaired lung function, Cluster 2 (n=13) - late-onset, atopic asthma, Cluster 3 (n=6) - late-onset, aspirin sensitivity, eosinophilic asthma, and Cluster 4 (n=7) - early-onset, atopic asthma. CONCLUSIONS: Our study is the first in Bulgaria in which cluster analysis is applied to asthmatic patients. We identified four clusters. The variables with greatest force for differentiation in our study were: age of asthma onset, duration of diseases, atopy, smoking, blood eosinophils, nonsteroidal anti-inflammatory drugs hypersensitivity, baseline FEV1/FVC and symptoms severity. Our results support the concept of heterogeneity of bronchial asthma and demonstrate that cluster analysis can be an useful tool for phenotyping of disease and personalized approach to the treatment of patients.