Association between blood pressure, inflammation and spirometry parameters in chronic obstructive pulmonary disease

Metabolic syndrome, genetic susceptibility, and risk of chronic obstructive pulmonary disease: The UK Biobank Study

AIM

To investigate the effect of metabolic syndrome (MetS), genetic predisposition, and their interactions, on the risk of developing chronic obstructive pulmonary disease (COPD).

METHODS

Cohort analyses included 287 868 participants from the UK Biobank Study. A genetic risk score for COPD was created using 277 single nucleotide polymorphisms. Cox proportional hazard models were used to evaluate the hazard ratios (HRs) with 95% confidence intervals (CIs) for COPD in relation to exposure factors.

RESULTS

During 2 658 936 person-years of follow-up, 5877 incident cases of COPD were documented. Compared with participants without MetS, those with MetS had a higher risk of COPD (HR 1.24, 95% CI 1.17-1.32). Compared to participants with low genetic predisposition, those with high genetic predisposition had a 17% increased risk of COPD. In the joint analysis, compared with participants without MetS and low genetic predisposition, the HR for COPD for those with MetS and high genetic predisposition was 1.50 (95% CI 1.36-1.65; P < 0.001). However, no significant interaction between MetS and genetic risk was found.

CONCLUSIONS

Metabolic syndrome was found to be associated with an increased risk of COPD, regardless of genetic risk. It is crucial to conduct further randomized control trials to determine whether managing MetS and its individual components can potentially reduce the likelihood of developing COPD.

Using random forest machine learning on data from a large, representative cohort of the general population improves clinical spirometry references

INTRODUCTION

Spirometry is associated with several diagnostic difficulties, and as a result, misdiagnosis of chronic obstructive pulmonary disease (COPD) occurs. This study aims to investigate how random forest (RF) can be used to improve the existing clinical FVC and FEV1 reference values in a large and representative cohort of the general population of the US without known lung disease.

MATERIALS AND METHODS

FVC, FEV1, body measures, and demographic data from 23 433 people were extracted from NHANES. RF was used to develop different prediction models. The accuracy of RF was compared with the existing Danish clinical references, an improved multiple linear regression (MLR) model, and a model from the literature.

RESULTS

The correlation between actual and predicted FVC and FEV1 and the 95% confidence interval for RF were found to be FVC = 0.85 (0.85; 0.86) (p < 0.001), FEV1 = 0.92 (0.92; 0.93) (p < 0.001), and existing clinical references were FVC = 0.66 (0.64; 0.68) (p < 0.001) and FEV1 = 0.69 (0.67; 0.70) (p < 0.001). Slope and intercept for the RF models predicting FVC and FEV1 were FVC 1.06 and -238.04 (mL), FEV1: 0.86 and 455.36 (mL), and for the MLR models, slope and intercept were FVC: 0.99 and 38.56 39 (mL), and FEV1: 1.01 and -56.57-57 (mL).

CONCLUSIONS

The results point toward machine learning models such as RF have the potential to improve the prediction of estimated lung function for individual patients. These predictions are used as reference values and are an important part of assessing spirometry measurements in clinical practice. Further work is necessary in order to reduce the size of the intercepts obtained through these results.

ASSOCIATION OF CASPASE-8 LEVELS WITH RESPIRATORY PARAMETERS AND PRESENCE OF HYPERTENSION IN COPD PATIENTS

OBJECTIVE

The aim: To investigate the association between hypertension and serum Caspase-8 levels in COPD patients.

PATIENTS AND METHODS

Materials and methods: 95 COPD patients (GOLD 2nd grade, group B) were included in the study: 47 non-hypertensive COPD patients formed the main group, and 48 patients with concomitant COPD and hypertension formed the comparison group. Patients underwent examination according to GOLD 2022 Guidelines. Caspase-8 serum levels were measured by ELISA.

RESULTS

Results: Performed analysis showed that an increase in Caspase-8 serum levels was significantly associated with the presence of concomitant hypertension in both univariate and multivariate analyses. A significant association was also found regarding FEV1 levels but not FVC.

CONCLUSION

Conclusions: Both presence of concomitant hypertension and spirometry parameters, which indicate the severity of COPD, can be considered strong predictors of the intensification of apoptosis in COPD patients.

PROGNOSTIC POTENTIAL OF LYMPHOCYTE-TO-MONOCYTE RATIO AND CASPASE-8 IN PREDICTION OF CHRONIC OBSTRUCTIVE PULMONARY DISEASE DEVELOPMENT

OBJECTIVE

The aim: To investigate the prognostic potential of lymphocyte-to-monocyte ratio and caspase-8 levels in prognosis of COPD development in healthy individuals.

PATIENTS AND METHODS

Materials and methods: 77 individuals were involved into the study: 47 with COPD and 30 healthy volunteers. Patients underwent examination according to GOLD 2022 Guidelines. Caspase-8 serum levels were measured by ELISA. Lymphocyte-to-monocyte ratio was calculated.

RESULTS

Results: In crude and adjusted models lymphocyte-to-monocyte ratio and caspase-8 were associated with COPD development (respectively OR = 0.371 [95.0 % CI 0.217-0.634], p<0.006 and OR = 12.823 [95.0 % CI 2.104-78.134], p = 0.006). Additionally, systolic blood pressure had direct association with COPD (OR = 1.196 [95.0 % CI 1.028-1.391], p = 0.021). Noteworthy, diastolic blood pressure showed significant reverse association in univariate but not in multivariate analysis: OR = 0.850 [95.0 % CI 0.743-0.974] (p = 0.019) and OR = 0.820 [95.0 % CI 0.665-1.012] (p =0.064).

CONCLUSION

Conclusions: Decreased lymphocyte-to-monocyte ratio and increased caspase-8 levels are important predictors of COPD development and can serve as an additional tool for early diagnosis of COPD in healthy individuals.

Serum cadmium positively correlates with inflammatory cytokines in patients with chronic obstructive pulmonary disease

BACKGROUND

Cadmium is a ubiquitous toxic heavy metal and environmental toxicant. Inflammation exerts central roles in the process of chronic obstructive pulmonary disease (COPD). However, few epidemiological studies on the correlation between cadmium exposure and COPD are available. The aim of this study was to evaluate the correlations among serum cadmium, inflammatory cytokines and pulmonary function in COPD patients.

METHODS

All 940 COPD patients were finally recruited in this study. Demographic characteristics and clinical information were extracted. Fasting serum was collected. Serum cadmium was detected through graphite furnace atomic absorption spectrophotometry. Serum inflammatory cytokines were measured using enzyme-linked immunosorbent assay.

RESULTS

All patients were classified into three groups according to the tertile division of serum cadmium concentration: low (<0.77 μg/L, L), medium (0.77-1.01 μg/L, M), and high (1.01 μg/L, H). Logistic regression analysis found that serum cadmium was inversely correlated with pulmonary function before and after adjusted confounding variables. When stratified by gender, serum cadmium was still negatively correlated with pulmonary function in COPD patients. Moreover, higher serum cadmium elevated CAT (COPD Assessment Test) score before and after adjusted confounding variables. Though a non-linear association between serum cadmium and inflammatory cytokines, serum cadmium was positively associated with inflammatory cytokines (TNF-α and MCP-1). TNF-α and MCP-1 exerted a partial mediator in the association between cadmium exposure and pulmonary function decline in COPD patients.

CONCLUSIONS

Serum cadmium concentration is inversely correlated with pulmonary function among COPD patients. Inflammatory cytokines may be important mediators for cadmium-induced pulmonary function decline in COPD patients.

Forecast the Exacerbation in Patients of Chronic Obstructive Pulmonary Disease with Clinical Indicators Using Machine Learning Techniques

Preventing exacerbation and seeking to determine the severity of the disease during the hospitalization of chronic obstructive pulmonary disease (COPD) patients is a crucial global initiative for chronic obstructive lung disease (GOLD); this option is available only for stable-phase patients. Recently, the assessment and prediction techniques that are used have been determined to be inadequate for acute exacerbation of chronic obstructive pulmonary disease patients. To magnify the monitoring and treatment of acute exacerbation COPD patients, we need to rely on the AI system, because traditional methods take a long time for the prognosis of the disease. Machine-learning techniques have shown the capacity to be effectively used in crucial healthcare applications. In this paper, we propose a voting ensemble classifier with 24 features to identify the severity of chronic obstructive pulmonary disease patients. In our study, we applied five machine-learning classifiers, namely random forests (RF), support vector machine (SVM), gradient boosting machine (GBM), XGboost (XGB), and K-nearest neighbor (KNN). These classifiers were trained with a set of 24 features. After that, we combined their results with a soft voting ensemble (SVE) method. Consequently, we found performance measures with an accuracy of 91.0849%, a precision of 90.7725%, a recall of 91.3607%, an F-measure of 91.0656%, and an AUC score of 96.8656%, respectively. Our result shows that the SVE classifier with the proposed twenty-four features outperformed regular machine-learning-based methods for chronic obstructive pulmonary disease (COPD) patients. The SVE classifier helps respiratory physicians to estimate the severity of COPD patients in the early stage, consequently guiding the cure strategy and helps the prognosis of COPD patients.

Low Vitamin D Status Is Associated with Inflammation in Patients with Chronic Obstructive Pulmonary Disease

Vitamin D deficiency is associated with increased risks of chronic obstructive pulmonary disease (COPD). Nevertheless, the mechanisms remain unknown. This study analyzed the correlations between vitamin D levels and inflammation in COPD patients. One hundred and one patients with COPD and 202 control subjects were enrolled. Serum 25(OH)D level and inflammatory cytokines were detected. Serum 25(OH)D was decreased and inflammatory cytokines were increased in COPD patients. According to forced expiratory volume in 1 s, COPD patients were divided into three grades. Furthermore, serum 25(OH)D was gradually decreased in COPD patients ranging from grade 1-2 to 4. Serum 25(OH)D was inversely associated with inflammatory cytokines in COPD patients. Further analysis found that NF-κB and AP-1 signaling were activated in COPD patients. Besides, inflammatory signaling was gradually increased in parallel with the severity of COPD. By contrast, pulmonary nuclear vitamin D receptor was decreased in COPD patients. In vitro experiments showed that 1,25(OH)₂D₃ inhibited LPS-activated inflammatory signaling in A549 cells (human lung adenocarcinoma cell). Mechanically, 1,25(OH)₂D₃ reinforced physical interactions between vitamin D receptor with NF-κB p65 and c-Jun. Our results indicate that vitamin D is inversely correlated with inflammatory signaling in COPD patients. Inflammation may be a vital mediator of COPD progress in patients with low vitamin D levels.