A unique protein profile of peripheral neutrophils from COPD patients does not reflect cytokine-induced protein profiles of neutrophils in vitro.

BACKGROUND: Inflammation, both local and systemic, is a hallmark of chronic obstructive pulmonary disease (COPD). Inflammatory mediators such as TNFα and GM-CSF are secreted by lung epithelium, alveolar macrophages and other inflammatory cells and are thought to be important contributors in the pathogenesis of COPD. Indeed, neutrophils are activated by these cytokines and these cells are one of the major inflammatory cell types recruited to the pulmonary compartment of COPD patients. Furthermore, these inflammatory mediators are found in the peripheral blood of COPD patients and, therefore, we hypothesized that TNFα/GM-CSF-induced protein profiles can be found in peripheral neutrophils of COPD patients. METHODS: Using fluorescence 2-dimensional difference gel electrophoresis we investigated differentially regulated proteins in peripheral neutrophils from COPD patients and healthy age-matched control subjects. Furthermore, protein profiles from COPD patients were compared with those of neutrophils of healthy age-matched controls that were stimulated with TNFα and/or GM-CSF in vitro. Protein gels were compared using DeCyder 7.0 software. RESULTS: We identified 7 significantly regulated protein spots between peripheral neutrophils from COPD patients and age-matched healthy control subjects. Stimulation of peripheral neutrophils with TNFα, GM-CSF or TNFα + GM-CSF in vitro resulted in 13, 20 and 22 regulated protein spots, respectively. However, these cytokine-induced protein differences did not correspond with the protein differences found in neutrophils from COPD patients. CONCLUSION: These results show that neutrophils from COPD patients have a unique protein profile compared to neutrophils from healthy age-matched controls. Furthermore, the neutrophil profiles of COPD patients do not reflect putative dominant signals induced by TNFα, GM-CSF or their combination. Our results indicate that systemic neutrophil responses in COPD patients are caused by a unique but subtle interplay between multiple inflammatory signals.

Effects of glucocorticoids on the neutrophil count: a cohort study among hospitalized patients.

BACKGROUND: Systemic glucocorticoids are often used in clinical practice for a large variety of indications. Clinical observations have shown that patients using glucocorticoids often have higher neutrophil counts. Debate remains whether this observed neutrophilia is associated with glucocorticoid use or that other factors, like disease and severity of disease, should be considered. The objective of this study was to investigate the effect of systemic glucocorticoids on the absolute neutrophil count in hospitalized patients. METHODS: A cohort study was conducted using data from the Utrecht Patient Oriented Database which comprises clinical data of patients of the University Medical Center Utrecht. We identified all adult patients, hospitalized in 2005 with at least two blood samples for hematological testing during admission and compared in-hospital glucocorticoid use with non-use. RESULTS: A total of 809 glucocorticoid users and 2658 non-users were included in the study with comparable neutrophil counts at admission (8.2.10(9)/l for glucocorticoid users and 8.0.10(9)/l for non-users). Overall analysis showed a slight association between glucocorticoid use and an increase in neutrophil count (RR 1.3; 95% CI 1.1-1.5). However, within diagnostic subgroups there was no increase in neutrophil count in glucocorticoid users. Furthermore, among all no dose response relationship, no effect of time between the two samples, and no effect of anti-inflammatory/sodium retaining potency was found. CONCLUSION: Observed neutrophilia in users of systemic glucocorticoids is probably associated with underlying disease, rather than glucocorticoid use itself.

Testing bias in clinical databases: methodological considerations.

BACKGROUND: Laboratory testing in clinical practice is never a random process. In this study we evaluated testing bias for neutrophil counts in clinical practice by using results from requested and non-requested hematological blood tests. METHODS: This study was conducted using data from the Utrecht Patient Oriented Database. This clinical database is unique, as it contains physician requested data, but also data that are not requested by the physician, but measured as result of requesting other hematological parameters. We identified adult patients, hospitalized in 2005 with at least two blood tests during admission, where requests for general blood profiles and specifically for neutrophil counts were contrasted in scenario analyses. Possible effect modifiers were diagnosis and glucocorticoid use. RESULTS: A total of 567 patients with requested neutrophil counts and 1,439 patients with non-requested neutrophil counts were analyzed. The absolute neutrophil count at admission differed with a mean of 7.4 x 109/l for requested counts and 8.3 x 109/l for non-requested counts (p-value < 0.001). This difference could be explained for 83.2% by the occurrence of cardiovascular disease as underlying disease and for 4.5% by glucocorticoid use. CONCLUSION: Requests for neutrophil counts in clinical databases are associated with underlying disease and with cardiovascular disease in particular. The results from our study show the importance of evaluating testing bias in epidemiological studies obtaining data from clinical databases.

Medication changes prior to hospitalization for obstructive lung disease: a case-crossover study.

BACKGROUND: Hospitalizations have always been seen as a solid outcome parameter in pharmacoepidemiology. However, the period leading to hospitalization and prehospital management of the patient are equally important. OBJECTIVE: To evaluate medication changes in the period prior to hospitalization for obstructive lung disease and to quantify the association between medication use and the risk of hospitalization. METHODS: We conducted a case-crossover study using the PHARMO record linkage system, which contains drug dispensing data from community pharmacies and hospital admission data. Patients included in the study were adults hospitalized for obstructive lung disease between 2005 and 2007. The index date of the case period was the date of hospitalization, and control moments were set at 3, 6, 9, and 12 months before admission. For each patient, all prescriptions prior to the date of hospitalization were identified. Medication use was ascertained in a 90-day time window prior to each case or control moment. RESULTS: We identified 1481 patients who were hospitalized for obstructive lung disease. It appeared that respiratory medication use increased in the 90 days prior to hospitalization. Hospitalization was associated with the use of 3 or more respiratory drugs (OR 2.2; 95% CI 1.8 to 2.8), systemic glucocorticoids (OR 4.5; 95% CI 3.8 to 5.4), and antibiotics (OR 3.1; 95% CI 2.7 to 3.6). CONCLUSIONS: The use of systemic glucocorticoids, antibiotics, and other respiratory drugs increased prior to hospitalization for obstructive lung disease. These results could be indicative of the development and/or treatment of an exacerbation. There is a need for markers to detect exacerbations in an early phase in order to start treatment as early as possible and possibly prevent hospitalizations for obstructive lung disease.

Identification of exacerbations in obstructive lung disease through biomarkers.

Inflammation has been identified as an important factor for disease exacerbation in obstructive lung disease. In this study, we used neutrophil and eosinophil counts as biomarkers for exacerbation in obstructive lung disease. We conducted a case-control study within a cohort of patients frequenting an outpatient clinic of Respiratory Medicine using data from the Utrecht Patient Oriented Database (UPOD). Cases were patients with a hospital admission for obstructive lung disease in 2005. For each case, one control patient was sampled from the same study base. We identified 143 cases (118 patients with chronic obstructive pulmonary disease and 25 asthma patients) and 143 controls. Admission was associated with both neutrophilia (adjusted odds ratio (OR) 4.3; 95% confidence interval (CI) 2.2-8.5), and eosinophilia (adjusted OR 2.6; 95% CI 1.1-6.2). The association with eosinophilia was only seen in asthma patients. In conclusion, neutrophil and eosinophil counts seem to be useful biomarkers for identifying exacerbations in pharmacoepidemiological studies on obstructive lung disease.

Expression of activated Fc gamma RII discriminates between multiple granulocyte-priming phenotypes in peripheral blood of allergic asthmatic subjects.

BACKGROUND: Allergic asthma is associated with chronic airway and systemic immune responses. Systemic responses include priming of peripheral blood eosinophils, which is enhanced after allergen challenge. In a subpopulation of asthmatic subjects, neutrophils are associated with bronchial inflammation. OBJECTIVE: We sought to monitor systemic granulocyte priming in allergic asthmatic subjects as a consequence of chronic and acute inflammatory signals initiated by allergen challenge. METHODS: Blood was taken at baseline and 6 to 24 hours after allergen challenge in asthmatic subjects with and without late asthmatic responses. Systemic granulocyte priming was studied by using expression of cellular markers, such as alpha-chain of Mac-1 (alpha m)/CD11b, L-selectin/CD62L, and an activation epitope present on Fc gamma RII/CD32 recognized by monoclonal phage antibody A17. RESULTS: Eosinophils of asthmatic subjects have a primed phenotype identified by cell-surface markers. Neutrophils of these patients were subtly primed, which was only identified after activation with N-formyl-methionyl-leucyl-phenylalanine. After allergen challenge, an acute increase in eosinophil priming characterized by enhanced expression of activated Fc gamma RII was found in patients experiencing a late asthmatic response and not in patients with a single early asthmatic response. In contrast, expression of alpha m/CD11b and L-selectin on granulocytes was not different between control and asthmatic subjects and was not affected by allergen challenge. Interestingly, expression of both adhesion molecules was positively correlated, and alpha m expression on eosinophils and neutrophils correlated positively with bronchial hyperresponsiveness. CONCLUSION: Different phases, phenotypes, or both of allergic asthma are associated with distinct priming profiles of inflammatory cells in peripheral blood. CLINICAL IMPLICATIONS: Insight in differences of systemic innate responses will lead to better definition of asthma subtypes and to better designs of new therapeutic options.

Hematocytometry analysis as discriminative marker for asthma phenotypes.

BACKGROUND: There is an increasing demand for easy to measure biomarkers in clinical practice. We created the relational database Utrecht Patient Oriented Database (UPOD) to develop tools for identifying new biomarkers for disease. In this study, we used UPOD to identify better biomarkers for discriminating different asthma phenotypes. METHODS: We performed a prospective study at the University Medical Center (UMC) Utrecht using blood from patients with asthma and a healthy reference group. Since asthma is an inflammatory disease, absolute leukocyte counts and leukocyte differential parameters were analyzed using raw data files and a logistic regression model. RESULTS: We compared 17 difficult-to-treat asthma (DTA) cases, 13 non-difficult-to-treat asthma cases, and 19 healthy volunteers. Absolute leukocyte counts and differential parameters for leukocytes were able to discriminate asthma patients from healthy volunteers. However, among patients with asthma, difficult-to-treat cases could be more accurately defined with a neutrophil morphology change (OR 8.0; 95% CI 1.5-42.0), compared to the absolute neutrophil count (OR 4.0; 95% CI 0.8-21.0). CONCLUSIONS: In this asthma patient population, we were able to define asthma phenotypes more precisely using neutrophil morphology parameters, compared to absolute counts. Using UPOD with differential parameters, it is possible to conduct larger scale biomarker studies, combining clinical, laboratory medicine, and epidemiological techniques.