Lung Proteomics in Intensive Care

Kipnis, Éric; Hansen, Kirk C.

doi:10.1007/978-3-540-92276-6_3

Cited by 1 publication

(6 citation statements)

References 49 publications

(48 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Exclusive peptide biomarkers have not been identified in the BALF of patients with ARDS in contrast to healthy individuals [19]. Instead transient concentration changes of BALF proteins were described at the onset of ARDS.…”

Section: Discussionmentioning

confidence: 97%

“…BALF is also a well studied method and is used in the clinical setting of ALI/ARDS for diagnostic purposes in a number of patients. The application of proteomics techniques to BALF has been shown to yield proteins associated with ALI/ARDS [18], [19], [26]–[28]. However, BAL is not without risk.…”

Section: Discussionmentioning

confidence: 99%

“…However, BAL is not without risk. In our study bronchoalveolar lavage was necessary for the diagnosis of bacterial, fungal or viral disease and remaining aliquots were taken for MALDI-ToF MS. Exhaled breath condensate, a possible alternative was also investigated by MALDI-ToF MS [13], [19], [40]. However, the peptide patterns of breath condensate with a limited number of peaks allowed no satisfying outcome prediction.…”

Section: Discussionmentioning

confidence: 99%

“…Recently, flow cytometry, gene expression arrays, and proteomics were all applied to BALF, pulmonary edema fluid and serum in order to identify peptides or proteins which are up- or downregulated significantly in various pulmonary diseases [17], [18]. Proteomic approaches to lung diseases typically have applied two-dimensional electrophoresis for protein separation followed by identification of differentially expressed proteins by mass spectrometry (MS) [19]. Healthy individuals [15], [18]–[21] and patients with asthma [22], chronic obstructive pulmonary disease (COPD) [23], [24], cystic fibrosis, sarcoidosis [25] and sepsis/ARDS [18], [19], [26]–[28] were investigated.…”

Section: Introductionmentioning

confidence: 99%

“…Proteomic approaches to lung diseases typically have applied two-dimensional electrophoresis for protein separation followed by identification of differentially expressed proteins by mass spectrometry (MS) [19]. Healthy individuals [15], [18]–[21] and patients with asthma [22], chronic obstructive pulmonary disease (COPD) [23], [24], cystic fibrosis, sarcoidosis [25] and sepsis/ARDS [18], [19], [26]–[28] were investigated. In some studies MS spectra of complex samples from lung patients were recorded and the peptide/protein patterns were analyzed by means of mathematical algorithms without peak identification.…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Outcome Prediction in Pneumonia Induced ALI/ARDS by Clinical Features and Peptide Patterns of BALF Determined by Mass Spectrometry

Frenzel

Geßner²,

Sandvoß³

et al. 2011

PLoS ONE

View full text Add to dashboard Cite

BackgroundPeptide patterns of bronchoalveolar lavage fluid (BALF) were assumed to reflect the complex pathology of acute lung injury (ALI)/acute respiratory distress syndrome (ARDS) better than clinical and inflammatory parameters and may be superior for outcome prediction.Methodology/Principal FindingsA training group of patients suffering from ALI/ARDS was compiled from equal numbers of survivors and nonsurvivors. Clinical history, ventilation parameters, Murray's lung injury severity score (Murray's LISS) and interleukins in BALF were gathered. In addition, samples of bronchoalveolar lavage fluid were analyzed by means of hydrophobic chromatography and MALDI-ToF mass spectrometry (MALDI-ToF MS).Receiver operating characteristic (ROC) analysis for each clinical and cytokine parameter revealed interleukin-6>interleukin-8>diabetes mellitus>Murray's LISS as the best outcome predictors. Outcome predicted on the basis of BALF levels of interleukin-6 resulted in 79.4% accuracy, 82.7% sensitivity and 76.1% specificity (area under the ROC curve, AUC, 0.853). Both clinical parameters and cytokines as well as peptide patterns determined by MALDI-ToF MS were analyzed by classification and regression tree (CART) analysis and support vector machine (SVM) algorithms. CART analysis including Murray's LISS, interleukin-6 and interleukin-8 in combination was correct in 78.0%. MALDI-ToF MS of BALF peptides did not reveal a single identifiable biomarker for ARDS. However, classification of patients was successfully achieved based on the entire peptide pattern analyzed using SVM. This method resulted in 90% accuracy, 93.3% sensitivity and 86.7% specificity following a 10-fold cross validation (AUC = 0.953). Subsequent validation of the optimized SVM algorithm with a test group of patients with unknown prognosis yielded 87.5% accuracy, 83.3% sensitivity and 90.0% specificity.Conclusions/SignificanceMALDI-ToF MS peptide patterns of BALF, evaluated by appropriate mathematical methods can be of value in predicting outcome in pneumonia induced ALI/ARDS.

show abstract

Section: Discussionmentioning

confidence: 97%