Pulmonary exacerbations (PEx) are clinically impactful events for individuals with CF. Unfortunately, many CF individuals with PEx fail to regain their baseline lung function despite treatment. The objective of this study was to use unbiased proteomic technology to identify novel blood protein biomarkers that change following intravenous (IV) antibiotic treatment and to explore if changes correlate with clinical response by the end of treatment. Blood samples from 25 PEx events derived from 22 unique CF adults were collected within 24 hours of hospital admission, day 5, day 10, and IV antibiotic completion. Three-hundred and forty-six blood proteins were evaluated with label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS) quantitative proteomics and immunoassays. Forty-seven plasma proteins changed significantly following 5 days of IV antibiotic treatment (q-value ≤ 0.10). Early change in IGF2R from hospital admission to day 5 correlated with overall change in symptom score (CFRSD-CRISS) by the end of treatment (r = −0.48, p-value = 0.04). Several plasma proteins identified and quantified by label-free LC-MS/MS changed early following treatment with IV antibiotics and many of these proteins are involved in complement activation and inflammatory/immune-related pathways. Early change in IGF2R correlated with symptom response following IV antibiotic treatment and requires further validation as a predictive biomarker of symptom response.

The factors that lead to poor pulmonary exacerbation (PEx) outcomes in individuals with cystic fibrosis (CF) are still being investigated; however, delayed diagnosis and treatment are likely contributory. Identifying individuals at imminent risk of PEx could enable closer monitoring and/or earlier initiation of therapies to improve outcomes. The goal of this study was to develop blood-based biomarkers that associate with imminent PEx risk in CF individuals. We examined the whole blood transcriptome and 55 inflammatory proteins from plasma and serum on 72 blood samples from 53 CF individuals. Biomarker candidate genes and proteins were selected from 14 CF individuals with paired stable and PEx visits (Cohort 1). The biomarker candidates were then estimated and tested to classify CF individuals who would experience a PEx within 4-months of a stable clinic visit or not (Cohort 2). A 16-gene panel and 9-protein panel were identified that could distinguish paired stable and PEx visits (AUC = 0.83 ± SE 0.28 and AUC = 0.92 ± SE 0.18, respectively). These two panels also demonstrated strong performance in classifying CF individuals who would experience a PEx within 4 months of a clinically stable visit or not (16-gene panel: AUC = 0.88; 9-protein panel: AUC = 0.83). In comparison, serum calprotectin and clinical variables (i.e. sex, ppFEV₁, and the number of IV antibiotics in the preceding year) had AUCs of 0.75 and 0.71, respectively. Blood-based mRNA and protein biomarkers demonstrated strong performance in classifying CF individuals at risk of imminent PEx. If the findings from this study can be validated, there is the potential to use blood biomarkers to enable more personalized disease activity monitoring in CF.

Exemplifying analysis of large-scale protein data from the 'Olink platform', primarily relative protein expression data that has been exported from 'Olink NPX Software', as well as QUANT data from 'Olink'. QUANT data is log-transformed. Materials focus on reading data, demonstrating data wrangling and quality control analysis, performing statistical analysis and generating figures to visualize the results of the statistical analysis. The goal of this package is to guide users extract biological insights from large-scale protein data run on the 'Olink platform'. More information on 'Olink' data can be found at .