Study population

The TGF-β1 genotypes for all three SNPs were determined in 56 CF-patients and 62 healthy controls. All CF patients had a confirmed diagnosis of CF according to the consensus guidelines of the Cystic Fibrosis Foundation [19]. Inclusion criteria were a signed informed consent and the ability of patients to expectorate sputum. Exocrine pancreatic insufficiency was diagnosed by repeated pancreas elastase testing of patients´ stools and confirmed by repeated levels < 200ug/g. The genomic DNA of CF patients was isolated from a whole blood sample obtained during the routine yearly blood sample collection. The DNA samples of 62 randomly chosen, healthy controls were obtained from paternity test samples at the Institute of Legal Medicine, to which the individuals had given their consent when these samples were obtained [20]. Patients with an acute pulmonary exacerbation at the study visit were excluded. All pulmonary function tests performed during the 5-year interval between 2010 and 2014 were reviewed. The best FEV1 value for every year was obtained for FEV1 slope calculation. 15 patients underwent changes in CF therapy (e.g. start of CFTR-modulatory therapy) or lung transplantation within this period of time. For these, a different five-year time span, prior to their new therapy, was chosen for calculation of the individual FEV1 slope.



polymorphism genotyping

DNA was extracted from whole blood and diluted to a standard concentration of 1 ng/(mu) l. The DNA was then amplified using Polymerase Chain Reaction (PCR) with specific primers designed to amplify two separate targets of the genome, containing the relevant SNPs, using Primer3Plus, BLAST and NCBI Electronic PCR-Software [21, 22]. Primers were produced and shipped by [23]. PCR primer sequences used are available on request. Agarose gel electrophoresis tests of the amplicons were performed to monitor the correct amplification of the two targets. Enzymatic purification of samples followed using Exonuclease and Shrimp Alkaline Phosphate (SAP). According to instructions of the SNaPshot™ Multiplex Kit (Applied Biosystems), a Single Base Extension (SBE) with didesoxyribonucleosid-triphosphates (ddNTPs), marked with four different fluorescent signals, QIAGEN Mastermix (containing DNA Polymerase AmpliTaq©, reaction puffer) was performed in a thermocycler (Gene AMP PCR System 2720 thermocycler, Applied Biosystems) [24,25,26]. SNP typing primer sequences were GGCAACAGGACACCTGA(A/G) for SNP rs1800469, CAGCGGTAGCAGGAGC(G/A) for Codon 10 SNP rs1800470 and GTGCTGACGCCTGGCC(G/C) for Codon 25 rs1800471.

Lastly, after enzymatic purification of the Single Base Extension reaction (SBE) reaction products, capillary electrophoresis (using ABI Prism 3130 Genetic Analyzers) was performed to determine the genotype of each SNP for all patients and controls using the software Genemapper 4.0 (Applied Biosystems). An exemplary capillary electrophoresis result of one patient’s genotype for all three polymorphisms is shown in Additional file 1: Figure A. Materials, concentrations, PCR primers sequences and exact reaction conditions for PCR and Single Base Extension (SBE) are available on request.


Spirometric measurements were performed according to the ATS guidelines using GLI references and assessed before any other study assessment with Master Screen Body (Jaeger, Heidelberg, Germany) and SentrySuite™ version 2.19 software (Carefusion, Becton Dickinson, Franklin Lakes, New Jersey, USA) [27]. For each measurement, the best FEV1 value was used for analysis. The best yearly FEV1 value was used in a linear regression model to calculate individual FEV1 slope values for every patient. Patient results were also analyzed within different FEV1 subgroups and FEV1 slope subgroups, according to FEV1 progression over time.

Pseudomonas aeruginosa (Pa) infection

The status of Pa infection, defined by clinically established Leeds criteria, was obtained from the patients’ files and is described according to the following three groups: Pa positive (= chronic infection), Pa naïve (= never infected) or Pa negative (infected in the past, currently not infected after eradication therapy) [28].

Sputum analysis of TGF-β


and other cytokines

As part of the regular outpatient visits, patients induced their sputum by inhalation of hypertonic saline during a routine physiotherapist session. This sputum was processed according to the standard operating procedure (SOP) of the TDN (Therapeutic Drug Development Network, USA). Concentrations of elastase and elafin in sputum were determined by specific ELISA assays (EnzChek® Elastase Assay Kit,—Molecular Probes Europe, Leiden, Netherlands; Elafin/Skalp Human ELISA Kit—abcam, Cambridge, UK). Pro-inflammatory cytokine concentrations in sputum were assessed using a human inflammatory cytokine ELISA-kit (BD Cytometric Bead Array Humane Inflammatory Cytokine Kit, San Jose, CA, USA). TGF-β1 levels in sputum and plasma were determined by a TGF- β1 specific ELISA-kit (Quantikine®ELISA Human TGF-β1, R&D systems, Minneapolis, MN, USA).

Statistical analysis

IBM SPSS Statistics 24 was used for statistical analysis. To compare two metric variables, we correlated using Pearson’s test. For correlation between one metric and one discontinuous variable, we used the Kruskal–Wallis test. For tests correlating two discontinuous variables we used cross-classified tables with exact Fisher’s test. For all tests, a p-value < 0,05 was considered statistically significant.

For a detailed analysis of FEV1 slopes, different patient subgroups were formed as summarized in Additional file 1: Figure B. One categorization involved a comparison between patients with positive FEV1 slope and those with negative slopes (Categorization 1). Two further categorizations were used to compare patients with steepest decline in FEV1 to patients with a relatively steady FEV1 (with only little decline or even small improvements) and patients with clear improvements in FEV1 over the period of investigation (Categorization 2 & 3). These categories were formed to investigate inflammatory status in different stages of CF lung disease and to determine the role of TGF-β1 in this process.

Additionally, for statistical analysis, patient subgroups were also formed according to patients’ absolute, best FEV1 at the end of the observed 5 year-period. Here patients were analyzed in different FEV1 subgroups in order to investigate patients who finished their 5-year FEV1 slope in a “normal” FEV1 group (> 80% predicted), an “intermediate” FEV1 group (40–80% predicted) or a “low” FEV1 group (< 40% predicted). A summary of these subgroups can be found in Additional file 1: Figure C.

For more detailed analysis of TGF-β1 genotypes, for some statistical investigations we used subgroups of combined genotypes to explore the impact of a heterozygous genotype when compared to homozygous genotypes (e.g. CT vs TT/CC).

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