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- Brandsma, Joost, et al.
(author)
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Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers
- 2018
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In: Metabolomics. - : Springer-Verlag New York. - 1573-3882 .- 1573-3890. ; 14:10
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Journal article (peer-reviewed)abstract
- Background: Lung epithelial lining fluid (ELF)-sampled through sputum induction-is a medium rich in cells, proteins and lipids. However, despite its key role in maintaining lung function, homeostasis and defences, the composition and biology of ELF, especially in respect of lipids, remain incompletely understood. Objectives: To characterise the induced sputum lipidome of healthy adult individuals, and to examine associations between different ELF lipid phenotypes and the demographic characteristics within the study cohort.Methods: Induced sputum samples were obtained from 41 healthy non-smoking adults, and their lipid compositions analysed using a combination of untargeted shotgun and liquid chromatography mass spectrometry methods. Topological data analysis (TDA) was used to group subjects with comparable sputum lipidomes in order to identify distinct ELF phenotypes.Results: The induced sputum lipidome was diverse, comprising a range of different molecular classes, including at least 75 glycerophospholipids, 13 sphingolipids, 5 sterol lipids and 12 neutral glycerolipids. TDA identified two distinct phenotypes differentiated by a higher total lipid content and specific enrichments of diacyl-glycerophosphocholines, -inositols and -glycerols in one group, with enrichments of sterols, glycolipids and sphingolipids in the other. Subjects presenting the lipid-rich ELF phenotype also had significantly higher BMI, but did not differ in respect of other demographic characteristics such as age or gender.Conclusions: We provide the first evidence that the ELF lipidome varies significantly between healthy individuals and propose that such differences are related to weight status, highlighting the potential impact of (over)nutrition on lung lipid metabolism.
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| 2. |
- Burg, Dominic, et al.
(author)
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Large-Scale Label-Free Quantitative Mapping of the Sputum Proteome
- 2018
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In: Journal of Proteome Research. - : American Chemical Society (ACS). - 1535-3893 .- 1535-3907. ; 17:6, s. 2072-2091
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Journal article (peer-reviewed)abstract
- Analysis of induced sputum supematant is a minimally invasive approach to study the epithelial lining fluid and, thereby, provide insight into normal lung biology and the pathobiology of lung diseases. We present here a novel proteomics approach to sputum analysis developed within the U-BIOPRED (unbiased biomarkers predictive of respiratory disease outcomes) international project. We present practical and analytical techniques to optimize the detection of robust biomarkers in proteomic studies. The normal sputum proteome was derived using data-independent HDMSE applied to 40 healthy nonsmoking participants, which provides an essential baseline from which to compare modulation of protein expression in respiratory diseases. The "core" sputum proteome (proteins detected in >= 40% of participants) was composed of 284 proteins, and the extended proteome (proteins detected in >= 3 participants) contained 1666 proteins. Quality control procedures were developed to optimize the accuracy and consistency of measurement of sputum proteins and analyze the distribution of sputum proteins in the healthy population. The analysis showed that quantitation of proteins by HDMSE is influenced by several factors, with some proteins being measured in all participants' samples and with low measurement variance between samples from the same patient. The measurement of some proteins is highly variable between repeat analyses, susceptible to sample processing effects, or difficult to accurately quantify by mass spectrometry. Other proteins show high interindividual variance. We also highlight that the sputum proteome of healthy individuals is related to sputum neutrophil levels, but not gender or allergic sensitization. We illustrate the importance of design and interpretation of disease biomarker studies considering such protein population and technical measurement variance.
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| 3. |
- Schofield, James P. R., et al.
(author)
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Topological data analysis (TDA) of U-BIOPRED paediatric peripheral blood gene expression identified asthma phenotypes characterised by alternative splicing of glucocorticoid receptor (GR) mRNA
- 2018
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In: European Respiratory Journal. - : European Respiratory Society. - 0903-1936 .- 1399-3003. ; 52
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Journal article (other academic/artistic)abstract
- Background: Molecular stratification of childhood asthma could enable targeted therapy.Aims: Unbiased analysis of gene expression in paediatric severe (SA) and moderate/mild asthma (MA) blood samples to identify sub-phenotypes.Methods: Transcriptomic profiling by microarray analysis of blood from the U-BIOPRED paediatric cohort (Fleming ERJ 2015), pre- and school-age children, (SApre, n=62; MApre, n=42; SAsc, n=75 and MAsc, n=37). Topological data analysis (TDA) was used for unbiased clustering.Results: Sub-phenotypes, P1, P2, P3 and P4 were identified and are highlighted in the TDA network in the figure and a heatmap of selected variables. P1 (38% of the cohort, median 11 yrs) was characterised by low expression of glucocorticoid receptor (GR) mRNA splice variant with a long 3’ UTR (q = 2.43E-17), but no significant difference in the expression of glucocorticoid receptor (GR) mRNA splice variant with a short 3’ UTR. In P1, COX2 expression was up (q = 1.89E-06) and IFN-γ was down (q = 5.61E-06), characteristics of a decreased steroid response.Conclusion: Unbiased analysis of U-BIOPRED paediatric peripheral blood gene expression identified a sub-phenotype, P1, with an inhibited steroid response. P1 is associated with low expression of a splice variant of GR with a long 3’ UTR.
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