39 results found
Hoda U, Pavlidis S, Bansal AT, et al., 2022, Clinical and transcriptomic features of persistent exacerbation-prone severe asthma in U-BIOPRED cohort, Clinical and Translational Medicine, Vol: 12, ISSN: 2001-1326
Background: Exacerbation-prone asthma is a feature of severe disease. Yet, the basis for its persistency remains unclear. Objectives: To determine the clinical and transcriptomic features of the frequent-exacerbator (FE) and of persistent FEs (PFE) in U-BIOPRED cohort. Methods: We compared features of FE (≥2 exacerbations in past year) to infrequent exacerbators (IE, <2 exacerbations) and of PFE with repeat ≥2 exacerbations during the following year to persistent IE (PIE). Transcriptomic data in blood, bronchial and nasal epithelial brushings, bronchial biopsies and sputum cells were analysed by gene set variation analysis for 103 gene signatures.Results: Of 317 patients, 62.4 % were FE of whom 63.6% were PFE, while 37.6% were IE of whom 61.3% were PIE. Using multivariate analysis, FE was associated with short-acting beta-agonist use, sinusitis and daily oral corticosteroid use, while PFE with eczema, short-acting beta-agonist use and asthma control index. CEA Cell Adhesion Molecule 5 (CEACAM5) was the only differentially-expressed transcript in bronchial biopsies between PE and IE. There were no differentially-expressed genes in the other 4 compartments. There were higher expression scores for Type 2 , T-helper type-17 and Type 1 pathway signatures together with those associated with viral infections in bronchial biopsies from FE compared to IE, while higher expression scores of Type 2, Type 1 and steroid insensitivity pathway signatures in bronchial biopsies of PFE compared to PIE.Conclusion: FE group and its PFE subgroup are associated with poor asthma control while expressing higher Type 1 and Type 2 activation pathways compared to IE and PIE, respectively.
Mikus MS, Kolmert J, Andersson L, et al., 2022, Plasma proteins elevated in severe asthma despite oral steroid use and unrelated to Type-2 inflammation, European Respiratory Journal, Vol: 59, Pages: 1-17, ISSN: 0903-1936
Rationale Asthma phenotyping requires novel biomarker discovery.Objectives To identify plasma biomarkers associated with asthma phenotypes by application of a new proteomic panel to samples from two well-characterised cohorts of severe (SA) and mild-to-moderate (MMA) asthmatics, COPD subjects and healthy controls (HCs).Methods An antibody-based array targeting 177 proteins predominantly involved in pathways relevant to inflammation, lipid metabolism, signal transduction and extracellular matrix was applied to plasma from 525 asthmatics and HCs in the U-BIOPRED cohort, and 142 subjects with asthma and COPD from the validation cohort BIOAIR. Effects of oral corticosteroids (OCS) were determined by a 2-week, placebo-controlled OCS trial in BIOAIR, and confirmed by relation to objective OCS measures in U-BIOPRED.Results In U-BIOPRED, 110 proteins were significantly different, mostly elevated, in SA compared to MMA and HCs. 10 proteins were elevated in SA versus MMA in both U-BIOPRED and BIOAIR (alpha-1-antichymotrypsin, apolipoprotein-E, complement component 9, complement factor I, macrophage inflammatory protein-3, interleukin-6, sphingomyelin phosphodiesterase 3, TNF receptor superfamily member 11a, transforming growth factor-β and glutathione S-transferase). OCS treatment decreased most proteins, yet differences between SA and MMA remained following correction for OCS use. Consensus clustering of U-BIOPRED protein data yielded six clusters associated with asthma control, quality of life, blood neutrophils, high-sensitivity C-reactive protein and body mass index, but not Type-2 inflammatory biomarkers. The mast cell specific enzyme carboxypeptidase A3 was one major contributor to cluster differentiation.Conclusions The plasma proteomic panel revealed previously unexplored yet potentially useful Type-2-independent biomarkers and validated several proteins with established involvement in the pathophysiology of SA.
Abdel-Aziz MI, Vijverberg SJH, Neerincx AH, et al., 2022, A multi-omics approach to delineate sputum microbiome-associated asthma inflammatory phenotypes, EUROPEAN RESPIRATORY JOURNAL, Vol: 59, ISSN: 0903-1936
- Author Web Link
- Citations: 2
Withnell E, Zhang X, Sun K, et al., 2021, XOmiVAE: an interpretable deep learning model for cancer classification using high-dimensional omics data, BRIEFINGS IN BIOINFORMATICS, Vol: 22, ISSN: 1467-5463
- Author Web Link
- Citations: 3
Nguyen T, Sun K, Wang S, et al., 2021, Privacy preservation in federated learning: An insightful survey from the GDPR perspective, COMPUTERS & SECURITY, Vol: 110, ISSN: 0167-4048
- Author Web Link
- Citations: 27
Alahmadi FH, Simpson AJ, Gomez C, et al., 2021, Medication adherence in patients with severe asthma prescribed oral corticosteroids in the U-BIOPRED cohort, Chest, Vol: 160, Pages: 53-64, ISSN: 0012-3692
BACKGROUND: Whilst estimates of sub-optimal adherence to oral corticosteroids in asthma range from 30 to 50%, no ideal method for measurement exists; the impact of poor adherence in severe asthma is likely to be particularly high. RESEARCH QUESTIONS: 1. What is the prevalence of suboptimal adherence detected using self-reporting and direct measures? 2. Is suboptimal adherence associated with disease activity? STUDY DESIGN AND METHODS: Data were included from individuals with severe asthma taking part in the U-BIOPRED study prescribed daily oral corticosteroids. Participants completed the MARS, a five-item questionnaire used to grade adherence on a scale from 1 to 5, and provided a urine sample for analysis of prednisolone and metabolites by liquid-chromatography mass spectrometry. RESULTS: Data from 166 participants were included in this study, mean (SD) age 54.2 (11.9) years, FEV1 65.1 (20.5) % predicted, 58% female. 37% completing the MARS reported sub-optimal adherence, and 43% with urinary corticosteroid data did not have detectable prednisolone or metabolites in their urine. Good adherence by both methods was detected in 35% participants who had both performed; adherence detection did not match between methods in 53%. Self-reported high-adherers had better asthma control and quality of life, whereas directly-measured high-adherers had lower blood eosinophils. INTERPRETATION: Low adherence is a common problem in severe asthma, whether measured directly or self-reported. We report poor agreement between the two methods suggesting some disassociation between self-assessment of medication adherence and regular oral corticosteroid use, which suggests that each approach may provide complementary information in clinical practice.
Zhang X, Xing Y, Sun K, et al., 2021, OmiEmbed: A Unified Multi-Task Deep Learning Framework for Multi-Omics Data, CANCERS, Vol: 13
- Author Web Link
- Citations: 15
Truong N, Lee GM, Sun K, et al., 2021, A blockchain-based trust system for decentralised applications: When trustless needs trust, FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, Vol: 124, Pages: 68-79, ISSN: 0167-739X
- Author Web Link
- Citations: 6
Kermani NZ, Song W-J, Badi Y, et al., 2021, Correction to: Sputum ACE2, TMPRSS2 and FURIN gene expression in severe neutrophilic asthma., Respiratory Research, Vol: 22, Pages: 1-3, ISSN: 1465-9921
Kermani N, Song W-J, Badi Y, et al., 2021, Sputum ACE2, TMPRSS2 and FURIN gene expression in severe neutrophilic asthma, Respiratory Research, Vol: 22, ISSN: 1465-9921
BackgroundPatients with severe asthma may have a greater risk of dying from COVID-19 disease. Angiotensin converting enzyme-2 (ACE2) and the enzyme proteases, transmembrane protease serine 2 (TMPRSS2) and FURIN, are needed for viral attachment and invasion into host cells.MethodsWe examined microarray mRNA expression of ACE2, TMPRSS2 and FURIN in sputum, bronchial brushing and bronchial biopsies of the European U-BIOPRED cohort. Clinical parameters and molecular phenotypes, including asthma severity, sputum inflammatory cells, lung functions, oral corticosteroid (OCS) use, and transcriptomic-associated clusters, were examined in relation to gene expression levels.ResultsACE2 levels were significantly increased in sputum of severe asthma compared to mild-moderate asthma. In multivariate analyses, sputum ACE2 levels were positively associated with OCS use and male gender. Sputum FURIN levels were significantly related to neutrophils (%) and the presence of severe asthma. In bronchial brushing samples, TMPRSS2 levels were positively associated with male gender and body mass index, whereas FURIN levels with male gender and blood neutrophils. In bronchial biopsies, TMPRSS2 levels were positively related to blood neutrophils. The neutrophilic molecular phenotype characterised by high inflammasome activation expressed significantly higher FURIN levels in sputum than the eosinophilic Type 2-high or the pauci-granulocytic oxidative phosphorylation phenotypes.ConclusionLevels of ACE2 and FURIN may differ by clinical or molecular phenotypes of asthma. Sputum FURIN expression levels were strongly associated with neutrophilic inflammation and with inflammasome activation. This might indicate the potential for a greater morbidity and mortality outcome from SARS-CoV-2 infection in neutrophilic severe asthma.
Kermani NZ, Saqi M, Agapow P, et al., 2021, Type 2-low asthma phenotypes by integration of sputum transcriptomics and serum proteomics., Allergy, Vol: 76, Pages: 380-383, ISSN: 0105-4538
Kermani NZ, Pavlidis S, Xie J, et al., 2020, Instability of sputum molecular phenotypes in U-BIOPRED severe asthma, European Respiratory Journal, Vol: 57, Pages: 1-5, ISSN: 0903-1936
Cruz AA, Riley JH, Barisal AT, et al., 2020, Asthma similarities across ProAR (Brazil) and U-BIOPRED (Europe) adult cohorts of contrasting locations, ethnicity and socioeconomic status, Respiratory Medicine, Vol: 161, Pages: 1-8, ISSN: 0954-6111
BackgroundAsthma prevalence is 339 million globally. ‘Severe asthma’ (SA) comprises subjects with uncontrolled asthma despite proper management.ObjectivesTo compare asthma from diverse ethnicities and environments.MethodsA cross-sectional analysis of two adult cohorts, a Brazilian (ProAR) and a European (U-BIOPRED). U-BIOPRED comprised of 311 non-smoking with Severe Asthma (SAn), 110 smokers or ex-smokers with SA (SAs) and 88 mild to moderate asthmatics (MMA) while ProAR included 544 SA and 452 MMA. Although these projects were independent, there were similarities in objectives and methodology, with ProAR adopting operating procedures of U-BIOPRED.ResultsAmong SA subjects, age, weight, proportion of former smokers and FEV1 pre-bronchodilator were similar. The proportion of SA with a positive skin prick tests (SPT) to aeroallergens, the scores of sino-nasal symptoms and quality of life were comparable. In addition, blood eosinophil counts (EOS) and the % of subjects with EOS > 300 cells/μl were not different. The Europeans with SA however, were more severe with a greater proportion of continuous oral corticosteroids (OCS), worse symptoms and more frequent exacerbations. FEV1/FVC pre- and post-bronchodilator were lower among the Europeans. The MMA cohorts were less comparable in control and treatment, but similar in the proportion of allergic rhinitis, gastroesophageal reflux disease and EOS >3%.ConclusionsProAR and U-BIOPRED cohorts, with varying severity, ethnicity and environment have similarities, which provide the basis for global external validation of asthma phenotypes. This should stimulate collaboration between asthma consortia with the aim of understanding SA, which will lead to better management.
Nguyen BT, Sun K, Lee GM, et al., 2020, GDPR-Compliant Personal Data Management: A Blockchain-Based Solution, IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, Vol: 15, Pages: 1746-1761, ISSN: 1556-6013
- Author Web Link
- Citations: 91
Truong N, Sun K, Guo Y, 2019, Blockchain-based personal data management: from fiction to solution, The 18th IEEE International Symposium on Network Computing and Applications (NCA 2019), Publisher: IEEE, Pages: 1-8
The emerging blockchain technology has enabledvarious decentralised applications in a trustless environmentwithout relying on a trusted intermediary. It is expected as apromising solution to tackle sophisticated challenges on personaldata management, thanks to its advanced features such as im-mutability, decentralisation and transparency. Although certainapproaches have been proposed to address technical difficultiesin personal data management; most of them only provided pre-liminary methodological exploration. Alarmingly, when utilisingBlockchain for developing a personal data management system,fictions have occurred in existing approaches and been promul-gated in the literature. Such fictions are theoretically doable;however, by thoroughly breaking down consensus protocols andtransaction validation processes, we clarify that such existingapproaches are either impractical or highly inefficient due tothe natural limitations of the blockchain and Smart Contractstechnologies. This encourages us to propose a feasible solution inwhich such fictions are reduced by designing a novel systemarchitecture with a blockchain-based “proof of permission”protocol. We demonstrate the feasibility and efficiency of theproposed models by implementing a clinical data sharing servicebuilt on top of a public blockchain platform. We believe thatour research resolves existing ambiguity and take a step furtheron providing a practically feasible solution for decentralisedpersonal data management.
Östling J, van Geest M, Schofield JPR, et al., 2019, IL-17-high asthma with features of a psoriasis immunophenotype, Journal of Allergy and Clinical Immunology, Vol: 144, Pages: 1198-1213, ISSN: 0091-6749
BACKGROUND: The role of interleukin-17 immunity is well established in inflammatory diseases like psoriasis and inflammatory bowel disease but not in asthma where further study is required. OBJECTIVE: To undertake a deep-phenotyping study of asthmatics with up-regulated interleukin-17 immunity. METHODS: Whole genome transcriptomic analysis was performed using epithelial brushings, bronchial biopsies (91 asthmatics patients and 46 healthy controls) and whole blood samples (n=498) from the U-BIOPRED cohort. Gene signatures induced in vitro by interleukin-17 and interleukin-13 in bronchial epithelial cells were used to identify patients with interleukin-17-high and interleukin-13-high phenotypes of asthma. RESULTS: 22 out of 91 patients were identified with interleukin-17 and 9 patients with interleukin-13 gene signatures. The interleukin-17-high asthmatics were characterised by risk of frequent exacerbations, airway (sputum and mucosal) neutrophilia, decreased lung microbiota diversity and urinary biomarker evidence of activation of the thromboxane B2 pathway. In pathway analysis, the differentially expressed genes in interleukin-17-high patients were shared with those reported as altered in psoriasis lesions, and included genes regulating epithelial barrier function and defence mechanisms, such as interleukin-1β, interleukin-6, interleukin-8, and beta-defensin. CONCLUSION: The interleukin-17-high asthma phenotype, characterized by bronchial epithelial dysfunction, upregulated anti-microbial and inflammatory response, resembles the immunophenotype of psoriasis, including activation of the thromboxane B2 pathway which should be considered as a biomarker for this phenotype in further studies, including clinical trials targeting interleukin-17.
Zhang J, Zhang X, Sun K, et al., 2019, Unsupervised Annotation of Phenotypic Abnormalities via Semantic Latent Representations on Electronic Health Records, 2019 IEEE International Conference on Bioinformatics and Biomedicine
Zhang X, Zhang J, Sun K, et al., 2019, Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification, 2019 IEEE International Conference on Bioinformatics and Biomedicine
Schofield JPR, Burg D, Nicholas B, et al., 2019, Stratification of asthma phenotypes by airway proteomic signatures, Journal of Allergy and Clinical Immunology, Vol: 144, Pages: 70-82, ISSN: 0091-6749
BACKGROUND: Stratification by eosinophil and neutrophil counts increases our understanding of asthma and helps target therapy, but there is room for improvement in our accuracy to predict treatment responses and a need for better understanding of the underlying mechanisms. OBJECTIVE: Identify molecular sub-phenotypes of asthma defined by proteomic signatures for improved stratification. METHODS: Unbiased label-free quantitative mass spectrometry and topological data analysis were used to analyse the proteomes of sputum supernatants from 246 participants (206 asthmatics) as a novel means of asthma stratification. Microarray analysis of sputum cells provided transcriptomics data additionally to inform on underlying mechanisms. RESULTS: Analysis of the sputum proteome resulted in 10 clusters, proteotypes, based on similarity in proteomics features, representing discrete molecular sub-phenotypes of asthma. Overlaying granulocyte counts onto the 10 clusters as metadata further defined three of these as highly eosinophilic, three as highly neutrophilic, and two as highly atopic with relatively low granulocytic inflammation. For each of these three phenotypes, logistic regression analysis identified candidate protein biomarkers, and matched transcriptomic data pointed to differentially activated underlying mechanisms. CONCLUSION: This study provides further stratification of asthma currently classified by quantifying granulocytic inflammation and gives additional insight into their underlying mechanisms which could become targets for novel therapies.
Perotin J-M, Schofield JPR, Wilson SJ, et al., 2019, Epithelial dysregulation in obese severe asthmatics with gastro-oesophageal reflux, European Respiratory Journal, Vol: 53, ISSN: 0903-1936
Brinkman P, Wagener AH, Hekking P-P, et al., 2019, Identification and prospective stability of electronic nose (eNose)-derived inflammatory phenotypes in patients with severe asthma, JOURNAL OF ALLERGY AND CLINICAL IMMUNOLOGY, Vol: 143, Pages: 1811-+, ISSN: 0091-6749
- Author Web Link
- Citations: 49
Jevnikar Z, Östling J, Ax E, et al., 2019, Epithelial IL-6 trans-signaling defines a new asthma phenotype with increased airway inflammation, Journal of Allergy and Clinical Immunology, Vol: 143, Pages: 577-590, ISSN: 0091-6749
BACKGROUND: Although several studies link high levels of IL-6 and soluble IL-6 receptor (sIL-6R) with asthma severity and decreased lung function, the role of IL-6 trans-signaling (IL-6TS) in asthma is unclear. OBJECTIVE: To explore the association between epithelial IL-6TS pathway activation and molecular and clinical phenotypes in asthma. METHODS: An IL-6TS gene signature, obtained from air-liquid interface (ALI) cultures of human bronchial epithelial cells stimulated with IL-6 and sIL-6R, was used to stratify lung epithelium transcriptomic data (U-BIOPRED cohorts) by hierarchical clustering. IL-6TS-specific protein markers were used to stratify sputum biomarker data (Wessex cohort). Molecular phenotyping was based on transcriptional profiling of epithelial brushings, pathway analysis and immunohistochemical analysis of bronchial biopsies. RESULTS: Activation of IL-6TS in ALI cultures reduced epithelial integrity and induced a specific gene signature enriched in genes associated with airway remodeling. The IL-6TS signature identified a subset of IL-6TS High asthma patients with increased epithelial expression of IL-6TS inducible genes in absence of systemic inflammation. The IL-6TS High subset had an overrepresentation of frequent exacerbators, blood eosinophilia, and submucosal infiltration of T cells and macrophages. In bronchial brushings, TLR pathway genes were up-regulated while the expression of tight junction genes was reduced. Sputum sIL-6R and IL-6 levels correlated with sputum markers of remodeling and innate immune activation, in particular YKL-40, MMP3, MIP-1β, IL-8 and IL-1β. CONCLUSIONS: Local lung epithelial IL-6TS activation in absence of type 2 airway inflammation defines a novel subset of asthmatics and may drive airway inflammation and epithelial dysfunction in these patients.
Simpson AJ, Hekking P-P, Shaw DE, et al., 2019, Treatable traits in the European U-BIOPRED adult asthma cohorts, Allergy, Vol: 74, Pages: 406-411, ISSN: 0105-4538
Zhang X, Zhang J, Sun K, et al., 2019, Integrated Multi-omics Analysis Using Variational Autoencoders: Application to Pan-cancer Classification, Publisher: IEEE
- Author Web Link
- Citations: 16
Pavlidis S, Takahashi K, Kwong FNK, et al., 2019, "T2-high" in severe asthma related to blood eosinophil, exhaled nitric oxide and serum periostin, European Respiratory Journal, Vol: 53, ISSN: 0903-1936
BACKGROUND: Type-2 (T2) immune responses in airway epithelial cells (AECs) classifies mild-moderate asthma into a T2-high phenotype. We examined whether currently-available clinical biomarkers can predict AEC-defined T2-high phenotype within U-BIOPRED cohort. METHODS: The transcriptomic profile of AECs obtained from brushings of 103 patients with asthma and 44 healthy controls was obtained and gene set variation analysis used to determine the relative expression score of T2 asthma using a signature from IL-13-exposed AECs. RESULTS: 37% of asthmatics (45% non-smoking severe asthma, n=49, 33% of smoking or ex-smoking severe asthma, n=18 and 28% mild-moderate asthma, n=36) were T2-high using AEC gene expression. They were more symptomatic with higher levels of nitric oxide in exhaled breath (FeNO) and of blood and sputum eosinophils but not of serum IgE or periostin. Sputum eosinophilia correlated best with the T2-high signature. FeNO (≥30 ppb) and blood eosinophils (≥300/µL) gave a moderate prediction of T2-high asthma. Sputum IL-4, IL-5 and IL-13 protein levels did not correlate with gene expression. CONCLUSION: T2-high severe asthma can be predicted to some extent from raised levels of FeNO, blood and sputum eosinophil counts, but serum IgE or serum periostin were poor predictors. Better bedside biomarkers are needed to detect T2-high.
Brandsma J, Goss VM, Yang X, et al., 2018, Lipid phenotyping of lung epithelial lining fluid in healthy human volunteers, Metabolomics, Vol: 14, ISSN: 1573-3882
BackgroundLung 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.ObjectivesTo 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.MethodsInduced 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.ResultsThe 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.ConclusionsWe 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.
Burg D, Schofield JPR, Brandsma J, et al., 2018, Large-scale label-free quantitative mapping of the sputum proteome, Journal of Proteome Research, Vol: 17, Pages: 2072-2091, ISSN: 1535-3893
Analysis of induced sputum supernatant 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.
De Meulder B, Lefaudeux D, Bansal AT, et al., 2018, A computational framework for complex disease stratification from multiple large-scale datasets, BMC Systems Biology, Vol: 12, ISSN: 1752-0509
BACKGROUND: Multilevel data integration is becoming a major area of research in systems biology. Within this area, multi-'omics datasets on complex diseases are becoming more readily available and there is a need to set standards and good practices for integrated analysis of biological, clinical and environmental data. We present a framework to plan and generate single and multi-'omics signatures of disease states. METHODS: The framework is divided into four major steps: dataset subsetting, feature filtering, 'omics-based clustering and biomarker identification. RESULTS: We illustrate the usefulness of this framework by identifying potential patient clusters based on integrated multi-'omics signatures in a publicly available ovarian cystadenocarcinoma dataset. The analysis generated a higher number of stable and clinically relevant clusters than previously reported, and enabled the generation of predictive models of patient outcomes. CONCLUSIONS: This framework will help health researchers plan and perform multi-'omics big data analyses to generate hypotheses and make sense of their rich, diverse and ever growing datasets, to enable implementation of translational P4 medicine.
Takahashi K, Pavlidis S, Ng Kee Kwong F, et al., 2018, Sputum proteomics and airway cell transcripts of current and ex-smokers with severe asthma in U-BIOPRED: an exploratory analysis, European Respiratory Journal, Vol: 51, ISSN: 0903-1936
Background: Severe asthma patients with a significant smoking history have airflow obstruction with reported neutrophilia. We hypothesise that multi1omic analysis will enable the definition of smoking and ex1smoking severe asthma molecular phenotypes.Methods The U1BIOPRED severe asthma patients containing current1smokers (CSA), ex1smokers (ESA), non1smokers (NSA) and healthy non1smokers (NH) was examined. Blood and sputum cell counts, fractional exhaled nitric oxide and spirometry were obtained. Exploratory proteomic analysis of sputum supernatants and transcriptomic analysis of bronchial brushings, biopsies and sputum cells was performed. Results Colony stimulating factor (CSF)2 protein levels were increased in CSA sputum supernatants with azurocidin 1, neutrophil elastase and CXCL8 upregulated in ESA. Phagocytosis and innate immune pathways were associated with neutrophilic inflammation in ESA. Gene Set Variation Analysis of bronchial epithelial cell transcriptome from CSA showed enrichment of xenobiotic metabolism, oxidative stress and endoplasmic reticulum stress compared to other groups. CXCL5 and matrix metallopeptidase 12 genes were upregulated in ESA and the epithelial protective genes, mucin 2 and cystatin SN, were downregulated. Conclusion Despite little difference in clinical characteristics, CSA were distinguishable from ESA subjects at the sputum proteomic level with CSA having increased CSF2 expression and ESA patients showed sustained loss of epithelial barrier processes.
Oehmichen A, Guitton F, Sun K, et al., 2017, eTRIKS analytical environment: A modular high performance framework for medical data analysis, 2017 IEEE International Conference on Big Data (BIGDATA), Pages: 353-360
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