MICA: STELAR (Study Team for Early Life Asthma Research) consortium - Asthma e-lab and identification of novel endotypes of childhood asthma

Lead Research Organisation: Imperial College London
Department Name: Dept of Medicine

Abstract

Asthma is the most common chronic disease of childhood and causes many hospital admissions. The number of children suffering from asthma has increased dramatically over the past 30 years. It is unclear why some people get asthma and others do not. Asthma is largely heritable, but despite lots of effort we have had limited success identifying which genes are important, and genetic studies of asthma have not yet had a positive impact on patient care. Many factors in the environment may contribute to the development of asthma (for example diet, immunizations, antibiotics, pets and tobacco smoke) but we don't know how to modify the environment to reduce the risks. One reason for the difficulty in understanding causes of asthma is that asthma may be a collection of different diseases which cause similar symptoms. As asthma generally starts early in life, the best way to study it is to recruit new born babies and follow them as they grow (so-called birth cohort). During early life it is possible to measure many things, such as exposure to allergens, (generally cats, dogs and dust mite) constituents of the diet and antibiotic usage. Questionnaires are used to collect information from parents about symptoms, and as the children get older they can take part in measurements of lung function and allergy testing. Most are willing to give sample for genetic testing. In the UK there are 5 such birth cohorts that have been designed to facilitate the study of risk factors for asthma and allergies. The Manchester Study has more than 1,000 children under active follow up; clinical follow up is complete for age 1, 3, 5, 8 and 11 years. The study from Aberdeen included 1,924 children who were followed up 6 months, 1, 2, 5 and 10 years. The Ashford birth cohort followed 642 children until age 12 years. The Isle of Wight study recruited 1,456 children, completing follow up at ages 1, 2, 4, 10 and 18 years. ALSPAC recruited through antenatal clinics in the former County of Avon, and enrolled 14,062 infants. Follow up is complete to age 16 years. All have collected data using questionnaire and performed measures of lung function and skin tests at intervals throughout early life. The researchers who lead these studies have worked together as a network over the last 7 years - the Study Team for Early Life Asthma Research (STELAR consortium). Over recent years we have adopted identical research methodologies, recognising that although each cohort is unique, there are many aspects in which we can work together, to increase our chances of detecting the main causes of asthma. We now propose to create a major new alliance which will combine our world-leading expertise in birth cohorts (STELAR consortium) with expertise in health informatics research (NW Institute for Bio-Health Informatics) and cutting-edge computational statistical methods (so-called statistical machine learning, with experts at our Industrial partner at Microsoft Research Cambridge). Our alliance includes clinicians, public health and epidemiology researchers, statisticians, informaticians and software engineers. We will construct a web based resource (Asthma e-Lab) in which to securely store all the data collected on the cohorts and recipes for analysing the data so that a larger group of scientists can repeat the work. This will enable consistent recording, description and sharing of data and emerging findings across all partners. We will also complete clinical follow-up of cohort participants where necessary. We will work together to apply newly developed state-of-the-art data analysis techniques to build complex models to describe different types of 'asthma' and investigate risk factors for each asthma subtype. In doing so we hope to understand the basic biological mechanisms that underlie the different forms of asthma, Our findings may underpin new trials of asthma prevention and may help identify targets for the discovery of novel therapies which are matched to specific patients.

Technical Summary

Asthma epidemiology is reaching the limit of what can be achieved through conventional hypothesis-driven research. We hypothesise that asthma is not a single disease, but a condition comprising multiple distinct disease entities (asthma endotypes), each with characteristic pathophysiology and risk factors, and that unbiased novel endotypes of asthma can be identified using complex, rich and expanding datasets from existing UK birth cohort studies by applying a combination of biostatistical and machine learning methods. We propose to form a major Alliance between MRC-funded network of all UK-based birth cohorts designed to study asthma (STELAR consortium), expertise in epidemiologically oriented health informatics research (NW Institute for Bio-Health Informatics) and experts in statistical machine learning (Microsoft Research Cambridge). We will capitalise on the unique collection of well characterised birth cohorts with harmonised clinical outcomes (ALSPAC, SEATON, MAAS, Ashford, Isle of Wight). We will create a secure web-based research environment (Asthma e-Lab) to support consistent recording, description and sharing of data and emerging findings across all partners, thus enabling collaborative epidemiology in near-real-time. The activities of data managers and researchers from the 5 STELAR sites will be made visible to one another, supporting team coordination and peer support and creating a scientific social network to enrich the ongoing modelling and interpretation. We will create and maintain across the consortium annotated dependency graphs of the problem space around the organising principles underlying asthma, and use a machine learning approach interactively over the combined datasets via Asthma e-Lab to discover the unbiased endotypes of asthma. Our findings may underpin new trials of asthma prevention and treatment, personalised for specific endotypes and may help identify novel targets for the discovery of endotypes-specific stratified treatments.

Planned Impact

The proposal facilitates the evaluation of all data from all subjects enrolled in UK-based birth cohorts on asthma (MRC-funded STELAR consortium). Beneficiary engagement will include active interactions within the trans-disciplinary team, with the general public and patient organisations and the clinical community.
We will establish a multi-disciplinary/multi-institutional collaborative partnership to develop a unified modelling approach that can take full advantage of this unparalleled resource. This will allow us to exploit fully the complexity of data, maximise sharing and linkage of data, and to develop data storage, which is in line with the MRC strategic aim 4. We will develop innovative resources for interdisciplinary collaboration - a step beyond sharing resources. Through Asthma e-Lab, we will create conditions to open up the analysis process and networking around the results to a range of investigators across the project, creating a trans-disciplinary informatics environment which will include epidemiologists, public health researchers, statisticians, informaticians and software engineers. We will draw upon our experience of a similar task in the ESRC-funded Obesity e-Lab project which produced Methodbox to offer fine-grained security and professional social networking facilities to enable investigators to find, extract, share, and reuse data extracts from large complex longitudinal data sets. The e-lab system will allow investigators to collaborate on-line over on-going analyses through the browser-based interface with networking facilities. An on-line STELAR community will be nurtured to maximise the transfer of knowledge between different areas of expertise.
We will extend this approach to a doctoral training scheme. Enabling the networking of datasets, expertise and methods for data preparation and analysis can help drive greater value from existing investments.
Engagement with general public will be undertaken through a combination of electronic communication (websites) and articles in newsletters, together with direct interaction with the public through the media (newspapers, radio, TV), public lectures and involvement with schools (e.g. through regular engagement events at the University of Manchester aimed at students between the ages of 12 and 18 year, who visit the University to learn more about the research we do). We will use these events to engage students about the importance of the work we carry out to understand asthma, and how this can potentially help people in the future.
Dissemination to UK and International clinical communities will be led by co-applicants (principal investigators from 5 UK birth cohorts).
Endotypes of asthma will be defined through the fusion of computational thinking and novel mathematical approaches with biomedical and environmental science and genetics. These novel endotypes better reflect the different underlying pathophysiological processes and molecular pathways underpinning different diseases in the asthma syndrome, and may be more relevant for epidemiological, genetic and therapeutic studies. The outputs will enable the UK to maintain world leadership by gaining insight into genetic and environmental interactions underlying asthma and better understanding of how different physiological processes work together (in line with the MRC strategic aim 1). This strategy may lead to the development of methods for prevention that are endotype-specific, and through better understanding of the disease mechanisms, identification of endotype-specific novel therapeutic targets. The findings may represent potentially valuable intellectual property, which we will seek to commercialise in collaboration with companies with interests in diagnostics and/or therapeutics. Participating universities have mechanisms and structures in place for exploring industrial applications both during and at the end of the lifecycle of the project grant.

Publications


10 25 50
Belgrave D (2016) The importance of being earnest in epidemiology. in Acta paediatrica (Oslo, Norway : 1992)
Belgrave D (2017) Disaggregating asthma: Big investigation versus big data. in The Journal of allergy and clinical immunology
Belgrave DC (2015) Atopic Dermatitis and Respiratory Allergy: What is the Link. in Current dermatology reports
Custovic A (2015) Evolution pathways of IgE responses to grass and mite allergens throughout childhood. in The Journal of allergy and clinical immunology
Custovic A (2017) Middleton's Allergy Essentials
Custovic A (2015) To what extent is allergen exposure a risk factor for the development of allergic disease? in Clinical and experimental allergy : journal of the British Society for Allergy and Clinical Immunology
Del Giacco SR (2017) Allergy in severe asthma. in Allergy
Deliu M (2016) Asthma phenotypes in childhood. in Expert review of clinical immunology
 
Description ARIA guidelines 2016
Geographic Reach Multiple continents/international 
Policy Influence Type Membership of a guideline committee
Impact Improvement in outcomes in allergic rhinitis
 
Description EAACI position paper: A new framework for the interpretation of IgE sensitization tests
Geographic Reach Multiple continents/international 
Policy Influence Type Membership of a guideline committee
Impact A new framework for the interpretation of IgE sensitization tests
 
Description EAACI position paper: Allergy in severe asthma
Geographic Reach Europe 
Policy Influence Type Citation in clinical reviews
 
Description MACVIA clinical decision algorithm in adolescents and adults with allergic rhinitis
Geographic Reach Multiple continents/international 
Policy Influence Type Membership of a guideline committee
Impact The selection of pharmacotherapy for patients with allergic rhinitis (AR) depends on several factors, including age, prominent symptoms, symptom severity, control of AR, patient preferences, and cost. Clinical decision support systems (CDSSs) might be beneficial for the assessment of disease control. CDSSs should be based on the best evidence and algorithms to aid patients and health care professionals to jointly determine treatment and its step-up or step-down strategy depending on AR control. Contre les MAladies Chroniques pour un VIeillissement Actif en Languedoc-Roussillon (MACVIA-LR [fighting chronic diseases for active and healthy ageing]), one of the reference sites of the European Innovation Partnership on Active and Healthy Ageing, has initiated an allergy sentinel network (the MACVIA-ARIA Sentinel Network). A CDSS is currently being developed to optimize AR control.
 
Description ERS Maurizio Vignola Gold Medal in Asthma 2015
Amount € 50,000 (EUR)
Organisation European Respiratory Society (ERS) 
Sector Charity/Non Profit
Country European Union (EU)
Start 10/2015 
End 09/2018
 
Description MRC & Asthma UK Centre in Allergic Mechanisms of Asthma
Amount £1,999,074 (GBP)
Funding ID AUK-BC-2015-01 
Organisation Asthma UK 
Sector Charity/Non Profit
Country United Kingdom of Great Britain & Northern Ireland (UK)
Start 08/2016 
End 08/2021
 
Description MRC Strategic Skills Fellowship - Career Development Award in Biostatistics to Dr Danielle Belgrave
Amount £350,000 (GBP)
Organisation Medical Research Council (MRC) 
Sector Academic/University
Country United Kingdom of Great Britain & Northern Ireland (UK)
Start 10/2015 
End 09/2018
 
Description Wellcome Trust Strategic Award: Pulmonary epithelial barrier and immunological functions at birth and in early life - key determinants of the development of asthma?
Amount £4,640,000 (GBP)
Funding ID WT108818MA 
Organisation The Wellcome Trust Ltd 
Sector Charity/Non Profit
Country United Kingdom of Great Britain & Northern Ireland (UK)
Start 09/2016 
End 08/2021
 
Title STELAR dataset 
Description In order to carry out the analyses and apply novel modelling approaches to the large, complex dataset from the five UK birth cohorts, the data must be accessible to the analysts, along with consistent information about the study measurements and the assumptions underlying the relations reflected in the annotated dependency graphs representing the problem space of asthma. To achieve this, we created a secure web-based research environment (Asthma e-Lab; www.asthmaelab.org) to support consistent recording, description and sharing of data, computational statistical methods and emerging findings across the cohorts. The Asthma e-Lab serves as a data repository populated with a unified dataset from our well-defined birth cohorts; in addition, it provides the computational resources and a scientific social network to support timely, collaborative research across the consortium. 
Type Of Material Database/Collection of data 
Year Produced 2017 
Provided To Others? Yes  
Impact Emerging findings are shared with all sites via the e-Lab, linked to explanations of analytical methods that might not be familiar to all participants, thereby creating a scientific social network enriching the on-going modelling and interpretation. 
URL https://www.asthmaelab.org/share/page/
 
Description The CREW consortium 
Organisation University of Wisconsin-Madison
Country United States of America 
Sector Academic/University 
PI Contribution We have created conditions that will facilitate data sharing with the consortium of 12 US-based birth cohorts (CREW). NIH has just announced that CREW were awarded funding through the Environmental influences on Child Health Outcomes (ECHO) programme, and CREW will utilise our UK STELAR knowledge management platform (eLab). This will provide a worldwide platform to help solve the global problem of asthma. Our flexible platform will be able to accommodate other cohorts and disease outcomes in future
Collaborator Contribution The National Institutes of Health (NIH) has awarded the University of Wisconsin School of Medicine and Public Health a two-year, $15 million grant to establish and oversee the Children's Respiratory Research and Environment Workgroup (CREW) - a national consortium of 14 institutions that will study how genetics interact with environmental exposures during the prenatal and early childhood years to cause specific subtypes of childhood asthma.
Impact We have created conditions that will facilitate data sharing with the consortium of 12 US-based birth cohorts.
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation Imperial College London (ICL)
Department National Heart & Lung Institute (NHLI)
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation Queen Mary University of London (QMUL)
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation Queen's University of Belfast
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation University of Aberdeen
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation University of Bristol
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation University of Edinburgh
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation University of Lausanne
Country Switzerland, Swiss Confederation 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Description Wellcome Trust Strategic Award WT Strategic Award WT108818MA 
Organisation University of Southampton
Country United Kingdom of Great Britain & Northern Ireland (UK) 
Sector Academic/University 
PI Contribution Population-based birth cohorts, which eliminate recall bias and enable repeated longitudinal long term phenotyping are the preferred method for understanding patterns of different wheezing subtypes and relating them to different genetic readouts. A major challenge is how best to utilise vast amounts of data and correlations between them to identify the latent (hidden) causes of phenotypes. By delineating the latent structure underlying the observed disease variation, we anticipate that pathophysiological processes specific to latent factors or classes will be identified. STELAR latent structures will be applied to the infants recruited in WS1 and then we will determine if there are differences between classes in the mechanistic studies of WS2-4. Conversely, the significance of novel molecules and pathways detected in these workstreams can be determined by mapping them to STELAR latent classes. Rather than data-mining, analyses will be informed by biological and clinical hypotheses. It is essential to integrate data; models/methods that can be tailored in full to the problem space; and human expertise to tailor models/methods and make sense of results in context. Bringing the data, methods and investigators together on-line is the key objective of the MRC-funded Study Team for Early Life Asthma Research (STELAR) consortium.
Collaborator Contribution Genome-wide genotyping data are currently available in only 2 STELAR cohorts, and we will increase the power of the discovery platform by adding genome-wide genotyping data from the others. We will develop cutting-edge analyses to map the latent structure of wheezing illnesses in children, to understand the biological pathways underpinning the phenotypic variation and to test these findings in the experimental workstreams of this programme. In turn we will test the clinical and population-attributable significance of novel biomarkers discovered in workstreams 2-4.
Impact N/A
Start Year 2016
 
Title STELAR Asthma eLab 
Description We created a secure web-based research environment (Asthma e-Lab; www.asthmaelab.org) to support consistent recording, description and sharing of data, computational statistical methods and emerging findings across the cohorts. The Asthma e-Lab serves as a data repository populated with a unified dataset from our well-defined birth cohorts; in addition, it provides the computational resources and a scientific social network to support timely, collaborative research across the consortium. The activities of data managers and investigators from the five STELAR sites are visible to one another, supporting team coordination and peer support, whilst creating a record of activity to ensure transparency. Researchers inputting the data can see how the data are being used in the analyses, and receive on-line training via the e-Lab, thereby harmonising the relevant knowledge, skills and practices needed to create a consistent STELAR dataset. Emerging findings are shared with all sites via the e-Lab, linked to explanations of analytical methods that might not be familiar to all participants, thereby creating a scientific social network enriching the on-going modelling and interpretation. 
IP Reference  
Protection Protection not required
Year Protection Granted 2016
Licensed Yes
Impact We have created conditions that will facilitate data sharing with the consortium of 12 US-based birth cohorts (CREW). NIH has just announced that CREW were awarded funding through the Environmental influences on Child Health Outcomes (ECHO) programme, and CREW will utilise our UK STELAR knowledge management platform (eLab). This will provide a worldwide platform to help solve the global problem of asthma. Our flexible platform will be able to accommodate other cohorts and disease outcomes in future.
 
Title ImmunoCAP ISAC (Thermo Fisher Scientific, Uppsala, Sweden) 
Description Clinical implications: Development of different clinical phenotypes of allergic diseases (asthma, eczema, and rhinitis), as well as asthma severity throughout childhood, is predicted by the molecular nature of IgE responses to individual allergen components. 
Type Diagnostic Tool - Non-Imaging
Current Stage Of Development Late clinical evaluation
Year Development Stage Completed 2015
Development Status Under active development/distribution
Impact Our findings suggest that different longitudinal patterns in the development of IgE responses to grass and mite allergen components during childhood are associated with different clinical outcomes and confirm the hypothesis that atopic sensitization can be stratified into subtypes with a diversification of their evolutionary pathways over time. Better resolution of such longitudinal patterns might help us better understand the pathophysiology underlying atopic diseases and might facilitate the development of biomarkers of allergic disease, which can be used for the prediction of future risk. 
 
Description Allergy web chat 
Form Of Engagement Activity Engagement focused website, blog or social media channel
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Patients, carers and/or patient groups
Results and Impact Allergy web chat focussed on:
How do I find out what triggers my seasonal allergies?
What is the difference between a food allergy and a food intolerance?
What should I know about anaphylactic shock?
Can allergies be 'cured'?
Year(s) Of Engagement Activity 2016
 
Description ERS Gold medal for asthma 
Form Of Engagement Activity A press release, press conference or response to a media enquiry/interview
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Media (as a channel to the public)
Results and Impact ERS has launched this new award to recognise excellence in asthma research. The ERS Maurizio Vignola Gold Medal in Asthma grants €50,000 to a researcher who has made an outstanding contribution in the field of asthma and is pursuing an active research project in asthma.
Year(s) Of Engagement Activity 2015
URL http://www.aukcar.ac.uk/professor-custovic-presented-with-ers-maurizio-vignola-gold-medal-in-asthma/
 
Description Inaugural lecture 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach International
Primary Audience Other audiences
Results and Impact Inaugural lecture of Professor Adnan Custovic. The talk is now available on the Imperial College London website
Response from the attendees: "Your talk and career story greatly motivated me to join team science research for the next step."
Year(s) Of Engagement Activity 2016
URL https://www.youtube.com/watch?v=WKL7Z99YC0k
 
Description Visit to Asthma UK 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach National
Primary Audience Supporters
Results and Impact Visit to Asthma UK to publicise the work of the STELAR consortium
Year(s) Of Engagement Activity 2017