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

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.

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.

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.