Title: NIHR Global Health Research Unit on Global Diabetes Outcomes Research, University of Dundee
Funder: Department of Health and Social Care

Abstract: The University of Dundee is actively engaged in global health issues across a broad range of disciplines, where not only life sciences, medicine, dentistry and nursing have significant impact, but also where environmental, political, and regulatory issues are major players in the health agenda. To this end the University of Dundee has formed the Tayside Institute for Global Health, which engages with staff and students from the University and NHS Tayside to tackle global health issues. The Institute will provide further opportunities for impact for the diabetes research proposed here. The current proposal will integrate existing areas of excellence in diabetes health informatics and genetics research in Scotland with that of the largest clinical network of diabetes care in India, Dr Mohan’s Diabetes Specialities Centre. This has over 20 centres around India with 400,000 registered patients with diabetes , and hosts a WHO coordinating centre for non-communicable diseases prevention and control. The University of Dundee has a proven track record in global health (Rated 7th in UK) . The University is rated 1st in UK for Research Outputs in Life Scences and 1st in the UK for impact in Medicine). The University of Dundee is an internationally recognised centre of excellence in diabetes research, hosting over 20 research groups that include some of the world’s most cited scientists. Dundee is one of the top four institutions in the UK for Diabetes UK-funded research, receiving more than the rest of the Scottish research community combined, a measure of the level of work taking place at the University. Professor Sir Mark Walport, the current Government Chief Scientific Adviser (GCSA) and Head of the Government Office for Science has stated that “If you live in Dundee and suffer from diabetes, you have been participating in a medical revolution.” (The Times, 30.05.11) It is this revolution that we wish to progress with partners in India. Proposed programme of research. The programme will establish the partnership of the Dundee group with the Madras Diabetes Research Foundation in Chennai with the training of a new generation of big data analysts in the analysis of linked molecular and clinical data, including the deep data mining of imaging and clinical datasets. This coupled to the existing advanced clinical management systems in both centres will accelerate the adoption of the big data revolution into real life personalized care in diabetes and related morbidity. In order to deliver this vision our strategic plan comprises six workpackages. WP1: Leveraging large scale health record data. (Short term Years 1 to 2 ) In order to provide a unique insight in to both inter-individual and population variation in the causes and consequences of diabetes in India we will consolidate and harmonize the pre-existing large scale clinical datasets in Scotland and India amounting in total to over 600,000 patients with diabetes with continuous data spanning over 20 years This includes all diagnostic codes, biochemistry, blood pressure, all relevant prescribing particular for diabetes, eye screening data, and podiatry. In Dundee we have extensive experience of using such holistic and longitudinal data to develop models of disease progression, susceptibility to complications and response to therapy (1-5). Recent work performed within our European network has determined new models that differentiate Type 2 diabetes into 5 different diseases. Preliminary analysis of Dr Mohan’s DiabetomeDb (6) has determined that over 95,000 patients have had C-peptide measured and these data are available. This one data point alone suggests that the biggest study of beta-cell reserve in Type 2 diabetes in the world is possible We will use these extensive data to: • Characterise the pathophysiology of subgroups of diabetes in India. • Undertake epidemiology of the complications of diabetes in India • Investigate determinants of inter-individual variation in drug response. WP2: Genetic epidemiology and pharmacogenetics. (medium term, Year 2-3) Both sites have stored blood samples available for genetic analysis on tens of thousands of individuals with diabetes. In GoDARTS GWAS data is already available on 9K patients and has been used in many GWAS studies published over the past 7 years (7-9). Both the Dundee group and Dr Mohan’s group have been involved in the international collaboration on trans-ethnic genetic determinants of susceptibility to type 2 diabetes (10). Within this project we will obtain a similar GWAS resource within DiabetomeDb by genotyping both pre-existing stored blood samples and de-novo collections of blood samples to around 20,000 diabetic individuals in India. Genotyping will be performed in an additional 11,000 scottish diabetic patients from GoSHARE (www.registerforshare.org) to provide a total trans-ethnic cohort of 40,000 type 2 diabetes with full genome genotyping and longitudinal outcome data including retinome analysis from WP3. We will exploit this to refine the clustering epidemiological analyses in WP1 to incorporate genomics to determine genomic signatures of diabetes subtypes specific to the Indian sub-continent including those defined by therapeutic response to established anti-diabetic medications. WP3: The Retinome as a clinical phenotype screening tool (medium term 2-3 years). As a means of direct visualization of blood vessels there is evidence that images of the retina contains information relevant to wide range of vascular phenotypes in diabetes beyond that of diabetic retinopathy (11). A retinal photograph may be able to provide a very low cost panel of imaging biomarkers indicating for the global vascular health of an individual; thus, facilitating more cost effective targeting of more complex and costly examinations. In GoDARTS we have accessed all digital diabetes retinal screening images which are currently being processed by the VAMPIRE platform(12). We have shown that VAMPIRE can efficiently detect and score hundreds of retinal features in eyes that reveal underlying disease, and previous exposure to risk factors such as high blood pressure and smoke exposure. We have also found that this extends to indicating susceptibility to subsequent development of various vascular disease outcomes such as heart disease, stroke and renal disease. In this work package we will extend the VAMPIRE analysis to around 20,000 retinal images in Dr Mohan’s DiabetomeDb from the individuals that are also being genotyped in WP2, and will adapt VAMPIRE for the low-cost Remidio “Fundus on the Phone” platform that is being deployed throughout Dr Mohan’s clinical network (13). This will include the development of automated analysis required for implementation in WP5. WP4: Integrative Predictive algorithms. (Long term, years 3 to 4 to integrate all modes of data) In this work package we will develop optimal models for disease prediction and management using clinical, genetic and retinome data to be deployed in Clinical decision making throughout Dr Mohan’s Speciality Clinic network, and for deployment in rural outreach in WP5. WP5: Next-Gen Telemedicine. (Short term: years 1 and 2 initiate mobile telemedicine logistics. Long term Years 3 and 4 implementation of automated analysis) The Chennai group has a major track record in rural diabetes screening with the highly successful Chunampet Rural Diabetes Prevention Project (CRDPP) which used a large fully equipped and custom built van to screen 27,000 individuals in 42 villages (14). This started in 2006, therefore the data transfer required Very Small Aperture Terminal satellite connectivity in collaboration with the Indian Space Research organization in Bangalore. Today this can be delivered with agile health worker units with inexpensive mobile phone connectivity and hand held instruments including the Remidio “fundus on Phone” apparatus currently implemented throughout the DMDSC clinic system. This will allow expansion of this activity to a wider area of both rural India and rural slums in Chennai and demonstrate a more affordable and sustainable option for the prevention and management of metabolic disease in the rural population. This programme will also include the development of a “personal portable electronic record” with the Dr Mohan’s Mobile App developed further to show store an individuals holistic medical record populated with data from the central system, this parallels similar developments in Scotland where we have developed the personal electronic record portal http://www.mydiabetesmyway.scot.nhs.uk/diabetes/default.asp. This will provide the ability for other speciality health care providers to have access to the patient’s diabetes history when considering treatment (for example at a cancer referral centre). This would greatly improve the integration of individual health care in this generally fragmented system. WP6. Capacity building and training. This programme will generate the next generation of postdoctoral analysts to bring big-data concepts into clinical utility . In addition, we will initiate a PhD programme with two intakes of 5 students over the funding period (October2017 and April 2018). These students will be recruited from the top Universities in India, and will be selected by a joint Dundee/Chennai team including the two directors. The programme will involve registration at the University of Dundee, and an initial year of training in health informatics in Dundee. This will be followed by a period of work in Chennai as determined by each student project requirements. This increased analytical manpower capacity will allow us to respond to commissioned work in a response mode as managed by the Unit Management board and advisory committee. In addition, contingency funding has been allocated to provide non-staff expenses to facilitate this commissioned and response mode research

Lay abstract: Diabetes results in a wide range of serious medical complications with significant implications both for the affected individual and their society. Globally three quarters of diabetes is now in low and middle-income countries who lack the infrastructure to manage the scale of the emerging problem. Diabetes is a major problem in India with 1 in 12 people affected amounting to 69 million individuals currently (more than the entire UK population). With increasing economic development, the numbers are rapidly increasing. The majority of studies on how diabetes develops, how patients respond to medications and the causes of medical complications that arise are from white European ancestry populations despite the fact that diabetes in Europeans is very different to diabetes in South Asians. There is an urgent need for a large in-depth study of the specific causes and consequences of diabetes in LMIC in order to identify different subtypes of diabetes that exist and understand how best to manage each subtype. The INSPIRED project is a 4-year partnership between two institutions, the University of Dundee’s Global Health Research Unit and Dr Mohan’s Speciality Diabetes Centres, who between them command access to two of the most advanced diabetes management systems in the world: the Scottish Clinical Care Information-Diabetes Care (SCI-DC), which provides a sophisticated shared electronic patient record for every individual with type 2 diabetes in Scotland (n=250K) and the Dr Mohan’s Speciality Diabetes Centres (DMDSC)(n=400K). Both clinical systems are partnered with internationally renowned research groups (GoDARTS in the UK and Madras Diabetes Research Foundation (MDRF) in India), who have previously collaborated in international studies of how genes influence susceptibility to type 2 diabetes. The INSPIRED partnership is focused on using this extensive infrastructure to deliver precision medicine to improve outcomes in patients with diabetes in India. Both groups are studying the molecular and clinical causes of major complications of type 2 diabetes such as heart disease, blindness, kidney failure and amputations. The UK investigators pioneered the concept of personalised medicine through the use of genetics to determine who will and will not respond to commonly used drugs in diabetes. They have also shown that using computers and the internet to summarise and communicate the patient’s medical details to the doctor leads to better health outcomes; and have made substantial inroads in the use of artificial intelligence to analyse digital pictures of patient retinas to find features that reveal a patient’s current disease status. The wide spread adoption of mobile phone technology in India, the development of inexpensive portable retinal cameras that work with mobile phones and the price of large scale genotyping rapidly tumbling to a few Euros per genotyping test, provides the potential to completely rethink strategies for health screening in India. It is INSPIRED’s ambition to advance knowledge in the field by combining clinical, retinal image and molecular information to build predictive models of complications for personalised diabetes treatment in India. In particular to provide a low cost, agile and sustainable solution supported by telemedicine for outreach to the poorest populations in rural India, the urban slums and potentially other LMIC.

Research activity codes: 4.5 RESOURCES AND INFRASTRUCTURE (DETECTION)
Health categories: METABOLIC AND ENDOCRINE