Multimorbidity clusters, trajectories and genetic risk, in British south Asians

Our research proposal covers an important area of health called 'multimorbidity', which describes where an individual is affected by 2 or more health conditions. Studies have shown that multimorbidity is getting more common in the United Kingdom, and the National Health Service does (NHS) not currently have services designed to tackle it well. Recent research has also shown that multimorbidity exists in 'clusters', with groups of common conditions (e.g. type 2 diabetes, high blood pressure, chronic pain, and depression) often co-exist. However, there is a lot still to learn about multimorbidity, and more research is needed to find out why it occurs, who is at risk, and how to design better health and social care to manage it. Our proposal will produce new knowledge that fills some of the important gaps in our understanding of multimorbidity.

We will study multimorbidity in people living in a large east London population of 1.05million people, one-third of whom come from a south Asian ethnic group and who live in high socioeconomic deprivation; both known to be risk factors for multimorbidity. Data collected in electronic health records (e.g. the diagnoses made or treatments given to you when you visit your GP) will be used to inform us about multimorbidity in this population. We will use state-of-the-art statistical techniques that use this data to tell us which are the most common 'clusters' of multimorbidity in east London, and whether they vary in British south Asians compared to Whites. Using historical records, we will study patterns of multimorbidity clusters during a person's life, what risk factors might be associated with them, and how severely they may impact an individual.

The next focus in our research will be to investigate the genetic causes of multimorbidity using cutting edge studies of the genome in volunteers participating in the East London Genes and Health (ELGH) study. ELGH is a large study of people of British-Bangladeshi and -Pakistani origin living in east London, with 32,000 volunteers involved already. Volunteers in ELGH have given consent for us to access their electronic health records and also study their genes using a spit sample donated to the study. We will investigate whether differences in the genetic code of individuals are linked to the risk of multimorbidity. One specific genetic code change we will be looking at is called 'autozygosity', a phenomenon affecting some people in these ethnic groups where parental relatedness is common. Autozygosity increases the chance that gene copies inherited from a person's mother and father are the same, and some studies have shown that this is linked to certain disease. We will study whether the amount of autozygosity in a person's genetic make-up could affect a person's risk of developing multimorbidity. We will also investigate an area of major interest in genetic and health studies at the moment, called polygenic risk scores (PRS). These scores identify multiple, small changes to an individual's genetic code that, when added together using a mathematical formula, strongly predict whether someone is at risk of developing conditions such as heart disease. PRSs have been studied mostly in people of White ethnic groups, and we will contribute to wider efforts to investigate their impact on disease and multimorbidity in south Asians.

Our research will use potentially sensitive data for our studies and we will take very stringent and careful approaches to using this data so that there are no data security issues, and to ensure all data has been collected using appropriate consent and information governance procedures.

We expect that the impact of our research will be wide-ranging, including supporting improvements in health and social care for multimorbidity and perhaps more efficient use of limited NHS funds. We will deliver direct benefits back to our research volunteers through educational programmes and public engagement.

Our proposal seeks to deliver new knowledge on multimorbidity, focusing on clustering, trajectories and its potential genetic risk in British South Asians, who are under-represented in research despite disproportionately high morbidity and mortality.

In an unselected, multiethnic, socioeconomically-deprived east London population of 1.05million, we will identify multimorbidity clusters, using exploratory factor analysis in electronic health record (EHR) data. We will investigate how clusters vary between British south Asians (and subgroups) and Whites. Trajectories of multimorbidity will be studied using a longitudinal data using multi-state modelling and survival analyses. We characterise the contribution from known risk factors to these trajectories as well as their ethnic variation.

East London Genes and Health (ELGH) is a community health and genomics study of British-Bangladeshis and -Pakistanis, with target (funded) recruitment of 100,000. Multi-source linked EHR data, exome-sequencing and genotype chip data will be used to study the association between multimorbidity and genetic risk. The possible genome-wide effects of autozygosity (from parental relatedness) on multimorbidity clusters and trajectories will be studied, hypothesising that they may increase the burden of rare homozygous damaging gene variants, and/or increasing additive variance and polygenic disease susceptibility. We will also investigate whether polygenic risk scores (PRSs) for individual traits can be combined to optimise prediction of multimorbid disease, and whether these PRSs for specific diseases and multimorbidity perform as well in south Asian as in White populations. Causal inference studies (e.g. Mendelian randomisation) will be applied where indicated.

Our proposal will deliver impact through the generation of new knowledge readily translatable to clinical care and societal benefit, and focusing on understudied populations.

The potential impact of this research are broad, and cover a range of domains, including academic, health policy and economic impact, as well as direct impact on the individuals contributing to the research through public engagement.

Academic impact: this will be achieved through the generation of new interdisciplinary knowledge relating to multimorbidity using electronic health record and genomic data. By studying disease clusters and trajectories using a large, population-based dataset including an under-studied British South Asian population at high risk of multimorbidity, we will generate new insights into who is at risk of multimorbidity and the different paths it follows. Through the combined study of genomic data within the East London Genes and Health subpopulation, we will be able to undertake innovative analysis that links these epidemiological patterns to potentially causal genetic phenomena, including the study of autozygosity and polygenic risk factors in populations. Our work would support large-scale, consortium-based efforts to define transethnic polygenic risk scores, and we would actively participate in these efforts through collaboration and data sharing. Our research will deliver new methodological insights related to the integration of health data science and genomics that could have direct impact to the academic community. We will actively support the training of junior academic researchers. Our findings will support research beyond the research disciplines included in this application, including translational and health services research into multimorbidity.

Economic and societal impact: we will deliver new knowledge on multimorbidity in a large ethnically-diverse and socioeconomically-deprived population at high risk. By using electronic health record data to generate this new knowledge on multimorbidity patterns, our research will support direct and feasible translation back to clinical care in the NHS, e.g. via better risk identification and stratification that could be applied to electronic health records, risk prediction tools and use of data dashboards. We have existing links to Health Data Research UK that we anticipate will help support health data science and its clinical applications within the NHS. Our research team includes clinicians embedded in local health systems (Finer, Hull, van Heel), and this will facilitate knowledge sharing and impact. We will take active steps to disseminate the results of our analyses with healthcare professionals, policymakers and commissioners to guide service improvements. Identification of autozygosity and polygenic risk scores as multimorbidity risk factors could improve clinical care through better genetic counselling to families at risk and identification of risk early in the lifecourse. As such, the research will support policy-level improvements in health care with potential economic impact, e.g. through targeting prevention strategies to those at the highest risk, reducing health inequalities, and the more efficient distribution of funds to models of care that tackle multimorbidity. By setting our research in a British south Asian population, we will be able to contribute to global research efforts on multimorbidity.

Public engagement: ELGH is a community-embedded study that keeps engagement at its core, supported by its ELGH Community Advisory Group, 'Helix Champions' (community researchers) and third sector organisations, e.g. Social Action for Health. This research would continue to support community engagement and health education activities sharing new knowledge amongst ELGH volunteers, their families and the wider east London population. We would continue our innovative engagement activities with the award-winning Centre of the Cell, to deliver educational workshops and interactive web- and app- content based on multimorbidity, polygenic risk and autozygosity.