Genetic Evaluation of Multimorbidity towards INdividualisation of Interventions - GEMINI

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1. To identify disease clusters using a combined genetic and observational approach; and to test the hypotheses that: a) using multiple data sources and genetic correlations will provide more robust estimates of clustering than has been so far possible, and that b) patterns of clustering differ between the sexes and ethnic minorities. 2. To improve reproducibility of multimorbidity research, and working with other collaborative bids where relevant, to develop STATA and R packages to standardize the MRC Reference: MR/V005359/1 Page 2 of 16 SPF Tackling Multimorbidity at Scale: Case for Support process of disease coding across GP databases, and to make these tools publicly accessible. 3. To develop and apply genetic and non-genetic "instruments" and causal inference methods to identify shared biological and non-biological determinants of disease clustering. These instruments will include clusters of genetic variants specific to potential shared disease processes and be randomized to disease incidence and adverse outcomes. 4. To identify a subset of emerging disease clusters for further, in depth study; to validate these clusters in additional datasets with different ascertainment criteria; and to test the hypothesis, using longitudinal data, that the timing sequences of the different disease components to the identified clusters differ from chance (life course). 5. To identify the cluster-associated outcomes of most impact, as informed by frequency, severity and our PPI advisors; to estimate the proportion of patients in each cluster who develop the most impactful outcomes and identify potential modifiable risk factors. 6. To identify the disease clusters that result in clinically meaningful differences in outcomes compared to patients with only one of the constituent diseases.