University of Exeter

Academic Institute

OFHS250013

More than half of people aged 65+ are living with more than one long-term condition (multimorbidity). Despite this, people with multiple long-term conditions are often excluded from clinical trials, and there has been limited research into identifying the causes of multimorbidity. The aim of our research is to uncover new links between long-term conditions that could lead to improved interventions including drug treatments or other more targeted interventions. The specific long-term conditions we will study are identified by our data-driven approach. Our interactive web browser (https://gemini-multimorbidity.shinyapps.io/atlas/) demonstrates the large number of conditions that co-occur more than expected by chance, and have genetic overlap. Conditions will include common diagnoses such as high blood pressure (hypertension), joint diseases (such as osteoarthritis), and less common conditions such as the iron-overload disease haemochromatosis, that itself increases risk of multimorbidity. Our Future Health presents an exciting opportunity to extend our research to a new, larger, more population-representative and socio-economically diverse cohort. We will use genetic information linked to lifestyle and participants characteristics (such as obesity), together with linked health records, to study the factors that impact both the age of disease diagnosis (individually, and in combination) and also the severity of symptoms. Many long-term conditions co-occur in the same patient more than expected by chance, but the reasons are often complicated. Healthcare professionals and researchers tend to focus on one condition at a time. For example, there has been a lot of research into the causes and consequences of osteoarthritis but not why people with osteoarthritis have a higher-than-expected frequency of asthma, even when accounting for sex, age and obesity. By identifying the specific mechanisms and risk factors that increase the chance of diseases co-occurring in the same patient we will highlight prevention, early diagnosis, or treatment opportunities. Acknowledging each person’s unique combination of genetics, environment, and lifestyle allows us to better study the risk factors and paves the way for personalised (or “stratified”) medicine.

We aim to understand why some long-term conditions occur together. This will improve prevention and treatment. We will: 1. Identify shared effects of medicines. Some medicine used to treat different conditions affect the same biological pathways. For example, we found that that a drug currently prescribed to treat rheumatoid arthritis and another prescribed to treat skin cancer target the same pathway. This may explain why some patients taking these medicine may develop both conditions. Understanding these links can help improve safety in prescribing. 2. Find common risk factors. Some health conditions share underlying causes. In a previous study, we found that while obesity increases risk of many diseases, certain combinations of conditions are more strongly linked to obesity than others. This highlights a greater need for advice and support in these groups. We will also look at how genetic information can help identify subsets of the population at higher risk of complications of long-term conditions. Identifying those at high risk earlier can help doctors take steps to prevent or delay severe symptoms. This research will support more effective prevention, earlier diagnosis, and better treatment in people with multiple long-term conditions, which affects the majority of people across their lifetime.

Public Health Research

21/07/2025

31/03/2025

TRE