Our research

Using a ‘big data’ approach, we will investigate how and why mental ill-health interacts with cardiovascular disease.

Using novel statistical and machine learning approaches, our researchers will identify the genetic, brain and body markers that are common to both conditions. These will form the basis of clinical tools for prediction, diagnosis and disease monitoring.

To achieve this, our project has been broken down into 8 'work-packages': 

  1. Data infrastructure and analytical tools
  2. Genetics of comorbidity trajectories
  3. Nature, nurture and genetics of lifestyle
  4. Functional mechanisms and body-brain imaging
  5. Precision medicine - prediction/stratification tools for pharma
  6. Dissemination, communication, exploitation and public outreach
  7. Management and coordination
  8. Ethics

All partners will work together to achieve our overall goals. 

Flow chat showing how the 7 CoMorment Workpackages listed above interact with one another (reciprocal arrows connect all workpackages together)


CoMorment will investigate the interactions between:

  • common mental health conditions (such as schizophrenia, bipolar disorder, major depressive disorder and drug-induced psychosis). 
  • lifestyle factors
  • cardiovascular disease

As a team, we will make use of:  

  • Health, genetic, lifestyle and brain imaging data from existing cohorts (1.8 million volunteers from across Northern Europe)
  • Cutting Edge Big Data tools (Baysian tools, LRP and GWAS) – for gene discovery, predicting comorbidity and disentangling nature from nurture.
  • Advanced Mapping Techniques - to study changes on brain MRI scans and movement of body fat into tissues that may be predictive of future ill-health. 

We will advance towards clinical utility by: 

  1. Understanding disease mechanisms
  2. Creating prediction tools
  3. Progressing towards treatment stratification (splitting patients into treatment groups)

Flow chat summarising the CoMorMent methods.