Brain ageing in schizophrenia and as a marker of physical and mental well-being

Background and context: The structure of the human brain changes as we age, and these changes are associated with cognitive decline and brain diseases. Individual differences exist in the brain ageing process and, potentially, deviations from healthy brain ageing trajectories could indicate underlying problems in apparently healthy people and relate to the risk and progression of disease and mortality [1]. Alternatively, the presence of a disease may result in progressive acceleration of the brain ageing process. For example, findings from several recent studies indicate significantly accelerated structural brain ageing in schizophrenia [2-4]. Furthermore, individuals with schizophrenia have a reduced life expectancy of up to 15 years, however, it is not well understood (i) whether this is driven by poor physical health or also through accelerated brain ageing and (ii) which genetic and/or modifiable lifestyle factors influence this acceleration.

Aims and objectives: This project focuses on healthy brain ageing in the general population and in individuals with schizophrenia. We will develop a novel signature of accelerated brain age (derived from structural MRI scans) to:

1. Investigate how brain age links to a large number of traits in the general population, including physical health (e.g. immune and cardiometabolic traits) (Study 1). Study 1 will be based on data from UK Biobank (subset with brain imaging data, n=21,915). We will derive a brain age measure based on a pipeline developed as part of the Enhancing Neuro-Imaging Genetics through Meta-Analysis (ENIGMA) Brain Age working Group (https://www.photon-ai.com/enigma_brainage) and test associations with all traits in UK Biobank (n=23,004). This will allow us to identify how brain ageing associates with a wide range of traits related to physical and mental health.

2. Shed light into the genetic architecture of brain ageing (Study 2). Study 2 will also be based on UK Biobank data. We will carry out a genome-wide association analysis to identify genetic variants associated with brain ageing, which could then be used as instrumental variables in a Mendelian randomization analysis to assess causality of associations identified in Study 1 [5].

3. Identify how schizophrenia (SZ) and linked modifiable lifestyle factors (e.g. cannabis use, smoking, BMI) impact accelerated brain ageing (Study 3). We will generate the largest study of brain ageing in SZ. Data will be analysed from the ENIGMA-SZ Group, which includes 39 well-characterized cross-sectional samples worldwide with brain imaging data (n=10,132, age 10-87). We will investigate brain age difference in patients and controls and how lifestyle factors might affect these differences.