Approved Research

Brain aging in major depressive disorder (MDD) investigated by multimodal magnetic resonance imaging at the network level

Lay summary

The aim of this project is to understand if depression which is a stress-related condition and highly prevalent in the population is associated with accelerated aging of the brain. First insights on this question have been gained from magnetic resonance imaging (MRI), but most analyses have not considered that depression is associated with other medical conditions and risk factors that influence aging. Another factor that influences brain aging through-out the life-span and needs consideration in such a study is early life adversity.

For this complex undertaking, the UK Biobank is an ideal platform as both psychometric and medical data along with MRI data are accessible. We will first study the association between age and brain anatomy and brain function in a large sample of healthy controls with no history of depression and no specific medical risk factors and disorders. As many data points altogether determine the aging status, we study this association by multivariate methods that consider hundreds to thousands of data values at the same time.

As a next step, we will use this model to predict the 'brain age' for a total of four clinical groups:

*            First, patients with a lifetime history of a major depression (and likely associated medical risk factors and disorders).

*            Second, patients with no depression but the same proportion of medical risk factors and disorders.

*            Both these groups will be subdivided into to subgroups according to the degree of early life adversity.

As the brain is organized in networks and as there is increasing insight that pathological aging such as Alzheimer's dementia affect specific networks more than others. One of the analysis principles of this study is therefore to study the brain's age at the network level, more specifically, calculating not one 'average' brain age but each one per network and per MRI technique. Here, we will use three MRI techniques: One focusing on the brain's macroscopic anatomy, one on its fiber connections ('wiring'), and one focusing on its (resting) functional status.

Last, we also address if the functional state of the brain during a depressive state bears similarity with 'advanced aging', that is, if the brain looks 'older' during a depression than it actually is biographically. Naturally, repeated measurements of patients with depression might be useful to understand if these 'advanced aging' pattern is reversible, similar as clinically most affective and cognitive problems pale off after a depressive episode.