The majority of adults without a mental illness still experience poor mental health, indicating a need for a better understanding of what separates mental wellness from mental illness. One way of exploring what separates those with good mental health from those with poor mental health is to use electroencephalography (EEG) to explore differences in brain activity within the healthy population. Previous research has shown that EEG measures differ between clinical groups and healthy participants, suggesting that these measures are useful indicators of mental functioning.

Miranda Chilver’s current project aims to examine how different EEG measures relate to each other and to test if they can be used to predict mental wellbeing. Furthermore, she hopes to distinguish between EEG markers of symptoms including depression and anxiety, and markers of positive symptoms of wellbeing to better understand how wellbeing can exist independently of mental illness. This will be done by obtaining measures of wellbeing and depression and anxiety symptoms using the COMPAS-W and DASS-42 questionnaires, respectively.

Because EEG measures and mental wellbeing are both impacted by genetics as well as the environment, Miranda will also be testing whether the links found between EEG activity and Wellbeing are driven primarily by heritable or by environmental factors. This information will inform the development of future interventions that will aim to improve wellbeing in the general population.

To achieve these goals, the project will assess the relationship between EEG activity and wellbeing, and between EEG and depression and anxiety symptoms to first test whether there is an association between EEG and mental health. Second, the heritability of the EEG, wellbeing, depression, and anxiety will be assessed to determine the extent to which these variables are explained through heritable or environmental factors. Finally, a model assessing the overlap between the heritable versus environmental contributions to each measure will be developed to assess whether genetics or environment drive the relationship between EEG and mental health.

This project is based on a sample of over 400 healthy adult twins from the Australian TWIN-E study of resilience led by Dr Justine Gatt. This research will pave the way for improved mental health interventions based on individual needs.

Despite numerous research into the genetics of psychiatric disorders, investigations regarding the molecular genetics of wellbeing and resilience and in general healthy functioning using new technologies and methods are still scarce. There is very little known about the genetic factors influencing our wellbeing and resilience. Only a few recent genome wide association studies successfully detected a number of genetic variants influencing wellbeing. However, these variants are only responsible for a very small proportion of wellbeing heritability and much more are still waiting to be discovered.

My research area is focused on understanding the role of genetics and environment in mental wellbeing and resilience; in particular, the role of genetic and epigenetic factors and how they interact with each other and the environment in predicting mental health.

We have at our disposal an amazing population of 1600 twins with psychological data including mental health and wellbeing questionnaires, including personality questionnaires and a specific composite wellbeing questionnaire developed by the Gatt group called COMPAS-W.  These twins also underwent a genetic analysis using PsychArray and their genotyping data is available. In addition, a portion of these twins have EEG and neuroimaging data (MRI, fMRI, DTI), which will allow us to further investigate the effect of genetic markers on these variables and how they interact to yield the end phenotype.

We have three main questions to answer in this project:

First, do genetic variations influence wellbeing in our twin cohort? Which genes? How and to what extent?

Second, do genetic variations influence the neurobiological markers measured by EEG, MRI, fMRI and DTI in the twin population?

Third, is there any connection or correlation between the genetic markers which influence wellbeing and those which influence the neurobiological markers? How much of these phenotypes are genetically correlated?