Study level

  • Master of Philosophy
  • Honours


Topic status

We're looking for students to study this topic.


Professor Dale Nyholt
Division / Faculty
Faculty of Health

External supervisors

  • Dr Eske Derks, QIMR


Mental health disorders (e.g., depression, anxiety, substance use) are the leading cause of global disease burden in the young adult population. Twin and family studies show that both genetic and environmental factors play a large role in the aetiology of these disorders. The Translational Neurogenomics group aims to identify genetic risk factors for a range of mental health and substance use disorders, and investigate the interplay between genetic and environmental risk factors.

UK Biobank is a major national and international health resource with the aim of improving the prevention, diagnosis and treatment of a wide range of serious and life-threatening illnesses. UK Biobank recruited 500,000 people aged between 40-69 years in 2006-2010 from across the country to take part in this project. They have undergone measures, provided blood, urine and saliva samples for future analysis, detailed information about themselves and agreed to have their health followed. Over many years this will build into a powerful resource to help scientists discover why some people develop particular diseases and others do not. Extensive information on mental health has been collected in a subset of 150,000 individuals.

Substance use and substance use disorders (SUDs) are explained by a combination of genetic and environmental factors. Exposure to traumatic experiences, particularly in childhood, has been linked with both substance abuse and dependence. Is this link stronger in people with a genetic predisposition to SUDs? This project will investigate the interaction between genetic liability to substance use and traumatic experiences in the UK Biobank.

A network approach to psychopathology is an alternative way of conceptualising mental illness. A disorder is conceptualised as a system of interacting relationships between symptoms, rather than the set of symptoms resulting from a single latent factor (the disorder). This project will conduct a network analysis of substance use disorders (SUDs) using symptom-level data from the UK Biobank. Networks will be estimated for groups with a high vs. low genetic predisposition for substance use in order to determine whether genetic risk is associated with differences in psychopathological network structure

Approaches, skills and techniques

  • We are seeking a highly motivated student with a strong interest in statistics and quantitative studies.
  • No specific expertise or skills in statistics or programming is required as this will be taught during the project; this will be a suitable project for someone who is keen to learn this
  • The student will analyse large-scale genetic datasets


  • The student can select their own specific research data
  • The focus will be on improving the influence of genetic and environmental risk factors on mental health disease
  • The student will get access to large-scale data and it is likely that the results will be suitable for a scientific publication as a first author



Contact Professor Eske Derks at the  QIMR Berghofer Medical Research Institute for more information.

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