Honours, Masters & Doctorate

Dissecting the genetic architecture of anxiety subtypes

PhD, Masters or Honours project. Seeking a motivated student, ideally with a background in psychology, genetics, epidemiology or statistics, to contribute to a dry-lab, analysis focused research project.

Caption

Project Supervisors

Brittany Mitchell

Dr Brittany Mitchell

Team Head

Dr Anna Monistrol Mula

Research Officer

Background

Anxiety disorders are common, multifaceted conditions that include subtypes such as generalized anxiety, social anxiety, and panic disorder. Research indicates that anxiety is moderately heritable, and genome wide association studies (GWAS) have identified several genetic variants associated with anxiety risk. However, emerging evidence suggests that different anxiety subtypes may be shaped by partly distinct genetic influences. Understanding the balance between shared and subtype specific genetic factors might explain why certain symptoms co occur, and how these differences might contribute to variation in treatment response.


Aim

This project will:

  1. Identify genetic factors that contribute differently to anxiety subtypes 9eg panic disorder vs generalised anxiety)
  2. Explore the relationship between anxiety subtypes, as well as their relationships with other traits.

Approach

Using large scale national and international genetic datasets, the project will apply advanced statistical genetics approaches, including GWAS, polygenic risk scoring (PRS), and genetic correlation analyses, to characterize the genetic architecture of anxiety subtypes. The student will investigate how genetic risk influences symptom patterns and potential links with treatment response.


Project Potential

This project will investigate the genetic underpinnings of anxiety subtypes to better understand why symptom patterns differ between individuals. Using large-scale genomic data and advanced quantitative methods, the research will examine biological pathways contributing to heterogeneity in anxiety disorders. The findings aim to support more refined, biologically informed models of classification and guide the development of targeted treatment strategies. Ultimately, the project seeks to improve outcomes for individuals who do not benefit from current standard therapies while providing rigorous training in complex trait genomics and statistical analysis.



Apply

Interested in applying?
Contact the supervisors below.