Available
Project number:
2025_68
Start date:
October 2025
Project themes:
Main supervisor:
Professor of Psychiatric Genetics
Co-supervisor:
Moritz Herle
Additional Information:
Longitudinal familial kinship and genetic analyses in the Genetic Links to Anxiety and Depression and UK BioBank studies.
Exploring the Genetic Architecture of Depression through Family-Based Analyses and Rare Variants
This project aims to enhance our understanding of the genetic underpinnings of Major Depressive Disorder (MDD) and anxiety disorders by leveraging the combined power of the Genetic Links to Anxiety and Depression (GLAD) study and UK Biobank, two of the largest cohorts with homogenous, DSM-based lifetime depression and anxiety phenotyping. They have been merged and form a dataset of over 90,000 psychiatric disorder cases and over 400,000 controls, with more than 50,000 identified relative pairs.
The project will focus on constructing familial relationship (kinship) matrices, enabling family-aware genetic analyses. Understanding familial genetics is critical to dissecting how shared genetic and environmental factors contribute to MDD. In addition to standard genome-wide association studies (GWAS), this project will explore the contributions of rare genetic variants to MDD using UK Biobank’s rich sequencing and biomarker data. Longitudinal questionnaire and medical record data will also be used to study how genetic and familial factors influence the onset, progression, and treatment response of MDD.
This research will be conducted in collaboration with global cohorts, including the Australian Genetics of Depression Study (AGDS), BIObanks Netherlands Internet Collective (BIONIC), and Generation Scotland, as part of the Identical Depression Phenotyping Study consortium. The project offers comprehensive training in statistical genetics, polygenic risk scoring, and the integration of rare and common variants, aiming to improve predictive models and provide novel insights into the biology of depression.
This groundbreaking work will significantly advance the understanding of MDD by integrating family-based data, enhancing both genetic prediction models and therapeutic strategies for this widespread condition.
See https://pubmed.ncbi.nlm.nih.gov/31715324/ for more about the GLAD study, see https://pubmed.ncbi.nlm.nih.gov/31926635/ for an example genetic paper, see https://pubmed.ncbi.nlm.nih.gov/29955165/ for a review of the utility of family genetics
We are now accepting applications for 1 October 2025
How to apply
Candidates should possess or be expected to achieve a 1st or upper 2nd class degree in a relevant subject including the biosciences, computer science, mathematics, statistics, data science, chemistry, physics, and be enthusiastic about combining their expertise with other disciplines in the field of healthcare.
Important information for International Students:
It is the responsibility of the student to apply for their Student Visa. Please note that the EPSRC DRIVE-Health studentship does not cover the visa application fees or the Immigration Health Surcharge (IHS) required for access to the National Health Service. The IHS is mandatory for anyone entering the UK on a Student Visa and is currently £776 per year for each year of study. Further detail can be found under the International Students tab below.
Next Steps
- Applications submitted by the closing date of Thursday 6 February 2025 will be considered by the CDT. We will contact shortlisted applicants with information about this part of the recruitment process.
- Candidates will be invited to attend an interview. Interviews are projected to take place in April 2025.
- Project selection will be through a panel interview chaired by either Professor Richard Dobson and Professor Vasa Curcin (CDT Directors) followed by informal discussion with prospective supervisors.
- If you have any questions related to the specific project you are applying for, please contact the main supervisor of the project directly.
For any other questions about the recruitment process, please email us at