About
Bade Uckac is a PhD candidate in the Computational Neurogenomics Group at QIMR Berghofer Medical Research Institute. Her research focuses on the genetic architecture of chronic widespread pain and its psychiatric comorbidities, using advanced statistical genomics approaches including genetic structural equation modelling and polygenic risk prediction through large-scale genome-wide association studies. Her work spans from unraveling different chronic widespread pain topologies to investigating the genetics of treatment response, contributing to efforts in drug repurposing and precision medicine for chronic pain.
She holds a Bachelor’s degree in Biological Sciences from University of Westminster and previously gained experience in genetic epidemiology and statistical genomics through research collaborations involving the University of Cambridge and the MRC Epidemiology Unit. Her broader background includes biopolymer research, molecular and cell biology, bioinformatics, and computational approaches for investigating complex human diseases.
Research Skills
- Genetic structural equation modelling
- Mendelian randomization
- Polygenic risk scoring
- Pharmacogenomics
- Genome wide association studies
Area of Interest
- Genetic risk stratification for chronic pain and intensity.
- Chronic pain and pharmacogenomic treatment response.
- Translational genomics and personalised medicine for chronic widespread pain.
- Neuroimaging, central sensitisation and chronic widespread pain.
Research Projects
Current Research Projects
Genetic Risk Predicts Chronic Widespread Pain Profiles and Severity
Clinical Impact of CYP2C19/CYP2D6 on Amitriptyline Outcomes in Chronic Pain
Publications
Uckac B, Ogonowski NS, García-Marín LM, Diaz-Torres S, Farrell SF, Nyholt DR and Rentería ME (2026) Decoding chronic pain: integrating genetics, neuroimaging, and AI for precision management. Front. Pain Res. 7:1747942. doi: 10.3389/fpain.2026.1747942