Developing non-invasive methods to monitor kidney transplant rejection

Developing non-invasive methods to monitor kidney transplant rejection

Project details

Sub-clinical inflammation and immune responses result in the failure of 15 to 20 per cent of all kidney transplants. Kidney punch biopsies of all patients are currently used to monitor kidney injury and transplant rejection, as there are currently no reliable non-invasive markers of this. Monitoring kidney status through studying urine has the potential to be a less invasive approach.

This project will involve developing and performing a high-resolution quantitative mass spectrometry analysis on serially collected urine samples from a growing cohort of kidney transplant recipients, with the co-supervision of kidney transplant surgeon Dr Peter Hughes. 

This project will involve implementing sample preparation, mass spectrometry and data analysis strategies in order to identify disease-specific signatures that predict renal transplant rejection


About our research group

Our research group uses high-resolution mass spectrometry and quantitative proteomics techniques to address important biological questions relevant to human health. Recently, we have begun implementing machine-learning algorithms into the various stages of our analysis with spectacular success. In particular, we are interested in developing the tools to detect novel diagnostic and prognostic markers we have compared disease-affected individuals with healthy controls and those with alternative diagnoses. 

Our laboratory regularly collaborates with clinician scientists and operates and the interface of disease discovery and clinical diagnosis. Our laboratory consists of two post-doctoral scientists, two senior post-doctoral scientists (bioinformaticians) and two PhD students. 





Dr Andrew Webb

Dr Andrew Webb in the lab
Acting Division Head
Dr Peter Hughes profile photo
Royal Melbourne Hospital Renal Transplant Unit
Dr Laura Dagley in the lab
Systems Biology and Personalised Medicine division

Project Type: