Associate Professor Brett Lidbury

B.Sc. (Hons) Ph.D. FFSc (RCPA)
Associate Professor - National Centre for Epidemiology and Public Health
ANU College of Health and Medicine
T: +61 (0)2 6125 7875

Areas of expertise

  • Medical Virology 110804
  • Biostatistics 010402
  • Infectious Diseases 110309
  • Pathology (Excl. Oral Pathology) 110316

Research interests

Previous laboratory-based interests in virology and pathogenesis have moved in silico, with the application of machine-learning/pattern-recognition techniques to support the study of human susceptibility or resistance to disease post viral infection (HBV; Post-viral Fatigue Syndrome - see below). Techniques include recursive partitioning (trees) and support vector machines (SVMs), as both classification and regression applications to biomedical data. This research theme has diversified into other aspects of quality in diagnostic pathology, supported by the Quality Use of Pathology Programme (QUPP - Commonwealth Department of Health), and in collaboration with the Royal College of Pathologists of Australasia Quality Assurance Programme (RCPAQAP), as well as public and private pathology laboratories.

Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) studies are ongoing with research participants recruited and assessed via clinical collaborators, and in collaboration with La Trobe University, Bio21 Institute (University of Melbourne) and Macquarie University. ME/CFS projects were funded by the Judith Jane Mason Foundation, Alison Hunter Memorial Foundation and ME Research UK. With Emerge Australia, a current programme is underway to develop Australia's first ME/CFS Biobank, again funded by the Mason Foundation.

Biography

I completed undergraduate and honours degrees at the University of Newcastle, followed by a Ph.D. at the ANU (JCSMR). Post-doctoral experience was gained in molecular virology and mucosal vaccine development, followed by a lecturing position (molecular biology, genetics, medical science) at the University of Canberra. Research during this period involved investigations of immuno-pathogenesis associated with Ross River virus (RRV) infection, with key findings published on the elucidation of the molecular basis of antibody-dependent enhancement (ADE - associated with several viruses, including dengue), models of muscle and bone pathology post-infection, and a model of long-term viral persistence in host cells.

Further research on virus-host interaction and pathogenesis was conducted while attached to the Department of Microbiology and Immunology at the University of North Carolina-Chapel Hill in the United States, supported by a NIH-R01 grant.

In the context of computational methods, recent fruitful international collaboration has been conducted with colleagues in the Department of Health Evidence, Radboudumc, Nijmegen (The Netherlands), particularly research concerning the development of machine learning supported systematic review to encourage non-animal methods for experimentation and testing.

In addition to the above, I have experience in diagnostic pathology and a period as a pre-clinical evaluator (toxicology) with the Therapeutic Goods Administration.

Researcher's projects

Current and ongoing projects are linked with the development of alternatives to animals in fundamental biomedical research. Through this approach there are two disease foci being explored utilising bioinformatics, genetic data and biological validation through human pathology testing. These projects are:

  1. Susceptibility or resistance to hepatitis B virus (HBV) infection and/or disease (this project has extended into liver disease generally and the role of routine LFTs in diagnosis), and enhanced laboratory diagnosis of anaemia - broadly in silico virology and pathology. This has extended into a population health framework, including a current doctoral student project on HBV in Nigeria;
  2. Discovery of key genetic and laboratory (pathology) markers of myalgic encephalomyelitis (ME, also known as "Chronic Fatigue Syndrome" - ME/CFS). The genetics phase has been completed and is due for publication in the near future. Also, pilot data from earlier studies have been analysed and informs a larger ongoing validation study on ME/CFS biomarker networks and immunology;
  3. Our group is also interested in conducting Systematic Review on biomedical topics of mutual interest.

Available student projects

There are data available from past and current ME/CFS projects that will benefit from student involvement. A background in medical science and experience in statistics and/or machine learning will be required. Other ME/CFS projects are available using sytematic review methods and meta-analysis.

From 2020 - 2025, Alice Richardson (SSN) and I are investigators on the National Biobank - Database consortium, funded by the J.J. Mason Foundation. Our role on the consortium is data analytics towards diagnostic marker development.

A project may also be available in the biological validation of bioinformatic models for HBV infection and disease, suitable for a medical science graduate with experience in laboratory diagnosis or pathology testing - involvement in this project will require specialised training and vaccination prior to commencement, due to contact with potentially infected human samples.

Innovation in human-centred biomedical research (also referred to as "NAMs" - New Approach Methodologies). For example, integration of machine learning with systematic review, both as an animal replacement alternative and as pre-experimentation scoping tool.

Current student projects

Current student projects involve the statistical and machine learning interrogation of pathology data linked with Hepatitis B Virus (HBV) infection and disease in Nigeria, to assist individual diagnosis and population monitoring.

Another student project is investigating biomarker patterns in aggregated ME/CFS results via machine learning.

Past student projects

Previous projects completed by doctoral students involved advanced statistics and machine learning to enhance routine pathology data prediction for cardiac disease and hepatitis B virus (HBV) infection (Chinese & Australian populations).

Graduate (MBBS) and undergraduate students have completed a range of projects applying combinations of machine learning, statistics and systematic review to infectious disease reseaarch. One successful study was published in the leading journal, Journal of Internal Medicine, which reported multiple regression models of retrospective ME/CFS orthostatic intolerance (standing test) data, identifying new physiological criteria and guidelines for the diagnosis of fatigue.

Others have interrogated cytokine patterns and mitochondrial function - clinical relationships for ME/CFS, as well as text analyses of clinical notes supporting HBV pathology requests.

All of the above projects also contributed to the development of alternative methods to help replace animal models of fundamental disease investigation.

Previous to this appointment, I have supervised students in Australia and the USA in areas pertaining to viral pathogeneis. In addition to the Post-Graduate and Graduate supervision stated above, I have also co-supervised a Masters student who studied the problem of missing values in pathology data sets.

Publications

Projects and Grants

Grants information is drawn from ARIES. To add or update Projects or Grants information please contact your College Research Office.

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Updated:  27 November 2022 / Responsible Officer:  Director (Research Services Division) / Page Contact:  Researchers