Associate Professor Brett Lidbury

B.Sc (Hons) (Newcastle) PhD (ANU) FFSc (RCPA)
Senior Fellow

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.

Research

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.

Publications

  • Ajuwon B, Richardson A, Roper K and Lidbury BA, 2023, 'Clinical Validity of a Machine Learning Decision Support System for Early Detection of Hepatitis B Virus: A Binational External Validation Study', Viruses, vol. 15, no. 8.
  • Ajuwon B, Richardson A, Roper K, Sheel M, Audu R, Salako, BL, Bojuwoye MO, Katibi IA and Lidbury BA, 2023, 'The development of a machine learning algorithm for early detection of viral hepatitis B infection in Nigerian patients', Scientific Reports, vol. 13.
  • Ajuwon B, Awotundun O, Richardson A, Roper K, Sheel M, Rahman N, Salako A and Lidbury BA, 2023, 'Machine learning prediction models for clinical management of blood-borne viral infections: a systematic review of current applications and future impact', International Journal of Medical Informatics, vol. 179.
  • Lazarevic, N, Smurthwaite, K, D'Este, C et al. 2023, 'Liver and cardiometabolic markers and conditions in a cross-sectional study of three Australian communities living with environmental per- and polyfluoroalkyl substances contamination', Environmental Research, vol. 226, p. 13.
  • Kavyani, B, Lidbury, B.A., Schloeffel, R et al. 2022, 'Could the kynurenine pathway be the key missing piece of Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) complex puzzle?', Cellular and Molecular Life Sciences, vol. 79, no. 8, p. 19.
  • St John, A, Morris, H, Richardson, A et al. 2021, 'Vitamin D testing: Impact of changes to testing guidelines on detection of patients at risk of vitamin D deficiency', Annals Of Clinical Biochemistry, vol. 58, no. 3, pp. 196-202.
  • Ajuwon B, Roper K, Richardson A and Lidbury BA, 2021, 'One Health Approach: A Data-Driven Priority for Mitigating Outbreaks of Emerging and Re-Emerging Zoonotic Infectious Diseases', Tropical Medicine and Infectious Disease, vol. 7, no. 4.
  • Ajuwon B, Yujuico I, Roper K, Richardson A, Sheel M and Lidbury BA, 2021, 'Hepatitis B virus infection in Nigeria: a systematic review and meta-analysis of data published between 2010 and 2019', BMC Infectious Diseases, vol. 21, no. 1.
  • Lidbury, B.A. 2021, 'Ross River Virus Immune Evasion Strategies and the Relevance to Post-viral Fatigue, and Myalgic Encephalomyelitis Onset', Frontiers in Medicine, vol. 8.
  • Lidbury, B.A., Koerbin, G, Richardson, A.M. et al. 2021, 'Gamma-Glutamyl Transferase (GGT) Is the Leading External Quality Assurance Predictor of ISO15189 Compliance for Pathology Laboratories', Diagnostics, vol. 11, no. 4.
  • Lidbury, BA & Fisher, P 2020, 'Biomedical Insights That Inform the Diagnosis of ME/CFS', Diagnostics, vol. 10, no. 2.
  • Missailidis, D, Annesley, S, Allan, C, Lidbury, BA, et al 2020, 'An isolated Complex V inefficiency and dysregulated mitochondrial function in immortalised lymphocytes from ME/CFS patients', International Journal of Molecular Sciences, vol. 21, no. 3.
  • Rivera, M, Mastronardi, C, Silva-Aldana, C, Lidbury, BA, et al 2019, 'Myalgic encephalomyelitis/chronic fatigue syndrome: A comprehensive review', Diagnostics, vol. 9, no. 3.
  • Lidbury, BA, Kita, B, Richardson, A et al 2019, 'Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning, and the Utility of Activin B for Defining Symptom Severity', Diagnostics, vol. 9, no. 79, pp. 1-21.
  • Arcos-Burgos, M, Velez, J, Martinez, A, Lidbury BA, et al 2019, 'ADGRL3 (LPHN3) variants predict substance use disorder', Translational Psychiatry, vol. 9, no. 42, pp. 15pp.
  • Brown, P, Tan, A, El-Esawi, M et al. 2019, 'Large expert-curated database for benchmarking document similarity detection in biomedical literature search', Database : the journal of biological databases and curation, vol. 2019.
  • France, M., Bain, S.F. & Lidbury, B.A. 2018, 'Australia and New Zealand', in Michael Balls, Robert Combes, Andrew Worth (ed.), The History of Alternative Test Methods in Toxicology, Academic Press, United Kingdom, pp. 71-76.
  • Lidbury, B.A. 2018, 'Predicting liver disease post hepatitis virus infection: In silico pathology and pattern recognition', E-Bio Medicine, vol. 35, pp. 10-11pp.
  • Richardson, A, Lewis, D, Kita, B et al 2018, 'Weighting of Orthostatic Intolerance Time Measurements with Standing Difficulty Score Stratifies ME/CFS Symptom Severity and Analyte Detection', Journal of Translational Medicine. 16:97
    https://doi.org/10.1186/s12967-018-1473-z
  • Lidbury, BA, Koerbin, G, Richardson, AM et al 2018, 'Integration of ISO15189 and external quality assurance data to assist the detection of poor laboratory performance in New South Wales', Pathology, vol. 50, no. 1, pp. D92.
  • Lidbury, B.A, Kita, B, Lewis, D et al 2017, 'Activin B is a novel biomarker for chronic fatigue syndrome/myalgic encephalomyelitis (CFS/ME) diagnosis: a cross sectional study', Journal of Translational Medicine, vol. 15, no. 1.
  • Lidbury, BA, Koerbin, G, Richardson, A et al 2017, 'Integration of ISO 15189 and external quality assurance data to assist the detection of poor laboratory performance in NSW, Australia', Journal of Laboratory and Precision Medicine, vol. 2, no. 97, pp. 1-15.
  • Richardson, A & Lidbury, B.A. 2017, 'Enhancement of hepatitis virus immunoassay outcome predictions in imbalanced routine pathology data by data balancing and feature selection before the application of support vector machines', BMC Medical Informatics and Decision Making, vol. 17, p. 121.
  • Herrero, L, Taylor, A, Roques, P et al 2016, 'Animal Models of Alphavirus-induced Inflammatory Disease', in Suresh Mahalingam, Lara Herrero and Belinda Herring (ed.), Alphaviruses: Current Biology, Caister Academic Press, United Kingdom, pp. 89-124.
  • Badrick, T, Richardson, A, Arnott, A, Lidbury, BA. 2016, 'The kinetics of haemoglobin and ferritin in longitudinal community patients with iron deficiency or hypoxia', Diagnosis, vol. 4, no. 1, pp. 7pp.
  • Lidbury, B.A. 2016, 'A New In Vitro Toxicology: Shifting from Cells to Serum by Exploiting Pathology Data and Machine Learning to Investigate Liver Toxicity', Applied In Vitro Toxicology, vol. 2, no. 4, pp. 217/222.
  • Richardson, A, Signor, B, Lidbury, B.A, Badrick, T. 2016, 'Clinical chemistry in higher dimensions: machine-learning and enhanced prediction from routine clinical chemistry data', Clinical Biochemistry.
  • Shang, G, Biggerstaff, B, Richardson, A, Lidbury,B.A. 2016, 'A simulation model to estimate the risk of transfusion-transmitted arboviral infection', Transfusion and Apheresis science, vol. online, pp. 1-7.
  • Badrick, T, Richardson, A, Lidbury, BA. 2016, 'Response to article: serum total bilirubin concentrations are inversely associated with total white blood cell counts in an adult population', Annals Of Clinical Biochemistry, vol. 53, no. 3, pp. 412-414.
  • Timoshanko, A, Marston, H & Lidbury, BA 2016, 'Australian Regulation of Animal Use in Science and Education: A Critical Appraisal', ILAR Journal, vol. 57, no. 3, pp. 324-332.
  • Badrick, T & Lidbury, B.A. 2015, Novel quantitative methods that enhance clinical decision support based on routine pathology testing. Report for The Quality Use of Pathology Programme, The Commonwealth Department of Health, Canberra Australia.
  • Langley, G, Austin, C, Balapure, A et al 2015, 'Lessons from toxicology: Developing a 21st-century paradigm for medical research', Environmental Health Perspectives, vol. 123, no. 11, pp. A268-A272.
  • Lidbury, B, Richardson, A, Badrick, T. 2015, 'Assessment of machine-learning techniques on large pathology data sets to address assay redundancy in routine liver function test profiles', Diagnosis, vol. 2, no. 1, pp. 41-51.
  • Taylor, A, Melton, J, Herrero, L et al 2016, 'Effects of an in-frame deletion of the 6k gene locus from the genome of Ross River virus', Journal of Virology, vol. 90, no. 8, pp. 4150-4159.
  • Badrick, T, Richardson, A, Arnott, A, Lidbury, BA. 2015, 'The early detection of anaemia and aetiology prediction through the modelling of red cell distribution width (RDW) in cross-sectional community patient data', Diagnosis, vol. 2, no. 3, pp. 171-179.
  • Lidbury, B.A & Mahalingam, S 2014, 'Dengue virus and host antibody: A dangerous balancing act', The Lancet Infectious Diseases, vol. 14, no. 9, pp. 783-784.
  • Chen, W, Foo, S, Rulli, N et al. 2014, 'Arthritogenic alphaviral infection perturbs osteoblast function and triggers pathologic bone loss', PNAS - Proceedings of the National Academy of Sciences of the United States of America, vol. 111, no. 16, pp. 6040-6045.
  • Reynolds, G, Lewis, D, Richardson, A, Lidbury B.A. 2014, 'Comorbidity of postural orthostatic tachycardia syndrome and chronic fatigue syndrome in an Australian cohort', Journal of Internal Medicine, vol. 275, no. 4, pp. 409-417.
  • Herrero, L, Lidbury, B.A, Bettadapura, J et al 2014, 'Characterization of Barmah Forest virus pathogenesis in a mouse model', Journal of General Virology, vol. 95, pp. 2146-2154.
  • Londono, A, Castellanos, F, Andres, A et al 2013, 'An 1H-MRS framework predicts the onset of Alzheimer's disease symptoms in PSEN1 mutation carriers', Alzheimer's & Dementia, vol. 2013, pp. 1-10.
  • Richardson, A.M. & Lidbury, B.A. 2013, 'Infection status outcome, machine learning method and virus type interact to affect the optimised prediction of hepatitis virus immunoassay results from routine pathology laboratory assays in unbalanced data', BMC Bioinformatics, vol. 14, no. 1, pp. -.
  • Shang, G, Easteal, S, Ohms, S et al 2013, 'Predicting the presence of hepatitis B virus surface antigen in Chinese patients by pathology data mining', Journal of Medical Virology, vol. 85, no. 8, pp. 1334-1339.
  • Leist, M, Lidbury, B, Yang, C et al 2012, 'Novel technologies and an overall strategy to allow hazard assessment and risk prediction of chemicals, cosmetics, and drugs with animal-free methods', Altex Alternativen zu Tierexperimenten, vol. 29, no. 4, pp. 373-388.
  • Lidbury, B & Townley, C 2012, 'Mousetraps and how to avoid them: the convergence of utilitarian and scientific cases for limiting the mouse model in biomedical research', Between the Species: an online journal for the study of philosophy and animals, vol. 15, no. 1, pp. 59-74.
  • Lidbury, B & Richardson, A 2012, 'A pattern recognition bioinformatics alternative system to rodent models in fundamental research', World Congress on Alternatives and Animal Use in the Life Sciences 2011, ed. Society ALTEX Edition, Kuesnacht, Switzerland, Spektrum Akademischer Verlag Springer-Verlag GmbH, Germany, pp. 515-520pp.
  • Johnston, J & Lidbury, B.A 2012, 'Testing times: A symposium on the ethics and epistemology of animal experimentation Sydney, Australia, September 20-21, 2011', Altex Alternativen zu Tierexperimenten, vol. 29, no. 1, pp. 96-97.
  • Lidbury, B.A., Rulli, N, Musso, C et al 2011, 'Identification and characterization of a Ross River virus variant that grows persistently in macrophages, shows altered disease kinetics in a mouse model, and exhibits resistance to type I interferon', Journal of Virology, vol. 85, no. 11, pp. 5651-5663.
  • Mahalingam, S, Meanger, J, Foster, P et al. 2002, 'The viral manipulation of the host cellular and immune environments to enhance propagation and survival: A focus on RNA viruses', Journal of Leukocyte Biology, vol. 72, no. 3, pp. 429-439.
  • Lidbury, B.A., Rulli, N, Musso, C et al 2011, 'Identification and characterization of a Ross River virus variant that grows persistently in macrophages, shows altered disease kinetics in a mouse model, and exhibits resistance to type I interferon', Journal of Virology, vol. 85, no. 11, pp. 5651-5663.
  • Ranmuthugala, G, Brown, L & Lidbury, B.A. 2011, 'Respiratory syncytial virus--the unrecognised cause of health and economic burden among young children in Australia.', Communicable Diseases Intelligence, vol. 35, no. 2, pp. 177-184.
  • Richardson, A, Shadabi, F & Lidbury, B.A. 2010, 'Learning from pathology databases to improve the laboratory diagnosis of infectious diseases.', First IMIA/IFIP Joint Symposium, E-Health 2010, Held as Part of WCC 2010, Proceedings, ed. Hiroshi Takeda, Springer, on line, pp. 226-227.
  • Lidbury, B.A., Rulli, N, Suhrbier, A et al 2008, 'Macrophage-derived proinflammatory factors contribute to the development of arthritis and myositis after infection with an arthrogenic alphavirus', Journal of Infectious Diseases, vol. 197, pp. 1585-1593.
  • Richardson, A, Hawkins, S, Shadabi, F et al 2008, 'Enhanced laboratory diagnosis of human Chlamydia pneumoniae through pattern recognition derived from pathology database analysis', International Conference on Pattern Recognition (ICPR 2008), ed. Conference Program Committee, IEEE Computer Society, Melbourne, Australia, pp. 227-232.
  • Lidbury, B.A. & Mahalingam, S 2008, Gene Profiles in Drug Design, CRC Press LLC, USA.
  • Lidbury, B.A., Musso, C, Johal, J et al 2007, 'RNA Viruses and RNA-Based Drugs: A Perfect Match for RNA Delivery and the Identification of Candidate Therapeutic Target Inflammatory Molecules', in Brett. A Lidbury and Suresh Mahalingam (ed.), Gene Profiles in Drug Design, CRC Press LLC, USA, pp. 115-130.
  • Brans, L & Lidbury, B.A. 2008, 'Ethical Considerations for a Genetic Future in Diagnosis and Drug Development', in Brett. A Lidbury and Suresh Mahalingam (ed.), Gene Profiles in Drug Design, CRC Press LLC, USA, pp. 131-141.
  • Shabman, R, Morrison, T, Moore, C et al 2007, 'Differential Induction of Type I Interferon Responses in Myeloid Dendritic Cells by Mosquito and Mammalian-Cell-Derived Alphaviruses', Journal of Virology, vol. 81, no. 1, pp. 237-247.
  • Morrison, T, Whitmore, A, Shabman, R et al 2006, 'Characterization of Ross River virus tropism and virus-induced inflammation in a mouse model of viral arthritis and myositis', Journal of Virology, vol. 80, no. 2, pp. 737-749.
  • Tupanceska D, Zaid A, Rulli N Lidbury BA, Matthaei KI, Ramirez R & Mahalingam S 2007, 'Ross River virus: an arthritogenic alphavirus of significant importance in the Asia-Pacific', in Sunil K. Lal (ed.), Emerging viral diseases of Southeast Asia, S Karger AG, Basel, New York. US, pp. 94-111.
  • Thomas, S, Redfern, J, Lidbury, B et al 2006, 'Antibody-dependent enhancement and vaccine development', Expert Review of Vaccines, vol. 5, no. 4, pp. 409-412.
  • Rulli, N, Suhrbier, A, Hueston, L et al 2005, 'Ross River virus: molecular and cellular aspects of disease pathogenesis', Pharmacology and Therapeutics, vol. 107, pp. 329-342.
  • Mahalingam S. and Lidbury B.A. (2003). Antibody-dependent enhancement of infection: Bacteria do it too. Trends in Immunology, 24: 465-467.
  • Mahalingam S. and Lidbury B.A. (2002). Suppression of lipopolysaccharide-induced antiviral transcription factor (STAT1 and NF-κB) complexes by antibody-dependent enhancement of macrophage infection by Ross River virus. Proceedings of the National Academy of Science, USA, 99:13819-13824.
  • Lidbury B.A. and Mahalingam S. (2000). The specific ablation of antiviral gene expression in macrophages by antibody-dependent enhancement of Ross River virus infection. Journal of Virology, 74: 8376-8381.
  • Way S.J.R., Lidbury B.A. and Banyer J.L. (2002). Persistent Ross River virus infection of murine macrophages: An in vitro model for the study of viral relapse and immune modulation during long-term infection. Virology, 301: 281-292.
  • Lidbury B.A., Simeonovic C., Maxwell G.E., Marshall I.D. and Hapel A.J. (2000). Macrophage-induced muscle pathology results in morbidity and mortality for Ross River virus infected mice. Journal of Infectious Disease, 181: 27-34.
  • Chaston T.B. and Lidbury B.A. (2001). Genetic 'budget' of viruses and the cost to the infected host: A theory on the relationship between the genetic capacity of viruses, immune evasion, persistence and disease. Immunology and Cell Biology, 79: 62-66.
  • Zhang F., Lidbury B.A., et al. 2012. Sustainable Language Support Practices in Science Education: Technologies and Solutions. IGI Global, Hershey, Pennsylvania, The United States.
  • Lidbury, B.A 2012, 'Language Focus for Genetics and Molecular Biology Students', in Felicia Zhang, Brett A. Lidbury (et al.), Sustainable language support practices in science education: Technologies and solutions, Information Science Reference, Hershey, Pennsylvania, USA.
  • Zhang, F & Lidbury, B.A 2012, 'Evaluating a Genetics Concept Inventory', in Felicia Zhang (ed.), Sustainable language support practices in science education: Technologies and solutions, Information Science Reference, Hershey, Pennsylvania, USA, pp. 116-128.
  • Mate, K, Rodger, J & Lidbury, B.A 2012, 'Language Support for First Year Human Physiology and Biology', in Felicia Zhang (ed.), Sustainable language support practices in science education: Technologies and solutions, Information Science Reference, Hershey, Pennsylvania, USA, pp. 129-159.
  • Zhang, F, Lidbury, B.A., Schulte, J et al 2010, 'Integrating Language Learning Practices in First Year Science Disciplines', The International Journal of Learning, vol. 17, pp. 481-502.
  • Zhang, F, Lidbury, B.A, Schulte, J et al 2009, 'Embedding in-discipline language support for first year students in the sciences: outcomes and future directions', National UniServe Science Conference 2009, ed. Conference Program Committee, UniServe Science, Sydney Australia, pp. 139-145.
  • Zhang, F, Lidbury, B.A, Schulte, J et al 2008, 'Language difficulties in first year Science - an interim report', UniServe Science Teaching and Learning Research Conference 2008, ed. Conference Program Committee, UniServe Science, Sydney Australia, pp. 159-164.
  • Richardson, A, Zhang, F & Lidbury, B.A 2008, 'Activating multiple senses in learning statistics', UniServe Science Teaching and Learning Research Conference 2008, ed. Conference Program Committee, UniServe Science, Sydney Australia, pp. 98-103.
  • Zhang, F & Lidbury, B.A 2006, 'It's all foreign to me: learning through the language of genetics and molecular biology', National UniServe Science Conference 2006, ed. Ian Johnston and Mary Peat, UniServe Science, Sydney Australia, pp. 153-159.

Teaching

ME Pathology in silico - There are data available from past and current projects that will benefit from student involvement. A background in medical science and experience in statistics and/or data mining will be required. Other ME projects are available using systematic review methods and meta-analyses. With the advent of COVID-19, research projects will aim to explore the pathogenesis of post-viral fatigue more broadly.

Infection and Immunity in silico: Hepatitis B virus - Biological validation of machine learning 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. Some experience in statistics and/or machine learning will be advantageous.

Genetics and Machine Learning - Through research collaborator Professor Mauricio Arcos-Burgos, future projects for students with an interest in human genetics will be available, primarily as in silico investigations on complex diseases like ME.

Supervisors (for students)

  • Brett Lidbury
  • Alice Richardson
  • Tony Badrick (Hon. Associate Professor)
  • Katrina Roper (Hon. Senior Lecturer)
  • Mauricio Arcos-Burgos (Colombia)