Personal Profile

Dr. Zhixiu Li, Associate Professor/Investigator and PhD Supervisor, School of Public Health and Emergency Management. My primary research focuses on the pathogenesis, early diagnosis, and precision intervention of immune-related complex and rare diseases, as well as the development of vaccines against major infectious diseases. She has published more than 40 papers in journals such as Nature Genetics, Annals of the Rheumatic Diseases, Nature Reviews Rheumatology, and Annual Review of Biophysics. She serves as a grant reviewer for foundations in the United Kingdom, France, Australia, and New Zealand, Guest Editor for Frontiers in Immunology, and a reviewer for SCI journals including Nature Genetics, Nature Communications, Arthritis & Rheumatology, and JAMA Network Open. She has been invited to deliver plenary and oral presentations at international conferences such as the American College of Rheumatology (ACR) Annual Meeting and the Asia Pacific League of Associations for Rheumatology (APLAR) Congress, and received the APLAR Best Abstract Award in 2019. She is a member of the International Genetics of Ankylosing Spondylitis (IGAS) consortium.
The laboratory is continuously recruiting post-doctoral fellows, PhD students, master’s students, research assistants (RAs), and visiting undergraduate/graduate students. Interested candidates are warmly invited to submit their CV by email.

Research Interest

1. Pathogenesis of immune-related complex and rare diseases

2. Early diagnosis, precision intervention, and management of ankylosing spondylitis and related method development

3. Precision vaccine design against major infectious diseases and viruses

Work Experience
Dec 2023 – Present Southern University of Science and Technology, School of Public Health and Emergency Management, Associate Professor
Jun 2023 – Dec 2023 Southern University of Science and Technology, School of Public Health and Emergency Management, Assistant Professor
2018 – 2022 Queensland University of Technology, Vice-Chancellor Research Fellow
2016 – 2018 Queensland University of Technology, Postdoctoral Fellow
2014 – 2016 The University of Queensland, Postdoctoral Fellow

Education
2009 – 2015 Indiana University, School of Informatics, Ph.D.
2005 – 2009 University of Science and Technology of China, School of Life Sciences, B.S.

Representative Publications (# equal contribution, * corresponding author)

1. Li, Z., McRae, A. F., Wang, G., et al. Genotype by sex interactions in ankylosing spondylitis. Nat. Genet. 55, 14–16 (2023).

2. Li, Z., Khan, M. K., Linden, S. M. van der, et al. HLA-B27, axial spondyloarthritis and survival. Ann. Rheum. Dis. (2023) doi:10.1136/ard-2023-224434.

3. Li, Z., Linden, S. M. van der, Khan, M. A., et al. Heterogeneity of axial spondyloarthritis: genetics, sex and structural damage matter. RMD Open 8, e002302 (2022).

4. Williams, C. J#., Li, Z.#, Harvey, N#., et al. Genome wide association study of response to interval and continuous exercise training: the Predict-HIIT study. J. Biomed. Sci. 28, 37 (2021).

5. Li, Z., Wu, X., Leo, P. J., et al. Polygenic Risk Scores have high diagnostic capacity in ankylosing spondylitis. Ann. Rheum. Dis. 80, 1168–1174 (2021).

6. Wang, G., Kim, T.-H., Li, Z.#, et al. MHC associations of ankylosing spondylitis in East Asians are complex and involve non-HLA-B27 HLA contributions. Arthritis Res. Ther. 22, 74 (2020).

7. Li, Z., Akar, S., Yarkan, H., et al. Genome-wide association study in Turkish and Iranian populations identify rare familial Mediterranean fever gene (MEFV) polymorphisms associated with ankylosing spondylitis. PLOS Genet. 15, e1008038 (2019).

8. Li, Z. & Brown, M. A. Progress of genome-wide association studies of ankylosing spondylitis. Clin. Transl. Immunol. 6, e163 (2017).

9. Li, Z., Haynes, K., Pennisi, D. J., et al. Epigenetic and gene expression analysis of ankylosing spondylitis-associated loci implicate immune cells and the gut in the disease pathogenesis. Genes Immun. 18, 135–143 (2017).

10. Li, Z., Yang, Y., Faraggi, E., Zhan, J. & Zhou, Y. Direct prediction of profiles of sequences compatible with a protein structure by neural networks with fragment-based local and energy-based nonlocal profiles. Proteins Struct. Funct. Bioinforma. 82, 2565–2573 (2014).

11. Li, Z., Yang, Y., Zhan, J., Dai, L. & Zhou, Y. Energy Functions in De Novo Protein Design: Current Challenges and Future Prospects. Annu. Rev. Biophys. 42, 315–335 (2013).