Overview
Background
I am a computational biologist specialising in the integration of multi-omics data to study rheumatoid arthritis (RA). My research combines clinical data, serum proteomics, single-cell transcriptomics, and spatial transcriptomics to understand disease progression, patient trajectories, and flare events.
I am particularly interested in the immune landscape of synovial tissue and how spatial organisation of immune and stromal cells contributes to inflammation and remission. Through advanced statistical modelling and machine learning, including clustering and trajectory inference, I aim to identify predictors of flare and uncover mechanisms that drive differences in patient outcomes.
Alongside my work in RA, I also investigate the link between systemic inflammation and cardiovascular disease, applying spatial, single-cell transcriptomics, proteomics and bioinformatics approaches to explore how chronic inflammation contributes to cardiac dysfunction.
The overarching goal of my research is to improve early prediction of disease trajectories, support personalised management strategies, and contribute to the development of targeted therapies for patients with RA.
Availability
- Dr Wittaya Suwakulsiri is:
- Available for supervision
Fields of research
Qualifications
- Doctor of Philosophy, La Trobe University
Research interests
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Multi-omics and Machine Learning for RA Flare Prediction and RA Patient Clustering Analysis
I integrate clinical data, serum proteomics, single-cell transcriptomics, and spatial transcriptomics to study rheumatoid arthritis. Using statistical modelling and machine learning approaches, including Louvain clustering, I analyse patient trajectories and identify predictors of flare. This work aims to improve understanding of disease progression and support personalised management strategies.
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Synovial tissue immune architecture using Spatial Transcriptomics
I analyse spatial transcriptomics of synovial tissues from a large cohort of rheumatoid arthritis patients. My aim is to characterise the immune landscape of synovial tissue and identify spatial patterns that may help explain disease progression and flare events. This work contributes to understanding rheumatoid arthritis at a tissue level and supports the development of targeted therapies.
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Inflammation-Driven Cardiovascular Disease in Rheumatoid Arthritis
I investigate the link between rheumatoid arthritis and cardiovascular disease by integrating cytokine profiling, proteomics, and bioinformatics. Using NULISAseq and other high-sensitivity proteomic platforms, I study how chronic inflammation contributes to cardiac dysfunction in RA. The goal is to identify biomarkers and molecular pathways that explain heightened cardiovascular risk in RA patients and support early detection and prevention strategies.
Research impacts
Rheumatoid arthritis (RA) is a chronic autoimmune disease with unpredictable flare events and highly variable patient outcomes. Current treatment strategies often rely on trial-and-error approaches, which can delay effective management and increase healthcare costs.
My research focuses on using advanced multi-omics approaches, including serum proteomics, single-cell transcriptomics, and spatial transcriptomics to better understand RA disease progression and flare events. By integrating these datasets with clinical information and applying statistical and machine learning methods, I aim to identify biomarkers that predict when patients are likely to flare and to cluster patients into distinct disease trajectories.
The impact of this work lies in its potential to transform RA management. Early identification of flare predictors and patient subgroups will allow clinicians to make more precise treatment decisions, reduce unnecessary treatments, and minimise long-term joint damage. In the long term, this research will contribute to more personalised care pathways, improved patient outcomes, and reduced burden on healthcare systems.
Works
Search Professor Wittaya Suwakulsiri’s works on UQ eSpace
2026
Journal Article
Oncogenic H-Ras reprograms Madin-Darby canine kidney (MDCK) cell-derived midbody remnant proteome following epithelial-mesenchymal transition
Shafiq, Adnan, Rai, Alin, Xu, Rong, Chen, Maoshan, Suwakulsiri, Wittaya, Greening, David W. and Simpson, Richard J. (2025). Oncogenic H-Ras Reprograms Madin-Darby Canine Kidney (MDCK) Cell-Derived Midbody Remnant Proteome Following Epithelial-Mesenchymal Transition. Proteomics, 26 (2-3) e70051, e70051-94. doi: 10.1002/pmic.70051
2025
Journal Article
Clinical relevance of extracellular vesicles in cancer - therapeutic and diagnostic potential
Greening, David W., Xu, Rong, Rai, Alin, Suwakulsiri, Wittaya, Chen, Maoshan and Simpson, Richard J. (2025). Clinical relevance of extracellular vesicles in cancer - therapeutic and diagnostic potential. Nature Reviews Clinical Oncology, 22 (12), 924-952. doi: 10.1038/s41571-025-01074-2
2025
Conference Publication
Expansion of viral-reactive CD8+T cell repertoire stratified by pathotype in new-onset ACPA plus rheumatoid arthritis
Coyle, Carl, Suwakulsiri, Wittaya, Andriessen, Lukas, Soon, Megan, Wehr, Pascale, Qureshi, Sumera, Altmann, Christopher, Small, Annabelle, Wong, Vincent, Cope, Andrew, Wei, Kevin, Nel, Hendrik, Wechalekar, Mihir and Thomas, Ranjeny (2025). Expansion of Viral-Reactive CD8+T cell Repertoire Stratified by Pathotype in New-onset ACPA plus Rheumatoid Arthritis. HOBOKEN: WILEY.
2025
Conference Publication
Spatial profiling of gene signatures in synovial tissue informs treatment strategy for rheumatoid arthritis
Wong, Vincent, Lowe, Katie, Small, Annabelle, Altmann, Christopher, Proudman, Susanna, Smith, Malcolm, Suwakulsiri, Wittaya, Thomas, Ranjeny, Kok, Chung Hoow and Wechalekar, Mihir (2025). Spatial profiling of gene signatures in synovial tissue informs treatment strategy for Rheumatoid Arthritis. HOBOKEN: WILEY.
2025
Conference Publication
Predicting rheumatoid arthritis flare using longitudinal cytokine trajectories, machine learning and spatial transcriptomic imaging
Suwakulsiri, Wittaya, Andriessen, Lukas, Fournier, Coline, Kodikara, Saritha, Anderson, Amy, Sim, Jasmine, Le Cao, Kim-Anh, Abraham, Yann, Wei, Kevin, Baker, Kenneth, Pratt, Arthur, Wechalekar, Mihir, Isaacs, John and Thomas, Ranjeny (2025). Predicting Rheumatoid Arthritis Flare Using Longitudinal Cytokine Trajectories, Machine Learning and Spatial Transcriptomic Imaging. HOBOKEN: WILEY.
2024
Journal Article
Transcriptomic analysis and fusion gene identifications of midbody remnants released from colorectal cancer cells reveals they are molecularly distinct from exosomes and microparticles
Suwakulsiri, Wittaya, Xu, Rong, Rai, Alin, Chen, Maoshan, Shafiq, Adnan, Greening, David W. and Simpson, Richard J. (2024). Transcriptomic analysis and fusion gene identifications of midbody remnants released from colorectal cancer cells reveals they are molecularly distinct from exosomes and microparticles. Proteomics, 24 (11) 2300058, 1-17. doi: 10.1002/pmic.202300058
2019
Journal Article
Distinct shed microvesicle and exosome microRNA signatures reveal diagnostic markers for colorectal cancer
Chen, Maoshan, Xu, Rong, Rai, Alin, Suwakulsiri, Wittaya, Izumikawa, Keiichi, Ishikawa, Hideaki, Greening, David W, Takahashi, Nobuhiro and Simpson, Richard J (2019). Distinct shed microvesicle and exosome microRNA signatures reveal diagnostic markers for colorectal cancer. PloS one, 14 (1), e0210003. doi: 10.1371/journal.pone.0210003
Funding
Current funding
Supervision
Availability
- Dr Wittaya Suwakulsiri is:
- Available for supervision
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Supervision history
Current supervision
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Master Philosophy
Rheumatoid arthritis synovial tissue and remission
Associate Advisor
Other advisors: Professor Ranjeny Thomas
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Doctor Philosophy
Spatially Resolved Multi-omic Profiling to Characterize Complex Immune Microenvironments in Acute and Chronic Inflammation
Associate Advisor
Other advisors: Professor Ranjeny Thomas
Media
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