Poster Presentation Lorne Infection and Immunity 2023

Immune cell profiling of acute rheumatic fever (#166)

Francis M Middleton 1 2 , Reuben McGregor 1 2 , Ciara Ramiah 1 , Anna Brooks 2 3 , Julie Bennett 1 2 4 , Michael Serralha 5 , Tim Barnett 5 , Rachel Webb 1 2 6 , Anna Ralph 7 , Jonathan R Carapetis 5 , Nikki J Moreland 1 2
  1. Faculty of Medical and Health Sciences, The University of Auckland, Auckland, New Zealand
  2. Maurice Wilkins Centre, The University of Auckland, Auckland, New Zealand
  3. School of Biological Sciences, The University of Auckland, Auckland, New Zealand
  4. University of Otago, Auckland, New Zealand
  5. Telethon Kids Institute, University of Western Australia, Perth, Australia
  6. Kidz First Hospital, Counties Manukau Health District, Auckland, New Zealand
  7. Global and Tropical Health, Menzies School of Health Research, Darwin, Australia

Acute Rheumatic Fever (ARF) is a serious autoimmune sequela that develops after a Group A Streptococcus (GAS) infection and is a major cause of health inequity in underserved Indigenous populations in Australia and New Zealand. Repeated ARF can result in chronic rheumatic heart disease (RHD) with significant global morbidity and mortality, particularly in low- and middle-income countries. The pathogenesis of ARF is poorly understood, which has contributed to a lack of specific biomarkers and effective immunomodulating treatments for the disease.  Responding to these urgent needs, ‘Searching for a Technology-Driven Acute Rheumatic Fever Test’ (START) is a trans-Tasman study designed to identify a diagnostic signature for ARF by use of systems biology and serology technologies(1). We will present preliminary results of 33-colour spectral flow cytometry profiling using peripheral blood mononuclear cells from START study participants. This provide the broadest characterization of immune cell populations in an ARF cohort to date (n=116). Age and ethnicity matched control groups, including infectious and inflammatory conditions that may present similarly to ARF, chronic RHD, and healthy subjects, will be used for rigorous identification of unique ARF-associated immunological traits (n=120). Automated clustering algorithms will be used to quantify changes in cell populations and phenotypes. This will provide insight into the role of immune cells in ARF pathogenesis, and has the potential to identify new therapeutic targets for immunomodulating intervention.

  1. Ralph AP, Webb R, Moreland NJ, McGregor R, Bosco A, Broadhurst D, et al. Searching for a technology-driven acute rheumatic fever test: The START study protocol. BMJ open. 2021;11(9):e053720.