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05.01 Protein profiling in plasma reveals molecular subgroups in systemic lupus erythematosus
  1. Helena Idborg1,
  2. Arash Zandian2,*,
  3. Cecilia Hellström2,
  4. Cecilia Mattsson2,
  5. Claudia Fredolini2,
  6. Mathias Uhlén2,
  7. Jochen M Schwenk2,
  8. Burcu Ayoglu2,
  9. Maja Neiman2,
  10. Iva Gunnarsson1,
  11. Elisabet Svenungsson1,
  12. Per-Johan Jakobsson1,*,
  13. Peter Nilsson2,*
  1. 1Karolinska Institutet and Karolinska University Hospital, Rheumatology Unit, Stockholm, Sweden
  2. 2Affinity Proteomics, SciLifeLab, School of Biotechnology, KTH – Royal Institute of Technology, Stockholm, Sweden
  3. *corresponding authors

Abstract

Objective Systemic Lupus Erythematosus (SLE) is a heterogeneous systemic autoimmune disease that is currently lacking specific diagnostic biomarkers. The diversity within the patients might obstruct clinical trials and could reflect differences in underlying pathogenesis. Our objective was to identify protein profiles that could be used for diagnosis and to identify molecular subgroups within SLE for patient stratification subjected to different treatment.

Method In a cross-sectional study we performed protein profiling of 695 plasma samples from SLE patients and matched controls. This was achieved by utilising an antibody suspension bead array targeting 367 proteins. T-test and ROC analysis was performed to identify differences in the protein profiles between SLE and controls. Unsupervised K-means clustering was performed to identify data-driven SLE subgroups.

Results We report that the novel proteins MMP1, SELE, and S100A12 can distinguish between SLE patients and controls with an area under curve of 0.80 in a ROC analysis. In addition, 28 proteins were found to show differences (corrected p-value<0.05) between SLE patients and controls. By unsupervised clustering we identified an IRF5, NOS3 and CLDN8-driven subgroup, an ARID2 and SELE-driven subgroup and one subgroup characterised by low SLC22A2 levels.

Conclusion We have identified potential biomarkers of SLE that may be used to improve the diagnosis of SLE patients. Our suggested panel of biomarkers needs to be validated in an additional SLE cohort and also in relation to other systemic autoimmune diseases before it can be used as a diagnostic test. We have also identified subgroups characterised by different molecular patterns, indicating underlying pathogenic differences. These patient groups might benefit from different treatment strategies. Our work adds new information to today’s view of classifying the heterogeneous subgroups within SLE and the importance of personalised medicine.

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