Artikel
Clinical characterization and transcriptome analysis of Systemic Lupus Erythematosus (SLE) patient subpopulations to identify common patterns and biomarkers in a dual approach
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Autoren
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Rasmus Schindehütte
- University Medical Center of the Johannes Gutenberg University, Department of Internal Medicine I, Division of Rheumatology and Clinical Immunology, Mainz
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Tamara Möckel
- University Medical Center of the Johannes Gutenberg University, Department of Internal Medicine I, Division of Rheumatology and Clinical Immunology, Mainz
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Sebastian Boegel
- University Medical Center of the Johannes Gutenberg University, Department of Internal Medicine I, Division of Rheumatology and Clinical Immunology, Mainz
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Andreas Schwarting
- University Medical Center of the Johannes Gutenberg University, Department of Internal Medicine I, Division of Rheumatology and Clinical Immunology, Mainz; Rheumatology Center Rhineland Palatine, Bad Kreuznach
| Veröffentlicht: | 30. August 2023 |
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Gliederung
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Introduction: Systemic Lupus Erythematosus (SLE) is a multisystem, chronic autoimmune disease. Clinical appearance and treatment requirements vary widely between patients and depending on disease activity. This heterogeneity demonstrates the circumstance that there is no one-size-fits-all method in the care and treatment of those affected and thus the need for a more individual management of patients affected by SLE. Furthermore, while parameters for ascertaining disease activity are well established, tools to predict the course of disease and which clinical manifestations will occur are non-existent.
Methods: Therefore, the research objective of this study is to examine the combined transcriptome analysis of whole blood samples of SLE patients (n=25) in the context of their clinical presentation. Patient’s medical reports were retrospectively compiled with special focus on course of the disease, disease activity, organ and tissue involvement. Finally, characteristic clinical appearance was linked to certain gene signatures in order to find common patterns within different SLE subpopulations.
Results: By analyzing the transcriptomic data, our study revealed two characteristic patterns in a subset of the SLE patients. While the greater expression of interferon induced proteins 27, 44 and 44 like (IFI27, IFI44, IFI44L) seemed to indicate increased disease activity, a pattern featuring predominantly IL1R2 (Interleukin 1 Receptor Type 2) and ACSL1 (Acyl-CoA Synthetase Long Chain Family Member 1) at the same time appeared to be indicative of an involvement of the kidneys and the hematological system. Moreover, patients displaying this pattern tended to have a lower disease activity in the time period around the day of blood sample collection.
Conclusion: In conclusion, our preliminary findings suggest the existence of small subpopulations within our cohort of SLE patients with similar clinical presentations and stereotypical gene patterns. Additionally, revealed signatures seem to be qualitative predictors of disease activity. By utilizing a validation cohort, the final objective is to replicate and confirm our findings.
