Gene signature fingerprints stratify SLE patients in groups with similar biological disease profiles: a multicentre longitudinal study

Author:

Wahadat M Javad12ORCID,Schonenberg-Meinema Dieneke3ORCID,van Helden-Meeuwsen Cornelia G1,van Tilburg Sander J1,Groot Noortje2ORCID,Schatorjé Ellen J H45,Hoppenreijs Esther P A H45,Hissink Muller Petra C E6,Brinkman Danielle M C6,Dvorak Denis7,Verkaaik Marleen2,van den Berg J Merlijn3,Bouchalova Kateřina7ORCID,Kamphuis Sylvia2ORCID,Versnel Marjan A1ORCID

Affiliation:

1. Department of Immunology, Erasmus MC

2. Department of Paediatric Rheumatology, Erasmus MC—Sophia Children’s hospital, University Medical Center Rotterdam , Rotterdam

3. Department of Pediatric Immunology, Rheumatology and Infectious diseases, Emma Children's Hospital, Amsterdam University Medical Centres, University of Amsterdam, Amsterdam

4. Department of Paediatric Rheumatology, Amalia Children’s Hospital, Radboudumc

5. Department of Paediatric Rheumatology, St. Maartenskliniek , Nijmegen

6. Department of Pediatrics, Division of Pediatric Rheumatology, Willem Alexander Children’s Hospital, Leiden University Medical Center , Leiden, The Netherlands

7. Paediatric Rheumatology, Department of Paediatrics, Faculty of Medicine and Dentistry, Palacky University Olomouc and University Hospital , Olomouc, Czech Republic

Abstract

Abstract Objectives Clinical phenotyping and predicting treatment responses in SLE patients is challenging. Extensive blood transcriptional profiling has identified various gene modules that are promising for stratification of SLE patients. We aimed to translate existing transcriptomic data into simpler gene signatures suitable for daily clinical practice. Methods Real-time PCR of multiple genes from the IFN M1.2, IFN M5.12, neutrophil (NPh) and plasma cell (PLC) modules, followed by a principle component analysis, was used to identify indicator genes per gene signature. Gene signatures were measured in longitudinal samples from two childhood-onset SLE cohorts (n = 101 and n = 34, respectively), and associations with clinical features were assessed. Disease activity was measured using Safety of Estrogen in Lupus National Assessment (SELENA)-SLEDAI. Cluster analysis subdivided patients into three mutually exclusive fingerprint-groups termed (1) all-signatures-low, (2) only IFN high (M1.2 and/or M5.12) and (3) high NPh and/or PLC. Results All gene signatures were significantly associated with disease activity in cross-sectionally collected samples. The PLC-signature showed the highest association with disease activity. Interestingly, in longitudinally collected samples, the PLC-signature was associated with disease activity and showed a decrease over time. When patients were divided into fingerprints, the highest disease activity was observed in the high NPh and/or PLC group. The lowest disease activity was observed in the all-signatures-low group. The same distribution was reproduced in samples from an independent SLE cohort. Conclusions The identified gene signatures were associated with disease activity and were indicated to be suitable tools for stratifying SLE patients into groups with similar activated immune pathways that may guide future treatment choices.

Funder

Sophia Children’s Hospital Fund

NVLE

Dutch Arthritis Society

Publisher

Oxford University Press (OUP)

Subject

Pharmacology (medical),Rheumatology

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