Background: IFN signature is known to play an important role in the pathogenesis of systemic autoimmune diseases such as systemic lupus erythematosus (SLE). Recently, therapeutic agents targeting IFNs (JAK inhibitors, anifrolumab (ANI)) have been approved for the treatment of these diseases. ANI is a monoclonal antibody against subunit 1 of the type I IFNα receptor (IFNAR1) and was shown to be more effective in a subgroup of SLE patients with high IFN signatures in the TULIP study [1]. IFN signature is assessed by the combination of different mRNA expression levels induced by IFN. By determining the extent of the IFN signature, the pathological condition can be estimated and this allows the selection of the most appropriate treatment. However, assessing gene expression in routine clinical practice would be cost impractical.

Objectives: To develop a simplified method for estimating IFN signatures from routine clinical laboratory tests.

Methods: A total of 36 samples of peripheral blood from 21 SLE patients, untreated or after 6 months of treatment, were subjected to gene expression analysis by next-generation sequencing. The 73 genes were selected as Type-1, 94 genes as Type-2 and 10 genes as Type-3 IFN-related genes [2,3], and the IFN signature was evaluated by scoring the sum of the Z-Scores of each gene expression as the IFN score. Multiple regression analysis was performed to select the general clinical laboratory items predicting the IFN score the most among a total of 129 items from urinalysis, blood count, blood biochemistry and immunological tests.

Results: A tendency for a positive correlation between the respective IFN scores and neutrophil counts was observed, whereas a negative correlation was observed for lymphocyte counts. By calculating and applying the neutrophil/lymphocyte ratio (NLR), the strongest correlation was found between the Log ₂ NLR (Min.=-0.34, 1 ^st Qu.=1.64, Mean=1.79, 3 ^rd Qu.=2.56, Max.=4.83) and IFN scores for Type 1 IFN (R2=0.57, P=1.74e-07), Type 2 IFN (R2=0. 36, P=1.24e-04) and Type 3 IFN (R2=0.57, P=1.32e-07).

Conclusion: ANI has been reported to be more effective in subgroups of SLE patients with high IFN signatures. The Log ₂ NLR was strongly correlated not only with Type 1 IFN signature, but also with Type 2 and Type 3 IFN signatures. The NLR can be easily calculated in routine clinical practice and therefore provides a simple indicator for estimating the IFN signature, which could be very useful for clinical applications.

REFERENCES: [1] Vital EM, et al. Anifrolumab efficacy and safety by type I interferon gene signature and clinical subgroups in patients with SLE: post hoc analysis of pooled data from two phase III trials. Annals of the rheumatic diseases 2022; 81(7): 951-61.

[2] Milacic M et al. The Reactome Pathway Knowledgebase 2024. Nucleic Acids Res 2024; 52(D1): D672-D8.

[3] Pico AR et al. WikiPathways: pathway editing for the people. PLoS Biol 2008; 6(7): e184.

Acknowledgements: NIL.

Disclosure of Interests: Yoshinobu Koyama Abbvie, Asahikasei, Ayumi, BMS, Esai, Eli-Lilly, Mitsubishi Tanabe, Taisho, Abbvie, AstraZeneca, Biogen Japan, Novartis, Yoshiharu Sato: None declared, Yu Nakai: None declared, Moe Tokunaga: None declared.