Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a variety of disease symptoms and an unpredictable clinical course. SLE can lead to premature death as the result of disease activity or because of treatment side effects. This underlines the urgency to identify patients at risk for a complicated disease course, and the need to tailor therapy. Stratification based on immunological manifestations such as autoantibodies, upregulation of type I interferon (IFN) regulated genes (IFN signature) and neutrophil extracellular trap (NET) formation via NETosis can help to improve treatment outcome in SLE.
Objectives
Here we study the association between SLE-related autoantibodies, the IFN signature and NET formation in patients with SLE, which could lead to improved tools for patient stratification and more targeted treatment options.
Methods
We studied the association between the IFN signature and plasma induced NET formation with 57 autoantibodies in 25 patients with SLE. The presence of an IFN signature was determined using the sum of standardized mRNA expression of IFI44L, IFITM1, SERPING1, and LY6E in monocytes from SLE patients. Plasma induced NET formation was studied with quantitative live imaging. The threshold for the presence of an IFN signature or NET formation were both set at 2 SD above the mean of a group of healthy controls. With principal component analysis (PCA) and hierarchical clustering we associated autoantibody concentrations with the IFN signature and NET formation. This study was a separate analysis from larger cohorts, of which results have been previously published.[1,2]
Results
We observed two distinct clusters with the PCA: one cluster contained mostly patients with an IFN signature, and another cluster contained a mix of patients with (IFN) and without (noIFN) an IFN signature. Patients with (NET) and without (noNET) plasma induced NET formation were equally distributed between the clusters. PC1 explains 22.7% of total variability, and is mainly driven by antibodies against histones, RibP2, RibP0, EphB2, RibP1, PCNA, dsDNA, and nucleosome. Hierarchical cluster analysis confirmed the two clusters (Figure 1). In addition, we found a trend towards increased concentrations of autoantibodies against EphB2, RibP1, and RNP70 in patients with an IFN signature. We found a negative correlation of NET formation with anti-FcER and anti-PmScl100.
Conclusion
We identified a subgroup of patients with an IFN signature who express increased concentrations of antibodies against DNA and RNA-associated proteins. We did not find positive associations between autoantibodies and plasma induced NET formation. Our study further strengthens the evidence of a correlation between RNA-binding autoantibodies and the IFN signature. As the IFN signature currently is not part of the standard follow-up for patients, partially due to its associated costs, a profile of DNA and RNA-binding autoantibodies might be used for patient stratification, especially related to anti-IFN treatment.
References
[1]Brunekreef, T., et al. (2021). "Microarray testing in patients with systemic lupus erythematosus identifies a high prevalence of CpG DNA-binding antibodies." Lupus Sci Med 8(1). [2]van der Linden, M., et al. (2018). "Neutrophil extracellular trap release is associated with antinuclear antibodies in systemic lupus erythematosus and anti-phospholipid syndrome." Rheumatology (Oxford) 57(7): 1228-1234.
Naive T cells in untreated HIV-1 infected individuals have a reduced T-cell receptor excision circle (TREC) content. Previous mathematical models have suggested that this is due to increased naive T-cell division. It remains unclear, however, how reduced naive TREC contents can be reconciled with a gradual loss of naive T cells in HIV-1 infection. We performed longitudinal analyses in humans before and after HIV-1 seroconversion, and used a mathematical model to investigate which processes could explain the observed changes in naive T-cell numbers and TRECs during untreated HIV-1 disease progression. Both CD4+ and CD8+ naive T-cell TREC contents declined biphasically, with a rapid loss during the first year and a much slower loss during the chronic phase of infection. While naive CD8+ T-cell numbers hardly changed during follow-up, naive CD4+ T-cell counts continually declined. We show that a fine balance between increased T-cell division and loss in the peripheral naive T-cell pool can explain the observed short- and long-term changes in TRECs and naive T-cell numbers, especially if T-cell turnover during the acute phase is more increased than during the chronic phase of infection. Loss of thymic output, on the other hand, does not help to explain the biphasic loss of TRECs in HIV infection. The observed longitudinal changes in TRECs and naive T-cell numbers in HIV-infected individuals are most likely explained by a tight balance between increased T-cell division and death, suggesting that these changes are intrinsically linked in HIV infection.
More than half of patients with Crohn's disease [CD] develop disease complications requiring aggressive medical therapy or surgery over time. However, predicting disease course and treatment response remains difficult. We therefore identified distinctive serum analytes associated with disease activity and course in newly diagnosed, untreated patients at presentation and during their follow-up.In a pilot study, a multiplex immunoassay analysis on 36 markers was performed on serum from 20 CD patients at the time of primary diagnosis following endoscopic evaluation. The 12 most potent markers associated with disease activity, phenotype and course were analysed in a consecutive cohort of 66 CD patients at diagnosis and follow-up [n = 39]. A healthy control group [n = 20] was included as a reference.CD patients had higher baseline levels of sTNF-R2 [p = 0.001], sIL-2R [p = 0.0001], and MMP-1 [p = 0.001] compared with healthy controls. Serial measurements revealed that these three analytes dropped statistically significantly from baseline level during remission and were high during exacerbation. Great decline of sTNF-R1 levels was found during remission, with 6.7-fold lower levels than in healthy controls [p = 0.015]. Patients who did not respond to initial prednisone treatment had higher baseline levels of sTNF-R2 [p = 0.001]. Patients experiencing relapses during follow-up had lower baseline sTNF-R2 and VCAM levels compared with patients with long-lasting remission.In a large cohort of newly diagnosed untreated CD patients, we identified candidate serum markers [sTNF-R1, sTNF-R2, sIL-2R, and MMP-1] associated with disease activity. Furthermore, sTNF-R2 was associated with prednisone response and, together with VCAM, with long-lasting remission.
File: Annexin-V+ CD4+ and CD8+ T cells. This SPSS file contains the percentage of Annexin-V+ CD4+ and CD8+ T cells at various time points during the MIRS trial. Please see the 'variable view' of the SPSS file and the 'methods' section of the paper for more information. We have used SAS software for our analyses.
File: Ki67+ CD4 and CD8 T cells. This SPSS file contains the percentage of Ki67+ CD4 and CD8 T cells at various time points during the MIRS trial. Please see the 'variable view' of the SPSS file and the 'methods' section of the paper for more information. We have used SAS software for our analyses.
File: Primary endpoint (absolute CD4 T cell count). This SPSS file contains the absolute number of CD4 T cells (primary endpoint) at various time points during the MIRS trial. Please see the 'variable view' of the SPSS file and the 'methods' section of the paper for more information. We have used SAS software for our analyses.
Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by a variety of disease symptoms and an unpredictable clinical course. To improve treatment outcome, stratification based on immunological manifestations commonly seen in patients with SLE such as autoantibodies, type I interferon (IFN) signature and neutrophil extracellular trap (NET) release may help. It is assumed that there is an association between these immunological phenomena, since NET release induces IFN production and IFN induces autoantibody formation via B-cell activation. Here we studied the association between autoantibodies, the IFN signature, NET release, and clinical manifestations in patients with SLE. We performed principal component analysis (PCA) and hierarchical clustering of 57 SLE-related autoantibodies in 25 patients with SLE. We correlated each autoantibody to the IFN signature and NET inducing capacity. We observed two distinct clusters: one cluster contained mostly patients with a high IFN signature. Patients in this cluster often present with cutaneous lupus, and have higher anti-dsDNA concentrations. Another cluster contained a mix of patients with a high and low IFN signature. Patients with high and low NET inducing capacity were equally distributed between the clusters. Variance between the clusters is mainly driven by antibodies against histones, RibP2, RibP0, EphB2, RibP1, PCNA, dsDNA, and nucleosome. In addition, we found a trend towards increased concentrations of autoantibodies against EphB2, RibP1, and RNP70 in patients with an IFN signature. We found a negative correlation of NET inducing capacity with anti-FcER (r = −0.530; p = 0.007) and anti-PmScl100 (r = −0.445; p = 0.03). We identified a subgroup of patients with an IFN signature that express increased concentrations of antibodies against DNA and RNA-binding proteins, which can be useful for further patient stratification and a more targeted therapy. We did not find positive associations between autoantibodies and NET inducing capacity. Our study further strengthens the evidence of a correlation between RNA-binding autoantibodies and the IFN signature.
