Faculty Bibliography

Background/Purpose: Identifying populations at risk of SLE is essential to curtail inflammatory damage and identify individuals for prevention trials. Unaffected blood relatives (BRs) of lupus patients have increased risk of SLE. Some BRs have autoantibodies (AutoAbs) or SLE clinical features, but do not progress, some progress, but do not meet the required >= 4 ACR classification criteria (incomplete lupus, ILE), while others progress to classified SLE. The goal of this study is to determine factors that distinguish previously healthy BRs who remain stable or subsequently progress to ILE or SLE.
Method(s): This is a nested study of re-enrolled BRs of SLE patients (n=436) who previously enrolled in a genetics study (mean time to follow-up = 6.3 yrs) and did not meet SLE classification at baseline (BL). Of the 177 (41%) and 259 (59%) who did/did not meet additional ACR criteria at follow-up (FU) in this cohort, we compared the 56 BRs who transitioned to SLE (>=4 ACR criteria) to 34 BRs who met 3 ACR criteria (ILE) at FU and 154 race/sex/age (+/- 5 years) matched BRs with < 3 ACR criteria at FU. BRs provided clinical and demographic information, and completed the SLE-specific portion of the CTD Screening Questionnaire (CSQ) at BL and FU. Medical records were reviewed for ACR classification criteria. BL and FU plasma samples were assessed for autoantibody production (ANA, anti-dsDNA, aCL, Ro, La, Sm, nRNP, and ribosomal p antibodies) and for 52 soluble inflammatory and regulatory mediators by xMAP and ELISA assay.
Result(s): 133/244 (55%) of BRs evaluated in this nested cohort did not have any change in ACR criteria between BL and FU (Fig. 1, red circles, Nonprogressors [NP]), while the remaining 111 BRs accrued >=1 classification criteria (Fig. 1, black circles, Progressors). There was no difference in time to FU between NP and Progressor BRs. No significant differences were seen in ACR criteria, either at BL or FU, between BRs with ILE at BL who were NP vs. those who progressed to SLE at FU. Yet, a number of differences were seen at BL in BRs meeting 2 ACR criteria at BL who were NP vs. those who progressed to ILE or SLE at FU. NP BRs with BL ACR Score = 2 were more likely to meet immunologic criteria (p< 0.0001), while those BRs with ACR score <= 2 who progressed to ILE or SLE were more likely to meet clinical criteria at BL, particularly malar rash (p=0.0126) or arthritis (p=0.0054). In addition, these same NP had significantly lower SLE-CSQ scores and features at BL (Fig. 2A), with lower plasma levels of IL-2Ralpha and lower ANA titers. At FU, ACR Score = 2 NP had lower levels of BLyS and accumulated fewer AutoAbs (Fig. 2B). At both BL and FU, levels of the regulatory mediator Native TGF-beta were significantly higher in ACR Score = 2 NP (Fig. 2B). For those BRs with ILE at BL, those who progressed to SLE at FU had higher BL levels of SCF, MCP-3, and more AutoAb specificities than BL ILE NP BRs, with no difference in levels of Native TGF-beta (Fig. 2C).
Conclusion(s): BRs of known SLE patients who progress to ILE or SLE compared to BRs who remain stable are more likely to have elevated inflammatory mediators, reduced regulatory mediators, and meet as few as one clinical ACR classification criterion. This suggests that ANA or serologic positivity alone is not predictive of progression to ILE or SLE in lupus relatives

INTRODUCTION/BACKGROUND:Systemic lupus erythematosus (SLE) is a severe chronic and incurable autoimmune disease. Treatment includes glucocorticoids and small molecule immunosuppressants which typically result in partial responses, and hence there is a great need for new therapies. The type I interferon (IFN) pathway is activated in more than 50% of SLE patients, and it is strongly implicated as a pathogenic factor in SLE. A number of therapeutics have been developed to target type I IFN in SLE. AREAS COVERED/UNASSIGNED:We searched the literature using "SLE and interferon antagonists" as search terms. This identified a number of therapeutics that have entered clinical development targeting type I IFN in SLE. These include monoclonal antibodies against type I IFN cytokines and a kinoid vaccination strategy to induce anti-IFN antibodies. We discuss these in our article. EXPERT OPINION/UNASSIGNED:Type I IFN antagonists have had some success, but many molecules have not progressed to phase III. These varied results are likely attributed to the multiple concurrent cytokine abnormalities present in SLE, the imprecise nature of the IFN signature as a readout for type I IFN and difficulties with clinical trials such as background medication use and diffuse composite disease activity measures. Despite these challenges, it seems likely that a type I IFN antagonist will come to clinical utility for SLE given the large unmet need and the recent phase III success with anifrolumab.

OBJECTIVE:To assess the familial occurrence of systemic lupus erythematosus (SLE) in a large Brazilian cohort. METHODS:Consecutive SLE patients were recruited, and stratified according to age at disease-onset into childhood (cSLE) or adult (aSLE). Each patient was personally interviewed regarding history of SLE across three generations (first-, second-, and third-degree relatives). Recurrence rates were analyzed for each degree of relation. RESULTS:for differences in recurrence proportions between cSLE and aSLE). There were no phenotypic differences in patients from multi-case vs. single case families, and there was no sex-skewing observed in the offspring of SLE patients. CONCLUSION/CONCLUSIONS:The greater decline in SLE recurrence rate by generation in cSLE vs. aSLE suggests a more polygenic and epistatic inheritance and that aSLE may be characterized by fewer risk factors that are individually stronger. This suggests a higher genetic load in cSLE vs. aSLE, and difference in the genetic architecture of the disease based on age at onset. This article is protected by copyright. All rights reserved.

OBJECTIVE:Published predictive models of disease outcomes in idiopathic inflammatory myopathies (IIMs) are sparse and of limited accuracy due to disease heterogeneity. Computational methods may address this heterogeneity by partitioning patients based on clinical and biological phenotype. METHODS:tests to link new patient groups with the myositis subtypes. RESULTS:SNF identified five patient groups in the discovery cohort that subdivided the myositis subtypes. The sparse multinomial regressor to predict patient group assignments (areas under the receiver operating characteristic curve = [0.78, 0.97]; areas under the precision-recall curve = [0.55, 0.96]) found that autoantibody enrichment defined four of these groups: anti-Mi-2, anti-signal recognition peptide (SRP), anti-nuclear matrix protein 2 (NXP2), and anti-synthetase (Syn). Depletion of immunoglobulin M (IgM) defined the fifth group. Each group was associated with one subtype, with adult DM being associated with anti-Mi-2 and anti-Syn autoantibodies, JDM being associated with anti-NXP2 autoantibodies, and adult PM being associated with IgM depletion and anti-SRP autoantibodies. These associations enabled us to further resolve the current myositis subtypes. CONCLUSION/CONCLUSIONS:Using unsupervised machine learning, we identified clinically and biologically homogeneous groups of patients with IIMs, forming the basis of an integrated disease classification based on both clinical and biological phenotype, thus validating other approaches and what has been previously described.

TLR7 and TLR8 are pattern recognition receptors that reside in the endosome and are activated by ssRNA molecules. TLR7 and TLR8 are normally part of the antiviral defense response, but they have also been implicated as drivers of autoimmune diseases such as lupus. The receptors have slightly different ligand-binding specificities and cellular expression patterns that suggest they have nonredundant specialized roles. How the roles of TLR7 and TLR8 differ may be determined by which cell types express each TLR and how the cells respond to activation of each receptor. To provide a better understanding of the effects of TLR7/8 activation, we have characterized changes induced by TLR-specific agonists in different human immune cell types and defined which responses are a direct consequence of TLR7 or TLR8 activation and which are secondary responses driven by type I IFN or cytokines produced subsequent to the primary response. Using cell sorting, gene expression analysis, and intracellular cytokine staining, we have found that the IFN regulatory factor (IRF) and NF-κB pathways are differentially activated downstream of the TLRs in various cell types. Studies with an anti-IFNAR Ab in human cells and lupus mice showed that inhibiting IFN activity can block secondary IFN-induced gene expression changes downstream of TLR7/8 activation, but not NF-κB-regulated genes induced directly by TLR7/8 activation at earlier timepoints. In summary, these results elucidate the different roles TLR7 and TLR8 play in immunity and inform strategies for potential treatment of autoimmune diseases driven by TLR7/8 activation.

Systemic lupus erythematosus (SLE) and rheumatoid arthritis (RA) are two common autoimmune rheumatic diseases that vary in severity, clinical presentation, and disease course between individuals. Molecular and genetic studies of both diseases have identified candidate genes and molecular pathways that are linked to various disease outcomes and treatment responses. Currently, patients can be grouped into molecular subsets in each disease, and these molecular categories should enable precision medicine approaches to be applied in rheumatic diseases. In this article, we will review key lessons learned about disease heterogeneity and molecular characterization in rheumatology, which we hope will lead to personalized therapeutic strategies.

Previously, we demonstrated in test and validation cohorts that type I IFN (T1IFN) activity can predict non-response to tumor necrosis factor inhibitors (TNFi) in rheumatoid arthritis (RA). In this study, we examine the biology of non-classical and classical monocytes from RA patients defined by their pre-biologic treatment T1IFN activity. We compared single cell gene expression in purified classical (CL, n = 342) and non-classical (NC, n = 359) monocytes. In our previous work, RA patients who had either high IFNβ/α activity (>1.3) or undetectable T1IFN were likely to have EULAR non-response to TNFi. In this study comparisons were made among patients grouped according to their pre-biologic treatment T1IFN activity as clinically relevant: "T1IFN undetectable (T1IFN ND) or IFNβ/α >1.3" (n = 9) and "T1IFN detectable but IFNβ/α ≤ 1.3" (n = 6). In addition, comparisons were made among patients grouped according to their T1IFN activity itself: "T1IFN ND," "T1IFN detected and IFNβ/α ≤ 1.3," and "IFNβ/α >1.3." Major differences in gene expression were apparent in principal component and unsupervised cluster analyses. CL monocytes from the T1IFN ND or IFNβ/α >1.3 group were unlikely to express JAK1 and IFI27 (p < 0.0001 and p 0.0005, respectively). In NC monocytes from the same group, expression of IFNAR1, IRF1, TNFA, TLR4 (p ≤ 0.0001 for each) and others was enriched. Interestingly, JAK1 expression was absent in CL and NC monocytes from nine patients. This pattern most strongly associated with the IFNβ/α>1.3 group. Differences in gene expression in monocytes among the groups suggest differential IFN pathway activation in RA patients who are either likely to respond or to have no response to TNFi. Additional transcripts enriched in NC cells of those in the T1IFN ND and IFNβ/α >1.3 groups included MYD88, CD86, IRF1, and IL8. This work could suggest key pathways active in biologically defined groups of patients, and potential therapeutic strategies for those patients unlikely to respond to TNFi.