Synovial fibroblast gene expression is associated with sensory nerve growth and pain in rheumatoid arthritis.

It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in the synovium; however, recent studies reveal that pain scores in patients do not correlate with synovial inflammation. We developed a machine-learning approach (graph-based gene expression module identification or GbGMI) to identify an 815-gene expression module associated with pain in synovial biopsy samples from patients with established RA who had limited synovial inflammation at arthroplasty. We then validated this finding in an independent cohort of synovial biopsy samples from patients who had early untreated RA with little inflammation. Single-cell RNA sequencing analyses indicated that most of these 815 genes were most robustly expressed by lining layer synovial fibroblasts. Receptor-ligand interaction analysis predicted cross-talk between human lining layer fibroblasts and human dorsal root ganglion neurons expressing calcitonin gene-related peptide (CGRP+). Both RA synovial fibroblast culture supernatant and netrin-4, which is abundantly expressed by lining fibroblasts and was within the GbGMI-identified pain-associated gene module, increased the branching of pain-sensitive murine CGRP+ dorsal root ganglion neurons in vitro. Imaging of solvent-cleared synovial tissue with little inflammation from humans with RA revealed CGRP+ pain-sensing neurons encasing blood vessels growing into synovial hypertrophic papilla. Together, these findings support a model whereby synovial lining fibroblasts express genes associated with pain that enhance the growth of pain-sensing neurons into regions of synovial hypertrophy in RA.

Machine Learning Reveals Synovial Fibroblast Genes Associated with Pain Affect Sensory Nerve Growth in Rheumatoid Arthritis.

It has been presumed that rheumatoid arthritis (RA) joint pain is related to inflammation in the synovium; however, recent studies reveal that pain scores in patients do not correlate with synovial inflammation. We identified a module of 815 genes associated with pain, using a novel machine learning approach, Graph-based Gene expression Module Identification (GbGMI), in samples from patients with longstanding RA, but limited synovial inflammation at arthroplasty, and validated this finding in an independent cohort of synovial biopsy samples from early, untreated RA patients. Single-cell RNA-seq analyses indicated these genes were most robustly expressed by lining layer fibroblasts and receptor-ligand interaction analysis predicted robust lining layer fibroblast crosstalk with pain sensitive CGRP+ dorsal root ganglion sensory neurons. Netrin-4, which is abundantly expressed by lining fibroblasts and associated with pain, significantly increased the branching of pain-sensitive CGRP+ neurons in vitro . We conclude GbGMI is a useful method for identifying a module of genes that associate with a clinical feature of interest. Using this approach, we find that Netrin-4 is produced by synovial fibroblasts in the absence of inflammation and can enhance the outgrowth of CGRP+ pain sensitive nerve fibers. One Sentence Summary: Machine Learning reveals synovial fibroblast genes related to pain affect sensory nerve growth in Rheumatoid Arthritis addresses unmet clinical need.

Computer Vision Analysis of Rheumatoid Arthritis Synovium Reveals Lymphocytic Inflammation Is Associated With Immunoglobulin Skewing in Blood.

OBJECTIVE: We sought to develop computer vision methods to quantify aggregates of cells in synovial tissue and compare these with clinical and gene expression parameters. METHODS: We assembled a computer vision pipeline to quantify five features encompassing synovial cell density and aggregates and compared these with pathologist scores, disease classification, autoantibody status, and RNA expression in a cohort of 156 patients with rheumatoid arthritis (RA) and 149 patients with osteoarthritis (OA). RESULTS: All five features were associated with pathologist scores of synovial lymphocytic inflammation (P < 0.0001). Three features that related to the cells per unit of tissue were significantly increased in patients with both seronegative and seropositive RA compared with those with OA; on the other hand, aggregate features (number and diameter) were significantly increased in seropositive, but not seronegative, RA compared with OA. Aggregate diameter was associated with the gene expression of immunoglobulin heavy-chain genes in the synovial tissue. Compared with blood, synovial immunoglobulin isotypes were skewed from IGHM and IGHD to IGHG3 and IGHG1. Further, patients with RA with high levels of lymphocytic infiltrates in the synovium demonstrated parallel skewing in their blood with a relative decrease in IGHGM (P < 0.002) and IGHD (P < 0.03) and an increase in class-switched immunoglobulin genes IGHG3 (P < 0.03) and IGHG1 (P < 0.002). CONCLUSION: High-resolution automated identification and quantification of synovial immune cell aggregates uncovered skewing in the synovium from naïve IGHD and IGHM to memory IGHG3 and IGHG1 and revealed that this process is reflected in the blood of patients with high inflammatory synovium.

Drivers of heterogeneity in synovial fibroblasts in rheumatoid arthritis.

Inflammation of non-barrier immunologically quiescent tissues is associated with a massive influx of blood-borne innate and adaptive immune cells. Cues from the latter are likely to alter and expand activated states of the resident cells. However, local communications between immigrant and resident cell types in human inflammatory disease remain poorly understood. Here, we explored drivers of fibroblast-like synoviocyte (FLS) heterogeneity in inflamed joints of patients with rheumatoid arthritis using paired single-cell RNA and ATAC sequencing, multiplexed imaging and spatial transcriptomics along with in vitro modeling of cell-extrinsic factor signaling. These analyses suggest that local exposures to myeloid and T cell-derived cytokines, TNF, IFN-γ, IL-1ß or lack thereof, drive four distinct FLS states some of which closely resemble fibroblast states in other disease-affected tissues including skin and colon. Our results highlight a role for concurrent, spatially distributed cytokine signaling within the inflamed synovium.

Rheumatology in the era of precision medicine: synovial tissue molecular patterns and treatment response in rheumatoid arthritis.

PURPOSE OF REVIEW: A critical unmet need in rheumatoid arthritis (RA) is the identification of biomarkers that predict which of the available medications will be most effective for an individual in order to lower disease activity sooner than is afforded by the current treat-to-target approach. Here we will discuss recent reports examining the potential for synovial tissue molecular, cellular, and spatial profiling in defining objective measures of treatment response and therein developing personalized medicine for RA. RECENT FINDINGS: Recent high-dimensional molecular profiling of RA synovium has provided unprecedented resolution of the cell types and pathways in tissues affected by rheumatic diseases. Heightened attention to tissue architecture is also emerging as a means to classify individual disease variation that may allow patients to be further stratified by therapeutic response. Although this wealth of data may have already pinpointed promising biomarkers, additional studies, likely including tissue-based functional drug response assays, will be required to demonstrate how the complex tissue environment responds. SUMMARY: Molecular, cellular, and more recently spatial profiling of the RA synovium are uncovering fundamental features of the disease. Current investigations are examining whether this information will provide meaningful biomarkers for individualized medicine in RA.

Arthritis After Cancer Immunotherapy: Symptom Duration and Treatment Response.

OBJECTIVE: Musculoskeletal manifestations of immune-related adverse events (irAEs) after checkpoint inhibitor immunotherapy for cancer remain incompletely characterized and poorly understood. A recently published case series suggested that immunotherapy-induced arthritis is an aggressive process requiring high-dose corticosteroids. METHODS: This was a retrospective chart review of all patients with musculoskeletal irAEs first seen by one of the authors between 2014 and 2016. All patients had been treated for a malignancy with immune checkpoint inhibitors targeting PD-1 (nivolumab, pembrolizumab), PD-L1 (durvalumab), and/or CTLA-4 (ipilimumab, tremelimumab) at Memorial Sloan Kettering Cancer Center. RESULTS: We identified 10 patients with a mean ± SD age of 63.2 ± 9.7 years. Seven were treated with a combination of checkpoint inhibitors and 3 with nivolumab monotherapy. Four patients developed inflammatory polyarthritis, 4 oligoarthritis, and 2 tenosynovitis. Six were antinuclear antibody positive and 2 had anti-cyclic citrullinated peptide antibodies. Mean ± SD time from the first dose of immunotherapy until joint involvement was 6.3 ± 4.3 months. All 10 patients were treated with systemic corticosteroids, but 6 of 10 required ≤20 mg per day of prednisone. Five patients received steroid-sparing agents. Mean ± SD time until resolution of joint symptoms after the last dose of immunotherapy was 9.2 ± 6.1 months. CONCLUSION: Musculoskeletal irAEs can manifest as a rheumatoid arthritis-like polyarthritis, oligoarthritis, tenosynovitis, or polymyalgia rheumatica. Musculoskeletal symptoms can last more than a year, but they can generally be managed with low to moderate doses of corticosteroids.

Brief Report: Whole-Exome Sequencing for Identification of Potential Causal Variants for Diffuse Cutaneous Systemic Sclerosis.

OBJECTIVE: Scleroderma is a genetically complex autoimmune disease with substantial phenotypic heterogeneity. Previous genome-wide association studies have identified common genetic variants associated with disease risk, but these studies are not designed to capture rare or potential causal variants. Our goal was to identify rare as well as common genetic variants in patients with diffuse cutaneous systemic sclerosis (dcSSc) through whole-exome sequencing (WES) in order to identify potential causal variants. METHODS: We generated WES data for 32 dcSSc patients with or without interstitial lung disease (ILD) and for 17 healthy "in-house" controls. Variants were annotated and filtered by quality, minor allele frequency, and deleterious effects on gene function. We applied a gene burden test to identify novel dcSSc and dcSSc-associated ILD candidate genes that were enriched with deleterious variants in cases compared to in-house controls as well as controls from the 1000 Genomes Project (n = 130). RESULTS: We identified 70 genes that were enriched with deleterious variants in dcSSc patients. Two of them (BANK1 and TERT) were in pathways previously implicated in SSc or ILD pathogenesis or known susceptibility loci. Newly identified genes (COL4A3, COL4A4, COL5A2, COL13A1, and COL22A1) were significantly enriched in the extracellular matrix-related pathway, which is relevant to the fibrotic features of dcSSc, and in the DNA repair pathway (XRCC4). CONCLUSION: This study demonstrates the value of WES for the identification of novel gene variants and pathways that may contribute to scleroderma risk and/or severity. The candidate genes we discovered are potential targets for in-depth functional studies.

Misfolded proteins induce aggregation of the lectin Yos9.

A substantial fraction of nascent proteins delivered into the endoplasmic reticulum (ER) never reach their native conformations. Eukaryotes use a series of complementary pathways to efficiently recognize and dispose of these terminally misfolded proteins. In this process, collectively termed ER-associated degradation (ERAD), misfolded proteins are retrotranslocated to the cytosol, polyubiquitinated, and degraded by the proteasome. Although there has been great progress in identifying ERAD components, how these factors accurately identify substrates remains poorly understood. The targeting of misfolded glycoproteins in the ER lumen for ERAD requires the lectin Yos9, which recognizes the glycan species found on terminally misfolded proteins. In a role that remains poorly characterized, Yos9 also binds the protein component of ERAD substrates. Here, we identified a 45-kDa domain of Yos9, consisting of residues 22-421, that is proteolytically stable, highly structured, and able to fully support ERAD in vivo. In vitro binding studies show that Yos9(22-421) exhibits sequence-specific recognition of linear peptides from the ERAD substrate, carboxypeptidase Y G255R (CPY*), and binds a model unfolded peptide ΔEspP and protein Δ131Δ in solution. Binding of Yos9 to these substrates results in their cooperative aggregation. Although the physiological consequences of this substrate-induced aggregation remain to be seen, it has the potential to play a role in the regulation of ERAD.

Road to ruin: targeting proteins for degradation in the endoplasmic reticulum.

Some nascent proteins that fold within the endoplasmic reticulum (ER) never reach their native state. Misfolded proteins are removed from the folding machinery, dislocated from the ER into the cytosol, and degraded in a series of pathways collectively referred to as ER-associated degradation (ERAD). Distinct ERAD pathways centered on different E3 ubiquitin ligases survey the range of potential substrates. We now know many of the components of the ERAD machinery and pathways used to detect substrates and target them for degradation. Much less is known about the features used to identify terminally misfolded conformations and the broader role of these pathways in regulating protein half-lives.

Strain conformation, primary structure and the propagation of the yeast prion [PSI+].

Prion proteins can adopt multiple infectious strain conformations. Here we investigate how the sequence of a prion protein affects its capacity to propagate specific conformations by exploiting our ability to create two distinct infectious conformations of the yeast [PSI(+)] prion protein Sup35, termed Sc4 and Sc37. PNM2, a G58D point mutant of Sup35 that was originally identified for its dominant interference with prion propagation, leads to rapid, recessive loss of Sc4 but does not interfere with propagation of Sc37. PNM2 destabilizes the amyloid core of Sc37 and causes compensatory effects that slow prion growth but aid prion division and result in robust propagation of Sc37. By contrast, PNM2 does not affect the structure or chaperone-mediated division of Sc4 but interferes with its delivery to daughter cells. Thus, effective delivery of infectious particles during cell division is a crucial and conformation-dependent step in prion inheritance.

Polyglutamine fibrils are formed using a simple designed beta-hairpin model.

Polyglutamine repeats are found in proteins associated with many neurodegenerative diseases. These repeats are responsible for intracellular protein aggregation that resemble amyloid plaques and contain the hallmarks of cross-beta fibrillar structures. Recent work has suggested that the glutamines are involved in aggregation through two possible mechanisms: one involving only side-chain hydrogen bonding and a second involving interdigitation of the glutamines with tight van der Waal's packing (steric zipper model). We are interested in determining which interactions are particularly involved in early assembly processes and have developed a beta-hairpin model system to address this problem. Our model system is designed to stabilize a putative high-energy nucleating structure to provide a window to view early assembly processes. We have applied spectroscopy tools (circular dichroism, infrared, and dynamic light scattering) to probe the self-assembly of beta-sheet fibrils. These experiments established the conditions to study fibrillar morphology using atomic force microscopy. We show that fibrils are short with minimal lateral growth, suggesting that this may be a good model system for studying early assembly steps.

Transient structural distortion of metal-free Cu/Zn superoxide dismutase triggers aberrant oligomerization.

Amyotrophic lateral sclerosis (ALS) is a neurodegenerative disease linked to the misfolding of Cu/Zn superoxide dismutase (SOD1). ALS-related defects in SOD1 result in a gain of toxic function that coincides with aberrant oligomerization. The structural events triggering oligomerization have remained enigmatic, however, as is the case in other protein-misfolding diseases. Here, we target the critical conformational change that defines the earliest step toward aggregation. Using nuclear spin relaxation dispersion experiments, we identified a short-lived (0.4 ms) and weakly populated (0.7%) conformation of metal-depleted SOD1 that triggers aberrant oligomerization. This excited state emanates from the folded ground state and is suppressed by metal binding, but is present in both the disulfide-oxidized and disulfide-reduced forms of the protein. Our results pinpoint a perturbed region of the excited-state structure that forms intermolecular contacts in the earliest nonnative dimer/oligomer. The conformational transition that triggers oligomerization is a common feature of WT SOD1 and ALS-associated mutants that have widely different physicochemical properties. But compared with WT SOD1, the mutants have enhanced structural distortions in their excited states, and in some cases slightly higher excited-state populations and lower kinetic barriers, implying increased susceptibility to oligomerization. Our results provide a unified picture that highlights both (i) a common denominator among different SOD1 variants that may explain why diverse mutations cause the same disease, and (ii) a structural basis that may aid in understanding how different mutations affect disease propensity and progression.