Outcomes of the EMDataResource cryo-EM Ligand Modeling Challenge.

The EMDataResource Ligand Model Challenge aimed to assess the reliability and reproducibility of modeling ligands bound to protein and protein-nucleic acid complexes in cryogenic electron microscopy (cryo-EM) maps determined at near-atomic (1.9-2.5 Å) resolution. Three published maps were selected as targets: Escherichia coli beta-galactosidase with inhibitor, SARS-CoV-2 virus RNA-dependent RNA polymerase with covalently bound nucleotide analog and SARS-CoV-2 virus ion channel ORF3a with bound lipid. Sixty-one models were submitted from 17 independent research groups, each with supporting workflow details. The quality of submitted ligand models and surrounding atoms were analyzed by visual inspection and quantification of local map quality, model-to-map fit, geometry, energetics and contact scores. A composite rather than a single score was needed to assess macromolecule+ligand model quality. These observations lead us to recommend best practices for assessing cryo-EM structures of liganded macromolecules reported at near-atomic resolution.

The structure of a 12-segmented dsRNA reovirus: New insights into capsid stabilization and organization.

Infecting a wide range of hosts, members of Reovirales (formerly Reoviridae) consist of a genome with different numbers of segmented double stranded RNAs (dsRNA) encapsulated by a proteinaceous shell and carry out genome replication and transcription inside the virion. Several cryo-electron microscopy (cryo-EM) structures of reoviruses with 9, 10 or 11 segmented dsRNA genomes have revealed insights into genome arrangement and transcription. However, the structure and genome arrangement of 12-segmented Reovirales members remain poorly understood. Using cryo-EM, we determined the structure of mud crab reovirus (MCRV), a 12-segmented dsRNA virus that is a putative member of Reovirales in the non-turreted Sedoreoviridae family, to near-atomic resolutions with icosahedral symmetry (3.1 Å) and without imposing icosahedral symmetry (3.4 Å). These structures revealed the organization of the major capsid proteins in two layers: an outer T = 13 layer consisting of VP12 trimers and unique VP11 clamps, and an inner T = 1 layer consisting of VP3 dimers. Additionally, ten RNA dependent RNA polymerases (RdRp) were well resolved just below the VP3 layer but were offset from the 5-fold axes and arranged with D5 symmetry, which has not previously been seen in other members of Reovirales. The N-termini of VP3 were shown to adopt four unique conformations; two of which anchor the RdRps, while the other two conformations are likely involved in genome organization and capsid stability. Taken together, these structures provide a new level of understanding for capsid stabilization and genome organization of segmented dsRNA viruses.

Retraction Note: A homing system targets therapeutic T cells to brain cancer.

This Article has been retracted; see accompanying Retraction.

Predictive modeling and cryo-EM: A synergistic approach to modeling macromolecular structure.

Over the last 15 years, structural biology has seen unprecedented development and improvement in two areas: electron cryo-microscopy (cryo-EM) and predictive modeling. Once relegated to low resolutions, single-particle cryo-EM is now capable of achieving near-atomic resolutions of a wide variety of macromolecular complexes. Ushered in by AlphaFold, machine learning has powered the current generation of predictive modeling tools, which can accurately and reliably predict models for proteins and some complexes directly from the sequence alone. Although they offer new opportunities individually, there is an inherent synergy between these techniques, allowing for the construction of large, complex macromolecular models. Here, we give a brief overview of these approaches in addition to illustrating works that combine these techniques for model building. These examples provide insight into model building, assessment, and limitations when integrating predictive modeling with cryo-EM density maps. Together, these approaches offer the potential to greatly accelerate the generation of macromolecular structural insights, particularly when coupled with experimental data.

Using Chemistry To Recreate the Complexity of the Extracellular Matrix: Guidelines for Supramolecular Hydrogel-Cell Interactions.

Hydrogels have emerged as a promising class of extracellular matrix (ECM)-mimicking materials in regenerative medicine. Here, we briefly describe current state-of-the-art of ECM-mimicking hydrogels, ranging from natural to hybrid to completely synthetic versions, giving the prelude to the importance of supramolecular interactions to make true ECM mimics. The potential of supramolecular interactions to create ECM mimics for cell culture is illustrated through a focus on two different supramolecular hydrogel systems, both developed in our laboratories. We use some recent, significant findings to present important design principles underlying the cell-material interaction. To achieve cell spreading, we propose that slow molecular dynamics (monomer exchange within fibers) is crucial to ensure the robust incorporation of cell adhesion ligands within supramolecular fibers. Slow bulk dynamics (stress-relaxation─fiber rearrangements, τ1/2 ≈ 1000 s) is required to achieve cell spreading in soft gels (<1 kPa), while gel stiffness overrules dynamics in stiffer gels. Importantly, this resonates with the findings of others which specialize in different material types: cell spreading is impaired in case substrate relaxation occurs faster than clutch binding and focal adhesion lifetime. We conclude with discussing considerations and limitations of the supramolecular approach as well as provide a forward thinking perspective to further understand supramolecular hydrogel-cell interactions. Future work may utilize the presented guidelines underlying cell-material interactions to not only arrive at the next generation of ECM-mimicking hydrogels but also advance other fields, such as bioelectronics, opening up new opportunities for innovative applications.

Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge.

This paper describes outcomes of the 2019 Cryo-EM Model Challenge. The goals were to (1) assess the quality of models that can be produced from cryogenic electron microscopy (cryo-EM) maps using current modeling software, (2) evaluate reproducibility of modeling results from different software developers and users and (3) compare performance of current metrics used for model evaluation, particularly Fit-to-Map metrics, with focus on near-atomic resolution. Our findings demonstrate the relatively high accuracy and reproducibility of cryo-EM models derived by 13 participating teams from four benchmark maps, including three forming a resolution series (1.8 to 3.1 Å). The results permit specific recommendations to be made about validating near-atomic cryo-EM structures both in the context of individual experiments and structure data archives such as the Protein Data Bank. We recommend the adoption of multiple scoring parameters to provide full and objective annotation and assessment of the model, reflective of the observed cryo-EM map density.

Microstructure characterization and mechanistic insight into polyether polyols and their associated polyurethanes.

This article reviews the analytical tool chest used for characterizing alkoxylates and their associated copolymer mixtures. Specific emphasis will be placed upon the use of mass spectrometry-based techniques as rapid characterization tools for optimizing reaction processes in an industrial R&D setting. An initial tutorial will cover the use of matrix-assisted laser desorption/ionization-mass spectrometry and tandem mass spectrometry fragmentation for detailed component analysis (e.g., polyol and isocyanate) of a model polyurethane-based foam. Next, this critical feedback information will be used with the guidance of mass spectrometry to initiate the development of a new, more efficient, tris(pentafluorophenyl)borane (FAB) catalyst-based alkoxylation process for generating the next generation of glycerin-initiated poly(propylene oxide)-co-poly(ethylene oxide) copolymers. Examples will be provided for each step in the FAB-based optimization process that were required to generate the final product. Following this example, two-dimensional liquid chromatography, supercritical fluid chromatography, and ion mobility separations, along with their coupling to mass spectrometry, will be reviewed for their efficiency in characterizing and quantitating the components within these complex polyether polyol mixtures.

Repurposing drugs for the treatment of osteoarthritis.

OBJECTIVE: Currently, no disease-modifying therapies for osteoarthritis (OA) exist, and attempts to identify novel cellular targets have been challenging. Risk factors for OA include advanced age, obesity, and metabolic syndrome. This creates an attractive opportunity to repurpose existing drugs that are used to treat comorbidities commonly encountered in patients with OA, if those drugs possess OA disease modifying properties. METHODS: This narrative review incorporates findings from knee or hand OA randomized clinical trials, post-hoc clinical trial analyses, prospective cohort studies, and observational data. RESULTS: Drugs used for the treatment of rheumatoid arthritis (methotrexate; TNFa, IL-1, and IL-6 pathway inhibitors; hydroxychloroquine), atopic/allergic disease (anti-histamines), osteoporosis (bisphosphonates and vitamin D), type 2 diabetes (metformin and GLP-1 agonists), and cardiovascular disease (atorvastatin, fish oil, and beta blockers) were reviewed for their potential benefit in OA. This review outlines the successful attributes of repurposed drugs, the challenges in repurposing drugs, and strategies for future clinical trials to support OA drug repurposing. Potential drug candidates for OA may be identified through the use of existing datasets and via collaborations with researchers in other fields to include OA endpoints in future clinical trials. CONCLUSION: Given the association of OA with several commonly treated comorbidities, drug repurposing is an appealing approach that could provide a favorable benefit-to-risk ratio for chronic OA treatment.

Genetic association between atopic disease and osteoarthritis.

OBJECTIVES: To evaluate the association between genetically determined risk for atopic disease and osteoarthritis (OA). METHODS: We performed linkage disequilibrium (LD) score regression using 1000 Genomes Project European samples as a reference for patterns of genome-wide LD. Summary statistics for atopic disease traits were obtained from the UK Biobank. We generated a pairwise genetic correlation between OA and traits for atopic disease to estimate the genetic correlation between traits (rg) and heritability for each trait. The association between atopy-related traits and OA was examined using Mendelian randomization (MR) on summary statistics; we reported inverse-variance weighted (IVW), MR-Egger, maximum likelihood estimation, weighted median, and weighted mode. RESULTS: There was a significant positive correlation between the genome-wide genetic architecture of asthma and all OA traits. Using the IVW (random effects), there was a significant association between asthma and knee OA ((odds ratio) OR = 1.04, 95% (confidence interval) CI 1.01-1.08, p = 0.0169). Using IVW (fixed effects), significant associations were identified between knee OA and allergic disease (OR = 1.07, 95% CI 1.01-1.14, p = 0.0342), allergic rhinitis (OR = 1.07, 95% CI 1.00-1.13, p = 0.0368), and asthma (OR = 1.04, 95% CI 1.01-1.07, p = 0.0139), as well as for OA at any site and asthma (OR = 1.02, 95% CI 1.00-1.04, p = 0.0166). CONCLUSIONS: We found a significant correlation between the overall genetic architecture of asthma and OA, as well as an increased risk of developing OA in patients with genetic variants associated with asthma and allergic rhinitis; predominately, this risk was for the development of knee OA. These results support a causal relationship between asthma and/or allergic rhinitis and knee OA.

Abundant transcriptomic alterations in the human cerebellum of patients with a C9orf72 repeat expansion.

The most prominent genetic cause of both amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) is a repeat expansion in the gene C9orf72. Importantly, the transcriptomic consequences of the C9orf72 repeat expansion remain largely unclear. Here, we used short-read RNA sequencing (RNAseq) to profile the cerebellar transcriptome, detecting alterations in patients with a C9orf72 repeat expansion. We focused on the cerebellum, since key C9orf72-related pathologies are abundant in this neuroanatomical region, yet TDP-43 pathology and neuronal loss are minimal. Consistent with previous work, we showed a reduction in the expression of the C9orf72 gene and an elevation in homeobox genes, when comparing patients with the expansion to both patients without the C9orf72 repeat expansion and control subjects. Interestingly, we identified more than 1000 alternative splicing events, including 4 in genes previously associated with ALS and/or FTLD. We also found an increase of cryptic splicing in C9orf72 patients compared to patients without the expansion and controls. Furthermore, we demonstrated that the expression level of select RNA-binding proteins is associated with cryptic splice junction inclusion. Overall, this study explores the presence of widespread transcriptomic changes in the cerebellum, a region not confounded by severe neurodegeneration, in post-mortem tissue from C9orf72 patients.

A homing system targets therapeutic T cells to brain cancer.

Successful T cell immunotherapy for brain cancer requires that the T cells can access tumour tissues, but this has been difficult to achieve. Here we show that, in contrast to inflammatory brain diseases such as multiple sclerosis, where endothelial cells upregulate ICAM1 and VCAM1 to guide the extravasation of pro-inflammatory cells, cancer endothelium downregulates these molecules to evade immune recognition. By contrast, we found that cancer endothelium upregulates activated leukocyte cell adhesion molecule (ALCAM), which allowed us to overcome this immune-evasion mechanism by creating an ALCAM-restricted homing system (HS). We re-engineered the natural ligand of ALCAM, CD6, in a manner that triggers initial anchorage of T cells to ALCAM and conditionally mediates a secondary wave of adhesion by sensitizing T cells to low-level ICAM1 on the cancer endothelium, thereby creating the adhesion forces necessary to capture T cells from the bloodstream. Cytotoxic HS T cells robustly infiltrated brain cancers after intravenous injection and exhibited potent antitumour activity. We have therefore developed a molecule that targets the delivery of T cells to brain cancer.

Enhanced Efflux Activity Facilitates Drug Tolerance in Dormant Bacterial Cells.

Natural variations in gene expression provide a mechanism for multiple phenotypes to arise in an isogenic bacterial population. In particular, a sub-group termed persisters show high tolerance to antibiotics. Previously, their formation has been attributed to cell dormancy. Here we demonstrate that bacterial persisters, under ß-lactam antibiotic treatment, show less cytoplasmic drug accumulation as a result of enhanced efflux activity. Consistently, a number of multi-drug efflux genes, particularly the central component TolC, show higher expression in persisters. Time-lapse imaging and mutagenesis studies further establish a positive correlation between tolC expression and bacterial persistence. The key role of efflux systems, among multiple biological pathways involved in persister formation, indicates that persisters implement a positive defense against antibiotics prior to a passive defense via dormancy. Finally, efflux inhibitors and antibiotics together effectively attenuate persister formation, suggesting a combination strategy to target drug tolerance.

Elementary school-aged children's perceptions of academic dishonesty: Definitions and moral evaluations of cheating behaviors in school.

A total of 76 children (Mage = 9 years 5 months, SD = 2.22 years) participated in a structured interview about their experiences with and knowledge of academic dishonesty. Overall, 27% of the sample reported having cheated in school. Most of these children were 10 to 13 years old, and the most prevalent form of cheating behavior reported was using forbidden materials during a test. Children's age group was a significant positive predictor of their reported cheating history; however, no significant difference was found between children's gender and engagement with cheating. Children's moral evaluations of cheating did not predict their reported cheating history, nor did children's parents' cheating history. Vignette type (cheating vs. non-cheating), age group, and the interaction between vignette type and age group were significant predictors of children's ability to accurately identify behaviors that constitute cheating. Children rated cheating behaviors as significantly less moral than non-cheating behaviors. Overall, the current results provide insight into what forms of cheating behavior children engage in at the elementary school-age level.

Senile plaque-associated transactive response DNA-binding protein 43 in Alzheimer's disease: A case report spanning 16 years of memory loss.

Transactive response DNA-binding protein 43 (TDP-43) pathological inclusions are found in frontotemporal lobar degeneration (FTLD-TDP) and Alzheimer's disease (AD-TDP). While clinically different, TDP-43 inclusions in FTLD-TDP and AD can have similar morphological characteristics. However, TDP-43 colocalizing with tau and forming "apple-bite" or "flame-shaped" neuronal cytoplasmic inclusions (NCI) are only found in AD-TDP. Here, we describe a case with AD and neuritic plaque-associated TDP-43. The patient was a 96-year-old right-handed Caucasian woman who had developed a slowly progressive amnestic syndrome compatible with typical AD at age 80. Genetic testing revealed APOE ε3/ε4, GRN r5848 CT, and MAPT H1/H2 genotype. Consistent with the old age at onset and long disease duration, limbic-predominant AD was found at autopsy, with high hippocampal yet low cortical neurofibrillary tangle (NFT) counts. Hippocampal and amygdala sclerosis were present. Immunohistochemistry for phospho-TDP-43 showed NCIs, dystrophic neurites, and rare neuronal intranuclear inclusions consistent with FTLD-TDP type A, as well as tau NFT-associated TDP-43 inclusions. These were frequent in the amygdala, entorhinal cortex, hippocampus, occipitotemporal gyrus, and inferior temporal gyrus but sparse in the mid-frontal cortex. Additionally, there were TDP-43-immunoreactive inclusions forming plaque-like structures in the molecular layer of the dentate fascia of the hippocampus. The presence of neuritic plaques in the same region was confirmed using thioflavin-S fluorescent microscopy and immunohistochemistry for phospho-tau. Double labeling immunofluorescence showed colocalization of TDP-43 and tau within neuritic plaques. Other pathologies included mild Lewy body pathology predominantly affecting the amygdala and olfactory bulb, aging-related tau astrogliopathy, and mixed small vessel disease (arteriolosclerosis and amyloid angiopathy) with several cortical microinfarcts. In conclusion, we have identified TDP-43 colocalizing with tau in neuritic plaques in AD, which expands the association of TDP-43 and tau in AD beyond NFTs. The clinical correlate of this plaque-associated TDP-43 appears to be a slowly progressive amnestic syndrome.

Light Control in Microbial Systems.

Light is a key environmental component influencing many biological processes, particularly in prokaryotes such as archaea and bacteria. Light control techniques have revolutionized precise manipulation at molecular and cellular levels in recent years. Bacteria, with adaptability and genetic tractability, are promising candidates for light control studies. This review investigates the mechanisms underlying light activation in bacteria and discusses recent advancements focusing on light control methods and techniques for controlling bacteria. We delve into the mechanisms by which bacteria sense and transduce light signals, including engineered photoreceptors and light-sensitive actuators, and various strategies employed to modulate gene expression, protein function, and bacterial motility. Furthermore, we highlight recent developments in light-integrated methods of controlling microbial responses, such as upconversion nanoparticles and optical tweezers, which can enhance the spatial and temporal control of bacteria and open new horizons for biomedical applications.

A spectroscopic liquid biopsy for the earlier detection of multiple cancer types.

BACKGROUND: A rapid, low-cost blood test that can be applied to reliably detect multiple different cancer types would be transformational. METHODS: In this large-scale discovery study (n = 2092 patients) we applied the Dxcover® Cancer Liquid Biopsy to examine eight different cancers. The test uses Fourier transform infrared (FTIR) spectroscopy and machine-learning algorithms to detect cancer. RESULTS: Area under the receiver operating characteristic curve (ROC) values were calculated for eight cancer types versus symptomatic non-cancer controls: brain (0.90), breast (0.76), colorectal (0.91), kidney (0.91), lung (0.91), ovarian (0.86), pancreatic (0.84) and prostate (0.86). We assessed the test performance when all eight cancer types were pooled to classify 'any cancer' against non-cancer patients. The cancer versus asymptomatic non-cancer classification detected 64% of Stage I cancers when specificity was 99% (overall sensitivity 57%). When tuned for higher sensitivity, this model identified 99% of Stage I cancers (with specificity 59%). CONCLUSIONS: This spectroscopic blood test can effectively detect early-stage disease and can be fine-tuned to maximise either sensitivity or specificity depending on the requirements from different healthcare systems and cancer diagnostic pathways. This low-cost strategy could facilitate the requisite earlier diagnosis, when cancer treatment can be more effective, or less toxic. STATEMENT OF TRANSLATIONAL RELEVANCE: The earlier diagnosis of cancer is of paramount importance to improve patient survival. Current liquid biopsies are mainly focused on single tumour-derived biomarkers, which limits test sensitivity, especially for early-stage cancers that do not shed enough genetic material. This pan-omic liquid biopsy analyses the full complement of tumour and immune-derived markers present within blood derivatives and could facilitate the earlier detection of multiple cancer types. There is a low barrier to integrating this blood test into existing diagnostic pathways since the technology is rapid, simple to use, only minute sample volumes are required, and sample preparation is minimal. In addition, the spectroscopic liquid biopsy described in this study has the potential to be combined with other orthogonal tests, such as cell-free DNA, which could provide an efficient route to diagnosis. Cancer treatment can be more effective when given earlier, and this low-cost strategy has the potential to improve patient prognosis.

Optical Screening and Classification of Drug Binding to Proteins in Human Blood Serum.

Protein-drug interactions in the human bloodstream are important factors in applications ranging from drug design, where protein binding influences efficacy and dose delivery, to biomedical diagnostics, where rapid, quantitative measurements could guide optimized treatment regimes. Current measurement approaches use multistep assays, which probe the protein-bound drug fraction indirectly and do not provide fundamental structural or dynamic information about the in vivo protein-drug interaction. We demonstrate that ultrafast 2D-IR spectroscopy can overcome these issues by providing a direct, label-free optical measurement of protein-drug binding in blood serum samples. Four commonly prescribed drugs, known to bind to human serum albumin (HSA), were added to pooled human serum at physiologically relevant concentrations. In each case, spectral changes to the amide I band of the serum sample were observed, consistent with binding to HSA, but were distinct for each of the four drugs. A machine-learning-based classification of the serum samples achieved a total cross-validation prediction accuracy of 92% when differentiating serum-only samples from those with a drug present. Identification on a per-drug basis achieved correct drug identification in 75% of cases. These unique spectroscopic signatures of the drug-protein interaction thus enable the detection and differentiation of drug containing samples and give structural insight into the binding process as well as quantitative information on protein-drug binding. Using currently available instrumentation, the 2D-IR data acquisition required just 1 min and 10 µL of serum per sample, and so these results pave the way to fast, specific, and quantitative measurements of protein-drug binding in vivo with potentially invaluable applications for the development of novel therapies and personalized medicine.

Increased risk of osteoarthritis in patients with atopic disease.

OBJECTIVES: To determine the incidence of osteoarthrits (OA) in patients with atopic disease compared with matched non-exposed patients. METHODS: We conducted a retrospective cohort study with propensity score matching using claims data from Optum's de-identified Clinformatics Data Mart (CDM) (January 2003 to June 2019) and electronic health record data from the Stanford Research Repository (STARR) (January 2010 to December 2020). We included adult patients without pre-existing OA or inflammatory arthritis who were exposed to atopic disease or who were non-exposed. The primary outcome was the development of incident OA. RESULTS: In Optum CDM, we identified 117 346 exposed patients with asthma or atopic dermatitis (mean age 52 years; 60% female) and 1 247 196 non-exposed patients (mean age 50 years; 48% female). After propensity score matching (n=1 09 899 per group), OA incidence was higher in patients with asthma or atopic dermatitis (26.9 per 1000 person-years) compared with non-exposed patients (19.1 per 1000 person-years), with an adjusted odds ratio (aOR) of 1.58 (95% CI 1.55 to 1.62) for developing OA. This effect was even more pronounced in patients with both asthma and atopic dermatitis compared with non-exposed patients (aOR=2.15; 95% CI 1.93 to 2.39) and in patients with asthma compared with patients with chronic obstructive pulmonary disease (aOR=1.83; 95% CI 1.73 to 1.95). We replicated our results in an independent dataset (STARR), which provided the added richness of body mass index data. The aOR of developing OA in patients with asthma or atopic dermatitis versus non-exposed patients in STARR was 1.42 (95% CI 1.36 to 1.48). CONCLUSIONS: This study demonstrates an increased incidence of OA in patients with atopic disease. Future interventional studies may consider targeting allergic pathways for the prevention or treatment of OA.

Liquid biopsies: the future of cancer early detection.

Cancer is a worldwide pandemic. The burden it imposes grows steadily on a global scale causing emotional, physical, and financial strains on individuals, families, and health care systems. Despite being the second leading cause of death worldwide, many cancers do not have screening programs and many people with a high risk of developing cancer fail to follow the advised medical screening regime due to the nature of the available screening tests and other challenges with compliance. Moreover, many liquid biopsy strategies being developed for early detection of cancer lack the sensitivity required to detect early-stage cancers. Early detection is key for improved quality of life, survival, and to reduce the financial burden of cancer treatments which are greater at later stage detection. This review examines the current liquid biopsy market, focusing in particular on the strengths and drawbacks of techniques in achieving early cancer detection. We explore the clinical utility of liquid biopsy technologies for the earlier detection of solid cancers, with a focus on how a combination of various spectroscopic and -omic methodologies may pave the way for more efficient cancer diagnostics.

A double-blind, placebo-controlled, randomized withdrawal trial of sarilumab for the treatment of glucocorticoid-dependent sarcoidosis.

OBJECTIVES: Effective steroid-sparing therapies for the treatment of sarcoidosis are lacking; interleukin-6 (IL-6) antagonists may reduce sarcoidosis disease activity. This study assessed the safety and efficacy of the IL-6 receptor antagonist, sarilumab, in subjects with glucocorticoid-dependent sarcoidosis. METHODS: This phase II, double-blind, placebo-controlled, randomized withdrawal trial enrolled 15 subjects with biopsy-proven sarcoidosis at Stanford University from November 2019 to September 2022. In Period 1, subjects were treated with open-label sarilumab 200mg subcutaneously every two weeks for 16 weeks, with predefined tapering of prednisone. Subjects who completed Period 1 without a sarcoidosis flare entered Period 2 and were randomized to continue sarilumab or to receive matching placebo for 12 weeks. Endpoints included flare-free survival, as well as changes in pulmonary function tests, chest imaging, patient reported outcomes, and laboratory values. RESULTS: Fifteen subjects were enrolled in the study (median age 57 years, 80% male, 73.3% White), and 10 subjects successfully completed Period 1. During Period 1, 4 of 15 subjects (26.7%) discontinued due to worsening of their sarcoidosis, and CT chest imaging worsened in 5 of 15 subjects (35.7%). During Period 2, 0 of 2 subjects in the sarilumab group and 1 of 8 subjects (12.5%) in the placebo group had a flare. Treatment with sarilumab 200 mg was generally well tolerated in subjects with sarcoidosis. CONCLUSION: In this double-blind, placebo-controlled, randomized withdrawal trial, a meaningful signal for improvement in subjects with sarcoidosis treated with sarilumab was not observed. Given the small numbers in this study, no definitive conclusions can be drawn. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04008069.