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The IL-17A inhibitor secukinumab is efficacious for the treatment of psoriasis. To better understand its mechanism of action, we investigated its impact on psoriatic lesions from 15 patients with moderate-to-severe plaque psoriasis undergoing secukinumab treatment. We characterized the longitudinal transcriptomic changes of whole lesional skin tissue as well as cutaneous CD4+ and CD8+ T effector cells and CD4+ T regulatory cells across 12 weeks of treatment. Secukinumab was clinically effective and reduced disease-associated overexpression of IL17A , IL17F, IL23A, IL23R, and IFNG in whole tissue as soon as 2 weeks after initiation of treatment. IL17A overexpression in T-cell subsets, primarily CD8+ T cells, was also reduced. Although secukinumab treatment resolved 89‒97% of psoriasis-associated expression differences in bulk tissue and T-cell subsets by week 12 of treatment, we observed expression differences involved in IFN signaling and metallothionein synthesis that remained unresolved at this time point as well as potential treatment-associated expression differences involved in IL-15 signaling. These changes were accompanied by shifts in broader immune cell composition on the basis of deconvolution of RNA-sequencing data. In conclusion, our study reveals several phenotypic and cellular changes within the lesion that underlie clinical improvement from secukinumab.

Psoriasis is a chronic, inflammatory skin disease that affects 2‒3% of the global population. Besides skin manifestations, patients with psoriasis have increased susceptibility to a number of comorbidities, including psoriatic arthritis, cardiovascular disease, and inflammatory bowel disease. To understand the systemic component of psoriasis pathogenesis, we performed a pilot study to examine the fecal metagenome, host colonic transcriptome, and host peripheral blood immune profiles of patients with psoriasis and healthy controls. Our study showed increased functional diversity in the gut microbiome of patients with psoriasis. In addition, we identified microbial species that preferentially associate with patients with psoriasis and which have been previously found to associate with other autoimmune diseases. Intriguingly, our data revealed three psoriasis subgroups that have distinct microbial and host features. Integrating these features revealed host‒microbe associations that are specific to psoriasis or particular psoriasis subgroups. Our findings provide insight into the factors that may affect the development of comorbidities in patients with psoriasis and may hold diagnostic potential for early identification of patients with psoriasis at risk for these comorbidities.

Introduction Lead exposure reduction has been one of the most successful environmental health campaigns ever undertaken. (1) However, for the target goal of 'zero' micrograms of lead in blood to [...]

Early diagnosis of psoriatic arthritis (PSA) is important for successful therapeutic intervention but currently remains challenging due, in part, to the scarcity of non-invasive biomarkers. In this study, we performed single cell profiling of transcriptome and cell surface protein expression to compare the peripheral blood immunocyte populations of individuals with PSA, individuals with cutaneous psoriasis (PSO) alone, and healthy individuals. We identified genes and proteins differentially expressed between PSA, PSO, and healthy subjects across 30 immune cell types and observed that some cell types, as well as specific phenotypic subsets of cells, differed in abundance between these cohorts. Cell type-specific gene and protein expression differences between PSA, PSO, and healthy groups, along with 200 previously published genetic risk factors for PSA, were further used to perform machine learning classification, with the best models achieving AUROC ≥ 0.87 when either classifying subjects among the three groups or specifically distinguishing PSA from PSO. Our findings thus expand the repertoire of gene, protein, and cellular biomarkers relevant to PSA and demonstrate the utility of machine learning-based diagnostics for this disease.

Ankylosing spondylitis (AS) is an immune-mediated inflammatory disorder that primarily affects the axial skeleton, especially the sacroiliac joints and spine. This results in chronic back pain and, in extreme cases, ankylosis of the spine. Despite its debilitating effects, the pathogenesis of AS remains to be further elucidated. This study used single cell CITE-seq technology to analyze peripheral blood mononuclear cells (PBMCs) in AS and in healthy controls. We identified a number of molecular features associated with AS. CD52 was found to be overexpressed in both RNA and surface protein expression across several cell types in patients with AS. CD16+ monocytes overexpressed TNFSF10 and IL-18Rα in AS, while CD8+ TEM cells and natural killer cells overexpressed genes linked with cytotoxicity, including GZMH, GZMB, and NKG7. Tregs underexpressed CD39 in AS, suggesting reduced functionality. We identified an overrepresented NK cell subset in AS that overexpressed CD16, CD161, and CD38, as well as cytotoxic genes and pathways. Finally, we developed machine learning models derived from CITE-seq data for the classification of AS and achieved an Area Under the Receiver Operating Characteristic (AUROC) curve of > 0.95. In summary, CITE-seq identification of AS-associated genes and surface proteins in specific cell subsets informs our understanding of pathogenesis and potential new therapeutic targets, while providing new approaches for diagnosis via machine learning.

Regulatory T cells (Tregs) reside in nonlymphoid tissues where they carry out unique functions. The molecular mechanisms responsible for Treg accumulation and maintenance in these tissues are relatively unknown. Using an unbiased discovery approach, we identified LAYN (layilin), a C-type lectin-like receptor, to be preferentially and highly expressed on a subset of activated Tregs in healthy and diseased human skin. Expression of layilin on Tregs was induced by TCR-mediated activation in the presence of IL-2 or TGF-β. Mice with a conditional deletion of layilin in Tregs had reduced accumulation of these cells in tumors. However, these animals somewhat paradoxically had enhanced immune regulation in the tumor microenvironment, resulting in increased tumor growth. Mechanistically, layilin expression on Tregs had a minimal effect on their activation and suppressive capacity in vitro. However, expression of this molecule resulted in a cumulative anchoring effect on Treg dynamic motility in vivo. Taken together, our results suggest a model whereby layilin facilitates Treg adhesion in skin and, in doing so, limits their suppressive capacity. These findings uncover a unique mechanism whereby reduced Treg motility acts to limit immune regulation in nonlymphoid organs and may help guide strategies to exploit this phenomenon for therapeutic benefit.

BackgroundPsoriasis is an inflammatory, IL-17-driven skin disease in which autoantigen-induced CD8+ T cells have been identified as pathogenic drivers.ObjectiveOur study focused on comprehensively characterizing the phenotypic variation of CD8+ T cells in psoriatic lesions.MethodsWe used single-cell RNA sequencing to compare CD8+ T-cell transcriptomic heterogeneity between psoriatic and healthy skin.ResultsWe identified 11 transcriptionally diverse CD8+ T-cell subsets in psoriatic and healthy skin. Among several inflammatory subsets enriched in psoriatic skin, we observed 2 Tc17 cell subsets that were metabolically divergent, were developmentally related, and expressed CXCL13, which we found to be a biomarker of psoriasis severity and which achieved comparable or greater accuracy than IL17A in a support vector machine classifier of psoriasis and healthy transcriptomes. Despite high coinhibitory receptor expression in the Tc17 cell clusters, a comparison of these cells with melanoma-infiltrating CD8+ T cells revealed upregulated cytokine, cytolytic, and metabolic transcriptional activity in the psoriatic cells that differed from an exhaustion program.ConclusionUsing high-resolution single-cell profiling in tissue, we have uncovered the diverse landscape of CD8+ T cells in psoriatic and healthy skin, including 2 nonexhausted Tc17 cell subsets associated with disease severity.

The Gene Ontology Consortium (GOC) provides the most comprehensive resource currently available for computable knowledge regarding the functions of genes and gene products. Here, we report the advances of the consortium over the past two years. The new GO-CAM annotation framework was notably improved, and we formalized the model with a computational schema to check and validate the rapidly increasing repository of 2838 GO-CAMs. In addition, we describe the impacts of several collaborations to refine GO and report a 10% increase in the number of GO annotations, a 25% increase in annotated gene products, and over 9,400 new scientific articles annotated. As the project matures, we continue our efforts to review older annotations in light of newer findings, and, to maintain consistency with other ontologies. As a result, 20 000 annotations derived from experimental data were reviewed, corresponding to 2.5% of experimental GO annotations. The website (http://geneontology.org) was redesigned for quick access to documentation, downloads and tools. To maintain an accurate resource and support traceability and reproducibility, we have made available a historical archive covering the past 15 years of GO data with a consistent format and file structure for both the ontology and annotations.

BackgroundSleep dysfunction and sleep disorders are important comorbidities of psoriasis. Not only do these sleep comorbidities contribute to reduced quality of life, but they may also lead to worsening psoriasis and increased susceptibility to cardiometabolic diseases. While psoriasis and sleep dysfunction are thought to be linked by itch, depression, and immune system dysregulation, the relationship between psoriasis and sleep dysfunction is not yet fully understood.ObjectiveWe sought to compare previous studies characterizing the gut microbiome in psoriasis and sleep dysfunction and examine the potential relevance of shared findings on cardiometabolic and overall health.MethodsWe performed literature searches of PubMed and Embase databases to find studies evaluating the gut microbiome in psoriasis, sleep dysfunction, and cardiometabolic diseases.ResultsStudies characterizing the gut microbiome in psoriasis and sleep dysfunction reveal shared findings, specifically an increased Firmicutes to Bacteroidetes ratio and reduced abundance of short chain fatty acid-producing bacteria. These dysbiotic features have also been shown to promote systemic inflammation and cardiometabolic disease.ConclusionIn favoring an increased Firmicutes to Bacteroidetes ratio and reduced abundance of short chain fatty acid-producing bacteria, sleep dysfunction could be contributing to worsening psoriasis and cardiometabolic comorbidities through intestinal dysbiosis. Future studies are needed to determine whether gut- and sleep-targeting interventions could be therapeutic in psoriasis patients with poor sleep.