Explore the vast range of titles available.

The immunopathogenesis of psoriasis, a common chronic inflammatory disease of the skin, is incompletely understood. Here we demonstrate, using a combination of single cell and spatial RNA sequencing, IL-36 dependent amplification of IL-17A and TNF inflammatory responses in the absence of neutrophil proteases, which primarily occur within the supraspinous layer of the psoriatic epidermis. We further show that a subset of SFRP2 + fibroblasts in psoriasis contribute to amplification of the immune network through transition to a pro-inflammatory state. The SFRP2 + fibroblast communication network involves production of CCL13 , CCL19 and CXCL12 , connected by ligand-receptor interactions to other spatially proximate cell types: CCR2 + myeloid cells, CCR7 + LAMP3 + dendritic cells, and CXCR4 expressed on both CD8 + Tc17 cells and keratinocytes, respectively. The SFRP2 + fibroblasts also express cathepsin S, further amplifying inflammatory responses by activating IL-36G in keratinocytes. These data provide an in-depth view of psoriasis pathogenesis, which expands our understanding of the critical cellular participants to include inflammatory fibroblasts and their cellular interactions. Changes in Psoriasis and other inflammatory skin diseases during severity stages can be investigated using single cell and spatial transcriptomics. Here the authors compare different inflammatory skin diseases to emphasise differences in immune cells and inflammatory markers particularly keratinocytes and fibroblasts.

Transcriptome-wide association studies (TWAS) have emerged as a powerful tool for identifying gene-trait associations by integrating gene expression mapping studies with genome-wide association studies (GWAS). While most existing TWAS approaches focus on marginal analyses through examining one gene at a time, recent developments in TWAS fine-mapping methods enable the joint modeling of multiple genes to refine the identification of potentially causal ones. However, these fine-mapping methods have primarily focused on modeling quantitative traits and examining local genomic regions, leading to potentially suboptimal performance. Here, we present FABIO, a TWAS fine-mapping method specifically designed for binary traits that is capable of modeling all genes jointly on an entire chromosome. FABIO employs a probit model to directly link the genetically regulated expression (GReX) of genes to binary outcomes while taking into account the GReX correlation among all genes residing on a chromosome. As a result, FABIO effectively controls false discoveries while offering substantial power gains over existing TWAS fine-mapping approaches. We performed extensive simulations to evaluate the performance of FABIO and applied it for in-depth analyses of six binary disease traits in the UK Biobank. In the real datasets, FABIO significantly reduced the size of the causal gene sets by 27.9%-36.9% over existing approaches across traits. Leveraging its improved power, FABIO successfully prioritized multiple potentially causal genes associated with the diseases, including GATA3 for asthma, ABCG2 for gout, and SH2B3 for hypertension. Overall, FABIO represents an effective tool for TWAS fine-mapping of disease traits.

Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis. Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10(-60)). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10(-9)). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied. Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship.

Psoriasis and coronary artery disease (CAD) are related comorbidities that are well established, but whether a genetic basis underlies this is not well studied. We apply trans-disease meta-analysis to 11,024 psoriasis and 60,801 CAD cases, along with their associated controls, identifying one opposing and three shared genetic loci, which are confirmed through colocalization analysis. Combining results from Bayesian credible interval analysis with independent information from genomic, epigenomic, and spatial chromatin organization, we prioritize genes (including IFIH1 and IL23A ) that have implications for common molecular mechanisms involved in psoriasis and CAD inflammatory signaling. Chronic systemic inflammation has been associated with CAD and myocardial infarction, and Mendelian randomization analysis finds that CAD as an exposure can have a significant causal effect on psoriasis ( OR  =  1.11; p  =  3×10 −6 ) following adjustment for BMI and waist-hip ratio. Together, these findings suggest that systemic inflammation which causes CAD can increase the risk of psoriasis. Coronary artery disease (CAD) and psoriasis are established comorbidities, however their molecular relationship remains unclear. Here, the authors performed trans-disease meta-analysis, highlighting four genetic loci with evidence of colocalization, and prioritized genes based on multiomic data integration.

The skin serves as the primary interface between our body and the external environment and acts as a barrier against entry of physical agents, chemicals, and microbes. Keratinocytes make up the main cellular constitute of the outermost layer of the skin, contributing to the formation of the epidermis, and they are crucial for maintaining the integrity of this barrier. Beyond serving as a physical barrier component, keratinocytes actively participate in maintaining tissue homeostasis, shaping, amplifying, and regulating immune responses in skin. Keratinocytes act as sentinels, continuously monitoring changes in the environment, and, through microbial sensing, stretch, or other physical stimuli, can initiate a broad range of inflammatory responses via secretion of various cytokines, chemokines, and growth factors. This diverse function of keratinocytes contributes to the highly variable clinical manifestation of skin immune responses. In this Review, we highlight the highly diverse functions of epidermal keratinocytes and their contribution to various immune-mediated skin diseases.

Adverse drug reactions (ADRs) pose critical public health issues, affecting over 6% of hospitalized patients. While knowledge of potential drug-drug interactions (DDI) is necessary to prevent ADR, the rapid pace of drug discovery makes it challenging to maintain a strong insight into DDIs. In this study, we present a novel literature-mining framework for enhancing the predictions of DDIs and ADR types by integrating drug-gene interactions (DGIs). The ADR types were adapted from a DDI corpus, including i ) adverse effect; ii ) effect at molecular level; iii ) effect related to pharmacokinetics; and iv ) DDIs without known ADRs. By using random forest classifier our approach achieves an F-score of 0.87 across the ADRs classification using only the DDI features. We then enhanced the performance of the classifier by including DGIs (F-score = 0.90), and applied the classification model trained with the DDI corpus to identify the drugs that might interact with the drugs for cutaneous diseases. We successfully predict previously known ADRs for drugs prescribed to cutaneous diseases, and are also able to identify promising new ADRs.

Systemic sclerosis (SSc) is a devastating autoimmune disease characterized by excessive production and accumulation of extracellular matrix, leading to fibrosis of skin and other internal organs. However, the main cellular participants in SSc skin fibrosis remain incompletely understood. Here using differentiation trajectories at a single cell level, we demonstrate a dual source of extracellular matrix deposition in SSc skin from both myofibroblasts and endothelial-to-mesenchymal-transitioning cells (EndoMT). We further define a central role of Hippo pathway effectors in differentiation and homeostasis of myofibroblast and EndoMT, respectively, and show that myofibroblasts and EndoMTs function as central communication hubs that drive key pro-fibrotic signaling pathways in SSc. Together, our data help characterize myofibroblast differentiation and EndoMT phenotypes in SSc skin, and hint that modulation of the Hippo pathway may contribute in reversing the pro-fibrotic phenotypes in myofibroblasts and EndoMTs. Systemic sclerosis (SSc) is an autoimmune disease causing skin fibrosis and organ inflammation. Here the authors generate and analyze SSc skin single cell RNA sequencing data to propose contributions from both myofibroblasts and endothelial-to-mesenchymal -transitioning cells (EndoMT) to skin fibrosis, and to implicate the involvement of Hippo signaling pathways.

Systemic lupus erythematosus is a heritable autoimmune disease that predominantly affects young women. To improve our understanding of genetic etiology, we conduct multi-ancestry and multi-trait meta-analysis of genome-wide association studies, encompassing 12 systemic lupus erythematosus cohorts from 3 different ancestries and 10 genetically correlated autoimmune diseases, and identify 16 novel loci. We also perform transcriptome-wide association studies, computational drug repurposing analysis, and cell type enrichment analysis. We discover putative drug classes, including a histone deacetylase inhibitor that could be repurposed to treat lupus. We also identify multiple cell types enriched with putative target genes, such as non-classical monocytes and B cells, which may be targeted for future therapeutics. Using this newly assembled result, we further construct polygenic risk score models and demonstrate that integrating polygenic risk score with clinical lab biomarkers improves the diagnostic accuracy of systemic lupus erythematosus using the Vanderbilt BioVU and Michigan Genomics Initiative biobanks. The genetic basis of systemic lupus erythematosus is not completely understood. Here, the authors perform multi-ancestry and multi-trait meta-analyses to identify 16 novel genetic loci and demonstrate the utility of polygenic risk score in clinical risk prediction when used with conventional lab tests.

Various autoimmune diseases have sex-linked biases. Gudjonsson and colleagues find that the transcription factor VGLL3 is associated with a female-biased molecular signature linked to susceptibility to autoimmune disease. Autoimmune diseases affect 7.5% of the US population, and they are among the leading causes of death and disability. A notable feature of many autoimmune diseases is their greater prevalence in females than in males, but the underlying mechanisms of this have remained unclear. Through the use of high-resolution global transcriptome analyses, we demonstrated a female-biased molecular signature associated with susceptibility to autoimmune disease and linked this to extensive sex-dependent co-expression networks. This signature was independent of biological age and sex-hormone regulation and was regulated by the transcription factor VGLL3, which also had a strong female-biased expression. On a genome-wide level, VGLL3-regulated genes had a strong association with multiple autoimmune diseases, including lupus, scleroderma and Sjögren's syndrome, and had a prominent transcriptomic overlap with inflammatory processes in cutaneous lupus. These results identified a VGLL3-regulated network as a previously unknown inflammatory pathway that promotes female-biased autoimmunity. They demonstrate the importance of studying immunological processes in females and males separately and suggest new avenues for therapeutic development.

Granulomas are complex cellular structures composed predominantly of macrophages and lymphocytes that function to contain and kill invading pathogens. Here, we investigated the single-cell phenotypes associated with antimicrobial responses in human leprosy granulomas by applying single-cell and spatial sequencing to leprosy biopsy specimens. We focused on reversal reactions (RRs), a dynamic process whereby some patients with disseminated lepromatous leprosy (L-lep) transition toward self-limiting tuberculoid leprosy (T-lep), mounting effective antimicrobial responses. We identified a set of genes encoding proteins involved in antimicrobial responses that are differentially expressed in RR versus L-lep lesions and regulated by interferon-γ and interleukin-1β. By integrating the spatial coordinates of the key cell types and antimicrobial gene expression in RR and T-lep lesions, we constructed a map revealing the organized architecture of granulomas depicting compositional and functional layers by which macrophages, T cells, keratinocytes and fibroblasts can each contribute to the antimicrobial response.