Patients on therapeutic immunosuppressants for immune-mediated inflammatory diseases were excluded from COVID-19 vaccine trials. We therefore aimed to evaluate humoral and cellular immune responses to COVID-19 vaccine BNT162b2 (Pfizer-BioNTech) in patients taking methotrexate and commonly used targeted biological therapies, compared with healthy controls. Given the roll-out of extended interval vaccination programmes to maximise population coverage, we present findings after the first dose. In this cohort study, we recruited consecutive patients with a dermatologist-confirmed diagnosis of psoriasis who were receiving methotrexate or targeted biological monotherapy (tumour necrosis factor [TNF] inhibitors, interleukin [IL]-17 inhibitors, or IL-23 inhibitors) from a specialist psoriasis centre serving London and South East England. Consecutive volunteers without psoriasis and not receiving systemic immunosuppression who presented for vaccination at Guy's and St Thomas' NHS Foundation Trust (London, UK) were included as the healthy control cohort. All participants had to be eligible to receive the BNT162b2 vaccine. Immunogenicity was evaluated immediately before and on day 28 (±2 days) after vaccination. The primary outcomes were humoral immunity to the SARS-CoV-2 spike glycoprotein, defined as neutralising antibody responses to wild-type SARS-CoV-2, and spike-specific T-cell responses (including interferon-γ, IL-2, and IL-21) 28 days after vaccination. Between Jan 14 and April 4, 2021, 84 patients with psoriasis (17 on methotrexate, 27 on TNF inhibitors, 15 on IL-17 inhibitors, and 25 on IL-23 inhibitors) and 17 healthy controls were included. The study population had a median age of 43 years (IQR 31–52), with 56 (55%) males, 45 (45%) females, and 85 (84%) participants of White ethnicity. Seroconversion rates were lower in patients receiving immunosuppressants (60 [78%; 95% CI 67–87] of 77) than in controls (17 [100%; 80–100] of 17), with the lowest rate in those receiving methotrexate (seven [47%; 21–73] of 15). Neutralising activity against wild-type SARS-CoV-2 was significantly lower in patients receiving methotrexate (median 50% inhibitory dilution 129 [IQR 40–236]) than in controls (317 [213–487], p=0·0032), but was preserved in those receiving targeted biologics (269 [141–418]). Neutralising titres against the B.1.1.7 variant were similarly low in all participants. Cellular immune responses were induced in all groups, and were not attenuated in patients receiving methotrexate or targeted biologics compared with controls. Functional humoral immunity to a single dose of BNT162b2 is impaired by methotrexate but not by targeted biologics, whereas cellular responses are preserved. Seroconversion alone might not adequately reflect vaccine immunogenicity in individuals with immune-mediated inflammatory diseases receiving therapeutic immunosuppression. Real-world pharmacovigilance studies will determine how these findings reflect clinical effectiveness. UK National Institute for Health Research.

Interleukin (IL)–36α, IL-36β, and IL-36γ are innate mediators of acute epithelial inflammation. We sought to demonstrate that these cytokines are also required for the pathogenesis of plaque psoriasis, a common and chronic skin disorder, caused by abnormal T helper 17 (T_H17) cell activation. To investigate this possibility, we first defined the genes that are induced by IL-36 cytokines in primary human keratinocytes. This enabled us to demonstrate a significant IL-36 signature among the transcripts that are up-regulated in plaque psoriasis and the susceptibility loci associated with the disease in genome-wide studies. Next, we investigated the impact of in vivo and ex vivo IL-36 receptor blockade using a neutralizing antibody or a recombinant antagonist. Both inhibitors had marked anti-inflammatory effects on psoriatic skin, demonstrated by statistically significant reductions in IL-17 expression, keratinocyte activation, and leukocyte infiltration. Finally, we explored the potential safety profile associated with IL-36 blockade by phenotyping 12 individuals carrying knockout mutations of the IL-36 receptor gene. We found that normal immune function was broadly preserved in these individuals, suggesting that IL-36 signaling inhibition would not substantially compromise host defenses. These observations, which integrate the results of transcriptomics and model system analysis, pave the way for early-stage clinical trials of IL-36 antagonists.

Biologic therapies targeting the IL-23/IL-17 axis have transformed the treatment of psoriasis. However, the early mechanisms of action of these drugs remain poorly understood. Here, we perform longitudinal single-cell RNA-sequencing in affected individuals receiving IL-23 inhibitor therapy. By profiling skin at baseline, day 3 and day 14 of treatment, we demonstrate that IL-23 blockade causes marked gene expression shifts, with fibroblast and myeloid populations displaying the most extensive changes at day 3. We also identify a transient WNT5A+/IL24+ fibroblast state, which is only detectable in lesional skin. In-silico and in-vitro studies indicate that signals stemming from these WNT5A+/IL24+ fibroblasts upregulate multiple inflammatory genes in keratinocytes. Importantly, the abundance of WNT5A+/IL24+ fibroblasts is significantly reduced after treatment. This observation is validated in-silico, by deconvolution of multiple transcriptomic datasets, and experimentally, by RNA in-situ hybridization. These findings demonstrate that the evolution of inflammatory fibroblast states is a key feature of resolving psoriasis skin.

Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images via neural networks to make predictions. A focus of deep learning research is skin lesion triage to detect cancer, but this may not translate to the wider scope of >2000 other skin diseases. We searched for studies applying deep learning to skin images, excluding benign/malignant lesions (1/1/2000-23/6/2022, PROSPERO CRD42022309935). The primary outcome was accuracy of deep learning algorithms in disease diagnosis or severity assessment. We modified QUADAS-2 for quality assessment. Of 13,857 references identified, 64 were included. The most studied diseases were acne, psoriasis, eczema, rosacea, vitiligo, urticaria. Deep learning algorithms had high specificity and variable sensitivity in diagnosing these conditions. Accuracy of algorithms in diagnosing acne (median 94%, IQR 86–98; n = 11), rosacea (94%, 90–97; n = 4), eczema (93%, 90–99; n = 9) and psoriasis (89%, 78–92; n = 8) was high. Accuracy for grading severity was highest for psoriasis (range 93–100%, n = 2), eczema (88%, n = 1), and acne (67–86%, n = 4). However, 59 (92%) studies had high risk-of-bias judgements and 62 (97%) had high-level applicability concerns. Only 12 (19%) reported participant ethnicity/skin type. Twenty-four (37.5%) evaluated the algorithm in an independent dataset, clinical setting or prospectively. These data indicate potential of deep learning image analysis in diagnosing and monitoring common skin diseases. Current research has important methodological/reporting limitations. Real-world, prospectively-acquired image datasets with external validation/testing will advance deep learning beyond the current experimental phase towards clinically-useful tools to mitigate rising health and cost impacts of skin disease.

Psoriasis is a common, debilitating immune-mediated skin disease. Genetic studies have identified biological mechanisms of psoriasis risk, including those targeted by effective therapies. However, the genetic liability to psoriasis is not fully explained by variation at robustly identified risk loci. To refine the genetic map of psoriasis susceptibility we meta-analysed 18 GWAS comprising 36,466 cases and 458,078 controls and identified 109 distinct psoriasis susceptibility loci, including 46 that have not been previously reported. These include susceptibility variants at loci in which the therapeutic targets IL17RA and AHR are encoded, and deleterious coding variants supporting potential new drug targets (including in STAP2, CPVL and POU2F3). We conducted a transcriptome-wide association study to identify regulatory effects of psoriasis susceptibility variants and cross-referenced these against single cell expression profiles in psoriasis-affected skin, highlighting roles for the transcriptional regulation of haematopoietic cell development and epigenetic modulation of interferon signalling in psoriasis pathobiology.

The routine use of targeted systemic immunomodulatory therapies has transformed outcomes for people with severe psoriasis, with skin clearance (clinical remission) rates up to 60% at one year of biologic treatment. However, psoriasis may recur following drug withdrawal, and so patients tend to remain on costly treatment indefinitely. Here, we review research into the 'inflammatory memory' in resolved psoriasis skin and the potential mechanisms leading to psoriasis recurrence following drug withdrawal. Research has implicated immune cells such as tissue-resident memory T cells, Langerhans cells and dermal dendritic cells, and there is growing interest in keratinocytes and fibroblasts. A better understanding of the interactions between these cell populations, enabled by single-cell technologies, will help to elucidate the events underpinning the shift from remission to recurrence. This may inform the development of personalised strategies for sustaining remission while reducing long-term drug burden.