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Background Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Knowledge gaps include whether molecular endotypes of psoriasis underlie distinct clinical phenotypes and the positive and negative molecular regulators of disease severity across tissue compartments. Methods We performed comprehensive RNA sequencing of skin and blood (n = 718) from prospectively-recruited, deeply-phenotyped discovery and replication cohorts of 146 subjects with moderate-to-severe chronic plaque psoriasis initiating TNF-inhibitor (adalimumab) or IL-12/23-inhibitor (ustekinumab) therapy. Results Here we show, using two complementary dimensionality reduction methods, that co-expressed gene modules and factors within skin and blood are significantly associated with psoriasis phenotypes and disease severity. We identify a 14-gene signature negatively associated with BMI in nonlesional skin and with disease severity in lesional skin. Genotype integration reveals that HLA-DQA1*01 and HLA-DRB1*15 genotypes are positively associated with baseline psoriasis severity. Using explainable machine learning models, we define two disease severity-associated gene modules in lesional skin - one positive, one negatively-associated - and a 9-gene signature in lesional skin predictive of disease severity. Disease severity signatures in blood are only seen following adalimumab exposure, suggesting greater systemic impact of adalimumab compared to ustekinumab, in line with its side effect profile. In contrast, a gene signature in blood linked to HLA-C*06:02 status is independent of disease severity or drug. Conclusions These findings delineate gene-environmental and genetic effects on the psoriasis transcriptome linked to disease severity. Plain language summary Psoriasis is a common and debilitating skin disease, linked to other inflammatory conditions. A lot is known about what causes psoriasis and the factors that influence it, but doctors still cannot offer personalised treatments. This is because it has been difficult to understand what makes psoriasis more or less severe, why people respond differently to treatment, or why some people develop related diseases. To help address this, we collected skin and blood samples and personal information from people with severe psoriasis across the United Kingdom. Using computer-based methods, we found shared biological processes that link the disease with obesity and help predict its severity. Rider, Grantham, Smith, Watson et al. integrate multiomic data from patients with psoriasis using dimensionality reduction and machine learning techniques. This approach identifies biological relationships between genetic background, clinical features and disease severity, providing insight into disease variability across individuals.

The authors commendably addressed this in part by undertaking a survey of dermatologists through a national group (the UK Dermatology Clinical Trials Network; appendix p 18).13 The results of this survey suggested that UK dermatologists were willing to accept a 25% reduction in effectiveness if this was balanced against a 10% reduction in mortality rate for “tetracycline to have potential as a primary treatment for bullous pemphigoid”.13 However, it is not entirely clear how the data from the survey fed into the setting of the primary endpoints or if the sample size was sufficient to detect a clinically relevant non-inferiority effectiveness margin. [...]although the authors aimed to restrict the use of topical corticosteroids for symptomatic relief, we do not know whether the amount applied by both groups was the same. [...]doxycycline is clearly safer than prednisolone for the treatment of bullous pemphigoid and demonstrates a reduced success rate, based on achieving three or fewer blisters, at 6 weeks. References 1 SM Langan, L Smeeth, R Hubbard, KM Fleming, CJ Smith, J West, Bullous pemphigoid and pemphigus vulgaris-incidence and mortality in the UK: population based cohort study, BMJ, Vol. 337, 2008, a180 2 Z Ren, DY Hsu, J Brieva, Hospitalization, inpatient burden and comorbidities associated with bullous pemphigoid in the USA, Br J Dermatol, Vol. 176, 2017, 87-99 3 E Schmidt, D Zillikens, Pemphigoid diseases, Lancet, Vol. 381, 2013, 320-332 4 P Joly, JC Roujeau, J Benichou, A comparison of oral and topical corticosteroids in patients with bullous pemphigoid, N Engl...

Despite increased understanding of psoriasis pathogenesis, molecular classification of clinical phenotypes and disease severity is poorly defined. Knowledge gaps include whether molecular endotypes of psoriasis underlie distinct clinical phenotypes and the positive and negative molecular regulators of disease severity across tissue compartments. We performed comprehensive RNA-sequencing of skin and blood (n=718) from prospectively-recruited, deeply-phenotyped discovery and replication cohorts of 146 subjects with moderate-to-severe psoriasis initiating TNF-inhibitor (adalimumab) or IL-12/23-inhibitor (ustekinumab) therapy. Using two complementary methods for dimensionality reduction, we defined distinct but interconnected co-expression modules and factors within skin and blood that were significantly associated with disease phenotypes and disease severity, as measured by Psoriasis Area Severity Index (PASI). We identified a 14-gene signature negatively associated with BMI in nonlesional skin and disease severity in lesional skin, respectively. Genotype integration revealed that HLA-DQA1*01 and HLA-DRB1*15 genotypes were positively associated with baseline disease severity. Using Gaussian process regression followed by SHAP (SHapley Additive exPlanations), we defined two core drug independent and disease severity-associated gene modules in lesional skin - one positive, one negative - and a lesional 9-gene signature predictive of disease severity. Disease severity signatures in blood were only seen following adalimumab exposure, suggesting greater systemic impact of adalimumab compared to ustekinumab, in line with its side effect profile. In contrast, a gene signature in blood linked to HLA-C*06:02 status was independent of disease severity or drug. These findings delineate gene-environmental and genetic effects on the psoriasis transcriptome linked to disease severity. Psoriasis is a common and debilitating skin disease, linked to multiple other inflammatory conditions. A lot is known about the mechanism of psoriasis and its inherited and external influences. Despite this, doctors cannot yet offer personalised treatments as it has been difficult to discover whether biological pathways are associated with disease severity, response to treatment or a person’s likelihood of having other linked diseases. To help address this, we collected skin and blood samples and the personal characteristics of a group of people with severe psoriasis across the United Kingdom. Using computer-based methods, we discovered common biological processes underlying different psoriasis types, including genes that connect psoriasis severity with obesity, and another set of genes that help predict disease severity.