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The article presents information on a research conducted to assess the role of innate lymphoid cells (ILCs) in the pathogenesis of rheumatic diseases. Particular focus is given to topics including a comparison between ILCs and Helper T cells, models of ILC development, and composition of ILC in psoriasis.

Background: Little is known about the extent of impairments in work and activities of daily life (ADL) in patients with psoriasis, and the influence of contextual factors such as disease-related characteristics and treatment. Therefore, this study aimed to assess these impairments in patients with psoriasis who started using biologicals/small molecule inhibitors. Methods: Using data from the prospective BioCAPTURE registry, we collected patient, disease, and treatment parameters, as well as work/ADL impairments at baseline, 6 and 12 months. Changes in impairment parameters and correlations between impairment and patient/disease characteristics were assessed using generalized estimating equations. Results: We included 194 patients in our analysis. After biological initiation, disease activity decreased significantly (PASI 11.2 at baseline versus 3.9 at 12 months, p<0.001). Work-for-pay in this cohort was lower than in the Dutch general population (53% versus 67%, p=0.01). In patients who had work-for-pay, presenteeism improved over time (5% at baseline versus 0% at 12months, p=0.04). Up to half of the patients reported impairments in ADL, which did not change over time. Associations between impairments and contextual factors varied, but all impairments were associated with worse mental/physical general functioning. Conclusion: Patients with psoriasis using biologicals are less likely to have work-for-pay. Treatment improves the work productivity of employed patients, but we were unable to detect changes in ADL performance. [ABSTRACT FROM AUTHOR]

Patients with psoriasis are at risk of developing psoriatic arthritis, which can lead to joint damage. While screening questionnaires have been developed, their performance varies. The objective of this study was to develop a referral tool for dermatologists to identify psoriasis patients with concomitant psoriatic arthritis for rheumatological referral. This study used data from the DAPPER study, in which psoriasis patients were screened by a rheumatologist for the presence of concomitant psoriatic arthritis. Multivariable regression analysis was used to identify predictive variables for the presence of concomitant psoriatic arthritis: treatment history with conventional systemic drugs (odds ratio (OR) 2.97, 95% confidence interval (95% CI) 1.01–8.74, p=0.04), treatment history with biologicals/small molecule inhibitors (OR 2.90, 95% CI 1.52– 5.53, p=0.01), patient-reported history of joint pain not caused by trauma (OR 4.23, 95% CI 1.21–14.79, p=0.01), patient-reported history of swollen joints (OR 4.25, 95% CI 2.17–8.32, p<0.001), and patientreported history of sausage-like swollen digits (OR 2.38, 95% CI 1.25–4.55, p=0.01). Based on these variables, a referral tool was created with an area under the curve of 0.82. This referral tool could be used to aid dermatologists to identify psoriasis patients with concomitant psoriatic arthritis, who may benefit from rheumatological referral. [ABSTRACT FROM AUTHOR]

Patients with psoriasis are at risk of developing psoriatic arthritis, which can lead to irreversible joint damage. However, a proportion of patients with psoriasis and concomitant psoriatic arthritis remain undiscovered in practice. The aims of this study were: to prospectively determine prevalence, characteristics, and disease burden of psoriatic arthritis in a psoriasis population; and to determine the prevalence and characteristics of patients with active psoriatic arthritis, who were not under rheumatological care. Patients with psoriasis were screened by a rheumatologist at the dermatology outpatient clinic for psoriatic arthritis. Patients with suspected active psoriatic arthritis who were not seeing a rheumatologist were referred to a rheumatologist for confirmation. The total prevalence of psoriatic arthritis in this observational, prospective cohort (n = 303) was 24%. Patients with psoriasis with concomitant psoriatic arthritis had longer duration of skin disease and more often a treatment history with systemic therapies. In this academic, specialized, setting, 2.3% of patients (n = 7), were not receiving rheumatological care despite having active psoriatic arthritis. These patients were characterized by a combination of low (perceived) disease burden and low yield of screening questionnaires, making it difficult for dermatologists to discover psoriatic arthritis in these patients. Thus, screening for more subtle active arthritis in patients with psoriasis in a dermatology setting could be improved. [ABSTRACT FROM AUTHOR]

Psoriasis (Pso) is a chronic inflammatory skin disease, and up to 30% of Pso patients develop psoriatic arthritis (PsA), which can lead to irreversible joint damage. Early detection of PsA in Pso patients is crucial for timely treatment but difficult for dermatologists to implement. We, therefore, aimed to find disease-specific immune profiles, discriminating Pso from PsA patients, possibly facilitating the correct identification of Pso patients in need of referral to a rheumatology clinic. The phenotypes of peripheral blood immune cells of consecutive Pso and PsA patients were analyzed, and disease-specific immune profiles were identified via a machine learning approach. This approach resulted in a random forest classification model capable of distinguishing PsA from Pso (mean AUC = 0.95). Key PsA-classifying cell subsets selected included increased proportions of differentiated CD4+CD196+CD183-CD194+ and CD4+CD196-CD183-CD194+ T-cells and reduced proportions of CD196+ and CD197+ monocytes, memory CD4+ and CD8+ T-cell subsets and CD4+ regulatory T-cells. Within PsA, joint scores showed an association with memory CD8+CD45RA-CD197- effector T-cells and CD197+ monocytes. To conclude, through the integration of in-depth flow cytometry and machine learning, we identified an immune cell profile discriminating PsA from Pso. This immune profile may aid in timely diagnosing PsA in Pso. [ABSTRACT FROM AUTHOR]