Multi‐omics profiling of chronic immune‐mediated skin diseases: SKINERGY protocol and strategic evaluation

Abstract

Background: The Dutch flagship project Next Generation ImmunoDermatology (NGID) aims to profile five chronic immune-mediated inflammatory skin diseases: atopic dermatitis (AD), plaque psoriasis (PSO), hidradenitis suppurativa (HS), chronic spontaneous urticaria (CSU) and cutaneous lupus erythematosus (CLE) in comparison with cutaneous T-cell lymphoma subtype mycosis fungoides (MF) and healthy volunteers. Within NGID, a clinical study entitled: ‘SKIN disease profiling by an Exploratory, pRospective, biomarker study in dermatoloGY practice (SKINERGY)’ will be conducted as a multicentre, parallel-cohort, open-label, observational, longitudinal basket study. Objectives: Objectives include evaluation of disease-related characteristics in comparison to those of healthy volunteers and evaluation of biomarkers for disease stratification and (targeted) treatment response in patients in a real-world clinical setting. Additionally, differences and similarities in disease characteristics between diseases, changes over time, and profiles of responders versus non-responders will be evaluated. Methods: Patients with AD (N = 120), PSO (N = 160), HS (N = 80), CSU (N = 120) and CLE (N = 120) will be enrolled in groups of N ≤ 40 patients per treatment. Matched healthy volunteers (N = 120) and the MF cohort (N = 120) will serve as control groups. Assessments include blood sampling, skin punch biopsies, tape stripping, skin swabs, (multimodal) imaging, tele-health and patient- and physician-reported outcomes. This manuscript describes the study protocol prior to data collection and its strategic evaluation of multi-omics profiling. Patient advocacy groups co-defined the research agenda and contributed to study design and informed consent document development, ensuring alignment with patients' needs and real-world relevance. Results: SKINERGY will generate a machine learning-ready dataset with information about changes in various biomarkers over time, including histology, metabolomics, spatial proteomics, transcriptomics, lipidomics, microbiomics, imaging biomarkers, tele-health, patient-reported outcome measures (PROMs) and clinical parameters. Conclusion: Identified biomarker profiles within SKINERGY may guide targeted treatment selection, enhance targeted therapeutic response in clinical practice and improve understanding of disease pathology in chronic immune-mediated skin diseases.