Transcriptomic profiling of chronic hand eczema skin reveals shared immune pathways and molecular drivers across subtypes.

Background: Chronic hand eczema (CHE) is a common skin disease with different subtypes, but knowledge of the molecular patterns associated with each subtype is limited.

Objective: We sought to characterize the CHE transcriptome across subtypes.

Methods: Using RNA sequencing, we studied the transcriptome of 220 full-thickness skin biopsy samples collected from palms, dorsa, and arms from 96 patients with CHE and/or atopic dermatitis (AD) and 32 healthy controls.

Inflammatory plasma signature of chronic hand eczema: Associations with aetiological and clinical subtypes.

Background: Chronic hand eczema (CHE) is a highly prevalent, heterogeneous, skin disease that encompasses different aetiological and clinical subtypes. Severe CHE without atopic dermatitis has been associated with systemic inflammation; yet it remains unknown if specific CHE subtypes leave distinct, systemic, molecular signatures.

Objectives: To characterize the inflammatory plasma signature of different aetiological and clinical CHE subtypes.

Circulating biomarkers are associated with disease severity of chronic hand eczema and atopic dermatitis.

Background: Although chronic hand eczema (CHE) is a highly prevalent and disabling skin disease, it is currently unknown if CHE is associated with systemic inflammation.

Objectives: To characterize the plasma inflammatory signature of CHE.

Methods: Using Proximity Extension Assay technology, we assessed 266 inflammatory and cardiovascular disease risk proteins in the plasma of 40 healthy controls, 57 patients with atopic dermatitis (AD) with active lesions, 11 with CHE and a history of AD (CHEPREVIOUS_AD), and 40 with CHE and no history of AD (CHENO_AD).

IL-17 Pathway Members as Potential Biomarkers of Effective Systemic Treatment and Cardiovascular Disease in Patients with Moderate-to-Severe Psoriasis.

Psoriasis is a chronic inflammatory condition associated with atherosclerotic cardiovascular disease (CVD). Systemic anti-psoriatic treatments mainly include methotrexate and biological therapies targeting TNF, IL-12/23 and IL-17A. We profiled plasma proteins from patients with moderate-to-severe psoriasis to explore potential biomarkers of effective systemic treatment and their relationship to CVD.

Biomarkers of subclinical atherosclerosis in patients with psoriasis.

Psoriasis is linked with increased risk of cardiovascular disease (CVD) that is underestimated by traditional risk stratification. We conducted a large-scale plasma proteomic analysis by use of a proximity extension assay in 85 patients with a history of moderate-to-severe psoriasis with or without established atherosclerotic CVD. Differentially expressed proteins associated with CVD were correlated with subclinical atherosclerotic markers including vascular inflammation determined by F-fluorodeoxyglucose positron emission tomography/computed tomography, carotid intima-media thickness (CIMT), carotid artery plaques, and coronary artery calcium score (CCS) in the patients without CVD and statin treatment.

Neutrophil Pathways of Inflammation Characterize the Blood Transcriptomic Signature of Patients with Psoriasis and Cardiovascular Disease.

Background: Patients with psoriasis have an increased risk of atherosclerotic cardiovascular disease (CVD). The molecular mechanisms behind this connection are not fully understood, but the involvement of neutrophils have drawn attention as a shared inflammatory factor.

Methods: RNA sequencing using the Illumina platform was performed on blood from 38 patients with moderate to severe psoriasis; approximately half had prior CVD.

Multiscale Biology of Cardiovascular Risk in Psoriasis: Protocol for a Case-Control Study.

Background: Patients with psoriasis have increased risk of cardiovascular disease (CVD) independent of traditional risk factors. The molecular mechanisms underlying the psoriasis-CVD connection are not fully understood. Advances in high-throughput molecular profiling technologies and computational analysis techniques offer new opportunities to improve the understanding of disease connections.