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Special Issue "Molecular Genetics and Pathogenesis of Atopic Dermatitis and Psoriasis"

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Immunology".

Deadline for manuscript submissions: 28 February 2022.

Special Issue Editor

Dr. Shigaku Ikeda
E-Mail Website
Guest Editor
Department of Dermatology and Allergology, Juntendo University Graduate School of Medicine, Tokyo, Japan
Interests: Keratinizing and bullous disorders (including psoriasis); Hair disorders; Medical mycology; Atopic dermatitis; molecular genetics; regenerative medicine

Special Issue Information

Dear Colleagues,

Psoriasis (PSO) and atopic dermatitis (AD) are common skin diseases by which patients’ QOL has been severely affected. Despite recent progress in the development of novel therapeutics, there have not been perfect therapeutic guidelines to cover all patients. This has is due to the variability and diversity of both diseases, as PSO and AD are multifactorial diseases. In this Special Issue, I would like to summarize genetics, immunology, environmental factors, and co-morbidities on both diseases. I hope that this Special Issue will bring insight into diversity in pathophysiology, and the innovation of novel therapeutic modalities of PSO and AD.

Dr. Shigaku Ikeda
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Psoriasis
  • Atopic dermatitis
  • GWAS
  • Molecular Immunology
  • Environmental factors
  • Co-morbidities

Published Papers (1 paper)

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Research

Article
Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients
Int. J. Mol. Sci. 2021, 22(20), 10990; https://0-doi-org.brum.beds.ac.uk/10.3390/ijms222010990 - 12 Oct 2021
Viewed by 256
Abstract
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 [...] Read more.
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. Full article
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