دورية أكاديمية
أعرض في EDS

Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients.

التفاصيل البيبلوغرافية
العنوان: Blood-Based Immune Profiling Combined with Machine Learning Discriminates Psoriatic Arthritis from Psoriasis Patients.
المؤلفون: Mulder MLM; Department of Rheumatology, Sint Maartenskliniek, 6524 Nijmegen, The Netherlands.; Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., He X; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., van den Reek JMPA; Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., Urbano PCM; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., Kaffa C; Center for Molecular and Biomolecular Informatics, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., Wang X; Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4475 Belvaux, Luxembourg.; College of Computer Science, Qinghai Normal University, Xining 810000, China., van Cranenbroek B; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., van Rijssen E; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., van den Hoogen FHJ; Department of Rheumatology, Sint Maartenskliniek, 6524 Nijmegen, The Netherlands., Joosten I; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., Alkema W; Institute for Life Science and Technology, Hanze University of Applied Sciences, 9727 Groningen, The Netherlands.; TenWise BV, 5344 KX Oss, The Netherlands., de Jong EMGJ; Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., Smeets RL; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands.; Department of Laboratory Medicine, Laboratory for Diagnostics, Radboud University Medical Center, 6524 Nijmegen, The Netherlands., Wenink MH; Department of Rheumatology, Sint Maartenskliniek, 6524 Nijmegen, The Netherlands., Koenen HJPM; Department of Laboratory Medicine-Medical Immunology, Department of Dermatology, Radboud University Medical Center, 6524 Nijmegen, The Netherlands.
المصدر: International journal of molecular sciences [Int J Mol Sci] 2021 Oct 12; Vol. 22 (20). Date of Electronic Publication: 2021 Oct 12.
نوع المنشور: Journal Article
اللغة: English
بيانات الدورية: Publisher: MDPI Country of Publication: Switzerland NLM ID: 101092791 Publication Model: Electronic Cited Medium: Internet ISSN: 1422-0067 (Electronic) Linking ISSN: 14220067 NLM ISO Abbreviation: Int J Mol Sci Subsets: MEDLINE
أسماء مطبوعة: Original Publication: Basel, Switzerland : MDPI, [2000-
مواضيع طبية MeSH: Machine Learning*, Arthritis, Psoriatic/*diagnosis , B-Lymphocyte Subsets/*metabolism , Psoriasis/*diagnosis , T-Lymphocyte Subsets/*metabolism, Adult ; Aged ; Area Under Curve ; B-Lymphocyte Subsets/cytology ; B-Lymphocyte Subsets/immunology ; Diagnosis, Differential ; Discriminant Analysis ; Female ; Humans ; Middle Aged ; Monocytes/cytology ; Monocytes/immunology ; Monocytes/metabolism ; Phenotype ; ROC Curve ; Receptors, Chemokine/metabolism ; T-Lymphocyte Subsets/cytology ; T-Lymphocyte Subsets/immunology ; T-Lymphocytes, Regulatory/cytology ; T-Lymphocytes, Regulatory/immunology ; T-Lymphocytes, Regulatory/metabolism
مستخلص: 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.
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معلومات مُعتمدة: N/A the regional Junior Researcher Grant from the Sint Maartenskliniek, Nijmegen and the Radboud University Medical Center, Nijmegen, the Netherlands; NSFC 61263039 and NSFC 11101321 National Natural Science Foundation of China; QHSTDP 2017-ZJ-768 and QHSTDP 2018-ZJ-776 Qinghai Science & Technology Department Project
فهرسة مساهمة: Keywords: detection; flow cytometry; immune profile; machine learning; psoriasis; psoriatic arthritis
المشرفين على المادة: 0 (Receptors, Chemokine)
تواريخ الأحداث: Date Created: 20211023 Date Completed: 20211227 Latest Revision: 20211227
رمز التحديث: 20240628
مُعرف محوري في PubMed: PMC8538368
DOI: 10.3390/ijms222010990
PMID: 34681660
قاعدة البيانات: MEDLINE
الوصف
تدمد:1422-0067
DOI:10.3390/ijms222010990