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The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression

Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that causes multi-articular synovitis. The illness is characterized by worsening inflammatory synovitis, which causes joint swelling and pain. Synovitis erodes articular cartilage and marginal bone, resulting in joint deterioration. Thi...

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Autores principales: Hassan, Wail M., Othman, Nashwa, Daghestani, Maha, Warsy, Arjumand, Omair, Maha A., Alqurtas, Eman, Amin, Shireen, Ismail, Abdulaziz, El-Ansary, Afaf, Bhat, Ramesa Shafi, Omair, Mohammed A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526504/
https://www.ncbi.nlm.nih.gov/pubmed/37759705
http://dx.doi.org/10.3390/biom13091305
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author Hassan, Wail M.
Othman, Nashwa
Daghestani, Maha
Warsy, Arjumand
Omair, Maha A.
Alqurtas, Eman
Amin, Shireen
Ismail, Abdulaziz
El-Ansary, Afaf
Bhat, Ramesa Shafi
Omair, Mohammed A.
author_facet Hassan, Wail M.
Othman, Nashwa
Daghestani, Maha
Warsy, Arjumand
Omair, Maha A.
Alqurtas, Eman
Amin, Shireen
Ismail, Abdulaziz
El-Ansary, Afaf
Bhat, Ramesa Shafi
Omair, Mohammed A.
author_sort Hassan, Wail M.
collection PubMed
description Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that causes multi-articular synovitis. The illness is characterized by worsening inflammatory synovitis, which causes joint swelling and pain. Synovitis erodes articular cartilage and marginal bone, resulting in joint deterioration. This bone injury is expected to be permanent. Cytokines play a prominent role in the etiology of RA and could be useful as early diagnostic biomarkers. This research was carried out at Riyadh’s King Khalid University Hospital (KKUH). Patients were enrolled from the Rheumatology unit. Seventy-eight RA patients were recruited (67 (85.9%) females and 11 (14.1%) males). Patients were selected for participation by convenience sampling. Demographic data were collected, and disease activity measurements at 28 joints were recorded using the disease activity score (DAS-28). Age- and sex-matched controls from the general population were included in the study. A panel of 27 cytokines, chemokines, and growth factors was determined in patient and control sera. Binary logistic regression (BLR) and discriminant analysis (DA) were used to analyze the data. We show that multiple cytokine biomarker profiles successfully distinguished RA patients from healthy controls. IL-17, IL-4, and RANTES were among the most predictive variables and were the only biomarkers incorporated into both BLR and DA predictive models for pooled participants (men and women). In the women-only models, the significant cytokines incorporated in the model were IL-4, IL-17, MIP-1b, and RANTES for the BLR model and IL-4, IL-1Ra, GM-CSF, IL-17, and eotaxin for the DA model. The BLR and DA men-only models contained one cytokine each, eotaxin for BLR and platelet-derived growth factor-bb (PDGF-BB) for DA. We show that BLR has a higher fidelity in identifying RA patients than DA. We also found that the use of gender-specific models marginally improves detection fidelity, indicating a possible benefit in clinical diagnosis. More research is needed to determine whether this conclusion will hold true in various and larger patient populations.
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spelling pubmed-105265042023-09-28 The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression Hassan, Wail M. Othman, Nashwa Daghestani, Maha Warsy, Arjumand Omair, Maha A. Alqurtas, Eman Amin, Shireen Ismail, Abdulaziz El-Ansary, Afaf Bhat, Ramesa Shafi Omair, Mohammed A. Biomolecules Article Rheumatoid arthritis (RA) is an autoimmune inflammatory disease that causes multi-articular synovitis. The illness is characterized by worsening inflammatory synovitis, which causes joint swelling and pain. Synovitis erodes articular cartilage and marginal bone, resulting in joint deterioration. This bone injury is expected to be permanent. Cytokines play a prominent role in the etiology of RA and could be useful as early diagnostic biomarkers. This research was carried out at Riyadh’s King Khalid University Hospital (KKUH). Patients were enrolled from the Rheumatology unit. Seventy-eight RA patients were recruited (67 (85.9%) females and 11 (14.1%) males). Patients were selected for participation by convenience sampling. Demographic data were collected, and disease activity measurements at 28 joints were recorded using the disease activity score (DAS-28). Age- and sex-matched controls from the general population were included in the study. A panel of 27 cytokines, chemokines, and growth factors was determined in patient and control sera. Binary logistic regression (BLR) and discriminant analysis (DA) were used to analyze the data. We show that multiple cytokine biomarker profiles successfully distinguished RA patients from healthy controls. IL-17, IL-4, and RANTES were among the most predictive variables and were the only biomarkers incorporated into both BLR and DA predictive models for pooled participants (men and women). In the women-only models, the significant cytokines incorporated in the model were IL-4, IL-17, MIP-1b, and RANTES for the BLR model and IL-4, IL-1Ra, GM-CSF, IL-17, and eotaxin for the DA model. The BLR and DA men-only models contained one cytokine each, eotaxin for BLR and platelet-derived growth factor-bb (PDGF-BB) for DA. We show that BLR has a higher fidelity in identifying RA patients than DA. We also found that the use of gender-specific models marginally improves detection fidelity, indicating a possible benefit in clinical diagnosis. More research is needed to determine whether this conclusion will hold true in various and larger patient populations. MDPI 2023-08-25 /pmc/articles/PMC10526504/ /pubmed/37759705 http://dx.doi.org/10.3390/biom13091305 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Hassan, Wail M.
Othman, Nashwa
Daghestani, Maha
Warsy, Arjumand
Omair, Maha A.
Alqurtas, Eman
Amin, Shireen
Ismail, Abdulaziz
El-Ansary, Afaf
Bhat, Ramesa Shafi
Omair, Mohammed A.
The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression
title The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression
title_full The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression
title_fullStr The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression
title_full_unstemmed The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression
title_short The Fidelity of Rheumatoid Arthritis Multivariate Diagnostic Biomarkers Using Discriminant Analysis and Binary Logistic Regression
title_sort fidelity of rheumatoid arthritis multivariate diagnostic biomarkers using discriminant analysis and binary logistic regression
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10526504/
https://www.ncbi.nlm.nih.gov/pubmed/37759705
http://dx.doi.org/10.3390/biom13091305
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