The Utility of Immune Function Profiling in Rheumatoid Arthritis Therapeutic Efficacy Monitoring
type: CreativeWork
description: Rheumatoid Arthritis (RA) is a chronic, systemic autoimmune disease, primarily affecting the small joints of the hands, wrists and feet. Disease onset is insidious with classical symptoms including pain, morning stiffness, and persistent synovitis; accompanied by fatigue, malaise and weight loss. RA patients also suffer from a number of extra-articular manifestations and additional comorbidities, including rheumatoid nodules and scleritis; as well as an increased risk of cardiovascular disease (CVD), lymphoma and infection. Ultimately, RA is a devastatingly progressive disease, if a diagnosis and an effective therapeutic regimen is not established quickly. Identifying when a therapy is proving ineffective can be difficult, however, and is reliant upon accurate formal joint counts, CRP measurements and patient global assessments. These are potentially insensitive means of assessing remission and may result in delayed changes to therapeutic regimens. The identification of new biomarkers to improve the predictive value of these evaluation models would therefore greatly benefit patient care. Based upon current evidence, it has been hypothesized that RA patients who fail to make a clinical improvement following the initiation of csDMARD and bDMARD therapeutic regimens are identifiable by their profile of the following CD4+ T-cell populations: follicular helper, memory helper, antigen-specific and naturally-occurring regulatory CD4+ T-cells. As such, flow cytometric assays have developed for the identification and enumeration of these respective CD4+ T-cell populations; the relative and absolute counts of which were investigated within a cohort of healthy controls, with normal distributions established. Subsequently, we have identified distinct alterations to the CD4+ T-cell compartments of newly-diagnosed, treatment-naïve and longstanding RA patients, with clear associations with patient clinical outcomes observed. Of notable significance, the relative distribution of CC…
abstract: Rheumatoid Arthritis (RA) is a chronic, systemic autoimmune disease, primarily affecting the small joints of the hands, wrists and feet. Disease onset is insidious with classical symptoms including pain, morning stiffness, and persistent synovitis; accompanied by fatigue, malaise and weight loss. RA patients also suffer from a number of extra-articular manifestations and additional comorbidities, including rheumatoid nodules and scleritis; as well as an increased risk of cardiovascular disease (CVD), lymphoma and infection. Ultimately, RA is a devastatingly progressive disease, if a diagnosis and an effective therapeutic regimen is not established quickly. Identifying when a therapy is proving ineffective can be difficult, however, and is reliant upon accurate formal joint counts, CRP measurements and patient global assessments. These are potentially insensitive means of assessing remission and may result in delayed changes to therapeutic regimens. The identification of new biomarkers to improve the predictive value of these evaluation models would therefore greatly benefit patient care. Based upon current evidence, it has been hypothesized that RA patients who fail to make a clinical improvement following the initiation of csDMARD and bDMARD therapeutic regimens are identifiable by their profile of the following CD4+ T-cell populations: follicular helper, memory helper, antigen-specific and naturally-occurring regulatory CD4+ T-cells. As such, flow cytometric assays have developed for the identification and enumeration of these respective CD4+ T-cell populations; the relative and absolute counts of which were investigated within a cohort of healthy controls, with normal distributions established. Subsequently, we have identified distinct alterations to the CD4+ T-cell compartments of newly-diagnosed, treatment-naïve and longstanding RA patients, with clear associations with patient clinical outcomes observed. Of notable significance, the relative distribution of CC…
author: Fox, Hannah Louise
language: en
date published: 2018
date modified: 2026-07-24T03:43:34Z
provider: Oxford Brookes University
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: Oxford Brookes University

PropertyValue
property ID: DOI
value: 10.24384/5ryj-j552