Dataset Information

T cell subsets: an immunological biomarker to predict progression to clinical arthritis in ACPA-positive individuals.

ABSTRACT:

Objectives

Anticitrullinated protein antibody (ACPA)+ individuals with non-specific musculoskeletal symptoms are at risk of inflammatory arthritis (IA). This study aims to demonstrate the predictive value of T cell subset quantification for progression towards IA and compare it with previously identified clinical predictors of progression.

Methods

103 ACPA+ individuals without clinical synovitis were observed 3-monthly for 12?months and then as clinically indicated. The end point was the development of IA. Naïve, regulatory T cells (Treg) and inflammation related cells (IRCs) were quantified by flow cytometry. Areas under the ROC curve (AUC) were calculated. Adjusted logistic regressions and Cox proportional hazards models for time to progression to IA were constructed.

Results

Compared with healthy controls (age adjusted where appropriate), ACPA+ individuals demonstrated reduced naïve (22.1% of subjects) and Treg (35.8%) frequencies and elevated IRC (29.5%). Of the 103 subjects, 48(46.6%) progressed. Individually, T cell subsets were weakly predictive (AUC between 0.63 and 0.66), although the presence of 2 T cell abnormalities had high specificity. Three models were compared: model-1 used T cell subsets only, model-2 used previously published clinical parameters, model-3 combined clinical data and T cell data. Model-3 performed the best (AUC 0.79 (95% CI 0.70 to 0.89)) compared with model-1 (0.75 (0.65 to 0.86)) and particularly with model-2 (0.62 (0.54 to 0.76)) demonstrating the added value of T cell subsets. Time to progression differed significantly between high-risk, moderate-risk and low-risk groups from model-3 (p=0.001, median 15.4 months, 25.8 months and 63.4?months, respectively).

Conclusions

T cell subset dysregulation in ACPA+ individuals predates the onset of IA, predicts the risk and faster progression to IA, with added value over previously published clinical predictors of progression.

SUBMITTER: Hunt L

PROVIDER: S-EPMC5036223 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Publications

T cell subsets: an immunological biomarker to predict progression to clinical arthritis in ACPA-positive individuals.

Hunt L L Hensor E M EM Nam J J Burska A N AN Parmar R R Emery P P Ponchel F F

Annals of the rheumatic diseases 20151201 10

<h4>Objectives</h4>Anticitrullinated protein antibody (ACPA)+ individuals with non-specific musculoskeletal symptoms are at risk of inflammatory arthritis (IA). This study aims to demonstrate the predictive value of T cell subset quantification for progression towards IA and compare it with previously identified clinical predictors of progression.<h4>Methods</h4>103 ACPA+ individuals without clinical synovitis were observed 3-monthly for 12 months and then as clinically indicated. The end point ...[more]

PMID: 27613874

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Project description:BackgroundAccording to the amyloid, tau, neurodegeneration research framework classification, amyloid and tau positive (A+T+) mild cognitive impairment (MCI) individuals are defined as prodromal Alzheimer disease. This study was designed to compare the clinical and biomarker features between A+T+MCI individuals who progressed to progressive MCI (pMCI) and those who remained stable MCI (sMCI), and to identify relevant baseline clinical biomarker and features that could be used to predict progression to dementia within 2 years.MethodsWe stratified 197 A+T+MCI individuals into pMCI (n = 64) and sMCI (n = 133) over 2 years. Demographics and cognitive assessment scores, cerebrospinal fluid (CSF), and neuroimaging biomarkers (18F-florbetapir positron emission tomography mean standardized uptake value ratios [SUVR] and structural magnetic resonance imaging [MRI]) were compared between pMCI and sMCI at baseline, 12- and 24-month follow-up. Logistic regression models then were used to evaluate clinical baseline and biomarker features that predicted dementia progression in A+T+MCI.ResultspMCI individuals had higher mean 18F-florbetapir SUVR, CSF total-tau (t-tau), and p-tau181P than those in sMCI individuals. pMCI individuals performed poorer in cognitive assessments, both global and domain specific (memory, executive, language, attention, and visuospatial skills) than sMCI. At baseline, there were significant differences in regions of interest of structural MRI between the two groups, including bilateral amygdala, hippocampus and entorhinal, bilateral inferior lateral ventricle, left superior and middle temporal, left posterior and caudal anterior cingulate (P < 0.05). Baseline CSF t-tau levels and cognitive scores of Montreal cognitive assessment, functional assessment questionnaire, and everyday cognition by the patient's study partner language domain could predict progression to dementia in A+T+MCI within 2 years.ConclusionsIn future clinical trials, specific CSF and cognitive measures that predict dementia progression in A+T+MCI might be useful risk factors for assessing the risk of dementia progression.

Dataset Information

T cell subsets: an immunological biomarker to predict progression to clinical arthritis in ACPA-positive individuals.

Objectives

Methods

Results

Conclusions

Publications

T cell subsets: an immunological biomarker to predict progression to clinical arthritis in ACPA-positive individuals.

Similar Datasets

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