Quantifying circulating Th17 cells by qPCR: potential as diagnostic biomarker for rheumatoid arthritis

Abstract

Objective The diagnosis of RA patients remains a challenge, especially in ACPA-negative disease. Novel T-cell subsets, particularly Th17 may be useful, although data on Th17 frequency using flow cytometry in RA are conflicting. We investigated whether a novel epigenetic qPCR assay for the quantification of Th17 could differentiate patients with RA from those with symptoms evolving towards an alternative diagnosis. Methods We used a qPCR assay measuring the extent of the methylation at a key position in the IL-17 and CD4 genes. Assays were performed on whole blood from 49 healthy controls (HC) and 165 early arthritis clinic patients. Flow cytometry was further used to detect the expression of CXCR4 on Th17 cells. Results In 75 inflammatory arthritis patients who progressed to RA, the qPCR assays showed significantly fewer Th17 cells compared with 90 patients who did not (P<0.0001). Regression models demonstrated a high predictive value for RA development (75.8% correct prediction), and particularly for the ACPA-negative group (n = 125) where Th17 and swollen joint count (SJC) were the only predictors (73% correct prediction). The chemokine receptor CXCR4 had significantly higher expression on Th17 from early RA patients (n = 11) compared with HC (n = 15). Conclusion The results of the epigenetic qPCR assay showed that low levels of Th17 cells were predictive of developing RA, particularly in the ACPA-negative patients. This could have value for insights into pathogenesis and management. The results suggest the recruitment of Th17 to the inflammatory disease site, consistent with high CXCR4 expression.

Circulating Immune Cell Composition and Cancer Risk: A Prospective Study Using Epigenetic Cell Count Measures

“…We previously reported a significant positive association between the ratio of FOXP3+ to total CD3+ T-lymphocytes -"ImmunoCRIT" immuno-tolerance ratio -and risk of lung, colorectal, and ER-negative breast cancers (7). While the associations of cancer risk with this ratio remain fully present and statistically significant within the sub-set of study participants used for the present study, our present analyses, using a more generalized modeling framework to examine the (28,29) or M1 and M2 macrophages (30), which all might have differential impacts on early cancer development, were not available for the current study, but are in development (6,(31)(32)(33). Although, our study is based on only a single blood sample per person, the findings from our embedded longitudinal reproducibility sub-study showed good correlations between individuals' relative immune cell counts measured repeatedly over a longer prospective time interval.…”

T-cell subset abnormalities predict progression along the Inflammatory Arthritis disease continuum: implications for management

“…Although the identification of Th17 cells using surrogate markers (CD4+ CD161+ CCR6+ CXCR3−) is now being developed for routine quantification protocols, discrepancies exist, limiting their utility as biomarker. Alternative techniques such as those based on the epigenetic reprograming of the IL-17 gene in Th17 cells (as for FoxP3 in Treg), may bring more accurate data 32 . The combination of Th17 with naïve and Treg cells may provide an even more comprehensive representation of T-cell in the IA-continuum and increase further the predictability of T-cell subsets.…”

Biological impact of iberdomide in patients with active systemic lupus erythematosus

“…Flow cytometry (Covance, Indianapolis, Indiana, USA) was used to analyse B cells (CD19+ and CD20+), T cells (including CD4+ and CD8+), plasmablasts, pDCs and myeloid dendritic cells (mDCs). T helper 17 (Th17) cells, regulatory T cells (Tregs) and T follicular helper (Tfh) cells were measured by epigenetic assays (Epiontis ID; Epiontis GmbH, Berlin, Germany), an approach that correlates strongly with flow cytometry 15–17…”