FOXP3 TSDR Measurement Could Assist Variant Classification and Diagnosis of IPEX Syndrome.

Pathogenic FOXP3 variants cause immune dysregulation polyendocrinopathy enteropathy X-linked (IPEX) syndrome, a progressive autoimmune disease resulting from disruption of the regulatory T cell (Treg) compartment. Assigning pathogenicity to novel variants in FOXP3 is challenging due to the heterogeneous phenotype and variable immunological abnormalities. The number of cells with demethylation at the Treg cell-specific demethylated region (TSDR) is an independent biomarker of IPEX. We aimed to investigate if diagnosing IPEX at presentation with isolated diabetes could allow for effective monitoring of disease progression and assess whether TSDR analysis can aid FOXP3 variant classification and predict disease course. We describe a large genetically diagnosed IPEX cohort (n = 65) and 13 individuals with other monogenic autoimmunity subtypes in whom we quantified the proportion of cells with FOXP3 TSDR demethylation, normalized to the number with CD4 demethylation (%TSDR/CD4) and compare them to 29 unaffected controls. IPEX patients presenting with isolated diabetes (50/65, 77%) often later developed enteropathy (20/50, 40%) with a median interval of 23.5 weeks. %TSDR/CD4 was a good discriminator of IPEX vs. unaffected controls (ROC-AUC 0.81, median 13.6% vs. 8.5%, p < 0.0001) with higher levels of demethylation associated with more severe disease. Patients with other monogenic autoimmunity had a similar %TSDR/CD4 to controls (median 8.7%, p = 1.0). Identifying increased %TSDR/CD4 in patients with novel FOXP3 mutations presenting with isolated diabetes facilitates diagnosis and could offer an opportunity to monitor patients and begin immune modulatory treatment before onset of severe enteropathy.

Urinary CD8+HLA-DR+ T Cell Abundance Non-invasively Predicts Kidney Transplant Rejection.

Early detection of kidney transplant (KT) rejection remains a challenge in patient care. Non-invasive biomarkers hold high potential to detect rejection, adjust immunosuppression, and monitor KT patients. So far, no approach has fully satisfied requirements to innovate routine monitoring of KT patients. In this two-center study we analyzed a total of 380 urine samples. T cells and tubular epithelial cells were quantified in KT patients with graft deterioration using flow cytometry. Epigenetic urine cell quantification was used to confirm flow cytometric results. Moreover, a cohort of KT patients was followed up during the first year after transplantation, tracking cell subsets over time. Abundance of urinary cell counts differed in patients with and without rejection. Most strikingly, various T cell subsets were enriched in patients with T cell-mediated rejection (TCMR) compared to patients without TCMR. Among T cell subsets, CD8+HLA-DR+ T cells were most distinctive (AUC = 0.91, Spec.: 95.9%, Sens.: 76.5%). Epigenetic analysis confirmed T cell and tubular epithelial cell quantities as determined by flow cytometry. Urinary T cell abundance in new KT patients decreased during their first year after transplantation. In conclusion urinary T cells reflect intrarenal inflammation in TCMR. T cell subsets yield high potential to monitor KT patients and detect rejection. Hereby we present a promising biomarker to non-invasively diagnose TCMR.

Determination of Immune Cell Identity and Purity Using Epigenetic-Based Quantitative PCR.

Immune cell subtype population frequencies can have a large effect on the efficacy of T cell therapies. Current methods, like flow cytometry, have specific sample requirements, high sample input, are low throughput, and are difficult to standardize, all of which are detrimental to characterization of cell therapy products during their development and manufacturing. The assays described herein accurately identify and quantify immune cell types in a heterogeneous mixture of cells using isolated genomic DNA (gDNA). DNA methylation patterns are revealed through bisulfite conversion, a process in which unmethylated cytosines are converted to uracils. Unmethylated DNA regions are detected through qPCR amplification using primers targeting converted areas. One unique locus per assay is measured and serves as an accurate identifier for a specific cell type. The assays are robust and identify CD8+, regulatory, and Th17 T cells in a high throughput manner. These optimized assays can potentially be used for in-process and product release testing for cell therapy process.

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

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.