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1.
Cells ; 12(19)2023 09 28.
Article in English | MEDLINE | ID: mdl-37830590

ABSTRACT

Biomarkers for the classification of rheumatoid arthritis (RA), and particularly for anti-citrullinated peptide antibody (ACPA)-negative patients, remain an important hurdle for the early initiation of treatment. Taking advantage of DNA-methylation patterns specific to early RA, quantitative methylation-specific qPCR (qMSP) offers a robust technology for the development of biomarkers. We developed assays and established their value as RA classification biomarkers. METHODS: DNA-methylation data were screened to select candidate CpGs to design qMSP assays. Eight assays were developed and tested on two early inflammatory arthritis cohorts. Logistic regression and bootstrapping were used to demonstrate the added value of the qMSP assays. RESULT: Differentially methylated CpG data were screened for candidate CpG, thereby meeting the qMSP assay requirements. The top CpG candidate was in the TNF gene, for which we successfully developed a qMSP assay. Significantly lower DNA-methylation levels were observed in RA (p < 4 × 10-9), with a high predictive value (OR < 0.54/AUC < 0.198) in both cohorts (n = 127/n = 157). Regression using both datasets showed improved accuracy = 87.7% and AUC = 0.944 over the model using only clinical variables (accuracy = 85.2%, AUC = 0.917). Similar data were obtained in ACPA-negative patients (n = 167, accuracy = 82.6%, AUC = 0.930) compared to the clinical variable model (accuracy = 79.5%, AUC = 0.892). Bootstrapping using 2000 datasets confirmed that the AUCs for the clinical+TNF-qMSP model had significant added value in both analyses. CONCLUSION: The qMSP technology is robust and can successfully be developed with a high specificity of the TNF qMSP assay for RA in patients with early inflammatory arthritis. It should assist classification in ACPA-negative patients, providing a means of reducing time to diagnosis and treatment.


Subject(s)
Arthritis, Rheumatoid , Tumor Necrosis Factor-alpha , Humans , Arthritis, Rheumatoid/diagnosis , Arthritis, Rheumatoid/genetics , Biomarkers , DNA , DNA Methylation/genetics , Tumor Necrosis Factor-alpha/genetics
2.
Clin Exp Rheumatol ; 36(1): 115-120, 2018.
Article in English | MEDLINE | ID: mdl-28980908

ABSTRACT

OBJECTIVES: Despite the well-established value of currently used classification criteria for the early diagnosis of rheumatoid arthritis (RA) there is a constant demand for novel biomarkers notably in autoantibody-negative patients. Interleukin 7 (IL-7) has been reported as a candidate diagnostic biomarker based on ACR-1987 criteria. However, clinical practice has moved to using the EULAR 2010 classification criteria. Therefore, to advance the use of IL-7 alongside the RA biomarker pipeline, we repeated the original study in a new cohort. METHODS: 255 patients were recruited. IL-7 was quantified by ELISA. Univariate and regression analyses were used to model RA diagnosis. RESULTS: 123 patients were diagnosed with RA (EULAR 2010) while 132 were classified as non-RA. In univariate analysis, RA was associated with autoantibodies and SE-positivity, higher joint counts, DAS28 (all p<0.001) and CRP (p=0.024). IL-7 was lower in RA (p=0.05). Logistic regression analysis in 227 patients with complete data set confirmed IL-7 was the second best predictive marker (p=0.035) following SJC (p=0.007) with good model fit (AUROC=0.889). A second model investigated 147 ACPA-negative patients: lower IL7 was the second best predictive marker (p=0.075) behind SJC (p=0.013). CONCLUSIONS: This study validates our previous results from a UK cohort using EULAR 2010 criteria although the predictive power associated with IL-7 is lower than in the study using ACR 1987 criteria (both French/UK cohorts). IL-7 remains a potential biomarker for ACPA-negative RA although further validation with larger numbers of ACPA-negative patients is still needed notably to translate these results into clinical applicability.


Subject(s)
Arthritis, Rheumatoid/diagnosis , Interleukin-17/blood , Adult , Aged , Area Under Curve , Arthritis, Rheumatoid/blood , Arthritis, Rheumatoid/immunology , Autoantibodies/blood , Biomarkers/blood , Early Diagnosis , Enzyme-Linked Immunosorbent Assay , Female , Humans , Male , Middle Aged , Predictive Value of Tests , Prognosis , ROC Curve , Reproducibility of Results , Serologic Tests , United Kingdom
3.
Neurotox Res ; 27(4): 421-9, 2015 May.
Article in English | MEDLINE | ID: mdl-25588864

ABSTRACT

Methamphetamine (METH) is a highly addictive CNS stimulant that its long-term use is associated with the loss of neurons in substantia nigra and development of Parkinson's disease later in life. Common form of METH is Ya-Ba tablet, in which, large portion of caffeine is added to the mass to enhance the stimulatory effect. Previous study demonstrated that caffeine potentiates the toxic effect of METH in association with the production of reactive oxygen species and the induction of apoptosis. Since METH causes induction of autophagy, the question was raised whether this pathway participates in the potentiating effect of caffeine on METH neurotoxicity. We used SH-SY5Y, a neuroblastoma cell line, as an in vitro model to study the effect of METH and caffeine. Co-treatment of non-toxic concentrations of METH, at 0.5 mM, and caffeine, at 1 mM, caused reduction of the cell viability. Reduction of the cell viability was associated with attenuation of autophagy, demonstrated by reduction of LC3-II levels and the number of autophagosome puncta, together with increase of caspase-3 activation. Similar effect was produced by treatment with autophagy inhibitors, 3-MA and wortmanin. Our results suggested that caffeine potentiates METH toxicity through inhibition of autophagy and that autophagy serves as a protective mechanism. In conclusion, we proposed the augmented hazard associated with caffeine and METH combination in Ya-Ba abusers.


Subject(s)
Autophagy/drug effects , Caffeine/toxicity , Central Nervous System Stimulants/toxicity , Methamphetamine/toxicity , Neurons/drug effects , Cell Line, Tumor , Cell Survival/drug effects , Humans , Microtubule-Associated Proteins/metabolism , Neuroblastoma , Neurons/metabolism
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