Sema4D as a biomarker for Predicting rheumatoid arthritis disease activity.

OBJECTIVE: The semaphorins are membrane or secreted proteins first identified in neural development. Semaphorin 4D (Sema4D) is the first family member found to have immune properties. We evaluated the potential of Sema4D as a marker for rheumatoid arthritis (RA) disease activity, singly and in combination with other known biomarkers including rheumatoid factor (RF) and C-reactive protein (CRP). METHODS: Three hundred and eleven RA patients were enrolled. The patients were divided into three groups based on their disease activity in 28 joints (DAS28): mild, moderate, and severe. The healthy group included 40 healthy individuals. SerumSema4D was measured by quantitative ELISA and the specificity and sensitivity of biomarkers were evaluated by generating a receiver operating characteristic (ROC) curve to analyze their diagnostic accuracy. RESULTS: Serum Sema4D levels in the moderate and severe RA groups were elevated significantly above those of the controls (P < 0.01), while levels in the mild RA and control groups did not differ significantly (P > 0.05). The Sema4D cutoff threshold was 15.7 ng/ml when the DAS28 was applied as a reference. Compared to the erythrocyte sedimentation rate (ESR and CRP, Sema4D had the highest specificity (96.8%) and area under the curve (0.80) for diagnosing RA activity. The highest specificity (100%) for the biomarker combinations was obtained when Sema4D was combined with CRP and anti-CCP, the combination of the Sema4D combined with ESR and anti-CCP had the highest sensitivity (99.35%). According to this result, a new model for jointly calculating RA activity of Sema4D,anti-CCP and CRP was constructed. Meanwhile another model is established by using the method of multivariate analysis.Model comparison results showed the the multiple regression algorithm method fitted the patients' disease activity better. CONCLUSION: The serum Sema 4D level effectively reflects moderate to severe RA activity. Sema4D levels can be used together with conventional RA biomarkers to increase the diagnostic power of RA activity. The multiple regression algorithm method is promising in disease activity calculation.

The prognostic value of whole-genome DNA methylation in response to Leflunomide in patients with Rheumatoid Arthritis.

Objective: Although Leflunomide (LEF) is effective in treating rheumatoid arthritis (RA), there are still a considerable number of patients who respond poorly to LEF treatment. Till date, few LEF efficacy-predicting biomarkers have been identified. Herein, we explored and developed a DNA methylation-based predictive model for LEF-treated RA patient prognosis. Methods: Two hundred forty-five RA patients were prospectively enrolled from four participating study centers. A whole-genome DNA methylation profiling was conducted to identify LEF-related response signatures via comparison of 40 samples using Illumina 850k methylation arrays. Furthermore, differentially methylated positions (DMPs) were validated in the 245 RA patients using a targeted bisulfite sequencing assay. Lastly, prognostic models were developed, which included clinical characteristics and DMPs scores, for the prediction of LEF treatment response using machine learning algorithms. Results: We recognized a seven-DMP signature consisting of cg17330251, cg19814518, cg20124410, cg21109666, cg22572476, cg23403192, and cg24432675, which was effective in predicting RA patient's LEF response status. In the five machine learning algorithms, the support vector machine (SVM) algorithm provided the best predictive model, with the largest discriminative ability, accuracy, and stability. Lastly, the AUC of the complex model(the 7-DMP scores with the lymphocyte and the diagnostic age) was higher than the simple model (the seven-DMP signature, AUC:0.74 vs 0.73 in the test set). Conclusion: In conclusion, we constructed a prognostic model integrating a 7-DMP scores with the clinical patient profile to predict responses to LEF treatment. Our model will be able to effectively guide clinicians in determining whether a patient is LEF treatment sensitive or not.

Development and validation of a nomogram for predicting stroke risk in rheumatoid arthritis patients.

We developed and validated a nomogram to predict the risk of stroke in patients with rheumatoid arthritis (RA) in northern China. Out of six machine learning algorithms studied to improve diagnostic and prognostic accuracy of the prediction model, the logistic regression algorithm showed high performance in terms of calibration and decision curve analysis. The nomogram included stratifications of sex, age, systolic blood pressure, C-reactive protein, erythrocyte sedimentation rate, total cholesterol, and low-density lipoprotein cholesterol along with the history of traditional risk factors such as hypertensive, diabetes, atrial fibrillation, and coronary heart disease. The nomogram exhibited a high Hosmer-Lemeshow goodness-for-fit and good calibration (P > 0.05). The analysis, including the area under the receiver operating characteristic curve, the net reclassification index, the integrated discrimination improvement, and clinical use, showed that our prediction model was more accurate than the Framingham risk model in predicting stroke risk in RA patients. In conclusion, the nomogram can be used for individualized preoperative prediction of stroke risk in RA patients.

Quality of life and influencing factors of patients with rheumatoid arthritis in Northeast China.

PURPOSE: Rheumatoid arthritis (RA) is a disease with a high disability rate, resulting in severe family and social burden. The aim of treatment is to improve the health-related quality of life (QoL) of patients. The purpose of this study was to evaluate the QoL of patients with RA in Northeast China and analyze its influencing factors. METHODS: The study group consisted of 200 patients diagnosed with RA. The control group consisted of 200 healthy subjects. All subjects were residents in Northeast China. The investigation was conducted by questionnaire survey and electronic medical record. The WHOQOL-BREF, The Short-Form 36 Health Survey (SF-36) and Quality of Life Instruments for Chronic Diseases-RA (QLICD-RA) were used as questionnaires. RESULTS: The QoL scores acquired by SF-36, WHOQOL-BREF and QLICD-RA scales showed significant differences between RA and control groups (P < 0.001). Multiple regression analysis showed that sleep duration (P = 0.001), psychological counseling (P < 0.001) and C4 level (P = 0.001) influenced the SF-36 scale evaluation model. IgA levels (P < 0.001) and being overweight (P = 0.030) were included in the WHOQOL-BREF evaluation model. Adequate sleep (P = 0.001) and psychological counseling(P = 0.050) entered the QLICD-RA scale evaluation model (P = 0.050), in which psychological counseling, normal C4 levels and being overweight were protective factors for RA, insufficient sleep and IgA levels were risk factors for RA. CONCLUSIONS: The QoL of RA patients is generally lower than those of healthy subjects in the Northeast China, Northeast China. Sleep duration, BMI (Body mass index), psychological counseling, C4 and IgA levels are factors that influence the QoL scores of RA patients.

Development and validation of a nomogram to predict coronary heart disease in patients with rheumatoid arthritis in northern China.

We developed and validated a nomogram to predict coronary heart disease (CHD) in patients with rheumatoid arthritis (RA) in northern China. We analyzed a cohort of RA patients admitted to the Department of Rheumatology and Immunology of the First Affiliated Hospital of China Medical University from 2011 to 2017. To select a high-performance model for clinical data prediction, we evaluated the F1-scores of six machine learning models. Based on the results, we selected multivariable logistic regression analysis for the development of a prediction model. We then generated an individualized prediction nomogram that included age, sex, hypertension, anti-cyclic citrullinated peptide antibody positivity, the erythrocyte sedimentation rate, and serum LDL-cholesterol, triglyceride and HDL-cholesterol levels. The prediction model exhibited better discrimination than the Framingham Risk Score in predicting CHD in RA patients. The area under the curve of the prediction model was 0.77, with a sensitivity of 63.9% and a specificity of 77.2%. The nomogram exhibited good calibration and clinical usefulness. In conclusion, our prediction model was more accurate than the Framingham Risk Score in predicting CHD in RA patients. Our nomogram combining various risk factors can be used for the individualized preoperative prediction of CHD in patients with RA.

Exploring metabolic and inflammatory abnormalities in rheumatoid arthritis patients developing stroke disease: a case-control study using electronic medical record data in northern China.

OBJECTIVES: Intend to investigate the roles of serum lipids, inflammatory markers, and serological status in rheumatoid arthritis and stroke patients by using case-control study. MATERIALS AND METHODS: Clinical data were retrieved from the electronic medical record of the First Affiliated Hospital of China Medical University during January 2011 to March 2018. The obtained data were categorized into case groups and three control groups, in the ratios of 1:2, respectively, with all matching age and gender. Multinomial logistic regression analysis and restricted cubic spline were conducted examining the associations between serum lipids, inflammatory markers, serological status, and the risk of stroke among RA patients. RESULTS: The present studies included 1057 study subjects. The elevated ESR, LDL-C levels, and much higher CRP levels ≥ 230 mg/L were independent risk factors for RA patients in developing stroke. Furthermore, we found that ESR and LDL-C levels could exhibit a linear association with the risk of comorbid stroke while CRP level had a nonlinearity association with stroke risk among RA patients. CONCLUSIONS: A close monitoring is required for RA patients with dyslipidemia and elevated inflammatory markers, and the primary stroke preventive strategies should be directed against these risk factors.

MicroRNA-217 attenuates intima-media complex thickness of ascending aorta measured by ultrasound bio-microscopy and inhibits inflammation and lipid metabolism in atherosclerotic models of ApoE-/- mice.

BACKGROUND: Little investigation was done to test the efficiency of microRNA-217 (miR-217) on atherosclerosis in vivo. METHODS: ApoE-/- mice were used to construct atherosclerotic models and ultrasound bio-microscopy (UBM) was applied to detect the intima-media thickness (IMT) of the ascending aorta. The serum level of miR-217 and correlation with IMT was investigated. After miR-217 mimic administration, the IMT, inflammation, and lipid-associated molecules were assayed. RESULTS: The serum level of miR-217 was reduced in ApoE-/- mice and showed a negative correlation with the IMT of the ascending aorta (r2 = 0.5899, p < 0.0001). miR-217 mimic administration attenuated IMT and down-regulated the level of serum triglyceride (TG), total cholesterol (TC), and low-density-lipoprotein cholesterol (LDL-C), while it could up-regulate high-density lipoprotein cholesterol (HDL-C). Inflammation relevant genes, such as F4/80, tumor necrosis factor (TNF)-α, interleukin (IL)-1, IL-6, and monocyte chemoattractant protein (MCP)-1, and lipid metabolism associated gene, such as LDL receptor, class A scavenger receptors (SR-A), scavenger receptor class B type I (SR-BI), CD36, ATP binding cassette subfamily A member 1 (ABCA1), and ATP binding cassette subfamily G member 1 (ABCG1) in the aorta were significantly down-regulated in miR-217 group when compared with atherosclerosis group. CONCLUSION: miR-217 could down-regulate IMT and modulate the inflammation and lipid metabolism process, which indicates that miR-217 could be a potential treatment option.

Increased frequency of CCR7+CD4+ T cells from patients with primary Sjögren's syndrome: An indicator of disease activity rather than of damage severity.

Expression of CCR7 on T cells has been reported to be associated with the lymphocytic migration and infiltration, which is recognized as a vital part of the pathogenesis of Primary Sjögren's syndrome (pSS). Here, we compared the expression of CCR7 on CD4+T cells between pSS patients and control groups, including healthy donors (HD) and patients with systemic lupus erythematosus (SLE) and examined correlations with disease activity and damage severity, which were evaluated by EULAR Sjögren's Syndrome Disease Activity Index (ESSDAI) and Sjogren's Syndrome Disease Damage Index (SSDDI), respectively. Peripheral blood mononuclear Cells (PBMC) were obtained from patients and controls and expressions of CCR7 were evaluated by flow cytometry. CCR7 was selectively and frequently expressed on CD4+T cells, but less on CD8+ T cells of patients with pSS. In contrast, this phenomenon was neither seen in normal subjects nor in patients with SLE. The expression level of CCR7 in the peripheral blood CD4+ T cells is closely correlated with ESSDAI, but not SSDDI. Correspondently, the chemotactic index (CI) of CD4+T cells was higher than CD8+T cells in patients with pSS. Furthermore, the CI of CD4+T cells is also higher than that of other controls, which is correlated with ESSDAI. All the findings suggested that CCR7 might play an important role in the development of pSS by mediating the migration of CD4+cells. Thus, the expression of CCR7 in CD4+ T cells is probably a useful biomarker to evaluate and monitor disease activity. CCR7 can also potentially be a novel target for the therapy of pSS.

Predicting castration-resistant prostate cancer after combined androgen blockade.

This study analyzed 99Tcm-MDP bone scans and investigated factors influencing early-stage castration resistance in prostate cancer (CRPC) patients with bone metastasis. We retrospectively analyzed clinical data from 92 patients with bone metastatic prostate cancer treated with maximal androgen blockade. Patients were imaged with 99Tcm-MDP bone scan to detect metastases, and prostate specific antigen (PSA) values were measured regularly. Before treatment, 464 total bone metastases were detected in the 92 patients, with pelvic bone metastases accounting for about 30.6% of the total. After combined androgen blockade treatment, median CRPC occurrence time was 23 months. A longer time to reach the lowest PSA value was an independent predictor of early-onset CRPC (occurrence <1 year after treatment). Our findings suggest that 99Tcm-MDP bone scans are useful for diagnosing prostate cancer bone metastasis and grading. Patients with Gleason scores>8, higher PSA values after treatment, and shorter times to reach the lowest PSA value had poorer responses to combined androgen blockade treatment.

[The effect of secondary lymphoid tissue chemokine and its receptor on chemotaxis of peripheral blood lymphocytes in the patients with Sjögren's syndrome].

AIM: To investigate the effect of secondary lymphoid tissue chemokine (SLTC) and its receptor CCL21/CCR7 on chemotaxis of peripheral blood lymphocytes in the patients with Sjögren's syndrome (SS) and explore their roles in the SS pathogenesis. METHODS: Thirty-one SS patients were selected, including 18 primary SS patients (pSS) and 13 secondary SS (sSS) patients. In addition, 20 healthy persons were selected as normal controls. Peripheral blood lymphocytes were isolated from all the SS patients and normal controls. The cell trans-membrane test with 24-well transwells was used to detect the effect of CCL21/CCR7 on the lymphocyte migration. RESULTS: In the presence of CCL21, the chemotactic indexes (CIs) of lymphocytes from pSS and sSS patients were 2.92±0.12 and 2.80±0.28, respectively. Both of them were significantly higher than that of normal controls (CI=1.32±0.11, P<0.01), while there was no difference between pSS and sSS patients. After anti-CCR7 mAb pretreatment, the lymphocyte CIs of pSS and sSS patients respectively, decreased significantly to 1.04±0.05 and 1.03±0.08 as compared with untreated controls. CONCLUSION: CCR7 is the one of the important factors resulting in lymphocyte migration. CCL21/CCR7 interaction mediates the migration of peripheral lymphocytes in SS patients and may be involved in the gland damage due to the infiltration of massive lymphocytes in exocrine glands in SS patients.

Anti-macrophage-derived chemokine antibody relieves murine lupus nephritis.

We observed the distribution of monocyte's changes in damage to renal tissue and the expression of macrophage-derived chemokine (MDC) in MRL/lpr mice. The 8-week-old MRL/lpr mice were randomly assigned to receive either MDC antibodies (n = 6) or placebo (n = 6) at a once-every-other-day dose of 300 µl from week 4. We then quantified the differences in 24-h urine protein and serum creatinine concentrations, performed a histological evaluation of renal tissue and assessed the expression of MDC protein and mRNA between the two groups 4 weeks after treatment was initiated. Antibody-treated mice demonstrated significantly lower urine protein and serum creatinine concentrations and had fewer renal lesions compared with control mice. The expression of MDC protein and mRNA in renal tissues was significantly lower in the antibody-treated mice than in control mice, suggesting that the elevated expression of MDC, which led to monocyte infiltration in the kidney, may play an important role in the development of lupus nephritis. Furthermore, the anti-MDC antibodies may act to alleviate the renal lesions of murine lupus nephritis by inhibiting the infiltration of monocytes in the renal tissue of the lupus mice.