ObjectiveTo discuss the relationship between antinuclear antibody (ANA) fluorescence pattern detected by indirect immunity fluorescence (IIF) and antinuclear antibody profiles (including anti-dsDNA, RNP, Sm, SSa, SSb, Scl-70, Jo-1 and rib-P) in human serum. MethodsA total of 7385 cases of ANA pattern and ANA profiles were retrospectively analyzed from January 2010 to December 2013. ANA was detected by IIF substrated as HEp-2 cells, anti-dsDNA by IIF substrated as crithidia, and the other 7 antibodies by enzyme immunoblot with purified antigen. ResultsGranular pattern mostly presented as anti-RNP, anti-Sm, anti-SSa and anti-SSb (P < 0.001); homogeneous pattern was anti-dsDNA and anti-SSa (P < 0.001); nucleolus, centromere, and mixed pattern was anti-SSa (P < 0.05); cytoplasm pattern was anti-rib-P and anti-SSa (P < 0.05). But few above antibodies could be detected in Golgi, dots, rim, actin, actotropomyosin, prolifevating cell nuclear antigen (PCNA) and vementin pattern. Homogeneous pattern was shown up to 77.91% in only anti-dsDNA positive serum; granular was 96.84%, 52.01%, and 82.35% respectively in only anti-RNP or anti-SSa or anti-Sm positive. Homogeneous and nucleolus mix pattern was up to 30.53% in only anti-Scl-70 positive. Cytoplasm pattern was 50.00% and 61.54% respectively in only anti-rib-P or anti-Jo-1 positive. But no fixed relationship was found between ANA pattern and anti-SSb. ConclusionsThere is a certain relationship between ANA and antinuclear antibody profiles. Granular, homogeneous and cytoplasm pattern often can be detected more than one autoantibodies. Eight kinds of specific autoantibodies often are negative when ANA patterns are centromere, Golgi, dots, rim, actin, tropomyosin, PCNA, and vimentin. Anti-dsDNA is mainly corresponding to homogeneous, anti-RNP, anti-SSa and anti-Sm to granular, anti-Scl-70 to homogeneous and nucleoli, anti-rib-P and anti-Jo-1 to cytoplasm. The study can give suggestions for further tests application and lab result checking.
ObjectiveTo evaluate the effect of autoantibody on the efficacy and safety of pegylated interferonα-2a (Peg-IFNα-2a) and ribavirin on chronic hepatitis C (HCV). MethodsWe enrolled 106 chronic HCV infected patients, who were divided into autoantibody-positive group and negative group based on the baseline autoantibody detection. The patients were treated for 48 weeks. The anti-viral response and adverse effects were observed. Data analyses were reported using the SPSS 20.0 statistical package. ResultsThe prevalence of any autoantibody in chronic hepatitis C patients amounted to 31.1%, and serum anti-nuclear antibody was positive in 24 patients. Difference in age, sex, serum alanine transaminase level, aspartate transaminase level, total bilirubin level, thyroid function and HCV RNA level between autoantibody-positive group and negative group was not significant (P > 0.05). The level of hemoglobin in autoantibody-positive group was significantly lower than the negative group (P=0.018). Of the 106 patients, 82 patients achieved sustained virological response (SVR), 56 achieved rapid virological response (RVR), 98 achieved ealy virological response (EVR) and 8 were non-responders. There were no significant differences between RVR, EVR and SVR in autoantibody-positive group and negative group (P > 0.05). The most common adverse effects in this study were fatigue, weight loss, hair loss and fever, and no significant differences in adverse effects were observed between the two groups (P > 0.05). ConclusionAutoantibody positivity may not affect the treatment response and is safe in chronic HCV infected patients with combination therapy of pegylated interferonα-2a plus ribavirin.
ObjectiveTo describe the clinical,radiographic,and laboratory features of autoimmune pulmonary alveolar proteinosis (PAP) from a single center. MethodsConsecutive autoimmune PAP cases diagnosed in the Nanjing Drum Tower Hospital between January 2006 and December 2012 were recruited in the study. The clinical,radiographic and laboratory data of the PAP patients were analyzed to explore the clinical significance of serum GM-CSF autoantibody (GMAb) and serum cytokeratin (CYFRA21-1). ResultsThe median serum GMAb level of the 26 cases was 28.64 μg/mL (interquartile range,19.2-75.4 μg/mL),which were diagnosed as autoimmune PAP based on the serum GMAb levels of these patients all above the cut-off value of 2.39 μg/mL while the serum GMAb levels of 30 normal controls were 0.10(0.05-0.15)μg/mL and all below the cut-off value. 34.6% of all recruited 26 autoimmune PAP patients had identified occupational inhalational exposure. There was no significant correlation in the serum GMAb in autoimmune PAP patients with disease severity scores (DSS),lung function parameters,chest high resolution computed tomography (HRCT) scores,or PaO2 (P>0.05). There was significant correlation of DSS of autoimmune PAP patients with PaO2,FVC%pred,TLCO%pred,opacity extent score of chest HRCT,and opacity severity score of chest HRCT (P<0.05). The median serum level of CYFRA21-1 of the autoimmune PAP patients was 9.9(4.3-19.5)ng/mL,which was significant higher than that of the normal control group (P<0.05). However there was no significant correlation in the serum CYFRA21-1 in the autoimmune PAP patients with DSS,lung function parameters,and chest HRCT scores. 92.3% of the chest HRCT of 26 autoimmune PAP patients had crazy paving sign,while 100% of them had geographic sparing sign. ConclusionSerum GMAb and CYFRA21-1 may be important biomarkers for diagnosis of autoimmune PAP. The PAP with occupational inhalational exposure constitutes a high proportion of autoimmune PAP patients.
Immune-mediated necrotizing myopathy (IMNM) is a type of autoimmune myopathy characterized by relatively severe proximal weakness with high serum muscle enzyme levels, myofiber necrosis with minimal inflammatory cell infiltrate on muscle biopsy, and infrequent extra-muscular involvement. The mechanism of necrotizing myopathy remains unclear. The new European Neuromuscular Centre criteria divides IMNM into three distinct subtypes according to different autoantibodies, which reminds us antibodies may be involved in the pathogenesis of IMNM and different subtypes may have different pathogenesis. This review summarizes the current understanding of the pathogenesis of IMNM.
ObjectiveBy integrating biological assays with imaging evaluations, a clinical prediction model is developed based on a cohort of ten thousand individuals to enhance the accuracy of distinguishing between benign and malignant pulmonary nodules. MethodsA retrospective analysis was conducted on the clinical data of 1,017 patients with pulmonary nodules who underwent chest CT and testing for seven types of lung cancer-related serum autoantibodies (7-AABs) at the First Affiliated Hospital of Zhejiang University School of Medicine from January 2020 to April 2024, all of whom had definitive pathological diagnosis results. Statistical analysis was performed using R and MSTATA software, with the development of univariate and multivariate logistic regression models, as well as a nomogram model. The performance of the models was evaluated using ROC curves, calibration curves, and decision curve analysis (DCA). ResultsA total of 1,017 patients with pulmonary nodules were included in the study. The training set consisted of 712 patients, including 291 males and 421 females, with a mean age of (58.12±12.41) years. The validation set included 305 patients, comprising 129 males and 176 females, with a mean age of (57.99±12.56) years. Univariate ROC curve analysis indicated that the combination of CT and 7-AABs testing achieved the highest AUC value (0.794), surpassing the diagnostic efficacy of CT alone (AUC=0.667) or 7-AABs alone (AUC=0.514). Multivariate logistic regression analysis included age, imaging nodule diameter, nodule characteristics, and the combination of CT and 7-AABs testing as independent predictive factors to construct a nomogram prediction model. The AUC values for this model were 0.831 and 0.861 in the training and validation sets, respectively, demonstrating excellent performance in decision curve analysis (DCA). ConclusionThe combination of 7-AABs with CT significantly enhances the accuracy of distinguishing between benign and malignant pulmonary nodules. The developed predictive model provides strong support for clinical decision-making and contributes to achieving precise diagnosis and treatment of pulmonary nodules.