Diagnostic delay and its associated factors in Chinese axial spondyloarthritis: A single-center study of 1295 patients.

AIM: To delineate the landscape of diagnostic delay in Chinese axial spondyloarthritis (axSpA), investigate its associated factors, and explore its potential impact on medication modalities. METHODS: A total of 1295 patients fulfilling the ASAS classification criteria were obtained. Demographic and clinical data were collected through face-to-face interviews, based on predesigned questionnaires and available medical records. Logistic regression analyses under univariate and multivariable model were performed, using the median of diagnostic delay as the cut-off point for group classification. Differences between early- and late-diagnosed groups were subsequently compared by the Pearson chi-square test or Mann-Whitney U test. RESULTS: Of 1295 axSpA patients, 80.3% were male and the median of disease duration was 8.0 years. The median (IQR) diagnostic delay in Chinese axSpA was 3.0 (1.0 ~ 7.0) years and 24.8% of them reported a history of misdiagnosis. Older age at onset (OR = 0.97, p < .001) and higher education attainment (p = .001) were correlated with early diagnosis of axSpA, whereas coming from less developed areas (p = .002), a history of peripheral arthritis at the time of diagnosis (OR = 1.58, p = .002) and history of misdiagnosis (OR = 1.98, p < .001) increased the risk of diagnostic delay. Oral medication modalities were similar between two groups, but the proportion with no medication ever was higher in the late-diagnosed group (26.5% vs. 20.7%, p = .02). CONCLUSION: Our findings depicted a detailed spectrum of diagnostic delay in Chinese axSpA, verified five associated factors that may help facilitate timely diagnosis of axSpA, and pinpointed that timely medication was unsatisfying, especially in the late diagnosis group.

Etanercept/celecoxib on improving MRI inflammation of active ankylosing spondylitis: A multicenter, open-label, randomized clinical trial.

Objective: To investigate the efficacy and safety of clinical, magnetic resonance imaging (MRI) changes in active ankylosing spondylitis (AS) patients with etanercept and celecoxib alone/combined treatment. Methods: A randomized controlled trial was conducted in three medical centers in China. Adult AS patients with BASDAI ≥4 or ASDAS ≥2.1, CRP >6 mg/L, or ESR 28 mm/1st hour were randomly assigned (1:1:1 ratio) to celecoxib 200 mg bid or etanercept 50 mg qw or combined therapy for 52 weeks. The primary outcomes were SPARCC change of the sacroiliac joint (SIJ) and spine and the proportion of patients achieving ASAS20 response at 52 weeks. Results: Between September 2014 and January 2016, we randomly assigned 150 patients (mean age, 32.4 years; mean disease duration, 109 months), and 133 (88.6%) completed the study. SPARCC inflammation scores of the SIJ and spine decreased in the three groups, and significant differences were found between the combined group and the celecoxib group [between-group difference: -6.33, 95% CI (-10.56, -2.10) for SIJ; -9.53, 95% CI (-13.73, -5.33) for spine] and between the etanercept group and the celecoxib group [between-group difference: -5.02, 95% CI (-9.29, -0.76) for SIJ; -5.80, 95% CI (-10.04, -1.57) for spine]. The ASAS20 response rates were 44%, 58%, and 84% in the celecoxib, etanercept, and combined groups, respectively, and a significant difference was only found between the combined and the celecoxib groups. Conclusion: Etanercept with or without celecoxib decreases inflammation detected by MRI at 1 year compared to celecoxib alone in active AS patients. The combination of etanercept and celecoxib was superior to celecoxib alone for the primary clinical response. Clinical Trial Registration: ClinicalTrials.gov, identifier NCT01934933.

The pattern and trends of disease burden due to low bone mineral density from 1990 to 2019 in China: findings from the Global Burden of Disease Study 2019.

Osteoporosis is becoming increasing important health problem in China. This study shows that the disease burden of low bone mineral density (BMD) in China is large and will remain increasing with the growth of aging population. In addition, male low BMD should not be ignored. Although burden of low BMD is partially representative of the real burden of osteoporosis, the information provided in our study could be used to better inform targeted public health prevention and management programs for osteopososis. PURPOSE: We aim to investigate the pattern and trends of disease burden due to low BMD by gender, year, and age in China from 1990 to 2019. METHODS: Data on summary exposure value (SEV) and disability-adjusted life years (DALYs) due to low BMD was obtained from the Global Burden of Disease Study 2019, and analyzed by gender, age, and years. Average annual percent change (AAPC) and annual percent change (APC) were calculated to qualify the trends of burden due to low BMD. RESULT: In 2019, the age-standardized SEV was higher in females than that in males (23.04, 95% UI = [17.25-29.83] and 12.50, 95% UI = [7.71-19.25], respectively), while the total number of DALYs was higher in males than females with 1,698,705.92 (95% UI = 1,281,580.79 to 2,076,364.25) and 1,621,569 (95% UI = 1,266,284.89 to 2,016,399.16), respectively. Though SEV exhibited decreasing trends during 1990 to 2019 in both sexes, the absolute number of DALYs due to low BMD increased steadily and almost doubled in 2019 compared to that in 1990. CONCLUSION: The burden of low BMD remains large and continues to increase. Although females are prone to low BMD, the disease burden for males should not be ignored.

Efficacy and safety of Fengshi Gutong Capsule in patients with active ankylosing spondylitis: A 4-week randomized controlled, double-blinded, double-dummy trial.

ETHNOPHARMACOLOGICAL RELEVANCE: Fengshi Gutong Capsule (FSGTC) is a traditional Chinese herbal medicine that is composed of seven herbs. It has been widely used for the treatment of joint pain in China. However, the clinical evidence supporting its use in patients with ankylosing spondylitis (AS) is lacking. AIM OF THE STUDY: This study aims to explore the efficacy and safety of FSGTC in the treatment of AS. MATERIALS AND METHODS: This randomized, controlled, double-blinded, double-dummy trial enrolled patients with active AS defined as Bath Ankylosing Spondylitis Disease ActivityIndex (BASDAI) ≥ 4 or Ankylosing Spondylitis Disease Activity Score with C-reactive protein (ASDAS-CRP) ≥ 2.1. Eligible patients were randomized (1:1:1) into combination group (FSGTC plus imrecoxib), FSGTC group (FSGTC plus imrecoxib placebo) or imrecoxib group (imrecoxib plus FSGTC placebo) over a 4-week treatment. The primary endpoint was the composite outcome measure of the Assessment in Ankylosing Spondylitis 20% (ASAS20) response at week 4. The secondary endpoints included ASDAS-CRP, BASDAI, Bath Ankylosing Spondylitis Functional Index (BASFI), Bath Ankylosing Spondylitis Metrology Index (BASMI), patient's global assessment of disease activity (PGTA) and safety. RESULTS: Of the 180 randomized patients, 159 patients (88.3%) completed the 4-week treatment. ASAS20 response rate at week 4 was achieved by 27.5% in imrecoxib group, compared with 37.0% in combination group (P > 0.05) and 37.0% in FSGTC group (P > 0.05). In comparison to imrecoxib group, there were significantly greater improvements of ASDAS-CRP and PTGA in combination group and greater improvement of ASDAS-CRP in FSGTC group while the rest of the secondary endpoints shown similar improvement. The incidence of gastrointestinal adverse events in imrecoxib group (15.7%) was significantly higher than that of FSGTC group (1.9%) and without a significant difference to combination group (7.4%). CONCLUSION: FSGTC alone or combined with NSAIDs has therapeutic efficacy in decreasing disease activity of active AS patients and with good gastrointestinal tolerability after 4-week of treatment.

Adalimumab Therapy Restores the Gut Microbiota in Patients With Ankylosing Spondylitis.

Growing evidence suggests that the gut microbiota is involved in the initiation and progression of ankylosing spondylitis (AS). In this study, we aimed to explore the gut microbiome alterations during adalimumab therapy and verify microbiome biomarkers predicting treatment response. By evaluating the gut microbial features of 30 AS patients before and after adalimumab therapy for 6 months and 24 healthy controls, we confirmed that the microbiome was restored remarkably after 6 months of adalimumab therapy in AS patients. We then compared the baseline gut microbiome of 22 adalimumab responders with 8 non-responders, a higher abundance of Comamonas was revealed in the latter, although no statistical difference was found after adjusting for the false discovery rate. These results suggested that adalimumab therapy restored the gut microbiome in AS patients and indicated the utility of gut microbiome to be potential biomarkers for therapeutic evaluation. These findings provided an insight into the development of predictive tools and the establishment of precise medical interventions for clinical practice.

Serum Metabolomics Signatures Associated With Ankylosing Spondylitis and TNF Inhibitor Therapy.

Ankylosing spondylitis (AS) is a type of spondyloarthropathies, the diagnosis of which is often delayed. The lack of early diagnosis tools often delays the institution of appropriate therapy. This study aimed to investigate the systemic metabolic shifts associated with AS and TNF inhibitors treatment. Additionally, we aimed to define reliable serum biomarkers for the diagnosis. We employed an untargeted technique, ultra-performance liquid chromatography-mass spectroscopy (LC-MS), to analyze the serum metabolome of 32 AS individuals before and after 24-week TNF inhibitors treatment, as well as 40 health controls (HCs). Multivariate and univariate statistical analyses were used to profile the differential metabolites associated with AS and TNF inhibitors. A diagnostic panel was established with the least absolute shrinkage and selection operator (LASSO). The pathway analysis was also conducted. A total of 55 significantly differential metabolites were detected. We generated a diagnostic panel comprising five metabolites (L-glutamate, arachidonic acid, L-phenylalanine, PC (18:1(9Z)/18:1(9Z)), 1-palmitoylglycerol), capable of distinguishing HCs from AS with a high AUC of 0.998, (95%CI: 0.992-1.000). TNF inhibitors treatment could restore the equilibrium of 21 metabolites. The most involved pathways in AS were amino acid biosynthesis, glycolysis, glutaminolysis, fatty acids biosynthesis and choline metabolism. This study characterized the serum metabolomics signatures of AS and TNF inhibitor therapy. We developed a five-metabolites-based panel serving as a diagnostic tool to separate patients from HCs. This serum metabolomics study yielded new knowledge about the AS pathogenesis and the systemic effects of TNF inhibitors.

Circulating Retinol-Binding Protein 4 as a Possible Biomarker of Treatment Response for Ankylosing Spondylitis: An Array-Based Comparative Study.

OBJECTIVE: To explore proteins associated with ankylosing spondylitis (AS) and to investigate potential proteins that may predict treatment response of adalimumab (ADA) in AS patients. METHODS: In the discovery cohort, 39 AS patients and 20 healthy controls (HCs) were included, and 16 AS patients received ADA treatment for 24 weeks after included. In the validation cohort, 43 AS patients and 39 HCs were enrolled, and all 43 patients received ADA treatment after enrollment. Blood samples and clinical information were collected from two cohorts at baseline from all participants and week 24 from patients received ADA treatment. A human antibody array containing 1,000 proteins was used in the discovery phase, and Elisa kits were used for protein validation. RESULTS: Compared with HCs, we identified 53 differentially expressed proteins (DEPs) in AS patients. Bioinformatics analysis revealed they were mostly enriched in coagulation function-related pathways, acute response signaling, and LXR/RXR activation. Bone metabolism pathways were also associated. Comparison between samples of pre- and post-ADA treatment revealed 42 DEPs. They were mostly associated with bone metabolism and inflammation response pathways. Significant enrichment was also found in LXR/RXR activation but not the coagulation function-related pathways. Upstream regulator analysis suggested that most regulators also significantly functioned under usage of ADA. Precisely, seven proteins were abnormally expressed in AS and restored after ADA treatment. Retinol-binding protein 4 (RBP4), one of the seven proteins, was validated that its baseline levels were inversely correlated with improvements in Ankylosing Spondylitis Disease Activity Score-C-reactive protein (ASDAS-CRP). Likewise, percentage changes in RBP4 levels were inversely correlated with changes in ASDAS-CRP score. CONCLUSION: A dysregulated serum protein profile existed in AS. ADA exerted a considerable but not entire alteration toward the dysregulation. RBP4 could be a biomarker for predicting and monitoring ADA treatment response.

Identification of the urine and serum metabolomics signature of gout.

OBJECTIVE: Gout is the most common inflammatory arthritis and the worldwide incidence is increasing. By revealing the metabolic alterations in serum and urine of gout patients, the first aim of our study was to discover novel molecular biomarkers allowing for early diagnosis. We also aimed to investigate the underlying pathogenic pathways. METHODS: Serum and urine samples from gout patients (n = 30) and age-matched healthy controls (n = 30) were analysed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to screen the differential metabolites and construct a diagnostic model. Next, the model was verified and optimized in the second validation cohort (n = 100). The pathways were illustrated to understand the underlying pathogenesis of gout. RESULTS: In general, serum metabolomics demonstrated a clearer distinction than urine metabolomics. In the discovery cohort, 40 differential serum metabolites were identified that could distinguish gout patients from healthy controls. Among them, eight serum metabolites were verified in the validation cohort. Through regression analysis, the final model consisted of three serum metabolites-pyroglutamic acid, 2-methylbutyryl carnitine and Phe-Phe-that presented optimal diagnostic power. The three proposed metabolites produced an area under the curve of 0.956 (95% CI 0.911, 1.000). Additionally, the proposed metabolic pathways were primarily involved in purine metabolism, branched-chain amino acids (BCAAs) metabolism, the tricarboxylic acid cycle, synthesis and degradation of ketone bodies, bile secretion and arachidonic acid metabolism. CONCLUSION: The metabolomics signatures could serve as an efficient tool for early diagnosis and provide novel insights into the pathogenesis of gout.

The Clinical Characteristics of Other HLA-B Types in Chinese Ankylosing Spondylitis Patients.

HLA-B27 has an established relationship with the development of ankylosing spondylitis (AS). After reviewing the HLA-B genotype from 407 Chinese subjects (318 patients and 89 sex-matched controls), we found that 252 patients and 32 controls were HLA-B27(+) and that HLA-B*27:04 was the dominant HLA-B27 subtype (N = 224). In all participants, HLA*27:04 homozygous were only detected in two patients. In the HLA-B27(+) group, HLA-B40 was observed in 51 cases and one control (p < 0.05, OR = 7.87, 95% CI 1.05-59.0); of these, the most genotype was HLA-B*27:04/B*40:01(N = 38). Two hundred thirty-nine patients' clinical information was recorded. Cases with HLA-B27/B46 had more peripheral joint involvement (OR = 3.95, 95% CI 1.77-8.79) in HLA-B27(+) AS. HLA-B*15:02 may be a significant risk element to peripheral joint involvement (p < 0.05) in HLA-B27(-) patients. Therefore, we believe HLA-B*40:01, HLA-B*46:01, and HLA-B*15:02 can be the test indicators for AS diagnostic value.

Age-Specific Imbalance of Circulating Tfh Cell Subsets and Its Association With Gout-Targeted Kidney Impairment.

Objective: Gout is a chronic disease characterized by the deposition of monosodium urate (MSU) crystals in tissue. Study with a focus on adaptive immune response remains to be understood although innate immune response has been reported extensively in gout etiology. Our study attempted to investigate the association of gout-related immune cell imbalance with clinical features and comorbidity with renal impairment and the implicated pathogenesis via the assessment of T and B cell subsets in different activity phases or with immune effects combined with the analyses of clinical parameters. Methods: Fifty-eight gout patients and 56 age- and sex-matched healthy individuals were enrolled. To learn the roles of circulating T cells, a lymphocyte profile incorporating 32 T cell subsets was tested from isolated freshly peripheral blood monocyte cells (PBMCs) with multiple-color flow cytometry. Furthermore, the collected clinical features of participants were used to analyze the characteristics of these differential cell subsets. Stratified on the basis of the level of creatinine (Cr, enzymatic method), all patients were categorized into Crlow (Cr ≤ 116 µmol/L) and Crhi (Cr > 116 µmol/L) groups to exploit whether these gout-associated T cell subsets were functional in gout-targeted kidney dysfunction. The differentiation of B cells was investigated in gout patients. Results: Our results show that CD 4+ T cells, Th2 cells, and Tc2 cells were upregulated, whereas Tc17 cells were downregulated. Tfh cells skewed toward the polarization of Tfh2 cells. Specifically, Tfh2 cells increased, but Tfh1 cells decreased, accompanied with aging for gout patients, suggesting that age might trigger the skewing of Tfh1/Tfh2 cell subsets to influence gout development. Moreover, Tfh2 cells were connected to renal dysfunction as well. No alterations of B cell subsets were observed in patients when compared to controls. Conclusions: Our data demonstrate age-specific dysfunctions of Tfh1/2 cells in gout occurrence, and Tfh2 cell upregulation is associated with gout-targeted renal dysfunction. However, Tfh2 cells may function in auto-inflammatory gout independent of helping B differentiation, and an in-depth study remains to be conducted.

Variations in gut microbial profiles in ankylosing spondylitis: disease phenotype-related dysbiosis.

BACKGROUND: Microbial involvement in ankylosing spondylitis (AS) has been suggested; however, the relationship between gut microbiome and the disease phenotypes of AS remains to be established. This study was to characterize and investigate differences in the gut microbiome between AS patients and healthy controls (HCs), and to determine whether the gut microbiome profile associated with the disease phenotypes. METHODS: 16S rRNA gene V4 region sequencing was performed on fecal DNA isolated from stool samples collected from 41 patients with AS [20 axial AS (axAS) and 21 peripheral AS (pAS)] and 19 HCs. QIIME based pipeline was used to process the raw sequence data. Alpha and beta diversities were assessed using QIIME, and comparisons of gut microbiome profile were performed using linear discriminant analysis (LDA) effect size (LEfSe) to examine differences between groups and subgroups. A gut microbiota-based model for predictive diagnosis of AS was constructed using random forest algorithm and its predictive value was assessed by receiver-operating characteristic analyses. RESULTS: Our results showed that fecal microbial communities in patients with AS differ significantly from those in HCs, driven by a higher abundance of 7 genera (Prevotella_9, Dialister, Comamonas, Collinsella, Streptococcus, Alloprevotella and Prevotella_2) and a lower abundance of 4 genera (Eubacterium_ruminantium_group, Ruminococcus_gnavus_group, Lachnospira and Bacteroides). In addition, pAS patients were more enriched in Comamonas, Streptococcus and Collinsella, while axAS patients were more enriched in Prevotella_2. An 8 genera-based model showed high accuracy for distinguishing AS patients from HCs with an area under the curve (AUC) up to 0.950. CONCLUSIONS: Our results revealed specific alterations in the gut microbiome in patients with different phenotypes of AS, and the classification model based on gut microbial features might provide a new direction for future clinical diagnosis. Lastly, discovery of the associated microbes of AS in the gut microbiome may help us to seek more treatments for this disease.