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Abstract Objective The objective of this study was to explore the associations of body mass index (BMI), fat mass index (FMI), skeletal mass index (SMI) and secondary osteoporosis (OP) in patients with rheumatoid arthritis (RA). Methods The bone mineral density (BMD) at sites of the femur neck (Neck), total hip (Hip) and lumbar vertebrae 1–4 (L1-4) was measured by dual-energy X-ray absorptiometry. The skeletal muscle index, body fat percentage and mineral content were measured by biological electrical impedance for calculating BMI, FMI and SMI. Results A total of 433 patient with RA and 158 healthy controls were enrolled. The BMDs at each site of the RA patients were lower compared with those of the healthy controls (p

Abstract Clinical studies have found 14-3-3η to be associated with osteoporosis through undefined mechanisms. We aimed to investigate the role of 14-3-3η in osteoporosis and its potential associations with miRNAs. The Gene Expression Omnibus(GEO) and Human Protein Atlas 1 databases were analyzed to examine both the mRNA and protein expression of 14-3-3η in OP. Gene enrichment analyses were performed to explore the underlying mechanism of 14-3-3η based on DAVID. miRWalk was used to predict the associated miRNAs. The statistics were analysed by R software and SPSS software. 14-3-3η was overexpressed and knock down expressed in BMSCs by lentiviral vector transfecting. And BMSCs were induced by hypoxia. qRT-PCR and Western-Blot verified the expression of mRNA and protein. Scratch assay detected the migration of osteocytes. Co-immunoprecipitation and luciferase assay studied the 14-3-3η targeted protein and miRNA. overexpression and knock down of miRNA to verify the relationship of 14-3-3η and target genes. The 14-3-3η mRNA expression level was low in patients with osteoporosis, as corroborated by immunohistochemical staining images. Functional analyses revealed enrichment of the MAPK-associated cascade. 14-3-3η was correlated with MAPK family proteins and five key miRNAs, including mir-142-3p. In addition, 14-3-3η knockdown in BMSCs increased the mRNA and protein expression levels of Hif-α, VEGF, BMP-2, OPN, OST, and Runx2, and enhanced the cells migration ability. Under hypoxic conditions, Hif-α and BMP-2 protein expression levels were upregulated, whereas those of 14-3-3η and MAPK3 were downregulated. Co-immunoprecipitation experiments showed decreased binding of 14-3-3η to MAPK3. 14-3-3η knockdown produced the same results as hypoxia induction. Adding caspase3 inhibitor and knocking down 14-3-3η again prevented MAPK3 cleavage by caspase3 and inhibited BMP-2 expression. Moreover, under hypoxic conditions, miR-142-3P expression was upregulated and luciferase assays revealed 14-3-3η as its target gene. miR-142-3P overexpression decreased mRNA and protein levels of 14-3-3η and MAPK3, while increasing BMP-2 expression. miR-142-3P knockdown reversed these results. BMSC osteogenesis was suppressed by 14-3-3η, whereas miRNA-142-3p promoted it through the inhibition of 14-3-3η.

ObjectiveAssociations between diseases of the musculoskeletal system and connective tissue (MSCTD) and breast cancer (BC) have not been elucidated completely. The purpose of this study was to investigate the associations of MSCTD, rheumatoid arthritis (RA), Sjogren syndrome (SS), systemic lupus erythematosus (SLE), systemic sclerosis (SSc), dermatomyositis (DM), polymyositis (PM), osteoarthritis (OA) of hip or knee, and ankylosing spondylitis (AS) with BC in European populations and East Asian populations using Mendelian randomized (MR) analysis.MethodsThe genetic instruments linked to MSCTD, RA, SS, SLE, SSc, DM, PM, OA, and AS were chosen from the EBI database of complete genome-wide association studies (GWAS) summary data and the FinnGen consortium. The associations of genetic variants with BC were extracted from the Breast Cancer Association Consortium (BCAC). Two Sample MR was performed using summary data from GWAS, principally using the inverse variant weighted (IVW) method. Heterogeneity, pleiotropy, and sensitivity analyses were performed to evaluate the robustness of the results by weighted median, MR Egger, simple mode, weighted mode, and leave-one-out analysis.ResultsIn the European population, causal relationships between RA and BC (OR=1.04, 95%CI: 1.01-1.07, P=0.023), AS and BC (OR=1.21, 95%CI: 1.06-1.36, P=0.013) were confirmed. IVW analysis showed DM (OR=0.98, 95%CI: 0.96-0.99, P=0.026) and PM (OR=0.98, 95%CI: 0.97-0.99, P=0.002) were associated with slightly decreased risks of estrogen receptor (ER)+ BC, and MSCTD was associated with an increased risk of ER- BC (OR=1.85, 95%CI: 1.27-2.44, P=0.039). There was no causal relationship between SLE, SS, SSc, OA, and BC, neither ER+ BC nor ER- BC. However, in the East Asian population, IVW analysis showed that RA (OR=0.94, 95%CI: 0.89-0.99, P=0.0096) and SLE (OR=0.95, 95%CI: 0.92-0.99, P=0.0058) was associated with decreased risks of BC.ConclusionsThis study suggests that causal relationships between patients with MSCTD and BC in the European population are different from those in the East Asian population, patients with RA and AS in the European population have an increased risk of BC, patients with MSCTD have increased risk of ER- BC in the European population, while patients with RA and SLE in the East Asian population have decreased risk of BC.

This work aims to analyze and construct a novel competing endogenous RNA (ceRNA) network in ankylosing spondylitis (AS) with bone bridge formation, lncRNA. Using RNA sequencing and bioinformatics, we analyzed expression profiles of long noncoding RNAs (lncRNAs), microRNAs (miRNAs), and mRNAs in whole blood cells from 5 AS patients and 3 healthy individuals. Next, we verified the expression levels of candidate lncRNAs in 97 samples using the ΔΔCt value of real-time quantitative polymerase chain reaction (qRT-PCR). We used multivariate logistic regression analysis to screen lncRNAs and clinical indicators for use in the prediction model. Both SPSS 24.0 and R software were used for data analysis and prediction model construction. The results showed that compared with the normal controls, 205 long noncoding RNAs (lncRNAs), 961 microRNAs (miRNAs), and 200 mRNAs (DEmRNAs) were differentially expressed in the AS patients. We identified lncRNA 122K13.12 and lncRNA 326C3.7 among 205 lncRNAs differentially expressed between AS patients and healthy humans. Then, we noted that 30 miRNAs and five mRNAs formed a ceRNA network together with these two lncRNAs. These ceRNA networks might regulate the tumor necrosis factor (TNF) signaling pathway in AS development. In addition, the expression level of lncRNA 122K13.12 and lncRNA 326C3.7 correlated with various structural damage indicators in AS. Specifically, the lncRNA 326C3.7 expression level was an independent risk factor in bone bridge formation [area under the ROC curve (AUC) = 0.739 (0.609–0.870) and p = 0.003], and the best Youden Index was 0.405 (sensitivity = 0.800 and specificity = 0.605). Moreover, we constructed a lncRNA-based nomogram that could effectively predict bone bridge formation [AUC = 0.870 (0.780–0.959) and p < 0.001, and the best Youden Index was 0.637 (sensitivity = 0.900 and specificity = 0.737)]. In conclusion, we uncovered a unique ceRNA signaling network in AS with bone bridge formation and identified novel biomarkers and prediction models with the potential for clinical applications.