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Background Vertebral fractures (VFs) are the most common clinical manifestation of osteoporosis associated with high morbimortality. A personal/familiar history of fractures increases the risk of fractures. The purpose of this study is to identify possible molecular markers associated with osteoporotic VFs in elderly women from community. Methods Transcriptomic analysis using Affymetrix HTA2 microarray was performed using whole blood samples of 240 subjects from a population‐based survey (Sao Paulo Ageing & Health [SPAH] study). Only elderly women with osteoporosis diagnosis by densitometry were analyzed, and divided in two groups: VF: women with osteoporosis and VFs versus no vertebral fracture (NVF): women with osteoporosis and NVFs. They were matched for age, chronic disease, medication use, and bone mineral density (BMD). The logistic regression model adjusted for age was applied for transcriptome data analysis. SYBR green‐based quantitative polymerase chain reaction (qPCR) was used to validate the most significant expression changes obtained in the microarray experiment. Results Microarray analysis identified 142 differentially expressed genes (DEGs, p < .01), 57 upregulated and 85 downregulated, compared VF versus NVF groups. The DEG with the greatest expression difference was the Gamma2‐Syntrophin (SNTG2) (β = 31.88, p = .005). Validation by qPCR confirmed increased expression in VF group of Syntrophin (SNTG2, fold change = 2.79, p = .009), TRAF3 Interacting Protein2 (TRAF3IP2, fold change = 2.79, p = .020), and Integrin Subunit Alpha 6 (ITGA6, fold change = 2.86, p = .038). Conclusion Our data identified and validated the association of SNTG2 (608715), TRAF3IP2 (607043), and ITGA6 (147556) with osteoporotic VF in elderly women, independently of BMD. These results suggest that these transcripts have potential clinical significance and may help to explain the molecular mechanisms and biological functions of vertebral fracture.

We report a rare case of aseptic arthritis in the temporomandibular joint of a patient with sickle cell anemia. A 22-year-old woman with sickle cell disease, in the 18th week of gestation, was referred by her hematologist to investigate a sudden mouth opening limitation and severe pain on her left cheek. The patient received a standard pain assessment protocol, clinical examination, and complementary exams (complete blood count, hemoglobin electrophoresis, blood solubility test, panoramic radiograph, and magnetic resonance imaging [MRI]). The blood results were consistent with a sickle cell crisis and the MRI showed an inflammatory process around the left temporomandibular joint. Treatment with opioid analgesics and blood transfusion provided good results. Sickle cell anemia is a disease that can cause arthritis of the temporomandibular joint, and although it is rare, clinicians should be attentive to the differential diagnosis in patients with this disease.

Despite the well-established association of gene expression deregulation with low muscle mass (LMM), the associated biological mechanisms remain unclear. Transcriptomic studies are capable to identify key mediators in complex diseases. We aimed to identify relevant mediators and biological mechanisms associated with age-related LMM. LMM-associated genes were detected by logistic regression using microarray data of 20 elderly women with LMM and 20 age and race-matched controls extracted from our SPAH Study (GSE152073). We performed weighted gene co-expression analysis (WGCNA) that correlated the identified gene modules with laboratorial characteristics. Gene enrichment analysis was performed and an LMM predictive model was constructed using Support Vector Machine (SVM). Overall, 821 discriminating transcripts clusters were identified (|beta coefficient| >1; p -value <0.01). From this list, 45 predictors of LMM were detected by SVM and validated with 0.7 of accuracy. Our results revealed that the well-described association of inflammation, immunity and metabolic alterations is also relevant at transcriptomic level. WGCNA highlighted a correlation of genes modules involved in immunity pathways with vitamin D level (R = 0.63, p = 0.004) and the Agatston score (R = 0.51, p = 0.02). Our study generated a predicted regulatory network and revealed significant metabolic pathways related to aging processes, showing key mediators that warrant further investigation.