Investigating the impact of Wnt pathway-related genes on biomarker and diagnostic model development for osteoporosis in postmenopausal females.

The Wnt signaling pathway is essential for bone development and maintaining skeletal homeostasis, making it particularly relevant in osteoporosis patients. Our study aimed to identify distinct molecular clusters associated with the Wnt pathway and develop a diagnostic model for osteoporosis in postmenopausal Caucasian women. We downloaded three datasets (GSE56814, GSE56815 and GSE2208) related to osteoporosis from the GEO database. Our analysis identified a total of 371 differentially expressed genes (DEGs) between low and high bone mineral density (BMD) groups, with 12 genes associated with the Wnt signaling pathway, referred to as osteoporosis-associated Wnt pathway-related genes. Employing four independent machine learning models, we established a diagnostic model using the 12 osteoporosis-associated Wnt pathway-related genes in the training set. The XGB model showed the most promising discriminative potential. We further validate the predictive capability of our diagnostic model by applying it to three external datasets specifically related to osteoporosis. Subsequently, we constructed a diagnostic nomogram based on the five crucial genes identified from the XGB model. In addition, through the utilization of DGIdb, we identified a total of 30 molecular compounds or medications that exhibit potential as promising therapeutic targets for osteoporosis. In summary, our comprehensive analysis provides valuable insights into the relationship between the osteoporosis and Wnt signaling pathway.

Management of Postmenopausal Osteoporosis by Moroccan General Practitioners: A Cross-Sectional Survey.

BACKGROUND: Despite the existence of effective treatments and prescribed therapeutic protocols, there is a lack of management of osteoporosis, resulting in increased secondary morbidity and mortality. The general practitioner (GP) is the first-line practitioner for the detection and management of osteoporosis. OBJECTIVE: This study was conducted to explore the practices, knowledge, and difficulties in postmenopausal osteoporosis management reported by GPs. METHODS: An anonymous questionnaire (19 questions) was created via Google Forms and distributed to 300 GPs via social networks (WhatsApp, Facebook, and Gmail). The survey results were automatically calculated on "Google Forms" and checked using SPSS.20 software. RESULTS: A total of 129 responses were received, representing a response rate of 43%. The majority of respondents were women (67.2%). The definition of osteoporosis was variable, with 51.6% defining it as a T-score of ≤-2.5 SD, 25.8% defining it as diffuse bone demineralization, and 12.1% defining it as a fracture after falling with low energy. Prolonged corticosteroid therapy was the most commonly indicated reason for measuring bone mineral density (BMD) (81.39%). The calcium phosphate balance was the most requested (90.1%). Vitamin D and calcium supplementation were reported by 74.41% and 54.26% of GPs, respectively. Fracture of the upper end of the femur was the main therapeutic indication (65.11%). Most GPs surveyed (73.3%) were unfamiliar with the fracture risk assessment tool (FRAX). Most of the GPs gave advice on fall prevention to their patients (83.72%), and 62.5% of GPs monitored their patients' height. Anti-osteoporosis treatment was maintained for 3 to 5 years by 44.96% of GPs. CONCLUSION: Our survey found that the practices and knowledge of GPs on osteoporosis vary widely and often deviate from the recommended standards. This highlights the need for more excellent education of GPs, due to their vital role in the management of osteoporosis.

Effect of denosumab on glucose metabolism in postmenopausal osteoporotic women with prediabetes: a study protocol for a 12-month multicenter, open-label, randomized controlled trial.

BACKGROUND: Participants with prediabetes are at a high risk of developing type 2 diabetes (T2D). Recent studies have suggested that blocking the receptor activator of nuclear factor-κB ligand (RANKL) may improve glucose metabolism and delay the development of T2D. However, the effect of denosumab, a fully human monoclonal antibody that inhibits RANKL, on glycemic parameters in the prediabetes population is uncertain. We aim to examine the effect of denosumab on glucose metabolism in postmenopausal women with osteoporosis and prediabetes. METHODS: This is a 12-month multicenter, open-label, randomized controlled trial involving postmenopausal women who have been diagnosed with both osteoporosis and prediabetes. Osteoporosis is defined by the World Health Organization (WHO) as a bone mineral density T score of ≤ - 2.5, as measured by dual-energy X-ray absorptiometry (DXA). Prediabetes is defined as (i) a fasting plasma glucose level of 100-125 mg/dL, (ii) a 2-hour plasma glucose level of 140-199 mg/dL, or (iii) a glycosylated hemoglobin A1c (HbA1c) level of 5.7-6.4%. A total of 346 eligible subjects will be randomly assigned in a 1:1 ratio to receive either subcutaneous denosumab 60 mg every 6 months or oral alendronate 70 mg every week for 12 months. The primary outcome is the change in HbA1c levels from baseline to 12 months. Secondary outcomes include changes in fasting and 2-hour blood glucose levels, serum insulin levels, C-peptide levels, and insulin sensitivity from baseline to 12 months, and the incidence of T2D at the end of the study. Follow-up visits will be scheduled at 3, 6, 9, and 12 months. DISCUSSION: This study aims to provide evidence on the efficacy of denosumab on glucose metabolism in postmenopausal women with osteoporosis and prediabetes. The results derived from this clinical trial may provide insight into the potential of denosumab in preventing T2D in high-risk populations. TRIAL REGISTRATION: This study had been registered in the Chinese Clinical Trials Registry. REGISTRATION NUMBER: ChiCTR2300070789 on April 23, 2023. https://www.chictr.org.cn .

Identification of ROCK1 as a novel biomarker for postmenopausal osteoporosis and pan-cancer analysis.

BACKGROUND: Postmenopausal osteoporosis (PMOP) is a prevalent bone disorder with significant global impact. The elevated risk of osteoporotic fracture in elderly women poses a substantial burden on individuals and society. Unfortunately, the current lack of dependable diagnostic markers and precise therapeutic targets for PMOP remains a major challenge. METHODS: PMOP-related datasets GSE7429, GSE56814, GSE56815, and GSE147287, were downloaded from the GEO database. The DEGs were identified by "limma" packages. WGCNA and Machine Learning were used to choose key module genes highly related to PMOP. GSEA, DO, GO, and KEGG enrichment analysis was performed on all DEGs and the selected key hub genes. The PPI network was constructed through the GeneMANIA database. ROC curves and AUC values validated the diagnostic values of the hub genes in both training and validation datasets. xCell immune infiltration and single-cell analysis identified the hub genes' function on immune reaction in PMOP. Pan-cancer analysis revealed the role of the hub genes in cancers. RESULTS: A total of 1278 DEGs were identified between PMOP patients and the healthy controls. The purple module and cyan module were selected as the key modules and 112 common genes were selected after combining the DEGs and module genes. Five Machine Learning algorithms screened three hub genes (KCNJ2, HIPK1, and ROCK1), and a PPI network was constructed for the hub genes. ROC curves validate the diagnostic values of ROCK1 in both the training (AUC = 0.73) and validation datasets of PMOP (AUC = 0.81). GSEA was performed for the low-ROCK1 patients, and the top enriched field included protein binding and immune reaction. DCs and NKT cells were highly expressed in PMOP. Pan-cancer analysis showed a correlation between low ROCK1 expression and SKCM as well as renal tumors (KIRP, KICH, and KIRC). CONCLUSIONS: ROCK1 was significantly associated with the pathogenesis and immune infiltration of PMOP, and influenced cancer development, progression, and prognosis, which provided a potential therapy target for PMOP and tumors. However, further laboratory and clinical evidence is required before the clinical application of ROCK1 as a therapeutic target.

Predictors of osteoporotic fracture in postmenopausal women: a meta-analysis.

Osteoporosis affects more than 200 million women worldwide, with postmenopausal women being particularly susceptible to this condition and its severe sequelae disproportionately, such as osteoporotic fractures. To date, the current focus has been more on symptomatic treatment, rather than preventive measures. To address this, we performed a meta-analysis aiming to identify potential predictors of osteoporotic fractures in postmenopausal women, with the ultimate goal of identifying high-risk patients and exploring potential therapeutic approaches. We searched Embase, MEDLINE and Cochrane with search terms (postmenopausal AND fracture) AND ("risk factor" OR "predictive factor") in May 2022 for cohort and case-control studies on the predictors of osteoporotic fracture in postmenopausal women. Ten studies with 1,287,021 postmenopausal women were found eligible for analyses, in which the sample size ranged from 311 to 1,272,115. The surveyed date spanned from 1993 to 2021. Our results suggested that age, BMI, senior high school and above, parity ≥ 3, history of hypertension, history of diabetes mellitus, history of alcohol intake, age at menarche ≥ 15, age at menopause < 40, age at menopause > 50, estrogen use and vitamin D supplements were significantly associated with osteoporotic fracture in postmenopausal women. Our findings facilitate the early prediction of osteoporotic fracture in postmenopausal women and may contribute to potential therapeutic approaches. By focusing on preventive strategies and identifying high-risk individuals, we can work toward reducing the burden of osteoporosis-related fractures in this vulnerable population.

Identification and evaluation of circulating exosomal miRNAs for the diagnosis of postmenopausal osteoporosis.

BACKGROUND: Postmenopausal osteoporosis (PMOP) is a common condition that leads to a loss of bone density and an increased risk of fractures in women. Recent evidence suggests that exosomal miRNAs are involved in regulating bone development and osteogenesis. However, exosomal miRNAs as biomarkers for PMOP diagnosis have not been systematically evaluated. In this study, we aim to identify PMOP-associated circulating exosomal miRNAs and evaluate their diagnostic performance. METHODS: We performed next-generation sequencing and bioinformatics analysis of plasma exosomal miRNAs from 12 PMOP patients and 12 non-osteoporosis controls to identify PMOP-associated exosomal miRNAs, and then validated them in an independent natural community cohort with 26 PMOP patients and 21 non-osteoporosis controls. Exosomes were isolated with the size exclusion chromatography method from the plasma of elder postmenopausal women. The plasma exosomal miRNA profiles were characterized in PMOP paired with controls with next-generation sequencing. Potential plasma exosomal miRNAs were validated by qRT-PCR in the validation cohort, and their performance in diagnosing PMOP was systematically evaluated with the receiver operating characteristic curve. RESULTS: Twenty-seven miRNAs were identified as differentially expressed in PMOP versus controls in sequencing data, of which six exosomal miRNAs (miR-196-5p, miR-224-5p, miR320d, miR-34a-5p, miR-9-5p, and miR-98-5p) were confirmed to be differentially expressed in PMOP patients by qRT-PCR in the validation cohort. The three miRNAs combination (miR-34a-5p + miR-9-5p + miR-98-5p) demonstrated the best diagnostic performance, with an AUC = 0.734. In addition, the number of pregnancies was found to be an independent risk factor that can improve the performance of exosomal miRNAs in diagnosing PMOP. CONCLUSIONS: These results suggested that the plasma exosomal miRNAs had the potential to serve as noninvasive diagnostic biomarkers for PMOP.

Klotho reduces the risk of osteoporosis in postmenopausal women: a cross-sectional study of the National Health and Nutrition Examination Survey (NHANES).

BACKGROUND: Osteoporosis (OP) is one of the diseases that endanger the health of the elderly population. Klotho protein is a hormone with anti-aging effects. A few studies have discussed the relationship between Klotho and OP. However, there is still a lack of research on larger populations. This study aims to evaluate the association between OP and Klotho in American postmenopausal women. METHODS: This is a retrospective study. We searched the National Health and Nutrition Examination Survey (NHANES) database and collected data of 3 survey cycles, finally involving 871 postmenopausal women over 50 years old in the present study. All participants took dual-energy X-ray absorptiometry examination and serum Klotho testing at the time of investigation. After adjusting the possible confounding variables, a multivariate regression model was employed to estimate the relationship between OP and Klotho proteins. Besides, the P for trend and restricted cubic spline (RCS) were applied to examine the threshold effect and calculate the inflection point. RESULTS: Factors influencing the occurrence of OP included age, ethnicity, body mass index and Klotho levels. Multivariate regression analysis indicated that the serum Klotho concentration was lower in OP patients than that in participants without OP (OR[log2Klotho] = 0.568, P = 0.027). The C-index of the prediction model built was 0.765, indicating good prediction performance. After adjusting the above-mentioned four variables, P values for trend showed significant differences between groups. RCSs revealed that when the Klotho concentration reached 824.09 pg/ml, the risk of OP decreased drastically. CONCLUSION: Based on the analysis of the data collected from the NHANES database, we propose a correlation between Klotho and postmenopausal OP. A higher serum Klotho level is related to a lower incidence of OP. The findings of the present study can provide guidance for research on diagnosis and risk assessment of OP.

A clinical prediction model for 10-year risk of self-reported osteoporosis diagnosis in pre- and perimenopausal women.

A machine learning model using clinical, laboratory, and imaging data was developed to predict 10-year risk of menopause-related osteoporosis. The resulting predictions, which are sensitive and specific, highlight distinct clinical risk profiles that can be used to identify patients most likely to be diagnosed with osteoporosis. PURPOSE: The aim of this study was to incorporate demographic, metabolic, and imaging risk factors into a model for long-term prediction of self-reported osteoporosis diagnosis. METHODS: This was a secondary analysis of 1685 patients from the longitudinal Study of Women's Health Across the Nation using data collected between 1996 and 2008. Participants were pre- or perimenopausal women between 42 and 52 years of age. A machine learning model was trained using 14 baseline risk factors-age, height, weight, body mass index, waist circumference, race, menopausal status, maternal osteoporosis history, maternal spine fracture history, serum estradiol level, serum dehydroepiandrosterone level, serum thyroid-stimulating hormone level, total spine bone mineral density, and total hip bone mineral density. The self-reported outcome was whether a doctor or other provider had told participants they have osteoporosis or treated them for osteoporosis. RESULTS: At 10-year follow-up, a clinical osteoporosis diagnosis was reported by 113 (6.7%) women. Area under the receiver operating characteristic curve of the model was 0.83 (95% confidence interval, 0.73-0.91) and Brier score was 0.054 (95% confidence interval, 0.035-0.074). Total spine bone mineral density, total hip bone mineral density, and age had the largest contributions to predicted risk. Using two discrimination thresholds, stratification into low, medium, and high risk, respectively, was associated with likelihood ratios of 0.23, 3.2, and 6.8. At the lower threshold, sensitivity was 0.81, and specificity was 0.82. CONCLUSION: The model developed in this analysis integrates clinical data, serum biomarker levels, and bone mineral densities to predict 10-year risk of osteoporosis with good performance.

The prevalence of osteoporosis in postmenopausal women in urban Tianjin, China and its related factors.

OBJECTIVES: The aims of the study are to understand the prevalence of osteoporosis in postmenopausal women in urban Tianjin, China and its related factors through a questionnaire and to assess the correlation between individual characteristics, physical mobility, psychological and emotional well-being, and prevalence, as well as people's awareness of osteoporosis. METHODS: We selected 240 postmenopausal women from 12 randomly selected streets in 6 administrative districts of Tianjin for bone mineral density measurement and a face-to-face questionnaire survey to obtain the relevant data. Female residents who had lived in the communities under the jurisdiction of the incorporated streets for more than 10 years and had been in menopause for 2 years were included. The women were made aware of the study, there were no communication barriers, and they were willing to undergo dual-energy absorptiometry and cooperate in completing the questionnaire. We used one-way analysis of variance, Fisher exact test, and Pearson correlation analysis for the statistical analysis. RESULTS: The overall prevalence of osteoporosis in postmenopausal women in the six districts of Tianjin was found to be 52.08%, and the χ 2 test for trend showed a clear trend of increasing with age ( P = 0.035). Body mass index was found to be the most significant personal characteristic affecting the prevalence of osteoporosis; the mean values of the nonosteoporosis and osteoporosis group were (25.45 ± 3.09) and (23.85 ± 3.16), respectively ( P < 0.001); previous fractures were closely associated with the prevalence of osteoporosis. Awareness about osteoporosis had not disseminated among the population, and 9.17% of the participants had never heard of the disease. While 75.42% and 72.92% of the participants, respectively, believe that the harm of osteoporosis cannot be compared with heart disease and cerebral infarction, 56.67% had never had an examination for osteoporosis and paid little to no attention to this disease. People still had major misconceptions about the hazards of osteoporosis and common-sense precautions that needed to be followed. CONCLUSIONS: Although osteoporosis is prevalent among postmenopausal women in urban Tianjin and is strongly linked to both history of fracture and body mass index, most women are only familiar with the disease's name and lack an understanding of the dangers it poses as well as the importance of early diagnosis and treatment. To ensure the prevention and control of osteoporosis, it is crucial to focus on increasing the examination and treatment rates and spreading awareness of the three-level diagnosis and treatment pattern among the public.

Estimating the future clinical and economic benefits of improving osteoporosis diagnosis and treatment among postmenopausal women across eight European countries.

A population-level, cross-sectional model was developed to estimate the clinical and economic burden of osteoporosis among women (≥ 70 years) across eight European countries. Results demonstrated that interventions aimed at improving fracture risk assessment and adherence would save 15.2% of annual costs in 2040. PURPOSE: Osteoporosis is associated with significant clinical and economic burden, expected to further increase with an ageing population. This modelling analysis assessed clinical and economic outcomes under different hypothetical disease management interventions to reduce this burden. METHODS: A population-level, cross-sectional cohort model was developed to estimate numbers of incident fractures and direct costs of care among women (≥ 70 years) in eight European countries under different hypothetical interventions: (1) an improvement in the risk assessment rate, (2) an improvement in the treatment adherence rate and (3) a combination of interventions 1 and 2. A 50% improvement from the status quo, based on existing disease management patterns, was evaluated in the main analysis; scenario analyses evaluated improvement of either 10 or 100%. RESULTS: Based on existing disease management patterns, a 44% increase in the annual number of fractures and costs was predicted from 2020 to 2040: from 1.2 million fractures and €12.8 billion in 2020 to 1.8 million fractures and €18.4 billion in 2040. Intervention 3 provided the greatest fracture reduction and cost savings (a decrease of 17.9% and 15.2% in fractures and cost, respectively) in 2040 compared with intervention 1 (decreases of 8.7% and 7.0% in fractures and cost, respectively) and intervention 2 (10.0% and 8.8% reductions in fracture and cost, respectively). Scenario analyses showed similar patterns. CONCLUSION: These analyses suggest that interventions which improve fracture risk assessment and adherence to treatments would relieve the burden of osteoporosis, and that a combination strategy would achieve greatest benefits.

Discovery of novel serum biomarkers for diagnosing and predicting postmenopausal osteoporosis patients by 4D-label free protein omics.

We aimed to identify protein biomarkers that could rapidly and accurately diagnose osteoporosis patients (OPs) using a highly sensitive proteomic immunoassay. Four-dimensional (4D) label-free proteomics analysis was performed to determine the differentially expressed proteins in serum collected from 10 postmenopausal osteoporosis patients and 6 non-osteoporosis patients. The ELISA method was used to select the predicted proteins for verification. Serum was taken from 36 postmenopausal osteoporosis patients and 36 healthy individuals from normal postmenopausal women. Receiver operating characteristic (ROC) curves were used to determine the diagnostic potential of this method. We validated the expression of these six proteins using ELISA. The CDH1, IGFBP2, and VWF of osteoporosis patients were significantly higher than those of the normal group. PNP was significantly lower than that in the normal group. And using ROC curve calculation, serum CDH1 had a cut-off of 3.78 ng/mL with a sensitivity of 84.4%, and PNP had a cut-off of 944.32 ng/mL with 88.9% sensitivity. These outcomes suggest that serum-level CHD1 and PNP have the potential power as effective indicators for the diagnosis of PMOP. Our results suggest that CHD1 and PNP might be associated with the pathogenesis of OP and would be helpful in diagnosing OP. Therefore, CHD1 and PNP may act as potential key markers in OP.

GRADE-ADOLOPMENT of clinical practice guideline for postmenopausal osteoporosis management-a Pakistani context.

Due to its high prevalence, we aimed to create postmenopausal osteoporosis clinical practice guideline via GRADE-ADOLOPMENT for Pakistan. We recommend a higher dose (2000-4000 IU) of vitamin D for osteoporotic patients who are old, have malabsorption, or are obese. The guideline will help standardize care provision and improve health care outcomes for osteoporosis. PURPOSE: Postmenopausal osteoporosis affects one in every five postmenopausal women in Pakistan. An evidence-based clinical practice guideline (CPG) is needed to standardize care provision to optimize health outcomes. Hence, we aimed to develop CPG for the management of postmenopausal osteoporosis in Pakistan. METHODS: The GRADE-ADOLOPMENT process was used to adopt (as is or with minor changes), exclude (omit), or adapt (modify based on local context) recommendations to the source guideline (SG)-clinical practice guidelines for the diagnosis and treatment of postmenopausal osteoporosis-2020 update from American Association of Clinical Endocrinology (AACE). RESULTS: The SG was "adoloped" to cater to the local context. The SG consisted of 51 recommendations. Forty-five recommendations were adopted as is. Due to unavailability of drugs, 4 recommendations were adopted with minor changes, and one was excluded, while one recommendation was adopted with the inclusion of use of a surrogate FRAX tool specific for Pakistan. One recommendation regarding vitamin D dosage was adapted to recommend a dose of 2000-4000 IU of vitamin D in patients with obesity, malabsorption, and old age. CONCLUSION: The developed Pakistani postmenopausal osteoporosis guideline consists of 50 recommendations. The guideline created recommends a higher dose (2000-4000 IU) of vitamin D for patients who are old, have malabsorption, or are obese, which is an adaptation from the SG by the AACE. This higher dose is justified as lower doses prove to be suboptimal in these groups and should be complemented with baseline vitamin D and calcium levels.

Controlling Nutritional Status score and postmenopausal osteoporosis.

OBJECTIVE: This study investigated the association between CONUT score and postmenopausal osteoporosis. METHODS: Postmenopausal women who were seen at an outpatient clinic in a tertiary hospital for routine gynecologic examination between January 2017 and June 2022 were included in the study. Based on their T-scores, a total of 423 women were divided into two groups. Group 1 included 216 women with osteoporosis (T-score < -2.5 SD), and group 2 included 207 women with normal bone mineral density (T-score > -1 SD). The formula for the CONUT score corresponds to collection of scores from albumin, total cholesterol, and total lymphocyte count. Higher scores indicate poorer nutritional control. RESULTS: Mean age and mean age at menopause were similar in both groups. The duration of menopause, however, was higher in the women with osteoporosis (11.55 ± 6.82 vs 9.202 ± 6.14 y, P < 0.001). The 25-hydroxy vitamin D level was low in both groups. Body mass index of women with normal bone mineral density was higher than that of women with osteoporosis (31.54 ± 4.19 vs 28.52 ± 4.43 kg/m 2 , P < 0.001). The CONUT scores of the two groups were calculated and found to be higher in women with osteoporosis (3.180 ± 1.804 vs 0.391 ± 0.687, P < 0.001). According to the receiver operating characteristic curve analysis of the CONUT score for predicting osteoporosis, the area under the curve was calculated as 0.932, with a sensitivity of 86.6% and a specificity of 91.1% ( P < 0.001). CONCLUSIONS: Diet plays an important role in the development of osteoporosis. In this study, it was shown that there is a relationship between CONUT score and osteoporosis.

Bioinformatics identification and experimental validation of m6A-related diagnostic biomarkers in the subtype classification of blood monocytes from postmenopausal osteoporosis patients.

Background: Postmenopausal osteoporosis (PMOP) is a common bone disorder. Existing study has confirmed the role of exosome in regulating RNA N6-methyladenosine (m6A) methylation as therapies in osteoporosis. However, it still stays unclear on the roles of m6A modulators derived from serum exosome in PMOP. A comprehensive evaluation on the roles of m6A modulators in the diagnostic biomarkers and subtype identification of PMOP on the basis of GSE56815 and GSE2208 datasets was carried out to investigate the molecular mechanisms of m6A modulators in PMOP. Methods: We carried out a series of bioinformatics analyses including difference analysis to identify significant m6A modulators, m6A model construction of random forest, support vector machine and nomogram, m6A subtype consensus clustering, GO and KEGG enrichment analysis of differentially expressed genes (DEGs) between different m6A patterns, principal component analysis, and single sample gene set enrichment analysis (ssGSEA) for evaluation of immune cell infiltration, experimental validation of significant m6A modulators by real-time quantitative polymerase chain reaction (RT-qPCR), etc. Results: In the current study, we authenticated 7 significant m6A modulators via difference analysis between normal and PMOP patients from GSE56815 and GSE2208 datasets. In order to predict the risk of PMOP, we adopted random forest model to identify 7 diagnostic m6A modulators, including FTO, FMR1, YTHDC2, HNRNPC, RBM15, RBM15B and WTAP. Then we selected the 7 diagnostic m6A modulators to construct a nomogram model, which could provide benefit with patients according to our subsequent decision curve analysis. We classified PMOP patients into 2 m6A subtypes (clusterA and clusterB) on the basis of the significant m6A modulators via a consensus clustering approach. In addition, principal component analysis was utilized to evaluate the m6A score of each sample for quantification of the m6A subgroups. The m6A scores of patients in clusterB were higher than those of patients in clusterA. Moreover, we observed that the patients in clusterA had close correlation with immature B cell and gamma delta T cell immunity while clusterB was linked to monocyte, neutrophil, CD56dim natural killer cell, and regulatory T cell immunity, which has close connection with osteoclast differentiation. Notably, m6A modulators detected by RT-qPCR showed generally consistent expression levels with the bioinformatics results. Conclusion: In general, m6A modulators exert integral function in the pathological process of PMOP. Our study of m6A patterns may provide diagnostic biomarkers and immunotherapeutic strategies for future PMOP treatment.

Comparison of Cytokine Profile between Postmenopausal Women with and Without Osteoporosis - A Case-Control Study.

BACKGROUND: Chronic low-grade inflammation is involved in the pathogenesis of postmenopausal osteoporosis, but the cytokines implicated remain elusive. OBJECTIVE: This study aimed to compare the difference in cytokine profile between postmenopausal women with and without osteoporosis in Klang Valley, Malaysia. METHODS: Postmenopausal women with (n = 20) and without osteoporosis (n = 20) were recruited for this study. Their bone health status was determined using dual-energy X-ray absorptiometry. Their fasting blood was collected for proteomic analysis. A protein array was performed for four subjects randomly selected from each group to screen the potential cytokines. Three cytokines at least 20% different between groups and consistently expressed by each subject were selected for validation using enzyme-linked immunosorbent assays (ELISA). RESULTS: The protein array screening demonstrated that platelet-derived growth factor-BB, interleukin- 6 receptor (IL-6R), and tissue inhibitor of metallopeptidase-2 were higher in women with osteoporosis than women without osteoporosis (n = 4 per group), and consistently expressed by all women. Only body mass index (BMI)-adjusted logarithmically transformed IL-6R levels were lower among postmenopausal women with osteoporosis compared to women with normal bone health (p = 0.026) (n = 16 per group) in the ELISA test. CONCLUSION: IL-6R was lower among postmenopausal women with osteoporosis compared to women with normal bone health after adjusting for BMI. However, a large-scale epidemiological study with proteomic analysis needs to confirm the findings.

Validation of the clinical consensus recommendations on the management of fracture risk in postmenopausal women with type 2 diabetes.

BACKGROUND AND AIMS: Bone fragility is recognized as a complication of type 2 diabetes (T2D). However, the fracture risk in T2D is underestimated using the classical assessment tools. An expert panel suggested the diagnostic approaches for the detection of T2D patients worthy of bone-active treatment. The aim of the study was to apply these algorithms to a cohort of T2D women to validate them in clinical practice. METHODS AND RESULTS: The presence of T2D-specific fracture risk factors (T2D ≥ 10 years, ≥1 T2D complications, insulin or thiazolidinedione use, poor glycaemic control) was assessed at baseline in 107 postmenopausal T2D women. In all patients at baseline and in 34 patients after a median follow-up of 60.2 months we retrospectively evaluated bone mineral density and clinical and morphometric vertebral fractures. No patient was treated with bone-active drug. Following the protocols, 34 (31.8%) and 73 (68.2%) patients would have been pharmacologically and conservatively treated, respectively. Among 49 patients without both clinical fractures and major T2D-related risk factors, who would have been, therefore, conservatively followed-up without vertebral fracture assessment, only one showed a prevalent vertebral fracture (sensitivity 90%, negative predictive value 98%). The two patients who experienced an incident fracture would have been pharmacologically treated at baseline. CONCLUSIONS: The clinical consensus recommendations showed a very good sensitivity in identifying T2D postmenopausal women at high fracture risk. Among those with treatment indication as many as 13% of patients experienced an incident fracture, and, conversely, among those without treatment indication no incident fractures were observed.