Exploring the causal relationship between inflammatory bowel disease and sarcopenia-related traits: a two-sample Mendelian randomization analysis.

Previous observational studies have shown an association between inflammatory bowel disease (IBD) and sarcopenia. However, the causal relationship between IBD (including ulcerative colitis and Crohn's disease) and sarcopenia remains unclear. Thus, this study investigated whether genetically predicted IBD play a function in the occurrence of sarcopenia using Mendelian randomization (MR) analysis. This study used independent single nucleotide polymorphisms (SNPs) significantly associated with IBD as instrument variables (IVs). Sarcopenia-related components (hand grip strength, walking space, and appendicular lean mass (ALM)) were investigated as outcome factors, with summary-level data regarding these components of sarcopenia obtained from the UK Biobank. The IVW-MR analysis revealed that there were significant negative associations between IBD and hand grip strength (both left and right) as well as ALM. Besides, the results of IVW-MR analysis provided strong evidence of a causal relationship between genetically predicted Crohn's disease and hand grip strength and ALM. However, there were no significant associations found between ulcerative colitis and sarcopenia-related traits. Sensitivity tests confirmed the accuracy and robustness of the above MR analysis. Conclusions: Our MR analysis showed the causal effect of Crohn's disease on hand grip strength and ALM. This suggests that Crohn's disease may be a potential risk factor for sarcopenia.

The concentrations of bone calcium, phosphorus and trace metal elements in elderly patients with intertrochanteric hip fractures.

Introduction: Trace metal elements may play a crucial role in bone mineralization and metabolism. However, the quantification of trace element concentrations in human bone tissue has received little attention. Materials and methods: Bone tissue samples were collected from 55 elderly patients (15 males and 40 females) with intertrochanteric hip fractures. The calcium, phosphorus, manganese, iron, copper, and zinc concentrations in the cortical bone zone, cancellous bone zone, and junction zone between cortical and cancellous bone were determined by energy-dispersive X-ray fluorescence (EDX). The differences in trace element concentrations in the three regions were compared, and the correlation between gender and bone trace element contents of the bones was analyzed using the Kruskal-Wallis's test. The correlation between age, body mass index (BMI), and bone calcium, phosphorus concentrations, and trace elements in three bone zones was determined using Spearman correlation analysis. Results: The Kruskal-Wallis test showed no difference in bone phosphorus concentration among the three regions. In contrast, the difference in the concentrations of bone calcium and four metal elements was statistically significant (P<0.01). In addition, no statistical differences were observed in the concentrations of trace elements among the three regions in elderly male and female patients. Spearman correlation analysis showed a strong negative correlation between bone calcium and phosphorus in three bone regions (r=-0.999, -0.95, -0.998, P < 0.01) and a significant positive correlation between trace metal elements in the cancellous bone zone. In the junction zone, the BMI showed a strong positive correlation with bone calcium content (r=0.347, P=0.009) and a significant negative correlation with phosphorus content (r=-0.349, P=0.009). Conclusion: Bone calcium and phosphorus were the main components of hydroxyapatite, and these two elements accounted for the majority of bone mineral salts. Trace metal elements are essential for bone metabolism and specific synergistic interactions. BMI may be associated with bone calcium and phosphorus contents in elderly patients with osteoporosis.

Association between bone trace elements and osteoporosis in older adults: a cross-sectional study.

Objectives: Metal micronutrients deficiency may be one of the risk factors for the development of osteoporosis. This study aimed to measure the trace element contents in human bone tissue to analyze the relationship between micronutrients and osteoporosis. Design: A cross-sectional survey was performed on data from 51 elderly patients with proximal femoral fracture. Methods: The concentrations of calcium, phosphorus, manganese, iron, copper, and zinc in bone tissue samples from 51 elderly patients with proximal femoral fracture were determined by energy-dispersive X-ray fluorescence (EDX). Subjects were divided into osteoporosis and non-osteoporosis groups according to their bone mineral density (BMD) T-score values. The difference in metal elements concentrations in bone tissue between the two groups was compared, and the role of metal elements in osteoporosis was discussed. Results: There was no statistical difference in age, sex, body mass index (BMI), serum albumin, biochemical blood indices, and bone turnover markers between the two groups. The Mann-Whitney U test was used to compare the difference in metal elements concentrations in bone tissue samples between the two groups. The results showed that manganese, copper, and zinc concentrations in the cancellous bone were significantly higher in the non-osteoporosis group than in the osteoporosis group. Multivariate logistic regression analysis indicated that high bone zinc concentration [odds ratio = 0.26, 95% confidence interval (CI) = 0.075-0.928, p = 0.038] was negatively correlated with osteoporosis. Conclusion: Manganese, copper, and zinc play an essential role in bone mineralization and metabolism. Among them, zinc may be most closely related to osteoporosis and play a key role in bone development and maintenance of bone mass. Therefore, we believe that the design of zinc-rich compounds or nutrients as a new complementary factor to increase the intake of zinc for the elderly could be able to prevent and intervene in the occurrence of osteoporosis in the early stage.

Development and Verification of a Combined Diagnostic Model for Sarcopenia with Random Forest and Artificial Neural Network.

Background: Sarcopenia is a chronic disease characterized by an age-related decline in skeletal muscle mass and function, and diagnosis is challenging owing to the lack of a clear "gold standard" assessment method. Objective: This study is aimed at combining random forest (RF) and artificial neural network (ANN) methods to screen key potential biomarkers and establish an early sarcopenia diagnostic model. Methods: Three gene expression datasets were downloaded and merged by searching the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) in the merged dataset were identified by R software and subjected to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Afterward, the STRING database was employed for interaction analysis of the differentially encoded proteins. Then, RF was used to identify key genes from the DEGs, and a sarcopenia diagnostic model was constructed by ANN. Finally, the diagnostic model was assessed using a validation dataset, while its diagnostic performance was evaluated by the area under curve (AUC) value. Results: 107 sarcopenia-related DEGs were identified, and they were mainly enriched in the FoxO and AMPK signaling pathways involved in the molecular pathogenesis of sarcopenia. Thereafter, seven key genes (MT1X, FAM171A1, ZNF415, ARHGAP36, CISD1, ETNPPL, and WISP2) were identified by the RF classifier. The proteins encoded by three of these genes (CISD1, ETNPPL, and WISP2) may be potential biomarkers for sarcopenia. Finally, a diagnostic model for sarcopenia was successfully designed by ANN, achieving an AUC of 0.999 and 0.85 in the training and testing datasets, respectively. Conclusion: We identified several potential genetic biomarkers and successfully developed an early predictive model with high diagnostic performance for sarcopenia. Moreover, our results provide a valuable reference for the early diagnosis and screening of sarcopenia in the future.

Screening Potential Diagnostic Biomarkers for Age-Related Sarcopenia in the Elderly Population by WGCNA and LASSO.

Background: Sarcopenia is a common chronic disease characterized by age-related decline in skeletal muscle mass and function, and the lack of diagnostic biomarkers makes community-based screening problematic. Methods: Three gene expression profiles related with sarcopenia were downloaded and merged by searching the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) and eigengenes of a module in the merged dataset were identified by differential expression analysis and weighted gene coexpression network analysis (WGCNA), and common genes (CGs) were defined as the intersection of DEGs and eigengenes of a module. CGs were subjected to gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. Subsequently, the least absolute shrinkage and selection operator (LASSO) analysis was performed to screen the CGs for identifying the diagnostic biomarkers of sarcopenia. Based on the diagnostic biomarkers, we established a novel nomogram model of sarcopenia. At last, we validated the diagnostic biomarkers and evaluated the diagnostic performance of the nomogram model by the area under curve (AUC) value. Results: We screened out 107 DEGs and 788 eigengenes in the turquoise module, and 72 genes were selected as CGs of sarcopenia by intersection. GO analysis showed that CGs were mainly involved in metal ion detoxification and mitochondrial structure, and KEGG analysis revealed that CGs were mainly enriched in the mineral absorption, glucagon signaling pathway, FoxO signaling pathway, insulin signaling pathway, AMPK signaling pathway, and estrogen signaling pathway. Then, six diagnostic biomarkers (ARHGAP36, FAM171A1, GPCPD1, MT1X, ZNF415, and RXRG) were identified by LASSO analysis. Finally, the validation AUC values indicated that the six diagnostic biomarkers had high diagnostic accuracy for sarcopenia. Conclusion: We identified six diagnostic biomarkers with high diagnostic performance, providing new insights into the incidence and progression of sarcopenia in future research.

Association between bone turnover markers, BMD and height loss of cemented vertebrae after percutaneous vertebroplasty in patients with osteoporotic vertebral compression fractures.

INTRODUCTION: Percutaneous vertebroplasty (PVP) was recently performed for treating patients with osteoporotic vertebral compression fractures (OVCF). However, recompression of cemented vertebra with significant vertebral height loss occurred in the patients after PVP was observed during the follow-up period. The purpose is to explore the risk factors among several potential predictors for the height loss of treated vertebral bodies after PVP in patients with OVCF. METHODS: A study of 93 patients who had undergone PVP between May 1, 2016, and March 1, 2019, at the Spine Center of Huadong Hospital Affiliated to Fudan University was conducted. The fractured vertebral height loss ratio ≥ 15% at final follow-up were defined as cemented vertebra recompression. The following variables were measured and collected: age, gender, body mass index (BMI), bone mineral density (BMD), volume of bone cement injected, bone cement leakage, fractured vertebra segment, contact between bone cement and endplates, serum of calcium and phosphorus, and six kinds of bone turnover markers. RESULTS: Mann-Whitney U test and Univariate Logistic regression analysis showed that the cemented vertebra recompression was correlated with BMD, contact between bone cement and endplates, parathyroid hormone (PTH), and 25-hydroxy vitamin D3 (25-OH-D3). Following multivariate modeling, multiple factors logistic regression elucidated that high BMD (P < 0.001, OR = 0.089) and high level of serum 25-OH-D3 (P = 0.012, OR = 0.877) were negatively correlated with the cemented vertebra recompression after PVP. CONCLUSION: Decreased BMD and lower level of serum 25-OH-D3 might be two critical and significant risk factors for the height loss of cemented vertebrae after PVP.

Development and validation of a novel diagnostic model for musculoskeletal aging (sarcopenia) based on cuproptosis-related genes associated with immunity.

OBJECTIVE: Sarcopenia is a geriatric disease characterized by accelerated skeletal muscle mass and function loss due to aging. Cell death plays a pivotal role in the onset and progress of sarcopenia. The purpose of this study was to investigate the role of cuproptosis-related genes (CRGs) and immune infiltration in sarcopenia development. METHODS: Three microarray expression datasets from the Gene Expression Omnibus (GEO) database were merged and batch-corrected by R software to identify differentially expressed genes (DEGs) between old and young skeletal muscles. Subsequently, DEGs were subjected to functional enrichment and gene set enrichment analysis (GSEA) to investigate the roles of DEGs and immune infiltration in the pathogenesis of musculoskeletal aging. Then, ssGSEA was performed to calculate the proportion of immune cells and functions within each muscle sample to analyze the differences between the older and young healthy muscle groups. In order to select candidate CRGs, the correlation between CRGs and immune infiltration was analyzed. Finally, a novel nomogram model of musculoskeletal aging was constructed based on candidate CRGs associated with immunity. Additionally, the diagnostic model based on key CRGs was tested using a validation dataset, and its diagnostic performance was evaluated by the area under curve (AUC) value. RESULTS: 141 DEGs were identified between 45 older samples and 50 young healthy samples. Compared to young healthy muscle tissues, significantly lower infiltration levels of T-regulatory cells were identified in older muscle tissues, while dendritic cells (DCs) and mast cells were relatively higher. Based on the CRGs from seven candidates, a novel model with high prediction efficiency (AUC = 0.856) was established to diagnose and screen for sarcopenia. CONCLUSION: The CRGs associated with immunity may play a vital role in the development of musculoskeletal aging, providing a novel avenue for early diagnosis. Furthermore, immune cell infiltration is essential for the progression of musculoskeletal aging.

Bone Marrow-derived Endothelial Progenitor Cells Are Associated with Bone Mass and Strength.

OBJECTIVE: Blood vessels of bone are thought to influence osteogenesis of bone. No clinical studies have determined whether angiogenesis is related to bone mass and gene expression of growth factors. We compared bone marrow endothelial progenitor cells (EPC), which control angiogenesis of bone in postmenopausal women incurring fragility fracture, with osteoporosis or traumatic fracture with normal bone mass (COM). METHODS: Bone specimens were obtained from age-matched women with osteoporosis or COM. Mononuclear cells were isolated and EPC were detected by flow cytometry. The expression levels of specific genes were measured. Bone mineral density (BMD) was determined, and serum markers of bone turnover also were measured. Differences between OP and COM were assessed with Student t test or Mann-Whitney U test, and correlations were determined using Spearman's correlation. RESULTS: Compared with COM, patients with OP had significantly lower levels of serum osteocalcin, procollagen type-1 N-terminal propeptide, and 25-hydroxy vitamin D, as well as decreased BMD of total hip and femoral neck and fewer bone marrow EPC. Expression levels of vascular endothelial growth factor, angiopoietin-1 (Ang-1), angiopoietin 2 (Ang-2), and the osteoblast-specific genes runt-related transcription factor 2 (RUNX2) and osterix in bone were significantly lower in OP than in COM. We determined that mature EPC were correlated positively with BMD of the femoral neck and total hip, gene expression of Ang-1, RUNX2, and CD31, and negatively with gene expression of receptor activator of nuclear factor-κB ligand and Ang-2. CONCLUSION: Our results demonstrate correlations of bone marrow EPC with bone mass and gene expression of growth factors, which support a hypothesis of crosstalk between angiogenesis and osteogenesis in bone health.

Host selection and niche differentiation in sucking lice (Insecta: Anoplura) among small mammals in southwestern China.

Understanding factors that shape host selection has been a classic issue in ecology, evolutionary biology, and epidemiological investigation. During the survey from 2000 to 2009, a total of 11,216 individuals of small mammals were captured from Yunnan Province in southwestern China. The captured small mammalian hosts belong to five orders, ten families, 35 genera, and 65 species and from their body surface, 38,885 individuals of ectoparasitic sucking lice were collected, which represent five families, seven genera, and 31 species. Based on niche overlap of dominant sucking lice on their primary hosts, we used hierarchical cluster analysis to sort different sucking louse species' resource utilizations of similar kind into respective categories. Given λ<5, there are only two groups clustered, however, sucking louse species' resource utilization was sorted into eight respective categories at λ=15. The results revealed that most species of sucking lice usually had high host specificity and a certain species of sucking louse usually restricted to one or few small mammalian species as their dominant hosts. Correspondence analysis was used to visualize associations between parasitic sucking lice and their small mammalian hosts, which suggested three different patterns of host resource utilization: species specialists, genera generalists, and multiple selections. For example, Sathrax durus (Johnson) only parasitized on species of Tupaia belangeri (Wagner), Hoplopleura edentula (Fahredholz) predominatly on genus of Eothenomys, and Polyplax reclinata (Nitzsch) on Family of Soricidae. Our results demonstrate that sucking lice have high host specificity and this might be due to coevolution between sucking lice and their hosts.