The metabolic score of insulin resistance is positively correlated with bone mineral density in postmenopausal patients with type 2 diabetes mellitus

Genetic predisposition to bone mineral density and their health conditions in East Asians

Osteoporosis, a condition defined by low BMD (typically < -2.5 SD), causes a higher fracture risk and leads to significant economic, social, and clinical impacts. Genome-wide studies mainly in Caucasians have found many genetic links to osteoporosis, fractures, and BMD, with limited research in East Asians (EAS). We investigated the genetic aspects of BMD in 86 716 individuals from the Taiwan Biobank and their causal links to health conditions within EAS. A genome-wide association study (GWAS) was conducted, followed by observational studies, polygenic risk score assessments, and genetic correlation analyses to identify associated health conditions linked to BMD. GWAS and gene-based GWAS studies identified 78 significant SNPs and 75 genes related to BMD, highlighting pathways like Hedgehog, WNT-mediated, and TGF-β. Our cross-trait linkage disequilibrium score regression analyses for BMD and osteoporosis consistently validated their genetic correlations with BMI and type 2 diabetes (T2D) in EAS. Higher BMD was linked to lower osteoporosis risk but increased BMI and T2D, whereas osteoporosis linked to lower BMI, waist circumference, hemoglobinA1c, and reduced T2D risk. Bidirectional Mendelian randomization analyses revealed that a higher BMI causally increases BMD in EAS. However, no direct causal relationships were found between BMD and T2D, or between osteoporosis and either BMI or T2D. This study identified key genetic factors for bone health in Taiwan, and revealed significant health conditions in EAS, particularly highlighting the genetic interplay between bone health and metabolic traits like T2D and BMI.

Osteocyte-mediated mechanical response controls osteoblast differentiation and function

Low bone mass is a pervasive global health concern, with implications for osteoporosis, frailty, disability, and mortality. Lifestyle factors, including sedentary habits, metabolic dysfunction, and an aging population, contribute to the escalating prevalence of osteopenia and osteoporosis. The application of mechanical load to bone through physical activity and exercise prevents bone loss, while sufficient mechanical load stimulates new bone mass acquisition. Osteocytes, cells embedded within the bone, receive mechanical signals and translate these mechanical cues into biological signals, termed mechano-transduction. Mechano-transduction signals regulate other bone resident cells, such as osteoblasts and osteoclasts, to orchestrate changes in bone mass. This review explores the mechanisms through which osteocyte-mediated response to mechanical loading regulates osteoblast differentiation and bone formation. An overview of bone cell biology and the impact of mechanical load will be provided, with emphasis on the mechanical cues, mechano-transduction pathways, and factors that direct progenitor cells toward the osteoblast lineage. While there are a wide range of clinically available treatments for osteoporosis, the majority act through manipulation of the osteoclast and may have significant disadvantages. Despite the central role of osteoblasts to the deposition of new bone, few therapies directly target osteoblasts for the preservation of bone mass. Improved understanding of the mechanisms leading to osteoblastogenesis may reveal novel targets for translational investigation.

Association between triglyceride glucose index and total bone mineral density: a cross-sectional study from NHANES 2011-2018

The Homeostatic Model Assessment for Triglyceride Glucose Index (TyG) and its related indices, including triglyceride glucose-waist circumference (TyG-WC), triglyceride glucose-waist-to-height ratio (TyG-WHtR) and triglyceride glucose-body mass index (TyG-BMI), has emerged as a practical tool for assessing insulin resistance in metabolic disorders. However, limited studies have explored the connection between TyG, TyG-related indices and osteoporosis. This population-based study, utilizing data from the National Health and Nutrition Examination Survey 2011-2018, involved 5456 participants. Through weighted multivariate linear regression and smoothed curve fitting, a significant positive correlation was found between TyG, TyG-related indices and total bone mineral density (BMD) after adjusting for covariates [β = 0.0124, 95% CI (0.0006, 0.0242), P = 0.0390; β = 0.0004, 95% CI (0.0003, 0.0004), P < 0.0001; β = 0.0116, 95% CI (0.0076, 0.0156), P < 0.0001; β = 0.0001, 95% CI (0.0001, 0.0001), P < 0.0001]. In subgroup analysis, race stratification significantly affected the relationship between TyG and total BMD. Additionally, gender and race were both significant for TyG-related indices. Non-linear relationships and threshold effects with inflection points at 9.106, 193.9265, 4.065, and 667.5304 (TyG, TyG-BMI, TyG-WHtR, TyG-WC) were identified. Saturation phenomena were observed between TyG-BMI, TyG-WC and total BMD with saturation thresholds at 314.177 and 1022.0428. These findings contributed to understanding the association between TyG, TyG-related indices and total BMD, offering insights for osteoporosis prevention and treatment.

Causal relationship between body mass index, type 2 diabetes and bone mineral density: Mendelian randomization

OBJECTIVE

To reveal the relationship between Body Mass Index(BMI), type 2 diabetes, and bone mineral density(BMD) using a mendelian randomization (MR) approach.

METHODS

GWAS data on BMI, type 2 diabetes, and BMD were selected from the IEU GWAS database at the University of Bristol.Univariable, multivariable, and mediated MR analyses were used to explore the relationship between BMI, type 2 diabetes, and BMD. beta(β) values were given, and three methods, including inverse variance weighting, MR-Egger regression, and weighted median, were used in this analysis.

RESULTS

Univariable mendelian randomization (UVMR) results showed that BMI and type 2 diabetes were positively associated with BMD. However, the association between BMI and BMD was insignificant in the multivariable Mendelian randomization (MVMR) analysis, while that between type 2 diabetes and BMD remained significant. Mediated MR analysis indicated that type 2 diabetes mediated the regulation of BMD by BMI.

CONCLUSION

This study provides evidence supporting a positive causal association between BMI, type 2 diabetes, and BMD. Type 2 diabetes acts as a mediator in the regulation of BMD by BMI, indicating that both BMI and type 2 diabetes exert a protective influence on BMD.