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Ali A, Flatt PR, Irwin N. Gut-Derived Peptide Hormone Analogues and Potential Treatment of Bone Disorders in Obesity and Diabetes Mellitus. Clin Med Insights Endocrinol Diabetes 2024; 17:11795514241238059. [PMID: 38486712 PMCID: PMC10938612 DOI: 10.1177/11795514241238059] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Accepted: 02/14/2024] [Indexed: 03/17/2024] Open
Abstract
Obesity and diabetes mellitus are prevalent metabolic disorders that have a detrimental impact on overall health. In this regard, there is now a clear link between these metabolic disorders and compromised bone health. Interestingly, both obesity and diabetes lead to elevated risk of bone fracture which is independent of effects on bone mineral density (BMD). In this regard, gastrointestinal (GIT)-derived peptide hormones and their related long-acting analogues, some of which are already clinically approved for diabetes and/or obesity, also seem to possess positive effects on bone remodelling and microarchitecture to reduce bone fracture risk. Specifically, the incretin peptides, glucagon-like peptide-1 (GLP-1) and glucose-dependent insulinotropic polypeptide (GIP), as well as glucagon-like peptide-2 (GLP-2), exert key direct and/or indirect benefits on bone metabolism. This review aims to provide an initial appraisal of the relationship between obesity, diabetes and bone, with a focus on the positive impact of these GIT-derived peptide hormones for bone health in obesity/diabetes. Brief discussion of related peptides such as parathyroid hormone, leptin, calcitonin and growth hormone is also included. Taken together, drugs engineered to promote GIP, GLP-1 and GLP-2 receptor signalling may have potential to offer therapeutic promise for improving bone health in obesity and diabetes.
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Affiliation(s)
- Asif Ali
- Diabetes Research Centre, Biomedical Sciences Research Institute, Ulster University, Coleraine, Northern Ireland, UK
| | - Peter R Flatt
- Diabetes Research Centre, Biomedical Sciences Research Institute, Ulster University, Coleraine, Northern Ireland, UK
| | - Nigel Irwin
- Diabetes Research Centre, Biomedical Sciences Research Institute, Ulster University, Coleraine, Northern Ireland, UK
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Li Z, Zhao W, Lin X, Li F. AI algorithms for accurate prediction of osteoporotic fractures in patients with diabetes: an up-to-date review. J Orthop Surg Res 2023; 18:956. [PMID: 38087332 PMCID: PMC10714483 DOI: 10.1186/s13018-023-04446-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 12/05/2023] [Indexed: 12/18/2023] Open
Abstract
Osteoporotic fractures impose a substantial burden on patients with diabetes due to their unique characteristics in bone metabolism, limiting the efficacy of conventional fracture prediction tools. Artificial intelligence (AI) algorithms have shown great promise in predicting osteoporotic fractures. This review aims to evaluate the application of traditional fracture prediction tools (FRAX, QFracture, and Garvan FRC) in patients with diabetes and osteoporosis, review AI-based fracture prediction achievements, and assess the potential efficiency of AI algorithms in this population. This comprehensive literature search was conducted in Pubmed and Web of Science. We found that conventional prediction tools exhibit limited accuracy in predicting fractures in patients with diabetes and osteoporosis due to their distinct bone metabolism characteristics. Conversely, AI algorithms show remarkable potential in enhancing predictive precision and improving patient outcomes. However, the utilization of AI algorithms for predicting osteoporotic fractures in diabetic patients is still in its nascent phase, further research is required to validate their efficacy and assess the potential advantages of their application in clinical practice.
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Affiliation(s)
- Zeting Li
- Department of Endocrinology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China
| | - Wen Zhao
- The Reproductive Center, The First Affiliated Hospital, Sun Yat-sen University, Guangzhou, China
| | - Xiahong Lin
- Department of Endocrinology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
| | - Fangping Li
- Department of Endocrinology, The Seventh Affiliated Hospital, Sun Yat-sen University, Shenzhen, China.
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Whittier DE, Bevers MSAM, Geusens PPMM, van den Bergh JP, Gabel L. Characterizing Bone Phenotypes Related to Skeletal Fragility Using Advanced Medical Imaging. Curr Osteoporos Rep 2023; 21:685-697. [PMID: 37884821 PMCID: PMC10724303 DOI: 10.1007/s11914-023-00830-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/11/2023] [Indexed: 10/28/2023]
Abstract
PURPOSE OF REVIEW Summarize the recent literature that investigates how advanced medical imaging has contributed to our understanding of skeletal phenotypes and fracture risk across the lifespan. RECENT FINDINGS Characterization of bone phenotypes on the macro-scale using advanced imaging has shown that while wide bones are generally stronger than narrow bones, they may be more susceptible to age-related declines in bone strength. On the micro-scale, HR-pQCT has been used to identify bone microarchitecture phenotypes that improve stratification of fracture risk based on phenotype-specific risk factors. Adolescence is a key phase for bone development, with distinct sex-specific growth patterns and significant within-sex bone property variability. However, longitudinal studies are needed to evaluate how early skeletal growth impacts adult bone phenotypes and fracture risk. Metabolic and rare bone diseases amplify fracture risk, but the interplay between bone phenotypes and disease remains unclear. Although bone phenotyping is a promising approach to improve fracture risk assessment, the clinical availability of advanced imaging is still limited. Consequently, alternative strategies for assessing and managing fracture risk include vertebral fracture assessment from clinically available medical imaging modalities/techniques or from fracture risk assessment tools based on clinical risk factors. Bone fragility is not solely determined by its density but by a combination of bone geometry, distribution of bone mass, microarchitecture, and the intrinsic material properties of bone tissue. As such, different individuals can exhibit distinct bone phenotypes, which may predispose them to be more vulnerable or resilient to certain perturbations that influence bone strength.
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Affiliation(s)
- Danielle E Whittier
- McCaig Institute for Bone and Joint Health and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada.
- Department of Cell Biology and Anatomy, University of Calgary, Calgary, Canada.
| | - Melissa S A M Bevers
- Department of Internal Medicine, VieCuri Medical Center, Venlo, The Netherlands
- NUTRIM School for Nutrition and Translational Research In Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands
| | - Piet P M M Geusens
- Subdivision of Rheumatology, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
- Department of Medicine and Life Sciences, Hasselt University, Hasselt, Belgium
| | - Joop P van den Bergh
- Department of Internal Medicine, VieCuri Medical Center, Venlo, The Netherlands
- NUTRIM School for Nutrition and Translational Research In Metabolism, Maastricht University Medical Center, Maastricht, The Netherlands
- Subdivision of Rheumatology, Department of Internal Medicine, Maastricht University Medical Center, Maastricht, The Netherlands
| | - Leigh Gabel
- McCaig Institute for Bone and Joint Health and Alberta Children's Hospital Research Institute, University of Calgary, Calgary, Canada
- Human Performance Laboratory, Faculty of Kinesiology, University of Calgary, Calgary, Canada
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Anwar A, Kanwal Q, Sadiqa A, Razaq T, Khan IH, Javaid A, Khan S, Tag-Eldin E, Ouladsmane M. Synthesis and Antimicrobial Analysis of High Surface Area Strontium-Substituted Calcium Phosphate Nanostructures for Bone Regeneration. Int J Mol Sci 2023; 24:14527. [PMID: 37833975 PMCID: PMC10572144 DOI: 10.3390/ijms241914527] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2023] [Revised: 09/08/2023] [Accepted: 09/09/2023] [Indexed: 10/15/2023] Open
Abstract
Continuous microwave-assisted flow synthesis has been used as a simple, more efficient, and low-cost route to fabricate a range of nanosized (<100 nm) strontium-substituted calcium phosphates. In this study, fine nanopowder was synthesized via a continuous flow synthesis with microwave assistance from the solutions of calcium nitrate tetrahydrate (with strontium nitrate as Sr2+ ion source) and diammonium hydrogen phosphate at pH 10 with a time duration of 5 min. The morphological characterization of the obtained powder has been carried out by employing techniques such as transmission electron microscopy, X-ray diffraction, and Brunauer-Emmett-Teller surface area analysis. The chemical structural analysis to evaluate the surface properties was made by using X-ray photoelectron spectroscopy. Zeta potential analysis was performed to evaluate the colloidal stability of the particles. Antimicrobial studies were performed for all the compositions using four bacterial strains and an opportunistic human fungal pathogen Macrophomina phaseolina. It was found that the nanoproduct with high strontium content (15 wt% of strontium) showed pronounced antibacterial potential against M. luteus while it completely arrested the fungal growth after 48 h by all of its concentrations. Thus the synthesis strategy described herein facilitated the rapid production of nanosized Sr-substituted CaPs with excellent biological performance suitable for a bone replacement application.
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Affiliation(s)
- Aneela Anwar
- Department of Chemistry, University of Engineering and Technology, Lahore 54890, Pakistan
- Biomedical Engineering Department, Stevens Institute of Technology, Hoboken, NJ 07030, USA
| | - Qudsia Kanwal
- Department of Chemistry, The University of Lahore, Lahore 54590, Pakistan; (Q.K.); (A.S.)
| | - Ayesha Sadiqa
- Department of Chemistry, The University of Lahore, Lahore 54590, Pakistan; (Q.K.); (A.S.)
| | - Tabassam Razaq
- Institute of Microbiology and Molecular Genetics, University of the Punjab, Lahore 54590, Pakistan;
| | - Iqra Haider Khan
- Department of Plant Pathology, Faculty of Agricultural Sciences, University of the Punjab, Quaid-i-Azam Campus, Lahore 54590, Pakistan; (I.H.K.); (A.J.)
| | - Arshad Javaid
- Department of Plant Pathology, Faculty of Agricultural Sciences, University of the Punjab, Quaid-i-Azam Campus, Lahore 54590, Pakistan; (I.H.K.); (A.J.)
| | - Safia Khan
- Faculty of Engineering and Technology, Future University in Egypt, New Cairo 11835, Egypt;
| | - ElSayed Tag-Eldin
- Shandong Technology Centre of Nanodevices and Integration, School of Microelectronics, Shandong University, Jinan 250101, China
| | - Mohamed Ouladsmane
- Department of Chemistry, College of Science, King Saud University, Riyadh 11451, Saudi Arabia
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Ji S, Jiang X, Han H, Wang C, Wang C, Yang D. Prediabetes and osteoporotic fracture risk: A meta-analysis of prospective cohort studies. Diabetes Metab Res Rev 2022; 38:e3568. [PMID: 35947530 DOI: 10.1002/dmrr.3568] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/06/2021] [Revised: 02/27/2022] [Accepted: 07/08/2022] [Indexed: 11/06/2022]
Abstract
BACKGROUND Diabetes confers an increased risk of fracture. However, whether prediabetes is also a risk factor of osteoporotic fracture has not been comprehensively examined. We performed a meta-analysis to evaluate the relationship between prediabetes and osteoporotic fracture risk. METHODS This meta-analysis included relevant prospective cohort studies from Medline, Embase, and Web of Science databases. A random-effect model after incorporation of the intra-study heterogeneity was selected to pool the results. Subgroup analyses were applied to evaluate the influences of study characteristics on relationship between prediabetes and osteoporotic fracture risk. RESULTS Eight studies including 33,136 community dwelling adult patients were included, and 7429 (22.4%) patients were prediabetic. Prediabetes was not independently associated with a higher risk of osteoporotic fracture compared with normoglycemia (adjusted risk ratio: 1.03, 95% confidence interval: 0.88-1.21, P = 0.69, I2 = 42%). Sensitivity limited to the elderly population showed consistent results (RR: 1.10, 95% CI: 0.91-1.24, P = 0.15, I2 = 0%). Subgroup analysis suggested that prediabetes defined by HbA1c (approximately 5.7%-6.4%) was associated with a higher risk of osteoporotic fracture (RR: 1.24, 95% CI: 1.01-1.53, P = 0.04), but not that defined by impaired fasting glucose or impaired glucose tolerance (P = 0.60). Sex, follow-up duration, and adjustment of bone mineral density did not significantly affect the outcome. CONCLUSIONS Current evidence does not support that prediabetes is independently associated with osteoporotic fracture risk. Different definitions of prediabetes may affect the association between prediabetes and osteoporotic fracture risk.
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Affiliation(s)
- Songjie Ji
- Department of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China
| | - Xu Jiang
- Department of Orthopaedic Surgery, Beijing Jishuitan Hospital, Beijing, China
| | - Huijun Han
- Department of Epidemiology and Biostatistics, Institute of Basic Medical Sciences, Chinese Academy of Medical Sciences & School of Basic Medicine, Peking Union Medical College, Beijing, China
| | - Cong Wang
- Department of Emergency, Beijing Jishuitan Hospital, Beijing, China
| | - Chao Wang
- Institute of Traumatology and Orthopaedics, Beijing, China
| | - Dan Yang
- Department of Traditional Chinese Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Translational Medicine Center, Chinese Academy of Medical Sciences, Beijing, China
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Kong XK, Zhao ZY, Zhang D, Xie R, Sun LH, Zhao HY, Ning G, Wang WQ, Liu JM, Tao B. Major osteoporosis fracture prediction in type 2 diabetes: a derivation and comparison study. Osteoporos Int 2022; 33:1957-1967. [PMID: 35583602 DOI: 10.1007/s00198-022-06425-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Accepted: 05/04/2022] [Indexed: 10/18/2022]
Abstract
UNLABELLED The widely recommended fracture prediction tool FRAX was developed based on and for the general population. Although several adjusted FRAX methods were suggested for type 2 diabetes (T2DM), they still need to be evaluated in T2DM cohort. INTRODUCTION This study was undertaken to develop a prediction model for Chinese diabetes fracture risk (CDFR) and compare its performance with those of FRAX. METHODS In this retrospective cohort study, 1730 patients with T2DM were enrolled from 2009.08 to 2013.07. Major osteoporotic fractures (MOFs) during follow-up were collected from Electronic Health Records (EHRs) and telephone interviews. Multivariate Cox regression with backward stepwise selection was used to fit the model. The performances of the CDFR model, FRAX, and adjusted FRAX were compared in the aspects of discrimination and calibration. RESULTS 6.3% of participants experienced MOF during a median follow-up of 10 years. The final model (CDFR) included 8 predictors: age, gender, previous fracture, insulin use, diabetic peripheral neuropathy (DPN), total cholesterol, triglycerides, and apolipoprotein A. This model had a C statistic of 0.803 (95%CI 0.761-0.844) and calibration χ2 of 4.63 (p = 0.86). The unadjusted FRAX underestimated the MOF risk (calibration χ2 134.5, p < 0.001; observed/predicted ratio 2.62, 95%CI 2.17-3.08), and there was still significant underestimation after diabetes adjustments. Comparing FRAX, the CDFR had a higher AUC, lower calibration χ2, and better reclassification of MOF. CONCLUSION The CDFR model has good performance in 10-year MOF risk prediction in T2DM, especially in patients with insulin use or DPN. Future work is needed to validate our model in external cohort(s).
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Affiliation(s)
- Xiao-Ke Kong
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Zhi-Yun Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Deng Zhang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Rui Xie
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Li-Hao Sun
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Hong-Yan Zhao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Guang Ning
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China
| | - Wei-Qing Wang
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Jian-Min Liu
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
| | - Bei Tao
- Department of Endocrine and Metabolic Diseases, Shanghai Institute of Endocrine and Metabolic Diseases, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
- Shanghai National Clinical Research Center for Metabolic Diseases, Key Laboratory for Endocrine and Metabolic Diseases of the National Health Commission of the PR China, Shanghai Key Laboratory for Endocrine Tumor, State Key Laboratory of Medical Genomics, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
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Fazullina ON, Korbut AI, Klimontov VV. Factors associated with trabecular bone score in postmenopausal women with type 2 diabetes and normal bone mineral density. World J Diabetes 2022; 13:553-565. [PMID: 36051426 PMCID: PMC9329840 DOI: 10.4239/wjd.v13.i7.553] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/02/2022] [Accepted: 06/24/2022] [Indexed: 02/06/2023] Open
Abstract
BACKGROUND Osteoporosis and type 2 diabetes (T2D) have been recognized as a widespread comorbidity leading to excess mortality and an enormous healthcare burden. In T2D, bone mineral density (BMD) may underestimate the risk of low-energy fractures as bone quality is reduced. It was hypothesized that a decrease in the trabecular bone score (TBS), a parameter assessing bone microarchitecture, may be an early marker of impaired bone health in women with T2D.
AIM To identify clinical and body composition parameters that affect TBS in postmenopausal women with T2D and normal BMD.
METHODS A non-interventional cross-sectional comparative study was conducted. Potentially eligible subjects were screened at tertiary referral center. Postmenopausal women with T2D, aged 50-75 years, with no established risk factors for secondary osteoporosis, were included. BMD, TBS and body composition parameters were assessed by dual-energy X-ray absorptiometry. In women with normal BMD, a wide range of anthropometric, general and diabetes-related clinical and laboratory parameters were evaluated as risk factors for TBS decrease using univariate and multivariate regression analysis and analysis of receiver operating characteristic (ROC) curves.
RESULTS Three hundred twelve women were initially screened, 176 of them met the inclusion criteria and underwent dual X-ray absorptiometry. Those with reduced BMD were subsequently excluded; 96 women with normal BMD were included in final analysis. Among them, 43 women (44.8%) showed decreased TBS values (≤ 1.31). Women with TBS ≤ 1.31 were taller and had a lower body mass index (BMI) when compared to those with normal TBS (Р = 0.008 and P = 0.007 respectively). No significant differences in HbA1c, renal function, calcium, phosphorus, alkaline phosphatase, PTH and 25(ОН)D levels were found. In a model of multivariate linear regression analysis, TBS was positively associated with gynoid fat mass, whereas the height and androgen fat mass were associated negatively (all P < 0.001). In a multiple logistic regression, TBS ≤ 1.31 was associated with lower gynoid fat mass (adjusted odd ratio [OR], 0.9, 95% confidence interval [CI], 0.85-0.94, P < 0.001), higher android fat mass (adjusted OR, 1.13, 95%CI, 1.03-1.24, P = 0.008) and height (adjusted OR, 1.13, 95%CI, 1.05-1.20, P < 0.001). In ROC-curve analysis, height ≥ 162.5 cm (P = 0.04), body mass index ≤ 33.85 kg/m2 (P = 0.002), gynoid fat mass ≤ 5.41 kg (P = 0.03) and android/gynoid fat mass ratio ≥ 1.145 (P < 0.001) were identified as the risk factors for TBS reduction.
CONCLUSION In postmenopausal women with T2D and normal BMD, greater height and central adiposity are associated with impaired bone microarchitecture.
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Affiliation(s)
- Olga N Fazullina
- Laboratory of Endocrinology, Research Institute of Clinical and Experimental Lymphology - Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630060, Russia
| | - Anton I Korbut
- Laboratory of Endocrinology, Research Institute of Clinical and Experimental Lymphology - Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630060, Russia
| | - Vadim V Klimontov
- Laboratory of Endocrinology, Research Institute of Clinical and Experimental Lymphology - Branch of the Institute of Cytology and Genetics, Siberian Branch of Russian Academy of Sciences, Novosibirsk 630060, Russia
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Jeddi S, Yousefzadeh N, Kashfi K, Ghasemi A. Role of nitric oxide in type 1 diabetes-induced osteoporosis. Biochem Pharmacol 2021; 197:114888. [PMID: 34968494 DOI: 10.1016/j.bcp.2021.114888] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 12/09/2021] [Accepted: 12/09/2021] [Indexed: 12/18/2022]
Abstract
Type 1 diabetes (T1D)-induced osteoporosis is characterized by decreased bone mineral density, bone quality, rate of bone healing, bone formation, and increased bone resorption. Patients with T1D have a 2-7-fold higher risk of osteoporotic fracture. The mechanisms leading to increased risk of osteoporotic fracture in T1D include insulin deficiency, hyperglycemia, insulin resistance, lower insulin-like growth factor-1, hyperglycemia-induced oxidative stress, and inflammation. In addition, a higher probability of falling, kidney dysfunction, weakened vision, and neuropathy indirectly increase the risk of osteoporotic fracture in T1D patients. Decreased nitric oxide (NO) bioavailability contributes to the pathophysiology of T1D-induced osteoporotic fracture. This review discusses the role of NO in osteoblast-mediated bone formation and osteoclast-mediated bone resorption in T1D. In addition, the mechanisms involved in reduced NO bioavailability and activity in type 1 diabetic bones as well as NO-based therapy for T1D-induced osteoporosis are summarized. Available data indicates that lower NO bioavailability in diabetic bones is due to disruption of phosphatidylinositol 3‑kinase/protein kinase B/endothelial NO synthases and NO/cyclic guanosine monophosphate/protein kinase G signaling pathways. Thus, NO bioavailability may be boosted directly or indirectly by NO donors. As NO donors with NO-like effects in the bone, inorganic nitrate and nitrite can potentially be used as novel therapeutic agents for T1D-induced osteoporosis. Inorganic nitrites and nitrates can decrease the risk for osteoporotic fracture probably directly by decreasing osteoclast activity, decreasing fat accumulation in the marrow cavity, increasing osteoblast activity, and increasing bone perfusion or indirectly, by improving hyperglycemia, insulin resistance, and reducing body weight.
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Affiliation(s)
- Sajad Jeddi
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Nasibeh Yousefzadeh
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Khosrow Kashfi
- Department of Molecular, Cellular, and Biomedical Sciences, Sophie Davis School of Biomedical Education, City University of New York School of Medicine, NY, USA.
| | - Asghar Ghasemi
- Endocrine Physiology Research Center, Research Institute for Endocrine Sciences, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
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Qi SS, Shao ML, Sun Z, Chen SM, Hu YJ, Li XS, Chen DJ, Zheng HX, Yue TL. Chondroitin Sulfate Alleviates Diabetic Osteoporosis and Repairs Bone Microstructure via Anti-Oxidation, Anti-Inflammation, and Regulating Bone Metabolism. Front Endocrinol (Lausanne) 2021; 12:759843. [PMID: 34777254 PMCID: PMC8579055 DOI: 10.3389/fendo.2021.759843] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 09/29/2021] [Indexed: 12/24/2022] Open
Abstract
Diabetic osteoporosis (DOP) belongs to secondary osteoporosis caused by diabetes; it has the characteristics of high morbidity and high disability. In the present study, we constructed a type 1 diabetic rat model and administered chondroitin sulfate (200 mg/kg) for 10 weeks to observe the preventive effect of chondroitin sulfate on the bone loss of diabetic rats. The results showed that chondroitin sulfate can reduce blood glucose and relieve symptoms of diabetic rats; in addition, it can significantly increase the bone mineral density, improve bone microstructure, and reduce bone marrow adipocyte number in diabetic rats; after 10 weeks of chondroitin sulfate administration, the SOD activity level was upregulated, as well as CAT levels, indicating that chondroitin sulfate can alleviate oxidative stress in diabetic rats. Chondroitin sulfate was also found to reduce the level of serum inflammatory cytokines (TNF-α, IL-1, IL-6, and MCP-1) and alleviate the inflammation in diabetic rats; bone metabolism marker detection results showed that chondroitin sulfate can reduce bone turnover in diabetic rats (decreased RANKL, CTX-1, ALP, and TRACP 5b levels were observed after 10 weeks of chondroitin sulfate administration). At the same time, the bone OPG and RUNX 2 expression levels were higher after chondroitin sulfate treatment, the bone RANKL expression was lowered, and the OPG/RANKL ratio was upregulated. All of the above indicated that chondroitin sulfate could prevent STZ-induced DOP and repair bone microstructure; the main mechanism was through anti-oxidation, anti-inflammatory, and regulating bone metabolism. Chondroitin sulfate could be used to develop anti-DOP functional foods and diet interventions for diabetes.
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Affiliation(s)
- Shan Shan Qi
- College of Food Science and Engineering, Northwest Agriculture and Forestry (A&F) University, Yangling, China
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, Hanzhong, China
| | - Meng Li Shao
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, Hanzhong, China
| | - Ze Sun
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
- QinLing-Bashan Mountains Bioresources Comprehensive Development C.I.C., Hanzhong, China
| | - Si Min Chen
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
| | - Ying Jun Hu
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
| | - Xin Sheng Li
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
- Shaanxi Key Laboratory of Resource Biology, Hanzhong, China
| | - De Jing Chen
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, Hanzhong, China
- *Correspondence: Tian Li Yue, ; Hong Xing Zheng, ; De Jing Chen,
| | - Hong Xing Zheng
- College of Biological Science and Engineering, Shaanxi University of Technology, Hanzhong, China
- Qinba State Key Laboratory of Biological Resources and Ecological Environment, Hanzhong, China
- Shaanxi Key Laboratory of Resource Biology, Hanzhong, China
- *Correspondence: Tian Li Yue, ; Hong Xing Zheng, ; De Jing Chen,
| | - Tian Li Yue
- College of Food Science and Engineering, Northwest Agriculture and Forestry (A&F) University, Yangling, China
- College of Food Science and Technology, Northwest University, Xi’an, China
- *Correspondence: Tian Li Yue, ; Hong Xing Zheng, ; De Jing Chen,
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