| Literature DB >> 29021829 |
A G D Vianna1,2, C P Sanches1, F C Barreto3.
Abstract
Diabetes complications and osteoporotic fractures are two of the most important causes of morbidity and mortality in older patients, and they share many features, including genetic susceptibility, molecular mechanisms, and environmental factors. Type 2 diabetes mellitus (T2DM) compromises bone microarchitecture by inducing abnormal bone cell function and matrix structure with increased osteoblast apoptosis, diminished osteoblast differentiation, and enhanced osteoclast-mediated bone resorption. The linkage between these two chronic diseases creates a possibility that certain antidiabetic therapies may affect bone function. The treatment of T2DM has been improved in the past two decades with the development of new therapeutic drugs. Each class has a pathophysiologic target related to the regulation of the energy metabolism and insulin secretion. However, both glycemic homeostasis and bone homeostasis are under the control of common regulatory factors. This background allows the individual pharmacological targets of antidiabetic therapies to affect bone quality due to their indirect effects on bone cell differentiation and the bone remodeling process. With a greater number of diabetic patients and antidiabetic agents being launched, it is critical to highlight the consequences of this disease and its pharmacological agents on bone health and fracture risk. Currently, there is little scientific knowledge approaching the impact of most anti-diabetic treatments on bone quality and fracture risk. Thus, this review aims to explore the pros and cons of the available pharmacologic treatments for T2DM on bone mineral density and risk fractures in humans.Entities:
Keywords: Antidiabetic therapy; Bone metabolism; Bone mineral density; Fractures; Treatment; Type 2 diabetes
Year: 2017 PMID: 29021829 PMCID: PMC5613523 DOI: 10.1186/s13098-017-0274-5
Source DB: PubMed Journal: Diabetol Metab Syndr ISSN: 1758-5996 Impact factor: 3.320
Fig. 1The potential effects of metformin, DPP4 inhibitors, and TZDs on bone metabolism. Metformin has a positive effect on osteoblast differentiation by activating the osteoblast-specific Runx2 transcription factor via the AMPK/USF-1/SHP regulatory cascade and an adverse effect on osteoclast differentiation by decreasing RANKL and increasing osteoprotegerin levels. PPARγ activation is associated with fewer osteoblasts, an increased number of adipocytes, greater support for osteoclastogenesis. DPP-4 inhibitors act to stabilize active forms of GIP and GLP-2. GIP increases osteoblast activity, and GLP-2 decreases osteoclast action. iDPP4 dipeptidyl peptidase-4 inhibitor, GIP glucose-dependent insulinotropic peptide, GLP-2 glucagon-like peptide-2, TZDs thiazolidinediones, PPARγ peroxisome proliferator-activated receptor-gamma, Runx2 runt-related transcription factor 2. Modified from Gilbert et al. [26]
Fig. 2The proposed relation between nutrition and bone mass. GIP, and possibly GLP-1 and GLP-2, may link nutrient ingestion to the suppression of bone resorption and the stimulation of bone formation. This link is likely because both osteoblasts and osteoclasts express receptors for incretins, which positively regulate bone metabolism IGF-1 insulin-like growth factor-1, GIP glucose-dependent insulinotropic peptide, GLP-2 glucagon-like peptide-2, PTH parathyroid hormone. Modified from Reid et al. [47]
Summary of the effects of antidiabetic drugs on bone metabolism
| Bone markers | Bone mineral density | Risk of fractures | ||
|---|---|---|---|---|
| Resorption | Formation | (BMD) | (RF) | |
| Metformin | ↑ [ | ↓ [ | ↔ [ | ↔ [ |
| Thiazolidinediones | ↑ [ | ↓ [ | ↓ [ | ↑↑ [ |
| Sulfonylureas | ↔ [ | ↓ [ | ↔ [ | Conflicting results [ |
| GLP-1 RA | ↓ [ | ↑ [ | NA | NA |
| iDPP-4 | ↔ [ | NA | ↔[ | ↔ [ |
| iSGLT2 | ↑ [ | ↑ [ | ↓[ | ↑ [ |
| Insulin | NA | NA | ↑ | ↑ [ |
↑ increases, ↓ decreases, ↔ neutral effect, NA data not available or insufficient evidence, BMD bone mineral density, RF risk of fractures
aResults for canagliflozin only
Core details of the references mentioned in the analysis of BMD and RF in Table 1
| References | Study category | Time of therapy before analysis (months) mean or range | HbA1c of the population at the baseline (%) Mean or range | Age (years) mean or range | Gender |
|---|---|---|---|---|---|
| [ | RCT | 48 | 7.4 | 56 | M/F |
| [ | RCT | 12 | 7.4 | 57 | M/F |
| [ | LC | 48 | 8.4 | 73 | M/F |
| [ | LC | NA | NA | 62 | M/F |
| [ | RCT | 12 | 7.3 | 63 | F |
| [ | MA | 3–48 | 6.7–9.9 | 50–75 | M/F |
| [ | RCT | 12 | 6.0 | 57 | M/F |
| [ | MA | 6–24 | 6.7–9.9 | 50–72 | M/F |
| [ | LC | 12 | 8.3 | 59 | M/F |
| [ | RCT | 29 | 8.2 | 62 | M/F |
| [ | RCT | 43 | 8.2 | 63 | M/F |
| [ | RCT | 24 | 6.5–8.5 | 61 | M/F |
| [ | RCT | 11 | 7.2 | 61 | M/F |
| [ | RCT | 24 | 7.7 | 64 | M/F |
| [ | MA | 6–37 | NA | NA | M/F |
| [ | LC | 114 | NA | 61 | F |
| [ | RCT | 18 | 8.6 | 51 | M/F |
| [ | CC | 49 | 8.0 | 70 | M/F |
LC longitudinal cohort, CC case–control study, RCT randomized controlled study, MA meta-analysis of RCT, NA data not available, HbA1c glycated haemoglobin, M, male, F female