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Copyright ©The Author(s) 2025.
World J Diabetes. Oct 15, 2025; 16(10): 111813
Published online Oct 15, 2025. doi: 10.4239/wjd.v16.i10.111813
Table 1 Fracture risk estimates from the key cohort/meta-analyses of type 1 diabetes mellitus and type 2 diabetes mellitus patients
Ref.
Design and population
Sample size
Fracture endpoint
Effect estimate (95%CI)
Diabetes type
Emanuelsson et al[29]United Kingdom Biobank + Copenhagen, Mendelian randomization + observational study507428Fragility fractureT1DM: HR = 1.50 (95%CI: 1.19-1.88); T2DM: HR = 1.22 (95%CI: 1.13-1.32)T1DM; T2DM
Zoulakis et al[1]Swedish elderly female cohort study3008Any fractureHR = 1.26 (95%CI: 1.04-1.54)T2DM
Champakanath et al[6]University of Colorado CACTI cohort1416Osteoporotic fractureHR = 1.08 (95%CI: 1.02-1.04)T1DM
Table 2 Three metabolic pathways of bone matrix advanced glycation end-product formation and their rate-limiting determinants
Pathway
Key steps
Products/intermediates
Rate-limiting determinants
Classical Maillard reactionGlucose reacts with epsilon-amino group of lysine, Schiff base, Amadori rearrangement, early Amadori productsFructosamine, 1-deoxy-1-ketofructoseBlood glucose concentration, temperature, pH
Glyco-oxidative stressROS/RNS oxidize sugars or Amadori products, carboxylated side chainsCML, CEL and other “oxidative AGEs”ROS levels, antioxidant defenses
Carbonyl stress/dicarbonyl pathwayGlucose autoxidation, degradation or lipid peroxidation, MGO, GO, 3-DG, conjugation with lysine/arginineMG-H1, glucosepane, pentosidineGlyoxalase-1 activity, glutathione pool
Table 3 Classification and representative structures of advanced glycation end-products
AGE type
Chemical name
Characteristics
Biological activity
CMLCMLOne of the most common AGEs; formed via glycoxidation or lipid peroxidationRAGE agonist; promotes inflammation and fibrosis
CELCELStructurally similar to CML; derived from pyruvate and other metabolic intermediatesAssociated with insulin resistance
PentosidineCrosslink product of reducing sugars with lysine or arginineSignature structure of AGE crosslinksStrongly associated with bone fragility and arterial stiffness
MG-H1MG-H1Key biomarker of diabetes-related AGEPromotes apoptosis and mitochondrial dysfunction
Table 4 Comparison of advanced glycation end product detection techniques in bone tissue and their application limitations
Method
Minimum sample size
Spatial resolution
Absolute quantification
Major advantages
Limitations
Ref.
HPLC-FLD/LC-MS2 mg defatted bone powderYesHigh sensitivity; can differentiate CML/CEL/MG-H1/PenDestructive; requires acid hydrolysis; labor-intensive[62]
Autofluorescence (Ex 335/Em 385)5 μm tissue sectionMicron levelNo (relative)Rapid, high-throughput; suitable for biopsy screeningInterference from mineral/Lipid autofluorescence; cannot distinguish AGE types[63]
Raman spectroscopyApplicable to both in vivo and tissue sectionsApproximately 1 μmNo (semiquantitative)In situ detection; simultaneously captures mineral-matrix informationSensitive to water; spectrum interpretation requires expertise[64]
Nano-FTIR/AFM-IR10 μm tissue section20-50 nmNo (semiquantitative)Highest spatial resolution; enables single-fiber localizationExpensive equipment; limited scanning area[65]
Table 5 Research progress on anti-glycation compounds
Intervention
Model and type
Dosage and duration
Evaluation indicators
Summary of main findings
Ref.
Aminoguanidine (AGE formation inhibitor)db/db genetic T2DM mice (in vivo)100 mg/kg/day, intraperitoneal injection, 8 weeks (estimated)Femoral BMD, microarchitecture, biomechanical strengthReduced AGE accumulation in bone matrix; increased BMD and trabecular number; significantly improved 3-point bending load[8]
Pyridoxamine (AGE formation inhibitor)STZ-induced T1DM bone defect model (in vivo); MC3T3-E1 osteoblasts (in vitro)1 g/L in drinking water for 4 weeks; 50-500 μM for cellsBone defect CT imaging, histology; ALP activityAccelerated bone defect healing; increased bone density in defect site within 7-14 days; rescued MGO-induced ALP suppression in vitro[91]
Metformin (AGE inhibition/antihyperglycemic)db/db T2DM mice (in vivo)200 mg/kg/day, oral gavage, 12 weeks (estimated)Bone volume fraction (BV/TV), biomechanical strengthIncreased trabecular bone volume and cortical thickness; improved bending strength; inhibited AGE accumulation in bone[8]
ALT-711 (AGE crosslink breaker)Cy/+ chronic kidney disease rats (diabetic osteoporosis-like, in vivo)3 mg/kg/day, intraperitoneal injection, 10 weeksBone AGE content, porosity, mechanical strengthDecreased total bone AGE levels and cortical porosity; no significant improvement in biomechanical strength[104]
FPS-ZM1 (RAGE small-molecule antagonist)High-glucose-treated bone marrow mesenchymal stem cells (in vitro)5 μM for 24 hoursInflammatory markers (e.g., IL-6), osteogenic markersInhibited RAGE and TXNIP/NLRP3 inflammasome; reduced IL-1β and IL-6; upregulated ALP and osteogenic gene expression[107]
Silybin (natural flavonolignan)STZ-induced diabetic rats (in vivo); MC3T3-E1 cells (in vitro)50 mg/kg/day intraperitoneal injection, 6 weeks; 100 μM in cellsBMD, bone strength; osteoblast apoptosis rateAttenuated diabetic bone loss, increased BMD; inhibited AGE-induced apoptosis by downregulating RAGE and mitochondrial pathway[111]
Resveratrol (natural polyphenol)STZ-induced diabetic bone defect model (in vivo)10 mg/kg/day oral gavage, 8 weeksBone regeneration (μCT), serum AGE levelsPromoted mineralized bone formation in defect site; reduced AGE deposition in bone; improved bone matrix quality[112]
Table 6 Relative effects of common antidiabetic medications on fracture risk
Drug class
Effect estimates and 95%CI
Study type
Ref.
SGLT-2 inhibitors vs placeboHR = 0.98 (95%CI: 0.70-1.37)Randomized controlled trialPerkovic et al[153]
SGLT-2 inhibitors vs DPP-4 inhibitorsHR = 0.90 (95%CI: 0.73-1.11)Cohort studyZhuo et al[17]
SGLT-2 inhibitors vs GLP-1 RAsHR = 1.00 (95%CI: 0.80-1.25)Cohort studyZhuo et al[17]
GLP-1 receptor agonists vs placeboOR = 1.27 (95%CI: 0.88-1.83)Systematic review/network meta-analysisChai et al[157]
DPP-4 inhibitors vs placeboRR = 1.44 (95%CI: 1.04-1.98)Network meta-analysisTsai et al[159]
TZDs (e.g., pioglitazone) vs placeboRR = 1.21 (95%CI: 1.01-1.45)Systematic review/meta-analysisAzhari and Dawson[162]