Glycemic fluctuation exacerbates inflammation and bone loss and alters microbiota profile around implants in diabetic mice with experimental peri-implantitis

Abstract

Background: The impact of glycemic fluctuation under diabetic condition on peri-implantitis in diabetic patients remains unclear. We hypothesized that glycemic fluctuation has greater adverse effect on experimental peri-implantitis, compared with sustained high blood glucose in diabetes.

Results: Maxillary left first and second molars of diabetic db/db mice were extracted and were replaced with one dental implant in the healed edentulous space. Glycemic control or fluctuation were managed by constant or interrupted oral administration of rosiglitazone to these mice. Meanwhile, experimental peri-implantitis was induced by ligation around implants. After 14 weeks, inflammatory responses, and peri-implant bone loss, together with oral microbiota profile were analyzed. Diabetic mice with glycemic fluctuation showed greater peri-implant bone loss, inflammatory cell infiltration, and osteoclastogenesis, compared with mice with sustained hyperglycemia. Compared to sustained hyperglycemia, glycemic fluctuation led to further increase in IL-1β, TNFα, RANKL, TLR2/4, IRAK1, and TRAF6 mRNA expression in peri-implant gingival tissues. Both rosiglitazone-induced glycemic control and glycemic fluctuation caused microbiota profile change in diabetic mice compared to that in uncontrolled hyperglycemic mice.

Conclusions: This study suggests that glycemic fluctuation may aggravate peri-implantitis inflammation and bone loss, which may be associated with a shift in peri-implant microbial profile towards dysbiotic changes and the activation of TLR2/4-IRAK1-TRAF6 signaling.

Keywords: Bone loss; Glycemic fluctuation; Inflammatory cytokine; Microbiota; Peri-implantitis; TLR signaling.

Fig. 1

Peri-implant bone loss detected using micro-CT. a Micro-CT images of mesial-distal bone surrounding implants in different groups of mice. b The peri-implant bone loss was calculated in 3D morphometric analysis (mean ± SD, n = 6, *p < 0.05; ns, no significance

Fig. 2

Inflammatory infiltrate in peri-implant tissues was examined using H&E staining. A Images of tissues surrounding implants in different groups of mice. B Numbers of infiltrated inflammatory cells in peri-implant tissues were analyzed (mean ± SD, n = 3, *p < 0.05, **p < 0.01; ns, no significance; I, implant space; B, bone; G, gingiva. Scale bars, 50 μm)

Fig. 3

Osteoclast formation in peri-implant tissues was detected using TRAP staining. A Histological images of TRAP staining of peri-implant tissues of different groups of mice. (black arrows, TRAP positive osteoclasts). B Numbers of osteoclasts in peri-implant tissues were analyzed (n = 3) (mean ± SD, n = 3, *p < 0.05, **p < 0.01; ns, no significance; I, implant space; B, bone; G, gingiva. Scale bars, 50 μm)

Fig. 4

The mRNA expression of inflammatory cytokines and bone formation proteins in peri-implant gingival tissues. Gingival tissues around ligatured site were excised and processed for RT-qPCR analyses to determine mRNA level of a TNF-α, b IL-1β, c IL-17, d IL-10, e RANKL, and f OPG (mean ± SD, n = 3, *p < 0.05, **p < 0.01, ns, no significance)

Fig. 5

The mRNA expression of TLR and NAMPT signaling members in peri-implant gingival tissues. Gingival tissues around ligatured site were excised and processed for RT-qPCR analyses to determine mRNA level of a TLR2, b TLR4, c IRAK1, d TRAF6, e NAMPT, and f SIRT1 (mean ± SD, n = 3, *p < 0.05, **p < 0.01, ns, no significance)

Fig. 6

Species of saliva oral bacteria were analyzed using 16S rRNA gene sequence. a Total numbers of observed species of oral bacteria from different groups at all timepoints (mean ± SD, n = 3). b Distribution of observed species of oral bacteria at WK6 (week 6), saliva samples from oral cavity were collected before implant insertion and glycemic alteration. c Distribution of observed species of oral bacteria at WK14 (week 14), saliva samples from oral cavity were collected before sacrifice