RESUMO
BACKGROUND: Orthodontically induced iatrogenic root resorption (OIIRR) is an unavoidable inflammatory process. Several factors claimed to be related to the severity of OIIRR. Orthodontic forces cause micro-trauma to the periodontal ligament and activate a cascade of cellular events associated with local periodontal inflammation. The purpose of this split-mouth study were (1) to investigate the changes in cytokine profile in the gingival crevicular fluid (GCF) secondary to heavy orthodontic forces and (2) to compare the cytokine expression between participants showing high and low root resorption. METHODS: Eight participants requiring maxillary first premolar extractions involved in this study. The teeth on the tested side (TS) received 225 g of controlled buccal tipping force for 28 days, while the contralateral teeth act as a control (CS). GCF was collected from both TS and CS teeth at 0 h (prior to application of force) and 3 h, 1 day, 3 days, 7 days and 28 days after the application of force, and analysed with multiplex bead immunoassay to determine the cytokine levels. RESULTS: Statistically significant temporal increase was found in the TS teeth for tumour necrosis factor alpha (TNF-α) at 3 h and 28 days (p = 0.01). Interleukin 7 (IL-7) significantly peaked at the 28th day. Comparing cytokine profile for participants with high and low root resorption (>0.35 and <0.15 mm3, respectively), the levels of GM-CSF was significantly greater in low root resorption cases (p < 0.05). The amounts of root resorption which craters on mesial, distal surfaces and middle third region were significant in the TS teeth (p < 0.05). CONCLUSIONS: IL-7 and TNF-α (pro-resorptive cytokine) increased significantly secondary to a high-level of orthodontic force application. Significantly high levels of granulocyte macrophage colony-stimulating factor (anti-resorptive cytokine) were detected in mild root resorption cases secondary to high-level orthodontic force application. A future long-term randomised clinical trial with larger sample taking in consideration gender, age and growth pattern distribution would be recommended.