Markers in blood and saliva for prediction of orthodontically induced inflammatory root resorption: a retrospective case controlled-study

血液和唾液中的标志物预测正畸引起的炎症性牙根吸收:一项回顾性病例对照研究

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Abstract

BACKGROUND: Hormonal and enzymatic factors may render certain individuals more susceptible to orthodontically induced inflammatory root resorption (OIIRR). The objectives of this study are (1) to identify biochemical key markers in blood and saliva that may be correlated to the trend of extensive OIIRR and (2) to utilise these markers to predict a susceptible patient-receiving orthodontic treatment. METHODS: Nine patients (mean age 23 + 2.9 years) who had moderate to severe OIIRR that assessed via orthopantomograms and met the inclusion criteria were classified as the root resorption group (RRG). Blood chemistry was evaluated using the collection of fasting blood and unstimulated saliva samples. Multiplex enzyme-linked immunosorbent assay (ELISA) arrays were used to screen blood and saliva samples for human cytokines, chemokines and several key enzymes that may play a role in root resorption following orthodontic force application. Biochemical findings from 16 matching subjects were used as the control (CG) for comparative measurements. RESULTS: Patients with moderate to severe OIIRR showed a significant increase in salivary cytokines including interleukin (IL) 7, IL-10, IL-12p70 and interferon-gamma (IFN-γ) level as well as a significant decrease in IL-4 level. Osteocalcin and procollagen type I N-terminal peptide (P1NP) appeared to be the only blood factors that showed a significant difference, more in the CG than the RRG. CONCLUSIONS: Saliva might be a more valuable way of measuring changes in cytokine expression than blood secondary to orthodontic treatment. Although the increased expression of pro-inflammatory and anti-inflammatory cytokines may be determinants in the development of moderate to severe OIIRR, cytokine expression may be affected by several potential inflammations in another part of the body. Future research could investigate the cause/effect relationship of different cytokines, in a larger group of patients and at different time intervals, using digital subtraction radiography techniques and microfluidic biosensors.

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