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Research article
Evaluation of Salivary Biomarkers for the Diagnosis of Periodontitis
Fan Chen
Peking University People's Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2975-5699
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: To investigate the diagnostic potential of salivary biomarkers and built a prediction panel for diagnosing periodontal disease.
Methods: In a cross-sectional study, a total of 85 participants were enrolled in the study and divided into healthy, gingivitis and periodontitis groups based on their periodontal examine results, a full mouth periodontal examination were received and unstimulated saliva were collected. Salivary IL-1β, MMP-8, ICTP and Pg were assessed and their potential of diagnosing periodontal disease were analyzed, the combinational prediction panels of periodontal disease were evaluated.
Results: The periodontitis group showed significantly higher level of IL-1β, MMP-8, ICTP and Pg compared to healthy group and higher level of IL-1β, ICTP and Pg compared to gingivitis group, the gingivitis group showed higher level of IL-1β, MMP-8 and Pg compared to healthy group. As a single marker, IL-1β showed the best diagnostic value of four markers and exhibited an AUC value of 0.88 with 94% sensitivity and 71% specificity to discriminate periodontitis from healthy subjects, an AUC value of 0.81 with 82% sensitivity and 76% specificity to discriminate gingivitis from healthy subjects and an AUC value of 0.67 with 69% sensitivity and 64% specificity to discriminate periodontitis from gingivitis subjects. The combination of IL-1, ICTP and Pg exhibited the highest value to discriminate periodontitis from healthy (AUC=0.94) and gingivitis (AUC=0.78) subjects, the combination of IL-1 and MMP-8 exhibited the best value to discriminate gingivitis from healthy subjects (AUC=0.85).
Conclusions: Salivary IL-1β, MMP-8, ICTP and Pg showed discriminate efficiency for diagnosing periodontal disease, the combination of IL-1, ICTP and Pg can be used to discriminate periodontitis from healthy and gingivitis subjects and the combination of IL-1 and MMP-8 can be used to discriminate gingivitis from healthy subjects.
Keywords
saliva, biomarker, diagnosis, peridontiits, gingivitis
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CURRENT STATUS: Under Revision
Version 1
Posted 17 Sep, 2020
No community comments so far
Review #2 received
Received 15 Oct, 2020
Editorial decision: Major revision
On 15 Oct, 2020
Review #1 received
Received 14 Oct, 2020
Reviewer #2 agreed
On 24 Sep, 2020
Editor assigned
On 21 Sep, 2020
Reviewers invited
Invitations sent on 21 Sep, 2020
Reviewer #1 agreed
On 21 Sep, 2020
Submission checks complete
On 15 Sep, 2020
Editor invited
On 15 Sep, 2020
First submitted
On 28 Aug, 2020
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This preprint is under consideration at BMC Oral Health. A preprint is a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Learn more about In Review
Research article
Evaluation of Salivary Biomarkers for the Diagnosis of Periodontitis
Fan Chen
Peking University People's Hospital
Corresponding Author
ORCiD: https://orcid.org/0000-0002-2975-5699
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
Peer Review Timeline
CURRENT STATUS: Under Revision
Version 1
Posted 17 Sep, 2020
No community comments so far
Review #2 received
Received 15 Oct, 2020
Editorial decision: Major revision
On 15 Oct, 2020
Review #1 received
Received 14 Oct, 2020
Reviewer #2 agreed
On 24 Sep, 2020
Editor assigned
On 21 Sep, 2020
Reviewers invited
Invitations sent on 21 Sep, 2020
Reviewer #1 agreed
On 21 Sep, 2020
Submission checks complete
On 15 Sep, 2020
Editor invited
On 15 Sep, 2020
First submitted
On 28 Aug, 2020
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background: To investigate the diagnostic potential of salivary biomarkers and built a prediction panel for diagnosing periodontal disease.
Methods: In a cross-sectional study, a total of 85 participants were enrolled in the study and divided into healthy, gingivitis and periodontitis groups based on their periodontal examine results, a full mouth periodontal examination were received and unstimulated saliva were collected. Salivary IL-1β, MMP-8, ICTP and Pg were assessed and their potential of diagnosing periodontal disease were analyzed, the combinational prediction panels of periodontal disease were evaluated.
Results: The periodontitis group showed significantly higher level of IL-1β, MMP-8, ICTP and Pg compared to healthy group and higher level of IL-1β, ICTP and Pg compared to gingivitis group, the gingivitis group showed higher level of IL-1β, MMP-8 and Pg compared to healthy group. As a single marker, IL-1β showed the best diagnostic value of four markers and exhibited an AUC value of 0.88 with 94% sensitivity and 71% specificity to discriminate periodontitis from healthy subjects, an AUC value of 0.81 with 82% sensitivity and 76% specificity to discriminate gingivitis from healthy subjects and an AUC value of 0.67 with 69% sensitivity and 64% specificity to discriminate periodontitis from gingivitis subjects. The combination of IL-1, ICTP and Pg exhibited the highest value to discriminate periodontitis from healthy (AUC=0.94) and gingivitis (AUC=0.78) subjects, the combination of IL-1 and MMP-8 exhibited the best value to discriminate gingivitis from healthy subjects (AUC=0.85).
Conclusions: Salivary IL-1β, MMP-8, ICTP and Pg showed discriminate efficiency for diagnosing periodontal disease, the combination of IL-1, ICTP and Pg can be used to discriminate periodontitis from healthy and gingivitis subjects and the combination of IL-1 and MMP-8 can be used to discriminate gingivitis from healthy subjects.