Dataset Information

Identification of biomarkers for periodontal disease using the immunoproteomics approach.

ABSTRACT:

Background

Periodontitis is one of the most common oral diseases associated with the host's immune response against periodontopathogenic infection. Failure to accurately diagnose the stage of periodontitis has limited the ability to predict disease status. Therefore, we aimed to look for reliable diagnostic markers for detection or differentiation of early stage periodontitis using the immunoprotemic approach.

Method

In the present study, patient serum samples from four distinct stages of periodontitis (i.e., mild chronic, moderate chronic, severe chronic, and aggressive) and healthy controls were subjected to two-dimensional gel electrophoresis (2-DE), followed by silver staining. Notably, we consistently identified 14 protein clusters in the sera of patients and normal controls.

Results

Overall, we found that protein levels were comparable between patients and controls, with the exception of the clusters corresponding to A1AT, HP, IGKC and KNG1 (p < 0.05). In addition, the immunogenicity of these proteins was analysed via immunoblotting, which revealed differential profiles for periodontal disease and controls. For this reason, IgM obtained from severe chronic periodontitis (CP) sera could be employed as a suitable autoantibody for the detection of periodontitis.

Discussion

Taken together, the present study suggests that differentially expressed host immune response proteins could be used as potential biomarkers for screening periodontitis. Future studies exploring the diagnostic potential of such factors are warranted.

SUBMITTER: Kerishnan JP

PROVIDER: S-EPMC5012327 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Publications

Identification of biomarkers for periodontal disease using the immunoproteomics approach.

Kerishnan Jesinda P JP Mohammad Sani S Alias Muhamad Shaifunizam MS Mu Alan Kang-Wai AK Vaithilingam Rathna Devi RD Baharuddin Nor Adinar NA Safii Syarida H SH Abdul Rahman Zainal Ariff ZA Chen Yu Nieng YN Chen Yeng Y

PeerJ 20160824

<h4>Background</h4>Periodontitis is one of the most common oral diseases associated with the host's immune response against periodontopathogenic infection. Failure to accurately diagnose the stage of periodontitis has limited the ability to predict disease status. Therefore, we aimed to look for reliable diagnostic markers for detection or differentiation of early stage periodontitis using the immunoprotemic approach.<h4>Method</h4>In the present study, patient serum samples from four distinct s ...[more]

PMID: 27635317

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Dataset Information

Identification of biomarkers for periodontal disease using the immunoproteomics approach.

Background

Method

Results

Discussion

Publications

Identification of biomarkers for periodontal disease using the immunoproteomics approach.

Similar Datasets

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