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Realizing the clinical utility of saliva for monitoring oral diseases.
Ebersole, Jeffrey L; Hasturk, Hatice; Huber, Michaell; Gellibolian, Robert; Markaryan, Adam; Zhang, Xiaohua D; Miller, Craig S.
Afiliação
  • Ebersole JL; Department of Biomedical Sciences, School of Dental Medicine, University of Nevada Las Vegas, Las Vegas, Nevada, USA.
  • Hasturk H; Immunology and Inflammation, Center for Clinical and Translational Research, The ADA Forsyth Institute, Cambridge, Massachusetts, USA.
  • Huber M; Department of Comprehensive Dentistry, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
  • Gellibolian R; CellectGen, Inc., Pasadena, California, USA.
  • Markaryan A; CellectGen, Inc., Pasadena, California, USA.
  • Zhang XD; Department of Biostatistics, College of Public Health, University of Kentucky, Lexington, Kentucky, USA.
  • Miller CS; Department of Oral Health Practice, College of Dentistry, University of Kentucky, Lexington, Kentucky, USA.
Periodontol 2000 ; 2024 Jul 15.
Article em En | MEDLINE | ID: mdl-39010260
ABSTRACT
In the era of personalized/precision health care, additional effort is being expended to understand the biology and molecular mechanisms of disease processes. How these mechanisms are affected by individual genetics, environmental exposures, and behavioral choices will encompass an expanding role in the future of optimally preventing and treating diseases. Considering saliva as an important biological fluid for analysis to inform oral disease detection/description continues to expand. This review provides an overview of saliva as a diagnostic fluid and the features of various biomarkers that have been reported. We emphasize the use of salivary biomarkers in periodontitis and transport the reader through extant literature, gaps in knowledge, and a structured approach toward validating and determine the utility of biomarkers in periodontitis. A summation of the findings support the likelihood that a panel of biomarkers including both host molecules and specific microorganisms will be required to most effectively identify risk for early transition to disease, ongoing disease activity, progression, and likelihood of response to standard periodontal therapy. The goals would be to develop predictive algorithms that serve as adjunctive diagnostic tools which provide the clinician and patient important information for making informed clinical decisions.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Ano de publicação: 2024 Tipo de documento: Article