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Saliva, Plasma, and Multifluid Metabolomic Signatures of Periodontal Disease, Type 2 Diabetes Progression, and Markers of Glycemia and Dyslipidemia Among Puerto Rican Adults With Overweight and Obesity.
Wang, Zicheng; Haslam, Danielle E; Sawicki, Caleigh M; Rivas-Tumanyan, Sona; Hu, Frank B; Liang, Liming; Wong, David T W; Joshipura, Kaumudi J; Bhupathiraju, Shilpa N.
Affiliation
  • Wang Z; Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA.
  • Haslam DE; Department of Nutrition Harvard T.H. Chan School of Public Health Boston MA USA.
  • Sawicki CM; Channing Division of Network Medicine Brigham and Women's Hospital and Harvard Medical School Boston MA USA.
  • Rivas-Tumanyan S; Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA.
  • Hu FB; Channing Division of Network Medicine Brigham and Women's Hospital and Harvard Medical School Boston MA USA.
  • Liang L; University of Puerto Rico Medical Sciences Campus San Juan Puerto Rico.
  • Wong DTW; Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA.
  • Joshipura KJ; Department of Nutrition Harvard T.H. Chan School of Public Health Boston MA USA.
  • Bhupathiraju SN; Department of Epidemiology Harvard T.H. Chan School of Public Health Boston MA USA.
J Am Heart Assoc ; 13(15): e033350, 2024 Aug 06.
Article de En | MEDLINE | ID: mdl-39023061
ABSTRACT

BACKGROUND:

Evidence from cohort studies indicates a bidirectional relationship between periodontal disease and type 2 diabetes (T2D), but the underlying mechanisms remain unknown. In this study, we aimed to (1) identify saliva, plasma, and multifluid metabolomic signatures associated with periodontal disease and (2) determine if these signatures predict T2D progression and cardiometabolic biomarkers at year 3. METHODS AND

RESULTS:

We included participants from the SOALS (San Juan Overweight Adult Longitudinal Study) (n=911). Metabolites from saliva (k=635) and plasma (k=1051) were quantified using liquid chromatography-mass spectrometry. We applied elastic net regression with 10-fold cross-validation to identify baseline metabolomic signatures of periodontal disease. Multivariable Cox proportional hazards regression and linear regression were used to evaluate the association with T2D progression and biomarker concentrations. Metabolomic profiles included highly weighted metabolites related to lysine and pyrimidine metabolism. Periodontal disease or its 3 metabolomic signatures were not associated with T2D progression in 3 years. Prospectively, 1-SD increments in the multifluid and saliva metabolomic signatures were associated with higher low-density lipoprotein (multifluid 12.9±5.70, P=0.02; saliva 13.3±5.11, P=0.009). A 1-SD increment in the plasma metabolomic signature was also associated with Homeostatic Model Assessment for Insulin Resistance (2.67±1.14, P=0.02) and triglyceride (0.52±0.18, P=0.002).

CONCLUSIONS:

Although metabolomic signatures of periodontal disease could not predict T2D progression, they were associated with low-density lipoprotein, triglyceride, and Homeostatic Model Assessment for Insulin Resistance levels at year 3.
Sujet(s)
Mots clés

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Maladies parodontales / Salive / Marqueurs biologiques / Évolution de la maladie / Diabète de type 2 / Dyslipidémies / Métabolomique / Obésité Langue: En Journal: J Am Heart Assoc Année: 2024 Type de document: Article Pays de publication: Royaume-Uni

Texte intégral: 1 Collection: 01-internacional Base de données: MEDLINE Sujet principal: Maladies parodontales / Salive / Marqueurs biologiques / Évolution de la maladie / Diabète de type 2 / Dyslipidémies / Métabolomique / Obésité Langue: En Journal: J Am Heart Assoc Année: 2024 Type de document: Article Pays de publication: Royaume-Uni