Proton‐Nuclear Magnetic Resonance Metabolomics of Gingival Crevicular Fluid During Orthodontic Tooth Movement With Aligners

ABSTRACT Objectives To determine the correlation between orthodontic tooth movement and a pre‐defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H‐NMR) spectroscopy. Materials and Methods A clinical randomised prospective split‐mouth study comparin...

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Published inOrthodontics & craniofacial research Vol. 28; no. 4; pp. 670 - 679
Main Authors Domini, Maria Chiara, Castroflorio, Tommaso, Deregibus, Andrea, Ravera, Serena, Migliaretti, Giuseppe, Costalonga, Massimo
Format Journal Article
LanguageEnglish
Published England Wiley Subscription Services, Inc 01.08.2025
John Wiley and Sons Inc
Subjects
Adolescent
Adult
bone remodelling
clear aligner appliances
Female
Gingival Crevicular Fluid - chemistry
Gingival Crevicular Fluid - metabolism
Glutamine
Humans
Magnetic Resonance Spectroscopy
Male
Malocclusion, Angle Class II - therapy
Metabolites
Metabolomics
Metabolomics - methods
Molar
Molars
NMR
Nuclear magnetic resonance
orthodontic tooth movements
Orthodontics
Principal Component Analysis
Principal components analysis
Prospective Studies
Proton Magnetic Resonance Spectroscopy
Spectroscopy
Spectrum analysis
Statistical analysis
Teeth
Tooth Movement Techniques - instrumentation
Uracil
Young Adult
bone remodelling
orthodontic tooth movements
metabolomics
proton magnetic resonance spectroscopy
clear aligner appliances
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Abstract ABSTRACT Objectives To determine the correlation between orthodontic tooth movement and a pre‐defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H‐NMR) spectroscopy. Materials and Methods A clinical randomised prospective split‐mouth study comparing the GCF metabolites around stationary and moving second maxillary molars. Twenty‐four healthy subjects diagnosed with dental class II malocclusion undergoing orthodontic clear aligner treatment (CAT) were enrolled. GCF samples from the mesial and distal sulcus of second molars under stationary conditions or under 1 N of distalising force were harvested at baseline, 1 h, 7 days and 21 days after the application of CAT. 1H‐NMR was utilised for GCF sample analysis. The 2‐dimensional total correlation spectroscopy spectral signature of 35 known GCF metabolites was compared in moving and stationary teeth. Principal component analysis (PCA), partial least squares‐discriminant analysis (PLS‐DA), variable importance in projection (VIP) score and area under the curve (AUC) were computed utilising MetaboAnalyst 5.0 software. Results VIP‐score values showed statistically significant differences between the metabolites involved in moving and stationary molars (p < 0.05). PCA and PLS‐DA results showed potential differences between the metabolite clusters. The variation of the 1H‐NMR signals of Glutamine, Uracil, N‐Acetylneuraminate and alpha‐ketoglutarate contributes primarily to the variance across metabolites in moving versus stationary teeth at 1 h, 7 days and 21 days. Conclusion High values of Glutamine and low values of Uracil, N‐Acetylneurinamate and alpha‐ketoglutarate could be utilised to predict the progress of orthodontic tooth movement over time. Knowledge of metabolites predictive of tooth movement could contribute to the design of tailored orthodontic treatment planning, reducing time, costs and side‐effects.
AbstractList To determine the correlation between orthodontic tooth movement and a pre-defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H-NMR) spectroscopy.OBJECTIVESTo determine the correlation between orthodontic tooth movement and a pre-defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H-NMR) spectroscopy.A clinical randomised prospective split-mouth study comparing the GCF metabolites around stationary and moving second maxillary molars. Twenty-four healthy subjects diagnosed with dental class II malocclusion undergoing orthodontic clear aligner treatment (CAT) were enrolled. GCF samples from the mesial and distal sulcus of second molars under stationary conditions or under 1 N of distalising force were harvested at baseline, 1 h, 7 days and 21 days after the application of CAT. 1H-NMR was utilised for GCF sample analysis. The 2-dimensional total correlation spectroscopy spectral signature of 35 known GCF metabolites was compared in moving and stationary teeth. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), variable importance in projection (VIP) score and area under the curve (AUC) were computed utilising MetaboAnalyst 5.0 software.MATERIALS AND METHODSA clinical randomised prospective split-mouth study comparing the GCF metabolites around stationary and moving second maxillary molars. Twenty-four healthy subjects diagnosed with dental class II malocclusion undergoing orthodontic clear aligner treatment (CAT) were enrolled. GCF samples from the mesial and distal sulcus of second molars under stationary conditions or under 1 N of distalising force were harvested at baseline, 1 h, 7 days and 21 days after the application of CAT. 1H-NMR was utilised for GCF sample analysis. The 2-dimensional total correlation spectroscopy spectral signature of 35 known GCF metabolites was compared in moving and stationary teeth. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), variable importance in projection (VIP) score and area under the curve (AUC) were computed utilising MetaboAnalyst 5.0 software.VIP-score values showed statistically significant differences between the metabolites involved in moving and stationary molars (p < 0.05). PCA and PLS-DA results showed potential differences between the metabolite clusters. The variation of the 1H-NMR signals of Glutamine, Uracil, N-Acetylneuraminate and alpha-ketoglutarate contributes primarily to the variance across metabolites in moving versus stationary teeth at 1 h, 7 days and 21 days.RESULTSVIP-score values showed statistically significant differences between the metabolites involved in moving and stationary molars (p < 0.05). PCA and PLS-DA results showed potential differences between the metabolite clusters. The variation of the 1H-NMR signals of Glutamine, Uracil, N-Acetylneuraminate and alpha-ketoglutarate contributes primarily to the variance across metabolites in moving versus stationary teeth at 1 h, 7 days and 21 days.High values of Glutamine and low values of Uracil, N-Acetylneurinamate and alpha-ketoglutarate could be utilised to predict the progress of orthodontic tooth movement over time. Knowledge of metabolites predictive of tooth movement could contribute to the design of tailored orthodontic treatment planning, reducing time, costs and side-effects.CONCLUSIONHigh values of Glutamine and low values of Uracil, N-Acetylneurinamate and alpha-ketoglutarate could be utilised to predict the progress of orthodontic tooth movement over time. Knowledge of metabolites predictive of tooth movement could contribute to the design of tailored orthodontic treatment planning, reducing time, costs and side-effects.
Objectives To determine the correlation between orthodontic tooth movement and a pre‐defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H‐NMR) spectroscopy. Materials and Methods A clinical randomised prospective split‐mouth study comparing the GCF metabolites around stationary and moving second maxillary molars. Twenty‐four healthy subjects diagnosed with dental class II malocclusion undergoing orthodontic clear aligner treatment (CAT) were enrolled. GCF samples from the mesial and distal sulcus of second molars under stationary conditions or under 1 N of distalising force were harvested at baseline, 1 h, 7 days and 21 days after the application of CAT. 1H‐NMR was utilised for GCF sample analysis. The 2‐dimensional total correlation spectroscopy spectral signature of 35 known GCF metabolites was compared in moving and stationary teeth. Principal component analysis (PCA), partial least squares‐discriminant analysis (PLS‐DA), variable importance in projection (VIP) score and area under the curve (AUC) were computed utilising MetaboAnalyst 5.0 software. Results VIP‐score values showed statistically significant differences between the metabolites involved in moving and stationary molars (p < 0.05). PCA and PLS‐DA results showed potential differences between the metabolite clusters. The variation of the 1H‐NMR signals of Glutamine, Uracil, N‐Acetylneuraminate and alpha‐ketoglutarate contributes primarily to the variance across metabolites in moving versus stationary teeth at 1 h, 7 days and 21 days. Conclusion High values of Glutamine and low values of Uracil, N‐Acetylneurinamate and alpha‐ketoglutarate could be utilised to predict the progress of orthodontic tooth movement over time. Knowledge of metabolites predictive of tooth movement could contribute to the design of tailored orthodontic treatment planning, reducing time, costs and side‐effects.
To determine the correlation between orthodontic tooth movement and a pre-defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H-NMR) spectroscopy. A clinical randomised prospective split-mouth study comparing the GCF metabolites around stationary and moving second maxillary molars. Twenty-four healthy subjects diagnosed with dental class II malocclusion undergoing orthodontic clear aligner treatment (CAT) were enrolled. GCF samples from the mesial and distal sulcus of second molars under stationary conditions or under 1 N of distalising force were harvested at baseline, 1 h, 7 days and 21 days after the application of CAT. 1H-NMR was utilised for GCF sample analysis. The 2-dimensional total correlation spectroscopy spectral signature of 35 known GCF metabolites was compared in moving and stationary teeth. Principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), variable importance in projection (VIP) score and area under the curve (AUC) were computed utilising MetaboAnalyst 5.0 software. VIP-score values showed statistically significant differences between the metabolites involved in moving and stationary molars (p < 0.05). PCA and PLS-DA results showed potential differences between the metabolite clusters. The variation of the 1H-NMR signals of Glutamine, Uracil, N-Acetylneuraminate and alpha-ketoglutarate contributes primarily to the variance across metabolites in moving versus stationary teeth at 1 h, 7 days and 21 days. High values of Glutamine and low values of Uracil, N-Acetylneurinamate and alpha-ketoglutarate could be utilised to predict the progress of orthodontic tooth movement over time. Knowledge of metabolites predictive of tooth movement could contribute to the design of tailored orthodontic treatment planning, reducing time, costs and side-effects.
ABSTRACT Objectives To determine the correlation between orthodontic tooth movement and a pre‐defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear magnetic resonance (1H‐NMR) spectroscopy. Materials and Methods A clinical randomised prospective split‐mouth study comparing the GCF metabolites around stationary and moving second maxillary molars. Twenty‐four healthy subjects diagnosed with dental class II malocclusion undergoing orthodontic clear aligner treatment (CAT) were enrolled. GCF samples from the mesial and distal sulcus of second molars under stationary conditions or under 1 N of distalising force were harvested at baseline, 1 h, 7 days and 21 days after the application of CAT. 1H‐NMR was utilised for GCF sample analysis. The 2‐dimensional total correlation spectroscopy spectral signature of 35 known GCF metabolites was compared in moving and stationary teeth. Principal component analysis (PCA), partial least squares‐discriminant analysis (PLS‐DA), variable importance in projection (VIP) score and area under the curve (AUC) were computed utilising MetaboAnalyst 5.0 software. Results VIP‐score values showed statistically significant differences between the metabolites involved in moving and stationary molars (p < 0.05). PCA and PLS‐DA results showed potential differences between the metabolite clusters. The variation of the 1H‐NMR signals of Glutamine, Uracil, N‐Acetylneuraminate and alpha‐ketoglutarate contributes primarily to the variance across metabolites in moving versus stationary teeth at 1 h, 7 days and 21 days. Conclusion High values of Glutamine and low values of Uracil, N‐Acetylneurinamate and alpha‐ketoglutarate could be utilised to predict the progress of orthodontic tooth movement over time. Knowledge of metabolites predictive of tooth movement could contribute to the design of tailored orthodontic treatment planning, reducing time, costs and side‐effects.
Author Ravera, Serena
Castroflorio, Tommaso
Deregibus, Andrea
Domini, Maria Chiara
Costalonga, Massimo
Migliaretti, Giuseppe
AuthorAffiliation 1 School of Orthodontics, Dental School, Department of Surgical Sciences University of Turin Turin Italy
4 Division of Basic Sciences, Department of Diagnostic and Biological Sciences School of Dentistry, University of Minnesota Minneapolis Minnesota USA
2 Private Practice Turin Italy
3 Department of Public Health and Pediatric Sciences University of Turin Turin Italy
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Issue 4
Keywords bone remodelling
orthodontic tooth movements
metabolomics
proton magnetic resonance spectroscopy
clear aligner appliances
Language English
License Attribution-NonCommercial-NoDerivs
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Notes Funding
Academic Health Center–Faculty Research Development Grant No. FRD15.30 from the University of Minnesota, Align Technology International Research Award and the International Orthodontics Foundation.
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Funding: Academic Health Center–Faculty Research Development Grant No. FRD15.30 from the University of Minnesota, Align Technology International Research Award and the International Orthodontics Foundation.
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Snippet ABSTRACT Objectives To determine the correlation between orthodontic tooth movement and a pre‐defined set of gingival crevicular fluid (GCF) metabolites...
To determine the correlation between orthodontic tooth movement and a pre-defined set of gingival crevicular fluid (GCF) metabolites through proton nuclear...
Objectives To determine the correlation between orthodontic tooth movement and a pre‐defined set of gingival crevicular fluid (GCF) metabolites through proton...
SourceID pubmedcentral
proquest
pubmed
crossref
wiley
SourceType Open Access Repository
Aggregation Database
Index Database
Publisher
StartPage 670
SubjectTerms Adolescent
Adult
bone remodelling
clear aligner appliances
Female
Gingival Crevicular Fluid - chemistry
Gingival Crevicular Fluid - metabolism
Glutamine
Humans
Magnetic Resonance Spectroscopy
Male
Malocclusion, Angle Class II - therapy
Metabolites
Metabolomics
Metabolomics - methods
Molar
Molars
NMR
Nuclear magnetic resonance
orthodontic tooth movements
Orthodontics
Principal Component Analysis
Principal components analysis
Prospective Studies
Proton Magnetic Resonance Spectroscopy
Spectroscopy
Spectrum analysis
Statistical analysis
Teeth
Tooth Movement Techniques - instrumentation
Uracil
Young Adult
Title Proton‐Nuclear Magnetic Resonance Metabolomics of Gingival Crevicular Fluid During Orthodontic Tooth Movement With Aligners
URI https://onlinelibrary.wiley.com/doi/abs/10.1111%2Focr.12916
https://www.ncbi.nlm.nih.gov/pubmed/40110902
https://www.proquest.com/docview/3229056822
https://www.proquest.com/docview/3179248850
https://pubmed.ncbi.nlm.nih.gov/PMC12233055
Volume 28
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