Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes
Objective. The concentrations of endogenous metabolites in saliva can be altered based on the systemic condition of the hosts and may, in theory, serve as a reflection of systemic disease progression. Hemoglobin A1C is used clinically to measure long-term average glycemic control. The aim of the stu...
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| Format: | Article |
| Language: | English |
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Wiley
2022-01-01
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| Series: | International Journal of Dentistry |
| Online Access: | http://dx.doi.org/10.1155/2022/7544864 |
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| author | Sompop Bencharit James Carlson Warren C. Byrd Escher L. Howard-Williams Jackson T. Seagroves Susan McRitchie John B. Buse Susan Sumner |
| author_facet | Sompop Bencharit James Carlson Warren C. Byrd Escher L. Howard-Williams Jackson T. Seagroves Susan McRitchie John B. Buse Susan Sumner |
| author_sort | Sompop Bencharit |
| collection | DOAJ |
| description | Objective. The concentrations of endogenous metabolites in saliva can be altered based on the systemic condition of the hosts and may, in theory, serve as a reflection of systemic disease progression. Hemoglobin A1C is used clinically to measure long-term average glycemic control. The aim of the study was to demonstrate if there were differences in the salivary metabolic profiles between well and poorly controlled type 1 and type 2 subjects with diabetes. Subjects and Methods. Subjects with type 1 and type 2 diabetes were enrolled (n = 40). The subjects were assigned to phenotypic groups based on their current level of A1C: <7 = well-controlled and >7 = poorly controlled. Demographic data, age, gender, and ethnicity, were used to match the two phenotypic groups. Whole saliva samples were collected and immediately stored at −80°C. Samples were spiked using an isotopically labeled internal standard and analyzed by UPLC-TOF-MS using a Waters SYNAPT G2-Si mass spectrometer. Results. Unsupervised principal components analysis (PCA) and orthogonal partial least squares regression discrimination analysis (OPLS-DA) were used to define unique metabolomic profiles associated with well and poorly controlled diabetes based on A1C levels. Conclusion. OPLS-DA demonstrates good separation of well and poorly controlled in both type 1 and type 2 diabetes. This provides evidence for developing saliva-based monitoring tools for diabetes. |
| format | Article |
| id | doaj-art-3970c9889a604fd69db39a22dd5ad73d |
| institution | Kabale University |
| issn | 1687-8736 |
| language | English |
| publishDate | 2022-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Dentistry |
| spelling | doaj-art-3970c9889a604fd69db39a22dd5ad73d2025-02-03T05:50:40ZengWileyInternational Journal of Dentistry1687-87362022-01-01202210.1155/2022/7544864Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 DiabetesSompop Bencharit0James Carlson1Warren C. Byrd2Escher L. Howard-Williams3Jackson T. Seagroves4Susan McRitchie5John B. Buse6Susan Sumner7Department of Oral and Craniofacial Molecular BiologySystems and Translational SciencesSchool of DentistrySchool of DentistryDepartment of Oral and Craniofacial Molecular BiologySystems and Translational SciencesDepartment of Internal MedicineSystems and Translational SciencesObjective. The concentrations of endogenous metabolites in saliva can be altered based on the systemic condition of the hosts and may, in theory, serve as a reflection of systemic disease progression. Hemoglobin A1C is used clinically to measure long-term average glycemic control. The aim of the study was to demonstrate if there were differences in the salivary metabolic profiles between well and poorly controlled type 1 and type 2 subjects with diabetes. Subjects and Methods. Subjects with type 1 and type 2 diabetes were enrolled (n = 40). The subjects were assigned to phenotypic groups based on their current level of A1C: <7 = well-controlled and >7 = poorly controlled. Demographic data, age, gender, and ethnicity, were used to match the two phenotypic groups. Whole saliva samples were collected and immediately stored at −80°C. Samples were spiked using an isotopically labeled internal standard and analyzed by UPLC-TOF-MS using a Waters SYNAPT G2-Si mass spectrometer. Results. Unsupervised principal components analysis (PCA) and orthogonal partial least squares regression discrimination analysis (OPLS-DA) were used to define unique metabolomic profiles associated with well and poorly controlled diabetes based on A1C levels. Conclusion. OPLS-DA demonstrates good separation of well and poorly controlled in both type 1 and type 2 diabetes. This provides evidence for developing saliva-based monitoring tools for diabetes.http://dx.doi.org/10.1155/2022/7544864 |
| spellingShingle | Sompop Bencharit James Carlson Warren C. Byrd Escher L. Howard-Williams Jackson T. Seagroves Susan McRitchie John B. Buse Susan Sumner Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes International Journal of Dentistry |
| title | Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes |
| title_full | Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes |
| title_fullStr | Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes |
| title_full_unstemmed | Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes |
| title_short | Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes |
| title_sort | salivary metabolomics of well and poorly controlled type 1 and type 2 diabetes |
| url | http://dx.doi.org/10.1155/2022/7544864 |
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