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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...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Hindawi
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433218/ https://www.ncbi.nlm.nih.gov/pubmed/36059915 http://dx.doi.org/10.1155/2022/7544864 |
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author | Bencharit, Sompop Carlson, James Byrd, Warren C. Howard-Williams, Escher L. Seagroves, Jackson T. McRitchie, Susan Buse, John B. Sumner, Susan |
author_facet | Bencharit, Sompop Carlson, James Byrd, Warren C. Howard-Williams, Escher L. Seagroves, Jackson T. McRitchie, Susan Buse, John B. Sumner, Susan |
author_sort | Bencharit, Sompop |
collection | PubMed |
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 | Online Article Text |
id | pubmed-9433218 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-94332182022-09-01 Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes Bencharit, Sompop Carlson, James Byrd, Warren C. Howard-Williams, Escher L. Seagroves, Jackson T. McRitchie, Susan Buse, John B. Sumner, Susan Int J Dent Research Article 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. Hindawi 2022-08-24 /pmc/articles/PMC9433218/ /pubmed/36059915 http://dx.doi.org/10.1155/2022/7544864 Text en Copyright © 2022 Sompop Bencharit et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Bencharit, Sompop Carlson, James Byrd, Warren C. Howard-Williams, Escher L. Seagroves, Jackson T. McRitchie, Susan Buse, John B. Sumner, Susan Salivary Metabolomics of Well and Poorly Controlled Type 1 and Type 2 Diabetes |
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 |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9433218/ https://www.ncbi.nlm.nih.gov/pubmed/36059915 http://dx.doi.org/10.1155/2022/7544864 |
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