1,5-Anhydroglucitol in Saliva Is a Noninvasive Marker of Short-Term Glycemic Control

Mook‐Kanamori, Dennis O.; Selim, Mohamed; Takiddin, Ahmed H.; Al-Homsi, Hala; Al-Mahmoud, Khoulood A.S.; Al-Obaidli, Amina; Zirie, Mahmoud; Rowe, Jillian; Yousri, Noha A.; Karoly, Edward D.; Kocher, Thomas; Gherbi, Wafaa Sekkal; Chidiac, Omar; Mook-Kanamori, Marjonneke J.; Kader, Sara Abdul; Muftah, Wadha A. Al; McKeon, Cindy; Suhre, Karsten

doi:10.1210/jc.2013-3596

Cited by 87 publications

(128 citation statements)

References 19 publications

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“…A number of studies have previously compared metabolite features measured across matrices sampled from the same persons (30, 32, 33, 51–56). To our knowledge, however, the results from this pilot study are among the first to examine matrix comparability between plasma (relatively invasive) and saliva or EBC (non-invasive) using this measurement method.…”

Section: Discussionmentioning

confidence: 99%

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

et al. 2017

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Introduction Advances in the development of high-resolution metabolomics (HRM) have provided new opportunities for their use in characterizing exposures to environmental air pollutants and air pollution-related disease etiologies. Exposure assessment studies have considered blood, breath, and saliva as biological matrices suitable for measuring responses to air pollution exposures. The current study examines comparability among these three matrices using HRM and explored their potential for measuring mobile source air toxics. Methods Four participants provided saliva, exhaled breath concentrate (EBC), and plasma before and after a 2-hour road traffic exposure. Samples were analyzed on a Thermo Scientific QExactive MS system in positive electrospray ionization (ESI) mode and resolution of 70,000 FHWM with C18 chromatography. Data were processed using apLCMS and xMSanalyzer on the R statistical platform. Results The analysis yielded 7,110, 6,019, and 7,747 reproducible features in plasma, EBC, and saliva, respectively. Correlations were moderate-to-strong (R = 0.41 – 0.80) across all pairwise comparisons of feature intensity within profiles, with the strongest between EBC and saliva. The associations of mean intensities between matrix pairs were positive and significant, controlling for subject and sampling time effects. Six out of 20 features shared in all three matrices putatively matched a list of known mobile-source air toxics. Conclusions Plasma, saliva, and EBC have largely comparable metabolic profiles measurable through HRM. These matrices have the potential to be used in identification and measurement of exposures to mobile source air toxics, though further, targeted study is needed.

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Section: Discussionmentioning

confidence: 99%

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

et al. 2017

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“…A major strength of the current study was that all participants were naïve to drug treatment [6]. In most cross-sectional metabolomics studies on type 2 diabetes the participants were using glucose-or lipid-lowering drugs, which could influence the results [5,10,26]. We did not perform any matching in our study and instead adjusted for covariates, while some metabolomics studies have been performed in matched case-control designs on age, sex and BMI [4,8].…”

Section: Discussionmentioning

confidence: 99%

“…It has been hypothesized that these branched-chain amino acids interfere with mitochondrial metabolism of fatty acids [12]. However, many other amino acids have also been shown to be involved, including phenylalanine [4e7, 9,11], tyrosine [4,6,7,9,11], glutamine [6], glycine [8,9,11], arginine [5], histidine [8], ornithine [5], proline [5,6,10] and tryptophan [9].…”

Section: Introductionmentioning

confidence: 99%

Type 2 diabetes is associated with postprandial amino acid measures

Mook‐Kanamori

Mutsert

Rensen

et al. 2016

Archives of Biochemistry and Biophysics

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Most studies examining the association between type 2 diabetes (T2D) and amino acids have focused on fasting concentrations. We hypothesized that, besides fasting concentrations, amino acid responses to a standardized meal challenge are also associated with T2D. In a cross-sectional study of 525 participants (165 newly-diagnosed T2D, 186 newly-diagnosed impaired fasting glycaemia, and 174 normal fasting glucose), we examined postprandial amino acid concentrations and the responses (defined as the concentrations and responses 150 min after a standardized meal) of fourteen amino acids in relation to T2D. T2D was associated with lower postprandial concentration of seven amino acids compared to the normal fasting glucose group (lowest effect estimate for serine: -0.54 standard deviations (SD) (95% CI: -0.77, -0.32)), and higher concentrations of phenylalanine, tryptophan, tyrosine and (iso-)leucine (highest effect estimate for (iso-)leucine: 0.44 SD (95% CI: 0.20, 0.67)). Regarding the meal responses, T2D was associated with lower responses of seven amino acids (ranging from -0.55 SD ((95% CI): -0.78, -0.33) for serine to -0.25 SD ((95% CI: -0.45, -0.02) for ornithine). We conclude that T2D is associated with postprandial concentrations of amino acids and a reduced amino acid meal response, indicating that these measures may also be potential markers of T2D.

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“…The level of 1,5-AG in blood is inversely related to the concentration of glucose and glycosylated hemoglobin levels in humans [41]. In the brain, 1,5-AG levels are elevated significantly compared with control animals.…”

Section: Discussionmentioning

confidence: 99%

“…This could relate to decreasing arginine availability. 1,5-AG (p=0.0059) is inversely-associated with glucose levels in biological fluids such as saliva and serum [41,57], thus, an increase in 1,5-AG levels could suggest subtle decreases in glucose availability. Trends toward decreases in lysolipids could reflect changes in signaling or demand for fatty acids to support beta-oxidation.…”

Section: Discussionmentioning

confidence: 99%

Experimental Periodontitis Results in Prediabetes and Metabolic Alterations in Brain, Liver and Heart: Global Untargeted Metabolomic Analyses

et al. 2016

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Results from epidemiological studies suggest that there is an association between periodontitis and prediabetes, however, causality is not known. The results from our previous studies suggest that induction of periodontitis leads to hyperinsulinemia glucose intolerance and insulin resistance, all hallmarks of prediabetes. However, global effects of periodontitis on critical organs in terms of metabolic alterations are unknown. We determined the metabolic effects of periodontitis on brain, liver, heart and plasma resulting from Porphyromonas gingivalis induced periodontitis in mice. Periodontitis was induced by oral application of the periodontal pathogen, Porphyromonas gingivalis for 22 weeks. Global untargeted biochemical profiles in samples from these organs/plasma were determined by liquid and gas chromatography/mass spectrometry and compared between controls and animals with periodontitis. Oral application of Porphyromonas gingivalis induced chronic periodontitis and hallmarks of prediabetes. The results of sample analyses indicated a number of changes in metabolic readouts, including changes in metabolites related to glucose and arginine metabolism, inflammation and redox homeostasis. Changes in biochemicals suggested subtle systemic effects related to periodontal disease, with increases in markers of inflammation and oxidative stress most prominent in the liver. Signs of changes in redox homeostasis were also seen in the brain and heart. Elevated bile acids in liver were suggestive of increased biosynthesis, which may reflect changes in liver function. Interestingly, signs of decreasing glucose availability were seen in the brain. In all three organs and plasma, there was a significant increase in the microbiome-derived bioactive metabolite 4-ethylphenylsulfate sulfate in animals with periodontitis. The results of metabolic profiling suggest that periodontitis/bacterial products alter metabolomic signatures of brain, heart, liver, and plasma in the prediabetic state. These data provide scientific community valuable metabolic signatures that become the basis for understanding the impact of periodontitis on a systemic disease and potentially targets for therapeutic intervention.

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1,5-Anhydroglucitol in Saliva Is a Noninvasive Marker of Short-Term Glycemic Control

Cited by 87 publications

References 19 publications

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

Metabolomic profiles of plasma, exhaled breath condensate, and saliva are correlated with potential for air toxics detection

Type 2 diabetes is associated with postprandial amino acid measures

Experimental Periodontitis Results in Prediabetes and Metabolic Alterations in Brain, Liver and Heart: Global Untargeted Metabolomic Analyses

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