Potential of Human Saliva for Nuclear Magnetic Resonance-Based Metabolomics and for Health-Related Biomarker Identification

Bertram, Hanne Christine; Eggers, Nina; Eller, Nanna Hurwitz

doi:10.1021/ac9020598

Cited by 78 publications

(57 citation statements)

References 25 publications

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“…Up to date, the statisticians or chemometricians or biologists have developed a large number of methods (Golub et al 1999;Madsen et al 2010;Tibshirani 1996;Wongravee et al 2009;Zou and Hastie 2005) which can be utilized to reveal the informative metabolites, of which the changes may reflect the potential metabolic disorder in the living systems (Bertram et al 2009;Boudonck et al 2009;Crews et al 2009;Graham et al 2009). To identify the informative metabolite, a criterion will usually be first defined and then employed to assess the importance of the metabolite under investigation.…”

Section: Introductionmentioning

confidence: 99%

Recipe for revealing informative metabolites based on model population analysis

Zeng

Tan

et al. 2010

Metabolomics

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An important application of metabolic profiles is to discover informative metabolites/biomarkers which are predictive of a clinical outcome under investigation. Therefore, there is a need to develop statistically efficient method for screening such kind of metabolites from the candidates. The most commonly used criteria to assess variable (metabolite) importance may be the P value obtained by performing t test on each metabolite alone, without considering the influence of other variables. In this work, a new strategy, called subwindow permutation analysis (SPA) coupled with partial least squares linear discriminant analysis (PLSLDA), is developed for statistical assessment of variable importance. The main contribution of SPA is that, unlike t test, it can output a conditional P value by implicitly taking into account the synergetic effect of all the other variables. In this sense, the conditional P value could to some extent help locate a good combination of informative variables. When applied to two metabolic datasets (type 2 diabetes mellitus data and childhood overweight data), it is shown that the performance of both the unsupervised principal component analysis (PCA) and the supervised PLSLDA are greatly improved when using the informative metabolites revealed by SPA. The source codes for implementing SPA in both MATLAB and R (R package for both Linux and Windows) are freely available at:

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Section: Introductionmentioning

confidence: 99%

Recipe for revealing informative metabolites based on model population analysis

Zeng

Tan

et al. 2010

Metabolomics

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“…Saliva and blood plasma were collected hourly and subsequently analyzed by GC/LC-MS. These matrices have been shown to yield valuable information regarding human metabolic state (13,18) and are easy to obtain.A total of 10 age-matched male subjects underwent the protocol (Fig. 1A) individually in isolation.…”

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confidence: 99%

“…The circadian metabolome also has been characterized in CBA/N mice, and ∼20% of the recorded molecules were found to vary in abundance with time of day (12). Similarly, the urine and saliva metabolomes of human subjects differ between morning and evening under real-world conditions (13,14). However, in mammals, indirect cues from behavior, such as feeding time and body temperature, are well-established and potent timing signals to the circadian clock (9, 15).…”

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confidence: 99%

The human circadian metabolome

Dallmann

Viola

Tarokh

et al. 2012

Proc. Natl. Acad. Sci. U.S.A.

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The circadian clock orchestrates many aspects of human physiology, and disruption of this clock has been implicated in various pathologies, ranging from cancer to metabolic syndrome and diabetes. Although there is evidence that metabolism and the circadian clockwork are intimately linked on a transcriptional level, whether these effects are directly under clock control or are mediated by the rest-activity cycle and the timing of food intake is unclear. To answer this question, we conducted an unbiased screen in human subjects of the metabolome of blood plasma and saliva at different times of day. To minimize indirect effects, subjects were kept in a 40-h constant routine of enforced posture, constant dim light, hourly isocaloric meals, and sleep deprivation. Under these conditions, we found that ∼15% of all identified metabolites in plasma and saliva were under circadian control, most notably fatty acids in plasma and amino acids in saliva. Our data suggest that there is a strong direct effect of the endogenous circadian clock on multiple human metabolic pathways that is independent of sleep or feeding. In addition, they identify multiple potential small-molecule biomarkers of human circadian phase and sleep pressure.metabolomics | LC/GC-MS | metabolite profiling | sleep-wake regulation T he circadian clock has been shown to modulate many aspects of behavior and physiology (1). It is thought to be an important regulator of metabolism, and disruption of the clock and sleep is associated with obesity, metabolic syndrome, and type 2 diabetes, as well as other disorders (2-4). In the last decade, ample data on the circadian transcriptome (5, 6) and the even larger circadian proteome (7) have been compiled. These datasets are directly dependent on the genome of a particular species and cannot be compared easily between model systems. However, changes in physiology and metabolism governed by these genes and proteins ultimately affect the abundance of small metabolites that are quite conserved among species and fewer in number (50-fold fewer than transcripts and 500-fold fewer than proteins).The relationship between metabolism and the clock is not unidirectional, and the two processes are intertwined (8). For example, metabolic status feeds back to the clock, so that feeding behavior directly entrains molecular clock function (9). Likewise, obesity is correlated with poor sleep (2), and in mice 80% of circadian transcription in the brain is dependent on the rest-activity cycle (10). Given these feedback mechanisms, it is unclear what proportion of circadian metabolic control is directly clockregulated and what proportion is controlled by circadian restactivity and food intake.In plants, the metabolome approach has been used to characterize the effects of clock disruption on general metabolism (11). The circadian metabolome also has been characterized in CBA/N mice, and ∼20% of the recorded molecules were found to vary in abundance with time of day (12). Similarly, the urine and saliva metabolomes of human subjects diff...

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“…Untargeted metabolomics profile many thousands of features (molecules of particular column retention times and molecular mass) globally and can discover novel biomarkers found in specific conditions and thus identify new targets (100, 102). One-dimensional (1D) NMR can also profile the metabolites from blood plasma, urine, saliva, and tissue extracts (103,104). NMR in two-dimensional (2D) mode can elucidate the molecular structure and facilitate molecule identification with increased signal dispersion (103).…”

Section: Figmentioning

confidence: 99%