Takayuki Teruya’s research while affiliated with Okinawa Institute of Science and Technology Graduate University and other places

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Publications (23)


Characteristics and classification of 18 subjects. (A) Subjects were divided into four groups based on their HbA1c levels and BMI. Gender composition, mean ± SD of HbA1c, and BMI for each group are shown. (B) Group composition of non-diabetic (ND), T2D, non-obese (non-Ob), and obese (Ob) groups. (C,D) Graphic presentations of HbA1c, plasma glucose, BMI, and age in ND vs T2D (C) and non-Ob vs Ob (D). In each panel, p-values are presented to show the significance of differences. P-values less than 0.05 are highlighted in blue.
Volcano plot analysis of blood metabolites. The identified 125 compounds are plotted. The x-axis is the log2-fold change, whereas the y-axis is the -log10 p value of the Mann–Whitney U-test. Two vertical dashed lines indicate 0.66 and 1.5-fold changes. The horizontal dashed line shows a p value = 0.05. (A) Metabolites that were more than 1.5 times higher in T2D than ND are shown in red, and metabolites that were less than two-thirds (0.66 times) lower are shown in blue. (B) Similar to (A), metabolites that were more than 1.5 times higher in Ob than non-Ob are shown in red, and metabolites that were less than two-thirds (0.66 times) lower are shown in blue. The highlighted 20 compounds in (A) and 13 in (B) were identified as T2D markers and obesity markers, respectively. RBC-enriched compounds are underlined.
Pearson's correlation analysis identified strong metabolic relationships. (A) Correlation coefficients of T2D markers were calculated. Orange and green boxes indicate positive (r > 0.75) and negative (r < − 0.75) correlations, respectively. 6-PG 6-phosphogluconate, N-Me-AdoN-methyl-adenosine, UDP-GlcUA UDP-glucuronate, G3P glyceraldehyde-3-phosphate, PP pentose-phosphate, UDP-Glc UDP-glucose, Kyn kynurenine, Cyd cytidine, diMe-xanthine dimethyl-xanthine. (B) Obesity markers with a correlation of 0.75 or higher are shown. N2-Ac-LysN2-acetyl-lysine, diMe-Arg dimethyl-arginine, triMe-Lys trimethyl-lysine, N1-Me-His N1-methyl-histidine, C3-Cnt propionyl-carnitine, C4-Cnt butyryl-carnitine, C5-Cnt valeryl-carnitine, N2-Ac-Arg N2-acetyl-arginine.
Hierarchical clustering heatmap of 20 T2D and 13 obesity-related compounds. A heat map was constructed for 18 subjects using a color matrix representing relative abundance data of 33 metabolites implicated in diabetes or obesity. Numerical values indicate the T score, a kind of standardized score. The average and standard deviation are 50 and 10, respectively. Blue cells indicate metabolite titers that are below average (50), whereas red cells indicate levels that are higher than average. Color intensity of cells reflects the T score.
PCA plots of T2D and obesity-related compounds. (A) All 125 compounds identified in the present study roughly divided the T2D and ND groups. (B) Twenty diabetic markers separated ND and T2D subjects, except one subject (no. 18). (C) Thirteen obesity markers largely separated non-Ob and Ob subjects. (D) Even eight metabolites separated four subject groups, Ob T2D, non-Ob ND, non-Ob T2D, and Ob ND, to up, down, left, and right sides, respectively.
Markers for obese and non-obese Type 2 diabetes identified using whole blood metabolomics
  • Article
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February 2023

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78 Reads

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11 Citations

Takayuki Teruya

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Sumito Sunagawa

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Mitsuhiro Yanagida

Definitive differences in blood metabolite profiles between obese and non-obese Type 2 diabetes (T2D) have not been established. We performed an LC–MS-based non-targeted metabolomic analysis of whole blood samples collected from subjects classified into 4 types, based on the presence or absence of obesity and T2D. Of the 125 compounds identified, 20, comprising mainly nucleobases and glucose metabolites, showed significant increases or decreases in the T2D group. These included cytidine, UDP-glucuronate, UMP, 6-phosphogluconate, and pentose-phosphate. Among those 20 compounds, 11 enriched in red blood cells (RBCs) have rarely been studied in the context of diabetes, indicating that RBC metabolism is more extensively disrupted than previously known. Correlation analysis revealed that these T2D markers include 15 HbA1c-associated and 5 irrelevant compounds that may reflect diabetic conditions by a different mechanism than that of HbA1c. In the obese group, enhanced protein and fatty acid catabolism causes increases in 13 compounds, including methylated or acetylated amino acids and short-chain carnitines. Our study, which may be considered a pilot investigation, suggests that changes in blood metabolism due to obesity and diabetes are large, but essentially independent.

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Decline of ergothioneine in frailty and cognition impairment

January 2022

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62 Reads

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19 Citations

Ergothioneine is a well-known anti-oxidant that is abundant in both human red blood cells and in fission yeast responding to nutritional stress. In frail elderly people, whose aging organs undergo functional decline, there is a correlation between ergothioneine levels and cognitive, but not skeletal muscle decline. In patients suffering from dementia, including Alzheimer's disease with hippocampal atrophy, deteriorating cognitive ability is correlated with declining ergothioneine levels. S-methyl-ergothioneine, trimethyl-histidine, and three other trimethyl-ammonium compounds also decrease sharply in dementia, whereas compounds such as indoxyl-sulfate and quinolinic acid increase, possibly exacerbating the disease. Using these opposing dementia markers, not only diagnosis, but also therapeutic interventions to mitigate cognitive decline may now become possible.


Whole-blood metabolomics of dementia patients reveal classes of disease-linked metabolites

September 2021

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70 Reads

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88 Citations

Proceedings of the National Academy of Sciences

Significance Dementia is a slowly progressing, chronic, and usually irreversible decline in cognitive function. Mechanistic causes and definitive treatments remain elusive. Using comprehensive metabolomics, we identified five groups of 33 metabolites (A to E), 13 of them previously reported, possibly useful for diagnosis and therapy of forms of dementia, such as Alzheimer’s disease. Seven A compounds may act as neurotoxins, whereas B to E compounds may protect the nervous system against oxidative stress, maintain energy reserves, supply nutrients and neuroprotective factors. Five metabolites, ergothioneine, S -methyl-ergothioneine, trimethyl-histidine, methionine, and tryptophan, overlap with those reported for frailty. Interventions for cognitive diseases involving these dementia metabolomic markers may be accomplished either by inhibiting A compounds or by supplementing B to E compounds in patients.


Figure 1. Volcano plot showing different levels of salivary metabolites in young and elderly subjects. The x-axis is the log2 fold change, whereas the y-axis is the -log10 p value of the Mann Whitney U-test. Two vertical dashed lines show the border of 0.66-and 1.5-fold change, respectively. The horizontal dashed line shows a p value = 0.05. Plots represent significantly higher (red), lower (blue), and unchanged metabolites (gray) in the elderly group. Twenty-one metabolites manifesting age differences are listed in the purple box.
Figure 2. Coefficients of variation (CVs) of 99 salivary metabolites in 27 people from Onna Village, Okinawa. Compounds were classified into 6 sub-groups according to their CVs, as explained in Chaleckis et al. 3 . Numbers of compounds belonging to subgroups are shown in parentheses. Abundances of compounds are semi-quantitatively indicated by their peak areas. In blood, compounds underlined are enriched in RBCs. Compounds shown with asterisks are age-related in saliva.
Figure 4. Hierarchical clustering heatmap of 21 salivary age-related metabolites in 14 elderly and 13 young subjects. Correlations between compounds are reflected by bar lengths, which is consistent with the correlation network data (Supplementary Fig. S3). Standardized scores (T scores) for each metabolite are represented by colors. The average value (50), white; values above average, red; values below average, blue. Color intensity of the cells reflects the T score. The cluster dendrogram was created by using R. Microsoft Excel was used to calculate T scores and create the heatmap.
Figure 5. Common human age-related metabolites in saliva, blood, and/or urine. (a) Numbers of shared compounds in overlapping regions. No compound was common to saliva, blood, and urine. Three, 7, and 8 compounds were common between saliva and blood, between blood and urine, and between saliva and urine, respectively. (b) Three, 8 and 7 age-linked compounds were found commonly between saliva and blood, between saliva and urine, and between blood and urine, respectively. (c) Ten salivary age-linked metabolites that did not overlap with blood or urine age-linked metabolites.
PCA of age-linked salivary compounds. (a) Taken together, all 99 identified metabolites cannot separate young (blue) and elderly subjects (red). (b) Oral aging may be detected by PCA of 21 age-linked metaoblites in a 2D manner (see text for explanation). Elderly subjects (no. 1–12, 14) are located in the negative domain of the x-axis, while young subjects (no. 15, 17–20, 22, 25–27) are located in the positive domain. However, four young subjects 16, 21, 23 and 24, appear in the negative domain, while elderly subject 13 is located in the positive domain. These positions parallel heatmap data (Fig. 4) which show metabolite levels for individual subjects. (c) Six metabolites can separate young and elderly subjects. (d) Even four metabolites largely separate them.
Human age-declined saliva metabolic markers determined by LC–MS

September 2021

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90 Reads

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26 Citations

Metabolites in human biofluids reflect individual physiological states influenced by various factors. Using liquid chromatography-mass spectrometry (LC–MS), we conducted non-targeted, non-invasive metabolomics using saliva of 27 healthy volunteers in Okinawa, comprising 13 young (30 ± 3 year) and 14 elderly (76 ± 4 year) subjects. Few studies have comprehensively identified age-dependent changes in salivary metabolites. Among 99 salivary metabolites, 21 were statistically age-related. All of the latter decline in abundance with advancing age, except ATP, which increased 1.96-fold in the elderly, possibly due to reduced ATP consumption. Fourteen age-linked and highly correlated compounds function in a metabolic network involving the pentose-phosphate pathway, glycolysis/gluconeogenesis, amino acids, and purines/pyrimidines nucleobases. The remaining seven less strongly correlated metabolites, include ATP, anti-oxidation-related glutathione disulfide, muscle-related acetyl-carnosine, N -methyl-histidine, creatinine, RNA-related dimethyl-xanthine and N -methyl-adenosine. In addition, glutamate and N -methyl-histidine are related to taste, so their decline suggests that the elderly lose some ability to taste. Reduced redox metabolism and muscle activity are suggested by changes in glutathione and acetyl-carnosine. These age-linked salivary metabolites together illuminate a metabolic network that reflects a decline of oral functions during human aging.


Figure 1. The metabolomic study of sarcopenia. (A) Overview of the study protocol. All participants were clinically assessed, and their
Figure 2. Ten mitochondrial metabolites are diagnostic for sarcopenia. (A) Three short-chain carnitines and their derivatives
Figure 4. Heatmap analysis and PCA for sarcopenia. (A) Heatmap analysis of metabolites involved in sarcopenia (top panel), and SMI (bottom). The heat map shows Z-scores of peak areas from LC-MS analysis. (B) PCA plot of 19 elderly participants. 22 sarcopenia markers were analyzed.
Figure 5. Summary of 25 metabolites related to sarcopenia and 15 frailty markers. 15 frailty markers (blue box) and 22 sarcopenia markers (dark green box) are presented. There is no overlap among them. 10 metabolites are muscle mass-related markers (light green box). Seven of the 15 frailty markers were antioxidants; however, sarcopenia markers include no antioxidants. Seven metabolites (isovaleryl-carnitine, 2-oxoglutarate, cis-aconitate, creatinine, dimethyl-arginine, dimethyl-guanosine, and N1-methyl-histidine) are both sarcopenia and muscle mass-related markers. 21 metabolites in orange are kidney-related markers.
Reduced uremic metabolites are prominent feature of sarcopenia, distinct from antioxidative markers for frailty

September 2021

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91 Reads

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28 Citations

Aging

Due to global aging, frailty and sarcopenia are increasing. Sarcopenia is defined as loss of volume and strength of skeletal muscle in elderlies, while frailty involves multiple domains of aging-related dysfunction, impaired cognition, hypomobility, and decreased social activity. However, little is known about the metabolic basis of sarcopenia, either shared with or discrete from frailty. Here we analyzed comprehensive metabolomic data of human blood in relation to sarcopenia, previously collected from 19 elderly participants in our frailty study. Among 131 metabolites, we identified 22 sarcopenia markers, distinct from 15 frailty markers, mainly including antioxidants, although sarcopenia overlaps clinically with physical frailty. Notably, 21 metabolites that decline in sarcopenia or low SMI are uremic compounds that increase in kidney dysfunction. These comprise TCA cycle, urea cycle, nitrogen, and methylated metabolites. Sarcopenia markers imply a close link between muscle and kidney function, while frailty markers define a state vulnerable to oxidative stress.


Figure 3
List of 33 dementia markers
Whole blood metabolomics of dementia patients reveal classes of disease-linked metabolites

June 2021

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80 Reads

Dementia is caused by factors that damage neurons. We quantified small molecular markers in whole blood of dementia patients, using non-targeted liquid chromatography-mass spectroscopy (LC-MS). Thirty-three metabolites, classified into 5 groups (A-E), differed significantly in dementia patients, compared with healthy elderly subjects. Seven Group A metabolites present in plasma, including quinolinic acid, kynurenine, and indoxyl-sulfate, increased. Possibly they act as neurotoxins in the central nervous system (CNS). The remaining 26 compounds (Groups B-E) decreased, possibly causing a loss of support or protection of the brain in dementia. Six Group B metabolites, normally enriched in red blood cells (RBCs) of healthy subjects, all contain trimethylated ammonium moieties. These metabolites include ergothioneine and structurally related compounds have scarcely been investigated as dementia markers, validating the examination of RBC metabolites. Ergothioneine, a potent anti-oxidant, is significantly decreased in various cognition-related disorders, such as mild cognitive impairment and frailty. Group C compounds, also include some oxidoreductants and are normally abundant in RBCs (NADP ⁺ , glutathione, ATP, pantothenate, S-adenosyl-methionine, and gluconate). Their decreased levels in dementia patients may also contribute to depressed brain function. Groups D (12) contains plasma compounds, such as amino acids, glycerophosphocholine, dodecanoyl-carnitine, 2-hydroxybutyrate, which normally protect the brain, but their diminution in dementia may reduce that protection. Seven Group D compounds have been identified previously as dementia markers. Group B-E compounds may be critical to maintain the CNS by acting directly or indirectly. How RBC metabolites act in the CNS and why they diminish so significantly in dementia remain to be determined. Significance Statement Dementia is a slowly progressing, chronic, and usually irreversible decline in cognitive function. Mechanistic causes and definitive treatments remain elusive. Using comprehensive metabolomics, we identified 5 groups of metabolites (A-E), 21 of which are novel, possibly useful for diagnosis and therapy of forms of dementia, such as Alzheimer’s disease. Seven Group A compounds may act as neurotoxins, whereas Group B-E compounds may protect the CNS against oxidative stress, maintain energy reserves, supply nutrients and neuroprotective factors. Five metabolites, ergothioneine, S -methyl-ergothioneine, trimethyl-histidine, methionine, and tryptophan identified in this study overlap with those reported for frailty. Interventions for cognitive diseases involving these dementia metabolomic markers may be accomplished either by inhibiting Group A compounds or by supplementing Group B-E compounds in patients.



Dot plot profiles of 55 age‐linked urine compounds, which comprise 11 groups, in samples from 27 individuals are shown. Pale red and azure dots represent elderly and young subjects, respectively. Bars represent medians in each group. The peak abundance of compounds and the ratio of median value between elderly and young are shown in Table 1A and 1B. P‐values were obtained using the non‐parametric Mann Whitney U‐test. Fifty‐three of 55 compounds were more abundant in urine of young subjects, while two (myo‐inositol and GSSG) were more abundant among the elderly
Correlation network among age‐linked compounds. (A) Values indicate correlation coefficients between paired compounds. Highly correlated pairs of aging markers (r > 0.85) are indicated with red circles. The most highly correlated pairs are indicated by green (0.92) and red arrows (0.91). (B) Interrelated compounds form a network. Correlations (r > 0.90) are highlighted in yellow. Creatinine was correlated with both groups (r = 0.74–0.84, shown in gray)
Heatmap representing urinary metabolic profiles of elderly and young subjects. Standardized data for each metabolite are shown for 27 subjects using a color matrix representing relative abundance data of 55 urinary aging markers. Numerical values indicate the t‐score, a kind of standardized score. The mean and standard deviation are 50 and 10, respectively. Color intensity of the cells reflects the t‐score. The mean and standard deviation are 50 and 10, respectively. Color intensity of the cells reflects the t‐score, indicating levels higher than average. T‐score <40 is white, low; 40 ~ 50 is thin red, slight low; 50–60 is moderate red, slight high; >60 is deep red, high. Elderly samples to the left were mostly white or pale red (lower level), except for myo‐inositol and GSSG, which were moderate or deep red (higher level)
PCA of 55 aging markers. (A) Thirteen young and 14 elderly subjects are shown in blue and red, respectively, with their subject numbers (indicated in the heatmap Figure 3). PC1 reflected the abundance of the compounds with strong correlation networks, such as pseudouridine and isoleucine (see Figure 2B and Figure S4). PC2 comprised metabolites that were not strongly correlated (glycerophosphocholine, S‐adenosyl‐homocysteine, etc.), but that were isolated from a strong correlation network. (B) PC1 score of each subject (X‐axis) is plotted versus subject age (Y‐axis). Subject 11 (F, age 81) is has a heatmap profile of a young person (Figure 3), while subject 15 (M, age 33) has an exceptionally elderly heatmap profile. The correlation coefficient is shown in the box
Scatter plots between GSSG and correlated compounds or age. (A) Ten metabolites with the relatively high correlations with GSSG are listed. Scatter plot of the peak abundance (×10⁶ AU) between GSSG and N‐acetyl aspartate (B), N‐methyl guanosine (C), dimethyl guanosine (D), pseudouridine (E), and the age of the subject (F). Dots for young and elderly subjects are blue and red, respectively
Aging markers in human urine: A comprehensive, non‐targeted LC‐MS study

October 2020

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57 Reads

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14 Citations

Metabolites in human biofluids document the physiological status of individuals. We conducted comprehensive, non‐targeted, non‐invasive metabolomic analysis of urine from 27 healthy human subjects, comprising 13 young adults (30 ± 3 years) and 14 seniors (76 ± 4 years). Quantitative analysis of 99 metabolites revealed 55 that displayed significant differences in abundance between the two groups. Forty‐four did not show a statistically significant relationship with age. These include 13 standard amino acids, 5 methylated, 4 acetylated, and 9 other amino acids, 6 nucleosides, nucleobases, and derivatives, 4 sugar derivatives, 5 sugar phosphates, 4 carnitines, 2 hydroxybutyrates, 1 choline, and 1 ethanolamine derivative, and glutathione disulfide. Abundances of 53 compounds decreased, while 2 (glutathione disulfide, myo‐inositol) increased in elderly people. The great majority of age‐linked markers were highly correlated with creatinine. In contrast, 44 other urinary metabolites, including urate, carnitine, hippurate, and betaine, were not age‐linked, neither declining nor increasing in elderly subjects. As metabolite profiles of urine and blood are quite different, age‐related information in urine offers additional valuable insights into aging mechanisms of endocrine system. Correlation analysis of urinary metabolites revealed distinctly inter‐related groups of compounds.


Well-established markers for fasting. After exhaustion of glycogen storage by fasting, lipids in human liver and white adipose tissues (WAT) are used as alternative energy sources. During fasting, 3-hydroxybutyrate (3-HB) is one of the most prominently increased metabolites (over 25-fold), which is generated from acetoacetic acid. Traversing the blood–brain barrier (BBB) via the monocarboxylate transporter (MCT), 3-HB is transported into brain, where fatty acids cannot be used for energy generation. Next, branched chain amino acids (BCAAs) are mainly released from muscles, followed by uptake into the TCA pathway, or lipogenesis in liver. Third, elevated acylcarnitines facilitate lipid transport into mitochondria. Abbreviations: HBD (α-Hydroxybutyric acid dehydrogenase), SCOT (succinyl-CoA:3-oxo-acid CoA transferase), Th (mitochondrial thiolase), mCPT1 (mitochondrial Carnitine palmitoyltransferase I).
Forty-four metabolites that increase during fasting include antioxidants, organic acids and signalling-related compounds. Non-targeted comprehensive metabolomics of whole blood detected increases of one-third (44) of metabolites identified during 58 h of fasting. In addition to metabolites for energy production, antioxidative metabolites were identified as fasting markers, which may combat oxidative stress resulting from enhanced mitochondrial activity. Moreover, signalling metabolites would contribute for remodelling of metabolic homeostasis during fasting. See the text for details. Abbreviations: ET; ergothioneine, OA; ophthalmic acid, PPP; pentose phosphate pathway, 3-HB; 3-hydroxybutyrate and 2-OG; 2-oxoglutarate.
Metabolomics of human fasting: new insights about old questions

September 2020

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317 Reads

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26 Citations

Since ancient days, human fasting has been performed for religious or political reasons. More recently, fasting has been employed as an effective therapy for weight reduction by obese people, and numerous studies have investigated the physiology of fasting by obese subjects. Well-established fasting markers (butyrates, BCAAs and carnitines) were considered essential energy substitutes after glycogen storage depletion. However, a recently developed metabolomic approach has unravelled previously unappreciated aspects of fasting. Surprisingly, one-third (44) of 120 metabolites investigated increase during 58 h of fasting, including antioxidative metabolites (carnosine, ophthalmic acid, ergothioneine and urates) and metabolites of entire pathways, such as the pentose phosphate pathway. Signalling metabolites (3-hydroxybutyrate and 2-oxoglutarate) and purines/pyrimidines may also serve as transcriptional modulators. Thus, prolonged fasting activates both global catabolism and anabolism, reprogramming metabolic homeostasis.


Citations (13)


... Both vegan and lacto-ovo diets are associated with a lower risk for DM development [28]. In obese individuals, protein and lipid catabolism levels are greater than in nonobese individuals [29]. The quality of a vegetarian diet influences the healthy phenotype of obese individuals [18]. ...

Reference:

Plant-based diet mitigated the risk of chronic kidney disease in overweight individuals
Markers for obese and non-obese Type 2 diabetes identified using whole blood metabolomics

... This interaction might also account for the neuroprotective effects of ERT observed in various in vitro and in vivo models. Regardless of the causative relationship between ERT reduction and disease onset, diminished circulating concentrations of ERT have been observed in individuals with cognitive impairment, Parkinson's disease, and frailty [25,56]. Furthermore, both ERT and its metabolite S-methyl-ERT have been shown to be lower in patients with dementia when compared to healthy older subjects [24,57]. ...

Decline of ergothioneine in frailty and cognition impairment
  • Citing Article
  • January 2022

... Case-control studies investigating metabolite levels in blood (plasma/serum) consisted of patients with AD dementia (n = 36 [5,[21][22][23][24][25][26]46,52,56,[59][60][61]64,), vascular dementia (n = 2 [52,64]), Lewy body dementia (n = 1 [91]), frontotemporal dementia (n = 4 [52,68,91,92]), all type dementia (n = 5 [69,[93][94][95][96]), MCI and AD dementia combined (n = 2 [97,98]), MCI (n = 14 [23][24][25]46,52,56,69,72,75,90,[99][100][101]), and post-stroke cognitive impairment (n = 3 [50,102,103]) (Tables 2 and S3). ...

Whole-blood metabolomics of dementia patients reveal classes of disease-linked metabolites

Proceedings of the National Academy of Sciences

... More than half of the plasma metabolites, particularly those involved in sphingolipid metabolism, were found to vary depending on age and sex (11). Age-related metabolomic changes in saliva are expected to be more complex, influenced by the functions mentioned above and many functional changes in the oral cavity, such as upregulation of chronic inflammation, changes in oral bacteria, and decreased salivary secretion (12)(13)(14). Although salivary amino acids have been well-profiled for individual parameters such as caries (15,16), periodontal disease (17,18), cancers (19), and aging (20), integrated analysis of amino acids and other metabolites should be conducted to obtain the holistic view of the salivary characteristics. ...

Human age-declined saliva metabolic markers determined by LC–MS

... In patients with sarcopenia there is a decrease in several metabolites including urea cycle metabolites, serum creatinine and creatinine kinase (39). According to Peng et al., a lower Blood urea nitrogen and Creatinine ratio (BUN/Cr) ratio was associated with an increased risk of both total stroke and ischemic stroke (37). ...

Reduced uremic metabolites are prominent feature of sarcopenia, distinct from antioxidative markers for frailty

Aging

... Because perturbations in metabolic pathways can be one of the first measurable alteration before disease manifestations, metabolomics can be used to characterize the dynamic biological aging processes. Previous aging-related metabolomic studies of various biofluids, such as blood samples (serum or plasma), urine, and saliva, obtained from model organisms and humans demonstrated that aging-related metabolites are mostly associated with carbohydrates, lipids, amino acids, DNA repair, and redox metabolism [9][10][11]. For example, a plasma-based metabolomics analysis of the aging process showed that ceramide, fatty acids, methionine, and nitric oxide pathways are associated with healthspan in healthy adults [12]. ...

Aging markers in human urine: A comprehensive, non‐targeted LC‐MS study

... That is, RDIF resulted in the upregulation of the pentose phosphate pathway in diabetic individuals. In a different study, it was also found that metabolites of the pentose phosphate pathway exhibited an increase during a 58-hour fasting period [48]. T2DM is primarily characterized by impaired insulin secretion. ...

Metabolomics of human fasting: new insights about old questions

... Scientific Reports | (2025) 15:14688 speed 43 Tryptophan levels are lower with frailty and correlated with MoCA score, 44 lower in people with mild cognitive impairment (MCI) 45 and later stages of AD pathology, 46 and are implicated in Aβ biochemistry and resultant toxicity 47 In the context of T2D, tryptophan levels are observed to be lower in diabetics 48 These associations follow the sequela of T2D increasing the risk for cognitive impairment and AD. Among the novel associations identified in EA discovery samples, the partially characterized metabolite X-21448 was positively associated with RAVLT Delayed Recall, DSC, and 3MSE. ...

Frailty markers comprise blood metabolites involved in antioxidation, cognition, and mobility

Proceedings of the National Academy of Sciences

... Two metabolites, malonic acid, and acetylcarnitine, increased compared to the CR intervention. Several other investigators have noted the increase in acetylcarnitine via fasting protocols 43,44 . This increase is consistent with free fatty acid mobilization and increased transportation of these fatty acids via carnitine acylation into the mitochondria for fatty acid oxidation. ...

Diverse Metabolic Reactions Activated During 58-hr Fasting are Revealed by Non-Targeted Metabolomic Analysis of Human Blood
  • Citing Article
  • January 2018

SSRN Electronic Journal

... For fasting subjects, it was shown by Rothman et al. using 13 C NMR that gluconeogenesis accounts for a substantial fraction of total blood glucose during the first 22 h of a fast (Rothman et al., 1991). Likewise, Teruya et al. showed that during fasting, various non-carbohydrate metabolites such as lipids and branched chain amino acids (BCAAs) (Teruya et al., 2019) are used as additional energy sources leading to a substantial increase in blood ketone bodies such as β-hydroxybutyrate and acetoacetate (Nicholson et al., 1984). As a result, samples collected from fasted individuals will tend to have higher levels of ketone bodies along with lower levels of glucose, lipids and BCAAs than those samples collected from individuals who have just consumed a meal (Bermingham et al., 2023;Shrestha et al., 2017). ...

Diverse metabolic reactions activated during 58-hr fasting are revealed by non-targeted metabolomic analysis of human blood