Capillary electrophoresis-mass spectrometry-based metabolome analysis of serum and saliva from neurodegenerative dementia patients

DMNAG: Prediction of disease-metabolite associations based on Neighborhood Aggregation Graph Transformer

The metabolic level within an organism typically reflects its health status. Studying the relationship between human diseases and metabolites helps enhance medical professionals' ability for early disease diagnosis and risk prediction. However, traditional biological experimental methods often require substantial resources and manpower, and there is still room for improvement in the performance of existing predictive models. To tackle these, we propose a novel method based on the Neighborhood Aggregation Graph Transformer (NAGphormer) to predict potential associations between diseases and metabolites (DMNAG), aiming to provide guidance for biological experiments and improve experimental efficiency. First, we calculated the Gaussian kernel similarity of diseases and the physicochemical similarity of metabolites, and combined them with known associations to construct a bipartite heterogeneous network. We then calculated the semantic similarity of diseases and the Mol2vec similarity of metabolites, using them respectively as the similarity feature vectors for the disease nodes and metabolite nodes. Meanwhile, we calculate the positional information features of nodes and combine them with similarity features as the initial features of the nodes. Next, we input the bipartite heterogeneous network and node initial features into the Hop2Token module to capture multihop neighborhood information between nodes. Finally, we input the multi-hop features of nodes into the Transformer model for training and obtain the edge prediction probabilities through the decoder. Through experiments, our model achieved an AUC value of 0.9801 and an AUPR value of 0.9818 in five-fold cross-validation. In case studies, most DMNAG-predicted associations have been validated, showcasing the model's reliability and superiority.

The Metabolic Profile of Plasma During Epileptogenesis in a Rat Model of Lithium-Pilocarpine-Induced Temporal Lobe Epilepsy

Temporal lobe epilepsy (TLE) arises mostly because of an initial injury. Certain stimuli can make a normal brain prone to repeated, spontaneous seizures via a process called epileptogenesis. This study examined the plasma metabolomics profile in rats with the induced TLE to identify feasible biomarkers that can distinguish progression of epileptogenesis in three different time points and reveal the underlying mechanisms of epileptogenesis. Status epilepticus (SE) was induced by repetitive intraperitoneal injections of low-dose lithium chloride-pilocarpine hydrocholoride. Blood samples were collected 48 h, 1 week, and 6 weeks after SE, respectively. Plasma metabolites were analyzed by nuclear magnetic resonance (NMR) spectrometry. Statistical analysis was performed using MetaboAnalyst 6.0. An orthogonal partial least squares discriminant analysis (OPLS-DA) model was employed to represent variations between the TLE model groups and respective controls. Volcano plot analysis was used to identify key features, applying a fold-change criterion of 1.5 and a t-test threshold of 0.05. 48 h after SE, dimethyl sulfone (DMSO2) and creatinine levels were decreased, whereas glycine and creatine levels were increased. The only metabolite that changed 1 week after SE was pyruvic acid, which was increased compared to its control level. Lactic acid, pyruvic acid, and succinic acid levels were increased 6 weeks after SE. The identified metabolites were especially related to the tricarboxylic acid cycle and glycine, serine, and threonine metabolism. The results illustrate that distinct plasma metabolites can function as phase-specific biomarkers in TLE and reveal new insights into the mechanisms underlying SE.

Nuclear adenine activates hnRNPA2B1 to enhance antibacterial innate immunity

Bacterial infection reprograms cellular metabolism and epigenetic status, but how the metabolic-epigenetic crosstalk empowers host antibacterial defense remains unclear. Here, we report that heterogeneous nuclear ribonucleoprotein A2B1 (hnRNPA2B1) is a sensor for metabolite adenine to launch an antimicrobial innate response through increasing Il1b transcription. Myeloid cell-specific Hnrnpa2b1-cKO mice are more susceptible to bacterial infection, while interleukin 1 beta (IL-1β) supplementation rescues the phenotype. Through a large-scale metabolites-hnRNPA2B1 interaction screen, we reveal that adenine directly binds and activates hnRNPA2B1 to mediate innate antibacterial response. Mechanistically, adenine directly recruits hnRNPA2B1 to Il1b enhancers, and hnRNPA2B1 increases Il1b enhancer chromatin accessibility through binding and recruiting nucleolin and fat mass and obesity-associated protein (FTO) to mediate Il1b enhancer DNA N6-methyladenosine (6mA) demethylation. Furthermore, bacterial infection elevates nuclear adenine at the early stage of infection, and in vivo adenine administration protects mice from death upon bacterial infection through the hnRNPA2B1-IL-1β circuit. Our findings offer new insights into metabolic-epigenetic crosstalk relevant to antibacterial innate immunity and indicate potential approaches for treating bacterial infections.

Guidelines for the standardization of pre-analytical variables for salivary biomarker studies in Alzheimer's disease research: An updated review and consensus of the Salivary Biomarkers for Dementia Research Working Group

There is a pressing need for accessible biomarkers with high diagnostic accuracy for Alzheimer's disease (AD) diagnosis to facilitate widespread screening, particularly in underserved groups. Saliva is an emerging specimen for measuring AD biomarkers, with distinct contexts of use that could complement blood and cerebrospinal fluid and detect various analytes. An interdisciplinary, international group of AD and related dementias (ADRD) researchers convened and performed a narrative review of published studies on salivary AD biomarkers. We critically appraised the current state of the literature, examining both consistencies and discrepancies in existing pre-analytical variables and methodologies. We discussed how various pre-analytical variables could influence the detection and quantification of salivary biomarkers, showed technologies available to standardize collection procedures, and proposed a standardized pre-analytical protocol to guide future studies on salivary AD biomarker examinations. We identified potential contexts of use, gaps, and priorities and proposed future research directions. HIGHLIGHTS: Given its non-invasive nature, wider accessibility, and cultural acceptability, particularly in low-resourced settings, saliva is a biofluid complementary to blood and CSF. Current salivary AD biomarker studies do not control for many confounding pre-analytical variables during the sampling process, potentially leading to inaccurate salivary biomarker readings and conclusions, contributing to conflicting findings. Reviewing the current literature, including the consistencies and non-consistencies observed in the existing parameters and methodologies, discussing how they can affect salivary AD biomarker detection and quantification. Proposing a standardized salivary pre-analytical protocol, identifying the gaps and prioritizations needed to move this area forward, proposing future directions and potential contexts of use.

Speciation of Potentially Carcinogenic Trace Nickel(II) Ion Levels in Human Saliva: A Sequential Metabolomics-Facilitated High-Field 1H NMR Investigation

Introduction/Objectives: Since the biological activities and toxicities of 'foreign' and/or excess levels of metal ions are predominantly determined by their precise molecular nature, here we have employed high-resolution 1H NMR analysis to explore the 'speciation' of paramagnetic Ni(II) ions in human saliva, a potentially rich source of biomolecular Ni(II)-complexants/chelators. These studies are of relevance to the in vivo corrosion of nickel-containing metal alloy dental prostheses (NiC-MADPs) in addition to the dietary or adverse toxicological intake of Ni(II) ions by humans. Methods: Unstimulated whole-mouth human saliva samples were obtained from n = 12 pre-fasted (≥8 h) healthy participants, and clear whole-mouth salivary supernatants (WMSSs) were obtained from these via centrifugation. Microlitre aliquots of stock aqueous Ni(II) solutions were sequentially titrated into WMSS samples via micropipette. Any possible added concentration-dependent Ni(II)-mediated pH changes therein were experimentally controlled. 1H NMR spectra were acquired on a JEOL JNM-ECZ600R/S1 spectrometer. Results: Univariate and multivariate (MV) metabolomics and MV clustering analyses were conducted in a sequential stepwise manner in order to follow the differential effects of increasing concentrations of added Ni(II). The results acquired showed that important Ni(II)-responsive biomolecules could be clustered into distinguishable patterns on the basis of added concentration-dependent responses of their resonance intensities and line widths. At low added concentrations (71 µmol/L), low-WMSS-level N-donor amino acids (especially histidine) and amines with relatively high stability constants for this paramagnetic metal ion were the most responsive (severe resonance broadenings were observed). However, at higher Ni(II) concentrations (140-670 µmol/L), weaker carboxylate O-donor ligands such as lactate, formate, succinate, and acetate were featured as major Ni(II) ligands, a consequence of their much higher WMSS concentrations, which were sufficient for them to compete for these higher Ni(II) availabilities. From these experiments, the metabolites most affected were found to be histidine ≈ methylamines > taurine ≈ lactate ≈ succinate > formate > acetate ≈ ethanol ≈ glycine ≈ N-acetylneuraminate, although they predominantly comprised carboxylato oxygen donor ligands/chelators at the higher added Ni(II) levels. Removal of the interfering effects arising from the differential biomolecular compositions of the WMSS samples collected from different participants and those from the effects exerted by a first-order interaction effect substantially enhanced the statistical significance of the differences observed between the added Ni(II) levels. The addition of EDTA to Ni(II)-treated WMSS samples successfully reversed these resonance modifications, an observation confirming the transfer of Ni(II) from the above endogenous complexants to this exogenous chelator to form the highly stable diamagnetic octahedral [Ni(II)-EDTA] complex (Kstab = 1.0 × 1019 M-1). Conclusions: The results acquired demonstrated the value of linking advanced experimental design and multivariate metabolomics/statistical analysis techniques to 1H NMR analysis for such speciation studies. These provided valuable molecular information regarding the identities of Ni(II) complexes in human saliva, which is relevant to trace metal ion speciation and toxicology, the in vivo corrosion of NiC-MADPs, and the molecular fate of ingested Ni(II) ions in this biofluid. The carcinogenic potential of these low-molecular-mass Ni(II) complexes is discussed.

Saliva Proteome, Metabolome and Microbiome Signatures for Detection of Alzheimer's Disease

Background: As the burden of Alzheimer's disease (AD) escalates with an ageing population, the demand for early and accessible diagnostic methods becomes increasingly urgent. Saliva, with its non-invasive and cost-effective nature, presents a promising alternative to cerebrospinal fluid and plasma for biomarker discovery. Methods: In this study, we conducted a comprehensive multi-omics analysis of saliva samples (n = 20 mild cognitive impairment (MCI), n = 20 Alzheimer's disease and age- and n = 40 gender-matched cognitively normal individuals), from the South Australian Neurodegenerative Disease (SAND) cohort, integrating proteomics, metabolomics, and microbiome data with plasma measurements, including pTau181. Results: Among the most promising findings, the protein Stratifin emerged as a top candidate, showing a strong negative correlation with plasma pTau181 (r = -0.49, p < 0.001) and achieving an AUC of 0.95 in distinguishing AD and MCI combined from controls. In the metabolomics analysis, 3-chlorotyrosine and L-tyrosine exhibited high correlations with disease severity progression, with AUCs of 0.93 and 0.96, respectively. Pathway analysis revealed significant alterations in vitamin B12 metabolism, with Transcobalamin-1 levels decreasing in saliva as AD progressed despite an increase in serum vitamin B12 levels (p = 0.008). Microbiome analysis identified shifts in bacterial composition, with a microbiome cluster containing species such as Lautropia mirabilis showing a significant decrease in abundance in MCI and AD samples. The overall findings were reinforced by weighted correlation network analysis, which identified key hubs and enriched pathways associated with AD. Conclusions: Collectively, these data highlight the potential of saliva as a powerful medium for early AD diagnosis, offering a practical solution for large-scale screening and monitoring.

Aggregation-Induced Emission Luminogen: Role in Biopsy for Precision Medicine

Biopsy, including tissue and liquid biopsy, offers comprehensive and real-time physiological and pathological information for disease detection, diagnosis, and monitoring. Fluorescent probes are frequently selected to obtain adequate information on pathological processes in a rapid and minimally invasive manner based on their advantages for biopsy. However, conventional fluorescent probes have been found to show aggregation-caused quenching (ACQ) properties, impeding greater progresses in this area. Since the discovery of aggregation-induced emission luminogen (AIEgen) have promoted rapid advancements in molecular bionanomaterials owing to their unique properties, including high quantum yield (QY) and signal-to-noise ratio (SNR), etc. This review seeks to present the latest advances in AIEgen-based biofluorescent probes for biopsy in real or artificial samples, and also the key properties of these AIE probes. This review is divided into: (i) tissue biopsy based on smart AIEgens, (ii) blood sample biopsy based on smart AIEgens, (iii) urine sample biopsy based on smart AIEgens, (iv) saliva sample biopsy based on smart AIEgens, (v) biopsy of other liquid samples based on smart AIEgens, and (vi) perspectives and conclusion. This review could provide additional guidance to motivate interest and bolster more innovative ideas for further exploring the applications of various smart AIEgens in precision medicine.

Highly sensitive and accurate measurement of underivatized phosphoenolpyruvate in plasma and serum via EDTA-facilitated hydrophilic interaction liquid chromatography-tandem mass spectrometry

Phosphoenolpyruvate (PEP) is an essential intermediate metabolite that is involved in various vital biochemical reactions. However, achieving the direct and accurate quantification of PEP in plasma or serum poses a significant challenge owing to its strong polarity and metal affinity. In this study, a sensitive method for the direct determination of PEP in plasma and serum based on ethylenediaminetetraacetic acid (EDTA)-facilitated hydrophilic interaction liquid chromatography-tandem mass spectrometry was developed. Superior chromatographic retention and peak shapes were achieved using a zwitterionic stationary-phase HILIC column with a metal-inert inner surface. Efficient dechelation of PEP-metal complexes in serum/plasma samples was achieved through the introduction of EDTA, resulting in a significant enhancement of the PEP signal. A PEP isotopically labelled standard was employed as a surrogate analyte for the determination of endogenous PEP, and validation assessments proved the sensitivity, selectivity, and reproducibility of this method. The method was applied to the comparative quantification of PEP in plasma and serum samples from mice and rats, as well as in HepG2 cells, HEK293T cells, and erythrocytes; the results confirmed its applicability in PEP-related biomedical research. The developed method can quantify PEP in diverse biological matrices, providing a feasible opportunity to investigate the role of PEP in relevant biomedical research.

The Potential of Metabolomics to Find Proper Biomarkers for Addressing the Neuroprotective Efficacy of Drugs Aimed at Delaying Parkinson's and Alzheimer's Disease Progression

The first objective is to highlight the lack of tools to measure whether a given intervention affords neuroprotection in patients with Alzheimer's or Parkinson's diseases. A second aim is to present the primary outcome measures used in clinical trials in cohorts of patients with neurodegenerative diseases. The final aim is to discuss whether metabolomics using body fluids may lead to the discovery of biomarkers of neuroprotection. Information on the primary outcome measures in clinical trials related to Alzheimer's and Parkinson's disease registered since 2018 was collected. We analysed the type of measures selected to assess efficacy, not in terms of neuroprotection since, as stated in the aims, there is not yet any marker of neuroprotection. Proteomic approaches using plasma or CSF have been proposed. PET could estimate the extent of lesions, but disease progression does not necessarily correlate with a change in tracer uptake. We propose some alternatives based on considering the metabolome. A new opportunity opens with metabolomics because there have been impressive technological advances that allow the detection, among others, of metabolites related to mitochondrial function and mitochondrial structure in serum and/or cerebrospinal fluid; some of the differentially concentrated metabolites can become reliable biomarkers of neuroprotection.

Metabolomics of Benzene Exposure and Development of Biomarkers for Exposure Hazard Assessment

Benzene, a common industrial solvent, poses significant health risks including poisoning and hematopoietic diseases. However, its precise toxicity mechanisms remain unclear. To assess the health impact of prolonged benzene exposure through metabolomic analyses of exposed workers and benzene-poisoned mice, aiming to identify biomarkers and minimize occupational hazards. This study compared 18 benzene-exposed workers with 18 non-exposed workers, matching for age, lifestyle, and BMI. The metabolites in the workers' samples were analyzed using ultra-high-performance liquid chromatography and mass spectrometry. A larger study included 118 exposed and 158 non-exposed workers, incorporating surveys and routine blood and urine tests with differential metabolites targeted via an enzyme-linked immunosorbent assay. The animal studies consisted of two 15- and 60-day benzene staining and control experiments on 28 C57BL/6J mice, followed by sample collection and organ analysis. The data analysis employed eXtensible Computational Mass Spectrometry (XCMS), Python, MetaboAnalyst 6.0, and SPSS24.0. The exposed workers exhibited altered metabolites indicating external benzene exposure, lower glucose levels, and changes in white blood cell counts and urinary ketone bodies. The plasma metabolomics revealed disturbances in energy and lipid metabolism. The benzene-exposed mice displayed reduced weight gain, behavioral changes, and organ damage. Oxidative stress and abnormal purine and lipid metabolism were observed in both the long-term benzene-exposed workers and benzene-exposed mice. Metabolic markers for the early detection of benzene exposure hazards were identified, underscoring the need to mitigate occupational risks.

Sex-specific metabolic signatures in methamphetamine addicts

Methamphetamine (METH) is a commonly abused addictive psychostimulant, and METH-induced neurotoxic and behavioural deficits are in a sex-specific manner. However, there is lack of biomarkers to evaluate METH addiction in clinical practice, especially for gender differences. We utilized ultra-high-performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS) to detect the serum metabolomics in METH addicts and controls, specially exploring the sex-specific metabolic alterations by METH abuse. We found that many differently expressed metabolites in METH addicts related to metabolisms of amino acid, energy, vitamin and neurological disorders. Further, METH abuse caused different patterns of metabolomics in a sex-specific manner. As to amino acid metabolism, L-phenylalanine, L-tryptophan and L-histidine in serum of male addicts and betaine in serum of female addicts were significantly changed by METH use. In addition, it seemed that purine and pyrimidine-related metabolites (e.g., xanthosine and adenosine 5'-monophosphate) in male and the metabolites of hormone (e.g., cortisol) and folate biosynthesis (e.g., 7,8-dihydrobiopterin and 4-hydroxybenzoic acid) in female were more sensitive to METH addiction. Our findings revealed that L-glutamic acid, L-aspartic acid, alpha-ketoglutarate acid and citric acid may be potential biomarkers for monitoring METH addiction in clinic. Considering sex-specific toxicity by METH, the metabolites of purine and pyrimidine metabolism in male and those of stress-related hormones in female may be used to facilitate the accurate diagnosis and treatment for METH addicts of different genders.

Untargeted Metabolomic Approach to Study the Impact of Aging on Salivary Metabolome in Women

Despite the growing interest in salivary metabolomics, few studies have investigated the impact of aging on the salivary metabolome. The alterations in metabolic pathways that occur with aging are likely to be observed in pathologies affecting older people and may interfere with the search for salivary biomarkers. It is therefore important to investigate the age-related changes occurring in the salivary metabolome. Using reversed phase liquid chromatography and hydrophilic interaction chromatography coupled to mass spectrometry used in positive and negative ionization modes, the salivary metabolic profiles of young (22 to 45 years old) and older people (55 to 92 years old) were obtained. Those profiles were compared with the use of XCMS online to highlight the under or overexpression of some metabolites with aging. A total of 60 metabolites showed differential expression with age. The identification of 26 of them was proposed by the METLIN database and, among them, 17 were validated by standard injections. Aging seemed to affect most of the main metabolic pathways (amino acid metabolism, Krebs cycle, fatty acid synthesis, and nucleic acid synthesis). Moreover, most of the metabolites that were over- or under-expressed with age in this study have already been identified as being potential biomarkers of diseases affecting older people, such as in Alzheimer's disease. Special attention should be paid in the search for biomarkers of pathologies affecting the elderly to differentiate age-related changes from disease-related changes.

Development of analytical methods to study the salivary metabolome: impact of the sampling

Advances in metabolomics have allowed the identification and characterization of saliva metabolites that can be used as biomarkers. However, discrepancies can be noted with the content of the same biomarker being increased or decreased for a given disease. Differences in the way saliva is collected, stored, and/or treated could cause these discrepancies. Indeed, there is no standardized method for saliva sampling and analysis. In this work, two chromatographic modes were used, i.e., RP-LC and HILIC both coupled to MS used in positive and negative ionization modes. The analytical conditions were optimized with a mixture of 90 compounds naturally present in saliva, representative of the wide range of molecular mass and polarity of salivary metabolites and being described as having a differential expression in various pathologies. These four methods were applied to the analysis of saliva samples collected by spitting, aspiration, or Salivette® with or without prior rinsing of the mouth. Rinsing had an effect on some metabolite concentrations. As it can induce an additional parameter of variability to the sampling, it seems therefore preferable to use methods without rinsing while effects of these parameters on the metabolites are investigated. Saliva obtained by spitting and aspiration gave statistically equivalent results for 84% of the metabolites studied. Conversely, Salivette® gave different results since the majority of the metabolites chosen for the study were not quantified in the samples. The Salivette® does not seem therefore to be a suitable sampling method for an untargeted analysis of the salivary metabolome, unlike aspiration and spitting.

Dihuang-Yinzi Alleviates Cognition Deficits via Targeting Energy-Related Metabolism in an Alzheimer Mouse Model as Demonstrated by Integration of Metabolomics and Network Pharmacology

Energy metabolism disturbance and the consequent reactive oxygen species (ROS) overproduction play a key and pathogenic role in the onset and progression of Alzheimer’s disease (AD). Dihuang-Yinzi (DHYZ) is a traditional Chinese herbal prescription clinically applied to treat AD and other neurodegenerative diseases for a long time. However, the systematical metabolic mechanism of DHYZ against AD remains largely unclear. Here we aimed to explore the mechanism of DHYZ in the treatment of AD comprehensively in an in vivo metabolic context by performing metabolomics analysis coupled with network pharmacology study and experimental validation. The network pharmacology was applied to dig out the potential target of DHYZ against AD. The metabolomics analysis based on UPLC-HRMS was carried out to profile the urine of 2× Tg-AD mice treated with DHYZ. By integrating network pharmacology and metabolomics, we found DHYZ could ameliorate 4 key energy-related metabolic pathways, including glycerophospholipid metabolism, nicotinate/nicotinamide metabolism, glycolysis, and tricarboxylic acid cycle. Besides, we identified 5 potential anti-AD targets of DHYZ, including DAO, HIF1A, PARP1, ALDH3B2, and ACHE, and 14 key differential metabolites involved in the 4 key energy-related metabolic pathways. Furthermore, DHYZ depressed the mitochondrial dysfunction and the resultant ROS overproduction through ameliorating glycerophospholipid metabolism disturbance. Thereby DHYZ increased nicotinamide adenine dinucleotide (NAD⁺) content and promoted glycolysis and tricarboxylic acid (TCA) cycle, and consequently improved oxidative phosphorylation and energy metabolism. In the present study, we provided a novel, comprehensive and systematic insight into investigating the therapeutic efficacy of DHYZ against AD via ameliorating energy-related metabolism.

Blood metabolites predicting mild cognitive impairment in the study of Latinos-investigation of neurocognitive aging (HCHS/SOL)

INTRODUCTION

Blood metabolomics-based biomarkers may be useful to predict measures of neurocognitive aging.

METHODS

We tested the association between 707 blood metabolites measured in 1451 participants from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL), with mild cognitive impairment (MCI) and global cognitive change assessed 7 years later. We further used Lasso penalized regression to construct a metabolomics risk score (MRS) that predicts MCI, potentially identifying a different set of metabolites than those discovered in individual-metabolite analysis.

RESULTS

We identified 20 metabolites predicting prevalent MCI and/or global cognitive change. Six of them were novel and 14 were previously reported as associated with neurocognitive aging outcomes. The MCI MRS comprised 61 metabolites and improved prediction accuracy from 84% (minimally adjusted model) to 89% in the entire dataset and from 75% to 87% among apolipoprotein E ε4 carriers.

DISCUSSION

Blood metabolites may serve as biomarkers identifying individuals at risk for MCI among US Hispanics/Latinos.

Molecular Probes, Chemosensors, and Nanosensors for Optical Detection of Biorelevant Molecules and Ions in Aqueous Media and Biofluids

Synthetic molecular probes, chemosensors, and nanosensors used in combination with innovative assay protocols hold great potential for the development of robust, low-cost, and fast-responding sensors that are applicable in biofluids (urine, blood, and saliva). Particularly, the development of sensors for metabolites, neurotransmitters, drugs, and inorganic ions is highly desirable due to a lack of suitable biosensors. In addition, the monitoring and analysis of metabolic and signaling networks in cells and organisms by optical probes and chemosensors is becoming increasingly important in molecular biology and medicine. Thus, new perspectives for personalized diagnostics, theranostics, and biochemical/medical research will be unlocked when standing limitations of artificial binders and receptors are overcome. In this review, we survey synthetic sensing systems that have promising (future) application potential for the detection of small molecules, cations, and anions in aqueous media and biofluids. Special attention was given to sensing systems that provide a readily measurable optical signal through dynamic covalent chemistry, supramolecular host-guest interactions, or nanoparticles featuring plasmonic effects. This review shall also enable the reader to evaluate the current performance of molecular probes, chemosensors, and nanosensors in terms of sensitivity and selectivity with respect to practical requirement, and thereby inspiring new ideas for the development of further advanced systems.

Which Role Plays 2-Hydroxybutyric Acid on Insulin Resistance?

Type 2 Diabetes Mellitus (T2D) is defined as a chronic condition caused by beta cell loss and/or dysfunction and insulin resistance (IR). The discovering of novel biomarkers capable of identifying T2D and other metabolic disorders associated with IR in a timely and accurate way is critical. In this review, 2-hydroxybutyric acid (2HB) is presented as that upheaval biomarker with an unexplored potential ahead. Due to the activation of other metabolic pathways during IR, 2HB is synthesized as a coproduct of protein metabolism, being the progression of IR intrinsically related to the increasing of 2HB levels. Hence, the focus of this review will be on the 2HB metabolite and its involvement in glucose homeostasis. A literature review was conducted, which comprised an examination of publications from different databases that had been published over the previous ten years. A total of 19 articles fulfilled the intended set of criteria. The use of 2HB as an early indicator of IR was separated into subjects based on the number of analytes examined simultaneously. In terms of the association between 2HB and IR, it has been established that increasing 2HB levels can predict the development of IR. Thus, 2HB has demonstrated considerable promise as a clinical monitoring molecule, not only as an IR biomarker, but also for disease follow-up throughout IR treatment.

Identification of Possible Salivary Metabolic Biomarkers and Altered Metabolic Pathways in South American Patients Diagnosed with Oral Squamous Cell Carcinoma

Oral squamous cell carcinoma (OSCC) represents 90% of oral malignant neoplasms. The search for specific biomarkers for OSCC is a very active field of research contributing to establishing early diagnostic methods and unraveling underlying pathogenic mechanisms. In this work we investigated the salivary metabolites and the metabolic pathways of OSCC aiming find possible biomarkers. Salivary metabolites samples from 27 OSCC patients and 41 control individuals were compared through a gas chromatography coupled to a mass spectrometer (GC-MS) technique. Our results allowed identification of pathways of the malate-aspartate shuttle, the beta-alanine metabolism, and the Warburg effect. The possible salivary biomarkers were identified using the area under receiver-operating curve (AUC) criterion. Twenty-four metabolites were identified with AUC > 0.8. Using the threshold of AUC = 0.9 we find malic acid, maltose, protocatechuic acid, lactose, 2-ketoadipic, and catechol metabolites expressed. We notice that this is the first report of salivary metabolome in South American oral cancer patients, to the best of our knowledge. Our findings regarding these metabolic changes are important in discovering salivary biomarkers of OSCC patients. However, additional work needs to be performed considering larger populations to validate our results.

An elaborative NMR based plasma metabolomics study revealed metabolic derangements in patients with mild cognitive impairment: a study on north Indian population

Mild cognitive impairment (MCI) is transition phase between cognitive decline and dementia. The current study aims to investigate altered metabolic pattern in plasma of MCI for potential biomarkers. MCI (N = 50) and healthy controls (HC, N = 50) age group 55-75 years were screened based on Mini Mental State Examination Test (MMSE) and diffusion tensor imaging (DTI imaging). The MMSE score of MCI was significantly lower (25.74 ± 1.83) compared to healthy control subjects (29 ± 1). The MCI patients exhibit significant changes in white matter integrity in the right frontal lobe, right temporal lobe, left frontal lobe, forcep major, fornix, corpus callosum. Further, the plasma samples of twenty seven MCI patients (N = 27) and twenty HC subjects (N = 20; having no significant differences in any demographics) were analyzed using 1H NMR based metabolomics approach. Consistent with many previous reports, the levels of several plasma metabolites were found to be elevated in MCI patients compared to healthy controls. Further univariate and multivariate ROC curve analyses provided three plasma metabolites as a diagnostic panel of biomarker for MCI; which are lysine, glycine, and glutamine. Overall, the results of this study will help to improve the diagnostic and prognostic strategies of MCI in addition to improving our understanding about disease pathogenesis. We believe that the over-nutritional metabolic phenotype of MCI needs to be targeted for developing future dietary interventions so that the progression of MCI can be limited. Metabolic derangements associated with Mild Cognitive Impairment.

Potential Neuroregenerative and Neuroprotective Effects of Uridine/Choline-Enriched Multinutrient Dietary Intervention for Mild Cognitive Impairment: A Narrative Review

In mild cognitive impairment (MCI) due to Alzheimer disease (AD), also known as prodromal AD, there is evidence for a pathologic shortage of uridine, choline, and docosahexaenoic acid [DHA]), which are key nutrients needed by the brain. Preclinical and clinical evidence shows the importance of nutrient bioavailability to support the development and maintenance of brain structure and function in MCI and AD. Availability of key nutrients is limited in MCI, creating a distinct nutritional need for uridine, choline, and DHA. Evidence suggests that metabolic derangements associated with ageing and disease-related pathology can affect the body's ability to generate and utilize nutrients. This is reflected in lower levels of nutrients measured in the plasma and brains of individuals with MCI and AD dementia, and progressive loss of cognitive performance. The uridine shortage cannot be corrected by normal diet, making uridine a conditionally essential nutrient in affected individuals. It is also challenging to correct the choline shortfall through diet alone, because brain uptake from the plasma significantly decreases with ageing. There is no strong evidence to support the use of single-agent supplements in the management of MCI due to AD. As uridine and choline work synergistically with DHA to increase phosphatidylcholine formation, there is a compelling rationale to combine these nutrients. A multinutrient enriched with uridine, choline, and DHA developed to support brain function has been evaluated in randomized controlled trials covering a spectrum of dementia from MCI to moderate AD. A randomized controlled trial in subjects with prodromal AD showed that multinutrient intervention slowed brain atrophy and improved some measures of cognition. Based on the available clinical evidence, nutritional intervention should be considered as a part of the approach to the management of individuals with MCI due to AD, including adherence to a healthy, balanced diet, and consideration of evidence-based multinutrient supplements.

Aging-Related Metabolic Dysfunction in the Salivary Gland: A Review of the Literature

Aging-related salivary dysfunction commonly induces the poor oral health, including decreased saliva flow and dental caries. Although the clinical significance of the salivary glands is well-known, the complex metabolic pathways contributing to the aging-dysfunction process are only beginning to be uncovered. Here, we provide a comprehensive overview of the metabolic changes in aging-mediated salivary gland dysfunction as a key aspect of oral physiology. Several metabolic neuropeptides or hormones are involved in causing or contributing to salivary gland dysfunction, including hyposalivation and age-related diseases. Thus, aging-related metabolism holds promise for early diagnosis, increased choice of therapy and the identification of new metabolic pathways that could potentially be targeted in salivary gland dysfunction.

Cognitive Dysfunction in a Mouse Model of Cerebral Ischemia Influences Salivary Metabolomics

Vascular dementia, caused by cerebrovascular disease, is associated with cognitive impairment and reduced hippocampal metabolite levels. Specifically, cognitive impairment can be induced by decreased hippocampal brain-derived neurotrophic factor (BDNF) expression. The development of low or non-invasive biomarkers to characterize these diseases is an urgent task. Disturbance of metabolic pathways has been frequently observed in cognitive impairment, and salivary molecules also showed the potentials to reflect cognitive impairment. Therefore, we evaluated salivary metabolic profiles associated with altered hippocampal BDNF expression levels in a cerebral ischemia mouse model using metabolomic analyses. The effect of tacrine (a cholinesterase inhibitor) administration was also examined. The arteries of ICR mice were occluded with aneurysm clips to generate the cerebral ischemia model. Learning and memory performance was assessed using the elevated plus maze (EPM) test. Hippocampal and blood BDNF levels were quantified using an enzyme-linked immunosorbent assay. Glutamate decarboxylase 1 (GAD1) mRNA expression, is associated with cognitive impairment, was quantified by a real-time polymerase chain reaction. The EPM test revealed impaired spatial working memory in the cerebral ischemia mouse model; tacrine administration ameliorated this memory impairment. Cerebral ischemia suppressed GAD1 expression by decreasing hippocampal BDNF expression. In total, seven salivary metabolites, such as trimethylamine N-oxide and putrescine, were changed by cognitive impairment and tacrine administration. Our data suggest that salivary metabolite patterns were associated with cognitive function.

Mechanistic Insights into Alzheimer's Disease Unveiled through the Investigation of Disturbances in Central Metabolites and Metabolic Pathways

Hydrophilic metabolites are closely involved in multiple primary metabolic pathways and, consequently, play an essential role in the onset and progression of multifactorial human disorders, such as Alzheimer’s disease. This review article provides a comprehensive revision of the literature published on the use of mass spectrometry-based metabolomics platforms for approaching the central metabolome in Alzheimer’s disease research, including direct mass spectrometry, gas chromatography-mass spectrometry, hydrophilic interaction liquid chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Overall, mounting evidence points to profound disturbances that affect a multitude of central metabolic pathways, such as the energy-related metabolism, the urea cycle, the homeostasis of amino acids, fatty acids and nucleotides, neurotransmission, and others.

Salivary metabolite levels in perinatally HIV-infected youth with periodontal disease

INTRODUCTION

Salivary metabolite profiles are altered in adults with HIV compared to their uninfected counterparts. Less is known about youth with HIV and how oral disorders that commonly accompany HIV infection impact salivary metabolite levels.

OBJECTIVE

As part of the Adolescent Master Protocol multi-site cohort study of the Pediatric HIV/AIDS Cohort Study (PHACS) network we compared the salivary metabolome of youth with perinatally-acquired HIV (PHIV) and youth HIV-exposed, but uninfected (PHEU) and determined whether metabolites differ in PHIV versus PHEU.

METHODS

We used three complementary targeted and discovery-based liquid chromatography-tandem mass spectrometry (LC-MS/MS) workflows to characterize salivary metabolite levels in 20 PHIV and 20 PHEU youth with and without moderate periodontitis. We examined main effects associated with PHIV and periodontal disease, and the interaction between them.

RESULTS

We did not identify differences in salivary metabolite profiles that remained significant under stringent control for both multiple between-group comparisons and multiple metabolites. Levels of cadaverine, a known periodontitis-associated metabolite, were more abundant in individuals with periodontal disease with the difference being more pronounced in PHEU than PHIV. In the discovery-based dataset, we identified a total of 564 endogenous peptides in the metabolite extracts, showing that proteolytic processing and amino acid metabolism are important to consider in the context of HIV infection.

CONCLUSION

The salivary metabolite profiles of PHIV and PHEU youth were overall very similar. Individuals with periodontitis particularly among the PHEU youth had higher levels of cadaverine, suggesting that HIV infection, or its treatment, may influence the metabolism of oral bacteria.

Validation and Application of a Derivatization-Free RP-HPLC-DAD Method for the Determination of Low Molecular Weight Salivary Metabolites

Saliva is an interesting, non-conventional, valuable diagnostic fluid. It can be collected using standardized sampling device; thus, its sampling is easy and non-invasive, it contains a variety of organic metabolites that reflect blood composition. The aim of this study was to validate a user-friendly method for the simultaneous determination of low molecular weight metabolites in saliva. We have optimized and validated a high throughput, direct, low-cost reversed phase liquid chromatographic method with diode array detection method without any pre- or post-column derivatization. We indexed salivary biomolecules in 35 whole non-stimulated saliva samples collected in 8 individuals in different days, including organic acids and amino acids and other carbonyl compounds. Among these, 16 whole saliva samples were collected by a single individual over three weeks before, during and after treatment with antibiotic in order to investigate the dynamics of metabolites. The concentrations of the metabolites were compared with the literature data. The multianalyte method here proposed requires a minimal sample handling and it is cost-effectiveness as it makes possible to analyze a high number of samples with basic instrumentation. The identification and quantitation of salivary metabolites may allow the definition of potential biomarkers for non-invasive "personal monitoring" during drug treatments, work out, or life habits over time.

Salivary biomarkers for diagnosis of systemic diseases and malignant tumors. A systematic review

Background

Saliva evaluation could be a possible alternative to blood and/or tissue analyses, for researching specific molecules associated to the presence of systemic diseases and malignancies. The present systematic review has been designed in order to answer to the question “are there significant associations between specific salivary biomarkers and diagnosis of systemic diseases or malignancies?”.

Material and Methods

The Preferred Reporting Item for Systematic Reviews and Meta-analysis (PRISMA) statement was used to guide the review. The combinations of “saliva” and “systemic diseases” or “diagnosis” or “biomarkers” or “cancers” or “carcinoma” or “tumors”, were used to search Medline, Scopus and Web of Science databases. Endpoint of research has been set at May 2019. Studies were classified into 3 groups according to the type of disease investigated for diagnosis: 1) malignant tumors; 2) neurologic diseases and 3) inflammatory/metabolic/cardiovascular diseases. Assessment of quality has been assigned according to a series of questions proposed by the National Institute of Health. Level of evidence was assessed using the categories proposed in the Oxford Center for Evidence-Based medicine (CEMB) levels for diagnosis (2011).

Results

Seventy-nine studies met the inclusion and exclusion criteria. Fifty-one (64%) investigated malignant tumors, 14 (17.5%) neurologic and 14 (18.5%) inflammatory/cardiovascular/metabolic diseases. Among studies investigating malignant tumors, 12 (23.5%) were scored as “good” and 11 of these reported statistically significant associations between salivary molecules and pathology. Two and 5 studies were found to have a good quality, among those evaluating the association between salivary biomarkers and neurologic and inflammatory/metabolic/cardiovascular diseases, respectively.

Conclusions

The present systematic review confirms the existence of some “good” quality evidence to support the role of peculiar salivary biomarkers for diagnosis of systemic diseases (e.g. lung cancer and EGFR).

Key words:Salivary diagnostics, biomarkers, systemic diseases, malignant tumors, early diagnosis.

Serum and urine metabolomics reveal potential biomarkers of T2DM patients with nephropathy

BACKGROUND

Diabetes is a metabolic disease and is often accompanied by severe microvascular and macrovascular complications. A comprehensive understanding of its complex mechanisms can help prevent type 2 diabetes mellitus (T2DM) complications, such as diabetic nephropathy (DN).

METHODS

To reveal the systemic metabolic changes related to renal injury, clinical information of T2DM patients with or without nephropathy was collected, and it was found that serum urea levels of DN patients were significantly higher in T2DM patients without nephropathy. Further along the disease progression, the serum urea levels also gradually increased. We used gas chromatograph coupled with time-of-flight mass spectrometry (GC-TOFMS) metabolomics to analyze the serum and urine metabolites of T2DM patients with or without nephropathy to study the metabolic changes associated with the disease.

RESULTS

Finally, we identified 61 serum metabolites and 46 urine metabolites as potential biomarkers related to DN (P<0.05, VIP >1). In order to determine which metabolic pathways were major altered in DN, we summarized pathway analysis based on P values from their impact values and enrichment. There were 9 serum metabolic pathways and 12 urine metabolic pathways with significant differences in serum and urine metabolism, respectively.

CONCLUSIONS

This study emphasizes that GC-TOFMS-based metabolomics provides insight into the potential pathways in the pathogenesis and progression of DN.

Age and gender characteristics of the biochemical composition of saliva: Correlations with the composition of blood plasma

Background

Recently, the attention of researchers to the study of the properties of human saliva, as a material with unique properties and diagnostic capabilities, has increased.

Research objective

to study the connection of the biochemical composition of saliva and blood plasma in the norm, depending on gender and age.

Methods

107 volunteers took part in the study, including 46 female (37.2 ± 3.9 years old) and 61 male (36.1 ± 2.8 years old). In all samples of saliva and blood plasma, 16 biochemical parameters were determined, including mineral and protein composition, enzyme activity. Non-parametric statistical methods were used to process the data.

Results

It has been shown that it is difficult to establish an unambiguous relation between biochemical parameters of saliva and blood plasma. The calculation of the Spearman correlation coefficients showed that only 7 of the 16 parameters demonstrate the presence of a weak correlation between the content in saliva and plasma.

Conclusion

In general, the determination of the composition of saliva may have an independent diagnostic value; in this case, drawing a parallel with the composition of serum and blood plasma is not advisable. Nevertheless, the use of saliva in clinical laboratory diagnostics is associated with the need to establish criteria for the norm and pathology for each biochemical parameter.

Salivary Metabolomics: From Diagnostic Biomarker Discovery to Investigating Biological Function

Metabolomic profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, metabolomic analysis of saliva, the most readily-available human biofluid, has lagged. This review explores the history of saliva-based metabolomics and summarizes current knowledge of salivary metabolomics. Current applications of salivary metabolomics have largely focused on diagnostic biomarker discovery and the diagnostic value of the current literature base is explored. There is also a small, albeit promising, literature base concerning the use of salivary metabolomics in monitoring athletic performance. Functional roles of salivary metabolites remain largely unexplored. Areas of emerging knowledge include the role of oral host-microbiome interactions in shaping the salivary metabolite profile and the potential roles of salivary metabolites in oral physiology, e.g., in taste perception. Discussion of future research directions describes the need to begin acquiring a greater knowledge of the function of salivary metabolites, a current research direction in the field of the gut metabolome. The role of saliva as an easily obtainable, information-rich fluid that could complement other gastrointestinal fluids in the exploration of the gut metabolome is emphasized.

The Differences of Serum Metabolites Between Patients With Early-Stage Alzheimer's Disease and Mild Cognitive Impairment

Background: Mild cognitive impairment (MCI) is regarded as a transition phase between normal aging and Alzheimer's disease (AD). Identification of novel and non-invasive biomarkers that can distinguish AD at an early stage from MCI is warranted for therapeutic and support planning. The goal of this study was to identify the differences of serum metabolomic profiles between MCI and early-stage AD, which could be potential non-invasive biomarkers for early diagnosis of AD.

Methods: The subjects enrolled in the study were classified into two diagnostic groups: MCI (n = 40) and early-stage AD (n = 40). Targeted metabolomics analysis of serum samples was performed using the Biocrates Absolute-IDQ P180 kit. Targeted metabolic data were analyzed by TargetLynx, and MetIDQ software was applied to integrate the metabolites by automated calculation of metabolite concentrations.

Results: The datasets of targeted metabolite analysis were analyzed by the orthogonal-projection-to-latent-structure–discriminant-analysis (OPLS-DA) model. The OPLS-DA score plots demonstrated considerable separation between the MCI and early-stage AD patients. The levels of pimelylcarnitine, putrescine, SM (OH) C24:1, and SM C24:0 were significantly lower, whereas the levels of acetylornithine, methionine sulfoxide, and PC ae C44:3 were significantly higher in early-stage AD patients as compared with MCI patients. Receiver operating characteristic curve analysis of a combination of three lipid metabolites [SM (OH) C24:1, SM C24:0, and PC ae C44:3] showed an acceptable discrimination between the early-stage AD and MCI patients (area under the curve = 0.788).

Conclusions: Our results characterized the differences of serum metabolic profiles between MCI and early-stage AD patients. The positive findings from this study indicate that the minimally invasive method of blood sampling may help to identify patients with AD at an early stage from those with MCI.

Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders

Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the investigation of underlying mechanism of therapeutic strategies.

Metabolomics and Age-Related Macular Degeneration

Age-related macular degeneration (AMD) leads to irreversible visual loss, therefore, early intervention is desirable, but due to its multifactorial nature, diagnosis of early disease might be challenging. Identification of early markers for disease development and progression is key for disease diagnosis. Suitable biomarkers can potentially provide opportunities for clinical intervention at a stage of the disease when irreversible changes are yet to take place. One of the most metabolically active tissues in the human body is the retina, making the use of hypothesis-free techniques, like metabolomics, to measure molecular changes in AMD appealing. Indeed, there is increasing evidence that metabolic dysfunction has an important role in the development and progression of AMD. Therefore, metabolomics appears to be an appropriate platform to investigate disease-associated biomarkers. In this review, we explored what is known about metabolic changes in the retina, in conjunction with the emerging literature in AMD metabolomics research. Methods for metabolic biomarker identification in the eye have also been discussed, including the use of tears, vitreous, and aqueous humor, as well as imaging methods, like fluorescence lifetime imaging, that could be translated into a clinical diagnostic tool with molecular level resolution.

Qualitative and Quantitative Analysis of the Major Constituents in WLJ Herbal Tea Using Multiple Chromatographic Techniques

Quality control of Chinese herbal tea remains a challenge due to our poor knowledge of their complex chemical profile. This study aims to investigate the chemical composition of one of the best-selling and famous brand of beverage in China, Wanglaoji Herbal Tea (WLJHT), via a full component quantitative analysis. In this paper, a total of thirty-four representative constituents were identified or tentatively characterized using ultra-high performance liquid chromatography coupled with quadrupole tandem time-of-flight mass spectrometry (UPLC-Q-TOF-MS). Moreover, the quantitative analyses of fourteen constituents were performed by high performance liquid chromatography with a triple quadruple tandem mass spectrometry (HPLC-MS/MS) method and saccharide compositions of WLJHT were also quantitatively determined by high performance liquid chromatography (HPLC) with evaporative light scattering detector (ELSD) on a Hilic column, separately. Using multiple chromatographic techniques presented a good precision, sensitivity, repeatability and stability, and was successfully applied to analyze 16 batches of WLJHT samples. Therefore, it would be a reliable and useful approach for the quality control of WLJHT.

Blood levels of D-amino acid oxidase vs. D-amino acids in reflecting cognitive aging

Feasible peripheral biomarker for Alzheimer's disease (AD) is lacking. Dysregulation of N-methyl-D-aspartate (NMDA) receptor is implicated in the pathogenesis of AD. D-amino acid oxidase (DAO) and amino acids can regulate the NMDA receptor function. This study aimed to examine whether peripheral DAO and amino acids levels are characteristic of age-related cognitive decline. We enrolled 397 individuals (including amnestic mild cognitive impairment (MCI), mild AD, moderate to severe AD, and healthy elderly). DAO levels in the serum were measured using ELISA. Amino acids levels in serum were measured by high performance liquid chromatography. Severity of the cognitive deficits in subjects was assessed using Clinical Dementia Rating Scale (CDR). The DAO levels increased with the severity of the cognitive deficits. DAO levels were significantly associated with D-glutamate and D-serine levels. The Receiver Operating Characteristics analysis of DAO levels for AD patients vs. healthy controls determined the optimal cutoff value, 30.10, with high sensitivity (0.842) and specificity (0.889) (area under curve = 0.928). This is the first study indicating that the peripheral DAO levels may increase with age-related cognitive decline. The finding supports the hypofunction of NMDA receptor hypothesis in AD. Whether DAO could serve as a potential surrogate biomarker needs further studies.

Serum Metabolomic Profiles for Human Pancreatic Cancer Discrimination

This study evaluated the clinical use of serum metabolomics to discriminate malignant cancers including pancreatic cancer (PC) from malignant diseases, such as biliary tract cancer (BTC), intraductal papillary mucinous carcinoma (IPMC), and various benign pancreaticobiliary diseases. Capillary electrophoresis−mass spectrometry was used to analyze charged metabolites. We repeatedly analyzed serum samples (n = 41) of different storage durations to identify metabolites showing high quantitative reproducibility, and subsequently analyzed all samples (n = 140). Overall, 189 metabolites were quantified and 66 metabolites had a 20% coefficient of variation and, of these, 24 metabolites showed significant differences among control, benign, and malignant groups (p < 0.05; Steel–Dwass test). Four multiple logistic regression models (MLR) were developed and one MLR model clearly discriminated all disease patients from healthy controls with an area under receiver operating characteristic curve (AUC) of 0.970 (95% confidential interval (CI), 0.946–0.994, p < 0.0001). Another model to discriminate PC from BTC and IPMC yielded AUC = 0.831 (95% CI, 0.650–1.01, p = 0.0020) with higher accuracy compared with tumor markers including carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), pancreatic cancer-associated antigen (DUPAN2) and s-pancreas-1 antigen (SPAN1). Changes in metabolomic profiles might be used to screen for malignant cancers as well as to differentiate between PC and other malignant diseases.

D-Glutamate is metabolized in the heart mitochondria

_D-Amino acids are enantiomers of L-amino acids and have recently been recognized as biomarkers and bioactive substances in mammals, including humans. In the present study, we investigated functions of the novel mammalian mitochondrial protein 9030617O03Rik and showed decreased expression under conditions of heart failure. Genomic sequence analyses showed partial homology with a bacterial aspartate/glutamate/hydantoin racemase. Subsequent determinations of all free amino acid concentrations in 9030617O03Rik-deficient mice showed high accumulations of D-glutamate in heart tissues. This is the first time that a significant amount of D-glutamate was detected in mammalian tissue. Further analysis of D-glutamate metabolism indicated that 9030617O03Rik is a D-glutamate cyclase that converts D-glutamate to 5-oxo-D-proline. Hence, this protein is the first identified enzyme responsible for mammalian D-glutamate metabolism, as confirmed in cloning analyses. These findings suggest that D-glutamate and 5-oxo-D-proline have bioactivities in mammals through the metabolism by D-glutamate cyclase.

A sensitive single-enzyme assay system using the non-ribosomal peptide synthetase BpsA for measurement of L-glutamine in biological samples

The ability to rapidly, economically and accurately measure L-glutamine concentrations in biological samples is important for many areas of research, medicine or industry, however there is room for improvement on existing methods. We describe here how the enzyme BpsA, a single-module non-ribosomal peptide synthetase able to convert L-glutamine into the blue pigment indigoidine, can be used to accurately measure L-glutamine in biological samples. Although indigoidine has low solubility in aqueous solutions, meaning direct measurements of indigoidine synthesis do not reliably yield linear standard curves, we demonstrate that resolubilisation of the reaction end-products in DMSO overcomes this issue and that spontaneous reduction to colourless leuco-indigoidine occurs too slowly to interfere with assay accuracy. Our protocol is amenable to a 96-well microtitre format and can be used to measure L-glutamine in common bacterial and mammalian culture media, urine, and deproteinated plasma. We show that active BpsA can be prepared in high yield by expressing it in the apo-form to avoid the toxicity of indigoidine to Escherichia coli host cells, then activating it to the holo-form in cell lysates prior to purification; and that BpsA has a lengthy shelf-life, retaining >95% activity when stored at either −20 °C or 4 °C for 24 weeks.

Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules

PURPOSE

Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease.

CONCLUSIONS

Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research.

Serum Amino Acid Profiles in Normal Subjects and in Patients with or at Risk of Alzheimer Dementia

BACKGROUND/AIMS

Abnormalities in the plasma amino acid profile have been reported in Alzheimer disease (AD), but no data exist for the prodromal phase characterized by subjective memory complaint (SMC). It was our aim to understand if serum amino acid levels change along the continuum from normal to AD, and to identify possible diagnostic biomarkers.

METHODS

Serum levels of 15 amino acids and 2 organic acids were determined in 4 groups of participants - 29 with probable AD, 18 with mild cognitive impairment (MCI), 24 with SMC, and 46 cognitively healthy subjects (HS) - by electrospray tandem mass spectrometry.

RESULTS

Glutamate, aspartate, and phenylalanine progressively decreased, while citrulline, argi-ninosuccinate, and homocitrulline progressively increased, from HS over SMC and MCI to AD. The panel including these 6 amino acids and 4 ratios (glutamate/citrulline, citrulline/phenylalanine, leucine plus isoleucine/phenylalanine, and arginine/phenylalanine) discriminated AD from HS with about 96% accuracy. Other panels including 20 biomarkers discriminated SMC or MCI from AD or HS with an accuracy ranging from 88 to 75%.

CONCLUSION

Amino acids contribute to a characteristic metabotype during the progression of AD along the continuum from health to frank dementia, and their monitoring in elderly individuals might help to detect at-risk subjects.

Salivary biomarkers in cancer detection

Cancer is the second most common cause of death in the USA. Its symptoms are often not specific and absent, until the tumors have already metastasized. Therefore, there is an urgent demand for developing rapid, highly accurate and noninvasive tools for cancer screening, early detection, diagnostics, staging and prognostics. Saliva as a multi-constituent oral fluid comprises secretions from the major and minor salivary glands, extensively supplied by blood. Molecules such as DNAs, RNAs, proteins, metabolites, and microbiota, present in blood, could be also found in saliva. Recently, salivary diagnostics has drawn significant attention for the detection of specific biomarkers, since the sample collection and processing are simple, cost-effective, and precise and do not cause patient discomfort. Here, we review recent salivary candidate biomarkers for systemic cancers by dividing them according to their origin into: genomic, transcriptomic, proteomic, metabolomic and microbial types.

CE-MS for metabolomics: Developments and applications in the period 2014-2016

CE–MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE–MS approaches for metabolomics studies. In this paper, which is a follow‐up of a previous review paper covering the years 2012–2014 (Electrophoresis 2015, 36, 212–224), recent CE–MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE–MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE–MS is also demonstrated. Representative examples illustrate the applicability of CE–MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE–MS‐based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given.

Towards Personalized Intervention for Alzheimer's Disease

Alzheimer's disease (AD) remains to be a grand challenge for the international community despite over a century of exploration. A key factor likely accounting for such a situation is the vast heterogeneity in the disease etiology, which involves very complex and divergent pathways. Therefore, intervention strategies shall be tailored for subgroups of AD patients. Both demographic and in-depth information is needed for patient stratification. The demographic information includes primarily APOE genotype, age, gender, education, environmental exposure, life style, and medical history, whereas in-depth information stems from genome sequencing, brain imaging, peripheral biomarkers, and even functional assays on neurons derived from patient-specific induced pluripotent cells (iPSCs). Comprehensive information collection, better understanding of the disease mechanisms, and diversified strategies of drug development would help with more effective intervention in the foreseeable future.

Plasma Biomarkers for Monitoring Brain Pathophysiology in FMR1 Premutation Carriers

Premutation carriers have a 55–200 CGG expansion in the fragile X mental retardation 1 (FMR1) gene. Currently, 1.5 million individuals are affected in the United States, and carriers are at risk of developing the late-onset neurodegenerative disorder Fragile X-associated tremor ataxia syndrome (FXTAS). Limited efforts have been made to develop new methods for improved early patient monitoring, treatment response, and disease progression. To this end, plasma metabolomic phenotyping was obtained for 23 premutation carriers and 16 age- and sex-matched controls. Three biomarkers, phenylethylamine normalized by either aconitate or isocitrate and oleamide normalized by isocitrate, exhibited excellent model performance. The lower phenylethylamine and oleamide plasma levels in carriers may indicate, respectively, incipient nigrostriatal degeneration and higher incidence of substance abuse, anxiety and sleep disturbances. Higher levels of citrate, isocitrate, aconitate, and lactate may reflect deficits in both bioenergetics and neurotransmitter metabolism (Glu, GABA). This study lays important groundwork by defining the potential utility of plasma metabolic profiling to monitor brain pathophysiology in carriers before and during the progression of FXTAS, treatment efficacy and evaluation of side effects.

Assessment of Saliva as a Potential Biofluid for Biodosimetry: A Pilot Metabolomics Study in Mice

Metabolomic analysis of easily accessible biofluids has provided numerous biomarkers in urine and blood for biodosimetric purposes. In this pilot study we assessed saliva for its utility in biodosimetry using a mouse model. Mice were exposed to 0.5, 3 and 8 Gy total-body gamma irradiation and saliva was collected on day 1 and 7 postirradiation. Global metabolomic profiling was conducted through liquid chromatography mass spectrometry and metabolites were positively identified using tandem mass spectrometry. Multivariate data analysis revealed distinct metabolic profiles for all groups at day 1, whereas at day 7 the two lower dose profiles appeared to have minimal differences. Metabolites that were identified include amino acids and fatty acids, and intermediates of the nicotinate and nicotinamide metabolism. The specificity and sensitivity of the radiation signature, as expected, was higher for the 8 Gy dose at both time points, as determined through generation of receiver operating characteristic curves. To the best of our knowledge, this is the first metabolomics study in saliva of irradiated mice to demonstrate the utility of this biofluid as a potential matrix for identification of radiation and dose-specific biomarkers.

Noninvasive metabolic profiling for painless diagnosis of human diseases and disorders

Metabolic profiling provides a powerful diagnostic tool complementary to genomics and proteomics. The pain, discomfort and probable iatrogenic injury associated with invasive or minimally invasive diagnostic methods, render them unsuitable in terms of patient compliance and participation. Metabolic profiling of biomatrices like urine, breath, saliva, sweat and feces, which can be collected in a painless manner, could be used for noninvasive diagnosis. This review article covers the noninvasive metabolic profiling studies that have exhibited diagnostic potential for diseases and disorders. Their potential applications are evident in different forms of cancer, metabolic disorders, infectious diseases, neurodegenerative disorders, rheumatic diseases and pulmonary diseases. Large scale clinical validation of such diagnostic methods is necessary in future.

Salivary Markers for Periodontal and General Diseases

The determination of biomarkers in saliva is becoming an important part of laboratory diagnostics and the prediction of not only periodontal, but also other tissue and organ diseases. Biomarkers in saliva (e.g., enzymes, protein markers, or oxidative stress markers) can be used for activity determination and for periodontal disease prognosis. Saliva also contains many markers which can predict the risk of certain diseases (e.g., diabetes mellitus, cardiovascular, oncology, endocrinology, and psychiatric diseases). The study of salivary components proteomics clearly shows the relationship of periodontal diseases and diseases of distant systems, organs, or tissues.