Quantitative metabolomics of saliva using proton NMR spectroscopy in patients with Parkinson's disease and healthy controls

A systematic review of salivary biomarkers in Parkinson's disease

The search for reliable and easily accessible biomarkers in Parkinson's disease is receiving a growing emphasis, to detect neurodegeneration from the prodromal phase and to enforce disease-modifying therapies. Despite the need for non-invasively accessible biomarkers, the majority of the studies have pointed to cerebrospinal fluid or peripheral biopsies biomarkers, which require invasive collection procedures. Saliva represents an easily accessible biofluid and an incredibly wide source of molecular biomarkers. In the present study, after presenting the morphological and biological bases for looking at saliva in the search of biomarkers for Parkinson's disease, we systematically reviewed the results achieved so far in the saliva of different cohorts of Parkinson's disease patients. A comprehensive literature search on PubMed and SCOPUS led to the discovery of 289 articles. After screening and exclusion, 34 relevant articles were derived for systematic review. Alpha-synuclein, the histopathological hallmark of Parkinson's disease, has been the most investigated Parkinson's disease biomarker in saliva, with oligomeric alpha-synuclein consistently found increased in Parkinson's disease patients in comparison to healthy controls, while conflicting results have been reported regarding the levels of total alpha-synuclein and phosphorylated alpha-synuclein, and few studies described an increased oligomeric alpha-synuclein/total alpha-synuclein ratio in Parkinson's disease. Beyond alpha-synuclein, other biomarkers targeting different molecular pathways have been explored in the saliva of Parkinson's disease patients: total tau, phosphorylated tau, amyloid-β1-42 (pathological protein aggregation biomarkers); DJ-1, heme-oxygenase-1, metabolites (altered energy homeostasis biomarkers); MAPLC-3beta (aberrant proteostasis biomarker); cortisol, tumor necrosis factor-alpha (inflammation biomarkers); DNA methylation, miRNA (DNA/RNA defects biomarkers); acetylcholinesterase activity (synaptic and neuronal network dysfunction biomarkers); Raman spectra, proteome, and caffeine. Despite a few studies investigating biomarkers targeting molecular pathways different from alpha-synuclein in Parkinson's disease, these results should be replicated and observed in studies on larger cohorts, considering the potential role of these biomarkers in determining the molecular variance among Parkinson's disease subtypes. Although the need for standardization in sample collection and processing, salivary-based biomarkers studies have reported encouraging results, calling for large-scale longitudinal studies and multicentric assessments, given the great molecular potentials and the non-invasive accessibility of saliva.

Causal association between phenylalanine and Parkinson's disease: a two-sample bidirectional mendelian randomization study

Background

Research findings indicate a putative indirect or latent association between phenylalanine (Phe) and Parkinson's disease (PD). In this study, we aimed to analyze the causal relationship between Phe and PD by two sample Mendelian randomization (MR) analysis.

Methods

In this study, the PD-related dataset and Phe-related dataset were downloaded from Integrative Epidemiology U1nit (IEU) Open Genome-Wide Association Study (GWAS) database. Four algorithms (MR Egger, maximum likelihood, inverse variance weighting (IVW) and unweighted regression) were used to perform MR analysis. The sensitivity analysis (heterogeneity test, horizontal pleiotropy test and Leave-One-Out (LOO) analysis) was used to assess the reliability of MR analyses.

Results

In the forward MR analysis, Phe was a safety factor for PD (p-value < 0.05 and odds ratios (OR) < 1). The results of reverse MR analysis showed that there was no causal relationship between PD and Phe (p-value > 0.05). In addition, sensitivity analysis showed that MR analysis was reliable.

Conclusion

The results of this study revealed that Phe was a safety factor for PD, meaning that Phe reduced the risk of PD.

Identification of metabolites reproducibly associated with Parkinson's Disease via meta-analysis and computational modelling

Many studies have reported metabolomic analysis of different bio-specimens from Parkinson's disease (PD) patients. However, inconsistencies in reported metabolite concentration changes make it difficult to draw conclusions as to the role of metabolism in the occurrence or development of Parkinson's disease. We reviewed the literature on metabolomic analysis of PD patients. From 74 studies that passed quality control metrics, 928 metabolites were identified with significant changes in PD patients, but only 190 were replicated with the same changes in more than one study. Of these metabolites, 60 exclusively increased, such as 3-methoxytyrosine and glycine, 54 exclusively decreased, such as pantothenic acid and caffeine, and 76 inconsistently changed in concentration in PD versus control subjects, such as ornithine and tyrosine. A genome-scale metabolic model of PD and corresponding metabolic map linking most of the replicated metabolites enabled a better understanding of the dysfunctional pathways of PD and the prediction of additional potential metabolic markers from pathways with consistent metabolite changes to target in future studies.

Impaired gut barrier integrity and reduced colonic expression of free fatty acid receptors in patients with Parkinson's disease

BACKGROUND

Altered gut metabolites, especially short-chain fatty acids (SCFAs), in feces and plasma are observed in patients with Parkinson's disease (PD).

OBJECTIVE

We aimed to investigate the colonic expression of two SCFA receptors, free fatty acid receptor (FFAR)2 and FFAR3, and gut barrier integrity in patients with PD and correlations with clinical severity.

METHODS

In this retrospective study, colonic biopsy specimens were collected from 37 PD patients and 34 unaffected controls. Of this cohort, 31 participants (14 PD, 17 controls) underwent a series of colon biopsies. Colonic expression of FFAR2, FFAR3, and the tight junction marker ZO-1 were assayed by immunofluorescence staining. The You Only Look Once (version 8, YOLOv8) algorithm was used for automated detection and segmentation of immunostaining signal. PD motor function was assessed with the Movement Disorder Society (MDS)-Unified Parkinson's Disease Rating Scale (UPDRS), and constipation was assessed using Rome-IV criteria.

RESULTS

Compared with controls, PD patients had significantly lower colonic expression of ZO-1 (p < 0.01) and FFAR2 (p = 0.01). On serial biopsy, colonic expression of FFAR2 and FFAR3 was reduced in the pre-motor stage before PD diagnosis (both p < 0.01). MDS-UPDRS motor scores did not correlate with colonic marker levels. Constipation severity negatively correlated with colonic ZO-1 levels (r = -0.49, p = 0.02).

CONCLUSIONS

Colonic expression of ZO-1 and FFAR2 is lower in PD patients compared with unaffected controls, and FFAR2 and FFAR3 levels decline in the pre-motor stage of PD. Our findings implicate a leaky gut phenomenon in PD and reinforce that gut metabolites may contribute to the process of PD.

Relationship Between Short-chain Fatty Acids and Parkinson's Disease: A Review from Pathology to Clinic

Parkinson's disease (PD) is a complicated neurodegenerative disease, characterized by the accumulation of α-synuclein (α-syn) in Lewy bodies and neurites, and massive loss of midbrain dopamine neurons. Increasing evidence suggests that gut microbiota and microbial metabolites are involved in the development of PD. Among these, short-chain fatty acids (SCFAs), the most abundant microbial metabolites, have been proven to play a key role in brain-gut communication. In this review, we analyze the role of SCFAs in the pathology of PD from multiple dimensions and summarize the alterations of SCFAs in PD patients as well as their correlation with motor and non-motor symptoms. Future research should focus on further elucidating the role of SCFAs in neuroinflammation, as well as developing novel strategies employing SCFAs and their derivatives to treat PD.

Salivary Biomarkers for Parkinson's Disease: A Systematic Review with Meta-Analysis

Parkinson's Disease (PD) is a common neurodegenerative disease which manifests with motor features, such as bradykinesia, resting tremor, rigidity, and postural instability. Using the non-invasive technique of saliva collection, we designed a systematic review to answer the question "Are salivary biomarkers reliable for the diagnosis of Parkinson's Disease?". Following inclusion and exclusion criteria, 30 studies were included in this systematic review (according to the PRISMA statement guidelines). Mostly proteins were reported as potential biomarkers in saliva. Based on meta-analysis, in PD patients, salivary levels of total alpha-synuclein were significantly decreased, and those of oligomeric alpha-synuclein were significantly increased. Also, according to pooled AUC, heme oxygenase-1 demonstrated significant predictive value for saliva-based PD diagnosis. In conclusion, some potential biomarkers, especially alpha-synuclein, can be altered in the saliva of PD patients, which could be reliably useful for early diagnosis of this neurodegenerative disease differentiating other synucleopathies.

Role of the Gut Bacteria-Derived Metabolite Phenylacetylglutamine in Health and Diseases

Over the past few decades, it has been well established that gut microbiota-derived metabolites can disrupt gut function, thus resulting in an array of diseases. Notably, phenylacetylglutamine (PAGln), a bacterial derived metabolite, has recently gained attention due to its role in the initiation and progression of cardiovascular and cerebrovascular diseases. This meta-organismal metabolite PAGln is a byproduct of amino acid acetylation of its precursor phenylacetic acid (PAA) from a range of dietary sources like egg, meat, dairy products, etc. The microbiota-dependent metabolism of phenylalanine produces PAA, which is a crucial intermediate that is catalyzed by diverse microbial catalytic pathways. PAA conjugates with glutamine and glycine in the liver and kidney to predominantly form phenylacetylglutamine in humans and phenylacetylglycine in rodents. PAGln is associated with thrombosis as it enhances platelet activation mediated through the GPCRs receptors α2A, α2B, and β2 ADRs, thereby aggravating the pathological conditions. Clinical evidence suggests that elevated levels of PAGln are associated with pathology of cardiovascular, cerebrovascular, and neurological diseases. This Review further consolidates the microbial/biochemical synthesis of PAGln and discusses its role in the above pathophysiologies.

Integrated metabolomics and proteomics analysis of plasma lipid metabolism in Parkinson's disease

INTRODUCTION

Metabolomics and proteomics are two growing fields of science which may shed light on the molecular mechanisms that contribute to neurodegenerative diseases. Studies focusing on these aspects can reveal specific metabolites and proteins that can halt or reverse the progressive neurodegenerative process leading to dopaminergic cell death in the brain.

AREAS COVERED

In this article, an overview of the current status of metabolomic and proteomic profiling in the neurodegenerative disease such as Parkinson's disease (PD) is presented. We discuss the importance of state-of-the-art metabolomics and proteomics using advanced analytical methodologies and their potential for discovering new biomarkers in PD. We critically review the research to date, highlighting how metabolomics and proteomics can have an important impact on early disease diagnosis, future therapy development and the identification of new biomarkers. Finally, we will discuss interactions between lipids and α-synuclein (SNCA) and also consider the role of SNCA in lipid metabolism.

EXPERT OPINION

Metabolomic and proteomic studies contribute to understanding the biological basis of PD pathogenesis, identifying potential biomarkers and introducing new therapeutic strategies. The complexity and multifactorial nature of this disease requires a comprehensive approach, which can be achieved by integrating just these two omic studies.

Stroke and Vascular Cognitive Impairment: The Role of Intestinal Microbiota Metabolite TMAO

The gut microbiome interacts with the brain bidirectionally through the microbiome-gutbrain axis, which plays a key role in regulating various nervous system pathophysiological processes. Trimethylamine N-oxide (TMAO) is produced by choline metabolism through intestinal microorganisms, which can cross the blood-brain barrier to act on the central nervous system. Previous studies have shown that elevated plasma TMAO concentrations increase the risk of major adverse cardiovascular events, but there are few studies on TMAO in cerebrovascular disease and vascular cognitive impairment. This review summarized a decade of research on the impact of TMAO on stroke and related cognitive impairment, with particular attention to the effects on vascular cognitive disorders. We demonstrated that TMAO has a marked impact on the occurrence, development, and prognosis of stroke by regulating cholesterol metabolism, foam cell formation, platelet hyperresponsiveness and thrombosis, and promoting inflammation and oxidative stress. TMAO can also influence the cognitive impairment caused by Alzheimer's disease and Parkinson's disease via inducing abnormal aggregation of key proteins, affecting inflammation and thrombosis. However, although clinical studies have confirmed the association between the microbiome-gut-brain axis and vascular cognitive impairment (cerebral small vessel disease and post-stroke cognitive impairment), the molecular mechanism of TMAO has not been clarified, and TMAO precursors seem to play the opposite role in the process of poststroke cognitive impairment. In addition, several studies have also reported the possible neuroprotective effects of TMAO. Existing therapies for these diseases targeted to regulate intestinal flora and its metabolites have shown good efficacy. TMAO is probably a new target for early prediction and treatment of stroke and vascular cognitive impairment.

Exploring the interplay between metabolomics and genetics in Parkinson's disease: Insights from ongoing research and future avenues

Parkinson's disease (PD) is a widespread neurodegenerative disorder, whose complex aetiology remains under construction. While rare variants have been associated with the monogenic PD form, most PD cases are influenced by multiple genetic and environmental aspects. Nonetheless, the pathophysiological pathways and molecular networks involved in monogenic/idiopathic PD overlap, and genetic variants are decisive in elucidating the convergent underlying mechanisms of PD. In this scenario, metabolomics has furnished a dynamic and systematic picture of the synergy between the genetic background and environmental influences that impact PD, making it a valuable tool for investigating PD-related metabolic dysfunctions. In this review, we performed a brief overview of metabolomics current research in PD, focusing on significant metabolic alterations observed in idiopathic PD from different biofluids and strata and exploring how they relate to genetic factors associated with monogenic PD. Dysregulated amino acid metabolism, lipid metabolism, and oxidative stress are the critical metabolic pathways implicated in both genetic and idiopathic PD. By merging metabolomics and genetics data, it is possible to distinguish metabolic signatures of specific genetic backgrounds and to pinpoint subgroups of PD patients who could derive personalized therapeutic benefits. This approach holds great promise for advancing PD research and developing innovative, cost-effective treatments.

Omics data integration suggests a potential idiopathic Parkinson's disease signature

The vast majority of Parkinson's disease cases are idiopathic. Unclear etiology and multifactorial nature complicate the comprehension of disease pathogenesis. Identification of early transcriptomic and metabolic alterations consistent across different idiopathic Parkinson's disease (IPD) patients might reveal the potential basis of increased dopaminergic neuron vulnerability and primary disease mechanisms. In this study, we combine systems biology and data integration approaches to identify differences in transcriptomic and metabolic signatures between IPD patient and healthy individual-derived midbrain neural precursor cells. Characterization of gene expression and metabolic modeling reveal pyruvate, several amino acid and lipid metabolism as the most dysregulated metabolic pathways in IPD neural precursors. Furthermore, we show that IPD neural precursors endure mitochondrial metabolism impairment and a reduced total NAD pool. Accordingly, we show that treatment with NAD precursors increases ATP yield hence demonstrating a potential to rescue early IPD-associated metabolic changes.

Metaorganismal choline metabolism shapes olfactory perception

Microbes living in the intestine can regulate key signaling processes in the central nervous system that directly impact brain health. This gut-brain signaling axis is partially mediated by microbe-host-dependent immune regulation, gut-innervating neuronal communication, and endocrine-like small molecule metabolites that originate from bacteria to ultimately cross the blood-brain barrier. Given the mounting evidence of gut-brain crosstalk, a new therapeutic approach of "psychobiotics" has emerged, whereby strategies designed to primarily modify the gut microbiome have been shown to improve mental health or slow neurodegenerative diseases. Diet is one of the most powerful determinants of gut microbiome community structure, and dietary habits are associated with brain health and disease. Recently, the metaorganismal (i.e., diet-microbe-host) trimethylamine N-oxide (TMAO) pathway has been linked to the development of several brain diseases including Alzheimer's, Parkinson's, and ischemic stroke. However, it is poorly understood how metaorganismal TMAO production influences brain function under normal physiological conditions. To address this, here we have reduced TMAO levels by inhibiting gut microbe-driven choline conversion to trimethylamine (TMA), and then performed comprehensive behavioral phenotyping in mice. Unexpectedly, we find that TMAO is particularly enriched in the murine olfactory bulb, and when TMAO production is blunted at the level of bacterial choline TMA lyase (CutC/D), olfactory perception is altered. Taken together, our studies demonstrate a previously underappreciated role for the TMAO pathway in olfactory-related behaviors.

Diagnosis of Parkinson's Disease via the Metabolic Fingerprint in Saliva by Deep Learning

Parkinson's disease (PD) is the second cause of the neurodegenerative disorder, affecting over 6 million people worldwide. The World Health Organization estimated that population aging will cause global PD prevalence to double in the coming 30 years. Optimal management of PD shall start at diagnosis and requires both a timely and accurate method. Conventional PD diagnosis needs observations and clinical signs assessment, which are time-consuming and low-throughput. A lack of body fluid diagnostic biomarkers for PD has been a significant challenge, although substantial progress has been made in genetic and imaging marker development. Herein, a platform that noninvasively collects saliva metabolic fingerprinting (SMF) by nanoparticle-enhanced laser desorption-ionization mass spectrometry with high-reproducibility and high-throughput, using ultra-small sample volume (down to 10 nL), is developed. Further, excellent diagnostic performance is achieved with an area-under-the-curve of 0.8496 (95% CI: 0.7393-0.8625) by constructing deep learning model from 312 participants. In conclusion, an alternative solution is provided for the molecular diagnostics of PD with SMF and metabolic biomarker screening for therapeutic intervention.

Identification of a Biomarker Panel for Diagnosis of Early Childhood Caries Using Salivary Metabolic Profile

Several studies have demonstrated that nuclear magnetic resonance (NMR) metabolic profiles can differentiate patients with caries from healthy individuals; however, these studies only identified individual metabolites. The present study aimed to identify a salivary metabolite biomarker panel for the diagnosis of early childhood caries (ECC). Saliva samples from children with and without caries were analyzed using NMR spectroscopy. Multivariate and univariate analyses were performed to identify the discriminating metabolites. Selected metabolites were further evaluated and used to detect ECC. The saliva samples of children with ECC were characterized based on the increased levels of formate, glycerophosphocholine, and lactate and reduced levels of alanine, glycine, isoleucine, lysine, proline, and tyrosine. The levels of these metabolites were significantly different from those in the control in the ECC subgroup according to caries severity and correlated with the number of decayed and filled teeth or surfaces. Subsequently, an optimal salivary metabolite biomarker panel comprising formate, lactate, proline, and glycine was developed. This panel exhibited a better diagnostic performance for ECC than a single metabolite. These results demonstrate that salivary metabolic signatures can reflect oral conditions associated with dental caries, thereby emphasizing the importance of distinct salivary metabolic profiles as potential biomarkers of ECC.

Salivary Metabolomics in the Diagnosis and Monitoring of Neurodegenerative Dementia

Millions of people suffer with dementia worldwide. However, early diagnosis of neurodegenerative diseases/dementia (NDD) is difficult, and no specific biomarkers have been found. This study aims to review the applications of salivary metabolomics in diagnostics and the treatment monitoring of NDD A literature search of suitable studies was executed so that a total of 29 original research articles were included in the present review. Spectroscopic methods, mainly nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry, give us a broad view of changes in salivary metabolites in neurodegenerative diseases. The role of different salivary metabolites in brain function is discussed. Further studies with larger patient cohorts should be carried out to investigate the association between salivary metabolites and brain function and thus learn more about the complicated pathways in the human body.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part III: Implementations for the Diagnosis of Non-Cancerous Disorders, Both Oral and Systemic

This communication represents Part III of our series of reports based on the applications of human saliva as a useful and conveniently collectable medium for the discovery, identification and monitoring of biomarkers, which are of some merit for the diagnosis of human diseases. Such biomarkers, or others reflecting the dysfunction of specific disease-associated metabolic pathways, may also be employed for the prognostic pathological tracking of these diseases. Part I of this series set the experimental and logistical groundwork for this report, and the preceding paper, Part II, featured the applications of newly developed metabolomics technologies to the diagnosis and severity grading of human cancer conditions, both oral and systemic. Clearly, there are many benefits, both scientific and economic, associated with the donation of human saliva samples (usually as whole mouth saliva) from humans consenting to and participating in investigations focused on the discovery of biomolecular markers of diseases. These include usually non-invasive collection protocols, relatively low cost when compared against blood sample collection, and no requirement for clinical supervision during collection episodes. This paper is centred on the employment and value of 'state-of-the-art' metabolomics technologies to the diagnosis and prognosis of a wide range of non-cancerous human diseases. Firstly, these include common oral diseases such as periodontal diseases (from type 1 (gingivitis) to type 4 (advanced periodontitis)), and dental caries. Secondly, a wide range of extra-oral (systemic) conditions are covered, most notably diabetes types 1 and 2, cardiovascular and neurological diseases, and Sjögren's syndrome, along with a series of viral infections, e.g., pharyngitis, influenza, HIV and COVID-19. Since the authors' major research interests lie in the area of the principles and applications of NMR-linked metabolomics techniques, many, but not all, of the studies reviewed were conducted using these technologies, with special attention being given to recommended protocols for their operation and management, for example, satisfactory experimental model designs; sample collection and laboratory processing techniques; the selection of sample-specific NMR pulse sequences for saliva analysis; and strategies available for the confirmation of resonance assignments for both endogenous and exogenous molecules in this biofluid. This article also features an original case study, which is focussed on the use of NMR-based salivary metabolomics techniques to provide some key biomarkers for the diagnosis of pharyngitis, and an example of how to 'police' such studies and to recognise participants who perceive that they actually have this disorder but do not from their metabolic profiles and multivariate analysis pattern-based clusterings. The biochemical and clinical significance of these multidimensional metabolomics investigations are discussed in detail.

Microbiome and Metabolome Insights into the Role of the Gastrointestinal-Brain Axis in Parkinson's and Alzheimer's Disease: Unveiling Potential Therapeutic Targets

Neurodegenerative diseases such as Parkinson's (PD) and Alzheimer's disease (AD), the prevalence of which is rapidly rising due to an aging world population and westernization of lifestyles, are expected to put a strong socioeconomic burden on health systems worldwide. Clinical trials of therapies against PD and AD have only shown limited success so far. Therefore, research has extended its scope to a systems medicine point of view, with a particular focus on the gastrointestinal-brain axis as a potential main actor in disease development and progression. Microbiome and metabolome studies have already revealed important insights into disease mechanisms. Both the microbiome and metabolome can be easily manipulated by dietary and lifestyle interventions, and might thus offer novel, readily available therapeutic options to prevent the onset as well as the progression of PD and AD. This review summarizes our current knowledge on the interplay between microbiota, metabolites, and neurodegeneration along the gastrointestinal-brain axis. We further illustrate state-of-the art methods of microbiome and metabolome research as well as metabolic modeling that facilitate the identification of disease pathomechanisms. We conclude with therapeutic options to modulate microbiome composition to prevent or delay neurodegeneration and illustrate potential future research directions to fight PD and AD.

Plasma Metabolic Disturbances in Parkinson's Disease Patients

Plasma from patients with Parkinson's disease (PD) is a valuable source of information indicating altered metabolites associated with the risk or progression of the disease. Neurotoxicity of dopaminergic neurons, which is triggered by aggregation of α-synuclein, is the main pathogenic feature of PD. However, a growing body of scientific reports indicates that metabolic changes may precede and directly contribute to neurodegeneration. Identification and characterization of the abnormal metabolic pattern in patients' plasma are therefore crucial for the search for potential PD biomarkers. The aims of the present study were (1) to identify metabolic alterations in plasma metabolome in subjects with PD as compared with the controls; (2) to find new potential markers, some correlations among them; (3) to identify metabolic pathways relevant to the pathophysiology of PD. Plasma samples from patients with PD (n = 25) and control group (n = 12) were collected and the gas chromatography-time-of-flight-mass spectrometry GC-TOFMS-based metabolomics approach was used to evaluate the metabolic changes based on the identified 14 metabolites with significantly altered levels using univariate and multivariate statistical analysis. The panel, including 6 metabolites (L-3-methoxytyrosine, aconitic acid, L-methionine, 13-docosenamide, hippuric acid, 9,12-octadecadienoic acid), was identified to discriminate PD from controls with the area under the curve (AUC) of 0.975, with an accuracy of 92%. We also used statistical criteria to identify the significantly altered level of metabolites. The metabolic pathways involved were associated with linoleic acid metabolism, mitochondrial electron transport chain, glycerolipid metabolism, and bile acid biosynthesis. These abnormal metabolic changes in the plasma of patients with PD were mainly related to the amino acid metabolism, TCA cycle metabolism, and mitochondrial function.

Mapping trends and hotspot regarding gastrointestinal microbiome and neuroscience: A bibliometric analysis of global research (2002-2022)

BACKGROUND

Scholars have long understood that gastrointestinal microorganisms are intimately related to human disorders. The literature on research involving the gut microbiome and neuroscience is emerging. This study exposed the connections between gut microbiota and neuroscience methodically and intuitively using bibliometrics and visualization. This study's objectives were to summarize the knowledge structure and identify emerging trends and potential hotspots in this field.

MATERIALS AND METHODS

On October 18, 2022, a literature search was conducted utilizing the Web of Science Core Collection (WoSCC) database for studies on gut microbiota and neuroscience studies from 2002 to 2022 (August 20, 2022). VOSviewer and CiteSpace V software was used to conduct the bibliometrics and visualization analysis.

RESULTS

From 2002 to 2022 (August 20, 2022), 2,275 publications in the WoSCC database satisfied the criteria. The annual volume of publications has rapidly emerged in recent years (2016-2022). The most productive nation (n = 732, 32.18%) and the hub of inter-country cooperation (links: 38) were the United States. University College Cork had the most research papers published in this area, followed by McMaster University and Harvard Medical School. Cryan JF, Dinan TG, and Clarke G were key researchers with considerable academic influence. The journals with the most publications are "Neurogastroenterology and Motility" and "Brain Behavior and Immunity." The most cited article and co-cited reference was Cryan JF's 2012 article on the impact of gut microbiota on the brain and behavior. The current research hotspot includes gastrointestinal microbiome, inflammation, gut-brain axis, Parkinson's disease (PD), and Alzheimer's disease (AD). The research focus would be on the "gastrointestinal microbiome, inflammation: a link between obesity, insulin resistance, and cognition" and "the role of two important theories of the gut-brain axis and microbial-gut-brain axis in diseases." Burst detection analysis showed that schizophrenia, pathology, and psychiatric disorder may continue to be the research frontiers.

CONCLUSION

Research on "gastrointestinal microbiome, inflammation: a link between obesity, insulin resistance, and cognition" and "the role of two important theories of the gut-brain axis and microbial-gut-brain axis in diseases" will continue to be the hotspot. Schizophrenia and psychiatric disorder will be the key research diseases in the field of gut microbiota and neuroscience, and pathology is the key research content, which is worthy of scholars' attention.

Clinical significance and potential role of trimethylamine N-oxide in neurological and neuropsychiatric disorders

In the past three decades, research on the gut microbiome and its metabolites, such as trimethylamines (TMA), trimethylamine N-oxide (TMAO), short-chain fatty acids (SCFAs), branched-chain amino acids (BCAAs), bile acids, tryptophan and indole derivatives, has attracted the attention of many scientists and industrialists. Among these metabolites, TMAO is produced from dietary choline, phosphatidylcholine, carnitine,andbetaine. TMAO and other gut metabolites, such as TMA and SCFAs, reach the brain by crossing the blood-brain barrier (BBB) and are involved in brain development, neurogenesis, and behavior. Gut-microbiota composition is influenced by diet, lifestyle, antibiotics, and age. Several studies have confirmed that altered TMAO levels contribute to metabolic, vascular, psychiatric, and neurodegenerative disorders. This review focuses on how altered TMAO levels impact oxidative stress, microglial activation, and the apoptosis of neurons, and may lead to neuroinflammation, which can subsequently result in the development of psychiatric, cognitive, and behavioral disorders.

The Key Role of Magnetic Resonance Imaging in the Detection of Neurodegenerative Diseases-Associated Biomarkers: A Review

Neurodegenerative diseases (NDs), including chronic disease such as Alzheimer's disease, Parkinson's disease, Huntington's disease, and multiple sclerosis, and acute diseases like traumatic brain injury and ischemic stroke are characterized by progressive degeneration, brain tissue damage and loss of neurons, accompanied by behavioral and cognitive dysfunctions. So far, there are no complete cures for NDs; thus, early and timely diagnoses are essential and beneficial to patients' treatment. Magnetic resonance imaging (MRI) has become one of the advanced medical imaging techniques widely used in the clinical examination of NDs due to its non-invasive diagnostic value. In this review, research published in English in current decade from PubMed electronic database on the use of MRI to detect specific biomarkers of NDs was collected, summarized, and discussed, which provides valuable suggestions for the early diagnosis, prevention, and treatment of NDs in the clinic.

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.

Gut microenvironmental changes as a potential trigger in Parkinson's disease through the gut-brain axis

Parkinson's disease (PD) is the second most common neurodegenerative disease attributed to the synergistic effects of genetic risk and environmental stimuli. Although PD is characterized by motor dysfunction resulting from intraneuronal alpha-synuclein accumulations, termed Lewy bodies, and dopaminergic neuronal degeneration in the substantia nigra, multiple systems are involved in the disease process, resulting in heterogenous clinical presentation and progression. Genetic predisposition to PD regarding aberrant immune responses, abnormal protein aggregation, autophagolysosomal impairment, and mitochondrial dysfunction leads to vulnerable neurons that are sensitive to environmental triggers and, together, result in neuronal degeneration. Neuropathology studies have shown that, at least in some patients, Lewy bodies start from the enteric nervous system and then spread to the central dopaminergic neurons through the gut-brain axis, suggesting the contribution of an altered gut microenvironment in the pathogenesis of PD. A plethora of evidence has revealed different gut microbiomes and gut metabolites in patients with PD compared to unaffected controls. Chronic gut inflammation and impaired intestinal barrier integrity have been observed in human PD patients and mouse models of PD. These observations led to the hypothesis that an altered gut microenvironment is a potential trigger of the PD process in a genetically susceptible host. In this review, we will discuss the complex interplay between genetic factors and gut microenvironmental changes contributing to PD pathogenesis.

Salivary Metabolomics for Oral Cancer Detection: A Narrative Review

The development of low- or non-invasive screening tests for cancer is crucial for early detection. Saliva is an ideal biofluid containing informative components for monitoring oral and systemic diseases. Metabolomics has frequently been used to identify and quantify numerous metabolites in saliva samples, serving as novel biomarkers associated with various conditions, including cancers. This review summarizes the recent applications of salivary metabolomics in biomarker discovery in oral cancers. We discussed the prevalence, epidemiologic characteristics, and risk factors of oral cancers, as well as the currently available screening programs, in India and Japan. These data imply that the development of biomarkers by itself is inadequate in cancer detection. The use of current diagnostic methods and new technologies is necessary for efficient salivary metabolomics analysis. We also discuss the gap between biomarker discovery and nationwide screening for the early detection of oral cancer and its prevention.

The Utility of Breath Analysis in the Diagnosis and Staging of Parkinson's Disease

BACKGROUND

The analysis of volatile organic compounds (VOCs) collected in breath samples has the potential to be a rapid, non-invasive test to aid in the clinical diagnosis and tracking of chronic conditions such as Parkinson's disease (PD).

OBJECTIVE

To assess the feasibility and utility of breath sample analysis done, both at point of collection in clinic and when sent away to be analyzed remotely, to diagnose, stratify and monitor disease course in a moderately large cohort of patients with PD.

METHODS

Breath samples were collected from 177 people with PD and 37 healthy matched control individuals followed over time. Standard clinical data (MDS-UPDRS & cognitive assessments) from the PD patients were collected at the same time as the breath sample was taken, these measures were then correlated with the breath test analysis of exhaled VOCs.

RESULTS

The breath test was able to distinguish patients with PD from healthy control participants and correlated with disease stage. The off-line system (remote analysis) gave good results with overall classification accuracies across a range of clinical measures of between 73.6% to 95.6%. The on-line (in clinic) system showed comparable results but with lower levels of correlation, varying between 33.5% to 82.4%. Chemical analysis identified 29 potential molecules that were different and which may relate to pathogenic pathways in PD.

CONCLUSION

Breath analysis shows potential for PD diagnostics and monitoring. Both off-line and on-line sensor systems were easy to do and provided comparable results which will enable this technique to be easily adopted in clinic if larger studies confirm our findings.

The Potential of Metabolomics in Biomedical Applications

The metabolome offers a dynamic, comprehensive, and precise picture of the phenotype. Current high-throughput technologies have allowed the discovery of relevant metabolites that characterize a wide variety of human phenotypes with respect to health, disease, drug monitoring, and even aging. Metabolomics, parallel to genomics, has led to the discovery of biomarkers and has aided in the understanding of a diversity of molecular mechanisms, highlighting its application in precision medicine. This review focuses on the metabolomics that can be applied to improve human health, as well as its trends and impacts in metabolic and neurodegenerative diseases, cancer, longevity, the exposome, liquid biopsy development, and pharmacometabolomics. The identification of distinct metabolomic profiles will help in the discovery and improvement of clinical strategies to treat human disease. In the years to come, metabolomics will become a tool routinely applied to diagnose and monitor health and disease, aging, or drug development. Biomedical applications of metabolomics can already be foreseen to monitor the progression of metabolic diseases, such as obesity and diabetes, using branched-chain amino acids, acylcarnitines, certain phospholipids, and genomics; these can assess disease severity and predict a potential treatment. Future endeavors should focus on determining the applicability and clinical utility of metabolomic-derived markers and their appropriate implementation in large-scale clinical settings.

Metabolite and lipoprotein profiles reveal sex-related oxidative stress imbalance in de novo drug-naive Parkinson's disease patients

Parkinson’s disease (PD) is the neurological disorder showing the greatest rise in prevalence from 1990 to 2016. Despite clinical definition criteria and a tremendous effort to develop objective biomarkers, precise diagnosis of PD is still unavailable at early stage. In recent years, an increasing number of studies have used omic methods to unveil the molecular basis of PD, providing a detailed characterization of potentially pathological alterations in various biological specimens. Metabolomics could provide useful insights to deepen our knowledge of PD aetiopathogenesis, to identify signatures that distinguish groups of patients and uncover responsive biomarkers of PD that may be significant in early detection and in tracking the disease progression and drug treatment efficacy. The present work is the first large metabolomic study based on nuclear magnetic resonance (NMR) with an independent validation cohort aiming at the serum characterization of de novo drug-naive PD patients. Here, NMR is applied to sera from large training and independent validation cohorts of German subjects. Multivariate and univariate approaches are used to infer metabolic differences that characterize the metabolite and the lipoprotein profiles of newly diagnosed de novo drug-naive PD patients also in relation to the biological sex of the subjects in the study, evidencing a more pronounced fingerprint of the pathology in male patients. The presence of a validation cohort allowed us to confirm altered levels of acetone and cholesterol in male PD patients. By comparing the metabolites and lipoproteins levels among de novo drug-naive PD patients, age- and sex-matched healthy controls, and a group of advanced PD patients, we detected several descriptors of stronger oxidative stress.

Plasma Metabolite Signature Classifies Male LRRK2 Parkinson’s Disease Patients

Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.

Updates and Original Case Studies Focused on the NMR-Linked Metabolomics Analysis of Human Oral Fluids Part I: Emerging Platforms and Perspectives

1H NMR-based metabolomics analysis of human saliva, other oral fluids, and/or tissue biopsies serves as a valuable technique for the exploration of metabolic processes, and when associated with ’state-of-the-art’ multivariate (MV) statistical analysis strategies, provides a powerful means of examining the identification of characteristic metabolite patterns, which may serve to differentiate between patients with oral health conditions (e.g., periodontitis, dental caries, and oral cancers) and age-matched heathy controls. This approach may also be employed to explore such discriminatory signatures in the salivary 1H NMR profiles of patients with systemic diseases, and to date, these have included diabetes, Sjörgen’s syndrome, cancers, neurological conditions such as Alzheimer’s disease, and viral infections. However, such investigations are complicated in view of quite a large number of serious inconsistencies between the different studies performed by independent research groups globally; these include differing protocols and routes for saliva sample collection (e.g., stimulated versus unstimulated samples), their timings (particularly the oral activity abstention period involved, which may range from one to 12 h or more), and methods for sample transport, storage, and preparation for NMR analysis, not to mention a very wide variety of demographic variables that may influence salivary metabolite concentrations, notably the age, gender, ethnic origin, salivary flow-rate, lifestyles, diets, and smoking status of participant donors, together with their exposure to any other possible convoluting environmental factors. In view of the explosive increase in reported salivary metabolomics investigations, in this update, we critically review a wide range of critical considerations for the successful performance of such experiments. These include the nature, composite sources, and biomolecular status of human saliva samples; the merits of these samples as media for the screening of disease biomarkers, notably their facile, unsupervised collection; and the different classes of such metabolomics investigations possible. Also encompassed is an account of the history of NMR-based salivary metabolomics; our recommended regimens for the collection, transport, and storage of saliva samples, along with their preparation for NMR analysis; frequently employed pulse sequences for the NMR analysis of these samples; the supreme resonance assignment benefits offered by homo- and heteronuclear two-dimensional NMR techniques; deliberations regarding salivary biomolecule quantification approaches employed for such studies, including the preprocessing and bucketing of multianalyte salivary NMR spectra, and the normalization, transformation, and scaling of datasets therefrom; salivary phenotype analysis, featuring the segregation of a range of different metabolites into ‘pools’ grouped according to their potential physiological sources; and lastly, future prospects afforded by the applications of LF benchtop NMR spectrometers for direct evaluations of the oral or systemic health status of patients at clinical ‘point-of-contact’ sites, e.g., dental surgeries. This commentary is then concluded with appropriate recommendations for the conduct of future salivary metabolomics studies. Also included are two original case studies featuring investigations of (1) the 1H NMR resonance line-widths of selected biomolecules and their possible dependence on biomacromolecular binding equilibria, and (2) the combined univariate (UV) and MV analysis of saliva specimens collected from a large group of healthy control participants in order to potentially delineate the possible origins of biomolecules therein, particularly host- versus oral microbiome-derived sources. In a follow-up publication, Part II of this series, we conduct censorious reviews of reported observations acquired from a diversity of salivary metabolomics investigations performed to evaluate both localized oral and non-oral diseases. Perplexing problems encountered with these again include those arising from sample collection and preparation protocols, along with 1H NMR spectral misassignments.

A targeted and nontargeted metabolomics study on the oral processing of epicatechins from green tea

Oral processing (OP), referring to the whole process of food digestion in human mouth, has a major influence on food flavor perception. This study focused on the compositional changes of the four green tea epicatechins (viz., EC, EGC, ECG, EGCG) during OP, based on targeted and nontargeted metabolomics. It was found that the four epicatechins were all extensively lost through transformation undergoing OP, among which EC was the most stable one, whereas EGCG the least. EGCG was further revealed to be susceptible to human oral cavity in the simulated OP in vitro. It could be converted physically by precipitating with mucin in saliva, and chemically through hydrolysis and dimerization, mediated mainly by the neutral pH condition. The OP of epicatechins also caused salivary composition changes possibly involving health benefits of green tea. These findings could raise awareness of the interactions between epicatechins, or any other food materials, with human mouth.

Association of Fecal and Plasma Levels of Short-Chain Fatty Acids With Gut Microbiota and Clinical Severity in Parkinson Disease Patients

BACKGROUND AND OBJECTIVES

Short-chain fatty acids (SCFAs) are gut microbial metabolites that promote the disease process in a rodent model of Parkinson's disease (PD), but fecal levels of SCFAs in PD patients are reduced. Simultaneous assessments of fecal and plasma SCFA levels, and their inter-relationships with the PD disease process are scarce. We aimed to compare fecal and plasma levels of different SCFAs subtypes in PD patients and healthy controls to delineate their interrelations and link to gut microbiota changes and clinical severity of PD.

METHODS

A cohort of 96 PD patients and 85 controls were recruited from National Taiwan University Hospital. Fecal and plasma concentrations of SCFAs were measured using chromatography and mass spectrometry. Gut microbiota was analyzed using metagenomic shotgun sequencing. Body mass index and medical co-morbidities were evaluated, and dietary information was obtained using a food frequency questionnaire. To assess motor and cognitive impairment, we used the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and the Mini-Mental Status Examination (MMSE).

RESULTS

Compared with controls, PD patients had lower fecal but higher plasma concentrations of acetate, propionate, and butyrate. After adjustment for age, sex, disease duration, and anti-PD medication dosage, MDS-UPDRS part III motor scores correlated with reduced fecal levels of acetate (ρ = -0.37, p = 0.012), propionate (ρ = -0.32, p = 0.036), and butyrate (ρ = -0.40, p = 0.004) and with increased plasma propionate concentrations (ρ = 0.26, p = 0.042) in PD patients. MMSE scores negatively correlated with plasma levels of butyrate (ρ = -0.09, p = 0.027) and valerate (ρ = -0.032, p = 0.033) after adjustment for confounders. SCFAs-producing gut bacteria correlated positively with fecal levels of SCFAs in healthy controls but revealed no association in patients with PD. In the PD patient group, the abundance of pro-inflammatory microbes, such as Clostridiales bacterium NK3B98 and Ruminococcus sp. AM07-15, significantly correlated with decreased fecal levels and increased plasma levels of SCFAs, especially propionic acid.

DISCUSSION

Reductions in fecal SCFAs but increased plasma SCFAs were observed in PD patients and corelated to specific gut microbiota changes and the clinical severity of PD.

CLASSIFICATION OF EVIDENCE

This study provides Class III evidence that gut metabolite SCFAs distinguish between PD patients and controls, and are associated with disease severity in patients with PD.

Metabolomics of neurological disorders in India

Metabolomics is the comprehensive study of the metabolome and its alterations within biological fluids and tissues. Over the years, applications of metabolomics have been explored in several areas, including personalised medicine in diseases, metabolome-wide association studies (MWAS), pharmacometabolomics and in combination with other branches of omics such as proteomics, transcriptomics and genomics. Mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy are the major analytical techniques widely employed in metabolomics. In addition, MS is coupled with chromatography techniques like gas chromatography (GC) and liquid chromatography (LC) to separate metabolites before analysis. These analytical techniques have made possible identification and quantification of large numbers of metabolites, encompassing characterization of diseases and facilitating a systematic and rational therapeutic strategy based on metabolic patterns. In recent years, the metabolomics approach has been used to obtain a deeper insight into the underlying biochemistry of neurodegenerative disorders and the discovery of biomarkers of clinical implications. The current review mainly focuses on an Indian perspective of metabolomics for the identification of metabolites and metabolic alterations serving as potential diagnostic biomarkers for neurological diseases including acute spinal cord injury, amyotrophic lateral sclerosis, tethered cord syndrome, spina bifida, stroke, Parkinson's disease, glioblastoma and neurological disorders with inborn errors of metabolism.

Review of Metabolomics-Based Biomarker Research for Parkinson's Disease

Parkinson's disease (PD), as the second most common neurodegenerative disease, is seriously affecting the life quality of the elderly. However, there is still a lack of efficient medical methods to diagnosis PD before apparent symptoms occur. In recent years, clinical biomarkers including genetic, imaging, and tissue markers have exhibited remarkable benefits in assisting PD diagnoses. Due to the advantages of high-throughput detection of metabolites and almost non-invasive sample collection, metabolomics research of PD is widely used for diagnostic biomarker discovery. However, there are also a few shortages for those identified biomarkers, such as the scarcity of verifications regarding the sensitivity and specificity. Thus, reviewing the research progress of PD biomarkers based on metabolomics techniques is of great significance for developing PD diagnosis. To comprehensively clarify the progress of current metabolic biomarker studies in PD, we reviewed 20 research articles regarding the discovery and validation of biomarkers for PD diagnosis from three mainstream academic databases (NIH PubMed, ISI Web of Science, and Elsevier ScienceDirect). By analyzing those materials, we summarized the metabolic biomarkers identified by those metabolomics studies and discussed the potential approaches used for biomarker verifications. In conclusion, this review provides a comprehensive and updated overview of PD metabolomics research in the past two decades and particularly discusses the validation of disease biomarkers. We hope those discussions might provide inspiration for PD biomarker discovery and verification in the future.

Metabolomics in Parkinson's disease

Parkinson's disease (PD) is a multifactorial neurodegenerative disorder in which environmental (lifestyle, dietary, infectious disease) factors as well as genetic make-up play a role. Metabolomics, an evolving research field combining biomarker discovery and pathogenetics, is particularly useful in studying complex pathophysiology in general and Parkinson's disease (PD) specifically. PD, the second most frequent neurodegenerative disorder, is characterized by the loss of dopaminergic neurons in the substantia nigra and the presence of intraneural inclusions of α-synuclein aggregates. Although considered a predominantly movement disorder, PD is also associated with number of non-motor features. Metabolomics has provided useful information regarding this neurodegenerative process with the aim of identifying a disease-specific fingerprint. Unfortunately, many disease variables such as clinical presentation, motor system involvement, disease stage and duration substantially affect biomarker relevance. As such, metabolomics provides a unique approach to studying this multifactorial neurodegenerative disorder.

Salivary Metabolomics for Diagnosis and Monitoring Diseases: Challenges and Possibilities

Saliva is a useful biological fluid and a valuable source of biological information. Saliva contains many of the same components that can be found in blood or serum, but the components of interest tend to be at a lower concentration in saliva, and their analysis demands more sensitive techniques. Metabolomics is starting to emerge as a viable method for assessing the salivary metabolites which are generated by the biochemical processes in elucidating the pathways underlying different oral and systemic diseases. In oral diseases, salivary metabolomics has concentrated on periodontitis and oral cancer. Salivary metabolites of systemic diseases have been investigated mostly in the early diagnosis of different cancer, but also neurodegenerative diseases. This mini-review article aims to highlight the challenges and possibilities of salivary metabolomics from a clinical viewpoint. Furthermore, applications of the salivary metabolic profile in diagnosis and prognosis, monitoring the treatment success, and planning of personalized treatment of oral and systemic diseases are discussed.

Sweat metabolome and proteome: Recent trends in analytical advances and potential biological functions

Metabolome and proteome profiling of biofluids, e.g., urine, plasma, has generated vast and ever-increasing amounts of knowledge over the last few decades. Paradoxically, omics analyses of sweat, one of the most readily available human biofluids, have lagged behind. This review capitalizes on the current knowledge and state of the art analytical advances of sweat metabolomics and proteomics. Moreover, current applications of sweat omics such as the discovery of disease biomarkers and monitoring athletic performance are also presented in this review. Another area of emerging knowledge that has been highlighted herein lies in the role of skin host-microbiome interactions in shaping the sweat metabolite-protein profiles. Discussion of future research directions describes the need to have a better grasp of sweat chemicals and to better understand how they function as aided by advances in omics tools. Overall, the role of sweat as an information-rich biofluid that could complement the exploration of the skin metabolome/proteome is emphasized.

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.

Proteomic Profile of Saliva in Parkinson's Disease Patients: A Proof of Concept Study

Parkinson’s disease (PD) is a progressive neurodegenerative disorder. It affects many organs. Lewy bodies—a histopathological “hallmark” of PD—are detected in about 75% of PD submandibular gland samples. We hypothesize that saliva can be a source of biomarkers of PD. The aim of the study was to evaluate and compare the salivary proteome of PD patients and healthy controls (HC). Salivary samples from 39 subjects (24 PD patients, mean age 61.6 ± 8.2; 15 HC, mean age 60.9 ± 6.7) were collected. Saliva was collected using RNA-Pro-Sal kits. Label-free LC-MS/MS mass spectrometry was performed to characterize the proteome of the saliva. IPA analysis of upstream inhibitors was performed. A total of 530 proteins and peptides were identified. We observed lower concentrations of S100-A16, ARP2/3, and VPS4B in PD group when compared to HC. We conclude that the salivary proteome composition of PD patients is different than that of healthy controls. We observed a lower concentration of proteins involved in inflammatory processes, exosome formation, and adipose tissue formation. The variability of expression of proteins between the two groups needs to be considered.

Use of nuclear magnetic resonance spectroscopy in diagnosis of inborn errors of metabolism

Nuclear Magnetic Resonance (NMR) spectroscopy has been applied in many fields of science and is increasingly being considered as a tool in the clinical setting. This review examines its application for diagnosis of inborn errors of metabolism (IEMs). IEMs, whether involving deficiency in the synthesis and degradation of metabolites, or in lipoprotein metabolism, affect nearly 3% of the global population. NMR is a preferred method for comprehensive evaluation of complex biofluids such as blood or urine, as it can provide a relatively unbiased overview of all compounds that are present and does not destroy or otherwise chemically alter the sample. While current newborn screening programs take advantage of other more sensitive methods, such as mass spectrometry, NMR has advantages especially for urine analysis with respect to ease of sample preparation and the reproducibility of results. NMR spectroscopy is particularly compatible with analysis of lipoproteins because it provides information about their size and density, not easily attained by other methods, that can help the clinician to better manage patients with dyslipidemia. We believe that NMR holds great potential for expanding clinical diagnosis in the future, in the field of IEMs and beyond.

Differences in Spectroscopic Properties of Saliva Taken From Normal Subjects and Oral Cancer Patients: Comparison Studies

Oral cancer disease is among the most common cancers in the world and are associated with mortality and morbidity. The characterization of saliva samples may help to distinguish patients with oral cancer disease from normal subjects. To characterize spectra of saliva samples from normal subjects and oral cancer patients by use of fluorescence, absorption, and 1H-NMR spectroscopy. Whole unstimulated saliva samples were collected from patients with oral cancer disease and normal subjects. The saliva samples were analyzed by absorption, fluorescence and 1H-NMR spectroscopic techniques. The characteristic spectra of saliva samples from patients with oral cancer disease and normal subjects were compared. For fluorescence spectroscopic studies, six fluorophores were found in saliva samples. Autofluorescence emission spectra and synchronous spectra of saliva were different between normal subjects and oral cancer patients. For absorption spectroscopic studies, the typical absorption spectra of saliva samples from normal subjects and oral cancer patients were also different in absorption intensity, 1st and 2nd derivative of absorption spectra values. For 1H-NMR studies, nine metabolites and four metabolites were found in saliva samples taken from normal subjects and oral cancer patients, respectively. The metabolic profiles of saliva samples from normal subjects and oral cancer patients were not similar. The characteristic spectra of saliva samples from normal subjects and oral cancer patients were found. These results showed differences in the spectra of saliva samples between both that groups. The spectra from each spectroscopic techniques could determine a candidate saliva biomarkers for distinguishing patients with oral cancer disease from normal subjects.

Circulating MicroRNAs and Long Non-coding RNAs as Potential Diagnostic Biomarkers for Parkinson's Disease

Parkinson’s disease (PD) is the world’s second most common neurodegenerative disease that is associated with age. With the aging of the population, patients with PD are increasing in number year by year. Most such patients lose their ability to self-care with disease progression, which brings an incalculable burden to individual families and society. The pathogenesis of PD is complex, and its clinical manifestations are diverse. Therefore, it is of great significance to screen for circulating biomarkers associated with PD to reveal its pathogenesis and develop objective diagnostic methods so as to prevent, control, and treat the disease. In recent years, microRNAs (miRNAs) and long non-coding RNAs (lncRNAs) are considered to be effective biomarkers for various diseases due to their stability, and resistance to RNAase digestion and extreme conditions in circulating fluids. Here, we review recent advances in the detection of abnormally expressed miRNAs and lncRNAs in PD circulating fluids, and discuss the function and molecular mechanisms of plasma or serum miR-124, miR-132, miR-29, miR-221, miR-7, miR-433, and miR-153 in the regulation and progression of PD. Additionally, application of the differential expression of lncRNAs in circulating fluid in the pathological progression and diagnosis of PD is also reviewed. In short, the determination of abnormally expressed circulating miRNAs and lncRNAs will be valuable for the future diagnosis and treatment of PD.

Brain Branched-Chain Amino Acids in Maple Syrup Urine Disease: Implications for Neurological Disorders

Maple syrup urine disease (MSUD) is an autosomal recessive disorder caused by decreased activity of the branched-chain α-ketoacid dehydrogenase complex (BCKDC), which catalyzes the irreversible catabolism of branched-chain amino acids (BCAAs). Current management of this BCAA dyshomeostasis consists of dietary restriction of BCAAs and liver transplantation, which aims to partially restore functional BCKDC activity in the periphery. These treatments improve the circulating levels of BCAAs and significantly increase survival rates in MSUD patients. However, significant cognitive and psychiatric morbidities remain. Specifically, patients are at a higher lifetime risk for cognitive impairments, mood and anxiety disorders (depression, anxiety, and panic disorder), and attention deficit disorder. Recent literature suggests that the neurological sequelae may be due to the brain-specific roles of BCAAs. This review will focus on the derangements of BCAAs observed in the brain of MSUD patients and will explore the potential mechanisms driving neurologic dysfunction. Finally, we will discuss recent evidence that implicates the relevance of BCAA metabolism in other neurological disorders. An understanding of the role of BCAAs in the central nervous system may facilitate future identification of novel therapeutic approaches in MSUD and a broad range of neurological disorders.

Identification of potential urine biomarkers in idiopathic parkinson's disease using NMR

INTRODUCTION

Parkinson's disease (PD) is the most common neurodegenerative disease caused by the loss of dopamine chemicals resulting in urinary incontinence, gastrointestinal dysfunction, gait impairment and mitochondrial dysfunction. Study investigated urinary metabolic profiles of patients with idiopathic PD as compared to healthy controls (HC) to identify the potential biomarkers.

METHODS

Urine samples were collected from 100 PD subjects and 50 HC using standard protocol. Metabolomic analyses were performed using high resolution nuclear magnetic resonance (NMR) spectroscopy. The integral values of 17 significant metabolites were estimated and concentration values were calculated, which were subjected to univariate and multivariate statistical analysis.

RESULTS

We found significantly increased levels of ornithine, phenylalanine, isoleucine, β-hydroxybutyrate, tyrosine and succinate in the urine of patients with PD in comparison with HC. These metabolites exhibited area under the curve greater than 0.60 on ROC curve analysis. We also observed a significant association between succinate concentration and UPDRS motor scores of PD.

DISCUSSION

Metabolic pathway alterations were observed in aromatic amino acid metabolism, ketone bodies synthesis, branched chain amino acid metabolism and ornithine metabolism. Comprehensive metabolomic profiling revealed variations in urinary signatures associated with severity of idiopathic PD. This profiling relies on non-invasive sampling and is complementary to existing clinical modalities.

Metabolic Profiles of Whole, Parotid and Submandibular/Sublingual Saliva

The detection of salivary molecules associated with pathological and physiological alterations has encouraged the search of novel and non-invasive diagnostic biomarkers for oral health evaluation. While genomic, transcriptomic, and proteomic profiles of human saliva have been reported, its metabolic composition is a topic of research: metabolites in submandibular/sublingual saliva have never been analyzed systematically. In this study, samples of whole, parotid, and submandibular/sublingual saliva from 20 healthy donors, without dental or periodontal diseases, were examined by nuclear magnetic resonance. We identified metabolites which are differently distributed within the three saliva subtypes (54 in whole, 49 in parotid, and 36 in submandibular/sublingual saliva). Principal component analysis revealed a distinct cluster for whole saliva and a partial overlap for parotid and submandibular/sublingual metabolites. We found exclusive metabolites for each subtype: 2-hydroxy-3-methylvalerate, 3-methyl-glutarate, 3-phenylpropionate, 4-hydroxyphenylacetate, 4-hydroxyphenyllactate, galactose, and isocaproate in whole saliva; caprylate and glycolate in submandibular/sublingual saliva; arginine in parotid saliva. Salivary metabolites were classified into standard and non-proteinogenic amino acids and amines; simple carbohydrates; organic acids; bacterial-derived metabolites. The identification of a salivary gland-specific metabolic composition in healthy people provides the basis to invigorate the search for salivary biomarkers associated with oral and systemic diseases.

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.