Metabolic profiles associated with exposure to ambient particulate air pollution: findings from the Betula cohort

Introduction

Air pollution is a significant contributor to morbidity and mortality globally and has been linked to an increased risk of dementia. Previous studies within the Betula cohort in Northern Sweden have demonstrated associations between air pollution and dementia, as well as distinctive metabolomic profiles in dementia patients compared to controls. This study aimed to investigate whether air pollution is associated with quantitative changes in metabolite levels within this cohort, and whether future dementia status would modify this association.

Methods

Both short-term and long-term exposure to air pollution were evaluated using high spatial resolution models and measured data. Air pollution from vehicle exhaust and woodsmoke were analyzed separately. Metabolomic profiling was conducted on 321 participants, including 58 serum samples from dementia patients and a control group matched for age, sex, and education level, using nuclear magnetic resonance spectroscopy.

Results

No statistically significant associations were found between any metabolites and any measures of short-term or long-term exposure to air pollution. However, there were trends potentially suggesting associations between both long-term and short-term exposure to air pollution with lactate and glucose metabolites. Notably, these associations were observed despite the lack of correlation between long-term and short-term air pollution exposure in this cohort. There were also tendencies for associations between air pollution from woodsmoke to be more pronounced in participants that would later develop dementia, suggesting a potential effect depending on urban/rural factors.

Discussion

While no significant associations were found, the trends observed in the data suggest potential links between air pollution exposure and changes in lactate and glucose metabolites. These findings provide some new insights into the link between air pollution and metabolic markers in a low-exposure setting. However, addressing existing limitations is crucial to improve the robustness and applicability of future research in this area. The pronounced associations in participants who later developed dementia may indicate an influence of urban/rural factors, warranting further investigation.

NMR analysis seeking for cognitive decline and dementia metabolic markers in plasma from aged individuals

BACKGROUND

Blood biomarkers can improve the ability to diagnose dementia, providing new information to better understand the pathophysiology and causes of the disease. Some studies with patients have already shown changes in metabolic profiles among patients with pathological cognitive decline or Alzheimer's disease, when compared to individuals with normal cognition.

METHODS

To search for new metabolic biomarkers of dementia, we analyzed serum levels of several metabolites, measured by nuclear magnetic resonance spectroscopy, in elderly individuals, a group with normal cognitive decline (control), and three other groups with cognitive decline. pathological (low, moderate, and severe).

RESULTS

Decreased plasma levels of tyrosine, glutamate, valine, leucine, and isoleucine are associated with worsening of pathological cognitive decline. However, the area under analysis of receptor operating characteristics suggests that tyrosine and glutamate have low specificity and sensitivity. Valine, leucine, and isoleucine are influenced by blood glucose or diabetes, but these conditions do not seem to be of great influence in the differences observed. Isobutyrate, histidine, acetone and unknown-1 metabolite also decrease their plasma levels with increasing CD. Isobutyrate ad histidine could have neuroprotective and antioxidant actions, respectively. To elucidate the role of decreased unknown metabolite-1 as a CD biomarker, it will be necessary to previously investigate its identity. To define and elucidate the role of acetone in pathological CD, additional laboratory and clinical studies must be performed. All these metabolites together may constitute a set of biomarkers with capability to identify pathological CD or dementia.

SIGNIFICANCE AND NOVELTY

Decrease of glutamate, tyrosine, valine, leucine, isoleucine, histidine, isobutyrate, acetone and unknown-1 metabolite together are a set of biomarkers able to identify pathological CD or dementia. Histidine, isobutyrate, acetone and unknown-1 metabolite are more specific biomarkers of CD.

TET protein inhibitors: Potential and limitations

TET proteins (methylcytosine dioxygenases) play an important role in the regulation of gene expression. Dysregulation of their activity is associated with many serious pathogenic states such as oncological diseases. Regulation of their activity by specific inhibitors could represent a promising therapeutic strategy. Therefore, this review describes various types of TET protein inhibitors in terms of their inhibitory mechanism and possible applicability. The potential and possible limitations of this approach are thoroughly discussed in the context of TET protein functionality in living systems. Furthermore, possible therapeutic strategies based on the inhibition of TET proteins are presented and evaluated, especially in the field of oncological diseases.

An Investigation into the Relationship of Circulating Gut Microbiome Molecules and Inflammatory Markers with the Risk of Incident Dementia in Later Life

The gut microbiome may be involved in the occurrence of dementia primarily through the molecular mechanisms of producing bioactive molecules and promoting inflammation. Epidemiological evidence linking gut microbiome molecules and inflammatory markers to dementia risk has been mixed, and the intricate interplay between these groups of biomarkers suggests that their joint investigation in the context of dementia is warranted. We aimed to simultaneously investigate the association of circulating levels of selected gut microbiome molecules and inflammatory markers with dementia risk. This case-cohort epidemiological study included 805 individuals (83 years, 66% women) free of dementia at baseline. Plasma levels of 19 selected gut microbiome molecules comprising lipopolysaccharide, short-chain fatty acids, and indole-containing tryptophan metabolites as well as four inflammatory markers measured at baseline were linked to incident all-cause (ACD) and Alzheimer's disease dementia (AD) in binary outcomes and time-to-dementia analyses. Independent of several covariates, seven gut microbiome molecules, 5-hydroxyindole-3-acetic acid, indole-3-butyric acid, indole-3-acryloylglycine, indole-3-lactic acid, indole-3-acetic acid methyl ester, isobutyric acid, and 2-methylbutyric acid, but no inflammatory markers discriminated incident dementia cases from non-cases. Furthermore, 5-hydroxyindole-3-acetic acid (hazard ratio: 0.58; 0.36-0.94, P = 0.025) was associated with time-to-ACD. These molecules underpin gut microbiome-host interactions in the development of dementia and they may be crucial in its prevention and intervention strategies. Future larger epidemiological studies are needed to confirm our findings, specifically in exploring the repeatedly measured circulating levels of these molecules and investigating their causal relationship with dementia risk.

Chronic Cerebral Hypoperfusion-Induced Disturbed Proteostasis of Mitochondria and MAM Is Reflected in the CSF of Rats by Proteomic Analysis

Declining cerebral blood flow leads to chronic cerebral hypoperfusion which can induce neurodegenerative disorders, such as vascular dementia. The reduced energy supply of the brain impairs mitochondrial functions that could trigger further damaging cellular processes. We carried out stepwise bilateral common carotid occlusions on rats and investigated long-term mitochondrial, mitochondria-associated membrane (MAM), and cerebrospinal fluid (CSF) proteome changes. Samples were studied by gel-based and mass spectrometry-based proteomic analyses. We found 19, 35, and 12 significantly altered proteins in the mitochondria, MAM, and CSF, respectively. Most of the changed proteins were involved in protein turnover and import in all three sample types. We confirmed decreased levels of proteins involved in protein folding and amino acid catabolism, such as P4hb and Hibadh in the mitochondria by western blot. We detected reduced levels of several components of protein synthesis and degradation in the CSF as well as in the subcellular fractions, implying that hypoperfusion-induced altered protein turnover of brain tissue can be detected in the CSF by proteomic analysis.

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.

The Microbiome-Gut-Brain Axis and Dementia: A Bibliometric Analysis

BACKGROUND

Associations between the microbiome-gut-brain axis and dementia have attracted considerable attention in research literature. This study examined the microbiome-gut-brain axis and dementia-related research from a bibliometric perspective.

METHODS

A search for original research and review articles on the microbiome-gut-brain axis and dementia was conducted in the Web of Science Core Collection (WOSCC) database. The R package "bibliometrix" was used to collect information on countries, institutions, authors, journals, and keywords. VOSviewer software was used to visualize the co-occurrence network of keywords.

RESULTS

Overall, 494 articles met the study inclusion criteria, with an average of 29.64 citations per article. Corresponding authors of published articles were mainly from China, the United States and Italy. Zhejiang University in China and Kyung Hee University in Korea were the most active institutions, while the Journal of Alzheimer's Disease and Nutrients published the most articles in this field. Expected main search terms, "Parkinson disease" and "chain fatty-acids" were high-frequency keywords that indicate current and future research directions in this field.

CONCLUSIONS

This bibliometric study helped researchers to identify the key topics and trends in the microbiome-gut-brain axis and dementia-related research. High-frequency keywords identified in this study reflect current trends and possible future directions in this field related to methodologies, mechanisms and populations of interest.

Exploration of the Gut-Brain Axis through Metabolomics Identifies Serum Propionic Acid Associated with Higher Cognitive Decline in Older Persons

The gut microbiome is involved in nutrient metabolism and produces metabolites that, via the gut−brain axis, signal to the brain and influence cognition. Human studies have so far had limited success in identifying early metabolic alterations linked to cognitive aging, likely due to limitations in metabolite coverage or follow-ups. Older persons from the Three-City population-based cohort who had not been diagnosed with dementia at the time of blood sampling were included, and repeated measures of cognition over 12 subsequent years were collected. Using a targeted metabolomics platform, we identified 72 circulating gut-derived metabolites in a case−control study on cognitive decline, nested within the cohort (discovery n = 418; validation n = 420). Higher serum levels of propionic acid, a short-chain fatty acid, were associated with increased odds of cognitive decline (OR for 1 SD = 1.40 (95% CI 1.11, 1.75) for discovery and 1.26 (1.02, 1.55) for validation). Additional analyses suggested mediation by hypercholesterolemia and diabetes. Propionic acid strongly correlated with blood glucose (r = 0.79) and with intakes of meat and cheese (r > 0.15), but not fiber (r = 0.04), suggesting a minor role of prebiotic foods per se, but a possible link to processed foods, in which propionic acid is a common preservative. The adverse impact of propionic acid on metabolism and cognition deserves further investigation.

Dietary Fiber Modulates the Release of Gut Bacterial Products Preventing Cognitive Decline in an Alzheimer's Mouse Model

Fiber intake is associated with a lower risk for Alzheimer´s disease (AD) in older adults. Intake of plant-based diets rich in soluble fiber promotes the production of short-chain fatty acids (SCFAs: butyrate, acetate, propionate) by gut bacteria. Butyrate administration has antiinflammatory actions, but propionate promotes neuroinflammation. In AD patients, gut microbiota dysbiosis is a common feature even in the prodromal stages of the disease. It is unclear whether the neuroprotective effects of fiber intake rely on gut microbiota modifications and specific actions of SCFAs in brain cells. Here, we show that restoration of the gut microbiota dysbiosis through the intake of soluble fiber resulted in lower propionate and higher butyrate production, reduced astrocyte activation and improved cognitive function in 6-month-old male APP/PS1 mice. The neuroprotective effects were lost in antibiotic-treated mice. Moreover, propionate promoted higher glycolysis and mitochondrial respiration in astrocytes, while butyrate induced a more quiescent metabolism. Therefore, fiber intake neuroprotective action depends on the modulation of butyrate/propionate production by gut bacteria. Our data further support and provide a mechanism to explain the beneficial effects of dietary interventions rich in soluble fiber to prevent dementia and AD. Fiber intake restored the concentration of propionate and butyrate by modulating the composition of gut microbiota in male transgenic (Tg) mice with Alzheimer´s disease. Gut dysbiosis was associated with intestinal damage and high propionate levels in control diet fed-Tg mice. Fiber-rich diet restored intestinal integrity and promoted the abundance of butyrate-producing bacteria. Butyrate concentration was associated with better cognitive performance in fiber-fed Tg mice. A fiber-rich diet may prevent the development of a dysbiotic microbiome and the related cognitive dysfunction in people at risk of developing Alzheimer´s disease.

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.

Mechanisms of Short-Chain Fatty Acids Derived from Gut Microbiota in Alzheimer's Disease

Short-chain fatty acids (SCFAs) are important metabolites derived from the gut microbiota through fermentation of dietary fiber. SCFAs participate a number of physiological and pathological processes in the human body, such as host metabolism, immune regulation, appetite regulation. Recent studies on gut-brain interaction have shown that SCFAs are important mediators of gut-brain interactions and are involved in the occurrence and development of many neurodegenerative diseases, including Alzheimer's disease. This review summarizes the current research on the potential roles and mechanisms of SCFAs in AD. First, we introduce the metabolic distribution, specific receptors and signaling pathways of SCFAs in human body. The concentration levels of SCFAs in AD patient/animal models are then summarized. In addition, we illustrate the effects and mechanisms of SCFAs on the cognitive level, pathological features (Aβ and tau) and neuroinflammation in AD. Finally, we analyze the translational value of SCFAs as potential therapeutic targets for the treatment of AD.

Sample optimization for saliva 1H-NMR metabolic profiling

Nuclear Magnetic Resonance (NMR) based metabolomic analysis of whole saliva has provided potential diagnostic biomarkers for numerous human diseases contributing to a better understanding of their mechanisms. However, a comprehensive interpretation of the significance of metabolites in whole, parotid, and submandibular/sublingual saliva subtypes is still missing. Precision and reproducibility of sample preparation is an essential step. Here, we present a simple and efficient protocol for saliva 1H-NMR metabolic profiling. This procedure has been specifically designed and optimized for the identification and quantification of low concentration metabolites (as low as 1.1 μM) and is suitable for all the saliva subtypes.

Predicting Satiety from the Analysis of Human Saliva Using Mid-Infrared Spectroscopy Combined with Chemometrics

The aim of this study was to evaluate the ability of mid-infrared (MIR) spectroscopy combined with chemometrics to analyze unstimulated saliva as a method to predict satiety in healthy participants. This study also evaluated features in saliva that were related to individual perceptions of human–food interactions. The coefficient of determination (R²) and standard error in cross validation (SECV) for the prediction of satiety in all saliva samples were 0.62 and 225.7 satiety area under the curve (AUC), respectively. A correlation between saliva and satiety was found, however, the quantitative prediction of satiety using unstimulated saliva was not robust. Differences in the MIR spectra of saliva between low and high satiety groups, were observed in the following frequency ratios: 1542/2060 cm⁻¹ (total protein), 1637/3097 cm⁻¹ (α-amino acids), and 1637/616 (chlorides) cm⁻¹. In addition, good to excellent models were obtained for the prediction of satiety groups defined as low or high satiety participants (R² 0.92 and SECV 0.10), demonstrating that this method could be used to identify low or high satiety perception types and to select participants for appetite studies. Although quantitative PLS calibration models were not achieved, a qualitative model for the prediction of low and high satiety perception types was obtained using PLS-DA. Furthermore, this study showed that it might be possible to evaluate human/food interactions using MIR spectroscopy as a rapid and cost-effective tool.

Salivary Proteomics Identifies Transthyretin as a Biomarker of Early Dementia Conversion

Background:

Alzheimer’s disease (AD) remains to date an incurable disease with a long asymptomatic phase. Early diagnosis in peripheral biofluids has emerged as key for identifying subjects at risk and developing therapeutics and preventative approaches.

Objective:

We apply proteomics discovery to identify salivary diagnostic biomarkers for AD, which are suitable for self-sampling and longitudinal biomonitoring during aging.

Methods:

57 participants were recruited for the study and were categorized into Cognitively normal (CNh) (n = 19), mild cognitive impaired (MCI) (n = 21), and Alzheimer’s disease (AD) (n = 17). On a subset of subjects, 3 CNh and 3 mild AD, shot-gun filter aided sample preparation (FASP) proteomics and liquid chromatography mass spectroscopy (LC-MS/MS) was employed in saliva and cerebrospinal fluid (CSF) to identify neural-derived proteins. The protein level of salivary Transthyretin (TTR) was validated using western blot analysis across groups.

Results:

We found that 19.8% of the proteins in saliva are shared with CSF. When we compared the saliva and CSF proteome, 24 hits were decreased with only one protein expressed more. Among the differentially expressed proteins, TTR with reported function in amyloid misfolding, shows a significant drop in AD samples, confirmed by western blot showing a 0.5-fold reduction in MCI and AD compared to CNh.

Conclusion:

A reduction in salivary TTR appears with the onset of cognitive symptoms. More in general, the proteomic profiling of saliva shows a plethora of biomarkers worth pursuing as non-invasive hallmarks of dementia in the preclinical stage.

Applied machine learning in Alzheimer's disease research: omics, imaging, and clinical data

Alzheimer's disease (AD) remains a devastating neurodegenerative disease with few preventive or curative treatments available. Modern technology developments of high-throughput omics platforms and imaging equipment provide unprecedented opportunities to study the etiology and progression of this disease. Meanwhile, the vast amount of data from various modalities, such as genetics, proteomics, transcriptomics, and imaging, as well as clinical features impose great challenges in data integration and analysis. Machine learning (ML) methods offer novel techniques to address high dimensional data, integrate data from different sources, model the etiological and clinical heterogeneity, and discover new biomarkers. These directions have the potential to help us better manage the disease progression and develop novel treatment strategies. This mini-review paper summarizes different ML methods that have been applied to study AD using single-platform or multi-modal data. We review the current state of ML applications for five key directions of AD research: disease classification, drug repurposing, subtyping, progression prediction, and biomarker discovery. This summary provides insights about the current research status of ML-based AD research and highlights potential directions for future research.

The Endocannabinoid System: A Bridge between Alzheimer's Disease and Gut Microbiota

Alzheimer's disease (AD) is a neurodegenerative disease that progresses from mild cognitive impairment to severe dementia over time. The main clinical hallmarks of the disease (e.g., beta-amyloid plaques and neurofibrillary tangles) begin during preclinical AD when cognitive deficits are not yet apparent. Hence, a more profound understanding of AD pathogenesis is needed to develop new therapeutic strategies. In this context, the endocannabinoid (eCB) system and the gut microbiome are increasingly emerging as important players in maintaining the general homeostasis and the health status of the host. However, their interaction has come to light just recently with gut microbiota regulating the eCB tone at both receptor and enzyme levels in intestinal and adipose tissues. Importantly, eCB system and gut microbiome, have been suggested to play a role in AD in both animal and human studies. Therefore, the microbiome gut-brain axis and the eCB system are potential common denominators in the AD physiopathology. Hence, the aim of this review is to provide a general overview on the role of both the eCB system and the microbiome gut-brain axis in AD and to suggest possible mechanisms that underlie the potential interplay of these two systems.

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.

Gut Microbiota Alterations and Cognitive Impairment Are Sexually Dissociated in a Transgenic Mice Model of Alzheimer's Disease

BACKGROUND

Normal aging is accompanied by cognitive deficiencies, affecting women and men equally. Aging is the main risk factor for Alzheimer's disease (AD), with women having a higher risk. The higher prevalence of AD in women is associated with the abrupt hormonal decline seen after menopause. However, other factors may be involved in this sex-related cognitive decline. Alterations in gut microbiota (GM) and its bioproducts have been reported in AD subjects and transgenic (Tg) mice, having a direct impact on brain amyloid-β pathology in male (M), but not in female (F) mice.

OBJECTIVE

The aim of this work was to determine GM composition and cognitive dysfunction in M and F wildtype (WT) and Tg mice, in a sex/genotype segregation design.

METHODS

Anxiety, short term working-memory, spatial learning, and long-term spatial memory were evaluated in 6-month-old WT and Tg male mice. Fecal short chain fatty acids were determined by chromatography, and DNA sequencing and bioinformatic analyses were used to determine GM differences.

RESULTS

We observed sex-dependent differences in cognitive skills in WT mice, favoring F mice. However, the cognitive advantage of females was lost in Tg mice. GM composition showed few sex-related differences in WT mice. Contrary, Tg-M mice presented a more severe dysbiosis than Tg-F mice. A decreased abundance of Ruminococcaceae was associated with cognitive deficits in Tg-F mice, while butyrate levels were positively associated with better working- and object recognition-memory in WT-F mice.

CONCLUSION

This report describes a sex-dependent association between GM alterations and cognitive impairment in a mice model of AD.

Towards personalised saliva spectral fingerprints: Comparison of mid infrared spectra of dried and whole saliva samples

The aims of this study were to compare two sample presentations (dry and whole) as well as the effects of both gender and age on the mid infrared (MIR) fingerprint spectra of human saliva. Unstimulated saliva was collected from 52 Female (31 subjects, aged 40.9 ± 14.6 year) and Male (21 subjects, aged 34 ± 11.8 year) participants, stored frozen, and subsequently thawed and analysed by MIR spectroscopy as whole and dried saliva, respectively. Data were analysed by means of principal components analysis (PCA) and partial least squares (PLS) to interpret and compare the effects of presentation (dry vs whole), age and gender on the MIR spectra of saliva. Interpretation of the MIR spectra of both whole and dried samples revealed specific characteristic and different spectral signals when gender and age were compared in the amide I and amide II of proteins (e.g. albumin) and DNA. While whole saliva analysis might be more convenient for rapid test, dried saliva spectra were more consistent across replicates, demonstrating greater ability to distinguish individual differences. The interpretation of the PCA and PLS loadings of both whole and dried saliva samples allowed identification of specific MIR regions associated with age and gender of participants between 1000 cm^-1 and 1800 cm^-1. In particular, the MIR regions associated with the absorption of polysaccharides, glycosylated proteins, and nucleic acid phosphate groups present in saliva were the most dominant. This paper demonstrates that MIR spectroscopy can be used to measure saliva samples and to interpret individual differences in participants due to age in either dry or whole samples. No clear trends were observed in the MIR spectra of the samples associated with gender when all samples were analysed together. However, PLS regression models were able to predict gender in a subset of samples having similar age. The approach described in this study shows promise for potentially using saliva as a tool in food studies (e.g. saliva interactions between food and consumers).

Salivary Aβ Secretion and Altered Oral Microbiome in Mouse Models of AD

BACKGROUND

Beta amyloid (Aβ) peptide containing plaque aggregations in the brain are a hallmark of Alzheimer's Disease (AD). However, Aβ is produced by cell types outside of the brain suggesting that the peptide may serve a broad physiologic purpose.

OBJECTIVE

Based upon our prior work documenting expression of amyloid β precursor protein (APP) in intestinal epithelium we hypothesized that salivary epithelium might also express APP and be a source of Aβ.

METHODS

To begin testing this idea, we compared human age-matched control and AD salivary glands to C57BL/6 wild type, App^NL-G-F , and APP/PS1 mice.

RESULTS

Both male and female AD, App^NL-G-F , and APP/PS1 glands demonstrated robust APP and Aβ immunoreactivity. Female App^NL-G-F mice had significantly higher levels of pilocarpine stimulated Aβ 1-42 compared to both wild type and APP/PS1 mice. No differences in male salivary Aβ levels were detected. No significant differences in total pilocarpine stimulated saliva volumes were observed in any group. Both male and female App^NL-G-F but not APP/PS1 mice demonstrated significant differences in oral microbiome phylum and genus abundance compared to wild type mice. Male, but not female, APP/PS1 and App^NL-G-F mice had significantly thinner molar enamel compared to their wild type counterparts.

CONCLUSION

These data support the idea that oral microbiome changes exist during AD in addition to changes in salivary Aβ and oral health.

Propionate and Alzheimer's Disease

Propionate, a short-chain fatty acid, serves important roles in the human body. However, our review of the current literature suggests that under certain conditions, excess levels of propionate may play a role in Alzheimer's disease (AD). The cause of the excessive levels of propionate may be related to the Bacteroidetes phylum, which are the primary producers of propionate in the human gut. Studies have shown that the relative abundance of the Bacteroidetes phylum is significantly increased in older adults. Other studies have shown that levels of the Bacteroidetes phylum are increased in persons with AD. Studies on the diet, medication use, and propionate metabolism offer additional potential causes. There are many different mechanisms by which excess levels of propionate may lead to AD, such as hyperammonemia. These mechanisms offer potential points for intervention.

Salivary metabolomics for the diagnosis of periodontal diseases: a systematic review with methodological quality assessment

INTRODUCTION

Early diagnosis of periodontitis by means of a rapid, accurate and non-invasive method is highly desirable to reduce the individual and epidemiological burden of this largely prevalent disease.

OBJECTIVES

The aims of the present systematic review were to examine potential salivary metabolic biomarkers and pathways associated to periodontitis, and to assess the accuracy of salivary untargeted metabolomics for the diagnosis of periodontal diseases.

METHODS

Relevant studies identified from MEDLINE (PubMed), Embase and Scopus databases were systematically examined for analytical protocols, metabolic biomarkers and results from the multivariate analysis (MVA). Pathway analysis was performed using the MetaboAnalyst online software and quality assessment by means of a modified version of the QUADOMICS tool.

RESULTS

Twelve studies met the inclusion criteria, with sample sizes ranging from 19 to 130 subjects. Compared to periodontally healthy individuals, valine, phenylalanine, isoleucine, tyrosine and butyrate were found upregulated in periodontitis patients in most studies; while lactate, pyruvate and N-acetyl groups were the most significantly expressed in healthy individuals. Metabolic pathways that resulted dysregulated are mainly implicated in inflammation, oxidative stress, immune activation and bacterial energetic metabolism. The findings from MVA revealed that periodontitis is characterized by a specific metabolic signature in saliva, with coefficients of determination ranging from 0.52 to 0.99.

CONCLUSIONS

This systematic review summarizes candidate metabolic biomarkers and pathways related to periodontitis, which may provide opportunities for the validation of diagnostic or predictive models and the discovery of novel targets for monitoring and treating such a disease (PROSPERO CRD42020188482).

Mental Disorders, Cognitive Impairment and the Risk of Suicide in Older Adults

More than 600 million people are aged 60 years and over are living in the world. The World Health Organization estimates that this number will double by 2025 to 2 billion older people. Suicide among people over the age of 60 is one of the most acute problems. The factors strongly associated with suicide are mentioned: physical illnesses, such as cancer, neurologic disorder, pain, liver disease, genital disorders, or rheumatoid disorders. Moreover, neurologic conditions, especially stroke, may affect decision-making processes, cognitive capacity, and language deficit. In addition to dementia, the most common mental disorders are mood and anxiety disorders. A common symptom of these disorders in the elderly is cognitive impairment. This study aimed to present the relationship between cognitive impairment due to dementia, mood disorders and anxiety, and an increased risk of suicide among older people. Dementia is a disease where the risk of suicide is significant. Many studies demonstrated that older adults with dementia had an increased risk of suicide death than those without dementia. Similar conclusions apply to prodromal dementia Depression is also a disease with a high risk of suicide. Many researchers found that a higher level of depression was associated with suicide attempts and suicide ideation. Bipolar disorder is the second entity in mood disorders with an increased risk of suicide among the elderly. Apart from suicidal thoughts, bipolar disorder is characterized by high mortality. In the group of anxiety disorders, the most significant risk of suicide occurs when depression is present. In turn, suicide thoughts are more common in social phobia than in other anxiety disorders. Suicide among the elderly is a serious public health problem. There is a positive correlation between mental disorders such as dementia, depression, bipolar disorder, or anxiety and the prevalence of suicide in the elderly. Therefore, the elderly should be comprehensively provided with psychiatric and psychological support.

Evaluation of Saliva Stability for NMR Metabolomics: Collection and Handling Protocols

Maintaining a salivary metabolic profile upon sample collection and preparation is determinant in metabolomics. Nuclear magnetic resonance (NMR) spectroscopy was used to identify metabolite changes during short-term storage, at room temperature (RT)/4 °C/-20 °C, and after sample preparation, at RT/4 °C (mimicking typical clinical/laboratory settings). Interestingly, significant metabolic inter-individual and inter-day variability were noted, probably determining sample stability to some extent. After collection, no changes were noted at -20 °C (at least for 4 weeks). RT storage induced decreases in methylated macromolecules (6 h); lactate (8 h); alanine (12 h); galactose, hypoxanthine, pyruvate (24 h); sarcosine, betaine, choline, N-acetyl-glycoproteins (48 h), while acetate increased (48 h). Less, but different, changes were observed at 4 °C, suggesting different oral and microbial status at different temperatures (with a possible contribution from inter-individual and inter-day variability), and identifying galactose, hypoxanthine, and possibly, choline esters, as potential general stability indicators. After preparation, addition of NaN3 did not impact significantly on saliva stabilization, neither at RT nor at 4 °C, although its absence was accompanied by slight increases in fucose (6.5 h) and proline (8 h) at RT, and in xylose (24 h) at 4 °C. The putative metabolic origins of the above variations are discussed, with basis on the salivary microbiome. In summary, after collection, saliva can be stored at RT/4 °C for up to 6 h and at -20 °C for at least 4 weeks. Upon preparation for NMR analysis, samples are highly stable at 25 °C up to 8 h and at 4 °C up to 48 h, with NaN3 addition preventing possible early changes in fucose, proline (6-8 h), and xylose (24 h) levels.

Changes in the Salivary Metabolic Profile of Generalized Periodontitis Patients after Non-surgical Periodontal Therapy: A Metabolomic Analysis Using Nuclear Magnetic Resonance Spectroscopy

Pattern analysis of the salivary metabolic profile has been proven accurate in discriminating between generalized periodontitis (GP) patients and healthy individuals (HI), as this disease modifies the salivary concentrations of specific metabolites. Due to the scarcity of data from previous studies, this study aimed to evaluate if non-surgical periodontal therapy (NST) could affect the metabolomic profile in GP patients’ saliva and if it compares to that of HI. Unstimulated salivary samples were collected from 11 HI and 12 GP patients before and 3 months after NST. Nuclear Magnetic Resonance (NMR) spectroscopy, followed by a supervised multivariate statistical approach on entire saliva spectra and partial least square (PLS) discriminant analysis, were performed to obtain metabolic profiles. In the GP group, periodontal treatment improved all clinical parameters, but not all the diseased sites were eradicated. PLS revealed an accuracy of 100% in distinguishing between metabolic profiles of GP patients before and after NST. Orthogonal projection to latent structure was able to discriminate between the three groups of subjects with an accuracy of 85.6%. However, the post-NST metabolic profile of GP patients could not be completely assimilated to that of HI. Although NST may produce significant changes in the metabolic profile, GP patients maintained a distinctive fingerprint compared to HI.

Biological and environmental predictors of heterogeneity in neurocognitive ageing: Evidence from Betula and other longitudinal studies

Individual differences in cognitive performance increase with advancing age, reflecting marked cognitive changes in some individuals along with little or no change in others. Genetic and lifestyle factors are assumed to influence cognitive performance in ageing by affecting the magnitude and extent of age-related brain changes (i.e., brain maintenance or atrophy), as well as the ability to recruit compensatory processes. The purpose of this review is to present findings from the Betula study and other longitudinal studies, with a focus on clarifying the role of key biological and environmental factors assumed to underlie individual differences in brain and cognitive ageing. We discuss the vital importance of sampling, analytic methods, consideration of non-ignorable dropout, and related issues for valid conclusions on factors that influence healthy neurocognitive ageing.

Urine Untargeted Metabolomic Profiling Is Associated with the Dietary Pattern of Successful Aging among Malaysian Elderly

Food intake biomarkers (FIBs) can reflect the intake of specific foods or dietary patterns (DP). DP for successful aging (SA) has been widely studied. However, the relationship between SA and DP characterized by FIBs still needs further exploration as the candidate markers are scarce. Thus, 1H-nuclear magnetic resonance (¹H-NMR)-based urine metabolomics profiling was conducted to identify potential metabolites which can act as specific markers representing DP for SA. Urine sample of nine subjects from each three aging groups, SA, usual aging (UA), and mild cognitive impairment (MCI), were analyzed using the ¹H-NMR metabolomic approach. Principal components analysis (PCA) and partial least-squares discriminant analysis (PLS-DA) were applied. The association between SA urinary metabolites and its DP was assessed using the Pearson’s correlation analysis. The urine of SA subjects was characterized by the greater excretion of citrate, taurine, hypotaurine, serotonin, and melatonin as compared to UA and MCI. These urinary metabolites were associated with alteration in “taurine and hypotaurine metabolism” and “tryptophan metabolism” in SA elderly. Urinary serotonin (r = 0.48, p < 0.05) and melatonin (r = 0.47, p < 0.05) were associated with oat intake. These findings demonstrate that a metabolomic approach may be useful for correlating DP with SA urinary metabolites and for further understanding of SA development.

Acyl-Alkyl-Phosphatidlycholines are Decreased in Saliva of Patients with Alzheimer's Disease as Identified by Targeted Metabolomics

Diagnosis of Alzheimer's disease (AD) is still a challenge. Salivary analysis could produce an easily accessible and inexpensive possibility to study metabolic changes in AD. In the present pilot study, we show for the first time using targeted metabolomics that acyl-alkyl phosphatidylcholines (PCae C34:1-2; PCae C36:1-2-3; PCaeC38:1c3; PCae C40:2-3) are significantly reduced in saliva of AD patients (n = 25) compared to healthy controls (n = 25). Saliva levels of PCae C36Λ1-2-3) were also decreased in patients with mild cognitive impairment (n = 25). No changes were seen for saliva diacyl-phosphatidylcholines, lyso-acyl-phosphatidylcholines, and sphinogomyelins. These data suggest specific lipid changes in the saliva of AD patients, thus salivary measures could establish new biomarkers. However, these preliminary results have to be established in larger scale studies.

Biochemical analysis of oral fluids for disease detection

The field of diagnostics using invasive blood testing represents the majority of diagnostic tests used as part of routine health monitoring. The relatively recent introduction of salivary diagnostics has lead to a major paradigm shift in diagnostic analyses. Additionally, in this era of big data, oral fluid testing has shown promising outcomes in a number of fields, particularly the areas of genomics, microbiomics, proteomics, metabolomics, and transcriptomics. Despite the analytical challenges involved in the interpretation of large datasets generated from biochemical studies involving bodily fluids, including saliva, many studies have identified novel oral biomarkers for diagnosing oral and systemic diseases. In this regard, oral biofluids, including saliva, gingival crevicular fluid (GCF), peri-implant crevicular fluid (PICF), dentinal tubular fluid (DTF), are now attracting increasing attention due to their important attributes, such as noninvasive sampling, easy handling, low cost, and more accurate diagnosis of oral diseases. Recently, the utilization of salivary diagnostics to evaluate systemic diseases and monitor general health has increased in popularity among clinicians. Saliva contains a wide range of protein, DNA and RNA biomarkers, which assist in the diagnosis of multiple diseases and conditions, including cancer, cardiovascular diseases (CVD), auto-immune and degenerative diseases, respiratory infections, oral diseases, and microbial (viral, bacterial and fungal) diseases. Moreover, due to its noninvasive nature and ease-of-adoption by children, it is now being used in mass screening programs, oral health-related studies and clinical trials in support of the development of therapeutic agents. The recent advent of highly sensitive technologies, such as next-generation sequencing, mass spectrometry, highly sensitives ELISAs, and homogeneous immunoassays, suggests that even small quantities of salivary biomarkers are able to be assayed accurately, providing opportunities for the development of many future diagnostic applications (including emerging technologies, such as point-of-care and rapid molecular technologies). The present article explores the omics and biochemical compositions of various oral biofluids with important value in diagnostics and monitoring.

Intraoral Microbial Metabolism and Association with Host Taste Perception

Metabolomics has been identified as a means of functionally assessing the net biological activity of a particular microbial community. Considering the oral microbiome, such an approach remains largely underused. While the current knowledge of the oral microbiome is constantly expanding, there are several deficits in knowledge particularly relating to their interactions with their host. This work uses nuclear magnetic resonance spectroscopy to investigate metabolic differences between oral microbial metabolism of endogenous (i.e., salivary protein) and exogenous (i.e., dietary carbohydrates) substrates. It also investigated whether microbial generation of different metabolites may be associated with host taste perception. This work found that in the absence of exogenous substrate, oral bacteria readily catabolize salivary protein and generate metabolic profiles similar to those seen in vivo. Important metabolites such as acetate, butyrate, and propionate are generated at relatively high concentrations. Higher concentrations of metabolites were generated by tongue biofilm compared to planktonic salivary bacteria. Thus, as has been postulated, metabolite production in proximity to taste receptors could reach relatively high concentrations. In the presence of 0.25 M exogenous sucrose, increased catabolism was observed with increased concentrations of a range of metabolites relating to glycolysis (lactate, pyruvate, succinate). Additional pyruvate-derived molecules such as acetoin and alanine were also increased. Furthermore, there was evidence that individual taste sensitivity to sucrose was related to differences in the metabolic fate of sucrose in the mouth. High-sensitivity perceivers appeared more inclined toward continual citric acid cycle activity postsucrose, whereas low-sensitivity perceivers had a more efficient conversion of pyruvate to lactate. This work collectively indicates that the oral microbiome exists in a complex balance with the host, with fluctuating metabolic activity depending on nutrient availability. There is preliminary evidence of an association between host behavior (sweet taste perception) and oral catabolism of sugar.

Role of mtDNA disturbances in the pathogenesis of Alzheimer's and Parkinson's disease

Neurodegenerative diseases (e.g. Alzheimer's and Parkinson's disease) are becoming increasingly problematic to healthcare systems. Therefore, their underlying mechanisms are trending topics of study in medicinal research. Numerous studies have evidenced a strong association between mitochondrial DNA disturbances (e.g. oxidative damage, mutations, and methylation shifts) and the initiation and progression of neurodegenerative diseases. Therefore, this review discusses the risk and development of neurodegenerative diseases in terms of disturbances in mitochondrial DNA and as a part of a complex ecosystem that includes other important mechanisms (e.g. neuroinflammation and the misfolding and aggregation of amyloid-β peptides, α-synuclein, and tau proteins). In addition, the influence of individual mitochondrial DNA haplogroups on the risk and development of neurodegenerative diseases is also described and discussed.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

Current State of Saliva Biomarkers for Aging and Alzheimer's Disease

INTRODUCTION

Aging is the primary risk factor for major human pathologies, including cancer, diabetes, cardiovascular diseases, and neurodegenerative diseases such as Alzheimer's Disease (AD). AD is a progressive degenerative disorder of the brain and is the most common form of dementia.

METHODS

To-date no simple, inexpensive and minimally invasive procedure is available to confirm with certainty the early diagnosis of AD prior to the manifestations of symptoms characteristic of the disease. Therefore, if population screening of individuals is to be performed, easily accessible tissues would need to be used for a diagnostic test that would identify those who exhibit altered or aberrant aging profiles that may be indicative of AD risk, so that they can be prioritized for primary prevention. This need for minimally invasive tests could be achieved by targeting saliva, since it is now well recognized that many aging diseases including AD are associated with peripheral biomarkers that are not only restricted to pathology and biomarkers within the brain.

RESULTS

Therefore, the aim of this review is to summarize some of the main findings of salivary biomarkers of aging and AD; including various proteins, metabolites, and alterations to DNA and miRNA. The future of healthy aging resides in innovative platforms, biosensors and point-of-care devices that can extract real time information on the health status of an individual. Those platforms may be achieved through the development and validation of novel biomarkers of health using saliva which, although being the least explored for biomedical purposes, has the distinct advantage that it can be self-collected in a non-invasive manner.

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.

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

INTRODUCTION

Parkinson's disease (PD) is a multisystem disorder of unknown etiology, highlights a broad array of symptoms and pathological features influencing organs throughout the body. The metabolic profile of saliva in patients with PD may be influenced by malabsorption in the gastroenteric tract, neurodegeneration, and mitochondrial dysfunction. In the present study, we apply a powerful NMR metabolomics approach for biomarker identification in PD using saliva, a non-invasive bio-fluid.

METHODS

Metabolic profiling of saliva were studied in patients with PD (n = 76) and healthy controls (HC, n = 37) were analyzed and differentiated PD from HC. A total of 40 metabolites including aromatic amino acids, short-chain fatty acids, branched chain amino acids, taurine, and N-acetylglutamate were identified. Spectral binned data and concentration of metabolites were estimated for analysis.

RESULTS

Increased concentration of phenylalanine, tyrosine, histidine, glycine, acetoacetate, taurine, TMAO, GABA, N-acetylglutamate, acetoin, acetate, alanine, fucose, propionate, isoleucine, and valine were observed in PD as compared to HC. Further, subgroup analysis among early PD, advanced PD, and HC groups, revealed increased metabolite concentration in early PD group as compared to advanced PD and HC group.

DISCUSSION

Analysis revealed potential biomarkers and their involvement in amino acid metabolism, energy metabolism, neurotransmitters metabolism, and microflora system. Patients with early PD exhibited higher metabolite concentration as compared to advanced PD group which might be associated with dopaminergic treatment.

CONCLUSION

The results of our data indicate that patients with PD might be characterized by metabolic imbalances like gut microflora system, energy metabolites, and neurotransmitters which may contribute to the PD pathogenesis.

Metabolomics technology and bioinformatics for precision medicine

Precision medicine is rapidly emerging as a strategy to tailor medical treatment to a small group or even individual patients based on their genetics, environment and lifestyle. Precision medicine relies heavily on developments in systems biology and omics disciplines, including metabolomics. Combination of metabolomics with sophisticated bioinformatics analysis and mathematical modeling has an extreme power to provide a metabolic snapshot of the patient over the course of disease and treatment or classifying patients into subpopulations and subgroups requiring individual medical treatment. Although a powerful approach, metabolomics have certain limitations in technology and bioinformatics. We will review various aspects of metabolomics technology and bioinformatics, from data generation, bioinformatics analysis, data fusion and mathematical modeling to data management, in the context of precision medicine.

Bioactive Food Abates Metabolic and Synaptic Alterations by Modulation of Gut Microbiota in a Mouse Model of Alzheimer's Disease

Recent investigations have demonstrated an important role of gut microbiota (GM) in the pathogenesis of Alzheimer's disease (AD). GM modulates a host's health and disease by production of several substances, including lipopolysaccharides (LPS) and short-chain fatty acids (SCFAs), among others. Diet can modify the composition and diversity of GM, and ingestion of a healthy diet has been suggested to lower the risk to develop AD. We have previously shown that bioactive food (BF) ingestion can abate neuroinflammation and oxidative stress and improve cognition in obese rats, effects associated with GM composition. Therefore, BF can impact the gut-brain axis and improved behavior. In this study, we aim to explore if inclusion of BF in the diet may impact central pathological markers of AD by modulation of the GM. Triple transgenic 3xTg-AD (TG) female mice were fed a combination of dried nopal, soy, chia oil, and turmeric for 7 months. We found that BF ingestion improved cognition and reduced Aβ aggregates and tau hyperphosphorylation. In addition, BF decreased MDA levels, astrocyte and microglial activation, PSD-95, synaptophysin, GluR1 and ARC protein levels in TG mice. Furthermore, TG mice fed BF showed increased levels of pGSK-3β. GM analysis revealed that pro-inflammatory bacteria were more abundant in TG mice compared to wild-type, while BF ingestion was able to restore the GM's composition, LPS, and propionate levels to control values. Therefore, the neuroprotective effects of BF may be mediated, in part, by modulation of GM and the release of neurotoxic substances that alter brain function.

Untargeted Urinary 1H NMR-Based Metabolomic Pattern as a Potential Platform in Breast Cancer Detection

Breast cancer (BC) remains the second leading cause of death among women worldwide. An emerging approach based on the identification of endogenous metabolites (EMs) and the establishment of the metabolomic fingerprint of biological fluids constitutes a new frontier in medical diagnostics and a promising strategy to differentiate cancer patients from healthy individuals. In this work we aimed to establish the urinary metabolomic patterns from 40 BC patients and 38 healthy controls (CTL) using proton nuclear magnetic resonance spectroscopy (1H-NMR) as a powerful approach to identify a set of BC-specific metabolites which might be employed in the diagnosis of BC. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied to a 1H-NMR processed data matrix. Metabolomic patterns distinguished BC from CTL urine samples, suggesting a unique metabolite profile for each investigated group. A total of 10 metabolites exhibited the highest contribution towards discriminating BC patients from healthy controls (variable importance in projection (VIP) >1, p < 0.05). The discrimination efficiency and accuracy of the urinary EMs were ascertained by receiver operating characteristic curve (ROC) analysis that allowed the identification of some metabolites with the highest sensitivities and specificities to discriminate BC patients from healthy controls (e.g. creatine, glycine, trimethylamine N-oxide, and serine). The metabolomic pathway analysis indicated several metabolism pathway disruptions, including amino acid and carbohydrate metabolisms, in BC patients, namely, glycine and butanoate metabolisms. The obtained results support the high throughput potential of NMR-based urinary metabolomics patterns in discriminating BC patients from CTL. Further investigations could unravel novel mechanistic insights into disease pathophysiology, monitor disease recurrence, and predict patient response towards therapy.

Saliva, an easily accessible fluid as diagnostic tool and potent stem cell source for Alzheimer's Disease: Present and future applications

Alzheimer's disease (AD) is a progressive and multifactorial disease. Many scientific advances have advanced our understanding of the pathogenesis of AD. However, the clinical diagnosis of AD remains difficult, with only post-mortem assays confirming its definitive diagnosis. There is a crucial need for an early and accurate detection of AD related symptoms. To date, current diagnosis techniques are costly or invasive. Finding a peripheral biomarker that could provide a sensitive, reproducible, and accurate detection prior to the onset of the AD clinical symptoms will allow identification of "at risk" individuals, thereby facilitating early initiation of treatments that may prove more effective. Salivary glands contain stem cells, which are affected by aging, suggesting that tissue samples from these glands may reveal a stem cell biomarker of AD, but also stem cells may be harvested from these glands, with proper timing and isolation technique, for cell-based regenerative medicine. Alternatively, instead of the salivary glands, saliva may represent an attractive source for biomarkers due to minimal discomfort to the patient, non-invasive collection, and the possibility of cost-effective screening large populations, encouraging greater compliance in clinical trials and frequent testing. In addition, salivary glands contain stem cells, which are likely also present in the saliva, making these cells as potentially sensitive cellular biomarker of and a therapeutic agent for AD. The aim of this review is to critically analyze the use of saliva for the identification of circulating biological markers to help the diagnosis of early cognitive impairment associated with AD and to generate insights into the potential application of stem cells derived from salivary glands or saliva as therapeutics (i.e., stem cell transplantation) for the disease.

Metabolomics Analyses of Saliva Detect Novel Biomarkers of Alzheimer's Disease

Using a non-invasive biofluid (saliva), we apply a powerful metabolomics workflow for unbiased biomarker discovery in Alzheimer's disease (AD). We profile and differentiate Cognitively Normal (CN), Mild Cognitive Impairment (MCI), and AD groups. The workflow involves differential chemical isotope labeling liquid chromatography mass spectrometry using dansylation derivatization for in-depth profiling of the amine/phenol submetabolome. The total sample (N = 109) was divided in to the Discovery Phase (DP) (n = 82; 35 CN, 25 MCI, 22 AD) and a provisional Validation Phase (VP) (n = 27; 10 CN, 10 MCI, 7 AD). In DP we detected 6,230 metabolites. Pairwise analyses confirmed biomarkers for AD versus CN (63), AD versus MCI (47), and MCI versus CN (2). We then determined the top discriminating biomarkers and diagnostic panels. A 3-metabolite panel distinguished AD from CN and MCI (DP and VP: Area Under the Curve [AUC] = 1.000). The MCI and CN groups were best discriminated with a 2-metabolite panel (DP: AUC = 0.779; VP: AUC = 0.889). In addition, using positively confirmed metabolites, we were able to distinguish AD from CN and MCI with good diagnostic performance (AUC > 0.8). Saliva is a promising biofluid for both unbiased and targeted AD biomarker discovery and mechanism detection. Given its wide availability and convenient accessibility, saliva is a biofluid that can promote diversification of global AD biomarker research.

Re-thinking the Etiological Framework of Neurodegeneration

Neurodegenerative diseases are among the leading causes of disability and death worldwide. The disease-related socioeconomic burden is expected to increase with the steadily increasing life expectancy. In spite of decades of clinical and basic research, most strategies designed to manage degenerative brain diseases are palliative. This is not surprising as neurodegeneration progresses "silently" for decades before symptoms are noticed. Importantly, conceptual models with heuristic value used to study neurodegeneration have been constructed retrospectively, based on signs and symptoms already present in affected patients; a circumstance that may confound causes and consequences. Hence, innovative, paradigm-shifting views of the etiology of these diseases are necessary to enable their timely prevention and treatment. Here, we outline four alternative views, not mutually exclusive, on different etiological paths toward neurodegeneration. First, we propose neurodegeneration as being a secondary outcome of a primary cardiovascular cause with vascular pathology disrupting the vital homeostatic interactions between the vasculature and the brain, resulting in cognitive impairment, dementia, and cerebrovascular events such as stroke. Second, we suggest that the persistence of senescent cells in neuronal circuits may favor, together with systemic metabolic diseases, neurodegeneration to occur. Third, we argue that neurodegeneration may start in response to altered body and brain trophic interactions established via the hardwire that connects peripheral targets with central neuronal structures or by means of extracellular vesicle (EV)-mediated communication. Lastly, we elaborate on how lifespan body dysbiosis may be linked to the origin of neurodegeneration. We highlight the existence of bacterial products that modulate the gut-brain axis causing neuroinflammation and neuronal dysfunction. As a concluding section, we end by recommending research avenues to investigate these etiological paths in the future. We think that this requires an integrated, interdisciplinary conceptual research approach based on the investigation of the multimodal aspects of physiology and pathophysiology. It involves utilizing proper conceptual models, experimental animal units, and identifying currently unused opportunities derived from human data. Overall, the proposed etiological paths and experimental recommendations will be important guidelines for future cross-discipline research to overcome the translational roadblock and to develop causative treatments for neurodegenerative diseases.

Advances and challenges in development of precision psychiatry through clinical metabolomics on mood and psychotic disorders

Metabolomics is defined as the study of the global metabolite profile in a system under a given set of conditions. The objective of this review is to comprehensively assess the literature on metabolomics in mood disorders and schizophrenia and provide data for mental health researchers about the challenges and potentials of metabolomics. The majority of studies in metabolomics in Psychiatry uses peripheral blood or urine. The most widely used analytical techniques in metabolomics research are nuclear magnetic resonance (NMR) and mass spectrometry (MS). They are multiparametric and provide extensive structural and conformational information on multiple chemical classes. NMR is useful in untargeted analysis, which focuses on biosignatures or 'metabolic fingerprints' of illnesses. MS targeted metabolomics approach focuses on the identification and quantification of selected metabolites known to be involved in a particular metabolic pathway. The available studies of metabolomics in Schizophrenia, Bipolar Disorder and Major Depressive Disorder suggest a potential in investigating metabolic pathways involved in these diseases' pathophysiology and response to treatment, as well as its potential in biomarkers identification.

Determining bacterial and host contributions to the human salivary metabolome

Background: Salivary metabolomics is rapidly advancing.

Aim and methods: To determine the extent to which salivary metabolites reflects host or microbial metabolic activity whole-mouth saliva (WMS), parotid saliva (PS) and plasma collected contemporaneously from healthy volunteers were analysed by ¹H-NMR spectroscopy. Spectra underwent principal component analysis and k-means cluster analysis and metabolite quantification. WMS samples were cultured on both sucrose and peptide-enriched media. Correlation between metabolite concentration and bacterial load was assessed.

Results: WMS contained abundant short-chain fatty acids (SCFAs), which were minimal in PS and plasma. WMS spectral exhibited greater inter-individual variation than those of PS or plasma (6.7 and 3.6 fold, respectively), likely reflecting diversity of microbial metabolomes. WMS bacterial load correlated strongly with SCFA levels. Additional WMS metabolites including amines, amino acids and organic acids were positively correlated with bacterial load. Lactate, urea and citrate appeared to enter WMS via PS and the circulation. Urea correlated inversely with WMS bacterial load.

Conclusions: Oral microbiota contribute significantly to the WMS metabolome. Several WMS metabolites (lactate, urea and citrate) are derived from the host circulation. WMS may be particularly useful to aid diagnosis of conditions reflective of dysbiosis. WMS could also complement other gastrointestinal fluids in future metabolomic studies.

Saliva NMR metabolomics: Analytical issues in pediatric oral health research

OBJECTIVES

Saliva metabolome is a promising diagnostic tool concerning oral and systemic diseases. We aimed at establishing a suitable protocol for saliva collection and gauging the relative impacts of gender, dentition stage, and caries on the saliva metabolome of a small children cohort.

SUBJECTS AND METHODS

A nuclear magnetic resonance-based metabolomics cross-sectional study of children saliva (n = 38) compared the effects of: (a) stimulation and unstimulation conditions, and (b) collection through passive drool and using an absorbing device. Multivariate and univariate statistical analyses were applied to evaluate such effects and those related to gender, dentition stage and caries.

RESULTS

No significant differences were found between unstimulated and stimulated saliva, and the former was used for subsequent studies. Swab collection induced significant changes in sample composition, indicating passive drool as preferential. The impacts of gender and dentition stage were not significant compared to that of caries, which induced variations in the levels of 21 metabolites. These comprised amino acids and monosaccharides observed for the first time to our knowledge regarding children caries, suggesting protein hydrolysis and deglycosylation.

CONCLUSIONS

Unstimulated passive drool saliva metabolome may carry a caries signature.

Serum Metabolite Markers of Dementia Through Quantitative NMR Analysis: The Importance of Threonine-Linked Metabolic Pathways

There is a great need for diagnostic biomarkers of impending dementia. Metabolite markers in blood have been investigated in several studies, but inconclusive findings encourage further investigation, particularly in the pre-diagnostic phase. In the present study, the serum metabolomes of 110 dementia or pre-diagnostic dementia individuals and 201 healthy individuals matched for age, gender, and education were analyzed by nuclear magnetic resonance spectroscopy in combination with multivariate data analysis. 58 metabolites were quantified in each of the 311 samples. Individuals with dementia were discriminated from controls using a panel of seven metabolites, while the pre-diagnostic dementia subjects were distinguished from controls using a separate set of seven metabolites, where threonine was a common significant metabolite in both panels. Metabolite and pathway alterations specific for dementia and pre-diagnostic dementia were identified, in particular a disturbed threonine catabolism at the pre-diagnostic stage that extends to several threonine-linked pathways at the dementia stage.

Diagnosis of Alzheimer's disease utilizing amyloid and tau as fluid biomarkers

Current technological advancements in clinical and research settings have permitted a more intensive and comprehensive understanding of Alzheimer’s disease (AD). This development in knowledge regarding AD pathogenesis has been implemented to produce disease-modifying drugs. The potential for accessible and effective therapeutic methods has generated a need for detecting this neurodegenerative disorder during early stages of progression because such remedial effects are more profound when implemented during the initial, prolonged prodromal stages of pathogenesis. The aggregation of amyloid-β (Aβ) and tau isoforms are characteristic of AD; thus, they are considered core candidate biomarkers. However, research attempting to establish the reliability of Aβ and tau as biomarkers has culminated in an amalgamation of contradictory results and theories regarding the biomarker concentrations necessary for an accurate diagnosis. In this review, we consider the capabilities and limitations of fluid biomarkers collected from cerebrospinal fluid, blood, and oral, ocular, and olfactory secretions as diagnostic tools for AD, along with the impact of the integration of these biomarkers in clinical settings. Furthermore, the evolution of diagnostic criteria and novel research findings are discussed. This review is a summary and reflection of the ongoing concerted efforts to establish fluid biomarkers as a diagnostic tool and implement them in diagnostic procedures.

Markers from body fluids could help clinicians diagnose Alzheimer’s disease before cognitive decline appears. After numerous setbacks in treating advanced Alzheimer’s, researchers are eager to identify biological indicators that facilitate earlier disease detection and interception. A review by YoungSoo Kim and colleagues at Yonsei University in South Korea, explores the promise of ‘fluid biomarkers,’ which enables diagnosis using cerebrospinal fluid (CSF), blood, oral, ocular, and olfactory fluid samples. Shifts in CSF levels of amyloid beta and tau, two proteins central to Alzheimer’s pathology, can reliably monitor at-risk individuals. Although CSF collection is unpleasant for patients, it remains more promising than blood, where current data for candidate fluid biomarkers are relatively inconclusive. In this review, investigations to discover safer, cheaper, and more reliable diagnostic tools to shift treatment from alleviation to prevention are introduced.