High-Throughput Metabolomics for Discovering Potential Metabolite Biomarkers and Metabolic Mechanism from the APPswe/PS1dE9 Transgenic Model of Alzheimer’s Disease

Non-invasive Biomarkers for Early Detection of Alzheimer's Disease: a New-Age Perspective

Alzheimer's disease (AD) is a progressive neurodegenerative disorder that primarily affects the elderly population. It gradually leads to memory loss, loss of thinking ability, and an overall cognitive decline. However, exhaustive literature is available to suggest that pathological changes in the brain occur decades before the first clinical symptoms appear. This review provides insight into the non-invasive biomarkers for early detection of AD that have been successfully studied in populations across the globe. These biomarkers have been detected in the blood, saliva, breath, and urine samples. Retinal imaging techniques are also reported. In this study, PubMed and Google scholar were the databases employed using keywords "Alzheimer's disease," "neurodegeneration," "non-invasive biomarkers," "early diagnosis," "blood-based biomarkers," and "preclinical AD," among others. The evaluation of these biomarkers will provide early diagnosis of AD in the preclinical stages due to their positive correlation with brain pathology in AD. Early diagnosis with reliable and timely intervention can effectively manage this disease.

Explaining a series of models by propagating Shapley values

Local feature attribution methods are increasingly used to explain complex machine learning models. However, current methods are limited because they are extremely expensive to compute or are not capable of explaining a distributed series of models where each model is owned by a separate institution. The latter is particularly important because it often arises in finance where explanations are mandated. Here, we present Generalized DeepSHAP (G-DeepSHAP), a tractable method to propagate local feature attributions through complex series of models based on a connection to the Shapley value. We evaluate G-DeepSHAP across biological, health, and financial datasets to show that it provides equally salient explanations an order of magnitude faster than existing model-agnostic attribution techniques and demonstrate its use in an important distributed series of models setting.

Investigation of urine metabolome of BALB/c mouse infected with an avirulent strain of Toxoplasma gondii

Background

The protozoan parasite Toxoplasma gondii is a major concern for human and animal health. Although the metabolic understanding of toxoplasmosis has increased in recent years, the analysis of metabolic alterations through noninvasive methodologies in biofluids remains limited.

Methods

Here, we applied liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based metabolomics and multivariate statistical analysis to analyze BALB/c mouse urine collected from acutely infected, chronically infected and control subjects.

Results

In total, we identified 2065 and 1409 metabolites in the positive electrospray ionization (ESI +) mode and ESI − mode, respectively. Metabolomic patterns generated from principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) score plots clearly separated T. gondii-infected from uninfected urine samples. Metabolites with altered levels in urine from T. gondii-infected mice revealed changes in pathways related to amino acid metabolism, fatty acid metabolism, and nicotinate and nicotinamide metabolism.

Conclusions

This is the first study to our knowledge on urine metabolic profiling of BALB/c mouse with T. gondii infection. The urine metabolome of infected mouse is distinctive and has value in the understanding of Toxoplasmosis pathogenesis and improvement of treatment.

Graphical Abstract

Supplementary Information

The online version contains supplementary material available at 10.1186/s13071-022-05408-2.

Multiomics technologies: role in disease biomarker discoveries and therapeutics

 

Medical research has been revolutionized after the publication of the full human genome. This was the major landmark that paved the way for understanding the biological functions of different macro and micro molecules. With the advent of different high-throughput technologies, biomedical research was further revolutionized. These technologies constitute genomics, transcriptomics, proteomics, metabolomics, etc. Collectively, these high-throughputs are referred to as multi-omics technologies. In the biomedical field, these omics technologies act as efficient and effective tools for disease diagnosis, management, monitoring, treatment and discovery of certain novel disease biomarkers. Genotyping arrays and other transcriptomic studies have helped us to elucidate the gene expression patterns in different biological states, i.e. healthy and diseased states. Further omics technologies such as proteomics and metabolomics have an important role in predicting the role of different biological molecules in an organism. It is because of these high throughput omics technologies that we have been able to fully understand the role of different genes, proteins, metabolites and biological pathways in a diseased condition. To understand a complex biological process, it is important to apply an integrative approach that analyses the multi-omics data in order to highlight the possible interrelationships of the involved biomolecules and their functions. Furthermore, these omics technologies offer an important opportunity to understand the information that underlies disease. In the current review, we will discuss the importance of omics technologies as promising tools to understand the role of different biomolecules in diseases such as cancer, cardiovascular diseases, neurodegenerative diseases and diabetes.

SUMMARY POINTS

Uncommon Noninvasive Biomarkers for the Evaluation and Monitoring of the Etiopathogenesis of Alzheimer's Disease

Background:

Alzheimer´s disease (AD) is the most widespread dementia in the world, followed by vascular dementia. Since AD is a heterogeneous disease that shows several varied phenotypes, it is not easy to make an accurate diagnosis, so it arises when the symptoms are clear and the disease is already very advanced. Therefore, it is important to find out biomarkers for AD early diagnosis that facilitate treatment or slow down the disease. Classic biomarkers are obtained from cerebrospinal fluid and plasma, along with brain imaging by positron emission tomography. Attempts have been made to discover uncommon biomarkers from other body fluids, which are addressed in this update.

Objective:

This update aims to describe recent biomarkers from minimally invasive body fluids for the patients, such as saliva, urine, eye fluid or tears.

Methods:

Biomarkers were determined in patients versus controls by single tandem mass spectrometry, and immunoassays. Metabolites were identified by nuclear magnetic resonance, and microRNAs with genome-wide high-throughput real-time polymerase chain reaction-based platforms.

Results:

Biomarkers from urine, saliva, and eye fluid were described, including peptides/proteins, metabolites, and some microRNAs. The association with AD neuroinflammation and neurodegeneration was analyzed, highlighting the contribution of matrix metalloproteinases, the immune system and microglia, as well as the vascular system.

Conclusion:

Unusual biomarkers have been developed, which distinguish each stage and progression of the disease, and are suitable for the early AD diagnosis. An outstanding relationship of biomarkers with neuroinflammation and neurodegeneration was assessed, clearing up concerns of the etiopathogenesis of AD.

Combination of Stem Cells with Chinese Herbs for Secondary Depression in Neurodegenerative Diseases Based on Traditional Chinese Medicine Theories

Depression is a common secondary symptom in neurodegenerative diseases (NDs) caused by the loss of neurons and glial cells. Recent research focuses on stem cell therapy to replace dead nerve cells, but the low efficiency of stem cell differentiation and short survival time are obstacles limiting the therapy's effectiveness. Clinically, patients with different diseases cannot obtain the same effect by using the same cell therapy. However, traditional Chinese medicine (TCM) often uses syndrome differentiation to determine the treatment plan for NDs. Based on TCM syndrome differentiation and treatment, this article summarizes the advantages of Chinese herbal medicine combined with stem cell therapy, mainly for the effects of various herbs on diseases and stem cells, including prolonging the survival time of stem cells, resisting inflammation, and antidepressant-like effects. In particular, it analyzes the unique pathways of the influence of drugs and acupuncture on different therapies, seeking to clarify the scientific TCM system. This review mainly elaborates on the treatment of secondary depression in TCM and the advantages of a herbal combined stem cell therapy in various methods. We believe it can provide a new clinical concept for secondary depression to obtain good clinical effects and reduce the risks borne by patients.

High-Throughput and Untargeted Metabolic Profiling Revealed the Potential Effect and Mechanisms of Paeoniflorin in Young Asthmatic Rats

Paeoniflorin (PF) is a multi-target monoterpenoid glycoside and possesses broad pharmacological functions, e.g., anti-inflammation, anti-depression, antitumor, abirritation, neuroprotection, antioxidant, and enhancing cognitive and learning ability. PF has gained a large amount of attention for its effect on asthma disease as the growth rate of asthma has increased in recent years. However, its mechanism of action on asthma is still unclear. In this study, we have explored the action mechanism of PF on asthma disease. Furthermore, high-throughput untargeted metabolic profiling was performed through ultraperformance liquid chromatography/electrospray ionization quadruple time-of-flight high-definition mass spectrometry (QA) UPLC-Q/TOF-MS combined with pattern recognition approaches and pathway analysis. A total of 20 potential biomarkers were discovered by UPLC/MS and urine metabolic profiling. The key pathways including the citrate cycle (the TCA cycle), pyrimidine metabolism, pentose phosphate pathway, tyrosine metabolism, and tryptophan metabolism were affected by PF. In conclusion, we have discovered metabolite biomarkers and revealed the therapeutic mechanism of PF based on liquid chromatography coupled with mass spectrometry untargeted metabolomics. The untargeted metabolomics combined with UPLC-MS is a useful tool for exploring the therapeutic mechanism and targets of PF in the treatment of asthma. Metabolomics combined with UPLC-MS is an integrated method to explore the metabolic mechanism of PF in the treatment of asthma rats and to reveal the potential targets, providing theoretical support for the study of the treatment of PF.

Omics sciences for systems biology in Alzheimer's disease: State-of-the-art of the evidence

Alzheimer's disease (AD) is characterized by non-linear, genetic-driven pathophysiological dynamics with high heterogeneity in biological alterations and disease spatial-temporal progression. Human in-vivo and post-mortem studies point out a failure of multi-level biological networks underlying AD pathophysiology, including proteostasis (amyloid-β and tau), synaptic homeostasis, inflammatory and immune responses, lipid and energy metabolism, oxidative stress. Therefore, a holistic, systems-level approach is needed to fully capture AD multi-faceted pathophysiology. Omics sciences - genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics - embedded in the systems biology (SB) theoretical and computational framework can generate explainable readouts describing the entire biological continuum of a disease. Such path in Neurology is encouraged by the promising results of omics sciences and SB approaches in Oncology, where stage-driven pathway-based therapies have been developed in line with the precision medicine paradigm. Multi-omics data integrated in SB network approaches will help detect and chart AD upstream pathomechanistic alterations and downstream molecular effects occurring in preclinical stages. Finally, integrating omics and neuroimaging data - i.e., neuroimaging-omics - will identify multi-dimensional biological signatures essential to track the clinical-biological trajectories, at the subpopulation or even individual level.

Capillary Electrophoresis-High Resolution Mass Spectrometry for Measuring In Vivo Arginine Isotope Incorporation in Alzheimer's Disease Mouse Models

Immune-based metabolic reprogramming of arginine utilization in the brain contributes to the neuronal pathology associated with Alzheimer's disease (AD). To enable our long-term goals of differentiation of AD mouse model genotypes, ages, and sexes based on activity of this pathway, we describe here the novel dosing (using uniformly labeled (¹³C₆¹⁵N₄) arginine) and analysis methods using capillary electrophoresis high-resolution accurate-mass mass spectrometry for isotope tracing of metabolic products of arginine. We developed a pseudoprimed infusion-dosing regimen, using repeated injections, to achieve a steady state of uniformly labeled arginine in 135-195 min post bolus dose. Incorporation of stable isotope labeled carbon and nitrogen from uniformly labeled arginine into a host of downstream metabolites was measured in vivo in mice using serially sampled dried blood spots from the tail. In addition to the dried blood spot time course samples, total isotope incorporation into arginine-related metabolites was measured in the whole brain and plasma after 285 min. Preliminary demonstration of the technique identified differences isotope incorporation in arginine metabolites between male and female mice in a mouse-model of sporadic Alzheimer's disease (APOE4/huNOS2). The technique described herein will permit arginine pathway activity differentiation between mouse genotypes, ages, sexes, or drug treatments in order to elucidate the contribution of this pathway to Alzheimer's disease.

CSF metabolites associate with CSF tau and improve prediction of Alzheimer's disease status

INTRODUCTION

Cerebrospinal fluid (CSF) total tau (t-tau) and phosphorylated tau (p-tau) are biomarkers of Alzheimer's disease (AD), yet much is unknown about AD-associated changes in tau metabolism and tau tangle etiology.

METHODS

We assessed the variation of t-tau and p-tau explained by 38 previously identified CSF metabolites using linear regression models in middle-age controls from the Wisconsin Alzheimer's Disease Research Center, and predicted AD/mild cognitive impairment (MCI) versus an independent set of older controls using metabolites selected by the least absolute shrinkage and selection operator (LASSO).

RESULTS

The 38 CSF metabolites explained 70.3% and 75.7% of the variance in t-tau and p-tau, respectively. Of these, seven LASSO-selected metabolites improved the prediction ability of AD/MCI versus older controls (area under the curve score increased from 0.92 to 0.97 and 0.78 to 0.93) compared to the base model.

DISCUSSION

These tau-correlated CSF metabolites increase AD/MCI prediction accuracy and may provide insight into tau tangle etiology.

Long-Term Consequence of Non-neurotropic H3N2 Influenza A Virus Infection for the Progression of Alzheimer's Disease Symptoms

Influenza viruses until today are a leading cause of worldwide severe pandemics and represent a major threat to human and animal health. Although the primary target of influenza viruses is the lung, infection may manifest with acute and even chronic neurological complications (e.g., status epilepticus, encephalopathies, and encephalitis) potentially increasing the long-term risk for neurodegenerative diseases. We previously described that a peripheral influenza A virus (IAV) infection caused by non-neurotropic H3N2 (maHK68) variant leads to long-term neuroinflammation and synapse loss together with impaired memory formation in young adult mice. Processes of neuroinflammation have been associated with neurodegenerative diseases such as Alzheimer’s disease (AD) and prolonged or excessive innate immune responses are considered a risk factor for AD. Here, the role of purely peripheral IAV infection for the development and progression of AD in a transgenic mouse model (APP/PS1) was investigated. At 2 months of age, mice were infected with H3N2 IAV and the detailed analysis of microglia morphology revealed neuroinflammation in the hippocampus already of 6 months old non-infected APP/PS1 mice together with impaired spatial learning, however, microglia activation, amyloid-β plaques load and cognitive impairments were even more pronounced in APP/PS1 mice upon H3N2 infection. Moreover, CA1 hippocampal dendritic spine density was reduced even at 120 dpi compared to wild-type and also to non-infected APP/PS1 mice, whereas neuronal cells number was not altered. These findings demonstrate that non-neurotropic H3N2 IAV infection as a peripheral immune stimulation may exacerbate AD symptoms possibly by triggering microglial hyperactivation.

Citrulline supplementation improves spatial memory in a murine model for Alzheimer's disease

OBJECTIVES

Alzheimer's disease (AD) correlates with the dysfunction of metabolic pathways that translates into neurological symptoms. An arginine deficiency, a precursor of nitric oxide (NO), has been reported for patients with AD. We aimed to evaluate the effect of citrulline oral supplementation on cognitive decline in an AD murine model.

METHODS

Three-month citrulline or water supplementation was blindly given to male and female wild-type and 3 × Tg mice with AD trained and tested in the Morris water maze. Cerebrospinal fluid and brain tissue were collected. Ultra-performance liquid chromatography was used for arginine determinations and the Griess method for NO.

RESULTS

Eight-month-old male 3 × Tg mice with AD supplemented with citrulline performed significantly better in the Morris water maze task. Arginine levels increased in the cerebrospinal fluid although no changes were seen in brain tissue and only a tendency of increase of NO was observed.

CONCLUSIONS

Citrulline oral administration is a viable treatment for memory improvement in the early stages of AD, pointing to NO as a viable, efficient target for memory dysfunction in AD.

Urinary metabolic phenotyping for Alzheimer's disease

Finding early disease markers using non-invasive and widely available methods is essential to develop a successful therapy for Alzheimer’s Disease. Few studies to date have examined urine, the most readily available biofluid. Here we report the largest study to date using comprehensive metabolic phenotyping platforms (NMR spectroscopy and UHPLC-MS) to probe the urinary metabolome in-depth in people with Alzheimer’s Disease and Mild Cognitive Impairment. Feature reduction was performed using metabolomic Quantitative Trait Loci, resulting in the list of metabolites associated with the genetic variants. This approach helps accuracy in identification of disease states and provides a route to a plausible mechanistic link to pathological processes. Using these mQTLs we built a Random Forests model, which not only correctly discriminates between people with Alzheimer’s Disease and age-matched controls, but also between individuals with Mild Cognitive Impairment who were later diagnosed with Alzheimer’s Disease and those who were not. Further annotation of top-ranking metabolic features nominated by the trained model revealed the involvement of cholesterol-derived metabolites and small-molecules that were linked to Alzheimer’s pathology in previous studies.

Urinary Biomarkers for Neurodegenerative Diseases

Global incidence of neurodegenerative diseases (NDDs) such as Alzheimer's disease (AD) and Parkinson's disease (PD) is rapidly increasing, but the diagnosis of these diseases at their early stage is challenging. Therefore, the availability of reproducible and reliable biomarkers to diagnose such diseases is more critical than ever. In addition, biomarkers could be used not only to diagnose diseases but also to monitor the development of disease therapeutics. Urine is an excellent biofluid that can be utilized as a source of biomarker to diagnose not only several renal diseases but also other diseases because of its abundance in invasive sampling. However, urine was conventionally regarded as inappropriate as a source of biomarker for neurodegenerative diseases because it is anatomically distant from the central nervous system (CNS), a major pathologic site of NDD, in comparison to other biofluids such as cerebrospinal fluid (CSF) and plasma. However, recent studies have suggested that urine could be utilized as a source of NDD biomarker if an appropriate marker is predetermined by metabolomic and proteomic approaches in urine and other samples. In this review, we summarize such studies related to NDD.

Targeted Metabolic Profiling of Urine Highlights a Potential Biomarker Panel for the Diagnosis of Alzheimer's Disease and Mild Cognitive Impairment: A Pilot Study

The lack of sensitive and specific biomarkers for the early detection of mild cognitive impairment (MCI) and Alzheimer’s disease (AD) is a major hurdle to improving patient management. A targeted, quantitative metabolomics approach using both ¹H NMR and mass spectrometry was employed to investigate the performance of urine metabolites as potential biomarkers for MCI and AD. Correlation-based feature selection (CFS) and least absolute shrinkage and selection operator (LASSO) methods were used to develop biomarker panels tested using support vector machine (SVM) and logistic regression models for diagnosis of each disease state. Metabolic changes were investigated to identify which biochemical pathways were perturbed as a direct result of MCI and AD in urine. Using SVM, we developed a model with 94% sensitivity, 78% specificity, and 78% AUC to distinguish healthy controls from AD sufferers. Using logistic regression, we developed a model with 85% sensitivity, 86% specificity, and an AUC of 82% for AD diagnosis as compared to cognitively healthy controls. Further, we identified 11 urinary metabolites that were significantly altered to include glucose, guanidinoacetate, urocanate, hippuric acid, cytosine, 2- and 3-hydroxyisovalerate, 2-ketoisovalerate, tryptophan, trimethylamine N oxide, and malonate in AD patients, which are also capable of diagnosing MCI, with a sensitivity value of 76%, specificity of 75%, and accuracy of 81% as compared to healthy controls. This pilot study suggests that urine metabolomics may be useful for developing a test capable of diagnosing and distinguishing MCI and AD from cognitively healthy controls.

Divergence in the metabolome between natural aging and Alzheimer's disease

Alzheimer's disease (AD) is a progressive and debilitating neurodegenerative disorder and one of the leading causes of death in the United States. Although amyloid plaques and fibrillary tangles are hallmarks of AD, research suggests that pathology associated with AD often begins 20 or more years before symptoms appear. Therefore, it is essential to identify early-stage biomarkers in those at risk for AD and age-related cognitive decline (ARCD) in order to develop preventative treatments. Here, we used an untargeted metabolomics analysis to define system-level alterations following cognitive decline in aged and APP/PS1 (AD) mice. At 6, 12, and 24 months of age, both control (Ctrl) and AD mice were tested in a 3-shock contextual fear conditioning (CFC) paradigm to assess memory decline. AD mice exhibited memory deficits across age and these memory deficits were also seen in naturally aged mice. Prefrontal cortex (PFC), hippocampus (HPC), and spleen were then collected and analyzed for metabolomic alterations. A number of significant pathways were altered between Ctrl and AD mice and naturally aged mice. By identifying systems-level alterations following ARCD and AD, these data could provide insights into disease mechanisms and advance the development of biomarker panels.

Metabolomics approach based on utra-performance liquid chromatography coupled to mass spectrometry with chemometrics methods for high-throughput analysis of metabolite biomarkers to explore the abnormal metabolic pathways associated with myocardial dysfunction

Ultra-performance liquid chromatography/mass spectrometry-based metabolomics can been used for discovery of metabolite biomarkers to explore the metabolic pathway of diseases. Identification of metabolic pathways is key to understanding the pathogenesis and mechanism of disease. Myocardial dysfunction induced by sepsis (SMD) is a severe complication of septic shock and represents major causes of death in intensive care units; however its pathological mechanism is still not clear. In this study, ultrahigh-pressure liquid chromatography with mass spectrometry-based metabolomics with chemometrics anaylsis and multivariate pattern recognition analysis were used to detect urinary metabolic profile changes in a lipopolysaccharide-induced SMD mouse model. Multivariate statistical analysis including principal component analysis and orthogonapartial least squares discriminant analysis for the discrimination of SMD was conducted to identify potential biomarkers. A total of 19 differential metabolites were discovered by high-resolution mass spectrometry-based urinary metabolomics strategy. The altered biochemical pathways based on these metabolites showed that tyrosine metabolism, phenylalanine metabolism, ubiquinone biosynthesis and vitamin B6 metabolism were closely connected to the pathological processes of SMD. Consequently, integrated chemometric analyses of these metabolic pathways are necessary to extract information for the discovery of novel insights into the pathogenesis of disease.

High-throughput metabolomics reveals the perturbed metabolic pathways and biomarkers of Yang Huang syndrome as potential targets for evaluating the therapeutic effects and mechanism of geniposide

High-throughput metabolomics can clarify the underlying molecular mechanism of diseases via the qualitative and quantitative analysis of metabolites. This study used the established Yang Huang syndrome (YHS) mouse model to evaluate the efficacy of geniposide (GEN). Urine metabolic data were quantified by ultraperformance liquid chromatography-tandem mass spectrometry. The non-target screening of the massive biological information dataset was performed, and a total of 33 metabolites, including tyramine glucuronide, aurine, and L-cysteine, were identified relating to YHS. These differential metabolites directly participated in the disturbance of phase I reaction and hydrophilic transformation of bilirubin. Interestingly, they were completely reversed by GEN. While, as the auxiliary technical means, we also focused on the molecular prediction and docking results in network pharmacological and integrated analysis part. We used integrated analysis to communicate the multiple results of metabolomics and network pharmacology. This study is the first to report that GEN indirectly regulates the metabolite "tyramine glucuronide" through its direct effect on the target heme oxygenase 1 in vivo. Meanwhile, heme oxygenase-1, a prediction of network pharmacology, was the confirmed metabolic enzyme of phase I reaction in hepatocytes. Our study indicated that the combination of high-throughput metabolomics and network pharmacology is a robust combination for deciphering the pathogenesis of the traditional Chinese medicine (TCM) syndrome.

High-throughput lipidomics analysis to discover lipid biomarkers and profiles as potential targets for evaluating efficacy of Kai-Xin-San against APP/PS1 transgenic mice based on UPLC-Q/TOF-MS

Lipid metabolism has a significant function in the central nervous system and Alzheimer's disease (AD) is an age-related senile disease characterized by central nerve degeneration. The pathological development of AD is closely related to lipid metabolism disorders. To reveal the influence of Kai-Xin-San (KXS) on lipid metabolism in APP/PSI transgenic mice and potential therapeutic targets for treating AD, brain tissue samples were collected and analyzed by high-throughput lipidomics based on UPLC-Q/TOF-MS. The collected raw data were processed by multivariate data analysis to discover the potential biomarkers and lipid metabolic profiles. Compared with the control wild-type mouse group, nine potential lipid biomarkers were found in the AD model group, of which seven were up-regulated and two were down-regulated. Orally administrated KXS can reverse the changes in these potential biomarkers. Compared with the model group, a total of six differential metabolites showed a recovery trend and may be potential targets for KXS to treat AD. This study showed that high-throughput lipidomics can be used to discover the perturbed pathways and lipid biomarkers as potential targets to reveal the therapeutic effects of KXS.

Chemical Discrimination of Astragalus mongholicus and Astragalus membranaceus Based on Metabolomics Using UHPLC-ESI-Q-TOF-MS/MS Approach

Astragalus mongholicus (MG) and Astragalus membranaceus (MJ), both generally known as Huangqi in China, are two perennial herbals widely used in variety diseases. However, there were still some differences in the chemical ingredients between MG and MJ. In this paper, metabolomics combined with the ultra-high performance liquid chromatography coupled with electrospray ionization/quadrupole time-of-flight mass spectrometry (UHPLC-ESI-Q-TOF-MS/MS) was employed to contrastively analyze the chemical constituents between MG and MJ. As a result, principal component analysis showed that MG and MJ were separated clearly. A total of 53 chemical markers were successfully identified for the discrimination of MG and MJ. Of them, the contents of 36 components including Astragaloside I~III, Astragaloside IV, Agroastragaloside I, etc. in MJ were significantly higher than those in MG. On the contrary, the contents of 17 other components including coumaric acid, formononetin, sophoricoside, etc. in MG were obviously higher than those in MJ. The results showed that the distinctive constituents in MG and MJ were remarkable, and MJ may own stronger pharmacological activities than MG. In a word, MG and MJ may be treated as two different herbs. This paper demonstrated that metabolomics was a vitally credible technology to rapidly screen the characteristic chemical composition of traditional Chinese medicine.

Recent Trends in the Quantification of Biogenic Amines in Biofluids as Biomarkers of Various Disorders: A Review

Biogenic amines (BAs) are bioactive endogenous compounds which play a significant physiological role in many cell processes like cell proliferation and differentiation, signal transduction and membrane stability. Likewise, they are important in the regulation of body temperature, the increase/decrease of blood pressure or intake of nutrition, as well as in the synthesis of nucleic acids and proteins, hormones and alkaloids. Additionally, it was confirmed that these compounds can be considered as useful biomarkers for the diagnosis, therapy and prognosis of several neuroendocrine and cardiovascular disorders, including neuroendocrine tumours (NET), schizophrenia and Parkinson's Disease. Due to the fact that BAs are chemically unstable, light-sensitive and possess a high tendency for spontaneous oxidation and decomposition at high pH values, their determination is a real challenge. Moreover, their concentrations in biological matrices are extremely low. These issues make the measurement of BA levels in biological matrices problematic and the application of reliable bioanalytical methods for the extraction and determination of these molecules is needed. This article presents an overview of the most recent trends in the quantification of BAs in human samples with a special focus on liquid chromatography (LC), gas chromatography (GC) and capillary electrophoresis (CE) techniques. Thus, new approaches and technical possibilities applied in these methodologies for the assessment of BA profiles in human samples and the priorities for future research are reported and critically discussed. Moreover, the most important applications of LC, GC and CE in pharmacology, psychology, oncology and clinical endocrinology in the area of the analysis of BAs for the diagnosis, follow-up and monitoring of the therapy of various health disorders are presented and critically evaluated.

High-throughput metabolomics and ingenuity pathway approach reveals the pharmacological effect and targets of Ginsenoside Rg1 in Alzheimer's disease mice

Ginsenoside Rg1, a natural triterpenoid saponins compound isolated from the Panax species, has been found to possess neuroprotective properties in neurodegenerative diseases such as Alzheimer's disease (AD). However, its pharmacological mechanism on AD has not been studied. In this study, an ultra-performance liquid chromatography combined with quadrupole time of-flight mass spectrometry (UPLC-Q/TOF-MS) based non-targeted metabolomics strategy was performed to explore the mechanism of Ginsenoside Rg1 protecting against AD mice by characterizing metabolic biomarkers and regulation pathways changes. A total of nineteen potential metabolites in serum were discovered and identified to manifest the difference between wild-type mice and triple transgenic mice in control and model group, respectively. Fourteen potential metabolites involved in ten metabolic pathways such as linoleic acid metabolism, arachidonic acid metabolism, tryptophan metabolism and sphingolipid metabolism were affected by Rg1. From the ingenuity pathway analysis (IPA) platform, the relationship between gene, protein, metabolites alteration and protective activity of ginsenoside Rg1 in AD mice are deeply resolved, which refers to increased level of albumin, amino acid metabolism and molecular transport. In addition, quantitative analysis of key enzymes in the disturbed pathways by proteomics parallel reaction was employed to verify changed metabolic pathway under Ginsenoside Rg1. The UPLC-Q/TOF-MS based serum metabolomics method brings about new insights into the pharmacodynamic studies of Ginsenoside Rg1 on AD mice.

High-throughput metabolomics for evaluating the efficacy and discovering the metabolic mechanism of Luozhen capsules from the excessive liver-fire syndrome of hypertension

Essential hypertension (EH) is a chronic disease characterized by a variety of causes of elevated systemic arterial pressure, which often causes functional or organic damage to important organs such as the heart, brain, and kidney. Hypertension of excessive liver-fire syndrome is a type of classification for young people with essential hypertension. The disease is slower in its onset and its symptoms are more ambiguous, and thus its pathogenesis is complicated and still unclear. In this study, aconite, dried ginger and cinnamon extracts were combined with l-NAME to establish a model of excessive liver-fire hypertension. Blood pressure (systolic blood pressure), ANGII, NE and 5-HT were used as evaluation indicators to establish the model. Urinary metabolomics based on ultra-high performance liquid chromatography coupled with quadruple time-of-flight mass spectrometry was used to characterize the metabolic changes and potential biomarkers in modeled rats. Compared to the treatment group, 32 potential biomarkers were initially identified in the model using multivariate statistical analysis involving 11 metabolic pathways. After oral administration of Luozhen capsules, eight biomarkers that can be adjusted in high, medium and low doses of Luozhen capsules in urine were preliminarily determined, mainly involving two metabolic pathways of amino acid metabolism and lipid metabolism. In conclusion, this study explored the metabolomic changes in rats with hypertension of liver-fire hyperactivity syndrome and the post-dose metabolomics, determined the relevant biomarker groups, and clarified the metabonomic connotation of Luozhen capsules in the treatment of liver-fire excessive type hypertension.

Essential hypertension (EH) is a chronic disease characterized by a variety of causes of elevated systemic arterial pressure, which often causes functional or organic damage to important organs such as the heart, brain, and kidney.

Targeting regulation of tryptophan metabolism for colorectal cancer therapy: a systematic review

Colorectal cancer (CRC) is one of the most malignant cancers resulting from abnormal metabolism alterations. As one of the essential amino acids, tryptophan has a variety of physiological functions, closely related to regulation of immune system, central nervous system, gastrointestinal nervous system and intestinal microflora. Colorectal cancer, a type of high-grade malignancy disease, stems from a variety of factors and often accompanies inflammatory reactions, dysbacteriosis, and metabolic disorders. Colorectal cancer accompanies inflammation and imbalance of intestinal microbiota and affects tryptophan metabolism. It is known that metabolites, rate-limiting enzymes, and ARH in tryptophan metabolism are associated with the development of CRC. Specifically, IDO1 may be a potential therapeutic target in colorectal cancer treatment. Furthermore, the reduction of tryptophan amount is proportional to the poor quality of life for colorectal cancer patients. This paper aims to discuss the role of tryptophan metabolism in a normal organism and investigate the relationship between this amino acid and colorectal cancer. This study is expected to provide theoretical support for research related to targeted therapy for colorectal cancer. Furthermore, strategies that modify tryptophan metabolism, effectively inhibiting tumor progression, may be more effective for CRC treatment.

Colorectal cancer (CRC) is one of the most malignant cancers resulting from abnormal metabolism alterations.

Gut microbiota as important modulator of metabolism in health and disease

The human gastrointestinal tract colonizes a large number of microbial microflora, forms a host-microbiota co-metabolism structure with the host to participate in various metabolic processes in the human body, and plays a major role in the host immune response. In addition, the dysbiosis of intestinal microbial homeostasis is closely related to many diseases. Thus, an in-depth understanding of the relationship between them is of importance for disease pathogenesis, prevention and treatment. The combined use of metagenomics, transcriptomics, proteomics and metabolomics techniques for the analysis of gut microbiota can reveal the relationship between microbiota and the host in many ways, which has become a hot topic of analysis in recent years. This review describes the mechanism of co-metabolites in host health, including short-chain fatty acids (SCFA) and bile acid metabolism. The metabolic role of gut microbiota in obesity, liver diseases, gastrointestinal diseases and other diseases is also summarized, and the research methods for multi-omics combined application on gut microbiota are summarized. According to the studies of the interaction mechanism between gut microbiota and the host, we have a better understanding of the use of intestinal microflora in the treatment of related diseases. It is hoped that the gut microbiota can be utilized to maintain human health, providing a reference for future research.

Identification of Differentially Expressed Profiles of Alzheimer's Disease Associated Circular RNAs in a Panax Notoginseng Saponins-Treated Alzheimer's Disease Mouse Model

Circular RNAs (circRNAs) play vital roles in AD pathogenesis. Thus, developing therapeutic candidates targeting circRNA may provide a novel therapeutic strategy for AD treatment. Our previous studies showed that Panax notoginseng saponins (PNS) could significantly prohibit the pathological progress of AD. However, the mechanisms by which PNS attenuates AD progression is still unclear. The present study shows that PNS may exhibit an ability to modulate the expression of AD-associated circRNAs. Specifically, PNS treatment leads to five circRNAs upregulation and two circRNAs downregulation, indicating that the therapeutic effect of PNS against AD may be associated with its role in the regulation of circRNA expression. Next, mmu_circRNA_013636 and mmu_circRNA_012180 were selected and GO and KEGG analyses were performed to further investigate the biological functions and potential mechanisms of these circRNAs. The results showed that the selected circRNAs were involved in AD-associated biological process and pathways, suggesting that these circRNAs may participate in AD pathogenesis. Collectively, our study indicates that the therapeutic effects of PNS on AD may be through modulating the expression of AD associated circRNAs and suggests that PNS is a potential circRNA-targeted agent against AD, which may provide useful resources for developing potential candidates targeting circRNAs against AD.

Cell metabolomics identify regulatory pathways and targets of magnoline against prostate cancer

Prostate cancer is known as a common malignant tumor in clinics and moreover, traditional chemotherapeutic drugs have great toxic side effects and drug resistance. Therefore, the searching the highly efficient and low toxicity antitumor drugs from natural drugs has become an important approach for the treatment of prostate cancer. Many studies showed that Cortex Phellodendri has important therapeutic significance for prostate cancer. Magnoline is the main component of Cortex Phellodendri Amurensis, and it is of great significance to evaluate the effect of magnoline on prostate cancer. By using metabolomics, we established a comprehensive analysis strategy based on cell metabolic analysis to study the inhibitory effect of magnoline on the proliferation of prostate cancer cell line 22RV1, and finally conducted an analysis on the cell metabolism footprint samples. Results showed that magnoline had a significant inhibitory effect on the proliferation of the prostate cancer cell line 22RV1. According to the established cell metabolomics methods, we found that 12 metabolic biomarkers of the cell metabolic footprint samples, respectively, could inhibit the proliferation of prostate cancer cells. Magnoline could significantly affect these metabolic biomarkers to disrupt the growth and proliferation of the prostate cancer cell line 22RV1. Additionally, through MetPA analysis indicated that these biomarkers were closely correlated with a variety of metabolic pathways in tumor cells, including the energy metabolism, amino acid metabolism and fatty acid metabolism, most of which were associated with nutrition and energy metabolism. Therefore, we speculated that because of the disturbance of nutrition metabolism and energy metabolism of the prostate cancer cell line 22RV1, cells could not provide the material basis for rapid proliferation, eventually resulting in the inhibition effect.

L-Norvaline Reverses Cognitive Decline and Synaptic Loss in a Murine Model of Alzheimer's Disease

The urea cycle is strongly implicated in the pathogenesis of Alzheimer's disease (AD). Arginase-I (ARGI) accumulation at sites of amyloid-beta (Aβ) deposition is associated with L-arginine deprivation and neurodegeneration. An interaction between the arginase II (ARGII) and mTOR-ribosomal protein S6 kinase β-1 (S6K1) pathways promotes inflammation and oxidative stress. In this study, we treated triple-transgenic (3×Tg) mice exhibiting increased S6K1 activity and wild-type (WT) mice with L-norvaline, which inhibits both arginase and S6K1. The acquisition of spatial memory was significantly improved in the treated 3×Tg mice, and the improvement was associated with a substantial reduction in microgliosis. In these mice, increases in the density of dendritic spines and expression levels of neuroplasticity-related proteins were followed by a decline in the levels of Aβ toxic oligomeric and fibrillar species in the hippocampus. The findings point to an association of local Aβ-driven and immune-mediated responses with altered L-arginine metabolism, and they suggest that arginase and S6K1 inhibition by L-norvaline may delay the progression of AD.

Effects of Oligosaccharides From Morinda officinalis on Gut Microbiota and Metabolome of APP/PS1 Transgenic Mice

Alzheimer's disease (AD), a progressive neurodegenerative disorder, lacks preclinical diagnostic biomarkers and therapeutic drugs. Thus, earlier intervention in AD is a top priority. Studies have shown that the gut microbiota influences central nervous system disorders and that prebiotics can improve the cognition of hosts with AD, but these effects are not well understood. Preliminary research has shown that oligosaccharides from Morinda officinalis (OMO) are a useful prebiotic and cause substantial memory improvements in animal models of AD; however, the mechanism is still unclear. Therefore, this study was conducted to investigate whether OMO are clinically effective in alleviating AD by improving gut microbiota. OMO were administered to APP/PS1 transgenic mice, and potential clinical biomarkers of AD were identified with metabolomics and bioinformatics. Behavioral experiments demonstrated that OMO significantly ameliorated the memory of the AD animal model. Histological changes indicated that OMO ameliorated brain tissue swelling and neuronal apoptosis and downregulated the expression of the intracellular AD marker Aβ₁₋₄₂. 16S rRNA sequencing analyses indicated that OMO maintained the diversity and stability of the microbial community. The data also indicated that OMO are an efficacious prebiotic in an animal model of AD, regulating the composition and metabolism of the gut microbiota. A serum metabolomics assay was performed using UHPLC-LTQ Orbitrap mass spectrometry to delineate the metabolic changes and potential early biomarkers in APP/PS1 transgenic mice. Multivariate statistical analysis showed that 14 metabolites were significantly upregulated, and 8 metabolites were downregulated in the model animals compared to the normal controls. Thus, key metabolites represent early indicators of the development of AD. Overall, we report a drug and signaling pathway with therapeutic potential, including proteins associated with cognitive deficits in normal mice or gene mutations that cause AD.

Identifying quality-markers from Shengmai San protects against transgenic mouse model of Alzheimer's disease using chinmedomics approach

BACKGROUND

Shengmai San (SMS), a Chinese classic herbal formula, has been widely used for the treatment of Qi-Yin deficiency syndrome in Asia. Modern pharmacological studies have shown that SMS improves the cognitive function. However, the quality markers (Q-markers) for SMS still need further research.

PURPOSE

Using chinmedocmics strategy to systematically evaluate the efficacy of SMS in the treatment of APPswe/PS1dE9 (APP/PS1) transgenic model of Alzheimer's disease (AD) and to discover the efficacy-related Q-markers.

METHODS

The effect of SMS on APP/PS1 mice was evaluated by behavioral test, immunohistochemistry and urine metabolic profile, and the urine marker metabolites associated with SMS treatment of AD were characterized using metabolomics method. In the premise of efficacy, Serum Pharmacochemistry of Traditional Chinese Medicine was applied to investigate the in vivo constituents of SMS. A correlation analysis between marker metabolites of therapeutic effects and serum constituents was completed by chinmedomics approach.

RESULTS

SMS had a therapeutic effect on APP/PS1 mice, and 34 potential urine biomarkers were reversed by SMS treatment. A total of 17 in vivo constituents were detected, including 14 prototype components and 3 metabolites. The correlation analysis showed that eight constituents were extremely correlated with protective effects of SMS in AD, and considered as potential Q-markers of SMS, including schisandrin, isoschisandrin, angeloylgomisin Q, gomisin D, angeloylgomisin H, gomisin M2, ginsenoside F1, 20(R)-ginsenoside Rg3.

CONCLUSION

This study has demonstrated that chinmedomics is novel strategy for discovering the potential effective constituents from herbal formula, which are recognized as Q-markers.

Application of Metabolomics in Alzheimer's Disease

Progress toward the development of efficacious therapies for Alzheimer’s disease (AD) is halted by a lack of understanding early underlying pathological mechanisms. Systems biology encompasses several techniques including genomics, epigenomics, transcriptomics, proteomics, and metabolomics. Metabolomics is the newest omics platform that offers great potential for the diagnosis and prognosis of neurodegenerative diseases as an individual’s metabolome reflects alterations in genetic, transcript, and protein profiles and influences from the environment. Advancements in the field of metabolomics have demonstrated the complexity of dynamic changes associated with AD progression underscoring challenges with the development of efficacious therapeutic interventions. Defining systems-level alterations in AD could provide insights into disease mechanisms, reveal sex-specific changes, advance the development of biomarker panels, and aid in monitoring therapeutic efficacy, which should advance individualized medicine. Since metabolic pathways are largely conserved between species, metabolomics could improve the translation of preclinical research conducted in animal models of AD into humans. A summary of recent developments in the application of metabolomics to advance the AD field is provided below.

High-throughput lipidomics reveal mirabilite regulating lipid metabolism as anticancer therapeutics

Altered lipid metabolism is an emerging hallmark of cancers. Mirabilite has a therapeutic effect on colorectal cancer (CRC); however, its metabolic mechanism remains unclear. This study aims to explore the potential therapeutic targets of mirabilite protection against colorectal cancer in APC^min/+ mice model. Oral administration of mirabilite was started from the ninth month, while the same dosage of distilled water was given to both the control group and the model group. Based on lipidomics, we collected serum samples of all mice at the 20^th week and used a non-targeted method to identify the lipid biomarkers of CRC. Compared with C57BL/6J mice, the metabolic profile of CRC model mice was significantly disturbed, and we identified that 25 lipid-related biomarkers, including linoleic acid, 2-hydroxybutyric acid, 6-deoxocastasterone, hypoxanthine, PC(16:1), PC(18:4), and retinyl acetate, were associated with CRC. According to the abovementioned results, there were six lipid molecules with significant differences that can be used as new targets for handling of CRC through six metabolic pathways, namely, linoleic acid metabolism, retinol metabolism, propanoate metabolism, arachidonic acid metabolism, biosynthesis of unsaturated fatty acids and purine metabolism. Compared with the model group, the metabolic profiles of these disorders tend to recover after treatment. These results indicated that the lipid molecules associated with CRC were regulated by mirabilite. In addition, we identified seven key lipid molecules, of which four had statistical significance. After administration of mirabilite, all disordered metabolic pathways showed different degrees of regulation. In conclusion, high-throughput lipidomics approach revealed mirabilite regulating the altered lipid metabolism as anticancer therapeutics.

Altered lipid metabolism is an emerging hallmark of cancers.