Metabolic phenotyping and systems biology approaches to understanding neurological disorders

Metabolic fingerprint of progression of chronic hepatitis B: changes in the metabolome and novel diagnostic possibilities

INTRODUCTION

Chronic hepatitis B (CHB) affects 257 million individuals worldwide with an annual estimated mortality rate of 880,000 individuals. Accurate diagnosis of the stage of disease is difficult, and there is considerable uncertainty concerning the optimal point in time, when treatment should be started.

OBJECTIVES

By analyzing and comparing the metabolomes of patients at different stages of CHB and comparing them to healthy individuals, we want to determine the metabolic signature of disease progression and develop a more accurate metabolome-based method for diagnosis of disease progression ultimately giving a better basis for treatment decisions.

METHODS

In this study, we used the combination of transient elastography and serum metabolomics of 307 serum samples from a group of 90 patients with CHB before and under treatment (with a follow-up time up to 10 years) at different progression stages over the clinical phases and 43 healthy controls..

RESULTS

Our data show that the metabolomics approach can successfully discover CHB changing from the immune tolerance to the immune clearance phase and show distinctive metabolomes from different medical treatment stages. Perturbations in ammonia detoxification, glutamine and glutamate metabolism, methionine metabolism, dysregulation of branched-chain amino acids, and the tricarboxylic acid (TCA) cycle are the main factors involved in the progression of the disease. Fluctuations increasing in aspartate, glutamate, glutamine, methionine and 13 other metabolites are fingerprints of progression.

CONCLUSIONS

The metabolomics approach may expand the diagnostic armamentarium for patients with CHB. This method can provide a more detailed decision basis for starting medical treatment.

Metabolomics in Central Sensitivity Syndromes

Central sensitization syndromes are a collection of frequently painful disorders that contribute to decreased quality of life and increased risk of opiate abuse. Although these disorders cause significant morbidity, they frequently lack reliable diagnostic tests. As such, technologies that can identify key moieties in central sensitization disorders may contribute to the identification of novel therapeutic targets and more precise treatment options. The analysis of small molecules in biological samples through metabolomics has improved greatly and may be the technology needed to identify key moieties in difficult to diagnose diseases. In this review, we discuss the current state of metabolomics as it relates to central sensitization disorders. From initial literature review until Feb 2020, PubMed, Embase, and Scopus were searched for applicable studies. We included cohort studies, case series, and interventional studies of both adults and children affected by central sensitivity syndromes. The majority of metabolomic studies addressing a CSS found significantly altered metabolites that allowed for differentiation of CSS patients from healthy controls. Therefore, the published literature overwhelmingly supports the use of metabolomics in CSS. Further research into these altered metabolites and their respective metabolic pathways may provide more reliable and effective therapeutics for these syndromes.

ASIC3-dependent metabolomics profiling of serum and urine in a mouse model of fibromyalgia

Fibromyalgia (FM) is characterized by chronic widespread pain. The pathogenesis of FM remains unclear. No specific biomarkers are available. Animal models of FM may provide an opportunity to explore potential biomarkers in a relative homogenous disease condition. Here, we probed the metabolomics profiles of serum and urine in a mouse model of FM induced by intermittent cold stress (ICS). We focused on the role of acid-sensing ion channel 3 (ASIC3) in the metabolomics profiling because ICS treatment induced chronic widespread muscle pain lasting for 1 month in wild-type (Asic3^+/+) but not Asic3-knockout (Asic3^−/−) mice. Serum and urine samples were collected from both genotypes at different ICS stages, including before ICS (basal level) and post-ICS at days 10 (middle phase, P10) and 40 (recovery phase, P40). Control naïve mice and ICS-induced FM mice differed in ¹H-NMR- and LC-MS-based metabolomics profiling. On pathway analysis, the leading regulated pathways in Asic3^+/+ mice were taurine and hypotaurine, cysteine and methionine, glycerophospholipid, and ascorbate and aldarate metabolisms, and the major pathways in Asic3^−/− mice involved amino acid-related metabolism. Finally, we developed an algorithm for the impactful metabolites in the FM model including cis-aconitate, kynurenate, taurine, pyroglutamic acid, pyrrolidonecarboxylic acid, and 4-methoxyphenylacetic acid in urine as well as carnitine, deoxycholic acid, lysoPC(16:0), lysoPC(20:3), oleoyl-L-carnitine, and trimethylamine N-oxide in serum. Asic3^−/− mice were impaired in only muscle allodynia development but not other pain symptoms in the ICS model, so the ASIC3-dependent metabolomics changes could be useful for developing diagnostic biomarkers specific to chronic widespread muscle pain, the core symptom of FM. Further pharmacological validations are needed to validate these metabolomics changes as potential biomarkers for FM diagnosis and/or treatment responses.

Brain metabonomics study of the antidepressant-like effect of Xiaoyaosan on the CUMS-depression rats by 1H NMR analysis

ETHNOPHARMACOLOGICAL RELEVANCE

Xiaoyaosan (XYS), a famous TCM prescription with a long history of clinical use for relieving a wide variety of depression symptoms, consists of Radix Bupleuri (Bupleurum chinense DC.), Radix Angelicae Sinensis (Angelica sinensis (Oliv.) Diels), Radix PaeoniaeAlba (Paeonia lactiflora Pall.), Rhizoma Atractylodis Macrocepha lae (Atractylodes macrocephala Koidz.), Poria (Poria cocos (Schw.)Wolf), Radix Glycyrrhizae (Glycyrrhiza uralensis Fisch.), Herba Menthae Haplocalycis (Mentha haplocalyx Briq.), and Rhizoma Zin-giberis Recens (Zingiber officinale Rosc.).

AIM OF THE STUDY

We aimed to characterize the diversity and variation of two kinds metabolites of brain, i.e. aqueous and lipophilic metabolites, gaining comprehensive insights into the metabolic processes of depression-like behavior, and to reveal the mechanisms of antidepressant-like effects of XYS.

MATERIALS AND METHODS

We first established a CUMS (Chronic Unpredictable Mild Stress)-induced depression-like behavior model. We then extracted both aqueous and lipophilic metabolites of rat brains by a two-phase extraction method, which were subsequently characterized by two differential sequences of ¹H nuclear magnetic resonance (NMR). Multivariate analysis including Principal Components Analysis (PCA) and Orthogonal Partial Least Squares-Discriminate Analysis (OPLS-DA) was applied.

RESULTS

Metabolic profiling by PCA indicated that XYS significantly reversed the metabolic perturbation caused by CUMS. OPLS-DA showed a total of 15 metabolites including 6 lipophilic and 9 aqueous metabolites was screened as potential biomarkers involved in CUMS-induced depression-like behavior. On top of this, five pathways including (1)D-glutamine and D-glutamate metabolism, (2) valine, leucine and isoleucine biosynthesis, (3) alanine, aspartate and glutamate metabolism, (4) taurine and hypotaurine metabolism and (5) arginine and proline metabolism were recognized as the most influenced pathways associated with the process of CUMS-induced depression-like behavior. Notably, XYS significantly reversed abnormality of 5 aqueous and 4 lipophilic metabolites to normal, suggesting that XYS synergistically mediated abnormalities of multiple pathways (1), (3), (4) and (5).

CONCLUSIONS

It is the first report to investigate the antidepressant-like effects and underlying mechanisms of XYS from the perspective of brain metabolites. In a broad sense, this study brings novel and valuable insights to evaluate the efficacy of traditional Chinese medicine (TCM), to interpret mechanisms, and to provide the theoretical basis for further research on therapeutic mechanisms in clinical practice.

Diet-induced metabolic changes of the human gut microbiome: importance of short-chain fatty acids, methylamines and indoles

The human gut is a home for more than 100 trillion bacteria, far more than all other microbial populations resident on the body's surface. The human gut microbiome is considered as a microbial organ symbiotically operating within the host. It is a collection of different cell lineages that are capable of communicating with each other and the host and has an ability to undergo self-replication for its repair and maintenance. As the gut microbiota is involved in many host processes including growth and development, an imbalance in its ecological composition may lead to disease and dysfunction in the human. Gut microbial degradation of nutrients produces bioactive metabolites that bind target receptors, activating signalling cascades, and modulating host metabolism. This review covers current findings on the nutritional and pharmacological roles of selective gut microbial metabolites, short-chain fatty acids, methylamines and indoles, as well as discussing nutritional interventions to modulate the microbiome.

Genetic and biochemical changes of the serotonergic system in migraine pathobiology

Migraine is a brain disorder characterized by a piercing headache which affects one side of the head, located mainly at the temples and in the area around the eye. Migraine imparts substantial suffering to the family in addition to the sufferer, particularly as it affects three times more women than men and is most prevalent between the ages of 25 and 45, the years of child rearing. Migraine typically occurs in individuals with a genetic predisposition and is aggravated by specific environmental triggers. Attempts to study the biochemistry of migraine began as early as the 1960s and were primarily directed at serotonin metabolism after an increase of 5-hydroxyindoleacetic acid (5-HIAA), the main metabolite of serotonin was observed in urine of migraineurs. Genetic and biochemical studies have primarily focused on the neurotransmitter serotonin, considering receptor binding, transport and synthesis of serotonin and have investigated serotonergic mediators including enzymes, receptors as well as intermediary metabolites. These studies have been mainly assayed in blood, CSF and urine as the most accessible fluids. More recently PET imaging technology integrated with a metabolomics and a systems biology platform are being applied to study serotonergic biology. The general trend observed is that migraine patients have alterations of neurotransmitter metabolism detected in biological fluids with different biochemistry from controls, however the interpretation of the biological significance of these peripheral changes is unresolved. In this review we present the biology of the serotonergic system and metabolic routes for serotonin and discuss results of biochemical studies with regard to alterations in serotonin in brain, cerebrospinal fluid, saliva, platelets, plasma and urine of migraine patients.

A diagnostic biomarker profile for fibromyalgia syndrome based on an NMR metabolomics study of selected patients and controls

BACKGROUND

Fibromyalgia syndrome (FMS) is a chronic pain syndrome. A plausible pathogenesis of the disease is uncertain and the pursuit of measurable biomarkers for objective identification of affected individuals is a continuing endeavour in FMS research. Our objective was to perform an explorative metabolomics study (1) to elucidate the global urinary metabolite profile of patients suffering from FMS, and (2) to explore the potential of this metabolite information to augment existing medical practice in diagnosing the disease.

METHODS

We selected patients with a medical history of persistent FMS (n = 18), who described their recent state of the disease through the Fibromyalgia Impact Questionnaire (FIQR) and an in-house clinical questionnaire (IHCQ). Three control groups were used: first-generation family members of the patients (n = 11), age-related individuals without any indications of FMS or related conditions (n = 10), and healthy young (18-22 years) individuals (n = 20). All subjects were female and the biofluid under investigation was urine. Correlation analysis of the FIQR showed the FMS patients represented a well-defined disease group for this metabolomics study. Spectral analyses of urine were conducted using a 500 MHz ¹H nuclear magnetic resonance (NMR) spectrometer; data processing and analyses were performed using Matlab, R, SPSS and SAS software.

RESULTS AND DISCUSSION

Unsupervised and supervised multivariate analyses distinguished all three control groups and the FMS patients, and significant increases in metabolites related to the gut microbiome (hippuric, succinic and lactic acids) were observed. We have developed an algorithm for the diagnosis of FMS consisting of three metabolites - succinic acid, taurine and creatine - that have a good level of diagnostic accuracy (Receiver Operating Characteristic (ROC) analysis - area under the curve 90%) and on the pain and fatigue symptoms for the selected FMS patient group.

CONCLUSION

Our data and comparative analyses indicated an altered metabolic profile of patients with FMS, analytically detectable within their urine. Validation studies may substantiate urinary metabolites to supplement information from medical assessment, tender-point measurements and FIQR questionnaires for an improved objective diagnosis of FMS.

Plasma Biomarkers for Monitoring Brain Pathophysiology in FMR1 Premutation Carriers

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

An Interactive Cluster Heat Map to Visualize and Explore Multidimensional Metabolomic Data

Heat maps are a commonly used visualization tool for metabolomic data where the relative abundance of ions detected in each sample is represented with color intensity. A limitation of applying heat maps to global metabolomic data, however, is the large number of ions that have to be displayed and the lack of information provided about important metabolomic parameters such as m/z and retention time. Here we address these challenges by introducing the interactive cluster heat map in the data-processing software XCMS Online. XCMS Online (xcmsonline.scripps.edu) is a cloud-based informatic platform designed to process, statistically evaluate, and visualize mass-spectrometry based metabolomic data. An interactive heat map is provided for all data processed by XCMS Online. The heat map is clickable, allowing users to zoom and explore specific metabolite metadata (EICs, Box-and-whisker plots, mass spectra) that are linked to the METLIN metabolite database. The utility of the XCMS interactive heat map is demonstrated on metabolomic data set generated from different anatomical regions of the mouse brain.

Brain region mapping using global metabolomics

Historically, studies of brain metabolism have been based on targeted analyses of a limited number of metabolites. Here we present an untargeted mass spectrometry-based metabolomic strategy that has successfully uncovered differences in a broad array of metabolites across anatomical regions of the mouse brain. The NSG immunodeficient mouse model was chosen because of its ability to undergo humanization leading to numerous applications in oncology and infectious disease research. Metabolic phenotyping by hydrophilic interaction liquid chromatography and nanostructure imaging mass spectrometry revealed both water-soluble and lipid metabolite patterns across brain regions. Neurochemical differences in metabolic phenotypes were mainly defined by various phospholipids and several intriguing metabolites including carnosine, cholesterol sulfate, lipoamino acids, uric acid, and sialic acid, whose physiological roles in brain metabolism are poorly understood. This study helps define regional homeostasis for the normal mouse brain to give context to the reaction to pathological events.

Cerebrospinal fluid analysis in Alzheimer's disease: technical issues and future developments

Alzheimer's disease (AD) is a leading cause of morbidity, mortality, and a major epidemic worldwide. Although clinical assessment continues to remain the keystone for patient management and clinical trials, such evaluation has important limitations. In this context, cerebrospinal fluid (CSF) biomarkers are important tools to better identify high-risk individuals, to diagnose AD promptly and accurately, especially at the prodromal mild cognitive impairment stage of the disease, and to effectively prognosticate and treat AD patients. Recent advances in functional genomics, proteomics, metabolomics, and bioinformatics will hopefully revolutionize unbiased inquiries into several putative CSF markers of cerebral pathology that may be concisely informative with regard to the various stages of AD progression through years and decades. Moreover, the identification of efficient drug targets and development of optimal therapeutic strategies for AD will increasingly rely on a better understanding and integration of the systems biology paradigm, which will allow predicting the series of events and resulting responses of the biological network triggered by the introduction of new therapeutic compounds. In this scenario, unbiased systems biology-based diagnostic and prognostic models in AD will consist of relevant comprehensive panels of molecules and key branches of the disease-affected cellular neuronal network. Such characteristic and unbiased biomarkers will more accurately and comprehensively reflect pathophysiology from the early asymptomatic and presymptomatic to the final prodromal and symptomatic clinical stages in individual patients (and their individual genetic disease predisposition), ultimately increasing the chances of success of future disease modifying and preventive treatments.