Objective diagnosis of post-stroke depression using NMR-based plasma metabonomics

Effect of electroacupuncture on metabolic alterations in the hippocampus and dorsal raphe nucleus of Wistar Kyoto rats

Depression is underpinned by a complex pathogenesis that involves the hippocampus and dorsal raphe nucleus (DRN) of the central nervous system. Although electroacupuncture (EA) is proven to be safe and effective for alleviating depression symptoms and causes minimal side effects, its underlying therapeutic mechanism remains unclear. In this study, we performed targeted metabolomics to identify metabolite alterations in the hippocampus and DRN of Wistar Kyoto (WKY) rats and elucidate the role and potential mechanism of action of EA. Our results indicated that 3 weeks of consecutive EA significantly ameliorated depression-like behaviors in WKY rats. Targeted metabolomics revealed 42 differentially expressed metabolites (DEMs) in the hippocampus and 97 DEMs in the DRN between Wistar and WKY rats. In addition, we observed 19 hippocampal DEMs and 41 DRN DEMs between WKY and EA-treated rats. Subsequent pathway analyses indicated that these DEMs were primarily enriched in amino acid-related metabolic pathways. Moreover, six DEMs were found to be significantly associated with at least one depression-like behavior, indicating their involvement in the pathogenesis of depression. EA intervention modulated the levels of 1-methylhistidine, 3-methylhistidine, carnosine, and riboflavin in depressed rats. Collectively, these findings demonstrate that disturbances in cerebral metabolites, especially amino acids, may be one of the causes underlying depression in WKY rats, and the therapeutic effect of EA is potentially mediated through the modulation of the levels of these metabolites.

Urinary Metabolic Profiling During Epileptogenesis in Rat Model of Lithium-Pilocarpine-Induced Temporal Lobe Epilepsy

Background/Objectives: Temporal lobe epilepsy (TLE) often develops following an initial brain injury, where specific triggers lead to epileptogenesis-a process transforming a healthy brain into one prone to spontaneous, recurrent seizures. Although electroencephalography (EEG) remains the primary diagnostic tool for epilepsy, it cannot predict the risk of epilepsy after brain injury. This limitation highlights the need for biomarkers, particularly those measurable in peripheral samples, to assess epilepsy risk. This study investigated urinary metabolites in a rat model of TLE to identify biomarkers that track epileptogenesis progression across the acute, latent, and chronic phases and elucidate the underlying mechanisms. Methods: Status epilepticus (SE) was induced in rats using repeated intraperitoneal injections of lithium chloride-pilocarpine hydrochloride. Urine samples were collected 48 h, 1 week, and 6 weeks after SE induction. Nuclear magnetic resonance spectrometry was used for metabolomic analysis, and statistical evaluations were performed using MetaboAnalyst 6.0. Differences between epileptic and control groups were represented using the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Volcano plot analysis identified key metabolic changes, applying a fold-change threshold of 1.5 and a p-value < 0.05. Results: The acute phase exhibited elevated levels of acetic acid, dihydrothymine, thymol, and trimethylamine, whereas glycolysis and tricarboxylic acid cycle metabolites, including pyruvic and citric acids, were reduced. Both the acute and latent phases showed decreased theobromine, taurine, and allantoin levels, with elevated 1-methylhistidine in the latent phase. The chronic phase exhibited reductions in pimelic acid, tiglylglycine, D-lactose, and xanthurenic acid levels. Conclusions: These findings highlight stage-specific urinary metabolic changes in TLE, suggesting distinct metabolites as biomarkers for epileptogenesis and offering insights into the mechanisms underlying SE progression.

Brain Specific RagA Overexpression Triggers Depressive-Like Behaviors in Mice via Activating ADORA2A Signaling Pathway

Neuroinflammation hallmarks the pathology of depression although the etiological complexity has not yet been resolved. Previous studies demonstrate that bacterial lipopolysaccharide induces depressive-like behaviors by activating RagA-mTOR-p70S6K signaling pathway. The current project aims to investigate whether and how brain-specific RagA overexpression triggers depressive-like behaviors in mice. Full-length RagA cDNA is cloned into the mammalian expression vector under the control of brain specific promoter, and subsequently overexpressed in the brain of mouse embryos. Indeed, RagA transgenic mice exhibit depressive-like behaviors and memory impairments. RNA-seq profiling of the prefrontal cortex (PFC) transcriptome highlights adenosine A2a receptor (ADORA2A) as a key differentially expressed gene (DEG). Western blotting confirms that ADORA2A and phospho-p70S6K are markedly elevated in RagA transgenic mice. Behavioral assessments demonstrate that ADORA2A inhibitor istradefylline markedly attenuates depressive-like behaviors. Further metabolomics reveals that N-acetylserotonin and several depression-related metabolites are downregulated while proteomic profiling showed that OLIG1 and other proteins are significantly regulated in RagA transgenic mice. Collectively, RagA overexpression alters the expression patterns of signaling proteins and the metabolism of depression-associated metabolites. RagA may cause depressive-like behaviors in mice via activating p70S6K/ADORA2A signaling pathway. Thus, RagA-p70S6K-ADORA2A signaling pathway may be a target for the development of new antidepressant therapies.

Relationship between oxidative balance score and post-stroke depression: insights from the NHANES 2005-2018 cross-sectional study

Introduction

The Oxidative Balance Score (OBS) represents an integrated measure of oxidative-reductive homeostasis. Despite the established role of oxidative stress in the development of post-stroke depression (PSD), the association between OBS and PSD in the general population remains unclear. This study aims to explore this relationship using data from the National Health and Nutrition Examination Survey (NHANES) spanning 2005-2018.

Methods

The OBS was calculated using validated methods that incorporate dietary and lifestyle factors, whereas PSD status was determined using self-reported data and the Patient Health Questionnaire-9 (PHQ-9) scores. Multivariable logistic regression was employed to evaluate the associations of total OBS, dietary OBS, and lifestyle OBS with PSD prevalence, adjusting for potential confounders. Dose-response relationships were further assessed using restricted cubic splines (RCS).

Results

Among the 26,668 participants included in the analysis, 201 were diagnosed with PSD. After adjusting for confounding variables, higher total OBS, dietary OBS, and lifestyle OBS were each significantly associated with reduced odds of PSD. The adjusted odds ratios (OR) and 95% confidence intervals (CI) for the highest versus lowest quartiles were 0.31 (95% CI: 0.15-0.67) for total OBS, 0.45 (0.27-0.73) for dietary OBS, and 0.28 (0.13-0.60) for lifestyle OBS. RCS analyses indicated a linear dose-response relationship for all three OBS categories with PSD risk. In sex-stratified analyses, significant inverse associations were observed between all OBS categories and PSD in females, whereas only lifestyle OBS was significantly associated with PSD in males.

Conclusion

Higher OBS was associated with reduced odds of PSD, with a particularly pronounced effect in females. These findings suggest that adherence to an antioxidant-rich diet and lifestyle may mitigate PSD risk.

The advantages of multi-level omics research on stem cell-based therapies for ischemic stroke

Stem cell transplantation is a potential therapeutic strategy for ischemic stroke. However, despite many years of preclinical research, the application of stem cells is still limited to the clinical trial stage. Although stem cell therapy can be highly beneficial in promoting functional recovery, the precise mechanisms of action that are responsible for this effect have yet to be fully elucidated. Omics analysis provides us with a new perspective to investigate the physiological mechanisms and multiple functions of stem cells in ischemic stroke. Transcriptomic, proteomic, and metabolomic analyses have become important tools for discovering biomarkers and analyzing molecular changes under pathological conditions. Omics analysis could help us to identify new pathways mediated by stem cells for the treatment of ischemic stroke via stem cell therapy, thereby facilitating the translation of stem cell therapies into clinical use. In this review, we summarize the pathophysiology of ischemic stroke and discuss recent progress in the development of stem cell therapies for the treatment of ischemic stroke by applying multi-level omics. We also discuss changes in RNAs, proteins, and metabolites in the cerebral tissues and body fluids under stroke conditions and following stem cell treatment, and summarize the regulatory factors that play a key role in stem cell therapy. The exploration of stem cell therapy at the molecular level will facilitate the clinical application of stem cells and provide new treatment possibilities for the complete recovery of neurological function in patients with ischemic stroke.

The role of amino acid metabolism alterations in acute ischemic stroke: From mechanism to application

Acute ischemic stroke (AIS) is the most prevalent type of stroke, and due to its high incidence, disability rate, and mortality rate, it imposes a significant burden on the health care system. Amino acids constitute one of the most crucial metabolic products within the human body, and alterations in their metabolic pathways have been identified in the microenvironment of AIS, thereby influencing the pathogenesis, severity, and prognosis of AIS. The amino acid metabolism characteristics in AIS are complex. On one hand, the dynamic progression of AIS continuously reshapes the amino acid metabolism pattern. Conversely, changes in the amino acid metabolism pattern also exert a double-edged effect on AIS. This interaction is bidirectional, dynamic, heterogeneous, and dose-specific. Therefore, the distinctive metabolic reprogramming features surrounding amino acids during the AIS process are systematically summarized in this paper, aiming to provide potential investigative strategies for the early diagnosis, treatment approaches, and prognostic enhancement of AIS.

Inflammatory Pathogenesis of Post-stroke Depression

Post-stroke depression (PSD) is a complex mood disorder that emerges in individuals following a stroke, characterized by the development of depressive symptoms. The pathogensis of PSD is diverse, with inflammation playing a vital role in its onset and progression. Emerging evidence suggests that microglial activation, astrocyte responses, nuclear factor κB(NF-κB) signaling, dysregulation of the hypothalamic pituitary adrenal (HPA) axis, alterations in brain-derived neurotrophic factor (BDNF) expression, neurotransmitter imbalances, adenosine triphosphate (ATP) and its receptors and oxidative stress are intricately linked to the pathogenesis of PSD. The involvement of inflammatory cytokines in these processes highlights the significance of the inflammatory pathway. Integrating these hypotheses, the inflammatory mechanism offers a novel perspective to expand therapeutic strategies for PSD.

Metabolite Biomarkers of Prolonged and Intensified Pain and Distress in Head and Neck Cancer Patients Undergoing Radio- or Chemoradiotherapy by Means of NMR-Based Metabolomics-A Preliminary Study

Treatment of head and neck squamous cell carcinoma (HNSCC) has a detrimental impact on patient quality of life. The rate of recognized distress/depression among HNSCC patients ranges from 9.8% to 83.8%, and the estimated prevalence of depression among patients receiving radiotherapy is 63%. Shorter overall survival also occurs in preexisting depression or depressive conditions. The present study analyzes the nuclear magnetic resonance (NMR) blood serum metabolic profiles during radio-/chemoradiotherapy and correlates the detected alterations with pain and/or distress accumulated with the disease and its treatment. NMR spectra were acquired on a Bruker 400 MHz spectrometer and analyzed using multivariate methods. The results indicate that distress and/or pain primarily affect the serum lipids and metabolites of energy (glutamine, glucose, lactate, acetate) and one-carbon (glycine, choline, betaine, methanol, threonine, serine, histidine, formate) metabolism. Sparse disturbances in the branched-chain amino acids (BCAA) and in the metabolites involved in protein metabolism (lysine, tyrosine, phenylalanine) are also observed. Depending on the treatment modality-radiotherapy or concurrent chemoradiotherapy-there are some differences in the altered metabolites.

A Metabolomic Signature of Ischemic Stroke Showing Acute Oxidative and Energetic Stress

Metabolomics is a powerful data-driven tool for in-depth biological phenotyping that could help identify the specific metabolic profile of cryptogenic strokes, for which no precise cause has been identified. We performed a targeted quantitative metabolomics study in West African patients who had recently suffered an ischemic stroke, which was either cryptogenic (n = 40) or had a clearly identified cause (n = 39), compared to a healthy control group (n = 40). Four hundred fifty-six metabolites were accurately measured. Multivariate analyses failed to reveal any metabolic profile discriminating between cryptogenic ischemic strokes and those with an identified cause but did show superimposable metabolic profiles in both groups, which were clearly distinct from those of healthy controls. The blood concentrations of 234 metabolites were significantly affected in stroke patients compared to controls after the Benjamini-Hochberg correction. Increased methionine sulfoxide and homocysteine concentrations, as well as an overall increase in saturation of fatty acids, were indicative of acute oxidative stress. This signature also showed alterations in energetic metabolism, cell membrane integrity, monocarbon metabolism, and neurotransmission, with reduced concentrations of several metabolites known to be neuroprotective. Overall, our results show that cryptogenic strokes are not pathophysiologically distinct from ischemic strokes of established origin, and that stroke leads to intense metabolic remodeling with marked oxidative and energetic stresses.

Metabolic Alterations and Related Biological Functions of Post-Stroke Depression in Ischemic Stroke Patients

Background

Post-stroke depression (PSD) is one of the most common neuropsychiatric complications after stroke. However, the underlying mechanisms of PSD remain ambiguous, and no objective diagnosis tool is available to diagnose PSD. Previous metabolomic studies on PSD included patients with ischemic and hemorrhagic stroke indiscriminately, which is not conducive to elucidating and predicting the occurrence of PSD. The aim of this study is to elucidate the pathogenesis of PSD and provide potential diagnostic markers for PSD in ischemic stroke patients.

Methods

In total, 51 ischemic stroke patients at 2 weeks were included in this study. Those with depressive symptoms were assigned to the PSD group, while the others were assigned to the non-PSD group. Plasma metabolomics based on liquid chromatography-mass spectrometry (LC-MS) was performed to explore the differential plasma metabolites between the PSD and non-PSD groups.

Results

Principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA) and orthogonal partial least-squares discriminant analysis (OPLS-DA) showed significant metabolic alterations between PSD patients and non-PSD patients. In total, 41 differential metabolites were screened out, mainly including phosphatidylcholines (PCs), L-carnitine and acyl carnitines, succinic acid, pyruvic acid and L-lactic acid. Metabolite-related pathway analysis revealed that alanine, aspartate and glutamate metabolism, glycerophospholipid metabolism and the citrate cycle (TCA cycle) may contribute to the pathogenesis of PSD. A panel of three signature metabolites [PC(22:5(7Z,10Z,13Z,16Z,19Z)/15:0), LysoPA(18:1(9Z)/0:0) and 1,5-anhydrosorbitol] was determined as potential biomarkers for PSD in ischemic stroke patients.

Conclusion

These findings are conducive to providing new insights into the pathogenesis of PSD and developing objective diagnostic tools for PSD in ischemic stroke patients.

An updated review on prediction and preventive treatment of post-stroke depression

INTRODUCTION

Post-stroke depression (PSD), one of the most common complications following stroke, affects approximately one-third of stroke patients and is significantly associated with increased disability and mortality as well as decreased quality of life, which makes it an important public health concern. Treatment of PSD significantly ameliorates depressive symptoms and improves the prognosis of stroke.

AREAS COVERED

The authors discuss the critical aspects of the clinical application of prediction and preventive treatment of PSD. Then, the authors update the biological factors associated with the onset of PSD. Furthermore, they summarize the recent progress in pharmacological preventive treatment in clinical trials and propose potential treatment targets. The authors also discuss the current roadblocks in the preventive treatment of PSD. Finally, the authors put postulate potential directions for future studies so as to discover accurate predictors and provide individualized preventive treatment.

EXPERT OPINION

Sorting out high-risk PSD patients using reliable predictors will greatly assist PSD management. Indeed, some predictors not only predict the incidence of PSD but also predict prognosis, which indicates that they might also aid the development of an individualized treatment scheme. Preventive application of antidepressants may also be considered.

Metabolomics combined with clinical analysis explores metabolic changes and potential serum metabolite biomarkers of antineutrophil cytoplasmic antibody-associated vasculitis with renal impairment

Background

Antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is an autoimmune systemic disease, and the majority of AAV patients have renal involvement presenting as rapid progressive glomerulonephritis (GN). Currently, the clinically available AAV markers are limited, and some of the newly reported markers are still in the nascent stage. The particular mechanism of the level changes of various markers and their association with the pathogenesis of AAV are not well defined. With the help of metabolomics analysis, this study aims to explore metabolic changes in AAV patients with renal involvement and lay the foundation for the discovery of novel biomarkers for AAV-related kidney damage.

Methods

We performed liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based on serum samples from patients with AAV (N = 33) and healthy controls (N = 33) in order to characterize the serum metabolic profiling. The principal component analysis (PCA) and orthogonal partial least-squares-discriminant analysis (OPLS-DA) were used to identify the differential metabolites. Least Absolute Shrinkage and Selection Operator (LASSO) and eXtreme Gradient Boosting (XGBoost) analysis were further conducted to identify the potential diagnostic biomarker. A receiver operating characteristic (ROC) curve analysis was conducted to evaluate the diagnostic performance of the identified potential biomarker.

Results

A total of 455 metabolites were detected by LC-MS analysis. PCA and OPLS-DA demonstrated a significant difference between AAV patients with renal involvement and healthy controls, and 135 differentially expressed metabolites were selected, with 121 upregulated and 14 downregulated. Ninety-two metabolic pathways were annotated and enriched based on the KEGG database. N-acetyl-L-leucine, Acetyl-DL-Valine, 5-hydroxyindole-3-acetic acid, and the combination of 1-methylhistidine and Asp-phe could accurately distinguish AAV patients with renal involvement from healthy controls. And 1-methylhistidine was found to be significantly associated with the progression and prognosis of AAV with renal impairment. Amino acid metabolism exhibits significant alternations in AAV with renal involvement.

Conclusion

This study identified metabolomic differences between AAV patients with renal involvement and non-AAV individuals. Metabolites that could accurately distinguish patients with AAV renal impairment from healthy controls in this study, and metabolites that were significantly associated with disease progression and prognosis were screened out. Overall, this study provides information on changes in metabolites and metabolic pathways for future studies of AAV-related kidney damage and lays a foundation for the exploration of new biomarkers of AAV-related kidney damage.

Multi-omics research strategies in ischemic stroke: A multidimensional perspective

Ischemic stroke (IS) is a multifactorial and heterogeneous neurological disorder with high rate of death and long-term impairment. Despite years of studies, there are still no stroke biomarkers for clinical practice, and the molecular mechanisms of stroke remain largely unclear. The high-throughput omics approach provides new avenues for discovering biomarkers of IS and explaining its pathological mechanisms. However, single-omics approaches only provide a limited understanding of the biological pathways of diseases. The integration of multiple omics data means the simultaneous analysis of thousands of genes, RNAs, proteins and metabolites, revealing networks of interactions between multiple molecular levels. Integrated analysis of multi-omics approaches will provide helpful insights into stroke pathogenesis, therapeutic target identification and biomarker discovery. Here, we consider advances in genomics, transcriptomics, proteomics and metabolomics and outline their use in discovering the biomarkers and pathological mechanisms of IS. We then delineate strategies for achieving integration at the multi-omics level and discuss how integrative omics and systems biology can contribute to our understanding and management of IS.

Peripheral blood and urine metabolites and biological functions in post-stroke depression

Post-stroke depression (PSD) is the most common and severe neuropsychiatric complication after stroke. However, the molecular mechanism of PSD is still unclear. Previous studies have identified peripheral blood and urine metabolites associated with PSD using metabolomics techniques. We searched and systematically summarized metabolites that may be involved in metabolic changes in peripheral blood and urine of patients with PSD from the Metabolite Network of Depression Database (MENDA) and other biomedical databases. MetaboAnalyst5.0 software was used for pathway analysis and enrichment analysis of differential metabolites, and subgroup analyses were performed according to tissue types and metabolomics techniques. We identified 47 metabolites that were differentially expressed between patients with and without PSD. Five differential metabolites were found in both plasma and urine, including L-glutamic acid, pyroglutamic acid, palmitic acid, L-phenylalanine, and L-tyrosine. We integrated these metabolites into metabolic pathways, and six pathways were significantly altered. These pathways could be roughly divided into three modules including amino acid metabolism, nucleotide metabolism, and glucose metabolism. Among them, the most significantly altered pathway was "phenylalanine metabolism" and the pathway containing the most associated metabolites was "aminoacyl-tRNA biosynthesis", which deserve further study to elucidate their role in the molecular mechanism of PSD. In summary, metabolic changes in peripheral blood and urine are associated with PSD, especially the disruption of "phenylalanine metabolism" and "aminoacyl-tRNA biosynthesis" pathways. This study provides clues to the metabolic characteristics of patients with PSD, which may help to elucidate the molecular pathogenesis of PSD.

Does urinary metabolite signature act as a biomarker of post-stroke depression?

BACKGROUND

It is difficult to conduct the precise diagnosis of post-stroke depression (PSD) in clinical practice due to the complex psychopathology of depressive disorder. Several studies showed that gas chromatography-mass spectrometry (GC-MS)-identified urinary metabolite biomarkers could significantly discriminate PSD from stroke survivors.

METHODS

A systematic review was performed for the keywords of "urinary metabolite" and "PSD" using Medline, Cochrane Library, Embase, Web of Science, PsycINFO, Wanfang, CNKI, CBM, and VIP database from inception to 31 March 2022.

RESULTS

Four related studies were included in the review. Differential urinary metabolites including lactic acid, palmitic acid, azelaic acid, and tyrosine were identified in all the included studies. As a significant deviation in the metabolite biomarker panel, glyceric acid, azelaic acid, phenylalanine, palmitic acid, pseudouridine, and tyrosine were found in at least 2 included studies, which indicated good potential for the differentiation of PSD.

CONCLUSION

The systematic review provided evidence that differential urinary metabolites analyzed by the GC-MS-based approach might be used as a biomarker for the diagnosis and prognosis of PSD.

Metabolomics Analysis of the Prefrontal Cortex in a Rat Chronic Unpredictable Mild Stress Model of Depression

BACKGROUND

Depressive disorder is the leading cause of disability and suicidality worldwide. Metabolites are considered indicators and regulators of depression. However, the pathophysiology of the prefrontal cortex (PFC) in depression remains unclear.

METHODS

A chronic unpredictable mild stress (CUMS) model and a maturation rodent model of depression was used to investigate metabolic changes in the PFC. Eighteen male Sprague-Dawley rats were randomly divided into CUMS and control groups. The sucrose preference test (SPT) and forced swimming test (FST) were employed to evaluate and record depression-associated behaviors and changes in body weight (BW). High-performance liquid chromatography-tandem mass spectrometry was applied to test metabolites in rat PFC. Furthermore, principal component analysis and orthogonal partial least-squares discriminant analysis were employed to identify differentially abundant metabolites. Metabolic pathways were analyzed using MetaboAnalyst. Finally, a metabolite-protein interaction network was established to illustrate the function of differential metabolites.

RESULTS

SPT and FST results confirmed successful establishment of the CUMS-induced depression-like behavior model in rats. Five metabolites, including 1-methylnicotinamide, 3-methylhistidine, acetylcholine, glycerophospho-N-palmitoyl ethanolamine, α-D-mannose 1-phosphate, were identified as potential biomarkers of depression. Four pathways changed in the CUMS group. Metabolite-protein interaction analysis revealed that 10 pathways play roles in the metabolism of depression.

CONCLUSION

Five potential biomarkers were identified in the PFC and metabolite-protein interactions associated with metabolic pathophysiological processes were explored using the CUMS model. The results of this study will assist physicians and scientists in discovering potential diagnostic markers and novel therapeutic targets for depression.

Changes of Metabolites in Acute Ischemic Stroke and Its Subtypes

Existing techniques have many limitations in the diagnosis and classification of ischemic stroke (IS). Considering this, we used metabolomics to screen for potential biomarkers of IS and its subtypes and to explore the underlying related pathophysiological mechanisms. Serum samples from 99 patients with acute ischemic stroke (AIS) [the AIS subtypes included 49 patients with large artery atherosclerosis (LAA) and 50 patients with small artery occlusion (SAO)] and 50 matched healthy controls (HCs) were analyzed by non-targeted metabolomics based on liquid chromatography–mass spectrometry. A multivariate statistical analysis was performed to identify potential biomarkers. There were 18 significantly different metabolites, such as oleic acid, linoleic acid, arachidonic acid, L-glutamine, L-arginine, and L-proline, between patients with AIS and HCs. These different metabolites are closely related to many metabolic pathways, such as fatty acid metabolism and amino acid metabolism. There were also differences in metabolic profiling between the LAA and SAO groups. There were eight different metabolites, including L-pipecolic acid, 1-Methylhistidine, PE, LysoPE, and LysoPC, which affected glycerophospholipid metabolism, glycosylphosphatidylinositol-anchor biosynthesis, histidine metabolism, and lysine degradation. Our study effectively identified the metabolic profiles of IS and its subtypes. The different metabolites between LAA and SAO may be potential biomarkers in the context of clinical diagnosis. These results highlight the potential of metabolomics to reveal new pathways for IS subtypes and provide a new avenue to explore the pathophysiological mechanisms underlying IS and its subtypes.

Metabolomics facilitates the discovery of metabolic biomarkers and pathways for ischemic stroke: a systematic review

INTRODUCTION

Ischemic stroke (IS) is a major contributor to the global disease burden, and effective biomarkers for IS management in clinical practice are urgently needed. Metabolomics can detect metabolites that are small enough to cross the blood-brain barrier in a high-throughput manner, and thus represents a powerful tool for discovering biomarkers of IS.

OBJECTIVES

In this study, we conducted a systematic review to identify potential metabolic biomarkers and pathways that might facilitate risk predictions, clinical diagnoses, the recognition of complications, predictions of recurrence and an understanding of the pathogenesis of IS.

METHODS

The PubMed and Web of Science databases were searched for relevant studies published between January 2000 and July 2019. The study objectives, study designs and reported metabolic biomarkers were systematically examined and compared. Pathway analysis was performed using the MetaboAnalyst online software.

RESULTS

Twenty-eight studies were included in this systematic review. Many consistent metabolites, including isoleucine, leucine, valine, glycine, lysine, glutamate, LysoPC(16:0), LysoPC(18:2), serine, uric acid, citrate and palmitic acid, possess potential as biomarkers of IS. Metabolic pathways and dysregulations that are implicated in excitotoxicity, inflammation, apoptosis, oxidative stress, neuroprotection, energy failure, and elevation of intracellular Ca²⁺ levels, were indicated as playing important roles in the development and progression of IS.

CONCLUSIONS

This systematic review summarizes potential metabolic biomarkers and pathways related to IS, which may provide opportunities for the construction of diagnostic or predictive models for IS and the discovery of novel therapeutic targets.