Discovery of Metabolite Biomarkers for Acute Ischemic Stroke Progression

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.

Lipidomic analysis identifies long-chain acylcarnitine as a target for ischemic stroke

INTRODUCTION

Lipid metabolism dysfunction is widely involved in the pathological process of acute ischemic stroke (AIS). The coordination of lipid metabolism between neurons and astrocytes is of great significance. However, the full scope of lipid dynamic changes and the function of key lipids during AIS remain unknown. Hence, identifying lipid alterations and characterizing their key roles in AIS is of great importance.

METHODS

Untargeted and targeted lipidomic analyses were applied to profile lipid changes in the ischemic penumbra and peripheral blood of transient middle cerebral artery occlusion (tMCAO) mice as well as the peripheral blood of AIS patients. Infarct volume and neurological deficits were assessed after tMCAO. The cell viability and dendritic complexity of primary neurons were evaluated by CCK8 assay and Sholl analysis. Seahorse, MitoTracker Green, tetramethyl rhodamine methyl ester (TMRM), 2',7'-dichlorodihydrofluorescein diacetate (DCFH-DA) and MitoSOX were used as markers of mitochondrial health. Fluorescent and isotopic free fatty acid (FFA) pulse-chase assays were used to track FFA flux in astrocytes.

RESULTS

Long-chain acylcarnitines (LCACs) were the lipids with the most dramatic changes in the ischemic penumbra and peripheral blood of tMCAO mice. LCACs were significantly elevated on admission in AIS patients and associated with poor outcomes in AIS patients. Increasing LCACs through a bolus administration of palmitoylcarnitine amplified stroke injury, while decreasing LCACs by overexpressing carnitine palmitoyltransferase 2 (CPT2) ameliorated stroke injury. Palmitoylcarnitine aggravated astrocytic mitochondrial damage after OGD/R, while CPT2 overexpression in astrocytes ameliorated cocultured neuron viability. Further study revealed that astrocytes stimulated by OGD/R liberated FFAs from lipid droplets into mitochondria to form LCACs, resulting in mitochondrial damage and lowered astrocytic metabolic support and thereby aggravated neuronal damage.

CONCLUSION

LCACs could accumulate and damage neurons by inducing astrocytic mitochondrial dysfunction in AIS. LCACs play a crucial role in the pathology of AIS and are novel promising diagnostic and prognostic biomarkers for AIS.

Characterization of the Components and Metabolites of Achyranthes Bidentata in the Plasma and Brain Tissue of Rats Based on Ultrahigh Performance Liquid Chromatography-High-Resolution Mass Spectrometry (UHPLC-HR-MS)

BACKGROUND

Achyranthes bidentata (AR) is a traditional Chinese herb used for the treatment of hypertension and cerebral ischemia, but its pharmacological effects are not known.

AIM OF STUDY

We aimed to detect and accurately identify the components and metabolites of AR in the plasma and brain tissue of Sprague Dawley rats.

METHODS

We employed ultrahigh performance liquid chromatography-high-resolution mass spectrometry (UHPLC-HR-MS) to detect AR components in the plasma and brain tissue of rats. The absorption and metabolites in the plasma and brain tissue of normal control rats and rats that underwent middle cerebral artery occlusion (MCAO) were characterized and compared.

RESULTS

A total of 281 compounds, including alkaloids, flavonoids, terpenoids, phenylpropanes, sugars and glycosides, steroids, triterpenes, amino acids, and peptides, was identified in samples of Achyranthes bidentata (TCM-AR). Four types of absorbable prototype components and 48 kinds of metabolites were identified in rats in the normal control plasma group which were given AR (AR plasma group), and five kinds of metabolites were identified in rats of the normal control brain tissue group which were given AR (AR brain group). Three absorbed prototype components and 13 metabolites were identified in the plasma of rats which underwent MCAO and were given AR (MCAO + AR plasma group). Six absorbed prototype components and two metabolites were identified in the brain tissue of rats who underwent MCAO and were administered AR (MCAO + AR brain group). These results showed that, after the oral administration of AR, the number of identified components in plasma was more than that in brain tissue. The number of prototype components in the AR plasma group was higher than that in the MCAO + AR plasma group, which may indicate that metabolite absorption in rats undergoing MCAO was worse. The number of prototype components in the MCAO + AR brain group was higher than that in the AR brain group, indicating that the blood-brain barrier was destroyed after MCAO, resulting in more compounds entering brain tissue.

CONCLUSIONS

UHPLC-HR-MS was used to rapidly analyze the components and metabolites of AR in the blood and brain of rats under normal and pathologic conditions, and to comprehensively characterize the components of TCM-AR. We also analyzed and compared the absorbable components and metabolites of normal rats under cerebral ischemia-reperfusion injury to explore the potential mechanism of action. This method could be applied to various Chinese herbs and disease models, which could promote TCM modernization.

Exploring the causal association between genetically determined circulating metabolome and hemorrhagic stroke

Background

Hemorrhagic stroke (HS), a leading cause of death and disability worldwide, has not been clarified in terms of the underlying biomolecular mechanisms of its development. Circulating metabolites have been closely associated with HS in recent years. Therefore, we explored the causal association between circulating metabolomes and HS using Mendelian randomization (MR) analysis and identified the molecular mechanisms of effects.

Methods

We assessed the causal relationship between circulating serum metabolites (CSMs) and HS using a bidirectional two-sample MR method supplemented with five ways: weighted median, MR Egger, simple mode, weighted mode, and MR-PRESSO. The Cochran Q-test, MR-Egger intercept test, and MR-PRESSO served for the sensitivity analyses. The Steiger test and reverse MR were used to estimate reverse causality. Metabolic pathway analyses were performed using MetaboAnalyst 5.0, and genetic effects were assessed by linkage disequilibrium score regression. Significant metabolites were further synthesized using meta-analysis, and we used multivariate MR to correct for common confounders.

Results

We finally recognized four metabolites, biliverdin (OR 0.62, 95% CI 0.40-0.96, PMVMR = 0.030), linoleate (18. 2n6) (OR 0.20, 95% CI 0.08-0.54, PMVMR = 0.001),1-eicosadienoylglycerophosphocholine* (OR 2.21, 95% CI 1.02-4.76, PMVMR = 0.044),7-alpha-hydroxy-3 -oxo-4-cholestenoate (7-Hoca) (OR 0.27, 95% CI 0.09-0.77, PMVMR = 0.015) with significant causal relation to HS.

Conclusion

We demonstrated significant causal associations between circulating serum metabolites and hemorrhagic stroke. Monitoring, diagnosis, and treatment of hemorrhagic stroke by serum metabolites might be a valuable approach.

Inflammation and Organic Cation Transporters Novel (OCTNs)

Inflammation is a physiological condition characterized by a complex interplay between different cells handled by metabolites and specific inflammatory-related molecules. In some pathological situations, inflammation persists underlying and worsening the pathological state. Over the years, two membrane transporters namely OCTN1 (SLC22A4) and OCTN2 (SLC22A5) have been shown to play specific roles in inflammation. These transporters form the OCTN subfamily within the larger SLC22 family. The link between these proteins and inflammation has been proposed based on their link to some chronic inflammatory diseases such as asthma, Crohn's disease (CD), and rheumatoid arthritis (RA). Moreover, the two transporters show the ability to mediate the transport of several compounds including carnitine, carnitine derivatives, acetylcholine, ergothioneine, and gut microbiota by-products, which have been specifically associated with inflammation for their anti- or proinflammatory action. Therefore, the absorption and distribution of these molecules rely on the presence of OCTN1 and OCTN2, whose expression is modulated by inflammatory cytokines and transcription factors typically activated by inflammation. In the present review, we wish to provide a state of the art on OCTN1 and OCTN2 transport function and regulation in relationships with inflammation and inflammatory diseases focusing on the metabolic signature collected in different body districts and gene polymorphisms related to inflammatory diseases.

NMR based Serum metabolomics revealed metabolic signatures associated with oxidative stress and mitochondrial damage in brain stroke

Brain stroke (BS, also known as a cerebrovascular accident), represents a serious global health crisis. It has been a leading cause of permanent disability and unfortunately, frequent fatalities due to lack of timely medical intervention. While progress has been made in prevention and management, the complexities and consequences of stroke continue to pose significant challenges, especially, its impact on patient's quality of life and independence. During stroke, there is a substantial decrease in oxygen supply to the brain leading to alteration of cellular metabolic pathways, including those involved in mitochondrial-damage, leading to mitochondrial-dysfunction. The present proof-of-the-concept metabolomics study has been performed to gain insights into the metabolic pathways altered following a brain stroke and discover new potential targets for timely interventions to mitigate the effects of cellular and mitochondrial damage in BS. The serum metabolic profiles of 108 BS-patients were measured using 800 MHz NMR spectroscopy and compared with 60 age and sex matched normal control (NC) subjects. Compared to NC, the serum levels of glutamate, TCA-cycle intermediates (such as citrate, succinate, etc.), and membrane metabolites (betaine, choline, etc.) were found to be decreased BS patients, whereas those of methionine, mannose, mannitol, phenylalanine, urea, creatine and organic acids (such as 3-hydroxybutyrate and acetone) were found to be elevated in BS patients. These metabolic changes hinted towards hypoxia mediated mitochondrial dysfunction in BS-patients. Further, the area under receiver operating characteristic curve (ROC) values for five metabolic features (methionine, mannitol, phenylalanine, mannose and urea) found to be more than 0.9 suggesting their high sensitivity and specificity for differentiating BS from NC subjects.

Plasma lipidomic profiling reveals six candidate biomarkers for the prediction of incident stroke in patients with hypertension

INTRODUCTION

The burden of stroke in patients with hypertension is very high, and its prediction is critical.

OBJECTIVES

We aimed to use plasma lipidomics profiling to identify lipid biomarkers for predicting incident stroke in patients with hypertension.

METHODS

This was a nested case-control study. Baseline plasma samples were collected from 30 hypertensive patients with newly developed stroke, 30 matched patients with hypertension, 30 matched patients at high risk of stroke, and 30 matched healthy controls. Lipidomics analysis was performed by ultrahigh-performance liquid chromatography-tandem mass spectrometry, and differential lipid metabolites were screened using multivariate and univariate statistical methods. Machine learning methods (least absolute shrinkage and selection operator, random forest) were used to identify candidate biomarkers for predicting stroke in patients with hypertension.

RESULTS

Co-expression network analysis revealed that the key molecular alterations of the lipid network in stroke implicate glycerophospholipid metabolism and choline metabolism. Six lipid metabolites were identified as candidate biomarkers by multivariate statistical and machine learning methods, namely phosphatidyl choline(40:3p)(rep), cholesteryl ester(20:5), monoglyceride(29:5), triglyceride(18:0p/18:1/18:1), triglyceride(18:1/18:2/21:0) and coenzyme(q9). The combination of these six lipid biomarkers exhibited good diagnostic and predictive ability, as it could indicate a risk of stroke at an early stage in patients with hypertension (area under the curve = 0.870; 95% confidence interval: 0.783-0.957).

CONCLUSIONS

We determined lipidomic signatures associated with future stroke development and identified new lipid biomarkers for predicting stroke in patients with hypertension. The biomarkers have translational potential and thus may serve as blood-based biomarkers for predicting hypertensive stroke.

Identify production area, growth mode, species, and grade of Astragali Radix using metabolomics "big data" and machine learning

BACKGROUND

Astragali Radix (AR) is a widely used herbal medicine. The quality of AR is influenced by several key factors, including the production area, growth mode, species, and grade. However, the markers currently used to distinguish these factors primarily focus on secondary metabolites, and their validation on large-scale samples is lacking.

PURPOSE

This study aims to discover reliable markers and develop classification models for identifying the production area, growth mode, species, and grade of AR.

METHODS

A total of 366 batches of AR crude slices were collected from six provinces in China and divided into learning (n = 191) and validation (n = 175) sets. Three ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) methods were developed and validated for determining 22 primary and 10 secondary metabolites in AR methanol extract. Based on the quantification data, seven machine learning algorithms, such as Nearest Neighbors and Gradient Boosted Trees, were applied to screen the potential markers and build the classification models for identifying the four factors associated with AR quality.

RESULTS

Our analysis revealed that secondary metabolites (e.g., astragaloside IV, calycosin-7-O-β-D-glucoside, and ononin) played a crucial role in evaluating AR quality, particularly in identifying the production area and species. Additionally, fatty acids (e.g., behenic acid and lignoceric acid) were vital in determining the growth mode of AR, while amino acids (e.g., alanine and phenylalanine) were helpful in distinguishing different grades. With both primary and secondary metabolites, the Nearest Neighbors algorithm-based model was constructed for identifying each factor of AR, achieving good classification accuracy (>70%) on the validation set. Furthermore, a panel of four metabolites including ononin, astragaloside II, pentadecanoic acid, and alanine, allowed for simultaneous identification of all four factors of AR, offering an accuracy of 86.9%.

CONCLUSION

Our findings highlight the potential of integrating large-scale targeted metabolomics and machine learning approaches to accurately identify the quality-associated factors of AR. This study opens up possibilities for enhancing the evaluation of other herbal medicines through similar methodologies, and further exploration in this area is warranted.

Blood and Brain Metabolites after Cerebral Ischemia

The study of an organism's response to cerebral ischemia at different levels is essential to understanding the mechanism of the injury and protection. A great interest is devoted to finding the links between quantitative metabolic changes and post-ischemic damage. This work aims to summarize the outcomes of the most studied metabolites in brain tissue-lactate, glutamine, GABA (4-aminobutyric acid), glutamate, and NAA (N-acetyl aspartate)-regarding their biological function in physiological conditions and their role after cerebral ischemia/reperfusion. We focused on ischemic damage and post-ischemic recovery in both experimental-including our results-as well as clinical studies. We discuss the role of blood glucose in view of the diverse impact of hyperglycemia, whether experimentally induced, caused by insulin resistance, or developed as a stress response to the cerebral ischemic event. Additionally, based on our and other studies, we analyze and critically discuss post-ischemic alterations in energy metabolites and the elevation of blood ketone bodies observed in the studies on rodents. To complete the schema, we discuss alterations in blood plasma circulating amino acids after cerebral ischemia. So far, no fundamental brain or blood metabolite(s) has been recognized as a relevant biological marker with the feasibility to determine the post-ischemic outcome or extent of ischemic damage. However, studies from our group on rats subjected to protective ischemic preconditioning showed that these animals did not develop post-ischemic hyperglycemia and manifested a decreased metabolic infringement and faster metabolomic recovery. The metabolomic approach is an additional tool for understanding damaging and/or restorative processes within the affected brain region reflected in the blood to uncover the response of the whole organism via interorgan metabolic communications to the stressful cerebral ischemic challenge.

LC-MS/MS based metabolomic analysis of serum from patients with cerebrovascular stenosis

Cerebrovascular stenosis (CVS) is the main cause of ischemic stroke, which greatly threatens human life. Hence, it's important to perform early screenings for CVS. Metabolomics is an emerging omics approach that has great advantages in disease screening and diagnosis. Therefore, we aim to elucidate the correlation between CVS and metabolomics, which can aid in conducting CVS screening at an early stage. Patients with CVS in Beijing Hospital were included in the study. A total of 36 participants, including 18 patients diagnosed with CVS and 18 healthy individuals, were recruited at Beijing Hospital between May 2022 and October 2021. The serum samples were analyzed for liquid chromatography-tandem mass spectrometry (LC-MS/MS). Then, multivariate statistical methods, including principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) were performed. Differential metabolites were obtained and demonstrated by volcano plot and heatmap. The study recruited 36 participants, including 18 patients with CVS and 18 healthy participants. A total of 150 metabolites were identified. Multivariate statistical analysis revealed significant differences between patients and healthy participants. Furthermore, 30 serum metabolites levels differed significantly between two groups. Differential metabolites were enriched in phenylalanine, tyrosine, and tryptophan biosynthesis; primary bile acid biosynthesis, and other pathways. This study identified differential metabolites in patients with CVS and elucidated the relevant metabolic pathways. Thus, these findings aid in the study of the pathogenesis of CVS and its early diagnosis. DATA AVAILABILITY STATEMENT: The datasets generated for this study are available on request to the corresponding author.

Metabolomics: A useful tool for ischemic stroke research

Ischemic stroke (IS) is a multifactorial and heterogeneous disease. Despite years of studies, effective strategies for the diagnosis, management and treatment of stroke are still lacking in clinical practice. Metabolomics is a growing field in systems biology. It is starting to show promise in the identification of biomarkers and in the use of pharmacometabolomics to help patients with certain disorders choose their course of treatment. The development of metabolomics has enabled further and more biological applications. Particularly, metabolomics is increasingly being used to diagnose diseases, discover new drug targets, elucidate mechanisms, and monitor therapeutic outcomes and its potential effect on precision medicine. In this review, we reviewed some recent advances in the study of metabolomics as well as how metabolomics might be used to identify novel biomarkers and understand the mechanisms of IS. Then, the use of metabolomics approaches to investigate the molecular processes and active ingredients of Chinese herbal formulations with anti-IS capabilities is summarized. We finally summarized recent developments in single cell metabolomics for exploring the metabolic profiles of single cells. Although the field is relatively young, the development of single cell metabolomics promises to provide a powerful tool for unraveling the pathogenesis of IS.

Lipidomic signature of stroke recurrence after transient ischemic attack

While TIA patients have transient symptoms, they should not be underestimated, as they could have an underlying pathology that may lead to a subsequent stroke: stroke recurrence (SR). Previously, it has been described the involvement of lipids in different vascular diseases. The aim of the current study was to perform a lipidomic analysis to identify differences in the lipidomic profile between patients with SR and patients without. Untargeted lipidomic analysis was performed in plasma samples of 460 consecutive TIA patients recruited < 24 h after the onset of symptoms. 37 (8%) patients suffered SR at 90 days. Lipidomic profiling disclosed 7 lipid species differentially expressed between groups: 5 triacylglycerides (TG), 1 diacylglyceride (DG), and 1 alkenyl-PE (plasmalogen) [specifically, TG(56:1), TG(63:0), TG(58:2), TG(50:5), TG(53:7, DG(38:5)) and PE(P-18:0/18:2)]. 6 of these 7 lipid species belonged to the glycerolipid family and a plasmalogen, pointing to bioenergetics pathways, as well as oxidative stress response. In this context, it was proposed the PE(P-18:0/18:2) as potential biomarker of SR condition.The observed changes in lipid patterns suggest pathophysiological mechanisms associated with lipid droplets metabolism and antioxidant protection that is translated to plasma level as consequence of a more intensive or high-risk ischemic condition related to SR.

Untargeted metabonomic analysis of a cerebral stroke model in rats: a study based on UPLC-MS/MS

Introduction

Brain tissue damage caused by ischemic stroke can trigger changes in the body's metabolic response, and understanding the changes in the metabolic response of the gut after stroke can contribute to research on poststroke brain function recovery. Despite the increase in international research on poststroke metabolic mechanisms and the availability of powerful research tools in recent years, there is still an urgent need for poststroke metabolic studies. Metabolomic examination of feces from a cerebral ischemia-reperfusion rat model can provide new insights into poststroke metabolism and identify key metabolic pathways, which will help reveal diagnostic and therapeutic targets as well as inspire pathophysiological studies after stroke.

Methods

We randomly divided 16 healthy adult pathogen-free male Sprague-Dawley (SD) rats into the normal group and the study group, which received middle cerebral artery occlusion/reperfusion (MCAO/R). Ultra-performance liquid chromatography-tandem mass spectrometry (UPLCMS/MS) was used to determine the identities and concentrations of metabolites across all groups, and filtered high-quality data were analyzed for differential screening and differential metabolite functional analysis.

Results

After 1 and 14 days of modeling, compared to the normal group, rats in the study group showed significant neurological deficits (p < 0.001) and significantly increased infarct volume (day 1: p < 0.001; day 14: p = 0.001). Mass spectra identified 1,044 and 635 differential metabolites in rat feces in positive and negative ion modes, respectively, which differed significantly between the normal and study groups. The metabolites with increased levels identified in the study group were involved in tryptophan metabolism (p = 0.036678, p < 0.05), arachidonic acid metabolism (p = 0.15695), cysteine and methionine metabolism (p = 0.24705), and pyrimidine metabolism (p = 0.3413), whereas the metabolites with decreased levels were involved in arginine and proline metabolism (p = 0.15695) and starch and sucrose metabolism (p = 0.52256).

Discussion

We determined that UPLC-MS/MS could be employed for untargeted metabolomics research. Moreover, tryptophan metabolic pathways may have been disordered in the study group. Alterations in the tryptophan metabolome may provide additional theoretical and data support for elucidating stroke pathogenesis and selecting pathways for intervention.

Combined Metabolipidomic and Machine Learning Approach in a Rat Model of Stroke Reveals a Deleterious Impact of Brain Injury on Heart Metabolism

Cardiac complications are frequently found following a stroke in humans whose pathophysiological mechanism remains poorly understood. We used machine learning to analyse a large set of data from a metabolipidomic study assaying 630 metabolites in a rat stroke model to investigate metabolic changes affecting the heart within 72 h after a stroke. Twelve rats undergoing a stroke and 28 rats undergoing the sham procedure were investigated. A plasmatic signature consistent with the literature with notable lipid metabolism remodelling was identified. The post-stroke heart showed a discriminant metabolic signature, in comparison to the sham controls, involving increased collagen turnover, increased arginase activity with decreased nitric oxide synthase activity as well as an altered amino acid metabolism (including serine, asparagine, lysine and glycine). In conclusion, these results demonstrate that brain injury induces a metabolic remodelling in the heart potentially involved in the pathophysiology of stroke heart syndrome.

Identification of three potential novel biomarkers for early diagnosis of acute ischemic stroke via plasma lipidomics

INTRODUCTION

Acute ischemic stroke (AIS) accounts for the majority of all stroke, globally the second leading cause of death. Due to its rapid development after onset, its early diagnosis is crucial.

OBJECTIVES

We aim to identify potential highly reliable blood-based biomarkers for early diagnosis of AIS using quantitative plasma lipid profiling via a machine learning approach.

METHODS

Lipidomics was used for quantitative plasma lipid profiling, based on ultra-performance liquid chromatography tandem mass spectrometry. Our samples were divided into a discovery and a validation set, each containing 30 AIS patients and 30 health controls (HC). Differentially expressed lipid metabolites were screened based on the criteria VIP > 1, p < 0.05, and fold change > 1.5 or < 0.67. The least absolute shrinkage and selection operator (LASSO) and random forest algorithms in machine learning were used to select differential lipid metabolites as potential biomarkers.

RESULTS

Three key differential lipid metabolites, CarnitineC10:1, CarnitineC10:1-OH and Cer(d18:0/16:0), were identified as potential biomarkers for early diagnosis of AIS. The former two, associated with thermogenesis, were down-regulated, whereas the latter, associated with necroptosis and sphingolipd metabolism, was upregulated. Univariate and multivariate logistic regressions showed that these three lipid metabolites and the resulting diagnostic model exhibited a strong ability in discriminating between AIS patients and HCs in both the discovery and validation sets, with an area under the curve above 0.9.

CONCLUSIONS

Our work provides valuable information on the pathophysiology of AIS and constitutes an important step toward clinical application of blood-based biomarkers for diagnosing AIS.

Neuroprotective Effects and Metabolomics Study of Protopanaxatriol (PPT) on Cerebral Ischemia/Reperfusion Injury In Vitro and In Vivo

Stroke, one of the leading causes of disability and death worldwide, is a severe neurological disease that threatens human life. Protopanaxatriol (PPT), panaxatriol-type saponin aglycone, is a rare saponin that exists in Panax ginseng and Panax Noto-ginseng. In this study, we established an oxygen-glucose deprivation (OGD)-PC12 cell model and middle cerebral artery occlusion/reperfusion (MCAO/R) model to evaluate the neuroprotective effects of PPT in vitro and in vivo. In addition, metabolomics analysis was performed on rat plasma and brain tissue samples to find relevant biomarkers and metabolic pathways. The results showed that PPT could significantly regulate the levels of LDH, MDA, SOD, TNF-α and IL-6 factors in OGD-PC12 cells in vitro. PPT can reduce the neurological deficit score and infarct volume of brain tissue in rats, restore the integrity of the blood-brain barrier, reduce pathological damage, and regulate TNF-α, IL-1β, IL-6, MDA, and SOD factors. In addition, the results of metabolomics found that PPT can regulate 19 biomarkers involving five metabolic pathways, including amino acid metabolism, arachidonic acid metabolism, sphingolipid metabolism, and glycerophospholipid metabolism. Thus, it could be inferred that PPT might serve as a novel natural agent for MCAO/R treatment.

Nuclear Magnetic Resonance-Based Metabolomics to Predict Early and Late Adverse Outcomes in Ischemic Stroke Treated with Intravenous Thrombolysis

Metabolic perturbations and inflammatory mediators play a fundamental role in both early and late adverse post-acute ischemic stroke outcomes. Using data from the observational MAGIC (MArker bioloGici nell'Ictus Cerebrale) study, we evaluated the effect of 130 serum metabolic features, using a nuclear magnetic spectroscopy approach, on the following outcomes: hemorrhagic transformation at 24 h after stroke, non-response to intravenous thrombolytic treatment with the recombinant tissue plasminogen activator (rt-PA), and the 3 month functional outcome. Blood circulating metabolites, lipoproteins, and inflammatory markers were assessed at the baseline and 24 h after rt-PA treatment. Adjusting for the major determinants for unfavorable outcomes (i.e., age, sex, time onset-to-treatment, etc.), we found that acetone and 3-hydroxybutyrate were associated with symptomatic hemorrhagic transformation and with non-response to rt-PA; while 24 h after rt-PA, levels of triglycerides high-density lipoprotein (HDL) and triglycerides low-density lipoprotein (LDL) were associated with 3 month mortality. Cholesterol and phospholipids levels, mainly related to smaller and denser very low-density lipoprotein (VLDL) and LDL subfractions were associated with 3 month poor functional outcomes. We also reported associations between baseline 24 h relative variation (Δ) in VLDL subfractions and ΔC-reactive protein, Δinterleukin-10 levels with hemorrhagic transformation. All observed metabolic changes reflect a general condition of energy failure, oxidative stress, and systemic inflammation that characterize the development of adverse outcomes.

Targeted metabolomics reveals serum changes of amino acids in mild to moderate ischemic stroke and stroke mimics

Background

The pathophysiological processes linked to an acute ischemic stroke (IS) can be reflected in the circulating metabolome. Amino acids (AAs) have been demonstrated to be one of the most significant metabolites that can undergo significant alteration after a stroke.

Methods

We sought to identify the potential biomarkers for the early detection of IS using an extensive targeted technique for reliable quantification of 27 different AAs based on ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS). A cohort with 216 participants was enrolled, including 70 mild to moderate ischemic stroke patients (National Institutes of Health Stroke Scale < 15, MB group), 76 stroke mimics (MM group) and 70 healthy controls (NC group).

Results

It was found that upon comparing MB and MM to control patients, AAs shifts were detected via partial least squares discrimination analysis (PLS-DA) and pathway analysis. Interestingly, MB and MM exhibited similar AAs pattern. Moreover, ornithine, asparagine, valine, citrulline, and cysteine were identified for inclusion in a biomarker panel for early-stage stroke detection based upon an AUC of 0.968 (95% CI 0.924-0.998). Levels of ornithine were positively associated with infract volume, 3 months mRS score, and National Institutes of Health Stroke Scale (NIHSS) score in MB. In addition, a metabolites biomarker panel, including ornithine, taurine, phenylalanine, citrulline, cysteine, yielded an AUC of 0.99 (95% CI 0.966-1) which can be employed to effectively discriminate MM patients from control.

Conclusion

Overall, alternations in serum AAs are characteristic metabolic features of MB and MM. AAs could serve as promising biomarkers for the early diagnosis of MB patients since mild to moderate IS patients were enrolled in the study. The metabolism of AAs can be considered as a key indicator for both the prevention and treatment of IS.

Ischemia preconditioning induces an adaptive response that defines a circulating metabolomic signature in ischemic stroke patients

Transient ischemic attacks (TIAs) before an acute ischemic stroke (AIS) could induce ischemic tolerance (IT) phenomena. with an endogenous neuroprotective role (Ischemic preconditioning. IPC). A consecutive prospective cohort of patients with AIS were recruited from 8 different hospitals. Participants were classified by those with non-previous recent TIA vs. previous TIA (within seven days. TIA ≤7d). A total of 541 AIS patients were recruited. 40 (7.4%). of them had previous TIA ≤7d. In line with IPC. patients with TIA ≤7d showed: 1) a significantly less severe stroke at admission by NIHSS score. 2) a better outcome at 7-90 days follow-up and reduced infarct volumes. 3) a specific upregulated metabolomics/lipidomic profile composed of diverse lipid categories. Effectively. IPC activates an additional adaptive response on increasing circulation levels of structural and bioactive lipids to facilitate functional recovery after AIS which may support biochemical machinery for neuronal survival. Furthermore. previous TIA before AIS seems to facilitate the production of anti-inflammatory mediators that contribute to a better immune response. Thus. the IT phenomena contributes to a better adaptation of further ischemia. Our study provides first-time evidence of a metabolomics/lipidomic signature related to the development of stroke tolerance in AIS patients induced by recent TIA.

Sex as a biological variable in determining the metabolic changes influencing acute ischemic stroke outcomes-Where is the data: A systematic review

Women continue to face a greater lifetime morbidity and mortality from stroke and have been shown to respond differently to stroke treatments compared to men. Since 2016, updated National Institutes of Health (NIH) policies require research studies to consider sex as a biological variable. However, the way in which this policy affects study design, analysis, and reporting is variable, with few studies performing and reporting a subgroup analysis based on biological sex. In acute ischemic stroke, the underlying biological explanation for sex-based differences in patient outcomes and response to treatments remains understudied. We performed a systematic review of preclinical and clinical research studies that explored sex differences in the metabolic response to acute ischemic stroke as it relates to neurological outcomes. Through a literature search in Ovid Medline, Embase, and Web of Science, 1,004 potential references were identified for screening. After abstract and full-text review, we identified only two studies which assessed metabolic response to acute ischemic stroke (within 72 h of last known well) and neurological outcome [Barthel Index, modified Rankin Scale (mRS) or an equivalent in preclinical models] and reported results based on biological sex. One article was a preclinical rat model and the other a clinical cohort study. In both studies, metabolites involved in amino acid metabolism, energy metabolism, fat metabolism, or oxidative stress were identified. We review these results and link to additional articles that use metabolomics to identify metabolites differentially expressed by sex or regulated based on stroke outcomes, but not both. The results of this systematic review should not only help identify targets in need of further investigation to improve the understanding of sex differences in the pathophysiology of acute ischemic stroke, but also highlight the critical need to expand the incorporation of sex as a biological variable in acute stroke research beyond simply including both sexes and reporting the proportion of males/females in each population studied.

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.

Metabolomics of ischemic stroke: insights into risk prediction and mechanisms

Ischemic stroke (IS) is the most prevalent type of stroke. The early diagnosis and prognosis of IS are crucial for successful therapy and early intervention. Metabolomics, a tool in systems biology based on several innovative technologies, can be used to identify disease biomarkers and unveil underlying pathophysiological processes. Accordingly, in recent years, an increasing number of studies have identified metabolites from cerebral ischemia patients and animal models that could improve the diagnosis of IS and prediction of its outcome. In this paper, metabolomic research is comprehensively reviewed with a focus on describing the metabolic changes and related pathways associated with IS. Most clinical studies use biofluids (e.g., blood or plasma) because their collection is minimally invasive and they are ideal for analyzing changes in metabolites in patients of IS. We review the application of animal models in metabolomic analyses aimed at investigating potential mechanisms of IS and developing novel therapeutic approaches. In addition, this review presents the strengths and limitations of current metabolomic studies on IS, providing a reference for future related studies.

Detection of acute ischemic stroke and backtracking stroke onset time via machine learning analysis of metabolomics

The time window from stroke onset is critical for the treatment decision. However, in unknown onset stroke, it is often difficult to determine the exact onset time because of the lack of assessment methods, which can result in controversial and random treatment decisions. Previous studies have shown that serum biomarkers, in addition to imaging assessment, are useful for determining the stroke onset time. However, as yet there are no specific biomarkers or corresponding methodologies that are accurate and effective for determining the onset time of unknown onset stroke. Herein, we describe our novel advanced metabolites-based machine learning method (termed extreme gradient boost [XGBoost]) combined with recursive feature elimination, which accurately screened five metabolites from 1124 metabolites detected in serum. These metabolites were capable of both detecting acute ischemic stroke and backtracking the acute ischemic stroke onset time. To further investigate the pathological mechanisms of acute ischemic stroke, we also examined characteristic metabolites in different brain regions, and found two metabolites that could distinguish the core infarct area from the ischemic penumbra. Although this study is based on animal experiments, our machine learning framework and selected metabolites may provide a basis for clinical stroke evaluation and treatment.

A UPLC-Q-TOF-MS-Based Metabolomics Approach to Screen out Active Components in Prepared Rhubarb for Its Activity on Noxious Heat Blood Stasis Syndrome

Background: Prepared rhubarb was obtained by steaming raw rhubarb with wine. Different from raw rhubarb with a purgative effect, prepared rhubarb shows effects of promoting blood circulation and removing blood stasis. However, the mechanisms of its action through regulating endogenous metabolites remain unclear.

Purpose: The purpose of this study was to explore active chemical components in prepared rhubarb for its activity on noxious heat blood stasis syndrome (NHBS) by comprehensive metabolomics profiling.

Study design: Plant extracts usually show their activities in a synergistic way; therefore, integrated omics was developed as a rational way for a better understanding of their biological effects and potential active compounds.

Methods: The activities of prepared rhubarb were evaluated by biochemical and metabolomic analysis; meanwhile, serum chemical profiles were sought using UHPLC-Q-TOF-MS. Gray correlation analysis (GCA) was used for calculating the underlying correlations between them.

Results: The metabolomics profiles of rat plasma from model and control groups were significantly different, with 31 endogenous metabolites changed by NHBS. Then, after the administration of prepared rhubarb, 18 of them were regulated. Multiple metabolic pathways were disturbed after NHBS modeling and restored by prepared rhubarb, among which had a greater impact on sphingolipid metabolism. A total of 28 compounds from prepared rhubarb absorbed into the plasma were identified, including nine prototypes and 19 metabolites. Statistical results suggested that rhein and its metabolites accounted for half of the top 10 active compounds in prepared rhubarb for its biomedical activities.

Conclusion: This study presented evidence for the therapeutic effects and active chemicals of prepared rhubarb on NHBS in the way of metabolomics.

The Effects of Enriched Rehabilitation on Cognitive Function and Serum Glutamate Levels Post-stroke

Aim

This study aimed to explore the effect of enriched rehabilitation (ER) on cognitive function and serum glutamate levels in patients with stroke.

Methods

Forty patients diagnosed with post-stroke cognitive impairment (PSCI), according to the inclusion criteria, and undergoing inpatient rehabilitation were enrolled in the study. Patients were randomly assigned to receive 8 weeks of ER treatment (ER group; n = 20) or conventional medical treatment (CM group; n = 20). In addition, 20 age-matched healthy subjects who were outpatients in our hospital during the same period formed the healthy control (HC) group. In- and between-group differences in cognitive function were assessed during pre-intervention and post-intervention based on the Montreal Cognitive Assessment (MoCA), the Symbol Digit Modalities Test (SDMT), and the Trail Making Test (TMT). The serum levels of glutamate, tumor necrosis factor (TNF), and malondialdehyde (MDA) levels were also detected pre-intervention and post-intervention.

Results

Pre-intervention cognitive function and the levels of all the serum parameters assessed significant difference between the HC group and the PSCI group (both ER and CM groups) (p < 0.05), but not between the two groups of patients with PSCI (p > 0.05). Significant improvements were observed in cognitive function in both the ER and the CM groups post-intervention compared with pre-intervention, as evidenced by the measured improvement in MoCA, SDMT, and TMT scores. Similar improvements were seen for serum glutamate, the degree of oxidative damage, and the level of inflammation in both the treatment groups (p < 0.05). More enhancements in cognitive function, including MoCA, SDMT, TMT scores, and the serum levels of glutamate, the degree of oxidative damage, and the level of inflammation were shown in the ER group compared with the CM group post-intervention (p < 0.05).

Conclusions

ER can improve cognitive function in patients with PSCI. The associated mechanism may be related to the negative regulatory effect of ER on serum glutamate, TNF, and MDA levels, which is likely to enhance synaptic plasticity and alleviate oxidative stress- and inflammation-related damage, at least to some extent.

Serum Metabonomics Reveals Risk Factors in Different Periods of Cerebral Infarction in Humans

Studies of key metabolite variations and their biological mechanisms in cerebral infarction (CI) have increased our understanding of the pathophysiology of the disease. However, how metabolite variations in different periods of CI influence these biological processes and whether key metabolites from different periods may better predict disease progression are still unknown. We performed a systematic investigation using the metabonomics method. Various metabolites in different pathways were investigated by serum metabolic profiling of 143 patients diagnosed with CI and 59 healthy controls. Phe-Phe, carnitine C18:1, palmitic acid, cis-8,11,14-eicosatrienoic acid, palmitoleic acid, 1-linoleoyl-rac-glycerol, MAG 18:1, MAG 20:3, phosphoric acid, 5α-dihydrotestosterone, Ca, K, and GGT were the major components in the early period of CI. GCDCA, glycocholate, PC 36:5, LPC 18:2, and PA showed obvious changes in the intermediate time. In contrast, trans-vaccenic acid, linolenic acid, linoleic acid, all-cis-4,7,10,13,16-docosapentaenoic acid, arachidonic acid, DHA, FFA 18:1, FFA 18:2, FFA 18:3, FFA 20:4, FFA 22:6, PC 34:1, PC 36:3, PC 38:4, ALP, and Crea displayed changes in the later time. More importantly, we found that phenylalanine metabolism, medium-chain acylcarnitines, long-chain acylcarnitines, choline, DHEA, LPC 18:0, LPC 18:1, FFA 18:0, FFA 22:4, TG, ALB, IDBIL, and DBIL played vital roles in the development of different periods of CI. Increased phenylacetyl-L-glutamine was detected and may be a biomarker for CI. It was of great significance that we identified key metabolic pathways and risk metabolites in different periods of CI different from those previously reported. Specific data are detailed in the Conclusion section. In addition, we also explored metabolite differences of CI patients complicated with high blood glucose compared with healthy controls. Further work in this area may inform personalized treatment approaches in clinical practice for CI by experimentally elucidating the pathophysiological mechanisms.

Micromolar Metabolite Measurement in an Electronically Multiplexed Format

The detection of metabolites such as choline in blood are important in clinical care for patients with cancer and cardiovascular disease. Choline is only present in human blood at low concentrations hence accurate measurement in an affordable point-of-care format is extremely challenging. Integration of microfluidics on to complementary metal-oxide semiconductor (CMOS) technology has the potential to enable advanced sensing technologies with extremely low limit of detection that are well suited to multiple clinical metabolite measurements. Although CMOS and microfluidics are individually mature technologies, their integration has presented challenges that we overcome in a novel, cost-effective, single-step process. To demonstrate the process, we present the microfluidic integration of a metabolomics-on-CMOS point-of-care platform with four capillary microfluidic channels on top of a CMOS optical sensor array. The fabricated device was characterised to verify the required structural profile, mechanical strength, optical spectra, and fluid flow. As a proof of concept, we used the device for the in-vitro quantification of choline in human blood plasma with a limit of detection of 3.2 M and a resolution of 1.6 M.

Mechanism of Sanhua Decoction in the Treatment of Ischemic Stroke Based on Network Pharmacology Methods and Experimental Verification

Objective

The mechanism of action of Sanhua Decoction (SHD) in the treatment of ischemic stroke (IS) was analyzed based on the network pharmacology technology, and the pharmacodynamics and key targets were verified using the rat middle cerebral artery occlusion (MCAO) model.

Methods

The GEO database was used to collect IS-related gene set S_D, and DrugBank and TTD databases were used to obtain the therapeutic drug target set S_T. IS disease gene set S_I was collected from DisGeNET, GeneCards, and OMIM databases. These three different gene sets obtained from various sources were merged, duplicates were removed, and the resulting IS disease gene set S_IS was imported into the STRING database to establish the protein-protein interaction (PPI) network. Two methods were used to screen the key targets of IS disease based on the PPI network analysis. The TCMSP database and PubChem were applied to retrieve the main chemical components of SHD, and the ACD/Labs software and the SwissADME online system were utilized for ADMET screening. HitPick, SEA, and SwissTarget Prediction online systems were used to predict the set of potential targets for SHD to treat IS. The predicted set of potential targets and the IS disease gene set were intersected. Subsequently, the set of potential targets for SHD treatment of IS was identified, the target information was confirmed through the UniProt database, and finally, the component-target data set for SHD treatment of IS was obtained. clusterProfiler was used for GO function annotation and KEGG pathway enrichment analysis on the target set of SHD active ingredients. A rat MCAO model was established to evaluate the pharmacodynamics of SHD in the treatment of IS, and Western blot analysis assessed the level of proteins in the related pathways.

Results

This study obtained 1,009 IS disease gene sets. PPI network analysis identified 12 key targets: AGT, SAA1, KNG1, APP, GNB3, C3, CXCR4, CXCL12, CXCL8, CXCL1, F2, and EDN1. Database analyses retrieved 40 active ingredients and 47 target genes in SHD. The network proximity algorithm was used to optimize the six key components in SHD. KEGG enrichment showed that the signaling pathways related to IS were endocrine resistance, estrogen, TNF signal pathway, and AGEs/RAGE. Compound-disease-target regulatory network analysis showed that AKT1, IL-6, TNF-α, TP53, VEGFA, and APP were related to the treatment of IS with SHD. Animal experiments demonstrated that SHD significantly reduces the neurological function of rat defect symptoms (P < 0.05), the area of cerebral avascular necrosis, and neuronal necrosis while increasing the levels of IL-6 and APP proteins (P < 0.05) and reducing the levels of AKT1 and VEGFA proteins (P < 0.05).

Conclusion

The effective components of SHD may regulate multiple signaling pathways through IL-6, APP, AKT1, and VEGFA to reduce brain damage and inflammatory damage and exert a neuroprotective role in the treatment of IS diseases. Thus, this study provides a feasible method to study the pharmacological mechanism of traditional Chinese medicine compound prescriptions and a theoretical basis for the development of SHD into a new drug for IS treatment.

Screening of Phospholipids in Plasma of Large-Artery Atherosclerotic and Cardioembolic Stroke Patients With Hydrophilic Interaction Chromatography-Mass Spectrometry

Ischemic stroke (IS) is a deadly and debilitating disease with a high incidence and recurrence rate in elderly people worldwide. Large-artery atherosclerotic (LAA) and cardioembolic (CE) stroke are two leading subtypes and require different management. As a complementary biochemistry method for current diagnostic techniques, a sensitive and accurate phospholipid (PL) targeted lipidomic method was developed in this study. Plasma PLs were selectively extracted with titanium dioxide/fibrous silica nanosphere material, then characterized and quantified with hydrophilic interaction chromatography-mass spectrometry. A total of 31 molecular species of PLs were determined and ten biomarkers including seven molecular species of sphingomyelins (SM d18:1/18:1, d18:1/18:0, d18:1/24:1, d18:1/16:1, d18:1/22:1, d18:1/24:2, and d18:1/16:0) and three molecular species of phosphatidylcholines (16:0/18:1, 16:0/18:2 and 16:0/22:6) showed significant differences in LAA, CE, and healthy control (HC) groups. The independent diagnostic capabilities of these PL biomarkers were successfully evaluated and validated with receiver operating characteristic curves. Additionally, the oleic acid-enriched SMs, which can result in atherogenic lipoprotein aggregation, were proved to be positively related to IS and may perform as the potential risk factors in the future. Meanwhile, valuable suggestions for dietary interventions as an essential source of endogenous PLs could be obtained from this study.

Studies on the mechanism of Panax Ginseng in the treatment of deficiency of vital energy dementia rats based on urine metabolomics

Panax Ginseng (PG) has been used to strengthen memory and physique for thousands of years, because its main components ginsenosides (GS) and ginseng polysaccharides (GP) play a major role, but its mechanism is not clear. In this study, a rat model of dementia with vital energy deficiency (DED) was established through intraperitoneal injection with D-galactose and AlCl₃ and combined with exhaustive swimming. Pharmacological studies and the urine metabolomics based on ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF-MS) were employed for evaluation the efficacy of PG and exploring this treatment mechanism. Through urine metabolic profiling, it can be seen that DED rats after PG administration are close to normal group (NG) rats, and PG can regulate the in vivo status of DED rats which tend to NG. The results of behavioral, biochemical indicators and immunohistochemistry further verified the above results, and the mechanism of action of each component is refined. Ultimately, we believe that the mechanism of PG in the treatment of DED is that ginsenosides (GS) intervenes in phenylalanine tryptophan and tyrosine metabolism, stimulates dopamine production, inhibits Aβ deposition and neuroinflammation; and that ginseng polysaccharides (GP) provides energy to strengthen the TCA cycle and improve immune capacity.

Nuciferine attenuates acute ischemic stroke in a rat model: a metabolomic approach for the mechanistic study

Nuciferine is a promise therapeutic candidate for ischemic stroke. 1H NMR metabolomics was conducted in this study to further elucidate its pharmacological mechanism, which is helpful to be used as a potential treatment for stroke clinically.

Breath and plasma metabolomics to assess inflammation in acute stroke

Inflammation is strongly implicated in both injury and repair processes occurring after stroke. In this exploratory study we assessed the feasibility of repeated sampling of exhaled volatile organic compounds and performed an untargeted metabolomic analysis of plasma collected at multiple time periods after stroke. Metabolic profiles were compared with the time course of the inflammatory markers C-reactive protein (CRP) and interleukin-6 (IL-6). Serial breath sampling was well-tolerated by all patients and the measurement appears feasible in this group. We found that exhaled decanal tracks CRP and IL-6 levels post-stroke and correlates with several metabolic pathways associated with a post-stroke inflammatory response. This suggests that measurement of breath and blood metabolites could facilitate development of novel therapeutic and diagnostic strategies. Results are discussed in relation to the utility of breath analysis in stroke care, such as in monitoring recovery and complications including stroke associated infection.

Metabolic network-based identification of plasma markers for non-small cell lung cancer

Metabolic markers, offering sensitive information on biological dysfunction, play important roles in diagnosing and treating cancers. However, the discovery of effective markers is limited by the lack of well-established metabolite selection approaches. Here, we propose a network-based strategy to uncover the metabolic markers with potential clinical availability for non-small cell lung cancer (NSCLC). First, an integrated mass spectrometry-based untargeted metabolomics was used to profile the plasma samples from 43 NSCLC patients and 43 healthy controls. We found that a series of 39 metabolites were altered significantly. Relying on the human metabolic network assembled from Kyoto Encyclopedia of Genes and Genomes (KEGG) database, we mapped these differential metabolites to the network and constructed an NSCLC-related disease module containing 23 putative metabolic markers. By measuring the PageRank centrality of molecules in this module, we computationally evaluated the network-based importance of the 23 metabolites and demonstrated that the metabolism pathways of aromatic amino acids and long-chain fatty acids provided potential molecular targets of NSCLC (i.e., IL4l1 and ACOT2). Combining network-based ranking and support-vector machine modeling, we further found a panel of eight metabolites (i.e., pyruvate, tryptophan, and palmitic acid) that showed a high capability to differentiate patients from controls (accuracy > 97.7%). In summary, we present a meaningful network method for metabolic marker discovery and have identified eight strong candidate metabolites for NSCLC diagnosis.

Analysis of Metabolite and Lipid Association Networks Reveals Molecular Mechanisms Associated with 3-Month Mortality and Poor Functional Outcomes in Patients with Acute Ischemic Stroke after Thrombolytic Treatment with Recombinant Tissue Plasminogen Activator

Here, we present an integrated multivariate, univariate, network reconstruction and differential analysis of metabolite–metabolite and metabolite–lipid association networks built from an array of 18 serum metabolites and 110 lipids identified and quantified through nuclear magnetic resonance spectroscopy in a cohort of 248 patients, of which 22 died and 82 developed a poor functional outcome within 3 months from acute ischemic stroke (AIS) treated with intravenous recombinant tissue plasminogen activator. We explored differences in metabolite and lipid connectivity of patients who did not develop a poor outcome and who survived the ischemic stroke from the related opposite conditions. We report statistically significant differences in the connectivity patterns of both low- and high-molecular-weight metabolites, implying underlying variations in the metabolic pathway involving leucine, glycine, glutamine, tyrosine, phenylalanine, citric, lactic, and acetic acids, ketone bodies, and different lipids, thus characterizing patients’ outcomes. Our results evidence the promising and powerful role of the metabolite–metabolite and metabolite–lipid association networks in investigating molecular mechanisms underlying AIS patient’s outcome.

Metabolomic Profiles of Men and Women Ischemic Stroke Patients

Background: Stroke is known to affect both men and women; however, incidence and outcomes differ between them. Therefore, the discovery of novel, sex-specific, blood-based biomarkers for acute ischemic stroke (AIS) patients has the potential to enhance the understanding of the etiology of this deadly disease in the content of sex. The objective of this study was to identify serum metabolites associated with male and female AIS patients. Methods: Metabolites were measured with the use of untargeted, reverse-phase ultra-performance liquid chromatography-tandem mass spectrometry quantification from blood specimens collected from AIS patients. Samples were collected from 36 patients comprising each of 18 men and women with matched controls. Metabolic pathway analysis and principal component analysis (PCA) was used to differentiate metabolite profiles for male and female AIS patients from the control, while logistic regression was used to determine differences in metabolites between male and female AIS patients. Results: In female AIS patients, 14 distinct altered metabolic pathways and 49 corresponding metabolites were identified, while 39 metabolites and 5 metabolic pathways were identified in male patients. Metabolites that are predictive of ischemic stroke in female patients were 1-(1-enyl-palmitoyl)-2-arachidonoyl-GPC (P-16:0/20:4) (AUC = 0.914, 0.765–1.000), 1-(1-enyl-palmitoyl)-2-palmitoyl-GPC (P-16:0/16:0) (AUC = 0.840, 0.656–1.000), and 5,6-dihydrouracil (P-16:0/20:2) (AUC = 0.815, 0.601–1.000). Significant metabolites that were predictive of stroke in male patients were 5alpha-androstan-3alpha,17beta-diol disulfate (AUC = 0.951, 0.857–1.000), alpha-hydroxyisocaproate (AUC = 0.938, 0.832–1.000), threonate (AUC = 0.877, 0.716–1.000), and bilirubin (AUC = 0.817, 0.746–1.000). Conclusions: In the current study, the untargeted serum metabolomics platform identified multiple pathways and metabolites associated with male and female AIS patients. Further research is necessary to characterize how these metabolites are associated with the pathophysiology in male and female AIS patients.

Pinocembrin attenuates hemorrhagic transformation after delayed t-PA treatment in thromboembolic stroke rats by regulating endogenous metabolites

Hemorrhagic transformation (HT) is a common serious complication of stroke after thrombolysis treatment, which limits the clinical use of tissue plasminogen activator (t-PA). Since early diagnosis and treatment for HT is important to improve the prognosis of stroke patients, it is urgent to discover the potential biomarkers and therapeutic drugs. Recent evidence shows that pinocembrin, a natural flavonoid compound, exerts anti-cerebral ischemia effect and expands the time window of t-PA. In this study, we investigated the effect of pinocembrin on t-PA-induced HT and the potential biomarkers for HT after t-PA thrombolysis, thereby improving the prognosis of stroke. Electrocoagulation-induced thrombotic focal ischemic rats received intravenous infusion of t-PA (10 mg/kg) 6 h after ischemia. Administration of pinocembrin (10 mg/kg, iv) prior t-PA infusion significantly decreased the infarct volume, ameliorated t-PA-induced HT, and protected blood-brain barrier. Metabolomics analysis revealed that 5 differential metabolites in the cerebral cortex and 16 differential metabolites in serum involved in amino acid metabolism and energy metabolism were significantly changed after t-PA thrombolysis, whereas pinocembrin administration exerted significant intervention effects on these metabolites. Linear regression analysis showed that lactic acid was highly correlated to the occurrence of HT. Further experiments confirmed that t-PA treatment significantly increased the content of lactic acid and the activity of lactate dehydrogenase in the cerebral cortex and serum, and the expression of monocarboxylate transporter 1 (MCT 1) in the cerebral cortex; pinocembrin reversed these changes, which was consistent with the result of metabolomics. These results demonstrate that pinocembrin attenuates HT after t-PA thrombolysis, which may be associated with the regulation of endogenous metabolites. Lactic acid may be a potential biomarker for HT prediction and treatment.

Brain-dead and coma patients exhibit different serum metabolic profiles: preliminary investigation of a novel diagnostic approach in neurocritical care

There is a clear difference between severe brain damage and brain death. However, in clinical practice, the differentiation of these states can be challenging. Currently, there are no laboratory tools that facilitate brain death diagnosis. The aim of our study was to evaluate the utility of serum metabolomic analysis in differentiating coma patients (CP) from individuals with brain death (BD). Serum samples were collected from 23 adult individuals with established diagnosis of brain death and 24 patients in coma with Glasgow Coma Scale 3 or 4, with no other clinical symptoms of brain death for at least 7 days after sample collection. Serum metabolomic profiles were investigated using proton nuclear magnetic resonance (NMR) spectroscopy. The results obtained were examined by univariate and multivariate data analysis (PCA, PLS-DA, and OPLS-DA). Metabolic profiling allowed us to quantify 43 resonance signals, of which 34 were identified. Multivariate statistical modeling revealed a highly significant separation between coma patients and brain-dead individuals, as well as strong predictive potential. The findings not only highlight the potential of the metabolomic approach for distinguishing patients in coma from those in the state of brain death but also may provide an understanding of the pathogenic mechanisms underlying these conditions.

Medioresinol as a novel PGC-1α activator prevents pyroptosis of endothelial cells in ischemic stroke through PPARα-GOT1 axis

AIM

Brain microvascular endothelial cells (BMVECs), as the important structure of blood-brain barrier (BBB), play a vital role in ischemic stroke. Pyroptosis of different cells in the brain may aggravate cerebral ischemic injury, and PGC-1α plays a major role in pyroptosis. However, it is not known whether BMVECs undergo pyroptosis after ischemic stroke and whether PGC-1α activator Medioresinol (MDN) we discovered may be useful against pyroptosis of endothelial cells and ischemic brain injury.

METHODS

For in vitro experiments, the bEnd.3 cells and BMVECs under oxygen and glucose-deprivation (OGD) were treated with or without MDN, and the LDH release, tight junction protein degradation, GSDMD-NT membrane location and pyroptosis-associated proteins were evaluated. For in vivo experiments, mice underwent transient middle cerebral artery occlusion (tMCAO) for ischemia model, and the neuroprotective effects of MDN were measured by infarct volume, the permeability of BBB and pyroptosis of BMVECs. For mechanistic study, effects of MDN on the accumulation of phenylalanine, mitochondrial reactive oxygen species (mtROS) were tested by untargeted metabolomics and MitoSOX Red probe, respectively.

RESULTS

BMVECs underwent pyroptosis after ischemia. MDN dose-dependently activated PGC-1α, significantly reduced pyroptosis, mtROS and the expressions of pyroptosis-associated proteins (NLRP3, ASC, cleaved caspase-1, IL-1β, GSDMD-NT), and increased ZO-1 and Occludin protein expressions in BMVECs. In tMCAO mice, MDN remarkably reduced brain infarct volume and the permeability of BBB, inhibited pyroptosis of BMVECs, and promoted long-term neurobehavioral functional recovery. Mechanistically, MDN promoted the interaction of PGC-1α with PPARα to increase PPARα nuclear translocation and transcription activity, further increased the expression of GOT1 and PAH, resulting in enhanced phenylalanine metabolism to reduce the ischemia-caused phenylalanine accumulation and mtROS and further ameliorate pyroptosis of BMVECs.

CONCLUSION

In this study, we for the first time discovered that pyroptosis of BMVECs was involved in the pathogenesis of ischemic stroke and MDN as a novel PGC-1α activator could ameliorate the pyroptosis of endothelial cells and ischemic brain injury, which might attribute to reduction of mtROS through PPARα/GOT1 axis in BMVECs. Taken together, targeting endothelial pyroptosis by MDN may provide alternative therapeutics for brain ischemic stroke.

Applications of Metabolomics in Forensic Toxicology and Forensic Medicine

Forensic toxicology and forensic medicine are unique among all other medical fields because of their essential legal impact, especially in civil and criminal cases. New high-throughput technologies, borrowed from chemistry and physics, have proven that metabolomics, the youngest of the “omics sciences”, could be one of the most powerful tools for monitoring changes in forensic disciplines. Metabolomics is a particular method that allows for the measurement of metabolic changes in a multicellular system using two different approaches: targeted and untargeted. Targeted studies are focused on a known number of defined metabolites. Untargeted metabolomics aims to capture all metabolites present in a sample. Different statistical approaches (e.g., uni- or multivariate statistics, machine learning) can be applied to extract useful and important information in both cases. This review aims to describe the role of metabolomics in forensic toxicology and in forensic medicine.

Multi-omic analysis of stroke recurrence in African Americans from the Vitamin Intervention for Stroke Prevention (VISP) clinical trial

African Americans endure a nearly two-fold greater risk of suffering a stroke and are 2–3 times more likely to die from stroke compared to those of European ancestry. African Americans also have a greater risk of recurrent stroke and vascular events, which are deadlier and more disabling than incident stroke. Stroke is a multifactorial disease with both heritable and environmental risk factors. We conducted an integrative, multi-omic study on 922 plasma metabolites, 473,864 DNA methylation loci, and 556 variants from 50 African American participants of the Vitamin Intervention for Stroke Prevention clinical trial to help elucidate biomarkers contributing to recurrent stroke rates in this high risk population. Sixteen metabolites, including cotinine, N-delta-acetylornithine, and sphingomyelin (d17:1/24:1) were identified in t-tests of recurrent stroke outcome or baseline smoking status. Serum tricosanoyl sphingomyelin (d18:1/23:0) levels were significantly associated with recurrent stroke after adjusting for covariates in Cox Proportional Hazards models. Weighted Gene Co-expression Network Analysis identified moderate correlations between sphingolipid markers and clinical traits including days to recurrent stroke. Integrative analyses between genetic variants in sphingolipid pathway genes identified 29 nominal associations with metabolite levels in a one-way analysis of variance, while epigenomic analyses identified xenobiotics, predominately smoking-associated metabolites and pharmaceutical drugs, associated with methylation profiles. Taken together, our results suggest that metabolites, specifically those associated with sphingolipid metabolism, are potential plasma biomarkers for stroke recurrence in African Americans. Furthermore, genetic variation and DNA methylation may play a role in the regulation of these metabolites.

Serum metabolomic patterns in young patients with ischemic stroke: a case study

BACKGROUND

Ischemic stroke is one of the leading causes of death and adult disability. The incidence of ischemic stroke continues to rise in young adults. This study aimed to provide a comprehensive evaluation of metabolic changes and explore possible mechanisms in young ischemic stroke patients without common risk factors.

METHODS

This study investigated serum metabolomics in 50 young patients with newly suffered ischemic stroke and 50 age-, sex-, and body mass index-matched healthy controls. Liquid chromatography coupled with a Waters Xevo TQ-S mass spectrometer with an electrospray ionization (ESI) source was used to analyze amino acid or bile acid, and free fatty acid or lipid was analyzed by liquid chromatography coupled with a Qtrap5500 mass spectrometer with an ESI source. The metabolomic data were analyzed by performing a multivariate statistical analysis.

RESULTS

A total of 197 metabolites, including amino acids, bile acids, free fatty acids, and lipids, were identified in all participants. Multivariate models showed significant differences in serum metabolomic patterns between young patients with ischemic stroke and healthy controls. The stroke patients had increased L-methionine, homocysteine, glutamine, uric acid, GCDCA, and PE (18:0/20:4, 16:0/22:5), and decreased levels of L-citrulline, taurine, PC (16:2/22:6, 16:2/20:5, 15:0/18:2), and SM (d18:1/23:0, d20:0/19:1, d18:1/22:0, d16:0/26:1, d16:0/18:0, d16:0/22:1, d18:1/19:1, d16:0/17:1, d16:1/24:1, d18:1/19:0). Based on the identified metabolites, the metabolic pathways of arginine biosynthesis, glycerophospholipid metabolism, and taurine and hypotaurine metabolism were significantly enriched in the young patients with ischemic stroke.

CONCLUSIONS

Serum metabolomic patterns were significantly different between young patients with ischemic stroke and healthy controls. Our study is beneficial in providing a further view into the pathophysiology of young patients with ischemic stroke.

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.

Effects of Acanthopanax senticosus (Rupr. & Maxim.) Harms on cerebral ischemia-reperfusion injury revealed by metabolomics and transcriptomics

ETHNOPHARMACOLOGICAL RELEVANCE

Cerebral ischemia-reperfusion (CIR) injury is one of the main diseases leading to death and disability. Acanthopanax senticosus (Rupr. & Maxim.) Harms (AS), also known as Panax ginseng, has neuroprotective effects on anti-CIR injury. However, the underlying molecular mechanism of its therapeutic effects is not clear.

AIM OF THE STUDY

To systematically study and explore the mechanism of Acanthopanax senticosus (Rupr. & Maxim.) Harms extract (ASE) in the treatment of CIR injury based on metabolomics and transcriptomics.

MATERIALS AND METHODS

The pharmacological basis of ASE in the treatment of CIR was evaluated, and samples were used in plasma metabolomics and brain tissue transcriptomics to reveal potential biomarkers. Finally, according to online database, we analyzed biomarkers identified by the two technologies, explained reasons for the therapeutic effect of ASE, and identify therapeutic targets.

RESULTS

A total of 53 differential metabolites (DMs) were identified in plasma and 3138 differentially expressed genes (DEGs) were identified in brain tissue from three groups of rats, including sham, ischemia-reperfusion (I/R), and ASE groups. Enrichment analysis showed that Nme6, Tk1, and Pold1 that are involved in the production of deoxycytidine and thymine were significantly up-regulated and Dck was significantly down-regulated by the intervention with ASE. These findings indicated that ASE participates in the pyrimidine metabolism by significantly regulating the balance between dCTP and dTTP. In addition, ASE repaired and promoted the lipid metabolism in rats, which might be due to the significant expression of Dgkz, Chat, and Gpcpd1.

CONCLUSIONS

The findings of this study suggest that ASE regulates the significant changes in gene expression in metabolites pyrimidine, and lipid metabolism in CIR rats and plays an active role in the treatment of CIR injury through multiple targets and pathways.

Advances in nanomedicines for diagnosis of central nervous system disorders

In spite of a great improvement in medical health services and an increase in lifespan, we have witnessed a skyrocket increase in the incidence of central nervous system (CNS) disorders including brain tumors, neurodegenerative diseases (Alzheimer's disease, Parkinson's disease, amyotrophic lateral sclerosis, Huntington's disease), ischemic stroke, and epilepsy, which have seriously undermined the quality of life and substantially increased economic and societal burdens. Development of diagnostic methods for CNS disorders is still in the early stage, and the clinical outcomes suggest these methods are not ready for the challenges associated with diagnosis of CNS disorders, such as early detection, specific binding, sharp contrast, and continuous monitoring of therapeutic interventions. Another challenge is to overcome various barrier structures during delivery of diagnostic agents, especially the blood-brain barrier (BBB). Fortunately, utilization of nanomaterials has been pursued as a potential and promising strategy to address these challenges. This review will discuss anatomical and functional structures of BBB and transport mechanisms of nanomaterials across the BBB, and special emphases will be placed on the state-of-the-art advances in the development of nanomedicines from a variety of nanomaterials for diagnosis of CNS disorders. Meanwhile, current challenges and future perspectives in this field are also highlighted.