Application of Metabolomics to the Discovery of Biomarkers for Ischemic Stroke in the Murine Model: a Comparison with the Clinical Results

Sex Differences in the Blood Metabolome During Acute Response to Ischemic Stroke

Introduction: Females suffer greater lifetime risk of stroke and greater morbidity and mortality from stroke compared with males. This study's objective was to identify differences in metabolomic profiling of females and males with stroke and which differences were associated with neurological outcome. Methods: Females and males with acute ischemic stroke enrolled in the Emergency Medicine Specimen Bank at a comprehensive stroke center provided whole blood samples upon arrival for mass spectrometry-based metabolomics. We used descriptive statistics to characterize the cohort. A linear regression model was fit for individual metabolites to determine differences in relative abundance between males and females while controlling for covariates (age, race/ethnicity, postmenopausal status, cardiovascular risk factors, depression, time between sample collection and last known well, and initial National Institutes of Health Stroke Scale [NIHSS] score). For each differentially expressed metabolite, a linear regression model was fit to determine the association between the metabolite and NIHSS at 24 hours after admission while controlling for the covariates and acute treatments. Results: After adjusting for covariates, eight metabolites differed in females and males with a stroke. These included amino acids or their metabolites (proline and tryptophan), nucleotides (guanosine diphosphate [GDP], and inosine-3',5'-cyclic monophosphate), citrate, dehydroascorbate, choline, and acylcarnitine-(5-OH). GDP and dehydroascorbate were significantly associated with 24-hour NIHSS (p = 0.0991). Conclusions: Few metabolites were differentially abundant in blood after a stroke when comparing females with males and controlling for confounders, but the interactions between biological sex and GDP, as well as biological sex and dehydroascorbate, were associated with 24-hour neurological function. This has important implications for future studies that evaluate the therapeutic potential of these metabolites in ischemic stroke.

Comparative physiological, biochemical and transcriptomic analyses to reveal potential regulatory mechanisms in response to starvation stress in Cipangopaludina chinensis

Cipangopaludina chinensis, as a financially significant species in China, represents a gastropod in nature which frequently encounters starvation stress owing to its limited prey options. However, the underlying response mechanisms to combat starvation have not been investigated in depth. We collected C. chinensis under several times of starvation stress (0, 7, 30, and 60 days) for nutrient, biochemical characteristics and transcriptome analyses. The results showed that prolonged starvation stress (> 30 days) caused obvious fluctuations in the nutrient composition of snails, with dramatic reductions in body weight, survival and digestive enzyme activity (amylase, protease, and lipase), and markedly enhanced the antioxidant enzyme activities of the snails. Comparative transcriptome analyses revealed 3538 differentially expressed genes (DEGs), which were significantly associated with specific starvation stress-responsive pathways, including oxidative phosphorylation and alanine, aspartate, and glutamate metabolism. Then, we identified 40 candidate genes (e.g., HACD2, Cp1, CYP1A2, and GPX1) response to starvation stress through STEM and WGCNA analyses. RT-qPCR verified the accuracy and reliability of the high-throughput sequencing results. This study provides insights into snail overwintering survival and the potential regulatory mechanisms of snail adaptation to starvation stress.

Exploring the "gene-metabolite" network of ischemic stroke with blood stasis and toxin syndrome by integrated transcriptomics and metabolomics strategy

A research model combining a disease and syndrome can provide new ideas for the treatment of ischemic stroke. In the field of traditional Chinese medicine, blood stasis and toxin (BST) syndrome is considered an important syndrome seen in patients with ischemic stroke (IS). However, the biological basis of IS-BST syndrome is currently not well understood. Therefore, this study aimed to explore the biological mechanism of IS-BST syndrome. This study is divided into two parts: (1) establishment of an animal model of ischemic stroke disease and an animal model of BST syndrome in ischemic stroke; (2) use of omics methods to identify differentially expressed genes and metabolites in the models. We used middle cerebral artery occlusion (MCAO) surgery to establish the disease model, and utilized carrageenan combined with active dry yeast and MCAO surgery to construct the IS-BST syndrome model. Next, we used transcriptomics and metabolomics methods to explore the differential genes and metabolites in the disease model and IS-BST syndrome model. It is found that the IS-BST syndrome model exhibited more prominent characteristics of IS disease and syndrome features. Both the disease model and the IS-BST syndrome model share some common biological processes, such as thrombus formation, inflammatory response, purine metabolism, sphingolipid metabolism, and so on. Results of the "gene-metabolite" network revealed that the IS-BST syndrome model exhibited more pronounced features of complement-coagulation cascade reactions and amino acid metabolism disorders. Additionally, the "F2 (thrombin)-NMDAR/glutamate" pathway was coupled with the formation process of the blood stasis and toxin syndrome. This study reveals the intricate mechanism of IS-BST syndrome, offering a successful model for investigating the combination of disease and syndrome.

Development of Transmission Ambient Pressure Laser Desorption Ionization/Postphotoionization Mass Spectrometry Imaging

Laser-based high-resolution mass spectrometry imaging at ambient conditions has promising applications in life science. However, the ion yield during laser desorption/ablation is poor. Here, transmission atmospheric pressure laser desorption ionization combined with a compact postphotoionization (t-AP-LDI/PI) assembly with a krypton discharge lamp was developed for the untargeted imaging of various biomolecules. The spatial distributions of numerous lipid classes, fatty acids, neurotransmitters, and amino acids in the subregions of mouse cerebellum tissue were obtained. Compared with single laser ablation, the sensitivities for most analytes were increased by 1 to 3 orders of magnitude by dopant-assisted postphotoionization. After careful optimization, a spatial resolution of 4 μm could be achieved for the metabolites in mouse hippocampus tissue. Finally, the melanoma tissue slices were analyzed using t-AP-LDI/PI MSI, which revealed the metabolic heterogeneity of the melanoma microenvironment and exhibited the phenomenon of abnormal proliferation and invasion trends in tumor cells.

Plasmalogens and Octanoylcarnitine Serve as Early Warnings for Central Retinal Artery Occlusion

Central retinal artery occlusion (CRAO) is a kind of ophthalmic emergency which may cause loss of functional visual acuity. However, the limited treatment options emphasize the significance of early disease prevention. Metabolomics has the potential to be a powerful tool for early identification of individuals at risk of CRAO. The aim of the study was to identify potential biomarkers for CRAO through a comprehensive analysis. We employed metabolomics analysis to compare venous blood samples from CRAO patients with cataract patients for the venous difference, as well as arterial and venous blood from CRAO patients for the arteriovenous difference. The analysis of metabolites showed that PC(P-18:0/22:6(4Z,7Z,10Z,13Z,16Z,19Z)), PC(P-18:0/20:4(5Z,8Z,11Z,14Z)) and octanoylcarnitine were strongly correlated with CRAO. We also used univariate logistic regression, random forest (RF), and support vector machine (SVM) to screen clinical parameters of patients and found that HDL-C and ApoA1 showed significant predictive efficacy in CRAO patients. We compared the predictive performance of the clinical parameter model with combined model. The prediction efficiency of the combined model was significantly better with area under the receiver operating characteristic curve (AUROC) of 0.815. Decision curve analysis (DCA) also exhibited a notably higher net benefit rate. These results underscored the potency of these three substances as robust predictors of CRAO occurrence.

Bone marrow mesenchymal stem cells therapy regulates sphingolipid and glycerophospholipid metabolism to promote neurological recovery in stroke rats: A metabolomics analysis

Bone marrow mesenchymal stem cells (BMSCs) have therapeutic potential in the subacute/chronic phase of acute ischemic stroke (AIS), but the underlying mechanisms are not yet fully elucidated. There is a knowledge gap in understanding the metabolic mechanisms of BMSCs in stroke therapy. In this study, we administered BMSCs intravenously 24 h after reperfusion in rats with transient cerebral artery occlusion (MCAO). The treatment with BMSCs for 21 days significantly reduced the modified neurological severity score of MCAO rats (P < 0.01) and increased the number of surviving neurons in both the striatum and hippocampal dentate gyrus region (P < 0.01, respectively). Moreover, BMSCs treatment resulted in significant enhancements in various structural parameters of dendrites in layer V pyramidal neurons in the injured hemispheric motor cortex, including total length (P < 0.05), number of branches (P < 0.05), number of intersections (P < 0.01), and spine density (P < 0.05). Then, we performed plasma untargeted metabolomics analysis to study the metabolic changes of BMSCs on AIS. There were 65 differential metabolites identified in the BMSCs treatment group. Metabolic profiling analysis revealed that BMSCs modulate abnormal sphingolipid metabolism and glycerophospholipid metabolism, particularly affecting core members such as sphingomyelin (SM), ceramide (Cer) and sphingosine-1-phosphate (S1P). The metabolic network analysis and pathway-based compound-reaction-enzyme-gene network analysis showed that BMSCs inhibited the Cer-induced apoptotic pathway and promoted the S1P signaling pathway. These findings suggest that the enhanced effects of BMSCs on neuronal survival and synaptic plasticity after stroke may be mediated through these pathways. In conclusion, our study provides novel insight into the potential mechanisms of BMSCs treatment in stroke and sheds light on the possible clinical translation of BMSCs.

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 levels of urea cycle related amino acids in association with risk of ischemic stroke: Findings from a nested case-control study

OBJECTIVES

The role of urea cycle related amino acids in the development of ischemic stroke (IS) remains unclear. The study aimed to evaluate the association of these amino acids with IS.

MATERIALS AND METHODS

We conducted a case-control study nested within a cohort study in Changshu, Eastern China. A total of 321 cases and 321 controls matched by age and gender were finally included. Plasma levels of ornithine, arginine, spermidine, and proline were measured using ultra-high performance liquid chromatography-tandem mass-spectrometry (UHPLC-MS/MS). Odds ratios (ORs) and their 95 % confidence intervals (CIs) were calculated by conditional logistic regression analyses.

RESULTS

Plasma ornithine was inversely associated with risk of IS [crude OR: 0.62 (95 % CI: 0.40-0.97)]. After adjustment for body mass index, smoking, hypertension, family history of stroke, estimated glomerular filtration rate, and total cholesterol, the corresponding ORs for the highest compared to the lowest quartiles was essentially unchanged [adjusted OR: 0.62 (95 % CI: 0.39-0.99)]. The risk association remained significant after repeating the analyses by excluding the first two years of follow-up. Plasma arginine, spermidine, and proline were not associated with the risk of IS.

CONCLUSION

We observed that higher plasma levels of ornithine were associated with a lower risk of incident IS. Our novel findings suggest a protective role of ornithine in the pathogenesis of IS.

[Algorithms for the diagnosis and treatment of cognitive impairment and dysphagia in stroke patients]

Stroke is a socially significant neurological disease, the second most common cause of disability and mortality. A wide range of neurological problems that occur after stroke: cognitive, motor, speech, and language disfunction, neuropsychiatric, swallowing disorders and others, complicate rehabilitation, impair social and everyday adaptation, and reduce the quality of life of patients and their caregivers. Cognitive impairment (CI) is one of the most significant and common complications of stroke. Stroke increases the risk of their development by 5-8 times. Dysphagia is also a common symptom of stroke, the cause of aspiration complications (pneumonia), and nutritional imbalance. It increases the possibility of developing CI and dementia, and contributes to an increase in mortality. Older adults with CI are at a higher risk of developing dysphagia, therefore the early symptoms of dysphagia (presbyphagia) should be diagnosed. In recent years, the connection between CI and dysphagia has been actively studied. It is extremely important to identify CI and swallowing disorders as early as possible in patients both before and at all stages after stroke; as well as to develop combined multidisciplinary protocols for the rehabilitation of patients with these disorders with pharmacological support for the process.

Assessing the causal effect of genetically predicted metabolites and metabolic pathways on stroke

BACKGROUND

Stroke is a common neurological disorder that disproportionately affects middle-aged and elderly individuals, leading to significant disability and mortality. Recently, human blood metabolites have been discovered to be useful in unraveling the underlying biological mechanisms of neurological disorders. Therefore, we aimed to evaluate the causal relationship between human blood metabolites and susceptibility to stroke.

METHODS

Summary data from genome-wide association studies (GWASs) of serum metabolites and stroke and its subtypes were obtained separately. A total of 486 serum metabolites were used as the exposure. Simultaneously, 11 different stroke phenotypes were set as the outcomes, including any stroke (AS), any ischemic stroke (AIS), large artery stroke (LAS), cardioembolic stroke (CES), small vessel stroke (SVS), lacunar stroke (LS), white matter hyperintensities (WMH), intracerebral hemorrhage (ICH), subarachnoid hemorrhage (SAH), transient ischemic attack (TIA), and brain microbleeds (BMB). A two-sample Mendelian randomization (MR) study was conducted to investigate the causal effects of serum metabolites on stroke and its subtypes. The inverse variance-weighted MR analyses were conducted as causal estimates, accompanied by a series of sensitivity analyses to evaluate the robustness of the results. Furthermore, a reverse MR analysis was conducted to assess the potential for reverse causation. Additionally, metabolic pathway analysis was performed using the web-based MetOrigin.

RESULTS

After correcting for the false discovery rate (FDR), MR analysis results revealed remarkable causative associations with 25 metabolites. Further sensitivity analyses confirmed that only four causative associations involving three specific metabolites passed all sensitivity tests, namely ADpSGEGDFXAEGGGVR* for AS (OR: 1.599, 95% CI 1.283-1.993, p = 2.92 × 10-5) and AIS (OR: 1.776, 95% CI 1.380-2.285, p = 8.05 × 10-6), 1-linoleoylglycerophosph-oethanolamine* for LAS (OR: 0.198, 95% CI 0.091-0.428, p = 3.92 × 10-5), and gamma-glutamylmethionine* for SAH (OR: 3.251, 95% CI 1.876-5.635, p = 2.66 × 10-5), thereby demonstrating a high degree of stability. Moreover, eight causative associations involving seven other metabolites passed both sensitivity tests and were considered robust. The association result of one metabolite (glutamate for LAS) was considered non-robust. As for the remaining metabolites, we speculate that they may potentially possess underlying causal relationships. Notably, no common metabolites emerged from the reverse MR analysis. Moreover, after FDR correction, metabolic pathway analysis identified 40 significant pathways across 11 stroke phenotypes.

CONCLUSIONS

The identified metabolites and their associated metabolic pathways are promising circulating metabolic biomarkers, holding potential for their application in stroke screening and preventive strategies within clinical settings.

omicsMIC: a Comprehensive Benchmarking Platform for Robust Comparison of Imputation Methods in Mass Spectrometry-based Omics Data

Mass spectrometry is a powerful and widely used tool for generating proteomics, lipidomics, and metabolomics profiles, which is pivotal for elucidating biological processes and identifying biomarkers. However, missing values in spectrometry-based omics data may pose a critical challenge for the comprehensive identification of biomarkers and elucidation of the biological processes underlying human complex disorders. To alleviate this issue, various imputation methods for mass spectrometry-based omics data have been developed. However, a comprehensive and systematic comparison of these imputation methods is still lacking, and researchers are frequently confronted with a multitude of options without a clear rationale for method selection. To address this pressing need, we developed omicsMIC (mass spectrometry-based omics with Missing values Imputation methods Comparison platform), an interactive platform that provides researchers with a versatile framework to simulate and evaluate the performance of 28 diverse imputation methods. omicsMIC offers a nuanced perspective, acknowledging the inherent heterogeneity in biological data and the unique attributes of each dataset. Our platform empowers researchers to make data-driven decisions in imputation method selection based on real-time visualizations of the outcomes associated with different imputation strategies. The comprehensive benchmarking and versatility of omicsMIC make it a valuable tool for the scientific community engaged in mass spectrometry-based omics research. OmicsMIC is freely available at https://github.com/WQLin8/omicsMIC.

The potential role of T-cell metabolism-related molecules in chronic neuropathic pain after nerve injury: a narrative review

Neuropathic pain is a common type of chronic pain, primarily caused by peripheral nerve injury. Different T-cell subtypes play various roles in neuropathic pain caused by peripheral nerve damage. Peripheral nerve damage can lead to co-infiltration of neurons and other inflammatory cells, thereby altering the cellular microenvironment and affecting cellular metabolism. By elaborating on the above, we first relate chronic pain to T-cell energy metabolism. Then we summarize the molecules that have affected T-cell energy metabolism in the past five years and divide them into two categories. The first category could play a role in neuropathic pain, and we explain their roles in T-cell function and chronic pain, respectively. The second category has not yet been involved in neuropathic pain, and we focus on how they affect T-cell function by influencing T-cell metabolism. By discussing the above content, this review provides a reference for studying the direct relationship between chronic pain and T-cell metabolism and searching for potential therapeutic targets for the treatment of chronic pain on the level of T-cell energy metabolism.

Metabolomics as a potential tool for monitoring patients with aneurysmal subarachnoid hemorrhage

Metabolomics has evolved into a particularly useful tool to study interactions between metabolites and serves as an aid in unraveling the complexity of entire metabolomes. Nonetheless, it is increasingly viewed as a methodology with practical applications in the clinical setting, where identifying and quantifying biomarkers of interest could prove useful for diagnostics. Starting from a concise overview of the most prominent analytical techniques employed in metabolomics, herein we present a review of its application in studies of brain metabolism and cerebrovascular diseases, paying most attention to its uses in researching aneurysmal subarachnoid hemorrhage. Both animal models and human studies are considered, and metabolites identified as potential biomarkers are highlighted.

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.

Integrated Metabolomics and Lipidomics Approach for the Study of Metabolic Network and Early Diagnosis in Cerebral Infarction

Cerebral infarction (CI) remains a major cause of high mortality and long-term disability worldwide. The exploration of biomarkers and pathogenesis is crucial for the early diagnosis of CI. Although the understanding of metabolic perturbations underlying CI has increased in recent years, the relationship between altered metabolites and disease pathogenesis has only been partially elucidated and requires further investigation. In this study, we performed an integrated metabolomics and lipidomics analysis on 59 healthy subjects and 47 CI patients. Ultimately, 49 metabolite and 68 lipid biomarkers were identified and enriched in 24 disturbed pathways. The metabolic network revealed a significant interaction between altered lipids and other metabolites. Using receiver operating characteristic curve (ROC) analysis, a panel of three polar metabolites and seven lipids was optimized in the training set, which included taurine, oleoylcarnitine, creatinine, PE(22:6/P-18:0), Cer 34:2, GlcCer(d18:0/18:0), DG 44:0, LysoPC(16:0), 22:6-OH/LysoPC, and TAG58:7-FA22:4. Subsequently, a support vector machine (SVM) model was constructed and validated, which showed excellent predictive ability in the validation set. Thereby, the integrated metabolomics and lipidomics approach could contribute to a comprehensive understanding of the metabolic dyshomeostasis associated with the pathogenesis of underlying CI. The present research may promote a deeper understanding and early diagnosis of CI in the clinic. All raw data were deposited in PRIDE (PXD036199).

Different gender-derived gut microbiota influence stroke outcomes by mitigating inflammation

Background and purpose

Stroke is associated with high disability and mortality rates and increases the incidence of organ-related complications. Research has revealed that the outcomes and prognosis of stroke are regulated by the state of the intestinal microbiota. However, the possibility that the manipulation of the intestinal microbiota can alter sex-related stroke outcomes remain unknown.

Methods

To verify the different effects of microbiota from different sexes on stroke outcomes, we performed mouse fecal microbiota transplantation (FMT) and established a model of ischemic stroke. Male and female mice received either male or female microbiota through FMT. Ischemic stroke was triggered by MCAO (middle cerebral artery occlusion), and sham surgery served as a control. Over the next few weeks, the mice underwent neurological evaluation and metabolite and inflammatory level detection, and we collected fecal samples for 16S ribosomal RNA analysis.

Results

We found that when the female mice were not treated with FMT, the microbiota (especially the Firmicutes-to-Bacteroidetes ratio) and the levels of three main metabolites tended to resemble those of male mice after experimental stroke, indicating that stroke can induce an ecological imbalance in the biological community. Through intragastric administration, the gut microbiota of male and female mice was altered to resemble that of the other sex. In general, in female mice after MCAO, the survival rate was increased, the infarct area was reduced, behavioral test performance was improved, the release of beneficial metabolites was promoted and the level of inflammation was mitigated. In contrast, mice that received male microbiota were much more hampered in terms of protection against brain damage and the recovery of neurological function.

Conclusion

A female-like biological community reduces the level of systemic proinflammatory cytokines after ischemic stroke. Poor stroke outcomes can be positively modulated following supplementation with female gut microbiota.

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.

Hippocampal metabolic recovery as a manifestation of the protective effect of ischemic preconditioning in rats

The ever-present risk of brain ischemic events in humans and its full prevention make the detailed studies of an organism's response to ischemia at different levels essential to understanding the mechanism of the injury as well as protection. We used the four-vessel occlusion as an animal model of forebrain ischemia to investigate its impact on the metabolic alterations in both the hippocampus and the blood plasma to see changes on the systemic level. By inducing sublethal ischemic stimuli, we focused on the endogenous phenomena known as ischemic tolerance. NMR spectroscopy was used to analyze relative metabolite levels in tissue extracts from rats' hippocampus and blood plasma in three various ischemic/reperfusion times: 3 h, 24 h, and 72 h. Hippocampal tissues were characterized by postischemically decreased glutamate and GABA (4-aminobutyrate) tissue content balanced with increased glutamine level, with most pronounced changes at 3 h reperfusion time. Glutamate (as well as glutamine) levels recovered towards the control levels on the third day, as if the glutamate re-synthesis would be firstly preferred before GABA. These results are indicating the higher feasibility of re-establishing of glutamatergic transmission three days after an ischemic event, in contrast to GABA-ergic. Tissue levels of N-acetylaspartate (NAA), as well as choline, were decreased without the tendency to recover three days after the ischemic event. Metabolomic analysis of blood plasma revealed that ischemically preconditioned rats, contrary to the non-preconditioned animals, did not show hyperglycemic conditions. Ischemically induced semi-ketotic state, manifested in increased plasma ketone bodies 3-hydroxybutyrate and acetoacetate, seems to be programmed to support the brain tissue revitalization after the ischemic event. These and other metabolites changes found in blood plasma as well as in the hippocampus were observed to a lower extent or recovered faster in preconditioned animals. Some metabolomic changes in hippocampal tissue extract were so strong that even single metabolites were able to differentiate between ischemic, ischemically preconditioned, and control brain tissues.

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.

The Differences of Metabolites in Different Parts of the Brain Induced by Shuxuetong Injection against Cerebral Ischemia-Reperfusion and Its Corresponding Mechanism

Ischemic stroke is often associated with a large disease burden. The existence of ischemia-reperfusion injury brings great challenges to the treatment of ischemic stroke. The purpose of this study was to explore the differences of metabolites in different parts of the brain induced by Shuxuetong injection against cerebral ischemia-reperfusion and to extend the corresponding mechanism. The rats were modeled by transient middle cerebral artery occlusion (t-MCAO) operation, and the success of modeling was determined by neurological function score and TTC staining. UPLC-Q/TOF-MS metabolomics technique and multivariate statistical analysis were used to analyze the changes and differences of metabolites in the cortex and hippocampus of cerebral ischemia-reperfusion rats. Compared with the model group, the neurological function score and cerebral infarction volume of the Shuxuetong treatment group were significantly different. There were differences and changes in the metabolic distribution of the cortex and hippocampus in each group, the distribution within the group was relatively concentrated. The separation trend between the groups was obvious, and the distribution of the Shuxuetong treatment group was similar to that of the sham operation group. We identified 13 metabolites that were differentially expressed in the cortex, including glutamine, dihydroorotic acid, and glyceric acid. We also found five differentially expressed metabolites in the hippocampus, including glutamic acid and fumaric acid. The common metabolic pathways of Shuxuetong on the cortex and hippocampus were D-glutamine and D-glutamate metabolism and nitrogen metabolism, which showed inhibition of cortical glutamine and promotion of hippocampal glutamic acid. Specific pathways of Shuxuetong enriched in the cortex included glyoxylate and dicarboxylate metabolism and pyrimidine metabolism, which showed inhibition of glyceric acid and dihydroorotic acid. Specific pathways of Shuxuetong enriched in the hippocampus include arginine biosynthesis and citrate cycle (TCA cycle), which promotes fumaric acid. Shuxuetong injection can restore and adjust the metabolic disorder of the cortex and hippocampus in cerebral ischemia-reperfusion rats. The expression of Shuxuetong in different parts of the brain is different and correlated.

Therapeutic Effect of Buyang Huanwu Decoction on the Gut Microbiota and Hippocampal Metabolism in a Rat Model of Cerebral Ischemia

Buyang Huanwu decoction (BHD) is a well-known Chinese herbal prescription. It has been widely used in the clinical treatment of cerebral ischemia (CI) in China. However, the mechanism underlying the treatment of CI with BHD remains to be elucidated. In this study, we combined microbiomic and metabolomic strategies to explore the therapeutic effects of BHD on middle cerebral artery occlusion (MCAO) in rats. Our results showed that BHD could effectively improve neurological severity scores and alleviate neuronal damage in rats with MCAO. BHD could also reduce the level of peripheral proinflammatory cytokines and inhibit neuroinflammation. 16S rRNA sequencing showed that BHD could increase the relative abundances of the genera Lactobacillus, Faecalibacterium, Ruminococcaceae_UCG-002, etc., while decreasing the relative abundances of the genera Escherichia-Shigella, Klebsiella, Streptococcus, Coprococcus_2, Enterococcus, etc. Untargeted metabolomic analysis of hippocampal samples showed that 17 significantly differentially abundant metabolites and 9 enriched metabolic pathways were linked with BHD treatment. We also found that the regulatory effects of BHD on metabolites were correlated with the differentially abundant microbial taxa. The predicted function of the gut microbiota and the metabolic pathway enrichment results showed that purine metabolism, glutamatergic synapses, arginine and proline metabolism, and alanine, aspartic acid and glutamate metabolism were involved in the effects of BHD. These pathways may be related to pathological processes such as excitotoxicity, neuroinflammation, and energy metabolism disorder in CI. In summary, these findings suggest that regulation of hippocampal metabolism and of the composition and function of the gut microbiota may be important mechanisms underlying the effect of BHD in the treatment of CI.

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.

Metabolic Changes Induced by Cerebral Ischemia, the Effect of Ischemic Preconditioning, and Hyperhomocysteinemia

¹H Nuclear Magnetic Resonance (NMR) metabolomics is one of the fundamental tools in the fast-developing metabolomics field. It identifies and quantifies the most abundant metabolites, alterations of which can describe energy metabolism, activated immune response, protein synthesis and catabolism, neurotransmission, and many other factors. This paper summarizes our results of the ¹H NMR metabolomics approach to characterize the distribution of relevant metabolites and their alterations induced by cerebral ischemic injury or its combination with hyperhomocysteinemia in the affected tissue and blood plasma in rodents. A decrease in the neurotransmitter pool in the brain tissue likely follows the disordered feasibility of post-ischemic neurotransmission. This decline is balanced by the increased tissue glutamine level with the detected impact on neuronal health. The ischemic injury was also manifested in the metabolomic alterations in blood plasma with the decreased levels of glycolytic intermediates, as well as a post-ischemically induced ketosis-like state with increased plasma ketone bodies. As the 3-hydroxybutyrate can act as a likely neuroprotectant, its post-ischemic increase can suggest its supporting role in balancing ischemic metabolic dysregulation. Furthermore, the ¹H NMR approach revealed post-ischemically increased 3-hydroxybutyrate in the remote organs, such as the liver and heart, as well as decreased myocardial glutamate. Ischemic preconditioning, as a proposed protective strategy, was manifested in a lower extent of metabolomic changes and/or their faster recovery in a longitudinal study. The paper also summarizes the pre- and post-ischemic metabolomic changes in the rat hyperhomocysteinemic models. Animals are challenged with hyperglycemia and ketosis-like state. A decrease in several amino acids in plasma follows the onset and progression of hippocampal neuropathology when combined with ischemic injury. The ¹H NMR metabolomics approach also offers a high potential for metabolites in discriminatory analysis in the search for potential biomarkers of ischemic injury. Based on our results and the literature data, this paper presents valuable findings applicable in clinical studies and suggests the precaution of a high protein diet, especially foods which are high in Met content and low in B vitamins, in the possible risk of human cerebrovascular neuropathology.

Therapeutic development of polymers for prion disease

Prion diseases, also known as transmissible spongiform encephalopathies, are caused by the accumulation of abnormal isoforms of the prion protein (scrapie isoform of the prion protein, PrPSc) in the central nervous system. Many compounds with anti-prion activities have been found using in silico screening, in vitro models, persistently prion-infected cell models, and prion-infected rodent models. Some of these compounds include several types of polymers. Although the inhibition or removal of PrPSc production is the main target of therapy, the unique features of prions, namely protein aggregation and assembly accompanied by steric structural transformation, may require different strategies for the development of anti-prion drugs than those for conventional therapeutics targeting enzyme inhibition, agonist ligands, or modulation of signaling. In this paper, we first overview the history of the application of polymers to prion disease research. Next, we describe the characteristics of each type of polymer with anti-prion activity. Finally, we discuss the common features of these polymers. Although drug delivery of these polymers to the brain is a challenge, they are useful not only as leads for therapeutic drugs but also as tools to explore the structure of PrPSc and are indispensable for prion disease research.

Potential Biomarkers for Post-Stroke Cognitive Impairment: A Systematic Review and Meta-Analysis

Stroke is a primary debilitating disease in adults, occurring in 15 million individuals each year and causing high mortality and disability rates. The latest estimate revealed that stroke is currently the second leading cause of death worldwide. Post-stroke cognitive impairment (PSCI), one of the major complications after stroke, is frequently underdiagnosed. However, stroke has been reported to increase the risk of cognitive impairment by at least five to eight times. In recent decades, peripheral blood molecular biomarkers for stroke have emerged as diagnostic, prognostic, and therapeutic targets. In this study, we aimed to evaluate some blood-derived proteins for stroke, especially related to brain damage and cognitive impairments, by conducting a systematic review and meta-analysis and discussing the possibility of these proteins as biomarkers for PSCI. Articles published before 26 July 2021 were searched in PubMed, Embase, the Web of Science, and the Cochrane Library to identify all relevant studies reporting blood biomarkers in patients with stroke. Among 1820 articles, 40 were finally identified for this study. We meta-analyzed eight peripheral biomarker candidates: homocysteine (Hcy), high-density lipoprotein cholesterol (HDL-C), C-reactive protein (CRP), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), triglyceride (TG), uric acid, and glycated hemoglobin (HbA1c). The Hcy, CRP, TC, and LDL-C levels were significantly higher in patients with PSCI than in the non-PSCI group; however, the HDL-C, TG, uric acid, and HbA1c levels were not different between the two groups. Based on our findings, we suggest the Hcy, CRP, TC, and LDL-C as possible biomarkers in patients with post-stroke cognitive impairment. Thus, certain blood proteins could be suggested as effective biomarkers for PSCI.