Targeted Metabolomic Biomarkers for Stroke Subtyping

BACKGROUND AND PURPOSE

Ischemic stroke is a heterogeneous disease with various etiologies. The current subtyping process is complicated, time-consuming, and costly. Metabolite-based biomarkers have the potential to improve classification and deliver optimal treatments. We here aimed to identify novel, targeted metabolomics-based biomarkers to discriminate between large-artery atherosclerosis (LAA) and cardioembolic (CE) stroke.

METHODS

We acquired serum samples and clinical data from a hospital-based acute stroke registry (ischemic stroke within 3 days from symptom onset). We included 346 participants (169 LAA, 147 CE, and 30 healthy older adults) and divided them into training and test sets. Targeted metabolomic analysis was performed using quantitative and quality-controlled liquid chromatography with tandem mass spectrometry. A multivariate regression model using metabolomic signatures was created that could independently distinguish between LAA and CE strokes.

RESULTS

The training set (n = 193) identified metabolomic signatures that were different in patients with LAA and CE strokes. Six metabolomic biomarkers, i.e., lysine, serine, threonine, kynurenine, putrescine, and lysophosphatidylcholine acyl C16:0, could discriminate between LAA and CE stroke after adjusting for sex, age, body mass index, stroke severity, and comorbidities. The enhanced diagnostic power of key metabolite combinations for discriminating between LAA and CE stroke was validated using the test set (n = 123).

CONCLUSIONS

We observed significant differences in metabolite profiles in LAA and CE strokes. Targeted metabolomics may provide enhanced diagnostic yield for stroke subtypes. The pathophysiological pathways of the identified metabolites should be explored in future studies.

Association of lysine pathway metabolites with moyamoya disease

BACKGROUND AND OBJECTIVE

Lysine and its pathway metabolites have been identified as novel biomarkers for metabolic and vascular diseases. The role of them in the identification of moyamoya disease (MMD) has not been elucidated. This study aimed to determine the association between lysine pathway metabolites and the presence of MMD.

METHODS

We prospectively enrolled 360 MMD patients and 89 healthy controls from September 2020 to December 2021 in Beijing Tiantan Hospital. Serum levels of lysine, pipecolic acid and 2-aminoadipic acid were measured by liquid chromatography-mass spectrometry. We employed logistic regression and restricted cubic spline to explore the association between these metabolites and the presence of MMD. Stratified analyses were also conducted to test the robustness of results.

RESULTS

We observed that lysine levels in MMD patients were significantly higher and pipecolic acid levels were significantly lower compared to HCs (both p < 0.001), while no difference was found in the level of 2-AAA between both groups. When comparing metabolites by quartiles, elevated lysine levels were linked to increased odds for MMD (the fourth quartile [Q4] vs the first quartile [Q1]: odds ratio, 3.48, 95%CI [1.39-8.75]), while reduced pipecolic acid levels correlated with higher odds (Q4 vs Q1: odds ratio, 0.08; 95 % CI [0.03-0.20]). The restricted cubic spline found a L-shaped relationship between pipecolic acid level and the presence of MMD, with a cutoff point at 2.52 μmol/L. Robust results were also observed across subgroups.

CONCLUSION

Elevated lysine levels were correlated with increased odds of MMD presence, while lower pipecolic acid levels were associated with higher odds of the condition. These results suggest potential new biomarkers for the identification of MMD.

CLINICAL TRIAL REGISTRY NUMBER

URL: https://www.chictr.org.cn/. Unique identifier: ChiCTR2200061889.

1H NMR metabolomics insights into comparative diabesity in male and female zebrafish and the antidiabetic activity of DL-limonene

Zebrafish have been utilized for many years as a model animal for pharmacological studies on diabetes and obesity. High-fat diet (HFD), streptozotocin and alloxan injection, and glucose immersion have all been used to induce diabetes and obesity in zebrafish. Currently, studies commonly used both male and female zebrafish, which may influence the outcomes since male and female zebrafish are biologically different. This study was designed to investigate the difference between the metabolites of male and female diabetic zebrafish, using limonene - a natural product which has shown several promising results in vitro and in vivo in treating diabetes and obesity-and provide new insights into how endogenous metabolites change following limonene treatment. Using HFD-fed male and female zebrafish, we were able to develop an animal model of T2D and identify several endogenous metabolites that might be used as diagnostic biomarkers for diabetes. The endogenous metabolites in males and females were different, even though both genders had high blood glucose levels and a high BMI. Treatment with limonene prevented high blood glucose levels and improved in diabesity zebrafish by limonene, through reversal of the metabolic changes caused by HFD in both genders. In addition, limonene was able to reverse the elevated expression of AKT during HFD.

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.

Effect of lactic acid bacteria by different concentrations of copper based on non-target metabolomic analysis

Copper (Cu) is an essential element for mammals, but excess intake can have detrimental health consequences. However, Cu is no longer present in the "Limit of Contaminants in Foods" promulgated in 2022. The potential impact of different Cu (II) concentrations on human health remains unclear. In this study, a strain of lactic acid bacteria (LAB), namely, Lactiplantibacillus plantarum CICC 23121 (L23121), was selected as a prebiotic indicator strain to indirectly assess the effects of food-limited Cu (II) concentrations (issued by Tolerance limit of copper in foods in 1994) on the functions of intestinal microbes. We used non-target metabolomics, automatic growth curve detector, scanning electron microscopy (SEM), and Fourier transform infrared spectroscopy (FTIR) to investigate the effects of Cu (II) on L23121. The study revealed shows that the 50% minimum inhibitory concentration (MIC50) of Cu (II) for most lactic acid bacteria was 4 mg/L. At low Cu (II) concentrations (≤ 4 mg/L), the pentose phosphate pathway and pyrimidine metabolism of the lactic acid bacteria were affected, resulting in a decrease in the content of beneficial secondary metabolites and a significant decrease in the cell activity. As Cu (II) concentrations increase (≥ 6 mg/L), the key amino acid and lipid metabolisms were affected, leading to the inhibition of growth and primary metabolite production of the bacteria. Under high concentration of Cu (II) (6 mg/L), the surface adhesion of the bacteria was distorted and covered with significantly large particles, and the functional groups of the cells were significantly shifted. As a probiotic, the abundance of lactic acid bacteria in the intestine is significantly reduced, which will inevitably seriously damage intestinal homeostasis. Thus, to protect human intestinal microbes' health, it is recommended to limit the concentration of Cu in food to less than 4 mg/L.

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.

Neuroprotective effects of Longxue Tongluo Capsule on ischemic stroke rats revealed by LC-MS/MS-based metabolomics approach

Objective

The present study aimed to evaluate the therapeutic effect and explore the underlying mechanisms of Longxue Tongluo Capsule (LTC) on ischemic stroke rats.

Methods

Twenty-six rats were randomly divided into four groups, including sham group, sham + LTC group, MCAO group, and MCAO + LTC group. Ischemic stroke rats were simulated by middle cerebral artery occlusion (MCAO), and LTC treatment group were orally administrated with 300 mg/kg of LTC once daily for seven consecutive days. LTC therapy was validated in terms of neurobehavioral abnormality evaluation, cerebral infarct area, and histological assessments. The plasma metabolome comparisons amongst different groups were conducted by UHPLC-Q Exactive MS in combination with subsequent multivariate statistical analysis, aiming to finding the molecules in respond to the surgery or LTC treatment.

Results

Intragastric administration of LTC significantly decreased not only the neurobehavioral abnormality scores but also the cerebral infarct area of MCAO rats. The interstitial edema, atrophy, and pyknosis of glial and neuronal cells occurred in the infarcted area, core area, and marginal area of cerebral cortex were improved after LTC treatment. A total of 13 potential biomarkers were observed, and Youden index of 11 biomarkers such as LysoPC, SM, and PE were more than 0.7, which were involved in neuroprotective process. The correlation and pathway analysis showed that LTC was beneficial to ischemic stroke rats via regulating glycerophospholipid and sphingolipid metabolism, together with nicotinate and nicotinamide metabolism. Heatmap and ternary analysis indicated the synergistic effect of carbohydrates and lipids may be induced by flavonoid intake from LTC.

Conclusion

The present study could provide evidence that metabolomics, as systematic approach, revealed its capacity to evaluate the holistic efficacy of TCM, and investigate the molecular mechanism underlying the clinical treatment of LTC on ischemic stroke.

Advancing Stroke Research on Cerebral Thrombi with Omic Technologies

Cerebrovascular diseases represent a leading cause of disability, morbidity, and death worldwide. In the last decade, the advances in endovascular procedures have not only improved acute ischemic stroke care but also conceded a thorough analysis of patients' thrombi. Although early anatomopathological and immunohistochemical analyses have provided valuable insights into thrombus composition and its correlation with radiological features, response to reperfusion therapies, and stroke etiology, these results have been inconclusive so far. Recent studies applied single- or multi-omic approaches-such as proteomics, metabolomics, transcriptomics, or a combination of these-to investigate clot composition and stroke mechanisms, showing high predictive power. Particularly, one pilot studies showed that combined deep phenotyping of stroke thrombi may be superior to classic clinical predictors in defining stroke mechanisms. Small sample sizes, varying methodologies, and lack of adjustments for potential confounders still represent roadblocks to generalizing these findings. However, these techniques hold the potential to better investigate stroke-related thrombogenesis and select secondary prevention strategies, and to prompt the discovery of novel biomarkers and therapeutic targets. In this review, we summarize the most recent findings, overview current strengths and limitations, and present future perspectives in the field.

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.

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.

Urinary metabotypes of newborns with perinatal asphyxia undergoing therapeutic hypothermia

Perinatal asphyxia (PA) still occurs in about three to five per 1,000 deliveries in developed countries; 20% of these infants show hypoxic-ischemic encephalopathy (HIE) on brain magnetic resonance imaging (MRI). The aim of our study was to apply metabolomic analysis to newborns undergoing therapeutic hypothermia (TH) after PA to identify a distinct metabotype associated with the development of HIE on brain MRI. We enrolled 53 infants born at >35 weeks of gestation with PA: 21 of them showed HIE on brain MRI (the “HIE” group), and 32 did not (the “no HIE” group). Urine samples were collected at 24, 48 and 72 hours of TH. Metabolomic data were acquired using high-resolution mass spectrometry and analyzed with univariate and multivariate methods. Considering the first urines collected during TH, untargeted analysis found 111 relevant predictors capable of discriminating between the two groups. Of 35 metabolites showing independent discriminatory power, four have been well characterized: L-alanine, Creatine, L-3-methylhistidine, and L-lysine. The first three relate to cellular energy metabolism; their involvement suggests a multimodal derangement of cellular energy metabolism during PA/HIE. In addition, seven other metabolites with a lower annotation level (proline betaine, L-prolyl-L-phenylalanine, 2-methyl-dodecanedioic acid, S-(2-methylpropionyl)-dihydrolipoamide-E, 2,6 dimethylheptanoyl carnitine, Octanoylglucuronide, 19-hydroxyandrost-4-ene-3,17-dione) showed biological consistency with the clinical picture of PA. Moreover, 4 annotated metabolites (L-lysine, L-3-methylhistidine, 2-methyl-dodecanedioic acid, S-(2-methylpropionyl)-dihydrolipoamide-E) retained a significant difference between the “HIE” and “no HIE” groups during all the TH treatment. Our analysis identified a distinct urinary metabotype associated with pathological findings on MRI, and discovered 2 putative markers (L-lysine, L-3-methylhistidine) which may be useful for identifying neonates at risk of developing HIE after PA.

Dynamic Associations of Milk Components With the Infant Gut Microbiome and Fecal Metabolites in a Mother-Infant Model by Microbiome, NMR Metabolomic, and Time-Series Clustering Analyses

Background: The gut microbiome and fecal metabolites of breastfed infants changes during lactation, and are influenced by breast milk components. This study aimed to investigate dynamic associations of milk components with the infant gut microbiome and fecal metabolites throughout the lactation period in a mother–infant model.

Methods: One month after delivery, breast milk and subsequent infant feces were collected in a pair for 5 months from a mother and an exclusively breastfed infant. Composition of the fecal microbiome was determined with 16S rRNA sequencing. Low-molecular-weight metabolites, including human milk oligosaccharides (HMOs), and antibacterial proteins were measured in feces and milk using ¹H NMR metabolomics and enzyme-linked immunosorbent assays. The association of milk bioactive components with the infant gut microbiome and fecal metabolites was determined with Python clustering and correlation analyses.

Results: The HMOs in milk did not fluctuate throughout the lactation period. However, they began to disappear in infant feces at the beginning of month 4. Notably, at this time-point, a bifidobacterium species switching (from B. breve to B. longum subsp. infantis) occurred, accompanied by fluctuations in several metabolites including acetate and butyrate in infant feces.

Conclusions: Milk bioactive components, such as HMOs, might play different roles in the exclusively breastfed infants depending on the lactation period.

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.

Plasma Metabolomics in a Nonhuman Primate Model of Abdominal Radiation Exposure

The acute radiation syndrome is defined in large part by radiation injury in the hematopoietic and gastrointestinal (GI) systems. To identify new pathways involved in radiation-induced GI injury, this study assessed dose- and time-dependent changes in plasma metabolites in a nonhuman primate model of whole abdominal irradiation. Male and female adult Rhesus monkeys were exposed to 6 MV photons to the abdomen at doses ranging between 8 and 14 Gy. At time points from 1 to 60 days after irradiation, plasma samples were collected and subjected to untargeted metabolomics. With the limited sample size of females, different discovery times after irradiation between males and females were observed in metabolomics pattern. Detailed analyses are restricted to only males for the discovery power. Radiation caused an increase in fatty acid oxidation and circulating levels of corticosteroids which may be an indication of physiological stress, and amino acids, indicative of a cellular repair response. The largest changes were observed at days 9 and 10 post-irradiation, with most returning to baseline at day 30. In addition, dysregulated metabolites involved in amino acid pathways, which might indicate changes in the microbiome, were detected. In conclusion, abdominal irradiation in a nonhuman primate model caused a plasma metabolome profile indicative of GI injury. These results point to pathways that may be targeted for intervention or used as early indicators of GI radiation injury. Moreover, our results suggest that effects are sex-specific and that interventions may need to be tailored accordingly.

Elevated Levels of Homocysteinesulfinic Acid in the Plasma of Patients with Amyotrophic Lateral Sclerosis: A Potential Source of Excitotoxicity?

OBJECTIVES

Excitotoxicity is thought to be involved in the pathogenesis of amyotrophic lateral sclerosis (ALS). One possible source of excitotoxicity is the presence of sulphur amino acids (SAAs). In the brain of subjects with ALS, there are increased levels of taurine. In the metabolism of methionine to taurine, excitatory sulphur amino acids (SAAs) are formed. These could potentially contribute to excitotoxicity in ALS. The present study has examined whether plasma levels of SAAs in 38 ALS patients differ from those of 30 healthy controls.

METHODS

Plasma levels of SAAs were measured by liquid chromatography mass spectrometry.

RESULTS

There were no significant changes in plasma cysteic acid, cysteine sulfinic acid, and homocysteic acid in ALS patients compared to healthy subjects. Significant elevations in plasma homocysteinesulfinic acid (HCSA) levels (p < 0.0001) were observed in the ALS patients (75.91 ± 15.38 nM) compared to healthy controls (54.06 ± 8.503 nM); 50% of the ALS patients had HCSA levels that were 1.5-2-folds higher than those of controls. Plasma levels of HCSA differed significantly (p = 0.0440) between patients with bulbar onset and spinal onset (68.57 ± 14.20 vs. 79.30 ± 14.95 nM, respectively).

CONCLUSION

HCSA is elevated in the blood of subjects with ALS. Since HCSA can be transported from the blood to the CNS by active transport, has neurotransmitter properties, and can activate synaptic receptors including NMDAR and metabotropic glutamate receptor, it is possible that increases in HCSA could influence glutamatergic neurotransmission and potentially contribute to excitotoxicity in some ALS 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.

Metabolomics and metabolites in ischemic stroke

Stroke is a major reason for disability and the second highest cause of death in the world. When a patient is admitted to a hospital, it is necessary to identify the type of stroke, and the likelihood for development of a recurrent stroke, vascular dementia, and depression. These factors could be determined using different biomarkers. Metabolomics is a very promising strategy for identification of biomarkers. The advantage of metabolomics, in contrast to other analytical techniques, resides in providing low molecular weight metabolite profiles, rather than individual molecule profiles. Technically, this approach is based on mass spectrometry and nuclear magnetic resonance. Furthermore, variations in metabolite concentrations during brain ischemia could alter the principal neuronal functions. Different markers associated with ischemic stroke in the brain have been identified including those contributing to risk, acute onset, and severity of this pathology. In the brain, experimental studies using the ischemia/reperfusion model (IRI) have shown an impaired energy and amino acid metabolism and confirmed their principal roles. Literature data provide a good basis for identifying markers of ischemic stroke and hemorrhagic stroke and understanding metabolic mechanisms of these diseases. This opens an avenue for the successful use of identified markers along with metabolomics technologies to develop fast and reliable diagnostic tools for ischemic and hemorrhagic stroke.

Cardioprotective effect of ginsenoside Rb1 via regulating metabolomics profiling and AMP-activated protein kinase-dependent mitophagy

Background

Ginsenoside Rb1, a bioactive component isolated from the Panax ginseng, acts as a remedy to prevent myocardial injury. However, it is obscure whether the cardioprotective functions of Rb1 are related to the regulation of endogenous metabolites, and its potential molecular mechanism still needs further clarification, especially from a comprehensive metabolomics profiling perspective.

Methods

The mice model of acute myocardial ischemia (AMI) and oxygen glucose deprivation (OGD)-induced cardiomyocytes injury were applied to explore the protective effect and mechanism of Rb1. Meanwhile, the comprehensive metabolomics profiling was conducted by high-performance liquid chromatography and quadrupole time-of-flight mass spectrometry (HPLC-Q/TOF-MS) and a tandem liquid chromatography and mass spectrometry (LC-MS).

Results

Rb1 treatment profoundly reduced the infarct size and attenuated myocardial injury. The metabolic network map of 65 differential endogenous metabolites was constructed and provided a new inspiration for the treatment of AMI by Rb1, which was mainly associated with mitophagy. In vivo and in vitro experiments, Rb1 was found to improve mitochondrial morphology, mitochondrial function and promote mitophagy. Interestingly, the mitophagy inhibitor partly attenuated the cardioprotective effect of Rb1. Additionally, Rb1 markedly facilitated the phosphorylation of AMP-activated protein kinase α (AMPKα), and AMPK inhibition partially weakened the role of Rb1 in promoting mitophagy.

Conclusions

Ginsenoside Rb1 protects acute myocardial ischemia injury through promoting mitophagy via AMPKα phosphorylation, which might lay the foundation for the further application of Rb1 in cardiovascular diseases.

Association of Circulating Metabolites in Plasma or Serum and Risk of Stroke: Meta-analysis From 7 Prospective Cohorts

OBJECTIVE

To conduct a comprehensive analysis of circulating metabolites and incident stroke in large prospective population-based settings.

METHODS

We investigated the association of metabolites with risk of stroke in 7 prospective cohort studies including 1,791 incident stroke events among 38,797 participants in whom circulating metabolites were measured by nuclear magnetic resonance technology. The relationship between metabolites and stroke was assessed with Cox proportional hazards regression models. The analyses were performed considering all incident stroke events and ischemic and hemorrhagic events separately.

RESULTS

The analyses revealed 10 significant metabolite associations. Amino acid histidine (hazard ratio [HR] per SD 0.90, 95% confidence interval [CI] 0.85, 0.94; p = 4.45 × 10-5), glycolysis-related metabolite pyruvate (HR per SD 1.09, 95% CI 1.04, 1.14; p = 7.45 × 10-4), acute-phase reaction marker glycoprotein acetyls (HR per SD 1.09, 95% CI 1.03, 1.15; p = 1.27 × 10-3), cholesterol in high-density lipoprotein (HDL) 2, and several other lipoprotein particles were associated with risk of stroke. When focused on incident ischemic stroke, a significant association was observed with phenylalanine (HR per SD 1.12, 95% CI 1.05, 1.19; p = 4.13 × 10-4) and total and free cholesterol in large HDL particles.

CONCLUSIONS

We found association of amino acids, glycolysis-related metabolites, acute-phase reaction markers, and several lipoprotein subfractions with the risk of stroke. These findings support the potential of metabolomics to provide new insights into the metabolic changes preceding 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.

Circulating Metabolites as Potential Biomarkers for Neurological Disorders-Metabolites in Neurological Disorders

There are, still, limitations to predicting the occurrence and prognosis of neurological disorders. Biomarkers are molecules that can change in different conditions, a feature that makes them potential tools to improve the diagnosis of disease, establish a prognosis, and monitor treatments. Metabolites can be used as biomarkers, and are small molecules derived from the metabolic process found in different biological media, such as tissue samples, cells, or biofluids. They can be identified using various strategies, targeted or untargeted experiments, and by different techniques, such as high-performance liquid chromatography, mass spectrometry, or nuclear magnetic resonance. In this review, we aim to discuss the current knowledge about metabolites as biomarkers for neurological disorders. We will present recent developments that show the need and the feasibility of identifying such biomarkers in different neurological disorders, as well as discuss relevant research findings in the field of metabolomics that are helping to unravel the mechanisms underlying neurological disorders. Although several relevant results have been reported in metabolomic studies in patients with neurological diseases, there is still a long way to go for the clinical use of metabolites as potential biomarkers in these disorders, and more research in the field is needed.

Metabolome Changes in Cerebral Ischemia

Cerebral ischemia is caused by perturbations in blood flow to the brain that trigger sequential and complex metabolic and cellular pathologies. This leads to brain tissue damage, including neuronal cell death and cerebral infarction, manifesting clinically as ischemic stroke, which is the cause of considerable morbidity and mortality worldwide. To analyze the underlying biological mechanisms and identify potential biomarkers of ischemic stroke, various in vitro and in vivo experimental models have been established investigating different molecular aspects, such as genes, microRNAs, and proteins. Yet, the metabolic and cellular pathologies of ischemic brain injury remain not fully elucidated, and the relationships among various pathological mechanisms are difficult to establish due to the heterogeneity and complexity of the disease. Metabolome-based techniques can provide clues about the cellular pathologic status of a condition as metabolic disturbances can represent an endpoint in biological phenomena. A number of investigations have analyzed metabolic changes in samples from cerebral ischemia patients and from various in vivo and in vitro models. We previously analyzed levels of amino acids and organic acids, as well as polyamine distribution in an in vivo rat model, and identified relationships between metabolic changes and cellular functions through bioinformatics tools. This review focuses on the metabolic and cellular changes in cerebral ischemia that offer a deeper understanding of the pathology underlying ischemic strokes and contribute to the development of new diagnostic and therapeutic approaches.

Circular RNA expression profile in blood according to ischemic stroke etiology

Background

The discovery of novel biomarkers of stroke etiology would be most helpful in management of acute ischemic stroke patients. Recently, circular RNAs (circRNAs) have been proposed as candidate biomarkers of neurological conditions due to its high stability. circRNAs function as sponges, sequestering miRNAs and are involved in most relevant biological functions. Our aim was to identify differentially expressed circRNAs in acute ischemic stroke patients according to stroke etiology.

Methods

A comprehensive expression profile of blood circRNAs was conducted by Arraystar Human circRNA arrays (13,617 probes) on a discovery cohort of 30 stroke patients with different stroke etiologies by TOAST classification. Real-time quantitative PCR (RT-qPCR) was used to validate array results in a cohort of 50 stroke patients. Functional in silico analysis was performed to identify potential interactions with microRNAs (miRNAs) and pathways underlying deregulated circRNAs.

Results

A set of 60 circRNAs were found to be upregulated in atherotrombotic versus cardioembolic strokes (fold-change > = 1.5 and p-value ≤ 0.05). Differential expression of hsa_circRNA_102488, originated from UBA52 gene, was replicated in the validation cohort. RNA-binding proteins (RBPs) sites of hsa_circRNA_102488 clustered around AGO2 and FUS proteins. Further functional analysis revealed interactions between deregulated circRNAs and a set of miRNAs involved in stroke-related pathways, such as fatty acid biogenesis or lysine degradation.

Conclusion

Different stroke subtypes show specific profiles of circRNAs expression. circRNAs may serve as a new source of biomarkers of stroke etiology in acute ischemic stroke patients.

High-resolution metabolomics study revealing l-homocysteine sulfinic acid, cysteic acid, and carnitine as novel biomarkers for high acute myocardial infarction risk

BACKGROUND

Identifying changes in serum metabolites before the occurrence of acute myocardial infarction (AMI) is an important approach for finding novel biomarkers of AMI.

METHODS

In this prospective cohort study, serum samples obtained from patients at risk of AMI (n = 112) and non-risk controls (n = 89) were tested using high-resolution metabolomics (HRM). Partial least-squares discriminant analysis (PLS-DA), along with univariate analysis using a false discovery rate (FDR) of q = 0.05 were performed to discriminate metabolic profiles and to determine significantly different metabolites between healthy control and AMI risk groups.

RESULTS

PLS-DA significantly separated the AMI risk sera from control sera. The metabolites associated with amino acid biosynthesis, 2-oxocarboxylic acid, tryptophan, and amino sugar and nucleotide sugar metabolism pathways were mainly elevated in patients at risk of AMI. Further validation and quantification by MS/MS showed that tryptophan, carnitine, L-homocysteine sulfinic acid (L-HCSA), and cysteic acid (CA) were upregulated, while L-cysteine and L-cysteine sulfinic acid (L-CSA) were downregulated, specifically among AMI risk sera. Additionally, these discriminant metabolic profiles were not related to hypertension, smoking or alcoholism.

CONCLUSION

In conclusion, detecting upregulated L-HCSA and CA along with carnitine among patients at risk for AMI could serve as promising non-invasive biomarkers for early AMI detection.

Establishing molecular signatures of stroke focusing on omic approaches: a narrative review

Stroke or 'brain attack' is considered to be the major cause of mortality and morbidity worldwide after myocardial infraction. Inspite of the years of research and clinical practice, the pathogenesis of stroke still remains incompletely understood. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The most significant development among all other omics technologies over the recent years has been seen by genomics which is a powerful tool for exploring the genetic architecture of stroke. Genomics has decisively established itself in stroke research and by now wealth of data has been generated providing new insights into the physiology and pathophysiology of stroke. However, the efficacy of genomic data is restricted to risk prediction only. Omics approaches not only enable the description of a huge number of molecular platforms but also have a potential to recognize new factors associated with various complex disorders including stroke. The data generated by omics technologies enables clinicians to provide detailed insight into the makeup of stroke in individual patients, which will further help in developing diagnostic procedures to direct therapies. Present review has been compiled with an aim to understand the potential of integrated omics approach to help in characterization of mechanisms leading to stroke, to predict the patient risk of getting stroke by analyzing signature biomarkers and to develop targeted therapeutic strategies.

Global metabolomics analysis of serum from humans at risk of thrombotic stroke

We aimed to determine the serum concentrations of altered compounds to understand the changes in metabolism and pathophysiology that occur prior to thrombotic stroke.

A Multi-Cohort Metabolomics Analysis Discloses Sphingomyelin (32:1) Levels to be Inversely Related to Incident Ischemic Stroke

BACKGROUND AND PURPOSE

To search for novel pathophysiological pathways related to ischemic stroke using a metabolomics approach.

METHODS

We identified 204 metabolites in plasma by liquid chromatography mass spectrometry in 3 independent population-based samples (TwinGene, Prospective Investigation of the Vasculature in Uppsala Seniors (PIVUS) and Uppsala Longitudinal Study of Adult Men). TwinGene was used for discovery and the other 2 samples were meta-analyzed as replication. In PIVUS, traditional cardiovascular (CV) risk factors, multiple markers of subclinical CV disease, markers of coagulation/fibrinolysis were measured and analyzed in relation to top metabolites.

RESULTS

In TwinGene (177 incident cases, median follow-up 4.3 years), levels of 28 metabolites were associated with incident ischemic stroke at a false discover rate (FDR) of 5%. In the replication (together 194 incident cases, follow-up 10 and 12 years, respectively), only sphingomyelin (32:1) was significantly associated (HR .69 per SD change, 95% CI .57-0.83, P value = .00014; FDR <5%) when adjusted for systolic blood pressure, diabetes, smoking, low density lipoportein (LDL)- and high density lipoprotein (HDL), body mass index (BMI) and atrial fibrillation. In PIVUS, sphingomyelin (32:1) levels were significantly related to both LDL- and HDL-cholesterol in a positive fashion, and to serum triglycerides, BMI and diabetes in a negative fashion. Furthermore, sphingomyelin (32:1) levels were related to vasodilation in the forearm resistance vessels, and inversely to leukocyte count (P < .0069 and .0026, respectively).

CONCLUSIONS

An inverse relationship between sphingomyelin (32:1) and incident ischemic stroke was identified, replicated, and characterized. A possible protective role for sphingomyelins in stroke development has to be further investigated in additional experimental and clinical studies.

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

INTRODUCTION

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

OBJECTIVES

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Discovery of a New Biomarker Pattern for Differential Diagnosis of Acute Ischemic Stroke Using Targeted Metabolomics

Stroke is one of the leading causes of disability all over the world. However, biomarkers for fast differential diagnosis of acute ischemic stroke (AIS) from vertigo or headache, remains lacking. Using a direct-infusion mass spectrometry method, it is possible to establish an efficient method for AIS differential diagnosis that requires only a few minutes. Thirty-eight clearly diagnosed AIS patients and 46 patients with a main complaint of vertigo were enrolled in this study. There was a total of 58 metabolites that were measured by our targeted metabolomics method, and the data were analyzed by pattern recognition algorithms. As a result, a clear classification between AIS and vertigo patients was achieved. Acylcarnitines are the major discriminating metabolites between the two groups. Arginine and its ratio, which is related to urea cycle metabolites, including arginine/ornithine and citrulline/arginine, also accounted for the classification. Interestingly, the levels of these metabolites were also found to be restored among recovering AIS patients (n = 11), which indicated that the metabolic alterations are possibly related to AIS development. Based on the characters from the data pattern reorganization, a novel biomarkers pattern was established using a binary logistic model, which contained arginine, arginine/ornithine, vaccenylcarnitine, and hydroxylbutyrylcarnitine. This biomarkers pattern achieved an area under the receiver operating characteristic curve of 0.89 for the differential diagnosis of AIS. Considering the efficiency and the diagnostic performance of the biomarkers pattern, our method has potential future use for the clinical application.

A Systems Vaccinology Approach Reveals the Mechanisms of Immunogenic Responses to Hantavax Vaccination in Humans

Hantavax is an inactivated vaccine for hemorrhagic fever with renal syndrome (HFRS). The immunogenic responses have not been elucidated yet. Here we conducted a cohort study in which 20 healthy subjects were administered four doses of Hantavax during 13-months period. Pre- and post- vaccinated peripheral blood mononuclear cells (PBMCs) and sera were analysed by transcriptomic and metabolomic profilings, respectively. Based on neutralizing antibody titers, subjects were subsequently classified into three groups; non responders (NRs), low responders (LRs) and high responders (HRs). Post vaccination differentially expressed genes (DEGs) associated with innate immunity and cytokine pathways were highly upregulated. DEG analysis revealed a significant induction of CD69 expression in the HRs. High resolution metabolomics (HRM) analysis showed that correlated to the antibody response, cholesteryl nitrolinoleate, octanoyl-carnitine, tyrosine, ubiquinone-9, and benzoate were significantly elevated in HRs, while chenodeoxycholic acid and methyl palmitate were upregulated in NRs and LRs, compared with HRs. Additionally, gene-metabolite interaction revealed upregulated gene-metabolite couplings in, folate biosynthesis, nicotinate and nicotinamide, arachidonic acid, thiamine and pyrimidine metabolism in a dose dependent manner in HR group. Collectively, our data provide new insight into the underlying mechanisms of the Hantavax-mediated immunogenicity in humans.

Biomarker for Ischemic Stroke Using Metabolome: A Clinician Perspective

Finding ischemic stroke biomarker is highly desirable because it can improve diagnosis even before a patient arrives to the hospital. Metabolome is one of new technologies that help to find biomarkers. Most metabolome-related ischemic stroke studies were done in Asia and had exploratory designs. Although failed to find specific biomarkers, they discovered several important metabolite-stroke associations which belong to three pathophysiological mechanisms: Excitotoxicity with activation of glutamate, resulting in the increase of glutamate derivatives proline and pyroglutamate; Oxidative stress with production of free radicals and perturbed concentrations of uric acid, matrix metalloproteinase-9, branch-chained amino acids, sphingolipids, homocysteine, asymmetric dimethylarginine, nitric oxide and folate cycle metabolites; and Stroke mediated inflammation, affecting phospholipid metabolism with perturbed levels of lysophosphatidylethanolamine and lysophosphatidylcholine. The discovered metabolite-stroke associations need further evaluation in prospective, high-quality studies with patients matched for age, risk factors, and medications.

Identification of potential biomarkers in cholestasis and the therapeutic effect of melatonin by metabolomics, multivariate data and pathway analyses

The present study investigated the anti‑cholestatic effect of melatonin (MT) against α‑naphthyl isothiocyanate (ANIT)‑induced liver injury in rats and screened for potential biomarkers of cholestasis. Rats were administered ANIT by intraperitoneal injection and then sacrificed 36 h later. Serum biochemical parameters were measured and liver tissue samples were subjected to histological analysis. Active components in the serum were identified by gas chromatography‑mass spectrometry, while biomarkers and biochemical pathways were identified by multivariate data analysis. The results revealed that the serum levels of alanine aminotransferase, aspartate aminotransferase, total bilirubin, direct bilirubin, γ‑glutamyl transpeptidase, and alkaline phosphatase were reduced in rats with ANIT‑induced cholestasis that were treated with MT. The histological observations indicated that MT had a protective effect against ANIT‑induced hepatic tissue damage. Metabolomics analysis revealed that this effect was likely to be associated with the regulation of compounds related to MT synthesis and catabolism, and amino acid metabolism, including 5‑aminopentanoate, 5‑methoxytryptamine, L‑tryptophan, threonine, glutathione, L‑methionine, and indolelactate. In addition, principal component analysis demonstrated that the levels of these metabolites differed significantly between the MT and control groups, providing further evidence that they may be responsible for the effects induced by MT. These results provide an insight into the mechanisms underlying cholestasis development and highlight potential biomarkers for disease diagnosis.

Elevated Metabolites of Steroidogenesis and Amino Acid Metabolism in Preadolescent Female Children With High Urinary Bisphenol A Levels: A High-Resolution Metabolomics Study

Health risks associated with bisphenol A (BPA) exposure are controversially highlighted by numerous studies. High-resolution metabolomics (HRM) can confirm these proposed associations and may provide a mechanistic insight into the connections between BPA exposure and metabolic perturbations. This study was aimed to identify the changes in metabolomics profile due to BPA exposure in urine and serum samples collected from female and male children (n = 18) aged 7-9. Urine was measured for BPA concentration, and the children were subsequently classified into high and low BPA groups. HRM, coupled with Liquid chromatography-mass spectrometry/MS, followed by multivariate statistical analysis using MetaboAnalyst 3.0, were performed on urine to discriminate metabolic profiles between high and low BPA children as well as males and females, followed by further validation of our findings in serum samples obtained from same population. Metabolic pathway analysis showed that biosynthesis of steroid hormones and 7 other pathways-amino acid and nucleotide biosynthesis, phenylalanine metabolism, tryptophan metabolism, tyrosine metabolism, lysine degradation, pyruvate metabolism, and arginine biosynthesis-were affected in high BPA children. Elevated levels of metabolites associated with these pathways in urine and serum were mainly observed in female children, while these changes were negligible in male children. Our results suggest that the steroidogenesis pathway and amino acid metabolism are the main targets of perturbation by BPA in preadolescent girls.

Metabolomics and Lipidomics of Ischemic Stroke

Ischemic stroke is a sudden loss of brain function due to the reduction of blood flow. Brain tissues cease to function with subsequent activation of the ischemic cascade. Metabolomics and lipidomics are modern disciplines that characterize the metabolites and lipid components of a biological system, respectively. Because the pathogenesis of ischemic stroke is heterogeneous and multifactorial, it is crucial to establish comprehensive metabolomic and lipidomic approaches to elucidate these alterations in this disease. Fortunately, metabolomic and lipidomic studies have the distinct advantages of identifying tissue/mechanism-specific biomarkers, predicting treatment and clinical outcome, and improving our understanding of the pathophysiologic basis of disease states. Therefore, recent applications of these analytical approaches in the early diagnosis of ischemic stroke were discussed. In addition, the emerging roles of metabolomics and lipidomics on ischemic stroke were summarized, in order to gain new insights into the mechanisms underlying ischemic stroke and in the search for novel metabolite biomarkers and their related pathways.

High-resolution metabolomics determines the mode of onset of type 2 diabetes in a 3-year prospective cohort study

Type 2 diabetes mellitus (DM) is a progressive disease and the rate of progression from non-diabetes to DM varies considerably between individuals, ranging from a few months to many years. It is important to understand the mechanisms underlying the progression of diabetes. In the present study, a high-resolution metabolomics (HRM) analysis was performed to detect potential biomarkers and pathways regulating the mode of onset by comparing subjects who developed and did not develop type 2 DM at the second year in a 3-year prospective cohort study. Metabolic profiles correlated with progression to DM were examined. The subjects (n=98) were classified into four groups: Control (did not develop DM for 3 years), DM (diagnosed with DM at the start of the study), DM onset at the third year and DM onset at the second year. The focus was on the comparison of serum samples of the DM groups with onset at the second and third year from the first year, where these two groups had not developed DM, yet. Analyses involved sample examination using liquid chromatography-mass spectrometry-based HRM and multivariate statistical analysis of the data. Metabolic differences were identified across all analyses with the affected pathways involved in metabolism associated with steroid biosynthesis and bile acid biosynthesis. In the first year, higher levels of cholesterol {mass-to charge ratio (m/z) 369.35, (M+H-H2O)+}, 25-hydroxycholesterol [m/z 403.36, (M+H)+], 3α,7α-dihydroxy-5β-cholestane [m/z 443.33, (M+K)+], 4α-methylzymosterol-4-carboxylate [m/z 425.34, (M+H‑H2O)+], and lower levels of 24,25-dihydrolanosterol [m/z 429.40, (M+H)+] were evident in the group with DM onset at the second year compared with those in the group with DM onset at the third year. These results, with a focus on the cholesterol biosynthesis pathway, point to important aspects in the development of DM and may aid in the development of more effective means of treatment and prevention.