Blood Metabolomic Predictors of 1-Year Outcome in Subarachnoid Hemorrhage

The Difference in Serum Metabolomic Profiles between the Good and Poor Outcome Groups at 3 Months in the Early and Late Phases of Aneurysmal Subarachnoid Hemorrhage

We aimed to investigate the characteristics of serum metabolomics in aneurysmal subarachnoid hemorrhage patients (aSAH) with different 3-month outcomes (good = modified Rankin score: 0-3 vs. poor = mRS 4-6). We collected serum samples from 46 aSAH patients at 24 (D1) and 168 (D7) hours after injury for analysis by liquid chromatography-mass spectrometry. Ninety-six different metabolites were identified. Groups were compared using multivariate (orthogonal partial least squares discriminant analysis), univariate, and receiving operator characteristic (ROC) methods. We observed a marked decrease in serum homocysteine levels at the late phase (D7) compared to the early phase (D1). At both D1 and D7, mannose and sorbose levels were notably higher, alongside elevated levels of kynurenine (D1) and increased 2-hydroxybutyrate, methyl-galactoside, creatine, xanthosine, p-hydroxyphenylacetate, N-acetylalanine, and N-acetylmethionine (all D7) in the poor outcome group. Conversely, levels of guanidinoacetate (D7) and several amino acids (both D1 and D7) were significantly lower in patients with poor outcomes. Our results indicate significant changes in energy metabolism, shifting towards ketosis and alternative energy sources, both in the early and late phases, even with adequate enteral nutrition, particularly in patients with poor outcomes. The early activation of the kynurenine pathway may also play a role in this process.

Metabolomic Analysis in Neurocritical Care Patients

Metabolomics is the analytical study of metabolites in biological matrices using high-throughput profiling. Traditionally, the metabolome has been studied to identify various biomarkers for the diagnosis and pathophysiology of disease. Over the last decade, metabolomic research has grown to include the identification of prognostic markers, the development of novel treatment strategies, and the prediction of disease severity. In this review, we summarized the available evidence on the use of metabolome profiling in neurocritical care populations. Specifically, we focused on aneurysmal subarachnoid hemorrhage, traumatic brain injury, and intracranial hemorrhage to identify the gaps in the current literature and to provide direction for future studies. A primary literature search of the Medline and EMBASE databases was conducted. Upon removing duplicate studies, abstract screening and full-text screening were performed. We screened 648 studies and extracted data from 17 studies. Based on the current evidence, the utility of metabolomic profiling has been limited due to inconsistencies amongst studies and a lack of reproducible data. Studies identified various biomarkers for diagnosis, prognosis, and treatment modification. However, studies evaluated and identified different metabolites, resulting in an inability to compare the study results. Future research towards addressing the gaps in the current literature, including reproducing data on the use of specific metabolite panels, is needed.

Serum Metabolomic Profiles in Critically Ill Patients with Shock on Admission to the Intensive Care Unit

Inflammatory processes are common in intensive care (ICU) patients and can induce multiple changes in metabolism, leading to increased risks of morbidity and mortality. Metabolomics enables these modifications to be studied and identifies a patient’s metabolic profile. The objective is to precise if the use of metabolomics at ICU admission can help in prognostication. This is a prospective ex-vivo study, realized in a university laboratory and a medico-surgical ICU. Metabolic profiles were analyzed by proton nuclear magnetic resonance. Using multivariable analysis, we compared metabolic profiles of volunteers and ICU patients divided into predefined subgroups: sepsis, septic shock, other shock and ICU controls. We also assessed possible correlations between metabolites and mortality. One hundred and eleven patients were included within 24 h of ICU admission, and 19 healthy volunteers. The ICU mortality rate was 15%. Metabolic profiles were different in ICU patients compared to healthy volunteers (p < 0.001). Among the ICU patients, only the subgroup of patients with septic shock had significant differences compared to the ICU control patients in several metabolites: pyruvate, lactate, carnitine, phenylalanine, urea, creatine, creatinine and myo-inositol. However, there was no correlation between these metabolite profiles and mortality. On the first day of ICU admission, we observed changes in some metabolic products in patients with septic shock, suggesting increased anaerobic glycolysis, proteolysis, lipolysis and gluconeogenesis. These changes were not correlated with prognosis.

Serum Levels of Myo-inositol Predicts Clinical Outcome 1 Year After Aneurysmal Subarachnoid Hemorrhage

BACKGROUND

Early prognostication of long-term outcome in patients suffering from spontaneous subarachnoid hemorrhage (SAH) remains a challenge. No biomarkers are routinely used for prognostication. A previous study has indicated that the metabolite myo-inositol (MI) may be used to predict long-term outcome.

OBJECTIVE

To investigate if MI measured in serum correlates with long-term clinical outcome in patients suffering from SAH.

METHODS

We conducted an observational cohort study including 88 patients treated for SAH at Umeå University Hospital. Serum samples were collected in the hospital, and a gas chromatography/mass spectroscopy method was used to quantitatively measure MI. Patients were assessed after 1 year using the Glasgow Outcome Scale Extended and dichotomized to favorable or unfavorable outcome. Differences in MI levels between the 2 groups were analyzed.

RESULTS

There was no difference in MI levels between the groups upon admission. Myo-inositol levels decreased over time in the entire study population. The decrease was significantly larger in the unfavorable outcome group. A receiver operating characteristics analysis yielded an area under the curve of 0.903 (CI 0.8-1.0, P < .001) for the MI value on day 7 to predict favorable outcome after 1 year.

CONCLUSION

Myo-inositol measured in serum may aid prognostication of outcome in patients with SAH. The mechanism behind this remains unclear, although it can be theorized to reflect processes leading to delayed cerebral ischemia, which affects long-term outcome. This is the first study to quantitively measure MI in serum for prognostication of outcome in patients with SAH.

Using Cerebral Metabolites to Guide Precision Medicine for Subarachnoid Hemorrhage: Lactate and Pyruvate

Subarachnoid hemorrhage (SAH) is one of the deadliest types of strokes with high rates of morbidity and permanent injury. Fluctuations in the levels of cerebral metabolites following SAH can be indicators of brain injury severity. Specifically, the changes in the levels of key metabolites involved in cellular metabolism, lactate and pyruvate, can be used as a biomarker for patient prognosis and tailor treatment to an individual’s needs. Here, clinical research is reviewed on the usefulness of cerebral lactate and pyruvate measurements as a predictive tool for SAH outcomes and their potential to guide a precision medicine approach to treatment.

Pharmacometabonomics: The Prediction of Drug Effects Using Metabolic Profiling

Metabonomics, also known as metabolomics, is concerned with the study of metabolite profiles in humans, animals, plants and other systems in order to assess their health or other status and their responses to experimental interventions. Metabonomics is thus widely used in disease diagnosis and in understanding responses to therapies such as drug administration. Pharmacometabonomics, also known as pharmacometabolomics, is a related methodology but with a prognostic as opposed to diagnostic thrust. Pharmacometabonomics aims to predict drug effects including efficacy, safety, metabolism and pharmacokinetics, prior to drug administration, via an analysis of pre-dose metabolite profiles. This article will review the development of pharmacometabonomics as a new field of science that has much promise in helping to deliver more effective personalised medicine, a major goal of twenty-first century healthcare.

Cerebrospinal fluid untargeted metabolomic profiling of aneurysmal subarachnoid hemorrhage: an exploratory study

INTRODUCTION

Despite advancements in medical and surgical therapies, clinical outcomes of aneurysmal subarachnoid hemorrhage (aSAH) continue to be poor. Currently, aSAH pathophysiology remains poorly understood. No aSAH biomarkers are commonly used in the clinical setting. This exploratory study used metabolomics profiling to identify global metabolic changes and metabolite predictors of long-term outcome using cerebrospinal fluid (CSF) samples of aSAH patients.

METHODS AND METHODS

Gas chromatography time-of-flight mass spectrometry was applied to CSF samples collected from 15 consecutive high-grade aSAH patients (modified Fisher grade 3 or 4). Collected CSF samples were analyzed at two time points (admission and the anticipated vasospasm timeframe). Metabolite levels at both time points were compared and correlated with vasospasm status and Glasgow Outcome Scale (GOS) of patients at 1 year post-aSAH. Significance level was defined as p < 0.05 with false discovery rate correction for multiple comparisons.

RESULTS

Of 97 metabolites identified, 16 metabolites, primarily free amino acids, significantly changed between the two time points. These changes were magnified in modified Fisher grade 4 compared with grade 3. Six metabolites (2-hydroxyglutarate, tryptophan, glycine, proline, isoleucine, and alanine) correlated with GOS at 1 year post-aSAH independent of vasospasm status. When predicting patients who had low disability (GOS 5 vs. GOS ≤4), 2-hydroxyglutarate had a sensitivity and specificity of 0.89 and 0.83 respectively.

CONCLUSIONS

Our preliminary study suggests that specific metabolite changes occur in the brain during the course of aSAH and that quantification of specific CSF metabolites may be used to predict long-term outcome in patients with aSAH. This is the first study to implicate 2-hydroxyglutarate, a known marker of tissue hypoxia, in aSAH pathogenesis.

From Metabonomics to Pharmacometabonomics: The Role of Metabolic Profiling in Personalized Medicine

Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments.