The combination of four analytical methods to explore skeletal muscle metabolomics: Better coverage of metabolic pathways or a marketing argument?

OBJECTIVES: Metabolomics is an emerging science based on diverse high throughput methods that are rapidly evolving to improve metabolic coverage of biological fluids and tissues. Technical progress has led researchers to combine several analytical methods without reporting the impact on metabolic coverage of such a strategy. The objective of our study was to develop and validate several analytical techniques (mass spectrometry coupled to gas or liquid chromatography and nuclear magnetic resonance) for the metabolomic analysis of small muscle samples and evaluate the impact of combining methods for more exhaustive metabolite covering. DESIGN AND METHODS: We evaluated the muscle metabolome from the same pool of mouse muscle samples after 2 metabolite extraction protocols. Four analytical methods were used: targeted flow injection analysis coupled with mass spectrometry (FIA-MS/MS), gas chromatography coupled with mass spectrometry (GC-MS), liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS), and nuclear magnetic resonance (NMR) analysis. We evaluated the global variability of each compound i.e., analytical (from quality controls) and extraction variability (from muscle extracts). We determined the best extraction method and we reported the common and distinct metabolites identified based on the number and identity of the compounds detected with low analytical variability (variation coefficient<30%) for each method. Finally, we assessed the coverage of muscle metabolic pathways obtained. RESULTS: Methanol/chloroform/water and water/methanol were the best extraction solvent for muscle metabolome analysis by NMR and MS, respectively. We identified 38 metabolites by nuclear magnetic resonance, 37 by FIA-MS/MS, 18 by GC-MS, and 80 by LC-HRMS. The combination led us to identify a total of 132 metabolites with low variability partitioned into 58 metabolic pathways, such as amino acid, nitrogen, purine, and pyrimidine metabolism, and the citric acid cycle. This combination also showed that the contribution of GC-MS was low when used in combination with other mass spectrometry methods and nuclear magnetic resonance to explore muscle samples. CONCLUSION: This study reports the validation of several analytical methods, based on nuclear magnetic resonance and several mass spectrometry methods, to explore the muscle metabolome from a small amount of tissue, comparable to that obtained during a clinical trial. The combination of several techniques may be relevant for the exploration of muscle metabolism, with acceptable analytical variability and overlap between methods However, the difficult and time-consuming data pre-processing, processing, and statistical analysis steps do not justify systematically combining analytical methods.

Lipidomics Reveals Cerebrospinal-Fluid Signatures of ALS.

Amyotrophic lateral sclerosis (ALS), the commonest adult-onset motor neuron disorder, is characterized by a survival span of only 2-5 years after onset. Relevant biomarkers or specific metabolic signatures would provide powerful tools for the management of ALS. The main objective of this study was to investigate the cerebrospinal fluid (CSF) lipidomic signature of ALS patients by mass spectrometry to evaluate the diagnostic and predictive values of the profile. We showed that ALS patients (n = 40) displayed a highly significant specific CSF lipidomic signature compared to controls (n = 45). Phosphatidylcholine PC(36:4), higher in ALS patients (p = 0.0003) was the most discriminant molecule, and ceramides and glucosylceramides were also highly relevant. Analysis of targeted lipids in the brain cortex of ALS model mice confirmed the role of some discriminant lipids such as PC. We also obtained good models for predicting the variation of the ALSFRS-r score from the lipidome baseline, with an accuracy of 71% in an independent set of patients. Significant predictions of clinical evolution were found to be correlated to sphingomyelins and triglycerides with long-chain fatty acids. Our study, which shows extensive lipid remodelling in the CSF of ALS patients, provides a new metabolic signature of the disease and its evolution with good predictive performance.

Low IDL-B and high LDL-1 subfraction levels in serum of ALS patients.

INTRODUCTION: Converging evidence highlights that lipid metabolism plays a key role in ALS pathophysiology. Dyslipidemia has been described in ALS patients and may be protective but peripheral lipoprotein subclasses have never been studied. MATERIAL AND METHODS: We collected sera from 30 ALS patients and 30 gender and age-matched controls. We analyzed 11 distinct lipoprotein subclasses by linear polyacrylamide gel electrophoresis (Lipoprint, Quantimetrix Corporation, USA). We also measured lipoprotein (a), apolipoprotein B, and apolipoprotein E levels. RESULTS: ALS patients had significant higher total cholesterol, HDL-cholesterol, and LDL-cholesterol levels than controls (p<0.0001, p=0.0007, and p=0.0065, respectively). The LDL-1 subfraction concentration was higher (1.03±0.41 vs. 0.71±0.28mmol/L; p=0.0006) and the IDL-B subfraction lower (6.5±2% vs. 8.0±2%; p=0.001) in ALS patients than controls. DISCUSSION: Our preliminary work confirmed the association between ALS and dyslipidemia. The low IDL-B levels may explain the hepatic steatosis frequently reported in ALS. The high levels of the cholesterol-rich LDL-1 subfraction is consistent with previously reported hypercholesterolemia. CONCLUSION: This study describes, for the first time, the distribution of serum lipoproteins in ALS patients, with low IDL-B and high LDL-1 subfraction level.

A decrease in blood cholesterol after gastrostomy could impact survival in ALS.

Although the global benefits of gastrostomy have been proven in amyotrophic lateral sclerosis (ALS), the impact on biological parameters has not been explored yet. The aim of this preliminary work was to evaluate the modification of biological parameters in patients with ALS undergoing gastrostomy. We retrospectively collected clinical and biological data from 44 patients having undergone gastrostomy at three time points (T0, T1 and T2: before, at the time of and after gastrostomy). We examined the relationship between the biological parameters and disease progression. Variations of the concentrations of total cholesterol significantly differed before (T1-T0) vs those after gastrostomy (T2-T1; P=0.0044). The variations of total cholesterol and low-density lipoprotein cholesterol concentrations after gastrostomy were negatively associated with survival (P=0.0002). This study showed for the first time that patients with ALS fed quite exclusively by gastrostomy had decreased blood cholesterol after gastrostomy. We suggest that a restoration of normal lipid metabolism should be planned in patients with ALS.

A Multiplatform Metabolomics Approach to Characterize Plasma Levels of Phenylalanine and Tyrosine in Phenylketonuria.

BACKGROUND: Different pathophysiological mechanisms have been described in phenylketonuria (PKU) but the indirect metabolic consequences of metabolic disorders caused by elevated Phe or low Tyr concentrations remain partially unknown. We used a multiplatform metabolomics approach to evaluate the metabolic signature associated with Phe and Tyr. MATERIAL AND METHODS: We prospectively included 10 PKU adult patients and matched controls. We analysed the metabolome profile using GC-MS (urine), amino-acid analyzer (urine and plasma) and nuclear magnetic resonance spectroscopy (urine). We performed a multivariate analysis from the metabolome (after exclusion of Phe, Tyr and directly derived metabolites) to explain plasma Phe and Tyr concentrations, and the clinical status. Finally, we performed a univariate analysis of the most discriminant metabolites and we identified the associated metabolic pathways. RESULTS: We obtained a metabolic pattern from 118 metabolites and we built excellent multivariate models to explain Phe, Tyr concentrations and PKU diagnosis. Common metabolites of these models were identified: Gln, Arg, succinate and alpha aminobutyric acid. Univariate analysis showed an inverse correlation between Arg, alpha aminobutyric acid and Phe and a positive correlation between Arg, succinate, Gln and Tyr (p < 0.0003). Thus, we highlighted the following pathways: Arg and Pro, Ala, Asp and Glu metabolism. DISCUSSION: We obtain a specific metabolic signature related to Tyr and Phe concentrations. We confirmed the involvement of different pathophysiological mechanisms previously described in PKU such as protein synthesis, energetic metabolism and oxidative stress. The metabolomics approach is relevant to explore PKU pathogenesis.

Validation of amino-acids measurement in dried blood spot by FIA-MS/MS for PKU management.

OBJECTIVES: Phenylketonuria (PKU) is a metabolic disorder leading to high concentrations of phenylalanine (Phe) and low concentrations of tyrosine (Tyr) in blood and brain that may be neurotoxic. This disease requires a regular monitoring of plasma Phe and Tyr as well as branched-chain amino-acids concentrations to adapt the Phe-restricted diet and other therapy that may be prescribed in PKU. We validated a Flow Injection Analysis tandem Mass Spectrometry (FIA-MS/MS) to replace the enzymatic method routinely used for neonatal screening in order to monitor in parallel to Phe, Tyr and branched-chain amino-acids not detected by the enzymatic method. DESIGN AND METHODS: We ascertained the performances of the method: linearity, detection and quantification limits, contamination index, accuracy. We cross validated the FIA-MS/MS and enzymatic methods and we evaluated our own reference ranges to monitor Phe, Tyr, Leu, Val on 59 dried blood spots of normal controls. We also evaluated Tyr, Leu and Val concentrations in PKU patients to detect some potential abnormalities, not evaluated by the enzymatic method. RESULTS: We developed a rapid method with excellent performances including precision and accuracy <15%. We noted an excellent correlation of Phe concentrations between FIA-MS/MS and enzymatic methods (p<0.0001) based on our database which are similar to references ranges published. We observed that 50% of PKU patients had lower concentrations of Tyr, Leu and/or Val that could not be detected by the enzymatic method. CONCLUSION: Based on laboratory accreditation recommendations, we validated a robust, rapid and reliable FIA-MS/MS method to monitor plasma Phe concentrations but also Tyr, Leu and Val concentrations, suitable for PKU management. We evaluated our own reference ranges of concentration for a routine application of this method.

Amyotrophic Lateral Sclerosis, 2016: existing therapies and the ongoing search for neuroprotection.

INTRODUCTION: Amyotrophic lateral sclerosis (ALS), one in a family of age-related neurodegenerative disorders, is marked by predominantly cryptogenic causes, partially elucidated pathophysiology, and elusive treatments. The challenges of ALS are illustrated by two decades of negative drug trials. AREAS COVERED: In this article, we lay out the current understanding of disease genesis and physiology in relation to drug development in ALS, stressing important accomplishments and gaps in knowledge. We briefly consider clinical ALS, the ongoing search for biomarkers, and the latest in trial design, highlighting major recent and ongoing clinical trials; and we discuss, in a concluding section on future directions, the prion-protein hypothesis of neurodegeneration and what steps can be taken to end the drought that has characterized drug discovery in ALS. EXPERT OPINION: Age-related neurodegenerative disorders are fast becoming major public health problems for the world's aging populations. Several agents offer promise in the near-term, but drug development is hampered by an interrelated cycle of obstacles surrounding etiological, physiological, and biomarkers discovery. It is time for the type of government-funded, public-supported offensive on neurodegenerative disease that has been effective in other fields.

Metabolomics in amyotrophic lateral sclerosis: how far can it take us?

Amyotrophic lateral sclerosis (ALS) is the most common adult-onset motor neuron disease. Alongside identification of aetiologies, development of biomarkers is a foremost research priority. Metabolomics is one promising approach that is being utilized in the search for diagnosis and prognosis markers. Our aim is to provide an overview of the principal research in metabolomics applied to ALS. References were identified using PubMed with the terms 'metabolomics' or 'metabolomic' and 'ALS' or 'amyotrophic lateral sclerosis' or 'MND' or 'motor neuron disorders'. To date, nine articles have reported metabolomics research in patients and a few additional studies examined disease physiology and drug effects in patients or models. Metabolomics contribute to a better understanding of ALS pathophysiology but, to date, no biomarker has been validated for diagnosis, principally due to the heterogeneity of the disease and the absence of applied standardized methodology for biomarker discovery. A consensus on best metabolomics methodology as well as systematic independent validation will be an important accomplishment on the path to identifying the long-awaited biomarkers for ALS and to improve clinical trial designs.

Biomarkers in amyotrophic lateral sclerosis: combining metabolomic and clinical parameters to define disease progression.

BACKGROUND AND PURPOSE: The objectives of this study were to define the metabolomic profile of cerebrospinal fluid in amyotrophic lateral sclerosis (ALS) patients, to model outcome through combined clinical and metabolomic parameters and independently to validate predictive models. METHODS: In all, 74 consecutive newly diagnosed patients were enrolled into training (Tr, n = 49) and test (Te, n = 25) cohorts. Investigators recorded clinical data and the metabalomic profile of cerebrospinal fluid at baseline was analyzed with (1)H nuclear magnetic resonance spectroscopy. Markers of disease progression, collected in 1-year prospective follow-up, included change in ALS Functional Rating Scale (var_ALSFRS), change in weight (var_weight) and survival time. Stepwise multiple regression selected from metabolomic and clinical parameters to model rate of progression in the Tr cohort. Best fit models were validated independently in the Te cohort. RESULTS: The best-fit statistical models, using both metabolomic and clinical covariates, predicted outcome with 70.8% (var_weight), 72% (var_ALSFRS) and 76% (survival) accuracy in the Te cohort. Models that used metabolomics or clinical data alone predicted outcome less well. Highlighted metabolites are involved in pathophysiological pathways previously described in ALS. CONCLUSION: Cerebrospinal fluid metabolomics can aid in predicting the clinical course of ALS and tap into pathophysiological processes. The precision of predictive models, independently reproduced in this study, is enhanced through inclusion of both metabolomic and clinical parameters. The findings bring the field closer to a clinically meaningful disease marker.

Biological follow-up in amyotrophic lateral sclerosis: decrease in creatinine levels and increase in ferritin levels predict poor prognosis.

BACKGROUND AND PURPOSE: Amyotrophic lateral sclerosis (ALS) is a fatal disorder of the motor neuron system, with a median survival of 2 to 4 years and a wide variety of prognosis. Thus, there is a critical need for diagnosis and prognosis biomarkers to improve the care of patients in routine practice. In this study, we aimed to determine prognostic value of routine biochemical markers in sporadic ALS (SALS). METHODS: We retrospectively collected clinical and biological data obtained during the systematic routine monitoring of 216 sporadic ALS patients. The main outcomes were disease duration and annual decline of Revised ALS Functional Rating Scale (ALSFRS-R). Changes to these biological variables over time were assessed, in link with disease progression. RESULTS: We found that concentrations of creatinine (P=0.0166) and ferritin (P=0.0306) changed significantly during the progression of ALS. A reduction of creatinine levels and an increase of ferritin levels were associated with disease progression. Multivariate analysis showed that early variation of ferritin was an independent predictive factor of patient survival (P=0.0048). CONCLUSION: Changes to ferritin and creatinine levels with time are associated with ALS progression. This is the first study describing the changes to these biological variables during ALS progression.