GABA/Glutamate synaptic pathways targeted by integrative genomic and electrophysiological explorations distinguish autism from intellectual disability.

Phenotypic and genetic heterogeneity is predominant in autism spectrum disorders (ASD), for which the molecular and pathophysiological bases are still unclear. Significant comorbidity and genetic overlap between ASD and other neurodevelopmental disorders are also well established. However, little is understood regarding the frequent observation of a wide phenotypic spectrum associated with deleterious mutations affecting a single gene even within multiplex families. We performed a clinical, neurophysiological (in vivo electroencephalography-auditory-evoked related potentials) and genetic (whole-exome sequencing) follow-up analysis of two families with known deleterious NLGN4X gene mutations (either truncating or overexpressing) present in individuals with ASD and/or with intellectual disability (ID). Complete phenotypic evaluation of the pedigrees in the ASD individuals showed common specific autistic behavioural features and neurophysiological patterns (abnormal MisMatch Negativity in response to auditory change) that were absent in healthy parents as well as in family members with isolated ID. Whole-exome sequencing in ASD patients from each family identified a second rare inherited genetic variant, affecting either the GLRB or the ANK3 genes encoding NLGN4X interacting proteins expressed in inhibitory or in excitatory synapses, respectively. The GRLB and ANK3 mutations were absent in relatives with ID as well as in control databases. In summary, our findings provide evidence of a double-hit genetic model focused on excitatory/inhibitory synapses in ASD, that is not found in isolated ID, associated with an atypical in vivo neurophysiological pattern linked to predictive coding.

Genetics of amyotrophic lateral sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal motor neuron disease characterized by upper and lower motor neuron damage in the bulbar and spinal territories. Although the pathophysiology of ALS is still unknown, the involvement of genetic factors is no longer a subject of debate. Familial ALS (fALS) accounts for 10-20% of cases. Since the identification of the SOD1 gene, more than 20 genes have been described, of which four can explain >50% of familial cases. This review is an update focused on major aspects of the field of ALS genetics concerning both causative and susceptibility factors.

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.

Comparative analysis of targeted metabolomics: dominance-based rough set approach versus orthogonal partial least square-discriminant analysis.

BACKGROUND: Metabolomics is an emerging field that includes ascertaining a metabolic profile from a combination of small molecules, and which has health applications. Metabolomic methods are currently applied to discover diagnostic biomarkers and to identify pathophysiological pathways involved in pathology. However, metabolomic data are complex and are usually analyzed by statistical methods. Although the methods have been widely described, most have not been either standardized or validated. Data analysis is the foundation of a robust methodology, so new mathematical methods need to be developed to assess and complement current methods. We therefore applied, for the first time, the dominance-based rough set approach (DRSA) to metabolomics data; we also assessed the complementarity of this method with standard statistical methods. Some attributes were transformed in a way allowing us to discover global and local monotonic relationships between condition and decision attributes. We used previously published metabolomics data (18 variables) for amyotrophic lateral sclerosis (ALS) and non-ALS patients. RESULTS: Principal Component Analysis (PCA) and Orthogonal Partial Least Square-Discriminant Analysis (OPLS-DA) allowed satisfactory discrimination (72.7%) between ALS and non-ALS patients. Some discriminant metabolites were identified: acetate, acetone, pyruvate and glutamine. The concentrations of acetate and pyruvate were also identified by univariate analysis as significantly different between ALS and non-ALS patients. DRSA correctly classified 68.7% of the cases and established rules involving some of the metabolites highlighted by OPLS-DA (acetate and acetone). Some rules identified potential biomarkers not revealed by OPLS-DA (beta-hydroxybutyrate). We also found a large number of common discriminating metabolites after Bayesian confirmation measures, particularly acetate, pyruvate, acetone and ascorbate, consistent with the pathophysiological pathways involved in ALS. CONCLUSION: DRSA provides a complementary method for improving the predictive performance of the multivariate data analysis usually used in metabolomics. This method could help in the identification of metabolites involved in disease pathogenesis. Interestingly, these different strategies mostly identified the same metabolites as being discriminant. The selection of strong decision rules with high value of Bayesian confirmation provides useful information about relevant condition-decision relationships not otherwise revealed in metabolomics data.

APOE ε4 allele is associated with an increased risk of bulbar-onset amyotrophic lateral sclerosis in men.

OBJECTIVE: Several association studies have identified possible susceptibility factors for sporadic amyotrophic lateral sclerosis (SALS). Studies on the APOE gene provided conflicting results, especially about the effect on bulbar onset. We assessed the possible role of APOE gene in a large cohort of patients with ALS and matched controls. METHODS: The APOE alleles were determined in 1482 patients with SALS and 955 controls and analysed by univariate and multivariate statistics, taking into account gender, site-of-onset and age-at-onset. RESULTS: Patients with bulbar onset were more likely to be women [odds ratio (OR)=2.17; 95% CI: 1.74-2.72] and to be older (OR=3.47; 95% CI: 2.58-4.67). The ε4-carriers were more frequent in the bulbar-onset group than in the limb-onset group (OR=1.39 bulbar onset versus limb onset; 95% CI: 1.08-1.80) but this association was observed amongst men (OR=1.78; 95% CI: 1.25-2.53) and not women (OR=1.09; 95% CI: 0.75-1.59). CONCLUSION: Our study provides evidence for a contribution of the ε4 allele in the occurrence of bulbar-onset ALS amongst men. We propose that men are normally protected by androgens against bulbar onset and that the ε4 allele inhibits this protection, perhaps by interfering with the androgen pathway.

Validation of plasma amino acid profile using UHPLC-mass spectrometer (QDa) as a screening method in a metabolic disorders reference centre: Performance and accreditation concerns.

INTRODUCTION: Amino acid (AA) analysis in plasma is essential for diagnosis and monitoring of inborn errors of metabolism (IEM). The efficacy of patient management is governed by the rapidity of AA profile availability, along with the robustness of the method. French quality guidelines and progress made in analytical techniques have led biologists to develop AA profile exploration via mass spectrometry (MS). OBJECTIVES: The aim of this study was to validate an analytical method with a single quadrupole mass spectrometer (MS) and to suggest reference values in regard to French quality and IEM society recommendations. DESIGN AND METHODS: Plasma samples from patients were deproteinised and derivatised with AccqTag™ reagent. Analysis was performed by reverse-phase chromatography coupled to QDA detector. We evaluated accuracy, intra-days and inter-days precision and limit of quantification by the ß-expectation tolerance interval method for 27 AA. Method comparison was performed with the standard method (ion exchange chromatography, IEC) on Jeol Aminotac® and to tandem MS. Reference values were established on AA concentrations of the cohort of patients who had no IEM. RESULTS: Our method allowed the separations of almost all amino acids with a total run time of 12 min. Separation of isoleucine and alloisoleucine was incomplete (R = 0.55) but without impact on biological interpretation. Precision, accuracy and quantification were satisfactory (intra-days coefficient of variation (CV) was <5%, inter-days precision CV <10% and accuracy <15%). The limits of quantification were validated between 1 and 900 µmol/L. Results were comparable between the new method and IEC. CONCLUSION: Ultimately, we validated a rapid method on plasma for quantifying 27 amino acids that can be used in routine practice, according to French quality laboratories and SFEIM (French Society of Inborn Error of Metabolism) recommendations. Furthermore, estimated reference values were similar to those found in published studies focusing on other methods. Despite a lower specificity compared to tandem MS, the simplicity and rapidity of our method are the main advantage of this technique and place it as a major tool in IEM diagnosis and management.

Behavioral, Hormonal, Inflammatory, and Metabolic Effects Associated with FGF21-Pathway Activation in an ALS Mouse Model.

In amyotrophic lateral sclerosis (ALS), motor neuron degeneration occurs simultaneously with systemic metabolic dysfunction and neuro-inflammation. The fibroblast growth factor 21 (FGF21) plays an important role in the regulation of both phenomena and is a major hormone of energetic homeostasis. In this study, we aimed to determine the relevance of FGF21 pathway stimulation in a male mouse model of ALS (mutated SOD1-G93A mice) by using a pharmacological agonist of FGF21, R1Mab1. Mice (SOD1-WT and mutant SOD1-G93A) were treated with R1Mab1 or vehicle. Longitudinal data about clinical status (motor function, body weight) and biological parameters (including hormonal, immunological, and metabolomics profiles) were collected from the first symptoms to euthanasia at week 20. Multivariate models were performed to identify the main parameters associated with R1Mab1 treatment and to link them with clinical status, and metabolic pathways involving the discriminant metabolites were also determined. A beneficial clinical effect of R1Mab1 was revealed on slow rotarod (p = 0.032), despite a significant decrease in body weight of ALS mice (p < 0.001). We observed a decrease in serum TNF-α, MCP-1, and insulin levels (p = 0.0059, p = 0.003, and p = 0.01, respectively). At 16 weeks, metabolomics analyses revealed a clear discrimination (CV-ANOVA = 0.0086) according to the treatment and the most discriminant pathways, including sphingolipid metabolism, butanoate metabolism, pantothenate and CoA biosynthesis, and the metabolism of amino acids like tyrosine, arginine, proline, glycine, serine, alanine, aspartate, and glutamate. Mice treated with R1Mab1 had mildly higher performance on slow rotarod despite a decrease on body weight and could be linked with the anti-inflammatory effect of R1Mab1. These results indicate that FGF21 pathway is an interesting target in ALS, with a slight improvement in motor function combined with metabolic and anti-inflammatory effects.

ABCB4 gene mutations and single-nucleotide polymorphisms in women with intrahepatic cholestasis of pregnancy.

AIM: To evaluate the nature and frequency of ATP-binding cassette subfamily B member 4 (ABCB4) gene variants in a series of French patients with intrahepatic cholestasis of pregnancy (ICP). METHODS: In this prospective study, the entire ABCB4 gene coding sequence was analysed by DNA sequencing in 50 unrelated women with ICP defined by pruritus and raised serum alanine aminotransferase activity or bile acid concentration, with recovery after delivery. Genomic variants detected in patients with ICP were sought in 107 control pregnant women. Patients with ICP and controls were of Caucasian origin. RESULTS: Eight genomic variants were observed. One nonsense mutation (p.Arg144Stop) and two missense mutations (p.Ser320Phe and p.Thr775Met) were revealed each in one heterozygous patient. A third missense mutation (p.Arg590Gln) was detected in three heterozygous patients and in two homozygous patients also homozygous for a particular haplotype of three single-nucleotide polymorphisms (c.175C>T, c.504T>C, c.711A>T). The chromosomal frequency of the p.Arg590Gln variant was significantly different between the ICP and control group (7.0% vs 0.5%; p = 0.0017; OR 16.03, 95% CI 1.94 to 132.16). An association was also found between allele T of the c.504T>C silent nucleotide polymorphism and ICP (68.0% vs 53.7%; p = 0.017; OR 1.83, 95% CI 1.08 to 3.11). The chromosomal frequency of the p.Arg652Gly variant did not differ between the ICP and control group (p = 0.40). CONCLUSIONS: This study shows that 16% of Caucasian patients with ICP bear ABCB4 gene mutations, and confirms the significant involvement of this gene in the pathogenesis of this complex disorder.

The specific metabolome profiling of patients infected by SARS-COV-2 supports the key role of tryptophan-nicotinamide pathway and cytosine metabolism.

The biological mechanisms involved in SARS-CoV-2 infection are only partially understood. Thus we explored the plasma metabolome of patients infected with SARS-CoV-2 to search for diagnostic and/or prognostic biomarkers and to improve the knowledge of metabolic disturbance in this infection. We analyzed the plasma metabolome of 55 patients infected with SARS-CoV-2 and 45 controls by LC-HRMS at the time of viral diagnosis (D0). We first evaluated the ability to predict the diagnosis from the metabotype at D0 in an independent population. Next, we assessed the feasibility of predicting the disease evolution at the 7th and 15th day. Plasma metabolome allowed us to generate a discriminant multivariate model to predict the diagnosis of SARS-CoV-2 in an independent population (accuracy > 74%, sensitivity, specificity > 75%). We identified the role of the cytosine and tryptophan-nicotinamide pathways in this discrimination. However, metabolomic exploration modestly explained the disease evolution. Here, we present the first metabolomic study in SARS-CoV-2 patients which showed a high reliable prediction of early diagnosis. We have highlighted the role of the tryptophan-nicotinamide pathway clearly linked to inflammatory signals and microbiota, and the involvement of cytosine, previously described as a coordinator of cell metabolism in SARS-CoV-2. These findings could open new therapeutic perspectives as indirect targets.

Typical bulbar ALS can be linked to GARS mutation.

Background: Amyotrophic lateral sclerosis is the most frequent motor neuron disorders (MND) in adults. The role of genetic factors is worldwide accepted, and currently, more than 30 genes have been linked to this disease. Genetics was also the matter of numerous studies in distal hereditary motor neuropathies (dHMN). GARS is classically linked to a predominant dHMN and, until now, no mutation has been described in GARS in other MND. Case Report: We report the case of a 70-year-old woman who developed a classical bulbar ALS phenotype. Owing to his familial history of ALS, a genetic screening was performed excluding the main genes linked to ALS and revealing a heterozygous missense mutation in GARS gene with a high probability of pathogenicity. Conclusion: This first description of mutation in GARS in ALS, extends once more the genetic overlap between ALS and other MND.

Causative Genes in Amyotrophic Lateral Sclerosis and Protein Degradation Pathways: a Link to Neurodegeneration.

Amyotrophic lateral sclerosis (ALS) is a disease caused by the degeneration of motor neurons (MNs) leading to progressive muscle weakness and atrophy. Several molecular pathways have been implicated, such as glutamate-mediated excitotoxicity, defects in cytoskeletal dynamics and axonal transport, disruption of RNA metabolism, and impairments in proteostasis. ALS is associated with protein accumulation in the cytoplasm of cells undergoing neurodegeneration, which is a hallmark of the disease. In this review, we focus on mechanisms of proteostasis, particularly protein degradation, and discuss how they are related to the genetics of ALS. Indeed, the genetic bases of the disease with the implication of more than 30 genes associated with familial ALS to date, together with the important increase in understanding of endoplasmic reticulum (ER) stress, proteasomal degradation, and autophagy, allow researchers to better understand the mechanisms underlying the selective death of motor neurons in ALS. It is clear that defects in proteostasis are involved in this type of cellular degeneration, but whether or not these mechanisms are primary causes or merely consequential remains to be clearly demonstrated. Novel cellular and animal models allowing chronic expression of mutant proteins, for example, are required. Further studies linking genetic discoveries in ALS to mechanisms of protein clearance will certainly be crucial in order to accelerate translational and clinical research towards new therapeutic targets and strategies.

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.

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.

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.

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.

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.

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.