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A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression
by
Patin, Franck
, Garçon, Guillaume
, Bede, Peter
, Blasco, Hélène
, Pradat, Pierre-François
, Meininger, Vincent
, Devos, David
, Corcia, Philippe
, Gossens, Jean François
, Lenglet, Timothée
, Gelé, Patrick
, Descat, Amandine
in
Adult
/ Aged
/ Amino acids
/ Amyotrophic lateral sclerosis
/ Amyotrophic Lateral Sclerosis - diagnosis
/ Amyotrophic Lateral Sclerosis - drug therapy
/ Amyotrophic Lateral Sclerosis - metabolism
/ Amyotrophic Lateral Sclerosis - pathology
/ Analysis
/ Arginine
/ Bioindicators
/ Biological effects
/ Biological markers
/ Biology and Life Sciences
/ Biomarkers
/ Biomarkers, Pharmacological - analysis
/ Biomarkers, Pharmacological - metabolism
/ Cholestenones - therapeutic use
/ Chromatography
/ Citrulline
/ Clinical trials
/ Computer and Information Sciences
/ Development and progression
/ Disease
/ Disease Progression
/ Double-Blind Method
/ Drug Resistance - drug effects
/ Female
/ Glutamine
/ Glycine
/ High performance liquid chromatography
/ Humans
/ Learning algorithms
/ Life Sciences
/ Lipids
/ Liquid chromatography
/ Machine learning
/ Male
/ Mass spectrometry
/ Mass spectroscopy
/ Medical prognosis
/ Medical research
/ Medication
/ Medicine and Health Sciences
/ Metabolism
/ Metabolites
/ Metabolome - drug effects
/ Metabolomics
/ Metabolomics - methods
/ Middle Aged
/ Multivariate analysis
/ Neurobiology
/ Neurons
/ Neurons and Cognition
/ Pathogenesis
/ Patient outcomes
/ Patients
/ Pharmaceutical sciences
/ Pharmacology
/ Physical Sciences
/ Placebos
/ Prognosis
/ Research and Analysis Methods
/ Spermidine
/ Test sets
2018
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A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression
by
Patin, Franck
, Garçon, Guillaume
, Bede, Peter
, Blasco, Hélène
, Pradat, Pierre-François
, Meininger, Vincent
, Devos, David
, Corcia, Philippe
, Gossens, Jean François
, Lenglet, Timothée
, Gelé, Patrick
, Descat, Amandine
in
Adult
/ Aged
/ Amino acids
/ Amyotrophic lateral sclerosis
/ Amyotrophic Lateral Sclerosis - diagnosis
/ Amyotrophic Lateral Sclerosis - drug therapy
/ Amyotrophic Lateral Sclerosis - metabolism
/ Amyotrophic Lateral Sclerosis - pathology
/ Analysis
/ Arginine
/ Bioindicators
/ Biological effects
/ Biological markers
/ Biology and Life Sciences
/ Biomarkers
/ Biomarkers, Pharmacological - analysis
/ Biomarkers, Pharmacological - metabolism
/ Cholestenones - therapeutic use
/ Chromatography
/ Citrulline
/ Clinical trials
/ Computer and Information Sciences
/ Development and progression
/ Disease
/ Disease Progression
/ Double-Blind Method
/ Drug Resistance - drug effects
/ Female
/ Glutamine
/ Glycine
/ High performance liquid chromatography
/ Humans
/ Learning algorithms
/ Life Sciences
/ Lipids
/ Liquid chromatography
/ Machine learning
/ Male
/ Mass spectrometry
/ Mass spectroscopy
/ Medical prognosis
/ Medical research
/ Medication
/ Medicine and Health Sciences
/ Metabolism
/ Metabolites
/ Metabolome - drug effects
/ Metabolomics
/ Metabolomics - methods
/ Middle Aged
/ Multivariate analysis
/ Neurobiology
/ Neurons
/ Neurons and Cognition
/ Pathogenesis
/ Patient outcomes
/ Patients
/ Pharmaceutical sciences
/ Pharmacology
/ Physical Sciences
/ Placebos
/ Prognosis
/ Research and Analysis Methods
/ Spermidine
/ Test sets
2018
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A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression
by
Patin, Franck
, Garçon, Guillaume
, Bede, Peter
, Blasco, Hélène
, Pradat, Pierre-François
, Meininger, Vincent
, Devos, David
, Corcia, Philippe
, Gossens, Jean François
, Lenglet, Timothée
, Gelé, Patrick
, Descat, Amandine
in
Adult
/ Aged
/ Amino acids
/ Amyotrophic lateral sclerosis
/ Amyotrophic Lateral Sclerosis - diagnosis
/ Amyotrophic Lateral Sclerosis - drug therapy
/ Amyotrophic Lateral Sclerosis - metabolism
/ Amyotrophic Lateral Sclerosis - pathology
/ Analysis
/ Arginine
/ Bioindicators
/ Biological effects
/ Biological markers
/ Biology and Life Sciences
/ Biomarkers
/ Biomarkers, Pharmacological - analysis
/ Biomarkers, Pharmacological - metabolism
/ Cholestenones - therapeutic use
/ Chromatography
/ Citrulline
/ Clinical trials
/ Computer and Information Sciences
/ Development and progression
/ Disease
/ Disease Progression
/ Double-Blind Method
/ Drug Resistance - drug effects
/ Female
/ Glutamine
/ Glycine
/ High performance liquid chromatography
/ Humans
/ Learning algorithms
/ Life Sciences
/ Lipids
/ Liquid chromatography
/ Machine learning
/ Male
/ Mass spectrometry
/ Mass spectroscopy
/ Medical prognosis
/ Medical research
/ Medication
/ Medicine and Health Sciences
/ Metabolism
/ Metabolites
/ Metabolome - drug effects
/ Metabolomics
/ Metabolomics - methods
/ Middle Aged
/ Multivariate analysis
/ Neurobiology
/ Neurons
/ Neurons and Cognition
/ Pathogenesis
/ Patient outcomes
/ Patients
/ Pharmaceutical sciences
/ Pharmacology
/ Physical Sciences
/ Placebos
/ Prognosis
/ Research and Analysis Methods
/ Spermidine
/ Test sets
2018
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A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression
Journal Article
A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression
2018
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Overview
There is an urgent and unmet need for accurate biomarkers in Amyotrophic Lateral Sclerosis. A pharmaco-metabolomics study was conducted using plasma samples from the TRO19622 (olesoxime) trial to assess the link between early metabolomic profiles and clinical outcomes. Patients included in this trial were randomized into either Group O receiving olesoxime (n = 38) or Group P receiving placebo (n = 36). The metabolomic profile was assessed at time-point one (V1) and 12 months (V12) after the initiation of the treatment. High performance liquid chromatography coupled with tandem mass spectrometry was used to quantify 188 metabolites (Biocrates® commercial kit). Multivariate analysis based on machine learning approaches (i.e. Biosigner algorithm) was performed. Metabolomic profiles at V1 and V12 and changes in metabolomic profiles between V1 and V12 accurately discriminated between Groups O and P (p<5×10-6), and identified glycine, kynurenine and citrulline/arginine as the best predictors of group membership. Changes in metabolomic profiles were closely linked to clinical progression, and correlated with glutamine levels in Group P and amino acids, lipids and spermidine levels in Group O. Multivariate models accurately predicted disease progression and highlighted the discriminant role of sphingomyelins (SM C22:3, SM C24:1, SM OH C22:2, SM C16:1). To predict SVC from SM C24:1 in group O and SVC from SM OH C22:2 and SM C16:1 in group P+O, we noted a median sensitivity between 67% and 100%, a specificity between 66.7 and 71.4%, a positive predictive value between 66 and 75% and a negative predictive value between 70% and 100% in the test sets. This proof-of-concept study demonstrates that the metabolomics has a role in evaluating the biological effect of an investigational drug and may be a candidate biomarker as a secondary outcome measure in clinical trials.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
/ Aged
/ Amyotrophic lateral sclerosis
/ Amyotrophic Lateral Sclerosis - diagnosis
/ Amyotrophic Lateral Sclerosis - drug therapy
/ Amyotrophic Lateral Sclerosis - metabolism
/ Amyotrophic Lateral Sclerosis - pathology
/ Analysis
/ Arginine
/ Biomarkers, Pharmacological - analysis
/ Biomarkers, Pharmacological - metabolism
/ Cholestenones - therapeutic use
/ Computer and Information Sciences
/ Disease
/ Drug Resistance - drug effects
/ Female
/ Glycine
/ High performance liquid chromatography
/ Humans
/ Lipids
/ Male
/ Medicine and Health Sciences
/ Neurons
/ Patients
/ Placebos
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