4 research outputs found

    Discovery and verification of amyotrophic lateral sclerosis biomarkers by proteomics

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    Recent studies using mass spectrometry have discovered candidate biomarkers for amyotrophic lateral sclerosis (ALS). However, those studies utilized small numbers of ALS and control subjects. Additional studies using larger subject cohorts are required to verify these candidate biomarkers. Cerebrospinal fluid (CSF) samples from 100 patients with ALS, 100 disease control, and 41 healthy control subjects were examined by mass spectrometry. Sixty-one mass spectral peaks exhibited altered levels between ALS and controls. Mass peaks for cystatin C and transthyretin were reduced in ALS, whereas mass peaks for posttranslational modified transthyretin and C-reactive protein (CRP) were increased. CRP levels were 5.84 ± 1.01 ng/ml for controls and 11.24 ± 1.52 ng/ml for ALS subjects, as determined by enzyme-linked immunoassay. This study verified prior mass spectrometry results for cystatin C and transthyretin in ALS. CRP levels were increased in the CSF of ALS patients, and cystatin C level correlated with survival in patients with limb-onset disease. Our biomarker panel predicted ALS with an overall accuracy of 82%. © 2010 Wiley Periodicals, Inc

    Plasma Metabolomic Biomarker Panel To Distinguish Patients With Amyotrophic Lateral Sclerosis From Disease Mimics

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    Our objective was to identify plasma biomarkers of ALS that can aid in distinguishing patients with ALS from those with disease mimics. In this multi-center study, plasma samples were collected from 172 patients recently diagnosed with ALS, 50 healthy controls, and 73 neurological disease mimics. Samples were analyzed using metabolomics. Using all identified biochemicals detected in \u3e 50% of all samples in the metabolomics analysis, samples were classified as ALS or mimic with 65% sensitivity and 81% specificity by LASSO analysis (AUC of 0.76). A subset panel of 32 candidate biomarkers classified these diagnosis groups with a specificity of 90%/sensitivity 58% (AUC of 0.81). Creatinine was lower in subjects with lower revised ALS Functional Rating Scale (ALSFRS-R) scores. In conclusion, ALS can be distinguished from neurological disease mimics by global biochemical profiling of plasma samples. Our analysis identified ALS versus mimics with relatively high sensitivity. We identified a subset of 32 metabolites that identify patients with ALS with a high specificity. Interestingly, lower creatinine correlates significantly with a lower ALSFRS-R score. Finally, molecules previously reported to be important in disease pathophysiology, such as urate, are included in our metabolite panel. © 2014 Informa Healthcare

    Biochemical alterations associated with ALS

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    Our objective was to identify metabolic pathways affected by ALS using non-targeted metabolomics in plasma, comparing samples from healthy volunteers to those from ALS patients. This discovery could become the basis for the identification of therapeutic targets and diagnostic biomarkers of ALS. Two distinct cross-sectional studies were conducted. Plasma was collected from 62 (Study 1) and 99 (Study 2) participants meeting El Escorial criteria for possible, probable, or definite ALS; 69 (Study 1) and 48 (Study 2) healthy controls samples were collected. Global metabolic profiling was used to detect and evaluate biochemical signatures of ALS. Twenty-three metabolites were significantly altered in plasma from ALS patients in both studies. These metabolites include biochemicals in pathways associated with neuronal change, hypermetabolism, oxidative damage, and mitochondrial dysfunction, all of which are proposed disease mechanisms in ALS. The data also suggest possible hepatic dysfunction associated with ALS. In conclusion, the data presented here provide insight into the pathophysiology of ALS while suggesting promising areas of focus for future studies. The metabolomics approach can generate novel hypotheses regarding ALS disease mechanisms with the potential to identify therapeutic targets and novel diagnostic biomarkers. © 2012 Informa Healthcare
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