19 research outputs found

    Longitudinal Screening Detects Cognitive Stability and Behavioral Deterioration in ALS Patients

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    Objective. To evaluate longitudinal cognitive/behavioral change over 12 months in participants enrolled in the ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS). Methods. We analyzed data from 294 ALS participants, 134 of whom were studied serially. Change over time was evaluated controlling for age, sex, symptom duration, education, race, and ethnicity. Using multiple regression, we evaluated associations among decline in ALS Functional Rating Scale-Revised (ALSFRS-R) scores, forced vital capacity (FVC), and cognitive/behavioral changes. Change in cognitive/behavioral subgroups was assessed using one-way analyses of covariance. Results. Participants with follow-up data had fewer baseline behavior problems compared to patients without follow-up data. We found significant worsening of behavior (ALS Cognitive Behavioral Screen (ALS CBS) behavioral scale, p \u3c 0.001; Frontal Behavioral Inventory-ALS (FBI-ALS) disinhibition subscale, p = 0.044). Item analysis suggested change in frustration tolerance, insight, mental rigidity, and interests (p \u3c 0.05). Changes in ALSFRS-R correlated with the ALS CBS. Worsening disinhibition (FBI-ALS) did not correlate with ALSFRS-R, FVC, or disease duration. Conclusion. We did not detect cognitive change. Behavioral change was detected, and increased disinhibition was found among patients with abnormal baseline behavioral scores. Disinhibition changes did not correlate with disease duration or progression. Baseline behavioral problems were associated with advanced, rapidly progressive disease and study attrition

    Longitudinal Screening Detects Cognitive Stability and Behavioral Deterioration in ALS Patients.

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    ObjectiveTo evaluate longitudinal cognitive/behavioral change over 12 months in participants enrolled in the ALS Multicenter Cohort Study of Oxidative Stress (ALS COSMOS).MethodsWe analyzed data from 294 ALS participants, 134 of whom were studied serially. Change over time was evaluated controlling for age, sex, symptom duration, education, race, and ethnicity. Using multiple regression, we evaluated associations among decline in ALS Functional Rating Scale-Revised (ALSFRS-R) scores, forced vital capacity (FVC), and cognitive/behavioral changes. Change in cognitive/behavioral subgroups was assessed using one-way analyses of covariance.ResultsParticipants with follow-up data had fewer baseline behavior problems compared to patients without follow-up data. We found significant worsening of behavior (ALS Cognitive Behavioral Screen (ALS CBS) behavioral scale, p < 0.001; Frontal Behavioral Inventory-ALS (FBI-ALS) disinhibition subscale, p = 0.044). Item analysis suggested change in frustration tolerance, insight, mental rigidity, and interests (p < 0.05). Changes in ALSFRS-R correlated with the ALS CBS. Worsening disinhibition (FBI-ALS) did not correlate with ALSFRS-R, FVC, or disease duration.ConclusionWe did not detect cognitive change. Behavioral change was detected, and increased disinhibition was found among patients with abnormal baseline behavioral scores. Disinhibition changes did not correlate with disease duration or progression. Baseline behavioral problems were associated with advanced, rapidly progressive disease and study attrition

    Fibroblast bioenergetics to classify amyotrophic lateral sclerosis patients

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    Abstract Background The objective of this study was to investigate cellular bioenergetics in primary skin fibroblasts derived from patients with amyotrophic lateral sclerosis (ALS) and to determine if they can be used as classifiers for patient stratification. Methods We assembled a collection of unprecedented size of fibroblasts from patients with sporadic ALS (sALS, n = 171), primary lateral sclerosis (PLS, n = 34), ALS/PLS with C9orf72 mutations (n = 13), and healthy controls (n = 91). In search for novel ALS classifiers, we performed extensive studies of fibroblast bioenergetics, including mitochondrial membrane potential, respiration, glycolysis, and ATP content. Next, we developed a machine learning approach to determine whether fibroblast bioenergetic features could be used to stratify patients. Results Compared to controls, sALS and PLS fibroblasts had higher average mitochondrial membrane potential, respiration, and glycolysis, suggesting that they were in a hypermetabolic state. Only membrane potential was elevated in C9Orf72 lines. ATP steady state levels did not correlate with respiration and glycolysis in sALS and PLS lines. Based on bioenergetic profiles, a support vector machine (SVM) was trained to classify sALS and PLS with 99% specificity and 70% sensitivity. Conclusions sALS, PLS, and C9Orf72 fibroblasts share hypermetabolic features, while presenting differences of bioenergetics. The absence of correlation between energy metabolism activation and ATP levels in sALS and PLS fibroblasts suggests that in these cells hypermetabolism is a mechanism to adapt to energy dissipation. Results from SVM support the use of metabolic characteristics of ALS fibroblasts and multivariate analysis to develop classifiers for patient stratification

    Additional file 1: Figure S1. of Fibroblast bioenergetics to classify amyotrophic lateral sclerosis patients

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    Flux analysis of control, sALS and PLS fibroblasts under forced oxidative metabolism in galactose medium. Scatter plots of OCR baseline (A; Control mean: 3850.0, SD: 1936.7; sALS mean: 3307.5, SD: 1430.7; PLS mean: 2989.2, SD: 1164.7), oligomycin sensitive rate (B; Control mean: 3630.0, SD: 1772.0; sALS mean: 2835.0, SD: 1135.4; PLS mean: 2707.5, SD: 1138.9), maximal respiratory capacity (C; Control mean: 5325.8, SD: 2993.3; sALS mean: 3613.3, SD: 1662.5; PLS mean: 3741.7, SD: 2102.3), spare respiratory capacity (D; Control mean: 1478.8, SD: 1385.2; sALS mean: 306.8, SD: 589.2; PLS mean: 754.5, SD: 1120.1), ECAR baseline (E; Control mean: 1114.8, SD: 349.3; sALS mean: 1063.3, SD: 573.2; PLS mean: 1007.8, SD: 351.7), and OCR base/ECAR base (F; Control mean: 3.6, SD: 1.3; sALS mean: 3.5, SD: 1.4; PLS mean: 3.3, SD: 1.4). Values are shown comparing sALS, PLS, and control lines. Middle bars represent the average values and error bars show standard deviations. p-values are indicated where there was a significant difference between groups. n.s.: no significant difference. n = 12 sALS; n = 12 PLS, n = 12 controls. (DOCX 132 kb
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