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Cytoplasmic TDP-43 aggregates are a hallmark of amyotrophic lateral sclerosis (ALS). Today, only two drugs are available for ALS treatment, and their modest effect prompts researchers to search for new therapeutic options. TDP-43 represents one of the most promising targets for therapeutic intervention, but reliable and reproducible in vitro protocols for TDP-43-mediated toxicity are lacking. Here, we used HEK293T cells transfected with increasing concentrations of TDP-43-expressing plasmid to evaluate different parameters of toxicity and alterations in cellular metabolism. Overexpression of TDP-43 induced aggregates occurrence followed by the detection of 25- and 35-kDa forms of TDP-43. TDP-43 overexpression decreased cell viability and increased cells arrested at G2/M phase and nuclear fragmentation. Analysis of the energetic metabolism showed a tendency to decrease oxidative phosphorylation and increase glycolysis, but no statistical differences were observed. Metabolomics revealed alterations in different metabolites (mainly sphingolipids and glycerophospholipids) in cells overexpressing TDP-43. Our data reveal the main role of TDP-43 aggregation in cellular death and highlight novel insight into the mechanism of cellular toxicity induced by TDP-43. Here, we provide a simple, sensitive, and reliable protocol in a human-derived cell line to be used in high-throughput screenings of potential therapeutic molecules for ALS treatment. [ABSTRACT FROM AUTHOR]

Objectives Autism spectrum disorders and intellectual disability present a challenge for therapeutic and dietary management. We performed a re-analysis of plasma amino acid chromatography of children with autism spectrum disorders ( n = 22) or intellectual disability ( n = 29) to search for a metabolic signature that can distinguish individuals with these disorders from controls ( n = 30). Methods We performed univariate and multivariate analyses using different machine learning strategies, from the raw data of the amino acid chromatography. Finally, we analysed the metabolic pathways associated with discriminant biomarkers. Results Multivariate analysis revealed models to discriminate patients with autism spectrum disorders or intellectual disability and controls from plasma amino acid profiles ( P < 0.0003). Univariate analysis showed that autism spectrum disorder and intellectual disability patients shared similar differences relative to controls, including lower glutamate ( P < 0.0001 and P = 0.0002, respectively) and serine ( P = 0.002 for both) concentrations. The multivariate model ( P < 6.12.10-7) to discriminate between autism spectrum disorders and intellectual disability revealed the involvement of urea, 3-methyl-histidine and histidine metabolism. Biosigner analysis and univariate analysis confirmed the role of 3-methylhistidine ( P = 0.004), histidine ( P = 0.003), urea ( P = 0.0006) and lysine ( P = 0.002). Conclusions We revealed discriminant metabolic patterns between autism spectrum disorders, intellectual disability and controls. Amino acids known to play a role in neurotransmission were discriminant in the models comparing autism spectrum disorders or intellectual disability to controls, and histidine and b-alanine metabolism was specifically highlighted in the model. [ABSTRACT FROM AUTHOR]