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Quantitative analysis of proteins of metabolism by reverse phase protein microarrays identifies potential biomarkers of rare neuromuscular diseases. [artículo]

Por: Santacatterina, Fulvio [Instituto de Investigación i+12] | Chamorro, Margarita [Instituto de Investigación imas12] | Núñez de Arenas, Cristina [Instituto de Investigación i+12] | Martín, Miguel Ángel [Instituto de investigación imas12] | Cuezva, J.M [Instituto de Investigación i+12] | Sánchez Aragó, María [Instituto de Investigación i+12].
Colaborador(es): Instituto de Investigación imas12.
Tipo de material: materialTypeLabelArtículoEditor: Journal of translational medicine, 2015Descripción: 13:65.Recursos en línea: Acceso libre Resumen: Background: Muscle diseases have been associated with changes in the expression of proteins involved in energy metabolism. To this aim we have developed a number of monoclonal antibodies against proteins of energy metabolism. Methods: Herein, we have used Reverse Phase Protein Microarrays (RPMA), a high throughput technique, to investigate quantitative changes in protein expression with the aim of identifying potential biomarkers in rare neuromuscular diseases. A cohort of 73 muscle biopsies that included samples from patients diagnosed of Duchenne (DMD), Becker (BMD), symptomatic forms of DMD and BMD in female carriers (Xp21 Carriers), Limb Girdle Muscular Dystrophy Type 2C (LGMD2C), neuronal ceroid lipofuscinosis (NCL), glycogenosis type V (Mc Ardle disease), isolated mitochondrial complex I deficiency, intensive care unit myopathy and control donors were investigated. The nineteen proteins of energy metabolism studied included members of the mitochondrial oxidation of pyruvate, the tricarboxylic acid cycle, β-oxidation of fatty acids, electron transport and oxidative phosphorylation, glycogen metabolism, glycolysis and oxidative stress using highly specific antibodies. Results: The results indicate that the phenotype of energy metabolism offers potential biomarkers that could be implemented to refine the understanding of the biological principles of rare diseases and, eventually, the management of these patients. Conclusions: We suggest that some biomarkers of energy metabolism could be translated into the clinics to contribute to the improvement of the clinical handling of patients affected by rare diseases.
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Formato Vancouver:
Santacatterina F, Chamorro M, de Arenas CN, Navarro C, Martín MA, Cuezva JM et al. Quantitative analysis of proteins of metabolism by reverse phase protein microarrays identifies potential biomarkers of rare neuromuscular diseases. J Transl Med. 2015 Feb 18;13:65.

PMID: 25880557
PMC4342896

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Background: Muscle diseases have been associated with changes in the expression of proteins involved in energy metabolism. To this aim we have developed a number of monoclonal antibodies against proteins of energy metabolism.
Methods: Herein, we have used Reverse Phase Protein Microarrays (RPMA), a high throughput technique, to investigate quantitative changes in protein expression with the aim of identifying potential biomarkers in rare neuromuscular diseases. A cohort of 73 muscle biopsies that included samples from patients diagnosed of Duchenne (DMD), Becker (BMD), symptomatic forms of DMD and BMD in female carriers (Xp21 Carriers), Limb Girdle Muscular Dystrophy Type 2C (LGMD2C), neuronal ceroid lipofuscinosis (NCL), glycogenosis type V (Mc Ardle disease), isolated mitochondrial complex I deficiency, intensive care unit myopathy and control donors were investigated. The nineteen proteins of energy metabolism studied included members of the mitochondrial oxidation of pyruvate, the tricarboxylic acid cycle, β-oxidation of fatty acids, electron transport and oxidative phosphorylation, glycogen metabolism, glycolysis and oxidative stress using highly specific antibodies.
Results: The results indicate that the phenotype of energy metabolism offers potential biomarkers that could be implemented to refine the understanding of the biological principles of rare diseases and, eventually, the management of these patients.

Conclusions: We suggest that some biomarkers of energy metabolism could be translated into the clinics to contribute to the improvement of the clinical handling of patients affected by rare diseases.

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