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El enfoque de sistemas integrados identifica nodos y redes genéticas en la enfermedad de Alzheimer de aparición
Bin Zhang1, Chris Gaiteri, Liviu-Gabriel Bodea
1Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY 10029, USA. bin.zhang@mssm.edu
Cell
|April 30, 2013
Resumen
Este estudio revela que la enfermedad de Alzheimer de aparición tardía (LOAD) altera las redes moleculares en el cerebro, particularmente un módulo inmune y de microglía. Esta estructura de red ayuda a predecir los mecanismos de la enfermedad y las respuestas a los cambios genéticos.
Área de la Ciencia:
- La neurociencia es la neurociencia.
- Genética La genética.
- Biología de Sistemas Biología de Sistemas.
Sus antecedentes:
- Enfermedades complejas como la enfermedad de Alzheimer de aparición tardía (LOAD) implican interacciones moleculares dentro de las vías celulares.
- Comprender estas interacciones a través de redes moleculares es crucial para caracterizar los mecanismos de la enfermedad.
Objetivo del estudio:
- Construir y analizar redes de regulación génica en los tejidos cerebrales para identificar sistemas moleculares asociados con LOAD.
- Para resaltar estructuras de red específicas y reguladores relevantes para la patología de LOAD.
Principales métodos:
- Construcción de redes de regulación genética utilizando tejidos cerebrales postmortem de 1.647 pacientes con LOAD y sujetos no dementados.
- Un enfoque integrador basado en la red para clasificar las estructuras de red por relevancia a la patología LOAD.
- Análisis de células de microglía de ratón para validar los hallazgos de las redes cerebrales humanas.
Principales resultados:
- Se demostró que LOAD reconfigura partes específicas de la estructura de interacción molecular en el cerebro.
- Se identificó un módulo específico para el sistema inmunológico y la microglía, dominado por genes de fagocitosis y regulado por TYROBP, y se encontró que está regulado al alza en LOAD.
- Los experimentos de microglia en ratones confirmaron cambios de expresión superpuestos con la red humana de TYROBP.
Conclusiones:
- Las estructuras de red de regulación genética son valiosas para comprender la patología LOAD y predecir las respuestas a las perturbaciones genéticas.
- El módulo inmunológico y microglia identificado proporciona un marco para probar modelos de enfermedades en LOAD.
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