Análisis de redes de coexpresión identifica posibles genes clave en el envejecimiento de la corteza prefrontal humana

Translated title of the contribution: Co-expression network analysis identifies possible hub genes in aging of the human prefrontal cortex

César Payán-Gómez, Julián Riaño-Moreno, Diana Amador-Muñoz, Sandra Ramírez-Clavijo

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Introduction: Aging is the main risk factor for the development of chronic diseases such as cancer, diabetes, Parkinson’s disease, and Alzheimer’s disease. The central nervous system is particularly susceptible to progressive functional deterioration associated with age, among the brain regions the prefrontal cortex (PFC) has one of the highest involvements. Transcriptomics studies of this brain region have identified the decrease in synaptic function and activation of neuroglia cells as fundamental characteristics of the aging process. The aim of this study was to identify hub genes in the transcriptomic deregulation in the PFC aging to advance in the knowledge of this process. Materials and methods: A gene co-expression analysis was carried out for 45 people 60 to 80 years old compared with 38 people 20 to 40 years old. The networks were visualized and analyzed using Cytoscape; citoHubba was used to determine which genes had the best topological characteristics in the co-expression networks. Results: Five genes with high topological characteristics were identified. Four of them —HPCA, CACNG3, CA10, PLPPR4— were repressed and one was over-expressed —CRYAB—. Conclusion: The four repressed genes are expressed preferentially in neurons and regulate the synaptic function and the neuronal plasticity, while the overexpressed gene is typical of glial cells and is expressed as a response to neuronal damage, facilitating myelination and neuronal regeneration.

Translated title of the contributionCo-expression network analysis identifies possible hub genes in aging of the human prefrontal cortex
Original languageSpanish
Pages (from-to)202-222
Number of pages21
JournalRevista Ciencias de la Salud
Volume17
Issue number2
DOIs
StatePublished - Jan 1 2019

All Science Journal Classification (ASJC) codes

  • Medicine (miscellaneous)
  • Health(social science)

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