Literature DB >> 28626023

Microarray analysis of aging-associated immune system alterations in the rostral ventrolateral medulla of F344 rats.

Sivasai Balivada1, Chanran K Ganta2, Yongqing Zhang3, Hitesh N Pawar4, Richard J Ortiz4, Kevin G Becker3, Arshad M Khan4, Michael J Kenney4.   

Abstract

The rostral ventrolateral medulla (RVLM) is an area of the brain stem that contains diverse neural substrates that are involved in systems critical for physiological function. There is evidence that aging affects some neural substrates within the RVLM, although age-related changes in RVLM molecular mechanisms are not well established. The goal of the present study was to characterize the transcriptomic profile of the aging RVLM and to test the hypothesis that aging is associated with altered gene expression in the RVLM, with an emphasis on immune system associated gene transcripts. RVLM tissue punches from young, middle-aged, and aged F344 rats were analyzed with Agilent's whole rat genome microarray. The RVLM gene expression profile varied with age, and an association between chronological age and specific RVLM gene expression patterns was observed [P < 0.05, false discovery rate (FDR) < 0.3]. Functional analysis of RVLM microarray data via gene ontology profiling and pathway analysis identified upregulation of genes associated with immune- and stress-related responses and downregulation of genes associated with lipid biosynthesis and neurotransmission in aged compared with middle-aged and young rats. Differentially expressed genes associated with the complement system and microglial cells were further validated by quantitative PCR with separate RVLM samples (P < 0.05, FDR < 0.1). The present results have identified age-related changes in the transcriptomic profile of the RVLM, modifications that may provide the molecular backdrop for understanding age-dependent changes in physiological regulation.

Entities:  

Keywords:  aging; neuro-immunology, microarrays; rostral ventrolateral medulla; transcriptomics

Mesh:

Year:  2017        PMID: 28626023      PMCID: PMC5582943          DOI: 10.1152/physiolgenomics.00131.2016

Source DB:  PubMed          Journal:  Physiol Genomics        ISSN: 1094-8341            Impact factor:   3.107


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