Literature DB >> 18455804

Novel approach to select genes from RMA normalized microarray data using functional hearing tests in aging mice.

Mary D'Souza1, Xiaoxia Zhu, Robert D Frisina.   

Abstract

UNLABELLED: Presbycusis - age-related hearing loss - is the number one communicative disorder and one of the top three chronic medical condition of our aged population. High-throughput technologies potentially can be used to identify differentially expressed genes that may be better diagnostic and therapeutic targets for sensory and neural disorders. Here we analyzed gene expression for a set of GABA receptors in the cochlea of aging CBA mice using the Affymetrix GeneChip MOE430A. Functional phenotypic hearing measures were made, including auditory brainstem response (ABR) thresholds and distortion-product otoacoustic emission (DPOAE) amplitudes (four age groups). Four specific criteria were used to assess gene expression changes from RMA normalized microarray data (40 replicates). Linear regression models were used to fit the neurophysiological hearing measurements to probe-set expression profiles. These data were first subjected to one-way ANOVA, and then linear regression was performed. In addition, the log signal ratio was converted to fold change, and selected gene expression changes were confirmed by relative real-time PCR. MAJOR
FINDINGS: expression of GABA-A receptor subunit alpha6 was upregulated with age and hearing loss, whereas subunit alpha1 was repressed. In addition, GABA-A receptor associated protein like-1 and GABA-A receptor associated protein like-2 were strongly downregulated with age and hearing impairment. Lastly, gene expression measures were correlated with pathway/network relationships relevant to the inner ear using Pathway Architect, to identify key pathways consistent with the gene expression changes observed.

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Year:  2008        PMID: 18455804      PMCID: PMC2440495          DOI: 10.1016/j.jneumeth.2008.02.022

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


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