Abstract
Connectivity in a gene-gene network declines with age, typically within gene clusters. We explored the effect of short-term (3 months) graded calorie restriction (CR) (up to 40 %) on network structure of aging-associated genes in the murine hypothalamus by using conditional mutual information. The networks showed a topological rearrangement when exposed to graded CR with a higher relative within cluster connectivity at 40CR. We observed changes in gene centrality concordant with changes in CR level, with Ppargc1a, and Ppt1 having increased centrality and Etfdh, Traf3 and Abcc1 decreased centrality as CR increased. This change in gene centrality in a graded manner with CR, occurred in the absence of parallel changes in gene expression levels. This study emphasizes the importance of augmenting traditional differential gene expression analyses to better understand structural changes in the transcriptome. Overall our results suggested that CR induced changes in centrality of biological relevant genes that play an important role in preventing the age-associated loss of network integrity irrespective of their gene expression levels.
Highlights
Brain aging has an impact on cognitive function and forms a major risk for the development of neurodegenerative disorders such as Parkinson’s, Huntington's and Alzheimer’s disease [1]
We initially used an orthogonal signal correction partial least squares discriminant analysis (O-PLS-DA) to classify 12 and 24 hr ad libitum (AL) fed groups (12AL, 24h ad libitum intake (24AL)) and calorie restriction (CR) groups based on the expression levels of genes involved in aging, inflammation and oxidative stress (n = 408) obtained from a priori defined gene lists curated by Ingenuity Pathway Analysis (IPA) (‘inflammation of the nervous system’ and ‘oxidative stress response’) and GenAge database (‘aging-associated genes’ in Mus musculus)
Model validation indicated that 41.8% of the variance in gene expression levels was explained by the different treatment groups (n = 6) (Xvar = 41.8 ± 18.5, p-value < 0.001)
Summary
Brain aging has an impact on cognitive function and forms a major risk for the development of neurodegenerative disorders such as Parkinson’s, Huntington's and Alzheimer’s disease [1]. In murine brain tissue, aging is associated with transcriptional changes in genes that induce an elevated inflammatory response and increased oxidative stress [2,3]. These transcriptomic patterns associated with aging may be established in the brain early in adolescent [2]. Network analyses of interactions between genes could further elaborate the complex mechanisms underlying both aging and CR. We can derive from the same observations a measure of information shared between gene expressions [13] (reviewed in [14]). The decline in structure and information flow during aging can be assessed by evaluating quantitative changes in network topology
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