Mechanisms of aging in senescence-accelerated mice
Gene-expression analysis and polymorphism screening to study molecular senescence of the retina and hippocampus in two rare inbred mouse models of accelerated neurological senescence as well as a related and an unrelated normal strain showed that most agerelated gene expression changes were strain-specific.
Abstract Background: Progressive neurological dysfunction is a key aspect of human aging. Because of underlying differences in the aging of mice and humans, useful mouse models have been difficult to obtain and study. We have used gene-expression analysis and polymorphism screening to study molecular senescence of the retina and hippocampus in two rare inbred mouse models of accelerated neurological senescence (SAMP8 and SAMP10) that closely mimic human neurological aging, and in a related normal strain (SAMR1) and an unrelated normal strain (C57BL/6J).
This study reports data from two dysgraphic patients, TH and PB, whose errors in spelling most often occurred in the final part of words. The probability of making an error increased monotonically towards the end of words. Long words were affected more than short words, and performance was similar across different output modalities (writing, typing and oral spelling). This error performance was found despite the fact that both patients showed normal ability to repeat the same words orally and to access their full spelling in tasks that minimized the involvement of working memory. This pattern of performance locates their deficit to the mechanism that keeps graphemic representations active for further processing, and shows that the functioning of this mechanism is not controlled or "refreshed" by phonological (or articulatory) processes. Although the overall performance pattern is most consistent with a deficit to the graphemic buffer, the strong tendency for errors to occur at the ends of words is unlike many classic "graphemic buffer patients" whose errors predominantly occur at word-medial positions. The contrasting patterns are discussed in terms of different types of impairment to the graphemic buffer.
The use of high-density oligonucleotide arrays to measure the expression levels of thousands of genes in parallel has become commonplace. To take further advantage of the growing body of data, we developed a method, termed "GeSNP," to mine the detailed hybridization patterns in oligonucleotide array expression data for evidence of genetic variation. To demonstrate the performance of the algorithm, the hybridization patterns in data obtained previously from SAMP8/Ta, SAMP10/Ta, and SAMR1/Ta inbred mice and from humans and chimpanzees were analyzed. Genes with consistent strain-specific and species-specific hybridization pattern differences were identified, and ∼90% of the candidate genes were independently confirmed to harbor sequence differences. Importantly, the quality of gene expression data was also improved by masking the probes of regions with putative sequence differences between species and strains. To illustrate the application to human disease groups, data from an inflammatory bowel disease study were analyzed. GeSNP identified sequence differences in candidate genes previously discovered in independent association and linkage studies and uncovered many promising new candidates. This approach enables the opportunistic extraction of genetic variation information from new or pre-existing gene expression data obtained with high-density oligonucleotide arrays.[Supplemental material is available online at www.genome.org. GeSNP can be accessed at
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