| First Author | Morihara T | Year | 2014 |
| Journal | Proc Natl Acad Sci U S A | Volume | 111 |
| Issue | 7 | Pages | 2638-43 |
| PubMed ID | 24497505 | Mgi Jnum | J:206719 |
| Mgi Id | MGI:5551907 | Doi | 10.1073/pnas.1307345111 |
| Citation | Morihara T, et al. (2014) Transcriptome analysis of distinct mouse strains reveals kinesin light chain-1 splicing as an amyloid-beta accumulation modifier. Proc Natl Acad Sci U S A 111(7):2638-43 |
| abstractText | Alzheimer's disease (AD) is characterized by the accumulation of amyloid-beta (Abeta). The genes that govern this process, however, have remained elusive. To this end, we combined distinct mouse strains with transcriptomics to directly identify disease-relevant genes. We show that AD model mice (APP-Tg) with DBA/2 genetic backgrounds have significantly lower levels of Abeta accumulation compared with SJL and C57BL/6 mice. We then applied brain transcriptomics to reveal the genes in DBA/2 that suppress Abeta accumulation. To avoid detecting secondarily affected genes by Abeta, we used non-Tg mice in the absence of Abeta pathology and selected candidate genes differently expressed in DBA/2 mice. Additional transcriptome analysis of APP-Tg mice with mixed genetic backgrounds revealed kinesin light chain-1 (Klc1) as an Abeta modifier, indicating a role for intracellular trafficking in Abeta accumulation. Abeta levels correlated with the expression levels of Klc1 splice variant E and the genotype of Klc1 in these APP-Tg mice. In humans, the expression levels of KLC1 variant E in brain and lymphocyte were significantly higher in AD patients compared with unaffected individuals. Finally, functional analysis using neuroblastoma cells showed that overexpression or knockdown of KLC1 variant E increases or decreases the production of Abeta, respectively. The identification of KLC1 variant E suggests that the dysfunction of intracellular trafficking is a causative factor of Abeta pathology. This unique combination of distinct mouse strains and model mice with transcriptomics is expected to be useful for the study of genetic mechanisms of other complex diseases. |
