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  • 标题:A Novel Dual Eigen-Analysis of Mouse Multi-Tissues’ Expression Profiles Unveils New Perspectives into Type 2 Diabetes
  • 本地全文:下载
  • 作者:Lei M. Li ; Xiuxiu Liu ; Lin Wang
  • 期刊名称:Scientific Reports
  • 电子版ISSN:2045-2322
  • 出版年度:2017
  • 卷号:7
  • 期号:1
  • DOI:10.1038/s41598-017-05405-x
  • 语种:English
  • 出版社:Springer Nature
  • 摘要:Type 2 diabetes (T2D) is a complex and polygenic disease yet in need of a complete picture of its development mechanisms. To better understand the mechanisms, we examined gene expression profiles of multi-tissues from outbred mice fed with a high-fat diet (HFD) or regular chow at weeks 1, 9, and 18. To analyze such complex data, we proposed a novel dual eigen-analysis, in which the sample- and gene-eigenvectors correspond respectively to the macro- and micro-biology information. The dual eigen-analysis identified the HFD eigenvectors as well as the endogenous eigenvectors for each tissue. The results imply that HFD influences the hepatic function or the pancreatic development as an exogenous factor, while in adipose HFD's impact roughly coincides with the endogenous eigenvector driven by aging. The enrichment analysis of the eigenvectors revealed diverse HFD impact on the three tissues over time. The diversity includes: inflammation, degradation of branched chain amino acids (BCAA), and regulation of peroxisome proliferator activated receptor gamma (PPARγ). We reported that in the pancreas remarkable up-regulation of angiogenesis as downstream of the HIF signaling pathway precedes hyperinsulinemia. The dual eigen-analysis and discoveries provide new evaluations/guidance in T2D prevention and therapy, and will also promote new thinking in biology and medicine.
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