SAGE application in the study of diabetes.
Type 2 diabetes is a multifactorial disease that is caused by the disruption of inter-organ networks. These disruptions lead to absolute and/or relative deficiencies in the actions of insulin due to either a genetic disposition or environmental factors. Specifically, the liver plays a central role in energy homeostasis and is a major source of bioactive secretory proteins that contribute to the pathophysiology of diabetes and subsequent complications. Therefore, comprehensive gene expression analyses of critical tissues, including the liver, are important steps for understanding the molecular signature of type 2 diabetes. Serial analysis of gene expression (SAGE) techniques have made it possible to compare tag levels among independent libraries and to identify previously unrecognized genes with novel functions that may be important in the development of diseases. Here, we review possible applications of SAGE to the study of diabetes from the following perspectives: (1) to understand and quantify normal gene expression profiles in the liver with respect to both a single gene and gene ontology of cellular components; (2) to identify biological pathways or co-regulated gene sets associated with the pathophysiology of diabetes to gain a more comprehensive understanding of genetic and environmental alterations; and (3) to identify novel functional hepatic genes that may regulate the pathophysiology of diabetes by comparing independent SAGE libraries in combination with DNA chip analyses. Such SAGE-based approaches may lead to the identification of novel therapeutic targets for the treatment of type 2 diabetes and its complications.
Takamura
Toshinari
T
Department of Disease Control and Homeostasis, Kanazawa University Graduate School of Medical Science, Kanazawa, Ishikawa 920-8641, Japan. ttakamura@m-kanazawa.jp
Misu
Hirofumi
H
Yamashita
Taro
T
Kaneko
Shuichi
S
D000818:Animals; D015415:Biomarkers / Q000378:metabolism; D003924:Diabetes Mellitus, Type 2 / Q000378:metabolism*; D020869:Gene Expression Profiling / Q000639:trends*; D006801:Humans; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*; D020543:Proteome / Q000378:metabolism*; D015398:Signal Transduction; D014157:Transcription Factors / Q000378:metabolism*
D015415:Biomarkers; D020543:Proteome; D014157:Transcription Factors