Bioinformatics assessment of Functional Genes/Prote ins Involved in Obesity-Induced Type 2 Diabetes

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Year 2013 Vol 2 Issue 1
Document Type :
¹Ehab M Abdella 1 ²Rasha R Ahmed 1 ³ Mohamed B Ashour 2 ⁴Osama M Ahmed 2,3 ⁵Sameh F AbouZid 4 ,
¹Cell Biology and Histology Divisio
²Cell Biology and Histology Divisio
³ Physiology Division, Zoology Department, Faculty of Science, Beni-Suef University
⁴ Physiology Division, Zoology Department, Faculty of Science, Beni-Suef University 3 Faculty of Oral & Dental Medicine, Nahda University , Beni-Suef, Egyp
⁵Pharmacognocy Department, Faculty of Pharmacy, Beni-Suef University, Beni-Suef, Egypt
Abstract
: Worldwide, the incidence of type-2 diabetes is risi ng rapidly, mainly because of the increase in the incidence of obesity, which is an imporant risk factor for this condition. Both obe sity and type-2 diabetes are complex genetic traits but they also s hare some nongenetic risk factors. Differences amon g individuals in their susceptibility to both these conditions proba bly reflect their genetic constitutions. The dramat ic improvements in genomic and bioinformatic resources are acceleratin g the pace of gene discovery. It is tempting to spe culate the key susceptible genes/proteins that bridges diabetes me llitus and obesity.

In this regard, we evaluated the role of several genes/proteins that a re believed to be involved in the evolution of obes ity associated diabetes through thorough literature search. Also w e analyzed the data pertaining to genes of these pr oteins extracted from the databases that are available onl ine for free access
The functional cDNA sequences of these genes/proteins are extracted from National Center for Biotechnology Information (NCBI) and Ens embl Genome Browser. Our bioinformatic analysis reports 21 genes as ominous link with obesity associated di abetes. Also this study indicated that, adipose tissue is n ow known to express and secrete a variety of metabo lites, hormones and cytokines that have been implicated in the deve lopment of insulin resistance. CONCLUSION: This bioinformatic study will be useful for future studi es towards therapeutic inventions of obesity associ ated type-2 diabetes.
Keywords
Bioinformatics tools functional genes obesity and type 2 diabetes
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