Bioinformatics assessment of Functional Genes/Prote ins Involved in Obesity-Induced Type 2 Diabetes
PDF (174 KB) 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 accessThe 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.
KeywordsBioinformatics tools functional genes obesity and
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