Research Article |
Open Access |
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Bioinformatic Analysis of Alzheimer’s Disease and Type2 Diabetes Mellitus: A
Bioinformatic Approach |
Allam Appa Rao 1, Siva Prasad Akula 2, Hanuman Thota 2, Srinubabu Gedela 1* |
1International Center for Bioinformatics and Center for Biotechnology, Andhra
University College of Engineering (Autonomous),
Visakhapatnam-530003, India |
2Department of Computer Sciences and Engineering, Acharya Nagarjuna University, Guntur-522510, India |
| *Corresponding author : |
Dr. Srinubabu Gedela, International Center for Bioinformatics,
Center for biotechnology, College of Engineering,
Andhra University, Visakhapatnam- 530 003,
Andhra Pradesh,
India, Phone : +91-891-2844204 (Off), Fax : +91-891- 2747969;
Email : srinubabuau6@gmail.com |
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| Received April 20, 2008; Accepted May 15, 2008; Published May 25, 2008 |
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Citation: Allam AR, Siva PA, Hanuman T, Srinubabu G (2008) Bioinformatic Analysis of Alzheimer’s Disease and Type2
Diabetes Mellitus: A Bioinformatic Approach. J Proteomics Bioinform S1: S050-S054. doi:10.4172/jpb.s1000009 |
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Copyright: © 2008 Allam AR, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and
source are credited. |
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We evaluated the role of several proteins that are likely to be involved in alzheimers disease (AD) and type 2 diabetes mellitus
(T2DM). By employing multiple sequence alignment using Clustalw tool, we have constructed a phylogenetic tree based on the
functional protein sequences extracted form NCBI. The phylogram was constructed using neighbor joining algorithm. Our
bioinformatic analysis reported that the two proteins such as AChE and BChE are playing major role in both the diseases out
of ten common proteins between these two diseases. Our in silico study may pave way for new therapeutic interventions/biomarker
identification in alzimers disease associated diabetes mellitus. |
Keywords |
| Bioinformatics; type 2 diabetes mellitus; Alzheimer’s disease |
Introduction |
Butyrylcholinesterase (BChE) is increased in the cerebral cortex
of Alzheimer’s disease (AD) patients, particularly those carryingå4 allele of the apolipoprotein E gene (ApoE) and certain BuChE
variants that predict increased AD risk and poor response to anticholinesterase
therapy.( Darreh-Shori, et al 2006 ). Measured
BChE activity and protein level in CSF of eighty mild AD patients
in relation to age, gender, ApoE å4 genotype, cognition
and cerebral glucose metabolism (CMRglc). BuChE activity was
23% higher in men than women (p < 0.03) and 40–60% higher
in ApoE å4 negative patients than in those carrying one or two å4
alleles (p < 0.0004). CSF BuChE level correlated with cortical
CMRglc. Patients with high to moderate CSF BuChE showed
better cognitive function scores than others. They hypothesize
that CSF BuChE varies inversely with BuChE in cortical amyloid
plaques. Thus, low BuChE in a patient’s CSF may predict
extensive incorporation in neuritic plaques, increased neurotoxicity
and greater central neurodegeneration.
Acetylcholinesterase and butyrylcholinesterase activities
emerge in association with plaques and tangles in Alzheimer’s
disease. These pathological cholinesterases, with altered properties,
are suggested to participate in formation of plaques ( Mariam
F. Eskander. et.al.2005). It is evident from the preceding discussion
that acetylcholinesterase and butyrylcholinesterase are
present in various regions of the brain and are increased in the
brains of patients with Alzheimer’s disease. Furthermore, the
activities of these two enzymes seem to be closely associated
with the disease activity itself. Thus, higher the activity of acetylcholinesterase
and butyrylcholinesterase, more severe the
manifestationsof Alzheimer’s disease and increasing number of
cortical and neocortical amyloid-rich neuritic plaques and neurofibrillary
tangles( Guillozet A.et.al.1997, Greig NH.et.al.2005).
It is interesting to note that changes in the activities of acetylcholinesterase
and butyrylcholinesterase have also been
reported in other diseases Acetylcholinesterase was found to be
about an order of magnitude higher in islets of Langerhans
than in the exocrine tissue in rat pancreas. This difference in
activity was found in rats made diabetic with streptozotocin as
well as in the controls ( Godfrey DA .et.al.1975).( Abbott et al 1993) reported that the activity of serum butyrylcholinesterase
was significantly elevated in both type 1 (8.10 ± 3.35 units/ml)
and type 2 (7.22 ± 1.95 units/ml) diabetes compared with the
control subjects (4.23 ± 1.89 units/ml) (P < 0.001). In addition,
serum butyrylcholinesterase activity correlated with serum
fasting triacylglycerol concentration and insulin sensitivity in
patients with type 1 and type 2 diabetes. On the other hand, in
non-diabetic subjects with butyrylcholinesterase deficiency
serum triacylglycerol levels were in the normal range. These
results suggested that butyrylcholinesterase might have a role
in the altered lipoprotein metabolism in hypertriglyceridaemia
associated with insulin insensitivity or insulin deficiency in
diabetes mellitus( Sanchez-Chavez G.et.al.2000).
In contrast, streptozotocin diabetes did not affect acetylcholinesterase
activity in the retina but increased its activity
in the cerebral cortex (100%) and in serum (55%), and decreased
it by 30-40% in erythrocytes. The butyrylcholinesterase activity
was decreased by 30-50% in retina and hippocampus and to a
lesser extent in retinal pigment epithelium from rats treated with
streptozotocin for one week. The changes noted in cholinesterase
activities were not correlated with the fasting blood glucose
concentration. These results suggest that diabetes might influence
a specific subset of cells and isoforms of cholinesterases
that could lead to alterations associated with diabetes complications
(Sanchez-Chavez G.et.al.2001). It was also reported that
the butyrylcholinesterase K variant allele was more common
among Type II diabetic subjects than non-diabetic subjects suggesting
that the close association of the butyrylcholinesterase gene
(3q26) with Type II diabetes could be related to an identified
susceptibility locus on chromosome 3q27 but independent of islet
function(Sanchez-Chavez G.et.al.2001).
Since elevated serum butyrylcholinesterase activity is
elevated in the diabetic rat, mouse and humans, Dave and Katyare
studied the source of the increased level of butyrylcholinesterase
and reported that in alloxan- induced diabetic animals both the serum and cardiac butyrylcholinesterase activities were increased
2.2- to 2.8- fold with almost no significant change in the activity
of the enzyme after insulin treatment compared with controls
(Dave KR, Katyare SS.et.al.2002). Furthermore, correlation
analysis showed that butyrylcholinesterase activity was positively
correlated with age, sex, body mass index, hypertension and diabetes,
as well as with
triglycerides, total cholesterol, low-density lipoprotein cholesterol
and apolipoprotein B (Apo B), whereas a step-wise multiple
regression analysis revealed that the only risk factors for
coronary heart disease that showed independent correlations with
butyrylcholinesterase activity were, in descending order of importance, Apo B, triglycerides, and diabetes. These findings reinforce
the idea that butyrylcholinesterase activity is associated
with lipoprotein synthesis, hypertension, and diabetes (Alcantara
VM .et.al.2002).
Above studies explains that AD and T2DM share several
molecular processes that underlie the respective degenerative
developments. In silico studies have established a pathway for
in vivo/in vitro studies for identification of proteins, having
therapeutic significance. Recent technological advances in
genetics, genomics, proteomics, and bioinformatics offer great
opportunities for biomarker discovery (Srinubabu et al, 2007).
In the present study we have reported the common proteins
involved in AD and T2DM. |
Sl.No |
Gene name |
Accession ID |
Length |
Tissue Type |
1 |
ACHE |
AAH94752 |
640 aa |
Brain, hypothalamus |
2 |
APOE |
AAB59546 |
317 aa |
liver and blood |
3 |
BCHE |
AAH08396. |
64aa |
Brain, primitive neuroectodermal |
4 |
CETP |
AAB59388 |
425aa |
Liver |
5 |
GAL |
AAC09250 |
318aa |
Blood |
6 |
HGF |
AAA52649 |
290aa |
lambda gt10 |
7 |
IDE |
AAA52712 |
1019aa |
Hepatoma |
8 |
MMP2 |
AAH02576 |
660aa |
Brain, neuroblastoma |
9 |
MMP9 |
AAH06093 |
707aa |
Primary B-Cells from Tonsils |
10 |
NGFB |
AAI26151 |
241aa |
Pooled, cerebellum, kidney, placenta,testis, lung, colon, liver, heart, thyroid, bladder,uterus, |
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Table 1: List of proteins Involved in AD and T2DM |
|
Methods |
| Based on the available literature we have collected 10
known proteins (table 1), which are believed to be involeved in
pathogenesis of AD and T2DM. The functional protein sequence
in FASTA forms for these genes are collected from NCBI (National
Center for Biotechnology Information http://
www.ncbi.nih.nlm.gov). These sequences are given to clustalw
http://www.ebi.ac.uk/clustalw) for the multiple sequence alignment
(it calculates that the best match for the selected sequences,
and lines them up so that the identities, similarities and differences
can be seen). Based on this result the score table and phylogeny
tree are derived. The phylogeny shows the distance between
the protein sequences. The protein sequences with minimum
distance are AChE & BChE (figure 1). |
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Figure 1: shows the relationship between the preoteins by using cladogram tree between Alzeimers and type 2 Diabetes.
|
|
Discussion |
| AD and T2DM are conditions that affect a large number of people
in developed and developing countries. Both conditions are on
the increase, and finding novel treatments to cure or prevent them
are a major aim in research. Somewhat surprisingly, AD and
T2DM share several molecular processes that underlie the respective
degenerative developments. ( Tahirovic I et al 2007) performed
the role of oxidative stress in the pathogenesis of metabolic
diseases like diabetes mellitus and its complications, as well
as in neurodegenerative disorders like AD and reported that the
oxidative stress alterations in the brain of STZ-induced rats and
humans with AD could be useful in the search for new drugs in
the treatment of AD that have antioxidant activity. The misfolding
of proteins plays an important role in both diseases, Our
bioinformatic analysis hypothesize that the close distance association
between AChE and BChE may modify the risk for AD in
individuals with T2DM. In a similar in silico study conducted by
(Wang Y and Klemke RL, 2008), demonstrated that PhosphoBlast
is a versatile mining tool capable of identifying related phosphorylation signatures and phosphoamino acid mutations among
complex proteomics datasets in a highly efficient and accurate
manner. Phosphoblast will aid in the informatics analysis of the
phosphoproteome and the identification of phosphoprotein
biomarkers of disease. So bioinformatic studies like multiple sequence
alignment and Phosphoblast analysis will aid in the
informatics analysis of the protein and the identification of new
therapeutic interventions/ protein biomarkers of the disease. |
Conclusions |
|
While the identification of these candidate proteins involved in
AD and T2DM is an important in silico milestone, follow up
studies are required for validation in a larger population of individuals
and for determination of laboratory-defined sensitivity
and specificity values using novel proteomic and metabolomic
tools. As represented in figure 2, the combination of proteomic
and bioinformatic studies are useful for more accurate prediction
of biomarkers/new therapeutic targets. |
|
Figure 2: Schematic representation of the diabetic macrovascular complications with reference to bioinformatic and proteomic
approaches for therapeutic drug target identification and/or biomarker identification
|
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Acknowledgement |
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This work was supported by IIT up gradation grants of AUCE
(A). |
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