BIOL 6150 – Genomics and Applied Bioinformatics
Group Project: Microarray Analysis
Title: Identification of the Shear-and Side-specific genes related
to Aortic Valve Calcification
Group: Swetha Rathan, HaozhengTian, Sandra Baethke, WafaEldarrat
Background:
Aortic valve (AV) calcification is one of the major causes of morbidity and mortality in elderly
population[1, 2]. The primary risk factors for AV calcification include hypertension, congenital
defects like bicuspid AV, age, smoking, diabetes and chronic kidney disease[3, 4]. The AV
experiences dynamic mechanical environment with significant variations in pressure, bending and
shear on either side[5]. Under physiological conditions, these stimuli constantly renew and remodel
the valve. Any alterations to this mechanical environment have been shown to cause a disease
condition, eventually resulting in aortic stenosis (AS) and aortic regurgitation (AR)[6]. Several studies
have been done to characterize the role of shear stresses on vascular biology and have indicated that
low and oscillatory shear stress is atheroprone whereas high shear is atheroprotective[7-10]. It has
been speculated that the reduced shear stresses on the non-coronary leaflet of the AV due to the
lack of coronary flow are responsible for the increased susceptibility to calcification of that
leaflet[11].
Hypothesis: Adverse patterns of shear stress were found to upregulate inflammatory markers in
valve leaflet tissues, indicating that the fibrosa is more atheroprone compared to the ventricularis
side, which is also seen in calcified human valves.
Thus the hypothesis of our study is that the Human Aortic Valve Endothelial Cells of fibrosa side
(fHAVECs) when exposed to oscillatory shear stress expresses similar genes that are seen in the
calcified human AVs.
Data sets chosen:
For our comparison purposes, we have chosen two data sets as follows:
1. GSE26953 (4 data sets - 6 replicates per data set)[12]
This is the data was extracted from part of the study: Discovery of Shear- and Side-specific mRNAs
and miRNAs in Human Aortic Valvular Endothelial Cells. In this study the HAVECs from either
sides of the valve were exposed to different shear stresses (both atheroprotective and atheroprone).
The total RNA was collected and the miRNA and mRNA arrays were carried out to identify if there
are any differentially expressed shear and side specific miRNA and mRNA that could play a role in
AV disease progression. For our project purposes, we used only the mRNA data sets.
mRNA microarray data was available for different data sets such as
 fHAVEC exposed to OS (FO)
 vHAVEC exposed to OS (VO)
 fHAVEC exposed to LS (FL)
 vHAVEC exposed to LS (VL)
Where the HAVECs are the human aortic valve endothelial cells from either the fibrosa side or the
ventricularis side (fHAVECs or vHAVECs respectively). OS: Oscillatory shear stress( proatherogenic) and LS : Laminar shear ( atheroprotective).
2.
GSE12644 ( 2 data sets – with 3 or 4 replicates)[13]
This data set has been extracted from the study: Gene expression profile of normal and calcified
stenotic human aortic valves. This study was used to gene expression profiling of human aortic
valves in patients with or without aortic stenosis. The dataset was generated constituteda large-scale
quantitative measurements of gene expression in normal and stenotic human valves. The goal of this
study was to compare gene expression levels between the two groups and identified a list of genes
that are up-or down-regulated in aortic stenosis. For our project purposes we used the entire mRNA
microarray data set provided, which is the following

Human Aortic Valve – control (10 samples)

Human Calcified Aortic Valve (diseased) - (10 samples)
Objectives:
In this project, the first step was to do the microarray analysis and to identify the differentially
expressed genes within each data set.
Our comparison groups are
1. For the sheared HAVECs data set, we have the following groups
a. Overall differences between different shear stress : Oscillatory vs Laminar
b. Overall differences between the sides : Fibrosa and Ventricularis
For more specific comparisons, we did the following.
c. fHAVECsvsvHAVECs exposed to same shear stress – Oscillatory
d. fHAVECsvsvHAVECs exposed to same shear stress – Laminar
e. fHAVECs exposed to different shear stresses – Oscillatory vs Laminar
f. vHAVECs exposed to different shear stresses – Oscillatory vs Laminar
2. For the calcified and normal AV microarray data set, we compared the gene expression
profiles between normal and calcified human AVs.
From 1, Our comparisons a and b gives us the list of the differentially expressed genes that are shear
sensitive and side- dependent respectively. Comparisons c and d will give us the differentially
expressed genes that are side-dependent when exposed to same shear. Comparisons e and f will give
us the differentially expressed genes that are shear-dependent on the same side.
From 2, We will obtain the gene expression profiles that are expressed in diseased calcified genes.
In our further steps, we will retrieve all the genes from the ids of the array platforms and then
separately run the statistics to see if any of the shear conditions upregulate the gene expressions that
are related to AV calcification.
Project detailed steps:
We used the tutorial provided and followed all the steps in order to retrieve the data sets from the
GEO website. Briefly, we use the accession number of the paper with shear data, GSE26953, and
obtained the information of the experimental design. : 24 samples; n=6 for the following 4 groups:
FO, VO, FL, and VL (24 miRNA and 24 mRNA arrays.
We have downloaded the series matrix files in txt.gz format. Since gz format files are all zipped files,
use the 7 zip or any other unzipping program to extract files. We then formatted it according to the
specifications for the JMP genomics software, as provided in the tutorial.
Original, formatted and normalized data files attached:
The data files were formatted, standardized and used for further analysis. Following are the list of
files in the order of entire expression data, experimental design and normalized data for two
accession numbers. These files are also attached along with the differentially expression profile files.
GSE 12644 – Calcified vs. Normal human aortic valves
1. gse12644_disease_exp
2. gse12644_disease_expression_data
3. gse12644_disease_expression_std
GSE 26953 – Shear data
4. gse26953_shear_exp
5. gse26953_shear_gene_express_std
6. gse26953_shear_gene_expression
Identification of differentially expressed genes:
To identify the differentially expressed genes, we followed the instructions in the tutorial, and used the pFDR
– multiple testing method, one-way ANOVA for overall statistics, and t-test for individual pairs. Alpha: 0.05.
All the specific p-values, corresponding list and the file names are listed in the table as follows. Also
specifically the list of these genes were obtained by selecting only the genes that are expressed above the
threshold p-value (above the red line in the anova plots).
1. Overall differences between different shear stress : Oscillatory vs Laminar : Effect of
shear stress
2. Overall differences between the sides : Fibrosa and Ventricularis – overall side
specificity
3. fHAVECsvsvHAVECs exposed to same shear stress – Oscillatory – Effect of
oscillatory or pro-atherogenic on either sides.
4. fHAVECsvsvHAVECs exposed to same shear stress – Laminar – Effect of laminar
or atheroprotective shear on either sides.
5. fHAVECs exposed to different shear stresses – Oscillatory vs Laminar – Response of
fibrosa side to different shear stresses – pathological vs physiological shear stresses.
6. vHAVECs exposed to different shear stresses – Oscillatory vs Laminar - Response of
fibrosa side to different shear stresses – pathological vs physiological shear stresses
7. Fixed effect: calcified VS normal. Cell type: aortic valve – To identify the differentially
expressed genes in pathological conditions.
Parameter Table:
Each row in this table details the contents of each file. See individual files in attachment for
row level details.
Seria
l No
Group
-log10(pvalue)cutto
ff
Differentiall
y expressed
genes
1
Overall differences 2.57
between
different
shear
stress
:
Oscillatory
vs
Laminar
2
Overall differences
between the sides :
Fibrosa and
Ventricularis
2.56
11
3
fHAVECsvsvHAVE
Cs exposed to same
shear stress –
Oscillatory
2.608
4
4
fHAVECsvsvHAVE 2.86
Cs exposed to same
shear stress
–
Laminar
3
5
fHAVECs exposed 2.47
to different shear
stresses – Oscillatory
vs Laminar
1052
1929
Fold
Change
(See
individual
files)
DIFF
Column
details the
FOLD
CHANGE
for the
correspondin
g row for
each gene
DIFF
Column
details the
FOLD
CHANGE
for the
correspondin
g row for
each gene
DIFF
Column
details the
FOLD
CHANGE
for the
correspondin
g row for
each gene
DIFF
Column
details the
FOLD
CHANGE
for the
correspondin
g row for
each gene
DIFF
Column
details the
FOLD
CHANGE
for the
File name
attached
gse26953_between
shear all sides diff
expressed
gse26953_f-v all
shear diff
expressed
gse26953_oscillato
ry shear -f and v
diff expressed
gse26953_laminar
shear -f and v diff
expressed
gse26953_side f oscillatory and
laminar shear diff
expressed
6
vHAVECs exposed 2.675
to different shear
stresses – Oscillatory
vs Laminar
964
7
Calcified vs Normal 3.27
human AV
130
Principal Component Analysis:
1. GSE12644 : Calcified vs normal human AV samples
correspondin
g row for
each gene
DIFF
Column
details the
FOLD
CHANGE
for the
correspondin
g row for
each gene
DIFF
Column
details the
FOLD
CHANGE
for the
correspondin
g row for
each gene
gse26953_side v oscillatory and
laminar shear diff
expressed
gse12644 Diff
expressed _disease
genes
Heat Map:
2. GSE26953 :Sheared HAVECs sample data.
Heat Map:
GSE12644 : Calcified vs normal human AV samples
Eigenvalues and variance along each principal component axis (eigenvector)
PCA
PCA 1
PCA 2
PCA 3
2D Plots
Eigenvalue
17.466
0.738
0.324
% of Variance
87.3
3.7
1.6
3D plot
Blue: Normal aortic valve, Red: Calcified aortic valve
Figure 1
Figure 2
Figure 1 : A 87.3% of the variance is shown along the first principal component axis. Two
groupings are clearly demonstrated in the PCA, however the normal and diseased aortic valve (blue
and red respectively) are not the dividing factors. The grouping element is unknown.
Figure 2 : The PCA here demonstrates the third principle component axis with a variance of 1.6%.In
both Figure 1 and Figure 2 the second principle component axis captures a variance of 3.7%. The
PCA in both figures show that the normal aortic valves lie in the positive region and the calcified
aortic valves represented by the red balls have negative readings along both axis ranging from 0 to 0.5.
Figure 3
Figure 3: This PCA shows no obvious grouping among the variables.
GSE26953 : Sheared HAVECs sample data
Eigenvalues and variance along each principal component axis (eigenvectors)
PCA
PCA 1
PCA 2
PCA 3
Eigenvalue
7.105
6.212
2.028
% of Variance
29.6
25.9
8.5
2D plot
3D plot
Blue: Fibrosa, Oscillatory shear
Green: Ventricularis, Laminar shear
Red: Fibrosa, Laminar shear
Brown: Ventricularis, Oscillatory shear
Figure 1
Figure 2
Figure 1: The variables which were exposed to laminar and oscillatory shear are represented in the
PCA as two distinct groups. However there is no distinct pattern among the ventricularis and the
fibrosa tissue. Along the first principal component there is a 29.6% variance.
Figure 2: This PCA shows no grouping among the different aortic valves. Along the third principal
component there is a 8.5% variance.
Figure 3
The aortic valves exposed to the laminar shear (red and green) and the valves exposed to the
oscillatory shear (blue and brown) show up on either sides of the Y-axis, with the former being on
negative side and the later in the positive region. Again in this PCA we cannot identify a grouping
among the fibrosa and the ventricularis variables.
Gene Ontology and Pathway Analysis:
Steps:
The Pathway analysis was performed using PATH VISIO 2- with WIKIPATHS (Analysis Collection
Pathways) to identify any pathways containing up regulated/down regulated genes.
For GSE12466- Up regulated genes are blue and down regulated genes are red. A gradient color
scheme was applied. The up regulated genes were selected if the fold was > 1 and down regulated
genes were selected if fold was < -1. All probes were subject to -log(p-vaIue) > 1.3 selection criteria.
For GSE26593- down regulated genes were blue and up regulated genes were red. A gradient color
scheme was applied. Down regulated genes were selected if fold value < 0 and up regulated genes
were selected if fold value > 0. The fold values in these data sets were small. The selection for all
records was -log(p-value) > 1.3. Not all samples provided pathways using these methods. In some
cases no z value was calculated.
Other PATH ANALYSIS tools were also attempted. Cytoscape, David, GenMapp CS Files and
GSEA. GenMApp CS provided output similar to PATHVISIO but did not seem to provide an easy
way to determine which paths could be used- in other words it displayed all paths- 181 of them.
GSEA- This one utility needed the original affymetrix probe data for all samples but only containing
the selected genes . We had used the JIMP data which did not contain this level of detail. The
original JIMP tables containing the affymetrix and illumina data contain all original probes not just
the selected probes. Most of these utilities need excel data saved as tab delimited files. JIMP files
cannot be read into them and we cannot access jump from home. David did not seem to provide
pathway 'pictures' and deciphering the output did not seem easy. We also tried using GOEAST for
Pathway Analysis, but could not get a decent diagram for GSE12466 (Calcified vs healthy Aortic)
with more than 10 genes. We also couldn't get a diagram for the other study GSE26593 Osc vs
Laminar data. GOEAST was abending or gave errors after waiting a long awhile.
However, with whatever different analysis we performed, we nailed it down to the following
important pathways and processes that regulated by the genes in response to different treatments or
conditions, which are explained in detail below.
Pathways:
GSE12644 (Calcified vs Healthy Human AVs)
Pathway regulated
Wnt Signaling Pathway and Pleuripotency
Statin Pathway
Senescence and Autophagy
Myometrial Relaction and Contraction
Focal Adhesion
Fatty Acid Beta Oxidation
Apoptosis
GSE26953 -Fibrosa side: Oscillatory vs Laminar
Nucelotide metabolism
Serotonin Receptor 2 & ELK-SRF/GATA4 signaling
Blood Clotting Cascade
FAS Pathway & Stress Induction
Tryptophan Metabolism
AD Signaling Pathway
Serotonin Receptor 4-6-7-and NR3C Signaling
Apoptosis Modulation
Compliment and Coagulation Cascades
Osteopontin Signaling
Heart Development
Fatty Acid Biosythesis
Wnt Signaling
GSE26953-Ocsillatory Shear on Fibrosa and Ventricularis
sides
No Pathways identified
GSE26953- Ventricularis side: Oscillatory & Laminar Shear
Serotonin Receptor 2 and ELK-SRF/GATA4 signaling
Blood Clotting Cascade
Tryptophan metabolism
Serotonin Receptor 4/6/7 and NR3C Signaling
Heart Development
miRs in Muscle Cell Differentiation
Nucleotide Metabolism
ID signaling pathway
Complement and Coagulation Cascades
Fatty Acid Beta Oxidation
Osteopontin Signaling
Fatty Acid Biosynthesis
Endochondral Ossification
Integrated Pancreatic Cancer Pathway
Androgen receptor signaling pathway
Selenium Pathway
Wnt Signaling Pathway
G Protein Signaling Pathways
GSE26953 - Laminar Shear - fibrosa and ventricularis
No Pathways found
Gene Ontology:
Calcified vs Normal Human AV samples: We first generated a list of processes and the
associated number of genes that are altered or regulated in the calcified valves compared to normal
valves. Following are the important biological functions and the corresponding number of genes
associated with them that are significantly upregulated in calcified human AVs compared to normal
human AVs. This data has been sorted based on two parameters: Important processes related to
valve physiology and pathology as well as the p-value. This list will be used as a guide to test our
hypothesis if the oscillatory shear on fibrosa side would trigger any of the genes that are associated
with the calcified valves.
Ontology
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
cellular_component
molecular_function
molecular_function
molecular_function
Term
cardiovascular system development
response to wounding
response to chemical stimulus
response to stress
cell migration
wound healing
cellular process
negative regulation of response to stimulus
inflammatory response
response to stimulus
tissue morphogenesis
osteoblast differentiation
angiogenesis
wound healing, spreading of epidermal cells
wound healing, spreading of cells
heart development
regulation of cell proliferation
response to external stimulus
negative regulation of antigen processing and
presentation
regulation of nitric oxide mediated signal
transduction
ossification
cell differentiation
extracellular matrix
extracellular matrix structural constituent
platelet-derived growth factor binding
SMAD binding
No. of
Genes
22
21
30
33
15
12
88
15
12
54
12
5
8
3
3
9
16
13
p-value
2.18E-10
3.67E-10
1.71E-07
1.87E-07
1.98E-07
1.55E-06
3.35E-06
3.35E-06
5.05E-06
2.14E-05
8.27E-05
0.001503143
0.002444354
0.003180017
0.003180017
0.00575483
0.006280226
0.006280226
2
0.006280226
2
6
23
183
17
11
5
0.006280226
0.015182975
0.015424909
9.93E-24
4.07E-18
5.34E-17
0.003407602
Sheared HAVECs:
We obtained the processes and the associated number of genes, which are regulated by different
treatments: Laminar vs shear as well as side-dependent. But since we are looking at the treatment
conditions that may potentially cause calcification, which is the effect of oscillatory shear on fibrosa
side, we narrowed our ontology list based on the above table and listed the most relevant and
important processes as follows.
1. Overall shear response: Oscillatory vs Laminar
Ontology
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
Term
regulation of cellular process
developmental process
translation
cellular response to stimulus
multicellular organismal development
anatomical structure development
system development
blood vessel development
vasculature development
signaling
cell communication
angiogenesis
regulation of signaling
cell motility
cellular lipid metabolic process
regulation of cell proliferation
intracellular protein transport
cell migration
negative regulation of metabolic process
regulation of signal transduction
cardiovascular system development
cell death
cell differentiation
negative regulation of cell cycle
cellular homeostasis
negative regulation of cell proliferation
regulation of cell migration
regulation of cell motility
cellular response to stress
No. of
genes
p
615
262
78
312
234
209
177
35
35
284
291
25
92
39
57
71
51
35
69
83
45
66
120
38
45
38
19
19
51
8.45E-34
7.73E-13
9.77E-13
3.09E-12
7.57E-11
3.09E-10
1.47E-08
1.85E-08
3.83E-08
6.98E-08
7.20E-08
1.13E-06
1.94E-06
2.59E-06
5.50E-06
1.06E-05
1.11E-05
1.20E-05
1.26E-05
1.58E-05
2.26E-05
9.42E-05
0.000145769
0.000615823
0.000650469
0.000678886
0.003357046
0.003357046
0.00797229
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
cellular_component
cellular_component
cellular_component
cellular_component
cellular_component
molecular_function
molecular_function
molecular_function
negative regulation of cell communication
cell-matrix adhesion
nitric oxide metabolic process
negative regulation of signal transduction
negative regulation of transcription, DNAdependent
regulation of MAP kinase activity
cell cycle
tissue homeostasis
negative regulation of signaling
negative regulation of hormone metabolic
process
negative regulation of smooth muscle cell
migration
tissue development
regulation of cell growth
negative regulation of blood coagulation
negative regulation of hemostasis
cell proliferation
Ras protein signal transduction
negative regulation of response to stimulus
wound healing
cell development
chemical homeostasis
regulation of programmed cell death
regulation of cell death
regulation of actin polymerization or
depolymerization
ion transmembrane transport
regulation of I-kappaB kinase/NF-kappaB
cascade
response to oxidative stress
cell
cell part
intracellular
intracellular part
endomembrane system
phosphotransferase activity, alcohol group as
acceptor
antioxidant activity
nucleoside-triphosphatase regulator activity
23
16
5
22
0.020000129
0.026543478
0.030876446
0.031319124
30
18
66
7
22
0.032141373
0.034176127
0.036313315
0.040350696
0.04130435
3
0.04189894
3
52
26
5
5
37
17
24
17
43
37
45
45
0.04189894
0.045163795
0.047520856
0.048777412
0.048777412
0.049297913
0.057022382
0.062378208
0.081455496
0.081615089
0.081727329
0.088334937
0.090526108
10 0.09069631
8 0.091831322
16 0.091831322
16 0.091831322
1357
2.98E-166
1357
2.98E-166
1230
4.80E-165
1199
1.07E-161
141
5.04E-12
93
1.57E-08
10 0.065424983
38 0.091831322
2. Fibrosa side: Oscillatory vs Laminar shear:
Ontology
Term
No. of
genes
p - value
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
cellular process
regulation of cellular process
response to stimulus
cellular component organization
multicellular organismal development
response to stress
cellular response to stimulus
gene expression
anatomical structure development
translation
signal transduction
cell communication
cell motility
cell migration
regulation of signal transduction
regulation of cell cycle
negative regulation of gene expression
regulation of gene expression
regulation of response to stimulus
regulation of cell communication
response to wounding
regulation of cell migration
regulation of cell motility
lipopolysaccharide-mediated signaling
pathway
negative regulation of blood coagulation
angiogenesis
nucleocytoplasmic transport
nuclear transport
cardiovascular system development
regulation of cell proliferation
lipid transport
positive regulation of macromolecule
metabolic process
regulation of coagulation
cell differentiation
cellular homeostasis
lipid localization
regulation of response to external
stimulus
positive regulation of response to
external stimulus
positive regulation of MAP kinase
activity
regulation of wound healing
571
340
241
115
141
93
179
83
122
44
155
167
25
23
51
36
26
125
58
34
31
14
14
3.49E-57
8.01E-19
4.25E-12
4.84E-09
7.93E-09
2.79E-08
3.52E-08
2.26E-07
3.73E-07
4.50E-07
3.57E-06
1.67E-05
7.28E-05
0.000120665
0.000195557
0.000222076
0.000329267
0.000425113
0.000498521
0.001408852
0.001408852
0.002100465
0.002100465
4
5
13
14
14
25
38
14
0.00522278
0.005312838
0.006336822
0.006676118
0.007394041
0.007571576
0.011687283
0.012033119
38
6
67
26
14
0.012434336
0.012434336
0.012981489
0.019414487
0.021018667
10
0.034446655
6
0.034446655
10
5
0.034446655
0.041267336
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
cellular_component
cellular_component
cellular_component
cellular_component
cellular_component
cellular_component
cellular_component
cellular_component
molecular_function
molecular_function
molecular_function
molecular_function
anatomical structure morphogenesis
gene silencing
cellular response to stress
positive regulation of endothelial cell
migration
regulation of MAP kinase activity
cell death
apoptotic process
cell
cell part
intracellular
intracellular part
nucleosome
membrane-bounded vesicle
extracellular region
cell junction
transition metal ion binding
oxidoreductase activity, acting on paired
donors, with incorporation or reduction
of molecular oxygen
L-ascorbic acid binding
calcium ion binding
46
6
30
0.04722417
0.049849136
0.057586055
3
12
34
31
744
744
669
647
9
32
88
31
134
0.05883972
0.059244202
0.064616034
0.065829318
1.85E-90
1.85E-90
1.69E-86
5.68E-82
0.006395077
0.007490244
0.009427704
0.026179387
0.000126894
13
6
55
0.006676118
0.006767938
0.007160141
3. Fibrosa vs Ventricularis side: Oscillatory shear
Ontology
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
biological_process
Term
regulation of catabolic process
cytoplasmic sequestering of NF-kappaB
fatty acid alpha-oxidation
regulation of Cdc42 protein signal transduction
regulation of Cdc42 GTPase activity
negative regulation of transmembrane transport
negative regulation of protein import into nucleus
negative regulation of NF-kappaB import into nucleus
negative regulation of transcription factor import into nucleus
cytoplasmic sequestering of transcription factor
negative regulation of I-kappaB kinase/NF-kappaB cascade
negative regulation of nucleocytoplasmic transport
negative regulation of intracellular protein transport
regulation of Rho GTPase activity
positive regulation of Ras GTPase activity
positive regulation of Rho GTPase activity
positive regulation of GTPase activity
positive regulation of protein complex assembly
negative regulation of intracellular transport
genes p
2 0.032616666
1
0.08034134
1 0.080861475
1 0.080861475
1 0.080861475
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.085464824
1 0.086473584
1 0.087431714
biological_process
molecular_function
molecular_function
molecular_function
molecular_function
regulation of NF-kappaB import into nucleus
Rac GTPase activator activity
NF-kappaB binding
Rac GTPase binding
Rho GTPase activator activity
1
1
1
1
1
0.092939231
0.08034134
0.085464824
0.085464824
0.094580619
Discussion:
We were able to generate pathway as well as the gene ontology details for all our comparison groups.
PCA analysis indicated that calcified vs healthy human AVs sample data are distinctly grouped into
two. Further pathway analysis showed that these calcified samples expressed genes that involved in
the Apoptosis, Wnt signaling, oxidation and statin pathways. These pathways when altered have
been known to be involved in the AV disease progression[6]. Further gene ontology revealed that,
the calcified valves expressed genes that negatively alter basic cell functions such as cell death,
proliferation, migration and development apart from the process that are associated with disease
initiating pathways such as angiogenesis, inflammation (via NF-KB pathway), apoptosis, ossification
and osteogenesis. These results are also in good agreement with the published results[13].
In order to test our hypothesis, which is fibrosa side when exposed to oscillatory shear stress,
expresses genes involved in AV disease progression, we primarily focused on the following groups
1. Overall shear effects: oscillatory vs laminar shear stress
2. Fibrosa: oscillatory vs laminar shear stress
3. Oscillatory shear stress: Fibrosa vs Ventricularis
We observed that when fibrosa was exposed to oscillatory vs laminar shear stress, some of the
pathways associated with disease were identified, such as osteopontin, wnt signaling, serotonin
receptor pathway, blood coagulation inducer, which were not observed on ventricularis side.
Further, specifically, the processes related to anatomic development were seen preferentially on
fibrosa when exposed to oscillatory shear. This can be justified stating that, although fibrosa and
ventricularis sides are part of the same valve, their composition differs, partly due to the
conditioning of the different mechanical stimuli and partly due to genetics. Perhaps, this can also
explain the preferential inflammation and calcification of the fibrosa side, under altered mechanical
stimuli, compared to ventricularis side, as also reported in an ex vivo study[7].
Genes involved in other functions such as cell cycle, migration, development, proliferation were
expressed in all different groups, but at different levels (or numbers). However, the published results
indicated other novel mechanosensitive pathways that were not detected by our analysis. This could
be due to the differences in the analysis softwares ( such as using JIMP vs SAM, open source tools
for pathways and ontology vs using Ingenuity Pathway Analysis etc)[12]. Albeit the differences in the
pathways identified, we found some of the common pathways between fibrosa exposed to
oscillatory shear and calcified human valves. This thus indicated that fibrosa when exposed to low
magnitude disturbed shear stresses such as low oscillatory shear can express genes that are involved
in AV disease progression. The negative effects of low magnitude oscillatory shear has been
observed even in the atherosclerosis of blood vessels, suggesting that AV disease progression can
potentially share some similarities with that of atherosclerosis[14].
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