The Vasculome of the Mouse Brain

Article · December 2012with136 Reads
DOI: 10.1371/journal.pone.0052665 · Source: PubMed
The blood vessel is no longer viewed as passive plumbing for the brain. Increasingly, experimental and clinical findings suggest that cerebral endothelium may possess endocrine and paracrine properties - actively releasing signals into and receiving signals from the neuronal parenchyma. Hence, metabolically perturbed microvessels may contribute to central nervous system (CNS) injury and disease. Furthermore, cerebral endothelium can serve as sensors and integrators of CNS dysfunction, releasing measurable biomarkers into the circulating bloodstream. Here, we define and analyze the concept of a brain vasculome, i.e. a database of gene expression patterns in cerebral endothelium that can be linked to other databases and systems of CNS mediators and markers. Endothelial cells were purified from mouse brain, heart and kidney glomeruli. Total RNA were extracted and profiled on Affymetrix mouse 430 2.0 micro-arrays. Gene expression analysis confirmed that these brain, heart and glomerular preparations were not contaminated by brain cells (astrocytes, oligodendrocytes, or neurons), cardiomyocytes or kidney tubular cells respectively. Comparison of the vasculome between brain, heart and kidney glomeruli showed that endothelial gene expression patterns were highly organ-dependent. Analysis of the brain vasculome demonstrated that many functionally active networks were present, including cell adhesion, transporter activity, plasma membrane, leukocyte transmigration, Wnt signaling pathways and angiogenesis. Analysis of representative genome-wide-association-studies showed that genes linked with Alzheimer's disease, Parkinson's disease and stroke were detected in the brain vasculome. Finally, comparison of our mouse brain vasculome with representative plasma protein databases demonstrated significant overlap, suggesting that the vasculome may be an important source of circulating signals in blood. Perturbations in cerebral endothelial function may profoundly affect CNS homeostasis. Mapping and dissecting the vasculome of the brain in health and disease may provide a novel database for investigating disease mechanisms, assessing therapeutic targets and exploring new biomarkers for the CNS.
11 Figures
The Vasculome of the Mouse Brain
Shuzhen Guo
*, Yiming Zhou
, Changhong Xing
, Josephine Lok
, Angel T. Som
, MingMing Ning
Xunming Ji
, Eng H. Lo
1Neuroprotection Research Laboratory, Departments of Radiology and Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts,
United States of America, 2Broad Institute, Massachusetts Institute of Technology and Harvard Medical School, Boston, Massachusetts, United States of America,
3Department of Pediatrics, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 4Clinical Proteomics Research
Center, Department of Neurology, Massachusetts General Hospital, Harvard Medical School, Boston, Massachusetts, United States of America, 5Cerebrovascular Research
Center, XuanWu Hospital, Capital Medical University, Beijing, Peoples Republic of China
The blood vessel is no longer viewed as passive plumbing for the brain. Increasingly, experimental and clinical findings
suggest that cerebral endothelium may possess endocrine and paracrine properties – actively releasing signals into and
receiving signals from the neuronal parenchyma. Hence, metabolically perturbed microvessels may contribute to central
nervous system (CNS) injury and disease. Furthermore, cerebral endothelium can serve as sensors and integrators of CNS
dysfunction, releasing measurable biomarkers into the circulating bloodstream. Here, we define and analyze the concept of
a brain vasculome, i.e. a database of gene expression patterns in cerebral endothelium that can be linked to other databases
and systems of CNS mediators and markers. Endothelial cells were purified from mouse brain, heart and kidney glomeruli.
Total RNA were extracted and profiled on Affymetrix mouse 430 2.0 micro-arrays. Gene expression analysis confirmed that
these brain, heart and glomerular preparations were not contaminated by brain cells (astrocytes, oligodendrocytes, or
neurons), cardiomyocytes or kidney tubular cells respectively. Comparison of the vasculome between brain, heart and
kidney glomeruli showed that endothelial gene expression patterns were highly organ-dependent. Analysis of the brain
vasculome demonstrated that many functionally active networks were present, including cell adhesion, transporter activity,
plasma membrane, leukocyte transmigration, Wnt signaling pathways and angiogenesis. Analysis of representative
genome-wide-association-studies showed that genes linked with Alzheimer’s disease, Parkinson’s disease and stroke were
detected in the brain vasculome. Finally, comparison of our mouse brain vasculome with representative plasma protein
databases demonstrated significant overlap, suggesting that the vasculome may be an important source of circulating
signals in blood. Perturbations in cerebral endothelial function may profoundly affect CNS homeostasis. Mapping and
dissecting the vasculome of the brain in health and disease may provide a novel database for investigating disease
mechanisms, assessing therapeutic targets and exploring new biomarkers for the CNS.
Citation: Guo S, Zhou Y, Xing C, Lok J, Som AT, et al. (2012) The Vasculome of the Mouse Brain. PLoS ONE 7(12): e52665. doi:10.1371/journal.pone.0052665
Editor: Cesar V Borlongan, University of South Florida, United States of America
Received September 25, 2012; Accepted November 20, 2012; Published December 2 , 2012
Copyright: ß2012 Guo 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.
Funding: This study was supported by studies funded in part by grants from the NIH (RC2-NS69335, R37-NS37074, R01-NS76694, P01-NS55104), the Claflin award
from Massachusetts General Hospital, the Phyliss and Jerome Lyle Rappaport MGH Research Scholar award, the Beijing Natural Science Foundation, and the China
National Basic Research 973 Program. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing Interests: The authors have declared that no competing interests exist.
* E-mail: (SG); (EHL)
In recent years, mechanistic investigations into brain function
and disease have shifted away from a purely ‘‘neurocentric’’ focus
into a more integrative perspective that involves all cell types in the
central nervous system [1,2,3,4]. For example, interactions
between neurons and glia are required for normal neurotransmis-
sion as well as remodeling and recovery after brain injury [5].
Signals from astrocytes and pericytes provide important regulatory
mechanisms for the blood-brain barrier [6,7,8]. And overlapping
mediators underlie crosstalk between neurogenesis, angiogenesis,
and common patterning of neural and blood vessel architectures
Blood vessels in the brain are no longer viewed as passive or
inert plumbing to simply carry blood flow for oxygen and glucose
delivery. Increasingly, it is now recognized that the cerebral
endothelium provide a rich source of signaling and trophic factors
that influence brain function. Cerebral endothelium can produce
growth factors that promote neurogenesis [10]. Cerebral endo-
thelium can release neuroprotective factors such as brain derived
neurotrophic factor (BDNF) and fibroblast growth factor (FGF)
that defend neurons against a wide range of metabolic and toxic
insults [11,12,13,14]. Conversely, ‘‘sick’’ endothelium can con-
tribute to CNS disease. In diabetes, oxidatively stressed cerebral
endothelium produce lower levels of neurotrophic factors that may
lead to increased neuronal susceptibility to stroke and neurode-
generation [15]. Dysfunctional microvessels and disrupted blood-
brain barrier function have been proposed to worsen neuronal
dysfunction in Alzheimer’s disease and amyotrophic lateral
sclerosis [16,17,18]. Hence, understanding the full functional
profile of cerebral endothelium may be extremely important for
investigations into CNS physiology and pathophysiology.
To date, many studies of brain endothelial gene expression have
been performed. The majority of these efforts primarily focus on
the blood-brain barrier [19,20,21], some of them are from the
microvascular fragments [22]. However, a broader approach that
connects the entire vascular blueprint to brain function and disease
has not been attempted. Here, we propose the concept of a brain
PLOS ONE | 1 December 2012 | Volume 7 | Issue 12 | e52665
vasculome, i.e. a systematic mapping of transcriptome profiles of
endothelial cells from brain in comparison with those from two
other major organs, the heart and kidney glomeruli, in order to
potentially reveal differential vascular function at a whole genome
level. Our database here is then dissected to assess the hypothesis
that the brain vasculome may contribute to CNS disease in terms
of mechanisms and circulating biomarkers.
Quality Control of Vasculome Gene Expression
Two levels of quality control were assessed. First, quality and
integrity of RNA samples were tested with standard NanoDrop
and Bioanalyzer approaches to ensure sufficient RNA concentra-
tions, 260/280 ratios, 28 s/18 s ratios and RNA integrity number
(RIN) scores. Second, the quality of microarray hybridization was
also assessed by manually checking the distribution of hybridiza-
tion signals, percentage of positive signals, ratio of 39to 59end of
housekeeping genes (GAPDH and b-Actin), and applying princi-
pal component analysis to identify potential outliers. All samples
passed these various checkpoints. For the final data sets, RNA
from n = 5 mice were pooled per microarray, and n = 3 in-
dependent microarrays were used for each group (see Methods).
Next, we asked whether our vasculome was contaminated by
parenchymal cells. For the brain vasculome, we compared our
data with gene markers for different brain cells in public GEO
GSE13379 datasets [23,24], that contain gene expression profiles
for neurons, astrocytes and oligodendrocytes. This analysis
demonstrated that genes known to be representative of neurons,
astrocytes and oligodendrocytes had extremely low expression
levels (signals ,50,) in our brain vasculome, whereas gene markers
of endothelial cells had much higher expression levels than others
(Table 1). These data suggest that our brain vasculome is
endothelial-specific and not contaminated by surrounding paren-
chymal brain cells. Another check of endothelial purity was
performed using RT-PCR to assess the expression of gene markers
in the vasculome from brain, heart and kidney glomeruli (Table
S1). Compared to corresponding whole organ tissue, each
vasculome had higher expression of endothelial markers ($3
fold), whereas gene expression levels were enriched for neuron and
astrocyte markers in whole brain samples; myocyte markers in
heart tissue samples; and kidney tubular markers in kidney tissue
samples, respectively (Figure S1). Taken together, these analyzes
suggest that the various organ vasculomes were not overtly
contaminated with parenchymal genes.
Brain Vasculome Specific Genes and Enriched Pathways
Although the microarrays revealed a large amount of data, we
only focused on genes whose maximal expression values across all
microarrays were greater than 200. Based on these criteria, we
identified 3,557 genes expressed in brain endothelial cells. Next,
we asked whether this brain vasculome differed from patterns
found in our comparative heart and kidney glomerular vascu-
lomes. Applying criteria of p,0.01, fold change $4, and maximal
expression value across all samples .200, we identified 318 probes
corresponding to 243 genes found to be highly expressed in brain
endothelial cells, 143 probes corresponding to 110 genes highly
expressed in heart endothelial cells, and 114 probes corresponding
to 81 genes highly expressed in kidney glomerular endothelial cells.
A heat-map analysis demonstrated that each vasculome was highly
organ-specific. Gene expression patterns in the brain vasculome
significantly differed from those in heart or kidney glomeruli
(Figure 1).
In the brain vasculome, as expected, blood-brain barrier genes
were easily detected. These included occludin (OCLN) and
claudin-5 (CLDN5), two major components of tight junctions in
the blood-brain barrier. Another known feature of cerebral
endothelium is the presence of glutamate receptors that influence
barrier function [25,26,27]. In our datasets, both ionotrophic and
metabtrophic glutamate receptors (Gria2, Gria3, Grin2b and
Grm5 for AMPA2, AMPA3, NMDA2B and mGluR5 respectively)
were specifically expressed in the vasculome from mouse brain but
not heart and kidney glomeruli. Overactivation of glutamate
receptors may cause excitotoxicity in neuronal compartments.
Similarly, activation of NMDA or mGluR5 receptors could also
mediate vascular responses caused by hyperhomocysteinemia and
nitrosative stress in brain endothelial cells [28,29]. The glutamate
transporter Slc1a1 (solute carrier family 1, member 1), known as
EAAC1/EAAT3, was also enriched in the brain vasculome. In
neurons, this transporter plays a key role in regulating synaptic
glutamate kinetics. But vascular functions may also exist, since
brain endothelial cells co-cultured with astrocytes displayed
a polarized brain-to-blood transport of glutamate, suggesting that
transporter responses in brain microvessels may participate in the
regulation of potentially excitotoxic amino acid concentrations
[30]. Overall, the brain vasculome demonstrated many mediators
commonly found in neural systems. For example, semaphorins
comprise a family of factors that control neurite extension and
axon guidance [31,32]. Here, we saw that Sema3C and Sema4D
were enriched in the vasculome of brain compared to heart and
kidney. Both Sema3C and Sema4D have been implicated in
angiogenesis regulation [33,34,35,36], so their involvement in
brain vascular homeostasis may also be important. Finally,
another parallel with neural signaling may also be underscored
by the detection of CamKIIa(calcium/calmodulin-stimulated
protein kinase II alpha) [37,38], indicating that common responses
to intracellular calcium fluxes may occur in both neuronal and
non-neuronal systems in the brain.
Using the Fisher’s exact test to probe GO (Gene Ontology) and
KEGG databases, many signaling and regulatory pathways were
found to be enriched in the brain vasculome (Table 2). These
included transporter activity, cell adhesion molecules (CAMs), and
the Wnt signaling pathway. Besides well-known brain endothelial
transporters such as Glut1 (glucose transporter type 1, or slc2a1,
solute carrier family 2, member 1) and P-gp (multidrug resistence
poly-glycoprotein, or Abcb1a, ATP-binding cassette, sub-family B,
member1A), high levels of transferrin (Tf), transferrin receptor
(TfR) and exporter ferroportin (slc40a1) were also detected in the
brain vasculome. For cell adhesion molecules, NrCAM (neuronal
cell adhesion molecule) appeared to be enriched in the brain
vasculome. NrCAM was originally known as a neuron-specific
gene required for axon guidance and organization of neural
circuitry [39,40,41]. However, NrCAM has recently been
discovered in dermal and umbilical venous endothelium as well,
with potential function in angiogenesis regulation and stress
response in endothelial cells [42,43]. The presence of NrCAM in
our initial draft of the brain vasculome but not the heart or
glomerular vasculome, further suggest close interactions and
potential crosstalk between vascular systems and the organ milieu
they inhabit. Similar enrichment in membrane proteins was found
in the neurexin network. We detected the expression of neurexin
and neuroligin in our mouse brain vasculome. In particular,
neurexin-1 showed high level of expression in the brain vasculome
rather than heart and kidney vasculomes. Once again, expression
of neural-related guidance systems in the brain vasculome suggests
crosstalk and signaling functions between blood vessels and brain
parenchyma [36,44].
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In addition to physiologic pathways that underlie normal
function, pathophysiologic pathways related to inflammation were
also expressed in the brain vasculome. In the context of brain
injury and neurodegeneration, cytokines and chemokines com-
prise a key network for regulating inflammation. In this vasculome
project, 236 probes were screened for 150 cytokines/chemokines.
Overall, low signals were detected for most cytokines/chemokines
(,50). Applying the criteria of signal intensity .200, only 17
probes for 11 cytokines/chemokines were expressed in the normal
mouse brain vasculome - ccl3, ccl9, ccl27, csf1, cxcl12 (SDF1), kitl,
pdgfb, pglyrp1, ptn, socs7 and tgfb2 (Table 3). Compared to heart
and kidney glomeruli, ccl3 (chemokine (C-C motif) ligand 3), ccl27
(chemokine (C-C motif) ligand 27) and pglyrp1 peptidoglycan
recognition protein 1) appeared to be enriched in the brain
vasculome (Table 3). Examination of the existing literature
suggested that these may be relevant hits. Ccl3 is released by
stimulated brain endothelial cells [45], and it has been reported
that it may be elevated in brain vessels of Alzheimer’s disease
patients [46]. CCL27 is well known for mediating skin in-
flammation but has also been detected in the brain [47]. Unlike
other chemokines, CCL27 has both secreted and nuclear targeting
forms that directly modulate transcription of many response genes,
thus any involvement of this factor in the brain vasculome could
potentially act as a potent amplifier of inflammation [48,49].
PGLYRPs (or PGRPs, peptidoglycan recognition proteins) have
four isoforms, PGLYRP1-4, that function in antibacterial immu-
Table 1. Differential expression of cell-type specific markers in brain vasculome versus other cell types in brain.
Cell Type Symbol Probe ID Brain vasculome Astrocyte Neuron Oligodendrocyte
astrocyte 2900052N01Rik 1436231_at 3.3209 12.1724 5.5117 5.5370
astrocyte Acsbg1 1422428_at 3.8742 10.2979 7.1814 6.9079
astrocyte Gfap 1440142_s_at 2.9647 12.4009 7.2991 7.2095
astrocyte Gjb6 1448397_at 3.3301 12.3716 8.2681 8.2473
astrocyte Slc39a12 1436611_at 2.9493 12.4861 8.6637 8.8039
astrocyte Ttpa 1427284_a_at 3.5321 9.9466 4.9249 4.2301
Neuron Crh 1457984_at 4.0607 9.8493 11.7976 10.5446
Neuron Hs3st2 1438624_x_at 3.2656 6.0426 10.2390 8.5537
Neuron Htr2c 1435513_at 3.4612 6.2973 10.2024 8.5207
Neuron Mal2 1427042_at 3.6787 9.1258 11.7147 10.1006
Neuron Necab1 1437156_at 2.6924 7.0119 10.7180 8.6910
oligodendrocyte Cldn11 1416003_at 5.4823 7.4864 8.6126 12.2323
oligodendrocyte Ermn 1436578_at 3.7956 5.3308 6.6879 11.9959
oligodendrocyte Ermn 1440902_at 2.4515 8.0862 9.0134 13.4799
oligodendrocyte Mag 1460219_at 3.4820 4.6254 8.2041 10.7587
oligodendrocyte Opalin 1435854_at 4.5864 6.0679 6.8508 12.1927
oligodendrocyte Pdgfra 1421917_at 4.8939 5.8151 8.1136 10.0721
oligodendrocyte S1pr5 1449365_at 4.3481 6.1865 8.1488 12.0642
oligodendrocyte Sox10 1451689_a_at 4.2181 6.0325 7.4529 10.7882
oligodendrocyte Tmem125 1434094_at 3.4232 3.7906 5.6062 11.1095
oligodendrocyte Ugt8a 1419063_at 4.8300 5.4295 9.0736 12.6444
endothelial Cdh5 1422047_at 10.2706 2.1884 2.1632 2.1702
endothelial Cdh5 1433956_at 8.5466 2.1817 2.1886 2.1702
endothelial Cldn5 1417839_at 11.6755 3.2007 4.8258 3.6992
endothelial Flt1 1419300_at 10.3308 2.1824 2.6425 2.1702
endothelial Flt1 1440926_at 9.9110 2.2568 2.3708 2.1702
endothelial Flt1 1451756_at 10.5391 2.1877 2.9728 2.2005
endothelial Flt1 1454037_a_at 11.6309 2.1818 2.1800 2.1702
endothelial Nos3 1422622_at 7.3330 5.6658 4.4708 5.0355
endothelial Ocln 1448873_at 9.9552 2.2325 2.5422 2.1702
endothelial Pecam1 1421287_a_at 10.0662 2.1817 2.1626 2.1702
endothelial Tek 1418788_at 11.3776 2.2534 2.7882 2.2962
endothelial Vwf 1435386_at 10.7795 2.7833 3.9346 4.0555
Note: Numbers for log2 signal intensity. Except for brain vasculome, all other data are listed from GSE13379 of GEO (Doyle JP et al. 2008 and Dougherty JD et al. 2010).
Brain vasculome represents mean value of 3 samples, astrocyte represents mean value of 6 samples, neuron represents mean value of 23 samples, oligodendrocyte
represents mean value of 4 samples. Well-established markers for neurons, astrocytes or oligodendrocytes are highly expressed in their corresponding cell types, while
all neuronal,. Astrocytic and oligodendroglial genes have extremely low expression levels (or not detectable) in the brain vasculome. In contrast, endothelial markers are
highly expressed in the vasculome and show low levels in other types of cells.
Mapping the Brain Vasculome
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nity and inflammation [50]. PGLYRP1 can bind with the key
stress response proteins such as Hsp70 and S100A4 to trigger
cytotxicity for antibacterial activity [51,52]. Expression pglyrp1 in
the brain have been reported, but its endothelial function is
currently unknown [53].
Another inflammatory example was found in pathways involved
in leukocyte transendothelial migration (Figure 2A). The brain
vasculome-enriched genes in this pathway included Ncf1 (neutro-
phil cytosolic factor1, or p47 phox), Prkcb (protein kinase C, beta)
and Prkcc (protein kinase C, gamma). Ncf1 is a subunit of
NADPH oxidase, a critical enzyme for ROS production in injured
or diseased vascular systems [54,55]. It was reported that Ncf1
mediated the Abeta42 and RAGE ligation induced ROS pro-
duction and downstream ERK1/2 phosphorylation and cPLA2
(cytosolic phospholipase A2) phosphorylation in cerebral endothe-
lial cells [56]. The PKC family is known to regulate the
phosphorylation and uptake of SLC6 family of neurotransmitter
transporters [57], also reported to be present in brain endothelial
cells and regulate the blood-brain barrier [58,59,60]. Whether
Prkcb and Prkcc in the brain vasculome contribute to disease
phenomena involved in cerebral ischemia, brain injury and
neurodegeneration remains to be fully elucidated.
Finally, a prominent network that was enriched in the brain
vasculome comprised the Wnt pathway (Figure 2B). Wnt is known
to regulate neuronal stem cells, neurogenesis and neuroplasticity
[61,62,63,64]. But recently, Wnt signaling has been reported to
also participate in the development of CNS vasculature, blood-
brain barrier formation, and the protection of endothelial cells
after injury [65,66,67,68,69]. In our draft of the brain vasculome,
b-cantenin (CTNNB1) was presented in the hub position of the
Wnt protein-protein interaction network, along with brain
endothelial-specific genes Axin2, MAPK10 (mitogen-activated
protein kinase 10) and Lef1 (lymphoid enhancer binding factor
1). Axin2 is a transcriptional target of active Wnt signaling that
also serves to autoregulate and repress the pathway by promoting
b-cantenin degradation [70]; In the conditional transgenic mice
Figure 1. The vasculome of mouse brain is unique and different from those found in mouse heart and kidney. Heatmap for
visualization of the expression levels of organ-specific endothelial genes across brain, heart and kidney glomeruli. X-axis represents individual
samples and y-axis represents different genes. The expression levels of genes are indexed by color.
Mapping the Brain Vasculome
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Table 2. Enriched pathways detected in the vasculome of mouse brain.
pvalue log2 odd ratio GO term GO category
1.94E-28 4.34 membrane part Cellular Component
1.09E-27 4.18 membrane Cellular Component
8.93E-27 4.24 intrinsic to membrane Cellular Component
2.21E-25 4.10 integral to membrane Cellular Component
9.93E-09 5.07 cell junction Cellular Component
6.22E-15 3.47 transport Biological Process
7.04E-13 7.41 cell-cell signaling Biological Process
5.45E-11 4.60 ion transport Biological Process
1.14E-07 2.42 cell communication Biological Process
1.63E-05 2.22 anatomical structure development Biological Process
3.41E-13 4.40 transporter activity Molecular Function
4.81E-12 4.95 substrate-specific transmembrane transporter activity Molecular Function
1.71E-11 4.57 transmembrane transporter activity Molecular Function
3.99E-10 4.60 ion transmembrane transporter activity Molecular Function
3.90E-05 2.27 signal transducer activity Molecular Function
pvalue log2 odd ratio KEGG pathway
2.67E-06 7.43 Cell adhesion molecules (CAMs)
1.57E-03 5.15 Leukocyte transendothelial migration
3.50E-03 10.95 Alzheimer’s disease
6.24E-03 3.84 Wnt signaling pathway
9.72E-03 5.09 Adherens junction
Note: Analysis based on brain endothelial specific genes in the mouse brain vasculome. These enriched pathways suggest that specific pathways and mechanisms are
selectively enhanced in brain compared to heart and kidney glomerular vasculomes.
Table 3. List of cytokines/chemokines expressed in the vasculome of mouse brain.
log2 signal intensity
Probe ID Entrez ID symbol description brain heart glomeruli
1419561_at 20302 Ccl3 chemokine (C-C motif) ligand 3 7.8736 4.9617 3.6407
1430375_a_at 20301 Ccl27 chemokine (C-C motif) ligand 27 8.7402 6.5498 6.4454
1449184_at 21946 Pglyrp1 peptidoglycan recognition protein 1 9.5253 4.9028 3.9403
1448823_at 20315 Cxcl12 chemokine (C-X-C motif) ligand 12 7.6783 7.6424 5.0764
1417936_at 20308 Ccl9 chemokine (C-C motif) ligand 9 7.9595 6.8725 5.3389
1450414_at 18591 Pdgfb platelet derived growth factor, B polypeptide 8.0818 7.5771 7.3091
1460220_a_at 12977 Csf1 colony stimulating factor 1 8.2981 9.2830 10.8936
1415855_at 17311 Kitl kit ligand 8.4188 8.2296 7.1033
1426152_a_at 17311 Kitl kit ligand 8.4408 8.0339 7.2815
1439084_at 20315 Cxcl12 chemokine (C-X-C motif) ligand 12 8.4423 7.7932 4.9062
1415854_at 17311 Kitl kit ligand 9.0837 9.3912 8.0980
1448117_at 17311 Kitl kit ligand 9.4871 9.5402 8.4600
1455402_at 192157 Socs7 suppressor of cytokine signaling 7 9.5695 9.2669 9.7154
1450923_at 21808 Tgfb2 transforming growth factor, beta 2 9.6153 7.9357 7.7813
1448254_at 19242 Ptn pleiotrophin 10.3194 6.4970 9.9998
1417574_at 20315 Cxcl12 chemokine (C-X-C motif) ligand 12 11.9791 11.4499 7.9319
1416211_a_at 19242 Ptn pleiotrophin 12.3765 7.9964 11.9745
Note: The first three factors (Ccl3, Ccl27, Pglryp1) are enriched in brain versus heart and kidney glomerular vasculomes.
Mapping the Brain Vasculome
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overexpressing b-Catenin, Axin2 is one of the antagonists changed
in the brain [71]. MAPK10 was originally described in neurons
but it was recently reported to also mediate endothelial migration
via eNOS [72]. And Lef1 is the specific transcriptional factor in
the downstream effectors of the Wnt pathway [73,74]. A critical
role of Wnt signaling in cell-cell communication can also be seen
because its central hub b-Catenin also serves in the protein-protein
interaction network for adherens junctions (Figure 2C) for brain
endothelial cells, linking specifically with the brain vasculome
genes of Igf1r (insulin-like growth factor 1 receptor), Tgfbr1
(transforming growth factor, beta receptor 1) and Lef1 in this
Angiogenesis and the Brain Vasculome
In terms of functional networks, angiogenesis should comprise
a central part of any vasculome. Probing the GO database
revealed a dense protein-protein interaction network for angio-
genesis-related genes in the brain vasculome, with hub positions
occupied by b-catenin, Rtn4, HIF-1a, Mapk14, Notch1, Ptk2
(protein tyrosine kinase 2, also called focal adhesion kinase 1) and
Tgfbr2 (Figure 3A). As described in above, b-catenin is highly
expressed in the brain and in the hub positions of other pathways,
connecting angiogenesis with these pathways, including Wnt
pathway and adherens junctions. Also, Rtn4 (also called Nogo) was
highly expressed in the brain. Rtn4 produces 3 isoforms (Nogo-A,
Nogo-B, Nogo-C) that may play overlapping roles in vascular as
well as neuronal systems in the CNS. Nogo-A is a well-
characterized inhibitor of axonal growth and repair [75], whereas
Nogo-B is already known to be highly expressed in endothelial
cells [76]. Nogo-B regulates vascular homeostasis and remodeling,
in part by controlling endothelial cell migration, macrophage
infiltration, leukocyte transmigration, and overall inflammation
response after tissue ischemia and injury [76,77,78]. Overall,
Nogo-B may be protective since it is lost after injury [76].
Another angiogeneis gene with high expression levels in the
brain vasculome is Gpx-1 (glutathione peroxidase 1), an in-
tracellular antioxidant enzyme that converts hydrogen peroxide to
water [79]. Various studies with Gpx-1 transgenic mice suggest
that this mediator may be neuroprotective against amyloid toxicity
[80], Parkinsons-related pathologies [81], ischemia-reperfusion
[82], or trauma [83]. These underlying mechanisms of vascular
neuroprotection may broadly include amelioration of cell death,
suppression of astrocyte and microglia activation, preservation of
BBB function, and a reduction of inflammatory infiltration
Figure 2. Protein-protein interaction (PPI) networks in the vasculome of mouse brain. A, PPI network for leukocyte transendothelial
migration. B, PPI network for the WNT signaling pathway. C, PPI network for adherence junctions. The expression levels of genes in the vasculome of
mouse brain are indexed by color.
Mapping the Brain Vasculome
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[82,84,85]. Furthermore, Gpx-1 may also contribute to CNS
recovery, in part by interacting with hypoxia inducible factor 1
(HIF-1) and its target genes such as VEGF to regulate the
angiogenesis process for tissue repair [86]. Gpx-1-deficient mice
show decreased recruitment and activation of endothelial pro-
Figure 3. Angiogenesis networks. A, Protein-protein interaction network for angiogenesis in the vasculome of mouse brain (including nearest
neighbors). Circles for genes in angiogenesis and squares for the neighbor genes. The expression levels of genes in the vasculome of mouse brain are
indexed by color. B, Heatmap comparison of expression profiles of genes in the VEGF signaling pathway from the vasculome of mouse brain, heart
and kidney glomeruli. The expression levels of genes are indexed by color.
Mapping the Brain Vasculome
PLOS ONE | 7 December 2012 | Volume 7 | Issue 12 | e52665
genitor cells after ischemic injury, leading to impaired angiogenesis
and revascularization [87].
Within the CNS context, VEGF signaling may be especially
important because this mediator may participate in both
angiogenesis as well as neurogenesis [88,89]. Comparison of
VEGF signaling pathways showed that these were highly
conserved across all three vasculomes in brain, heart and kidney
glomeruli (Figure 3B). This may not be surprising since VEGF-
mediated angiogenesis may be commonly required network
regardless of organ systems. However, it is worth noting that
there were two VEGF signaling mediators that appeared to be
specifically expressed in the brain vasculome - Prkcb and Prkcc.
These two signals were also identified in the leukocyte transen-
dothelial migration network of the brain vasculome (see previous
section). Thus, it is possible that particular brain vasculome-
specific components may critically influence how the CNS
responds to injury and disease. Angiogenesis is a physiological
process involving the growth of new blood vessels. This
phenomenon is vital not only for organ development but also for
tissue repair and wound healing. Insofar as the brain vasculome
may be a critical component of CNS plasticity and remodeling,
these angiogenesis networks may represent a rich database to
probe for potential mechanisms and targets for neurorecovery
after stroke, brain injury or neurodegeneration.
Correlation between Brain Vasculome and CNS Disease
Associated Genes
Genome-wide association studies (GWAS) provide valuable
information for identifying molecular risk factors and mechanisms
for many diseases [90]. For CNS disorders, however, GWAS may
be complicated by the fact that disease processes operate not only
in neuronal cells but also in other cells from glial and vascular
compartments. In the context of stroke and neurodegeneration,
pathophysiologic mechanisms are increasingly known to take place
in the neurovascular system [1,2,3,4,16]. So we next asked
whether GWAS-defined genes for major CNS diseases could be
found in our initial draft of the mouse brain vasculome. Genes
implicated in Alzheimer’s disease (AD), Parkinson’s disease (PD)
and stroke were compiled from the Database of Genotypes and
Phenotypes (dbGaP) at NCBI. A substantial portion of these
disease genes was expressed in the brain vasculome –41 AD genes,
53 PD genes and 133 stroke genes (Table 4; complete gene list is
provided in Table S2). Representative genes are briefly surveyed
Alzheimer’s Disease. CD2-associated protein (CD2AP), as
an adapter molecule, is mainly studied in kidney glomeruli. It is
highly expressed by podocytes and binds with nephrin to maintain
glomerular slit diaphragm function. Mice lacking CD2AP exhibit
a congenital nephritic syndrome at early age of 3 weeks [91]. In
other tissues, including brain and heart, CD2AP is located in
endothelial or epithelial cells, but the functions of CD2AP in brain
and heart are still unknown [92].
PAKs (p21-activated kinases), comprising two subfamilies and at
least 6 members (PAK1-6), are serine/threonine protein kinases
that act downstream of Rho family GTPases Cdc42 and Rac.
PAK2 (also known as gamma-PAK), bind with actin and become
activated in response to a variety of stresses, and these responses
have been implicated in regulation of cytoskeletal structure,
apoptosis angiogenesis, vascular integrity and endothelial cell
contraction [93,94,95,96]. PAK2 deletion leads to cerebral
hemorrhage in redhead zebrafish and this defect is rescued by
endothelial-specific expression of PAK2, demonstrating the
important role of PAK2 in brain vessels [94].PAK2 may also
mediate the VEGF-induced increase of vascular permeability [97].
In the brain, PAK1-3 was reported to regulate the morphology of
embryonic cortical neurons, whereas inhibiting Pak activity
causing misorientation and branching process of neurons, with
increased numbers of nodes, terminals and length of processes
[98]. In this regard, PAK may represent yet another example of
overlaps between neural and vascular signals in AD pathophys-
Ataxin-1 (ATXN1), is a causative gene for spinocerebellar
ataxia type 1 (SCA1), with mutation of expanded CAG tri-
nucleotide repeats encoding a polyglutamine tract (polyQ) in the
gene [99]. ATXN1 is expressed in both brain and non-neuronal
tissues, and may participate in calcium homeostasis, glutamate
signaling/excitotoxicity, and Notch signaling pathways [100,101]
through the regulation of transcriptional repression and protein
degradation [102,103,104]. In primary neuron cultures, knock-
down of ATXN1 significantly increases Ab40 and Ab42, with
increased APP cleavage by b-secretase; while overexpression of
ATXN1 decreases Ablevels [105]. The role of ATXN1 in
endothelial cells is not presently well understood, so whether
vascular responses in ATXN1 may also affect Abhomeostasis
remains unknown.
Angiomotin (AMOT), first identified as a binding protein to
angiostatin, is a transmembrane protein associated with actin.
AMOT controls cell migration and motility, cell polarity, tight
junction formation and angiogenesis, and also plays critical roles in
the tumor suppressor Hippo pathway [106,107,108]. AMOT is
expressed mostly in endothelial cells and in some epithelial cells,
with two protein isoforms, p80 and p130 [109]. The ratio of the
two isoforms may regulate the switch between migration and
stabilization of endothelial cells [110,111]. Most of Amot knockout
mice die between embryonic day E11 and E11.5 and exhibit
severe vascular insufficiency in the intersomitic region as well as
dilated vessels in the brain [81]. Whether AMOT contributes to
dysfunctional remodeling of brain vessels in the face of progressive
Table 4. Expression of disease-related genes in the vasculome of mouse brain.
Alzheimer’s disease Parkinson’s disease stroke
GWAS genes in dbGAP 274 364 920
GWAS genes in mouse HomolGene 198 264 643
GWAS genes in mouse M430 2.0 178 239 596
GWAS genes in brain vasculome 41 53 133
p value 0.017 0.016 0.00019
odds ratio 1.50 1.42 1.45
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Alzheimer’s neurodegeneration is a hypothesis that remains to be
fully assessed.
STK24 (sterile20-like kinase 24, also known as Mst3 (Mamma-
lian sterile 20-like kinase-3)) mediates the axon-promoting effects
of trophic factors, and may help regulate axon regeneration in
damaged neurons [112,113]. Stk24 has also been reported to
regulate cell morphology, migration and apoptosis [114,115,116].
In the context of AD or PD, Stk24 may contribute to neuronal
Tau phosphorylation, neurite outgrowth and synaptic plasticity
modulation by binding with LRRK2 (leucine-rich repeat kinase 2),
the most common genetic cause of PD [117]. Recently, Stk24 has
also been associated with vascular functions. Stk24, when linked
with striatin into a large signaling complex, acts as an essential
downstream effector of CCM signaling during cardiovascular
development. CCM3 is the disease gene for cerebral cavernous
malformations (CCMs), a condition that leads to characteristic
changes in brain capillary architecture resulting in neurologic
deficits, seizures, or stroke [118]. How these vascular effects
interact with neuronal phenomenon remains unclear.
Parkinson’s Disease. Regulator of G protein signaling
(RGS) proteins form a large family of GTPase-activating proteins
(GAP activity) for heterotrimeric G protein alpha subunits that
negatively regulate G-protein-coupled receptor signaling. RGS2
selectively accelerates the GTPase activity of Gq/11aand Gi/oa
subunits. RGS2 deficiency in mice leads to hypertension and
cardiac hypertrophy [119]. Endothelium-specific deletion of
RGS2 caused endothelial dysfunction with impaired EDHF-
dependent vasodilatation [120]. In the brain, both clinical and
animal models showed that lower RGS2 expression is associated
with anxiety disorders [121,122]. In neurons, RGS2 was reported
to regulate ionic channel function and synaptic plasticity in the
hippocampus [123,124,125,126]. But how RGS2 in brain vessels
interacts with neuronal sequelae in PD remains unknown.
HnRNP U (heterogeneous ribonuclear protein U, also scaffold
attachment facrot A, SFA) is a multi-functional nuclear matrix
protein that has been implicated in multiple inflammatory
pathways [127,128]. Proinflammatory toll-like receptor signaling
can stimulate the translocation of hnRNP U from nuclear to
cytoplasmic compartments, which then allows it to bind and
stabilize mRNA of various proinflammatory cytokines [129]. How
these inflammatory actions affect the brain vasculome in PD
remains to be determined.
RNF114 (RING finger protein 114, also as ZNF313, zinc finger
protein 313), first identified and reported in 2003, is an ubiquitin
binding protein and disease susceptibility gene for psoriasis, an
immune-mediated skin disorder [130]. RNF114 is reported to
regulate a positive feedback loop that enhances pathogenic double-
stranded RNA induced production of type 1 interferon by
modulating RIG-1/MDA5 signaling [131].
ITSN2 (intersectins 2), a Cdc42 guanine nucleotide exchange
factor (GEF), is a multidomain adaptor/scaffold protein involved
in clatherin- and caveolin-mediated endocytosis, exocytosis, actin
cytoskeleton rearrangement and signal transduction [132]. Several
isoforms of ITSN protein can be assembled from alternative
splicing, including a brain specific isoform [133]. A role of ITSN-
2L in regulating endocytosis within endothelial cells has been
reported [134].
PAK1 belongs to the family of p21 activated kinases. In
neurons, PAK1 is known to regulate migration [135,136], spine
morphogenesis and synapse formation [137], neuronal polarity
[138], and hippocampal long-term potentiation [139]. Besides
being a PD GWAS gene, PAK1 may also modulate or bind with
other disease proteins, including Fragile X mental retardation 1
(FMR1) for Fragile X syndrome (FXS), the most commonly
inherited form of mental retardation and autism [140]; Disrupted-
in-Schizophrenia 1 (DISC1) for schizophrenia [141]; ALS2/Alsin
for amyotrophic lateral sclerosis (ALS) [142], and Down syndrome
cell adhesion molecule (DSCAM) [143]. In endothelial cells,
PAK1 may regulate barrier function in different organs [144,145],
and the migration of endothelial cells during angiogenesis [146].
In the context of inflammation, Pak1 is known to assist the
invasion of Escherichia coli through human brain microvascular
endothelial cells [147,148].
Ubiquitin C-terminal hydrolase 5 (UCHL5), is one of the
proteasome 19S regulatory-particle-associated deubiquitinase.
Inhibiting the activity of UCHL5 leads to cell apoptosis by
altering Bax/Bcl-2 ratios and activating caspase-9 and caspase-3
[149]. Through Rpn13, UCHL5 is recruited in the 26 s
proteasome complex during the deubiquitination process. it is
reported to regulate the degradation of iNOS and IkappaB-alpha
and participated in the process of inflammation and host defense
regulation [150,151]. In the nucleus, UCHL5 is also associated
with human Ino80 chromatin-remodeling complex and kept in
inactive state, and then activated by transient interaction of the
Ino80 complex with proteasome, suggesting that it may cooperate
to regulate transcription or DNA repair [152]. UCHL5 interacts
with Smads and potentially reverse Smurf-mediated degradation;
it also stabilizes type 1 TGF-beta receptor and regulates TFG-beta
signaling [153]. It is possible that these inflammatory phenome-
nons may also be important in the brain vasculome.
TGF-beta signaling is necessary for the development of blood
vessels in many organs including brain and heart. Selective
deletion of TGF-beta in endothelial cells, but not in neural cells,
led to brain-specific vascular pathologies, including intracerebral
hemorrhage [154]. Inactivation of TGF-beta type II receptor
(Tgfbr2) in endothelial cells in mouse embryo resulted in deficient
ventricular separation and haemorrhage from cerebral blood
vessels [155]. At the same time, TGF-beta signaling is also
important for neural cells. In the midbrain, Tgfbr2 ablation results
in ectopic expression of Wnt1/b-Catenin and FGF8, activation of
Wnt target genes for regulating neural stem cell expansion [156].
These overlapping actions in neuronal and vascular compartments
may allow TGF-beta to play a key role as a PD GWAS gene.
Transcription factor 6 (ATF6) is one of the effectors of
endoplasmic reticulum stress [157]. Both oxidized LDL and
phospholipolyzed LDL can induce endoplasmic reticulum stress in
endothelial cells with ATF6 activation, and this process has been
implicated in the initiation of vascular inflammation with pro-
gression of atherosclerosis. Via endoplasmic reticulum stress,
ATF6 may also regulate responses in angiogenesis and expression
of tight junction proteins [158,159].
Stroke. BRM (Brahma), ATPase subunit in the chromatin-
remodeling complex SWI/SNF, has important role in gene
regulation, inflammation response, tumorigenesis and embryo
development and differentiation. BRM is preferentially expressed
in brain, liver, fibromuscular stroma and endothelial cell [160]. It
is reported that BRM and Brahma/SWI2-related gene 1(Brg1)
regulate HIF-1 induced gene expression after hypoxia [161]. Two
single nucleotide polymorphisms (SNP) sites were found to be
associated with schizophrenia in a Japanese population. A risk
allele of a missense polymorphism (rs2296212) induced a lower
nuclear localization efficiency of BRM, and risk alleles of intronic
polymorphisms (rs3793490) were associated with low SMARCA2
expression levels in the postmortem prefrontal cortex [162].
MBD2 belongs to family of methyl-CpG binding domain
(MBD)-containing factors, and mediate epigenetic effects through
gene expression regulation. It has been reported that MBD2 was
induced in hippocampus within few hours post-ischemia and
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maintained at high levels for several days [163]. Furthermore,
Mbd2 deficient mice were protected against hind-limb ischemia
evidenced by improved perfusion recovery and increased capillary
and arteriole formation [164]. In vitro experiment also confirmed
that knockdown of MBD2 significantly enhanced angiogenesis and
provided protection against H2O2-induced apoptosis [164].
NF-kb inhibitor kappa B alpha (NFKBIA, also known as IkB-
alpha) is the major regulator of NF-kB activation. Since NF-kBis
a central factor in the vast network of inflammation pathways, this
stroke GWAS gene is likely to contribute to multiple vascular
responses in the brain. In damaged endothelium, dynamic
response and inhibitory feedback loops exist between the rapid
increase of IkB-alpha and the original NF-kB signal [165]. Links
to oxidative stress and vasoregulation may also be important as
eNOS-derived nitric oxide can be an endogenous inhibitor of NF-
kB activity through IkB-alpha regulation [166].
WNK1, is a member of novel serine/threonine kinase family,
With-No-K(lysine), with pleiotropic actions. Intronic deletions in
WNK1 gene cause Gordon’s Syndrome, an autosomal dominant,
hypertensive and hyperkalemic disorder [167]. WNK1 poly-
morphisms have also been associated with common essential
hypertension [168]. Mechanistically, the WNK1 to ste20/SPAK/
OSR1 signaling cascade regulates cation-chloride cotransporters
(NKCC1-2), which may be vital for sodium homeostasis regula-
tion, blood pressure response and vascular contractions [168,169].
Endothelial-specific expression of WNK1 is essential for angio-
genesis and heart development in mice, as WNK1 deficiency leads
to cardiovascular developmental defects with smaller chambers
and reduced myocardial trabeculation, together with defective
angiogenesis in both arteries and veins [170]. Overlap with neural
responses may also be important. WNK1 mutations have been
identified as the cause of hereditary sensory and autonomic
neuropathy type II, an early-onset autosomal disease of peripheral
sensory nerves. WNK1 can interact with LINGO-1 (a component
of tripartite receptor complexes) to regulate nogo-induced in-
hibition of neurite extension, through activation of RhoA [171].
ADD1 is one of three adducin proteins. ADD1 is a well-known
hypertension risk gene. Altered adducin function might cause
hypertension through enhanced constitutive tubular sodium
reabsorption [172]. Polymorphisms of the ADD1 gene are
associated with many physiological responses in hypertensive
individuals as well as healthy subjects. For example, the Trp460
ADD1 allele is associated with higher systolic and diastolic blood
pressure [173], with increased incidence of peripheral arterial
disease (PAD) and coronary heart disease (CHD) [174], increased
carotid artery intima-media thickness (IMT) [175,176], increased
risk of stroke [176], and reduced acetylcholine-stimulated forearm
blood flow (FBF) response via an impaired endothelium-dependent
vasodilation [177]. Again, the study of variants in risk genes
suggested that there are physiological interaction between ADD1
and WNK1-NEDD4L pathways to regulate the renal sodium
handling, blood pressure and antihypertensive responses to drugs
[178]. Furthermore, the overexpression of rat wild type ADD1 in
endothelial cells Increased tube formation in vitro and enhanced
capillary formation in Matrigel implants in vivo, suggesting ADD1
could regulate angiogenesis process [179].
Among all of these disease genes, there are some with brain
vasculome specificity compared to heart and kidney glomeruli. For
example, the AD disease gene Pllp (plasma membrane proteolipid,
also known as transmembrane 4 superfamily member 11 or
plasmolipin), is a myelin structure protein and mainly expressed in
brain oligodendrocytes and kidney tubular epithelial cells [180]. It
was reported that pllp could form voltage-dependent and K(+)-
selective ion channels in the membrane, or act as entry receptor
for a kind endogenous retrovirous [181]. The expression of Pllp
was signifiacantly reduced in the temporal cortex of patients with
schizophrenia and patients with major depressive disorder,
suggesting its role in the mental disorders [182,183]. The PD
disease gene Foxf1 (forkhead box F1, also known as HFH-8 or
Freac-1), is a developmentally important transcriptional factor.
The deficiency of Foxf1 could cause severe abnormalities in the
development of many organs including lung, liver and gallbladder,
with reduced expression of intergrin-beta3 [184]. As the target of
hedgehog, foxf1 and its target gene Bmp4 mediate the induction of
vasculogenesis [185] or link hedgehog signaling with Wnt
signaling, to regulate the development of organs [186]. The
expression of foxf1 in endothelial cells has been reported, and may
regulate the inflammation response [187]. For stroke, Apcdd1,
Atp2b2, Axin2, ITIH-5 and Slc1a1 are specifically expressed in
brain vasculome. As previously discussed, Slc1a1 and Axin2 may
be involved in cerebral glutamate handling and vascular de-
velopment and patterning respectively. Apcdd1(adenomatosis
polyposis coli down-regulated 1), a membrane-bound glycopro-
tein, is the target gene of Wnt/b-Catenin signaling pathway
[188,189], also a novel inhibitor to Wnt signaling in a cell-
autonomous manner and acts upstream of b-Catenin [190].
Apcdd1 has an essential role in hair growth [190], or regulate
astro-gliogenesis in the brain [191]. ITIH 5 is one of heavy chain
subunits of Inter-alpha-trypsin inhibitors (ITIs), a family of serine
protease inhibitors. ITIHs stabilize the extracellular matrix (ECM)
by interacting with hyaluronic acid, which is a major ECM
component [192]. So far, ITIH molecules have been reported to
play a particulary important role in inflammation and carcino-
genesis [193]. ITIH5 may also be a regulator of human
metabolism, as the expression of ITIH5 in adipose tissue was
increased in obesity, and associated with measures of body size and
metabolism [194]. Hypermethylation in the upstream region of
the promoter-associated CpG island of ITIH5, has been detected
in breast cancer, and associated with adverse clinical outcome,
suggesting ITIH5 as a potential prognostic marker [195]. Atp2b2
is also known as PMCA2 for plasma membrane calcium-
transporting ATPase 2, encoding a plasma membrane Ca2+-
ATPase type 2 pump, which extrudes calcium from the cytosol
into the extracellular space. The mutation of Atp2b2 may cause
deafness and imbalance in mice probably by affecting sensory
transduction in stereocilia as well as neurotransmitter release from
the basolateral membrane [196]. In human primary endothelial
cells, Atp2b2 is found to bind with endogenous eNOS, leading to
the phosphorylation of eNOS and downregulation of its activity;
furthermore, NO production by endothelial cells was significantly
reduced by ectopic expression of Atp2b2 [197].
Overlap between Brain Vasculome and Plasma Protein
By acting as a sensor and integrator of brain dysfunction,
endothelial cells within the vast network of cerebral microvessels
may represent a critical contributor to CNS biomarkers in
circulating blood [198]. We compared our mouse brain vasculome
with four independent proteomic databases of human plasma
proteins (PMID16041672, PMID16335952, PMID16684767, and
PMID18632595) [199,200,201,202,203,204]. Protein products
corresponding to 754, 1211, 781, and 723 genes respectively,
were detected in the mouse brain vasculome (Table 5; complete
gene list is provided in Table S3). To be more conservative, we
defined a core plasma protein set as the intersection of all 4
databases. This yielded 387 proteins. Out of this core plasma
protein dataset, 100 proteins (25.8%) were expressed in the brain
vasculome. Whether these ‘‘hits’’ from the normal brain
Mapping the Brain Vasculome
PLOS ONE | 10 December 2012 | Volume 7 | Issue 12 | e52665
vasculome or future analyses of diseased brain vasculomes may
eventually lead to measurable biomarkers in blood remains to be
This study presented initial proof-of-concept for a brain
vasculome. The dense network of microvessels in the brain can
no longer be simply viewed as inert plumbing. Cerebral
endothelium may also be an important source of signaling and
trophic factors that communicate with the brain parenchyma.
Hence, the brain vasculome may offer a critical tool for
investigating how the neurovascular system contributes to the
physiology of normal brain function, the pathophysiology of
stroke, brain injury and neurodegeneration, as well as provide
a database for potential circulating biomarkers that are produced
by endothelium in CNS disorders. Our initial analyses suggest that
the mouse brain vasculome (1) is unique and significantly different
from heart and glomerular vascular systems; (2) is enriched in
many vital signaling networks; (3) includes key elements that may
contribute to CNS disorders; (4) contain many common genes that
have been identified in GWAS databases for stroke, AD and PD;
and (5) show significant overlap with plasma protein databases of
potential biomarkers in circulating blood.
Taken together, this proof-of-concept study suggests that, when
integrated with other genomic and proteomic databases, the brain
vasculome may provide a valuable tool for dissecting disease
mechanisms, assessing new therapeutic targets as well as searching
for new biomarkers in CNS disorders. Nevertheless, there are
several caveats that must be kept in mind. First, there is the
possibility of gene contributions from non-cerebral-endothelial cell
types. Comparisons with other neuronal and glial databases
suggest that this may not be a major problem. But we still can not
unequivocally exclude this potential source of false positives.
Second, although we only focus on endothelial cells in this initial
draft of the vasculome, the neurovascular system obviously
includes perivascular cells such as pericytes and smooth muscle
cells. How the brain vasculome interacts with and is regulated by
these other cells warrant deeper studies. Third, our database is
based on samples prepared from the entire brain cortex in order to
maximize signal-to-noise. But it is likely that the neurovascular
system differs in genomic status and function depending on brain
region. Whether higher resolution maps of the brain vasculome
can be rigorously obtained in the future remains to be determined.
Fourth, our vasculome will not operate in isolation but should
significantly interact with multiple systems in the entire body. Our
data already suggest that vasculome profiles are regulated by the
different milieus of each ‘‘host’’ organ. It is likely that the
vasculome would also interact with circulating blood cells insofar
as genomic signatures in circulating blood are affected by stroke,
trauma and various CNS disorders [205]. Fifth, the current draft
of our brain vasculome is focused only on mRNA, i.e. the
transcriptome. However, other modes of genomic information,
including single-nucleotide polymorphism (SNP), copy-number
variation (CNV), and epigenomics should also be studied and
integrated, in order to obtain a full molecular landscape of the
neurovascular system. Ultimately, proteomic and metabolic maps
of the brain vasculome should also be extremely useful. Finally, the
brain vasculome should be mapped across disease models and
states in stroke, brain trauma and neurodegeneration. The normal
vasculome presented here only provides a physiologic baseline.
Clearly, the vasculome is connected to CNS disease as suggested
by the significant overlaps with many GWAS studies of stroke, AD
and PD. Mapping the brain vasculome in aged and diseased
mouse models may allow us to understand how this system is
pathophysiologically affected by and responds to various triggers of
injury and disease.
In conclusion, this study provided initial proof-of-concept for
a mouse brain vasculome. Mapping and dissecting the full
profile of the brain vasculome in health and disease may
provide a novel database for investigating disease mechanisms,
assessing therapeutic targets and exploring new biomarkers for
the CNS.
Materials and Methods
Preparation of Microvessel Endothelial Cells
Ten week old male C57BLKS/J mice (Jackson Labs) were used.
All experiments were reviewed and approved by a Subcommittee
for Research Animal Care of the Massachusetts General Hospital
IACUC (Institutional Animal Care and Use Committee) and all
these institutionally-approved animal protocols are consistent with
the NIH Guide for the Care and Use of Laboratory Animals. To
measure the vasculome, we extracted endothelial cells from brain,
heart and kidney glomeruli, with modified method from previously
published protocols [206,207]. Briefly, mice were anesthetized by
isofluorane and perfused with 8610
7 inactivated Dynabeads
diluted in 40 ml of HBSS (Invitrogen). The cerebral cortex, heart
and kidneys were dissected and combined from 5 mice, minced
and digested in Collagenase A at 37uC for 30–40 minutes with
vigorous shaking (2 mg/ml for cortex and heart, 1 mg/ml for
kidney). The digested tissue were mechanically dissociated by
titurating, filtered through a 70 mM cell strainer (Becton Dickinson
Labware, Bedford, MA), and centrifuged at 5006g for 5 minutes
at 4uC. For kidney, materials were further filtered twice with
a 100 mM and a 70 mM cell strainer. Cell pellets from brain cortex
Table 5. Expression of plasma proteins in the vasculome of mouse brain.
Data source plasma protein
plasma proteins expressed in brain
vasculome % Reference
PMID:16041672 3365 754 22.4 Muthusamy B. et al, 2005
PMID:16335952 3344 723 21.6 Liu T. et al, 2005
PMID:16684767 2837 781 27.5 Liu T et al, 2006
PMID:18632595 5776 1211 21.0 Qian WJ. et al, 2008
core* 387 100 25.8
Note: *core is the intersect of all 4 independent data set. Lists of circulating proteins in human plasma were compiled from 4 different proteomic studies, then each
study was overlapped with the expression profile of the brain vasculome. A core set of 387 proteins were defined as common proteins detected in all 4 human plasma
protein studies. Out of the core set of plasma proteins, 100 proteins were expressed in the brain vasculome.
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and heart were resuspended in cold HBSS and mounted on
magnetic separator to remove Dynabeads, then supernatant was
collected and centrifuged, and incubated with PECAM-1 coated
Dynabeads (5 ml for each organ from one mouse) for 30 minutes at
4uC with rotation. A magnetic separator was used to recover bead-
bound endothelial cells. Cell pellets from kidney were also
resuspended in HBSS and mounted directly on the magnetic
separator to select glomeruli containing Dynabeads. Purified
glomeruli were further digested with 5 mg/ml of type V
Collagenase (Sigma) at 37uC for 30 minutes with agitation,
magnetically separated, and then Digested glomeruli were
centrifuged, resuspended and incubated with PECAM-1 coated
Dynabeads. After washing all materials with HBSS for 5 times,
recovered endothelial cells from all organs were lysed with buffer
RLT plus for RNA preparation, with RNeasy Micro Plus kit
Real Time PCR
Relative expressions of selected markers for different types of
cells were tested with RT-PCR, with pre-designed primers and
Syber Green system from Bioscience. First strand cDNA was
synthesized with QuantiTect reverse transcription system
(Qiagen). Date normalization was performed by quantification
of the endogenous 18S rRNA, and fold change was measured
with 2
method. The markers for endothelial cells included
VE-cadherin, PECAM-1 and eNOS. To ensure that our brain
vasculome was not contaminated by parenchymal non-endothe-
lial cells, we also checked markers for astrocytes (Aquaporin-4,
GFAP), markers for neurons (MAP-2, Neurogranin), and
markers for pericytes and smooth muscle cells (smooth muscle
alpha-Actin Acta2), calponin 1 CNN1, desmin, myosin heavy
polypeptide 11 Myh11, transgelin Tagln). For heart and
glomerular preparations, we checked markers for myocytes
(Myh6, NKX 2–5), markers for glomerular podocytes (Nphs-1,
Nphs-2) and markers for kidney tubules (Cadherin-16, Claudin-
16, Lrp2).
Transcriptional Profiling with Microarray
Three RNA samples for each organ were individually
hybridized to Affymetrix GeneChip Mouse Genome 430 2.0
microarrays, after checking the RNA quantity and quality. RNA
concentration was measured by Nanodrop, and the integrity of
RNA was tested with RNA integrity number (RIN) score on
Agilent Bioanalyzer 2010. All samples were used only when
RIN scores were verified to be larger than 7.0. Microarray
hybridization and scanning was performed after amplification
with the NuGEN Ovation WTA Pico kit and fragmentation
and labeling with Encore Biotin Module. Raw expression data
for each chip was summarized and normalized using RMA
algorithm, to allow direct comparison of results obtained among
different chips. The quality of each chip was determined by
manually checking mean values, variances and paired scatter
plots as well as Principal Component Analysis (PCA)plots. All
chips passed the quality check. Among the large amount of
probes/genes, we only focused on genes whose maximal
expression values across all microarrays were great than 200,
while the probes with intensity less than 200 were eliminated for
further analysis.
Identification of Organ Specifically Expressed Genes
The specific genes between two groups were identified based on
both statistical significances, which were determined using SAM
algorithm (a variant of t-test and specifically designed for
microarray data), and fold change. To minimize false positives,
only the genes with maximum expression values across all
microarrays greater than 200 were analyzed here. The genes with
p,0.01 and fold change .4 were considered as specifically
expressed. The combination of p value and fold change threshold
serves to eliminate most false positives, as suggested from a large
microarray study led by FDA [208]. Fisher’s exact test was used to
identify the potential enriched pathways from these brain
endothelial specific genes.
Protein-protein Interaction (PPI) Networks
PPI datasets for human and mouse were downloaded from
BIOGRID database at version 3.1.71. Since there were only
2314 proteins and 4118 interactions in the mouse PPI dataset,
we transformed human PPI information into mouse’s based on
the homolog genes between human and mouse according to
NCBI HomolGene database. The human PPI dataset contained
10121 proteins and 52693 interactions. After combining the
native mouse dataset and the transformed mouse dataset and
deleting repeated records and self-self interaction records,
a mouse PPI network with 9189 proteins and 36073 interactions
was built. Since not all proteins in the networks are expressed in
the endothelial cells under this study, we further shrink the
network to EC-specific PPI (EC-PPI) network by deleting the
proteins that are not expressed and their corresponding
interactions. The EC-PPI contains 4243 proteins and 10825
interactions. The properties of network were calculated with
IGRAPH package in R. The PPI networks were visualized by
Cytoscape software with force-directed layout.
GWAS and Plasma Protein Databases
Genome-wide- association-studies of disease select the risk
genes for the disease. GWAS-identified disease genes for stroke,
Alzheimer’s disease and Parkinson’s disease were collected
sgap_plus.htm) to analyze the expression of such disease-related
genes in endothelial cells. The expression of human plasma
proteins were also tested in the brain vasculome. Human
plasma proteins determined by proteomics from 4 different
studies were used [199,200,201,202,203,204]. A core set of
human plasma proteins was build with proteins detected in all
of these 4 studies, consisting of 387 individual proteins. It is
worthwhile to notice that GWAS and plasma protein databases
evolve and grow over the time, correlations with our brain
vasculome will have to be continually re-assessed in future
Statistical Methods
All statistical analyses were performed with the statistics
software R (Version 2.6.2; available from http://www.r-project.
org) and R packages developed by the BioConductor project
(available from Overall, raw
expression data for each chip was summarized and normalized
using RMA algorithm, genes with maximum expression levels
across all microarrays great than 200 were considered for further
analysis. Organ specifically expressed genes were identified using
SAM algorithm; Fisher’s exact test was used to identify the
enriched pathways from these organ specific genes. Only genes
with p,0.01 and fold change .4 were considered as specifically
expressed. The combination of p value and fold change threshold
serves to eliminate most false positives, as validated by a large
microarray study led by FDA [208]. Fisher’s exact test was also
used to test the enrichment of GWAS genes for each disease in the
vasculome of mouse brain.
Mapping the Brain Vasculome
PLOS ONE | 12 December 2012 | Volume 7 | Issue 12 | e52665
Supporting Information
Figure S1 Purity of isolation protocols for brain, heart
and kidney glomerular endothelial cells. The expression of
different cell type specific genes were tested by RT-PCR, and
compared between endothelial cells and corresponding whole
tissue samples.
Table S1 List of endothelial genes specifically ex-
pressed in brain, heart and kidney glomeruli.
Table S2 Full list of GWAS disease associated genes
expressed in brain vasculome. The label ‘‘brain EC
expressed’’ indicates whether the gene is expressed in brain
vasculome (True) or not (False).
Table S3 Full list of plasma proteins expressed in brain
Thanks to Francis Luscinskas and Veronica Azcutia Criado (Brigham and
Women’s Hospital and Harvard Medical School, Boston, MA) for helpful
discussions about the isolation of endothelial cells.
Author Contributions
Conceived and designed the experiments: SG YZ EHL. Performed the
experiments: SG JL CX ATS. Analyzed the data: YZ EHL SG. Wrote the
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Mapping the Brain Vasculome
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    • Neonatal injury may be related to in utero growth restriction and inflammation, asphyxia, and hypoxic ischemic injury[16,17]and mechanistically in part due to neural and vascular impairment[11,23,24]. Early vasculopathy has been reported as a key contributor to neurodevelopmental vulnerability and this is not solely due to acute vascular rupture. Abnormal bidirectional transport across the cerebral endothelial cells may lead to abnormal function of the accessory cells participating in a functional neurovascular unit[3]. Recognizing developmental cerebral vasculopathy has shed light on the stage specific risk of hemorrhagic vulnerability in the choroid plexus not only in utero but also postnatally and this may be related to energy requirements of the microvasculature[17].
    [Show abstract] [Hide abstract] ABSTRACT: Penumbral perfusion is critical to brain viability. Proximal arterial occlusion and deep brain stroke has variable effect on cortical dysfunction. Cortical microvessel collaterals may be recruited and at times sufficient for partial parenchymal perfusion. Postnatal neural and endothelial cells are markedly vulnerable to glutamate excitotoxicity. Early vascular cell stress may promote partial protective neural preconditioning though postnatally a developmental window of the cerebral microvasculature may be particularly vulnerable to injury. We tested the hypothesis that postnatal NMDA excitotoxic injury, when cerebral endothelial cells’ central energy source is via glycolysis, is age specific. Neurovascular responses of cortical viability were directly identified with diffuse reflectance patterns of perfusion properties in a non-invasive manner, over time. Histological evaluation for neural and vascular cytoarchitectonic abnormalities were evaluated 4- 7 days post injury. Optical diffuse reflectance recordings were obtained at the injection site prior to, immediately after and 48 hours post injury. Extent of neurovascular injury at the infarct zone was greatest at PND 5 and cortical perfusion responses identified with recordings of pattern change. These data further suggest excitotoxic injury to both neural and vascular cells, in vivo, can enhance CNS injury in the young and neuroprotective strategies may benefit from vascular directed therapies.
    Full-text · Article · Jun 2017
    • Using a different database (Ingenuity pathway analysis) convergent lists of enriched pathways were obtained, related to Glycolysis/neoglucogenesis, phenylalanine metabolism Wnt, IL1, or nuclear receptor signalling [17]. Other reports using different approaches to extract the core of endothelial secreted proteins from 4 independent studies identified a " vasculome " of 99 proteins from adult mouse brain microvessels [13] . Near 60% of these proteins were identified in forebrain enriched microvessels as proteins (n = 22) or exhibiting mRNA expression modulation (n = 42).
    [Show abstract] [Hide abstract] ABSTRACT: Infants born before 29 weeks gestation incur a major risk of preterm encephalopathy and subependymal/intracerebral/intraventricular haemorrhage. In mice, an ontogenic window of haemorrhage risk was recorded up to 5 days after birth in serpine1 knock-out animals. Using proteome and transcriptome approaches in mouse forebrain microvessels, we previously described the remodelling of extracellular matrix and integrins likely strengthening the vascular wall between postnatal day 5 (P5) and P10. Haemorrhage is the ultimate outcome of vessel damage (i.e., during ischaemia), although discreet vessel insults may be involved in the aetiology of preterm encephalopathy. In this study, we examined proteins identified by mass spectrometry and segregating in gene ontology pathways in forebrain microvessels in P5, P10, and adult wild type mice. In parallel, comparative transcript levels were obtained using RNA hybridization microarrays and enriched biological pathways were extracted from genes exhibiting at least a two-fold change in expression. Five major biological functions were observed in those genes detected both as proteins and mRNA expression undergoing at least a two-fold change in expression in one or more age comparisons: energy metabolism, protein metabolism, antioxidant function, ion exchanges, and transport. Adult microvessels exhibited the highest protein and mRNA expression levels for a majority of genes. Energy metabolism–enriched gene ontology pathways pointed to the preferential occurrence of glycolysis in P5 microvessels cells versus P10 and adult preparations enriched in aerobic oxidative enzymes. Age-dependent levels of RNA coding transport proteins at the plasma membrane and mitochondria strengthened our findings based on protein data. The data suggest that immature microvessels have fewer energy supply alternatives to glycolysis than mature structures. In the context of high energy demand, this constraint might account for vascular damage and maintenance of the high bleeding occurrence in specific areas in immature brain.
    Full-text · Article · Jan 2017
  • [Show abstract] [Hide abstract] ABSTRACT: Despite the reported functional recovery in transplanted stroke models and patients, the mechanism of action underlying stem cell therapy remains not well understood. Here, we examined the role of stem cell-mediated vascular repair in stroke. Adult rats were exposed to transient occlusion of the middle cerebral artery and 3 hours later randomly stereotaxically transplantated with 100K, 200K, or 400K human cerebral endothelial cell 6 viable cells or vehicle. Animals underwent neurological examination and motor test up to day 7 after transplantation then euthanized for immunostaining against neuronal, vascular, and specific human antigens. A parallel in vitro study cocultured rat primary neuronal cells with human cerebral endothelial cell 6 under oxygen-glucose deprivation and treated with vascular endothelial growth factor (VEGF) and anti-VEGF. Stroke animals that received vehicle infusion displayed typical occlusion of the middle cerebral artery-induced behavioral impairments that were dose-dependently reduced in transplanted stroke animals at days 3 and 7 after transplantation and accompanied by increased expression of host neuronal and vascular markers adjacent to the transplanted cells. Some transplanted cells showed a microvascular phenotype and juxtaposed to the host vasculature. Infarct volume in transplanted stroke animals was significantly smaller than vehicle-infused stroke animals. Moreover, rat neurons cocultured with human cerebral endothelial cell 6 or treated with VEGF exhibited significantly less oxygen-glucose deprivation-induced cell death that was blocked by anti-VEGF treatment. We found attenuation of behavioral and histological deficits coupled with robust vasculogenesis and neurogenesis in endothelial cell-transplanted stroke animals, suggesting that targeting vascular repair sets in motion a regenerative process in experimental stroke possibly via the VEGF pathway.
    Full-text · Article · Oct 2013
  • [Show abstract] [Hide abstract] ABSTRACT: The pathophysiology of stroke is complex. Adaptive and maladaptive signalling occurs between multiple cell types in the brain. There is crosstalk between central and systemic responses. And there are overlapping pathways during initial injury and subsequent repair. These numerous feed-forward and feed-back interactions have made it difficult to translate experimental discoveries into clinical applications. An emerging hypothesis in biomedical research now suggests that contrary to a traditional model, translation may not be efficiently obtained without a rigorous understanding of mechanisms. Hence, to optimize diagnostics and therapeutics for stroke patients, it is necessary to identify and define causal mechanisms. Mirroring the multi-compartment interactions in stroke pathophysiology, bench-to-bedside, and bedside-back-to-bench advances in stroke may be best achieved with inter-disciplinary collaborations between basic research, neuroimaging, and broadly based clinical science. Causation can then be two-fold, ie, dissecting mechanisms and targets, as well as developing future scientists who can blur the boundaries between basic, translational, and clinical research. In systems theory, a critical goal is to distinguish causation from correlation. In stroke research, causation may perhaps be found through a collaborative search for mechanisms.
    Article · Nov 2013
  • [Show abstract] [Hide abstract] ABSTRACT: The neurovascular unit is now well accepted as a conceptual framework for investigating the mechanisms of ischemic stroke. From a molecular and cellular perspective, three broad mechanisms may underlie stroke pathophysiology - excitotoxicity, oxidative stress and inflammation. To date, however, most investigations of these basic mechanisms have focused on neuronal responses. In this mini-review, we ask whether these mechanisms of excitotoxicity, oxidative stress and inflammation can also be examined in terms of non-neuronal interactions in the neurovascular unit, including the release of extracellular vesicles for cell-cell signaling.
    Article · Dec 2013
  • [Show abstract] [Hide abstract] ABSTRACT: Common methods for studying angiogenesis in vitro include the tube formation assay, the migration assay, and the study of the endothelial genome. The formation of capillary-like tubes in vitro on basement membrane matrix mimics many steps of the angiogenesis process in vivo and is used widely as a screening test for angiogenic or antiangiogenic factors. Other assays related to the study of angiogenesis include the cell migration assay, the study of gene expression changes during the process of angiogenesis, and the study of endothelial-derived microparticles. Protocols for these procedures will be described here.
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