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Stereological Investigation of Age-Related Changes of the Capillaries in White Matter.

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THE ANATOMICAL RECORD 293:1400–1407 (2010)
Stereological Investigation of
Age-Related Changes of the
Capillaries in White Matter
WEI-HUA SHAO,1,2 CHEN LI,1,2,3 LIN CHEN,1,2 XUAN QIU,1,2 WEI ZHANG,1
CHUN-XIA HUANG,4 LEI XIA,1,2 JI-MING KONG,1,2* AND YONG TANG1,2*
1
Department of Histology and Embryology, Chongqing Medical University, Chongqing,
People’s Republic of China
2
Laboratory of Stem Cells and Tissue Engineering, Chongqing Medical University,
Chongqing, People’s Republic of China
3
Department of Neurology, First Affiliated Hospital, Chongqing Medical University,
Chongqing, People’s Republic of China
4
Department of Physiology, Chongqing Medical University, Chongqing, People’s
Republic of China
ABSTRACT
We, for the first time, investigated the age-related changes of the capillaries in white matter using immunohistochemistry and stereological techniques. Ten young female (7 months) and 10 aged female (27 months) rats
were used. The total length, total volume, and total surface area of the
capillaries in white matter of aged rats were all significantly lower than
those of young rats. The age-related changes of the capillaries in white
matter may have important implications for age-related white matter
atrophy and age-related cognitive impairments. Anat Rec, 293:1400–1407,
C 2010 Wiley-Liss, Inc.
2010. V
Key words: white matter; capillaries; rat; aging; stereology
The capillaries in the brain play a crucial role in
maintaining local brain perfusion and thus are essential
for fulfilling the metabolic needs of normal brain activities. Studies on age-related changes of the capillaries in
the brain have included age-related alterations of the
microvascular ultrastructure (e.g., atrophy of endothelium, basement membrane thickening, and pericyte
degeneration) (Burns et al., 1981; Hicks et al., 1983;
Mooradian, 1988; Keuker et al., 2000; Farkas and
Luiten, 2001; Alba et al., 2004; Morita et al., 2005), qualitative changes in microvascular structure such as glomerular loops and twisted capillaries in different regions
of the aged brain (de Jong et al., 1990; Moody et al.,
1997; Wegiel et al., 2002), and quantitative analyses of
structural parameters in brain capillaries in the cortical
and hippocampal regions (Bell and Ball, 1981; Pawlik
et al., 1981; Mann et al., 1986; Amenta et al., 1995; Løkkegaard et al., 2001).
The interest in aged white matter has increased dramatically in recent years. Ample evidence suggests that
healthy brain aging is a process affecting predominantly
the white matter but not the grey matter (Pakkenberg
and Gundersen, 1997; Tang et al., 1997; Piguet et al.,
2009). Until now, however, only one study quantified
C 2010 WILEY-LISS, INC.
V
capillary parameters in the corpus callosum of transgenic murine model of Alzheimer’s disease (Lee et al.,
2005). There were no studies investigating the capillary
Grant sponsor: Natural Science Foundation of China; Grant
number: 30973155; Grant sponsor: 2008 Specialized Research
Grants for the Doctoral Training Program from the Ministry of
Education; Grant number: 200806310007; Grant sponsor: Key
Projects of Natural Science Foundation of Chongqing
Government; Grant number: 2009BA5035; Grant sponsor: 2008
Key Projects of Chongqing Medical University Foundation;
Grant number: XBZD200801.
*Correspondence to: Yong Tang or Ji-Ming Kong, Department
of Histology and Embryology, College of Basic Medical Sciences,
Chongqing Medical University, Chongqing 400016, People’s
Republic of China. Fax: þ86-2368485868. E-mail: ytang062@
yahoo.com.cn or kongj@cc.umanitoba.ca
Wei-Hua Shao and Chen Li have contributed equally to this
work.
Received 13 November 2009; Accepted 28 March 2010
DOI 10.1002/ar.21184
Published online 17 May 2010 in Wiley InterScience (www.
interscience.wiley.com).
CHANGES OF THE CAPILLARIES IN AGED WHITE MATTER
1401
Fig. 1. To get isotropic, uniform random (IUR) sections, the embedded tissue blocks are treated with the orientator technique. As shown
in the left figure, numbers 0–36 are equidistantly labeled in the circle.
The original horizontal surface of the tissue block is put on the circle.
A number is randomly selected. In this example, number 16, in other
words, 16–34 direction, is randomly selected. The tissue block is cut
in this direction, perpendicular to the plane of the circle. The cut surface and the original horizontal surface make a straight edge. The
figure on the right illustrates the second step of the orientator technique. Numbers 0–97 are nonequidistantly labeled in this circle. One of
the two cut blocks in the left figure is randomly selected. The selected
tissue block is placed on the circle with the straight edge parallel to the
0–0 direction of the circle. A number is randomly selected again from 0
to 97. In this example, 20 is randomly selected. The tissue block is cut
along this direction perpendicularly to the circle. The second cut surface is called isotropic, uniform random (IUR) surface.
changes in healthy aged white matter using stereological
techniques. In the current study, we investigated the
age-related changes of the capillaries in the white matter of female Long-Evans rats by means of immunohistochemistry and stereological techniques.
Each hemisphere was coronally cut into 2-mm thick
slabs, starting randomly from the rostral pole. Eight to
nine slabs were obtained from each hemisphere. The left
or right hemisphere was sampled at random. The white
matter volume was estimated according to Cavalieri’s
principle (Gundersen et al., 1988; Tang and Nyengaard,
1997, 2004).
The slabs of the randomly selected hemisphere were
postfixed in 4% paraformaldehyde for at least 2 hr.
Then, they were embedded in paraffin with the caudal
surface being faced down. To get the isotropic, uniform
random (IUR) sections, the embedded slabs were treated
with the orientator technique (Gundersen et al., 1988;
Mattfeldt et al., 1990), as illustrated in Fig. 1. After the
IUR surface was obtained, the tissue blocks were sectioned at 4 lm along the direction parallel to the IUR
surface. We called the cut 4-lm sections IUR sections.
The orientator technique ensures that the capillaries, in
each direction of three-dimensional space, have the same
probability of being sampled.
MATERIALS AND METHODS
Animals
Ten young female Long-Evans rats (7-month-old) and
10 aged female Long-Evans rats (27-month-old) were
obtained from the Third Military Medical University,
P.R. China. The rats were housed three to four per cage
at a temperature of 22 C 1 C. They were kept under a
constant 12-hr light and 12-hr dark cycle. Food and
water were available ad libitum. The colony was certified specific pathogen free for the following: mouse pneumonia virus, sendia virus, hepatitis virus, reovirus,
lymphocytic choriomeningitis, Theiler Martin encephalomyelitis virus, ectromelia, minute virus of rats, and
mucoplasma pulmonitis. Animal care and treatment followed the National Institute of Health Guide for the
Care and Use of Laboratory Animals (NIH Publications
No. 80–23) revised 1996.
Tissue Processing
The rats were deeply anaesthetized with 4% chloral
hydrate (10 mL/kg) intraperitoneally and perfusion fixed
with 4% paraformaldehyde in 0.6 M phosphate buffered
saline (pH 7.4). After perfusion, the cerebellum, brain
stem, and cranial nerves under the pavimentum cerebri
were cut and the cerebral hemispheres were taken out.
Immunohistochemistry
Immunohistochemistry was performed using the Histostain TM-Plus SP/9001 kit from ZYMED (ZSGB; Beijing, China). Briefly, the 4-lm paraffin sections were
deparaffinized in xylol and rehydrated in graded alcohol
series. The sections were then immersed in citrate buffer
(0.01 M, pH 6.0) and heated in a microwave oven for
15 min for antigen retrieval. After being cooled, sections
were washed twice in phosphate-buffered saline (PBS,
0.01 M, pH 7.4). Endogenous peroxidase was inhibited
by incubation with 3% H2O2 for 10 min and then washed
1402
SHAO ET AL.
associated with each point was placed at random on the
caudal surface. The points hitting the white matter were
counted under an optical microscope (Fig. 2). The white
matter volume, V (wm), was calculated according to the
Cavalieri’s principle (Gundersen et al., 1988; Tang and
Nyengaard, 1997, 2004):
V ðwmÞ ¼ t að pÞ RPðwmÞ 2
(1)
where t equals the slab thickness, 2 mm, a(p) equals the
area associated with each grid point, 0.4 mm2, and
RP(wm) is the total number of grid points hitting the
white matter per rat hemisphere.
Tissue Shrinkage
Fig. 2. The point grid is put on each brain slice and the total points
hitting white matter are counted (RPWM). When counting, the right
upper corner of the crossline is used. The point is counted where the
right upper corner of the crossline hits white matter.
in PBS three times for 5 min. Nonspecific binding sites
were blocked with normal goat serum for 20 min at
room temperature. Sections were incubated at 4 C overnight and then 37 C for 1 hr with rabbit polyclonal
anti-collagen IV primary antibody (ab6586; Abcam, Cambridge, UK) at a dilution of 1:200 in PBS. After three
5-min washes in PBS, sections were incubated with biotinylated goat anti-rabbit IgG for 20 min at 37 C, which
was followed by three additional 5-min washes in PBS.
Then, the specimens were incubated with S-A/HRP for
20 min at 37 C, which was followed by repeated washes
as described previously. Diaminobenzidine (DAB, ZLI9032, ZSGB; Beijing, China) was used as a chromogen.
Then, sections were dehydrated by sequential immersion
in gradient ethanol and xylene and then coverslipped.
The sections were viewed using a modified Olympus
BX51 microscope (Olympus, Tokyo, Japan). A DP-70 video
camera mounted on the top of the microscope was connected to a computer system. Under an oil objective lens
(100), the entire white matter region on each section
was photographed. Three to five fields of vision were captured from each section. For each section, vessels with
luminal diameter of <10 lm were defined as components
of the capillary net (Villena et al., 2003; Alba et al., 2004).
Estimation of White Matter Volume
On each slab of the randomly selected hemisphere,
a transparent counting grid with an area of 0.4 mm2
To estimate the volume shrinkage of white matter
induced by tissue processing, two tissue blocks were randomly taken from each animal. The white matter volume of each tissue block before the tissue processing,
Vbefore, was estimated according to the Cavalieri’s principle (Gundersen et al., 1988; Tang and Nyengaard, 1997,
2004) as described above. After a series of tissue processing (dehydrating, embedding, and sectioning), the white
matter volume of each tissue block was estimated again
in the way illustrated in Fig. 3. First, a 4-lm section
was cut along the z-axis direction (or the direction of the
slab’s thickness) from the embedded tissue block and
stained with hematoxylin. A sliding caliper was used to
measure the slab’s thickness after tissue processing, t0 .
Then, another 4-lm section was cut along the slab’s coronal surface direction and was stained with hematoxylin
and eosin. The point grid was randomly put on the
stained coronal section. The points hitting white matter
0
) under microscope using a 4 objecwere counted (PWM
tive lens. The white matter volume of tissue block after
tissue processing, Vafter, was calculated, again, according
to the Cavalieri’s principle (Gundersen et al., 1988; Tang
and Nyengaard, 1997, 2004):
Vafter ¼ t0 að pÞ P0WM
(2)
where a(p) equals the area associated with each grid
point, 0.4 mm2.
The processing-induced volume shrinkage for one
brain was calculated as an average of the two tissue
blocks (Tang et al., 2001):
Volume shrinkage ¼ meanð1 Vafter =Vbefore Þ
(3)
where Vbefore is the white matter volume of the selected
tissue block before tissue processing, Vafter is the white
matter volume of the same tissue block after tissue processing, and mean is the simple arithmetic mean over the
two tissue blocks.
Estimation of the Length Density, Volume
Density, and Surface Area Density of the
Capillaries in White Matter
An unbiased counting frame (Gundersen, 1977) was
randomly superimposed onto the captured photographs.
The capillary profiles inside the counting frame or
CHANGES OF THE CAPILLARIES IN AGED WHITE MATTER
1403
Fig. 3. As shown in the left figure, the point grid is randomly put on the stained coronal section, and
0
the points hitting white matter are counted (PWM
). The right figure illustrates the measurement of the slab’s
thickness after tissue processing (t0 ).
Fig. 4. A: The unbiased counting frame is put on the randomly captured image. The capillary profiles are counted if they are completely
inside the counting frame or partly inside the counting frame but only
touching the counting lines (dotted lines), as indicated by an arrow.
The capillary profiles are excluded if they touch the exclusion lines
(solid lines), as indicated by a star. Bar ¼ 10 lm. B: The point grid is
put on the randomly captured image. The points hitting on the capillaries and the points hitting on the white matter are counted separately.
‘‘!’’ points out one of the points counted. Bar ¼ 10 lm. C: The test
lines are put on the randomly captured photomicrograph. The number
of intersections between the test lines and capillary luminal surface
are counted, as indicated by intersections. Bar ¼ 10 lm.
touching the top line and right line (inclusion lines)
were included for counting and the capillary profiles
touching the left line, bottom line and the extensions of
the right line and left line (exclusion lines) were
excluded for counting (Fig. 4A). The length density of
the capillaries in white matter, Lv (cap/wm), was estimated as (Gundersen et al., 1988; Tang and Nyengaard,
1997, 2004; Tang et al., 1999):
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SHAO ET AL.
Fig. 5. Comparisons of the white matter volume before tissue processing between young female rats and aged female rats are shown.
~ indicates P < 0.05.
Lv ðcap=wmÞ ¼ 2 RQðcapÞ=½aðframeÞ Rframes
(4)
where RQ(cap) denotes the total number of the capillary
profiles counted per rat white matter, a(frame) equals
the area associated with a counting frame, and Rframes
is the total number of counting frames counted.
A transparent counting grid with a total of 1680
points was randomly placed on the photographs. The
points hitting the capillaries, RP (cap), and the points
hitting the white matter, RP (wm), were counted (Fig.
4B). The volume density of the capillaries in white matter, Vv (cap/wm), was estimated as (Gundersen et al.,
1988; Tang and Nyengaard, 1997, 2004; Tang et al.,
1999):
Vv ðcap=wmÞ ¼ RPðcapÞ=RPðwmÞ
(5)
The test lines with length of 5 mm associated with
each line were randomly placed on the photographs. The
number of intersections between the test lines and capillary luminal surface, RI (cap), and the total length of
test lines hitting the white matter, RL (wm), were
recorded (Fig. 4C). The surface area density of the capillaries in white matter, Sv (cap/wm), was estimated as
(Gundersen et al., 1988; Tang et al., 1999):
Sv ðcap=wmÞ ¼ 2 RIðcapÞ=RLðwmÞ
Fig. 6. Comparisons of the length density (A) and total length of
the capillaries in the white matter (B) between young female rats and
aged female rats are shown. * indicates P < 0.01.
(6)
Estimation of the Total length, Total Volume,
and Total Surface Area of the Capillaries in
White Matter
Because of the volume shrinkage induced by the histological processing, the total volume of white matter was
corrected for shrinkage by multiplying the white matter
volume before tissue processing by (1 volume shrinkage) (Tang et al., 2001). The total length, total volume,
and total surface area of the capillaries in white matter
were estimated by multiplying the length density, volume density, and the surface area density of the capillaries in white matter by the corrected white matter
volume (Gundersen et al., 1988; Tang and Nyengaard,
1997, 2004; Tang et al., 1999, 2001).
Statistics
Unpaired, two-tailed Student t test was used. A significant difference was considered when P < 0.05.
RESULTS
White Matter Volume
The volume shrinkage of white matter induced by tissue processing was 46.4 8.8% in the young female
group and 46.1 7.3% in the aged female group. The
mean white matter volume before tissue processing in
the young rats (91.7 12.1 mm3, mean SD) was significantly larger than that of aged rats (78.0 16.4
mm3) (P < 0.05; Fig. 5). After corrected for tissue
shrinkage, the mean white matter volume was 49.7 12.6 mm3 in the young female group and 42.1 9.9
mm3 in the aged female group.
Capillaries in White Matter
The length density and total length of the capillaries
in the white matter of young female rats (0.7 0.07 m/
mm3 and 34.4 7.8 m, respectively) were significantly
higher than those of aged female rats (0.57 0.09 m/
mm3, P < 0.01 and 23.3 5.1 m, P < 0.01, respectively)
(Fig. 6).
CHANGES OF THE CAPILLARIES IN AGED WHITE MATTER
Fig. 7. Comparisons of the volume density (A) and total volume of
the capillaries in the white matter (B) between young female rats and
aged female rats are shown. ~ indicates P < 0.05. * indicates P < 0.01.
The volume density and total volume of the capillaries
in the white matter of young female rats (1.7 0.42 102 and 0.81 0.13 mm3, respectively) was significantly higher than those of aged female rats (1.3 0.34 102, P < 0.05 and 0.54 0.14 mm3, P < 0.01,
respectively) (Fig. 7).
There was no significant difference in the surface area
density of the capillaries in white matter between the
two groups (11.6 2.8 mm2/mm3 in the young group,
and 9.3 2.1 mm2/mm3 in the aged group, respectively,
P > 0.05). The total surface area of the capillaries in the
white matter of young female rats (5.6 1.0 cm2) was
significantly higher than that of aged female rats (3.8 0.89 cm2) (P < 0.01) (Fig. 8).
DISCUSSION
In the past, Morita et al. (2005) detected a slight
decrease in laminin immunolabeling in the basement
membrane of the capillaries in the white matter of old
dogs, as compared with that in the white matter of
young dogs. Farkas et al. (2006) found that the number
of intact microvessels in white matter decreased with
age. In contrast with those qualitative studies or semiquantitative studies of capillaries, we investigated, for
the first time, age-related changes of capillaries in white
matter with design-based stereological technology and
immunohistochemistry. The present study described efficient and unbiased methods of quantitatively investigat-
1405
Fig. 8. Comparisons of the surface area density (A) and total surface area of the capillaries in the white matter (B) between young
female rats and aged female rats are shown. * indicates P < 0.01.
ing the capillaries of white matter. Methodologically, the
methods described in the current study have several
advantages over the previously used methods.
Previously, researchers selected typical parts of a
brain region of interest. Farkas et al. (2006) examined
the capillary density of the human white matter of 14
subjects. They did not sample the white matter uniformly but selected the subcortical white matter of the
frontal, parietal, and occipital regions for investigation.
The conclusions that can be drawn from the analysis of
a certain typical portion of the region of interest, a
standard section or sections in which the objects of interest are best identified can only apply to that part of tissue and those sections. The ‘‘ideal tissue’’ and ‘‘ideal
fields’’ are not representative of the entire tissue and
thus introduce a bias. A uniform random sampling of
the white matter was used in this study so that all parts
of the white matter were sampled equally. When an
unbiased estimate of the length and surface area of
capillaries is obtained from two-dimensional sections,
the capillary profiles must be either from isotropic, uniform, and random sections or the capillary profiles must
be isotropic themselves. In this study, isotropic, uniform
random sections were ensured by the orientator technique so that all the capillaries in three-dimensional
space had an equal probability of being sampled (Gundersen et al., 1988; Mattfeldt et al., 1990).
1406
SHAO ET AL.
Besides the aforementioned problem associated with
sampling in previously used methods, another methodological problem in previous studies was that they measured the densities of microvessels rather than the total
quantities of microvessels (Moody et al., 2004; Farkas
et al., 2006). Biological conclusions based on density
measurements are very difficult to interpret because it
will never be known if changes in density are due to an
alteration of total quantity and/or an alteration in the
reference volume (Braendgaard and Gundersen, 1986).
In the present study, the problem associated with the
density estimate has been solved by the use of a designbased stereological technique, the Cavalieri principle, to
estimate the reference volume. The total length, total
volume, and total surface area of the capillaries were
obtained by multiplying the density estimates with the
volume of white matter. Therefore, our results are
the estimates of total quantities of the capillaries in
white matter and can be interpreted unambiguously.
The white matter volume was estimated before the tissue processing, and the capillary density parameters
were estimated from the tissue sections that were dehydrated, embedded and sectioned. If the tissue shrinkage
happened during the tissue processing, the total quantity of the capillaries in white matter could not be
obtained by multiplying the white matter volume before
the tissue processing by the density parameters after
the tissue processing. In the current study, the tissue
was embedded in paraffin, which is the embedding medium that induces the largest shrinkage (Iwadare et al.,
1984), and the shrinkage of brains of young individuals
may not be the same as the brains of old individuals
(Haug and Eggers, 1991). Therefore, the tissue shrinkage induced by tissue processing was estimated in the
current study. The volume shrinkage induced by histological processing was 46.4% in young rats and 46.1% in
aged rats. These changes were significant. Therefore,
the white matter volume was corrected for the tissue
shrinkage. In this way, we estimated the white matter
volume and the capillary density under the same conditions, and thus the estimation of the total parameters of
capillaries in white matter would not be affected by
shrinkage.
In the present study, the total length, total volume,
and total surface area of the capillaries in white matter
of aged rats were all significantly lower than those of
young rats, which indicated that there was significant
loss of the capillaries in aged white matter. Farkas and
Luiten (2001) reported that there was the ultrastructural degeneration in cerebral microvessels with aging.
Moreover, it has been reported that angiogenesis was
substantially impaired in aged brains (Black et al., 1989;
Riddle et al., 2003). These factors might induce the agerelated loss of the capillaries in white matter. It was
reported that there was significantly lower cerebral
blood flow in aged brains (Tachibana et al., 1984; Reich
and Rusinek, 1989; Schultz et al., 1999). The results in
the current study might provide the morphological basis
for the decline of cerebral blood flow in aged brains.
Our research team found that there were age-related
changes of white matter and the nerve fibers in the
white matter (Tang et al., 1997; Li et al., 2009; Yang
et al., 2009). The current study further confirmed that
there was age-related reduction of white matter volume.
This study also found that there was age-related decline
of the capillaries in white matter. Is there any relationship between the age-related change of white matter
and age-related change of the capillaries in white matter? Wender et al. (1991) investigated white matter of
temporal, parietal and occipital lobes of 13 subjects
using histological methods and biochemical techniques.
They found that there were significantly age-related
change of the expression of myelin-associated protein in
both the brains with vascular changes only and brains
with senile atrophy of the Alzheimer type. They thought
that the degeneration of vessels might be the decisive
factor in the pathogenetic mechanism of myelin lesions
in the aged brains. Some researchers also found that experimental cerebral hypoperfusion had a deleterious
impact on the neural tissue in the white matter, such as
vacuoles and irregular myelin sheaths (Wakita et al.,
2002; Farkas et al., 2004). Brown et al. (2007) investigated the vessel density in 12 subjects with leukoaraiosis (LA) and 9 age-matched normal subjects. They found
that both the lesion and nonlesion areas of white matter
showed lower vascular density in LA subjects when compared to normal subjects. They postulated that vascular
loss precedes parenchymal cell loss. According to these
studies, we speculate that the age-related loss of capillaries identified in the present study may have important
implications for the degeneration of the myelinated
fibers in white matter. However, the exact relationship
between the morphometric parameter changes of capillaries and myelinated fiber changes in aged white matter
needs to be investigated further. What are the likely
functional implications of the age-related loss of capillaries in the white matter? Adequate oxygen and substrate
supply are all dependent on the integrity of capillary
network. Dysregulated nutrient and/or oxygen transport
caused by the rarefaction of the capillary network would
upset the normal functioning of the surrounding neural
tissue, which might represent a precondition for the development of cognitive impairment. Therefore, we presumed that the capillary loss in white matter might be
one of the reasons for cognition decline during aging.
In conclusion, the present study, for the first time,
investigated the age-related changes of the capillaries in
rat white matter using stereological techniques. The
total length, total volume, and total surface area of the
capillaries in the white matter of aged rats were significantly decreased as compared to young rats. The agerelated changes of the capillaries in white matter may
have important implications for the age-related white
matter atrophy and cognitive impairments. An important goal of future research will be to relate these structural changes to myelinated fiber changes in white
matter and brain function changes that accompany normal aging.
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