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Department of Neuroscience and Anatomy, The Pennsylvania State University College of Medicine, Hershey Medical Center, Hershey, PA 17033 and * Graduate Program in Nutrition, The Pennsylvania State University, University Park, PA 16814
1To whom correspondence should be addressed.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSMeasurementsRESULTSDISCUSSIONREFERENCES |
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KEY WORDS: • iron deficiency • iron excess • rats • brain • development
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSMeasurementsRESULTSDISCUSSIONREFERENCES |
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). The association of iron
deficiency with biochemical, behavioral and cognitive alterations is
well documented, although the specific mechanisms are not yet
understood. Iron is unevenly distributed in the brain, with some
regions (i.e., substantia nigra, globus pallidus and ventral pallidus)
having high concentration of iron (Beard et al. 1993a
).
These iron-rich regions are also associated with dopamine (DA)
metabolism (Beard et al. 1993a
and 1994
, Youdim et al. 1989
). Researchers have shown a decrease in the total
amount of iron in the brain (Chen et al. 1995b
,
Erikson et al. 1997
), as well as alterations of DA
metabolism (Chen et al. 1995a
, Nelson et al. 1997
) in studies of the effects of ID in rats. The involvement
of excess iron in neurologic disease has received more attention in
recent years, especially in reference to the increased iron
concentration in the brains of patients with Alzheimer’s disease and
Parkinson’s disease (Beard et al. 1993b
, Connor et al. 1992a
, 1992b
and 1995
).
The effects of iron deficiency or iron supplementation on neurologic
function are likely to be affected by the neurologic maturity of the
animals. That is, the age of onset of the dietary iron deficiency may
have a vast effect on what has been reported with regard to how
much and where brain iron is lost, and on reversibility
with subsequent iron repletion. The effects of iron excess have not
been studied with the use of a developmentally sensitive design,
although it is common to find reports in the literature in which the
so-called control diet is really a diet with supplemental iron. It
must be noted that the development of the nervous system in rats does
not occur over the same time course relative to the development of
humans. Nonetheless, the process is assumed to be similar in the
sequence of events. Understanding the timing of the brain growth spurt
in different species is crucial for hypotheses that relate to
vulnerability (Dobbing and Sands 1979
). The human brain
growth spurt peaks between -2 and + 3 mo around birth, but in rats, it
peaks around postnatal days (PND) 7 and 10 (Dobbing and Sands 1979
). These periods of growth spurt cannot be taken as a
general rule because there is regional heterogeneity of the timing of
developmental events in the brain, with each small region, tract or
system having its own growth spurt and period of vulnerability. The
myelination process, an important one for brain function, coincides
roughly with the brain growth spurt for humans and rats (Davison and Dobbing 1966
). Another important difference between
humans and rats is that the bulk of iron acquisition during early
stages of development occurs mainly during the third trimester of
pregnancy in humans, and postnatally in rats, coinciding with the peak
of the myelination process.
There are no data on the response that iron deficiency and iron excess elicit on iron acquisition and distribution by the different brain regions of rats during early development. To investigate further the relationship between neurologic maturity and the effects of iron deficiency, excess and repletion, a set of experiments was designed with the rat as the animal model, and taking into account the neurodevelopmental differences between humans and rats mentioned above, as well as the differences in terms of early iron acquisition, so that more valid conclusions could be drawn from the results.
The overall hypothesis of these experiments is that iron deficiency and iron supplementation induce changes in brain iron, that these changes are not regionally uniform, and that they are age dependent, as well as duration and severity dependent. That is, early onset iron deficiency (early ID) or supplementation (early SU) affect brain iron metabolism in a different fashion than late onset and long-term ID and SU. Moreover, it is hypothesized that recovery from early ID is not complete after 2 wk of iron repletion.
The specific aims of the project were to determine the following:
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSMeasurementsRESULTSDISCUSSIONREFERENCES |
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A longitudinal design that used dietary and cross-fostering
strategies to create iron deficiency, iron excess and control groups of
rats was assembled. Such a design produces animals that are iron
deficient (ID), control (CN) or iron supplemented (SU) between PND 10
and 21, 21 and 35, or 10 and 35, with appropriate groups to test for
reversibility of iron depletion from the first period. To produce
dietary manipulations during the late lactational period (between PND
10 and 21) the pups from control dams were fostered to
iron-deficient or supplemented dams. The dietary manipulations
after weaning (after PND 21) were created by weaning the rats to the
corresponding control, iron-deficient or supplemented diet. The
design is illustrated graphically in Figure 1
.
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Male and female Sprague-Dawley rats (250-270 g and 150-170 g, respectively) were purchased from Harlan Sprague Dawley (Indianapolis, IN). The female rats were fed a control diet (CN, see below) upon arrival; the males were fed a commercial pelleted diet (Laboratory Rodent Diet, PMI Nutrition International, Brentwood, MO). At 200-220 g of body weight, the females were mated with a male for a period of 5 d (two females and one male), after which the rats were separated and the females placed in individual cages. Pregnancy was checked by the appearance of vaginal plugs under the cages during the mating period, and by recording the animal weight every other day.
At ~d 10 of pregnancy, counted from the appearance of vaginal plugs,
some pregnant dams were randomly switched to ID or SU diets. This date
was selected to allow for the dams receiving the ID diet to become iron
deficient by d 10 postpartum and to be used as foster dams for pups
born to CN dams. The first morning that pups appeared in the cage was
considered PND 1. At PND 4, the litter size was reduced to eight pups
per dam and, if possible, four males and four females. At PND 10, the
pups from CN dams were randomly assigned to ID, SU or another CN dam.
Hence, at PND 21, there were three groups of rats, i.e., CN, ID and SU.
At PND 21, the rats were randomly assigned to be weaned to a CN, ID or
SU diet, or to be killed, except for the SU group, which was assigned
either to a SU diet or killed (see Fig. 1
). As a result, at PND 35,
when the rest of the rats were killed, the following groups of rats
were generated: 1) IDID, rats that were ID from PND 10;
2) IDCN, rats that were ID from PND 10 to 21, and were
iron repleted with a CN diet between PND 21 and 35; 3)
IDSU, rats that were ID from PND 10 to 21, and were iron repleted with
a SU diet between PND 21 and 35; 4) CNID, rats that were
CN from PND 10 to 21, and were iron depleted with an ID diet between
PND 21 and 35; 5) CNCN, rats that were CN from PND 10 to
35; 6) CNSU, rats that were CN from PND 10 to PND21, and
iron supplemented between PND 21 and 35; and 7) SUSU,
rats that were SU from PND 10 to 35.
The diets were mixed in our laboratory, following the defined
composition of the AIN-93G diet (Reeves et al. 1993
),
but using cornstarch as the only source of carbohydrates in the
mixture.
The amount of iron in the mineral mix was manipulated by the addition of iron citrate to produce a diet containing 3.5 mg Fe/kg diet (ID diet), 35-40 mg Fe/kg diet (CN diet) or 400 mg Fe/kg diet (SU diet).
Upon analysis of the diets by flame atomic absorption spectrophotometry after wet digestion with nitric acid, the iron content of the diet was measured to be (mean ± SEM) 39.7 ± 0.8 mg/kg (CN diet), 3.04 ± 0.4 mg/kg (ID diet) and 420 ± 8.1 mg/kg (SU diet).
All of the rats were housed individually under controlled environmental conditions (0600-1800 h light cycle and 25°C) and were provided free access to food and water. Food intake and body weight were recorded every other day. All animal procedures were approved by The Pennsylvania State University Animal Care and Use Committee.
The dams’ iron status was closely followed by measuring hemoglobin (Hb) and hematocrit (Hct) before mating, and at midpregnancy, delivery, midlactation and weaning. The pups Hb and Hct were determined at PND 10, 14, 17, 20, 27 and 35. The blood samples were collected via tail prick.
Specimen collection.
The rats were anesthetized with Halothane; blood samples were collected directly from the heart with a heparinized syringe after a laparatomy was performed, and aliquots were analyzed for Hb and Hct. The remaining blood was refrigerated and plasma separated by centrifugation at 4°C and 1000 x g for 15 min. Plasma was frozen at -20°C before analysis for Fe and total iron-binding capacity (TIBC).
The rats were perfused with ice-cold 0.1 mol/L PBS solution, pH 7.3, through the left ventricle, with drainage through the right atrium, until the effluent was clear. The brain, liver and spleen were removed, frozen on dry ice and kept at -70°C for further analyses. Some brains from each group and sex were randomly selected and fixed by immersion in 40 g/L neutral buffered paraformaldehyde overnight, then cryoprotected by floating in sucrose (0.29, 0.58 and 0.87 mol/L) sequentially, and refrigerated at 4°C in 0.87 mol/L sucrose for histochemical determinations.
The brains perfused with PBS and frozen were dissected into the
following regions: cerebral cortex (CX), deep cerebellum nuclei (DCB),
superficial cerebellum (SC), hippocampus (HC), pons (PS), striatum
(ST), substantia nigra (SN) and thalamus (TH) according to published
methods (Focht et al. 1997
). The regions were dissected
on a cold aluminum block and frozen at -70°C. These samples were
later diluted with 0.32 mol/L sucrose (S 7903, Sigma, St. Louis, MO)
1:4 (wt/v) and homogenized with the use of a sonicator with a microtip
(Branson Sonifier 250, Branson, Danbury, CT) on pulse mode. Aliquots
for the different analyses were separated and frozen at -70°C.
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Measurements |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSMeasurementsRESULTSDISCUSSIONREFERENCES |
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Hemoglobin was measured colorimetrically by the cyanmethemoglobin method (procedure # 525, Sigma, St. Louis, MO). Hematocrit was determined by centrifugation of blood collected into heparinized microcapillary tubes.
Plasma iron and TIBC were determined by the colorimetric method
described by Cook (1980a)
modified to use 50
µL of sample. Transferrin saturation was calculated by
expressing the ratio plasma Fe/TIBC as a percentage. Liver nonheme iron
was determined by the standard colorimetric technique described by
Cook (1980b)
with ferrozine as the color reagent.
Brain total iron.
This was measured according to the method described by Erikson et al. (1997)
.
Total protein.
The brain tissue homogenates were diluted 1:50 with 10 mmol/L PBS, pH 7.4, and their protein concentration was determined by the micro-Lowry method (P5656, Sigma, St. Louis, MO) modified for the use of 96-well plates and 30 µL of sample.
Ferritin.
Ferritin concentration in the different brain regions was measured by
immunoblot according to the immunosorbent technique previously
described (Roskams and Connor 1994
). The total protein
concentration loaded into the slots was 5 µg/100
µL. The primary antibody was used at a 1:2000 dilution,
and the secondary antibody was diluted 1:5000. The primary antibody was
an mouse anti-rat liver ferritin monoclonal antibody (a generous
gift of James Cook, University of Kansas Medical Center, Kansas City,
KS); the secondary antibody was sheep anti-mouse immunoglobulin G
(IgG) alkaline phosphatase conjugated (A5324, Sigma). The ferritin
standard used was rat liver ferritin (F-7005, Sigma). An internal
standard composed of a pool of brain homogenate was analyzed on each
membrane to ensure quality control between assays. All measurements
were performed using a Eagle-Eye Densitometer (Stratagene, San
Diego, CA). Regression analyses were performed on the acquired
densities of the standard curves on each membrane, and the
concentration of samples was determined.
Transferrin.
Transferrin concentrations in the different brain regions were measured by ELISA, using a method recently developed in our laboratory. The procedure was as follows: on d 1 of the assay, 96-well plates (flat bottom, Nunc MaxiSorp) were coated with the standards [1 ng to 31.25 pg of rat transferrin (A-3937, Sigma)], and the samples (5 µg of total protein for CX, DCB, SC, ST and TH, and 3 µg for HC, PS and SN) in triplicate, sealed and incubated at 4°C overnight. On d 2, the plates were washed three times with Tris-buffered saline solution (TBS)-Tween buffer (200 µL/well); 100 µL of 10 g/L bovine serum albumin (BSA) in 0.15 mol/L TBS was added to each well, and then the plates were incubated for 1 h at room temperature. After the incubation, the wells were aspirated and 100 µL rabbit anti-rat transferrin polyclonal antibody (a generous gift of Richard Fine, Boston University, Boston, MA) diluted 1:2000 in 10 g/L BSA-TBS was added. The plates were sealed and incubated overnight at 4°C. On d 3, the plates were washed three times with TBS-Tween buffer (200 µL/well), and 100 µL of secondary antibody (goat anti-rabbit IgG alkaline phosphatase conjugated antibody diluted 1:4000 in 10 g/L BSA) was added to each cell. The plates were then sealed and incubated at room temperature for 1 h. After the incubation, the plates were washed again three times with TBS-Tween buffer, and 100 µL substrate buffer [p-nitrophenyl phosphate disodium (N-2765, Sigma) dissolved in 1 mol/L diethanolamine buffer, 0.5 mmol/L MgCl2, pH 9.8] was added to each well. The plates were sealed and incubated at room temperature until color developed (~40 min). The reaction was then stopped by adding 100 µL of 2.5 mol/L NaOH per well, and the plate read in a plate reader (Model EL340, Bio-Tek Instruments, Winooski, VT) with dual wavelength at 405/570 nm. A blank of reagents and an internal standard composed of a mixture of brain homogenates were analyzed on each plate. Regression analyses were performed for the standard curve on each plate and Tf concentration calculated for the samples accordingly. The coefficient of determination (r2) for the standard curves was always >0.97. An interassay CV of 4.7% was estimated by using the internal standard values from each plate.
Transferrin receptor.
The concentration of TfR in the different brain regions was measured by means of the same ELISA procedure described for transferrin, with the following differences: the primary antibody was mouse anti-rat transferrin receptor (MCA-155, Serotec, Oxford, England) diluted 1:2000. The secondary antibody was sheep anti-mouse IgG alkaline phosphatase conjugate (A-5324, Sigma) diluted 1:4000. Sample (5 µg) was added per well in triplicate for each one of the regions. The substrate reaction was extended to 90 min for optimal color development. It was not possible to construct standard curves for this ELISA because there is no commercial rat TfR standard available. Instead, CN, ID and SU brain homogenate mixtures were used on each plate as internal standard to correct for plate-to-plate variability. The interassay CV for the internal standard was 7%. For the purpose of comparisons among groups, the results were expressed as absorbance per microgram of protein.
Statistical analyses.
Data were analyzed using the SAS System for Windows v6.12 statistical
analysis package (SAS Institute, Cary, NC). Factorial ANOVA with two
between-group factors was used to evaluate the interactions between
sex and groups. One-way ANOVA with one between-group factor
followed by Dunnett’s post-hoc test was used to evaluate whether
the experimental treatments were different from their adequate controls
for the different variables. The 
-level for the analyses was set at
P < 0.05, and the data were tested for normality. Data
are reported as means ± SEM All means presented are
for males and females combined because sex and group x sex
interactions were not significantly different in any analysis.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSMeasurementsRESULTSDISCUSSIONREFERENCES |
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Early iron deficiency.
Rat pups were made iron deficient by cross-fostering them to an
iron-deficient dam at PND 10. Some of these pups were killed at PND
21 (ID group). Brain iron concentration was ~20-25% lower in ID rats
compared with age-matched CN rats (P < 0.001) in
most, but not all brain regions (Table 1
). The clear exception was the thalamus, which was virtually unaffected
by low iron intake for 11 d. Transferrin receptor (Table 1)
was
up-regulated 20-25% (a level comparable to the drop in iron
concentration) in most but not all brain regions in response to iron
deficiency; HC was not responsive. Striatum and superficial cerebellum
had a TfR concentration 50% greater than that of controls, but this
did not prevent the 25% lower iron concentration. Immunohistochemical
evaluations of brains from these rats revealed that much of this change
was in endothelial cells, and some in microgial cells (photomicrographs
not shown).
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. With the
exceptions of SC, in which Tf concentration nearly doubled, and ST
(>75%), the rest of the regions had more modest changes. The pons
transferrin concentration did not respond to dietary iron deficiency,
despite a 25% decrease in iron and a 40% increase in TfR. Ferritin
and iron concentrations fell in iron deficiency in a seemingly
appropriate, proportional amount (Table 1)
because most regions had
15-20% lower ferritin concentration compared with CN.
Late iron deficiency.
Some rats fed the control diet between PND 10 and 21, were then fed an
iron-deficient diet for 14 d after weaning to create a state
of postweaning or late iron deficiency (CNID). Brain iron was
significantly lower for all brain regions except HC. Compared with the
CNCN group, the CNID group lost 36 and 33% of iron for DCB and SC,
respectively, and ~20% for all other regions except HC (8%)
(Table 2
). Transferrin receptor concentrations were significantly higher for all
regions except DCB compared with the control group (Table 2)
. The two
regions with the largest drop in iron concentration, DCB and SC, are
also the two with the smallest increase in TfR concentration.
Transferrin concentrations increased significantly for all regions
(Table 2)
, up to 92, 90 and 72% for CX, SC, and DCB, respectively, and
to 35% for HC, SN and TH. The L-ferritin was not as
responsive to the dietary iron deficiency in this period (Table 2)
.
Although the overall brain ferritin concentration was lower in the CNID
rats, the only significant regional change was in ST, the region with
the lowest concentration of ferritin in the CNCN group.
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), although the difference ranged from 53% lower for DCB to 20% for
CX, HC and TH. Although there was a 5-10% extra loss of brain iron
when iron deficiency was continued from weaning to PND 35, not all
regions responded in the same way. For some regions such as CX, HC and
ST, the percentage of change was the same at PND 21 as at PND 35. For
other regions such as DCB, PS and TH, the loss of iron postweaning was
considerably greater than lactational iron deficiency at PND 21.
Transferrin receptor concentrations were significantly increased for
all regions (Table 3)
, with four regions, CX, HC, PS and SC, nearly
doubling the concentration compared with their controls. The least
responsive of all brain regions was SN with 59% higher TfR
concentration than CNCN. In most regions, however, the change in TfR
was twice as high as that observed in the early ID rats, except in ST,
in which the percentage of change was the same at both times.
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. Of all regions, HC, SC, SN
and TH were the most responsive, and DCB and ST were the least
responsive. Ferritin concentrations decreased significantly for all
brain regions except DCB and ST (Table 3)
in this paradigm of iron
deficiency, which spanned two developmental periods. As noted
previously with transferrin, both superficial cerebellum and SN were
the most responsive, with a 40% decrease in ferritin concentration.
Although long-term ID had greater effects on ferritin concentration
in several brain regions (CX, PS, SC and SN), other regions showed much
greater developmental dependence. For example, the response in TH was
the same, proportionally, in ID and IDID, indicating no further loss of
iron and ferritin. Recovery from iron deficiency
Some rats that were iron deficient from PND 10 to 21 were
repleted with iron after PND 21 by weaning them onto either the control
diet (IDCN) or the supplemented diet (IDSU). Brain iron concentration
increased significantly in all brain regions of ID rats within 14 d of repletion with either the CN or SU diet (Table 4
). In comparing the iron concentration in each region with that of rats
who had not been iron deficient (CNCN), we observed normalized iron
concentrations in CX, HC and SC with control diet repletion, and
further normalization in PS, ST and TH with supplemented diet
repletion. Only DCB and SN continued to have lower iron concentrations
than those of CNCN at the end of this brief repletion period.
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. In comparison to CNCN as the age appropriate
controls, TfR concentrations for IDCN were normal in all brain regions
except HC, in which it was still significantly higher, and fell to
levels significantly below CNCN concentrations in several brain regions
(CX, DCB, HC, PS and SC) when the rats were repleted with the SU diet
for 2 wk. The levels of TfR were not the same for the different
regions, and the response tended to be associated with the levels of
iron in the diet used to replete the rats. Thus, the rats repleted with
control diet had a smaller TfR response than those repleted with the
supplemented diet, except for SN, ST and TH (Table 4)
. Transferrin
concentrations were normalized in all regions, with the exception of SN
and ST, which required the higher amount of dietary iron to return the
Tf concentrations to normal (Table 4)
, and HC and PS, which
down-regulated the levels of Tf significantly compared with the
CNCN. The heterogeneity of Tf distribution was apparent, with regions
such as TH having a concentration ~75% lower than HC and ST (Table 4)
.
Brain L-ferritin concentrations were affected only modestly
in most brain regions during the early ID period; thus, it is not
surprising that iron therapy resulted in the normalization of
concentration with the control repletion (Table 4)
. Interestingly, ST
was quite unresponsive to CN or SU repletion.
Effects of iron supplementation on brain iron metabolism
Early iron supplementation.
Iron supplementation during the late period of lactation produced a
larger iron increment in DCB and HC (45 and 38% higher than CN,
respectively) than any other brain region analyzed (Table 1)
. Striatum,
in contrast to other brain regions, did not show any change associated
with iron loading during this period. Iron loading led to a highly
variable response in the TfR concentration during this period of early
iron deficiency, with no down-regulation in ST, and yet a large
response in SN (>50% lower than CN) (Table 1)
.
The concentration of transferrin decreased only mildly in response to
iron supplementation. In PS, HC, SC and SN, Tf concentrations were
< 5% lower compared with CN. Striatum was also the most
responsive region to iron loading (25% lower Tf than CN) (Table 1)
.
Iron and ferritin did not increase in a consistent fashion with iron supplementation. The region with the largest increase in iron concentration (DCB), for example, did not have the largest increase in ferritin (SC).
Late iron supplementation.
Iron supplementation during the postweaning period (CNSU) produced a
smaller increment in iron concentration than during the previous period
(SU) (Table 2)
for every region analyzed. Striatum, SN and SC showed
only a small change associated with iron loading during this period.
The down-regulation of the transferrin receptors was not very
substantial in most regions (Table 2)
, with the exception of SC, which
showed a marked increase in the response compared with the change that
occurred during the early supplementation period.
Transferrin concentrations were between 10 and 20% lower than controls
in most regions except ST (40%) during this late iron-loading
period (Table 2)
. Iron supplementation induced higher ferritin
concentrations in practically all regions except HC and TH (Table 2)
.
Long-term iron supplementation.
A number of rats from the supplemented group (SU) also were fed an
iron-supplemented diet after PND 21 up to PND 35. These rats,
therefore, were provided high dietary iron from PND 12 to 35 (SUSU).
The iron concentration of the different regions of the brain responded
differently to this cumulative iron loading. Cortex, HC and SC
accumulated between 20 and 30% more iron than their counterpart CNCN,
but DCB and SN had less than a 10% increase (Table 3)
.
The transferrin receptor was down-regulated to a similar degree in
most brain regions as it was during the early iron supplementation
(Table 3)
. The exceptions, HC and SN, demonstrated only half of the
ability to decrease that they had earlier. The amount of TfR in
striatum was not responsive to supplementation during any period.
However, ST had the largest decrease in Tf of all regions, almost a
50% change, whereas SN did not show any change
Superficial cerebellum and TH had a large increase in ferritin concentration associated with long-term supplementation with iron (>40%). The other regions accumulated ~20% more ferritin than the control, except CX, which had only a 10% increase.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSMeasurementsRESULTSDISCUSSIONREFERENCES |
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The reduction of brain iron in specific brain regions, with lactational
iron deficiency, extends the previous observations that brain iron
concentration can be reduced rapidly with postweaning iron deficiency
(Chen et al. 1995b
, Erikson et al. 1997
and 1998
). The quantitative decline in brain iron concentration
over the 10 d of consuming low iron milk was not equal in all
brain regions, nor was this sensitivity the same as that observed in
studies of later iron deficiency. Cortex and HC lost less iron in the
late ID than in the early ID, whereas DCB, SC and TH were more affected
during the late ID; the rest of the regions did not differ
substantially between the two periods. However, the most dramatic
change was in TH, almost resilient to the deficiency during the early
anemia, and having 20% less iron with either late or long-term
anemia. These data show that the sensitivity to iron deficiency is
developmentally linked. It appears that adaptive responses to protect
against iron depletion were more successful in some regions. Perhaps
regional needs for iron were lower in the regions with smaller change,
preventing a large decline in iron concentration.
The repletion studies demonstrated that the brain is fully capable of
regaining iron in a rapid fashion, despite the early reports that brain
turnover (or more exactly, brain iron loss from the body) is a very
slow process (Dallman et al. 1975
, Dallman and Spirito 1977
). This capacity to replete iron in all brain
regions is not supported by the accepted notion in the scientific
literature that iron deficiency in the preweaning period leads to
irreversible alterations in brain size and iron concentration
(Dallman and Spirito 1977
, Felt and Lozoff 1996
). Previous studies from our research group demonstrated
rapid reversibility of regional brain iron concentration after
postweaning iron deficiency (Erikson et al. 1997
).
Others have shown increases in iron uptake into the brain in iron
deficiency and that the increased transcytosis of iron and Tf that
occurs across the blood brain barrier (BBB) (Crowe and Morgan 1992
) can account in large part for this rapid recovery of
brain iron concentration. The brain obtains iron via regulation of the
Tf receptor on the surface of endothelial cells on the brain
microvasculature (Kalaria et al. 1992
, Morris et al. 1992
). The data in this study and unpublished histochemical
analysis concur that endothelial cells are the most identifiable cell
type that responds to iron deficiency via up-regulation of the TfR.
There is a large regional variation in the quantitative ELISA data,
which suggests that regional regulation of movement across the BBB does
in fact occur (Hill et al. 1985
). The increase in uptake
of iron observed in iron deficiency is not reflective of overall
changes in BBB permeability, and is highly selective to iron and Tf.
Although actual kinetic data were not collected in this experiment, it
is reasonable to assume that up-regulation of transferrin receptors
is responsible in part for this alteration in uptake.
The regional specificity for brain iron acquisition is of great
interest because the distribution of iron in the developing brain is
not the same as that in the adult brain (Connor 1994
,
Focht et al. 1997
, Hill 1988
,
Roskams and Connor 1994
). In a recent quantitative study
using 10-wk-old Fisher 344 rats, Focht et al. (1997)
reported nearly equivalent concentrations of iron in the striatum,
hippocampus, thalamus and frontal cortex, followed by brain stem,
medial cortex, pons and cerebellum. Although the amount of iron was
about three times the amount measured here, there is a rough similarity
in iron distribution between the two studies. Systematic evaluations of
strain differences in brain iron distribution in rats have not been
conducted, but rat strain as well as mouse strain differences in the
response to dietary iron have been reported (Morse et al. 1999
, Rao and Jagadeesan 1995
).The
substantia nigra, an iron-rich region in the adult rat brain as
assessed by histochemical methods (Hill 1988
), had the
highest iron concentration in these young rat brains at PND 21 and 35.
This region had TfR values very close to the control and a large
increase in Tf concentration during iron repletion, suggesting that
iron was somehow ‘targeted’ to go to the substantia nigra. In studies
of uptake and distribution of iron in the brains of young rats, it has
been suggested that mechanisms may exist for the translocation of iron
from one area of the brain to another (Dwork et al. 1990
). It is interesting to recall that iron accumulates in the
substantia nigra, globus pallidus and caudate of elderly humans, in
particular those with Alzheimer’s disease and Parkinson’s disease
(Good et al. 1992
, Loeffler et al. 1995
).
The transferrin receptor data, although only relative because we could
not calculate the actual amount of the protein, are valuable in the
sense that it is probably the first time that they have been measured
under these very well-controlled experimental conditions. These
data show that some regions such as striatum are very responsive to
iron deficiency early in development, up-regulating the synthesis
of TfR, but that this is not the case if the deficiency occurs after
weaning. Other regions such as HC and CX responded better to the
deficiency during the late, rather than the early period of iron
deficiency.
In a previous study, we found very little association between iron and
ferritin concentrations in the different brain regions when an antibody
not specific to a ferritin isomer was used (Erikson et al. 1997
). In a correlation analysis using all rats in this study,
ferritin concentrations paralleled those of iron in all brain regions
except TH and ST. This supports the assumption that
L-ferritin, even in developing brain, is designed to store
nonessential amounts of iron in cells. H-Ferritin analyses are
ongoing and may provide further insight into the regulation of iron
movement.
Iron is important for normal dopamine functioning in regions connected
to the substantia nigra (Chen et al. 1995a
,
Youdim et al. 1989
). The substantia nigra is also rich
in both iron and dopaminergic neurons (Hill 1988
). The
nigro-striatal dopaminergic pathway in the striatum has been found
to be sensitive to iron deficiency with both decreases in dopamine
D2 receptors and increases in extracellular dopamine
observed (Ashkenazi et al. 1982
, Chen et al. 1995a
, Youdim et al. 1989
). Recent studies from
our laboratory demonstrated that extracellular dopamine concentrations
in the striatum return to normal within the same time frame for
restoration of ventral midbrain iron concentration (Nelson et al. 1997
). In addition, radioligand binding studies have
demonstrated alterations in dopamine transporters in striatal pathways
in iron deficiency (Morse et al. 1999
).
Although the traditional view has been that the brain is resistant to excess dietary iron, this experiment is the first to evaluate the effects of iron excess on brain iron. Our data show that dietary iron excess can increase brain iron concentration, and that this increase is developmentally linked and not uniform for the different brain regions. This is very important because many studies of the effects of iron deficiency on brain iron have used control diets comparable to our supplemented diet. This could lead to artificially large differences between the two groups because dietary iron excess does increase brain iron.
One of the strengths of our experimental design is that it addresses
the developmental differences between humans and rats, and matches the
initiation of the nutritional injury to a developmental stage that is
similar in the two species. The greatest prevalence of iron deficiency
occurs in infants after 6 mo of life, with an increased risk after the
first 4 mo, especially if the infant was premature or bottle-fed
and did not receive iron supplements during this period (Allen 1997
, de Andraca et al. 1997
). The experimental
design used in this study closely matches the rat to the same
neurodevelopmental stage an infant would be by the time the risk for
iron-deficient anemia is greater, i.e., PND 10 in rats and 4-6 mo
of life in the infant, thereby defining a better animal model for the
study of the pernicious effects of iron deficiency early in life.
In conclusion, the results of this study suggest that the effects of nutritional iron deficiency and excess on brain iron metabolism are tightly associated with the brain development patterns. Although the different brain regions seem to be capable of regulating their iron concentration in response to local needs, when faced with an alteration in systemic iron delivery, the substantial TfR response suggests that this is a primary mechanism for local regulation, and this response was found to be developmentally dependent.
|
FOOTNOTES |
|---|
Manuscript received April 12, 1999. Initial review completed July 19, 1999. Revision accepted October 11, 1999.
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L. E. Murray-K |
