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Departments of
*
Nutrition,
Anatomy, Physiology and Cell Biology (Veterinary Medicine),
**
Food Science & Technology and
Internal Medicine, University of California, Davis, CA 95616
2To whom correspondence and reprint requests should be addressed.
 |
ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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KEY WORDS: • iron deficiency • marginal iron • dopamine • myelin • c-aconitase • m-aconitase • mice
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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). In numerous epidemiologic studies, improved iron status
has been positively correlated with enhanced cognitive and motor
performance (Idjradinata and Pollitt 1993
,
Pollitt et al. 1997
, Seshadri and Gopaldas 1989
, Soewondo et al. 1989
); however, the
long-term effect of iron deficiency during early development on
biochemical and behavioral outcomes has not been established. A recent
study by Hurtado et al. (1999)
found that early
childhood anemia was one factor linked to an increased risk for mental
retardation later in life. Although these human studies do not clearly
establish dietary iron deficiency as a causative factor in abnormal
brain development, work in animal models supports the concept that
dietary iron restriction can result in early developmental defects. For
example, in rodent models, both moderate and severe iron deficiency
have been shown to cause alterations in activity patterns and motor
development (Edgerton et al. 1972
, Kwik-Uribe et al. 1999
, Weinberg et al. 1979
and 1980
), as
well as diminished cognitive performance (Felt and Lozoff 1996
, Kwik-Uribe et al. 2000
, Massaro and Widmayer 1981
, Williamson and Ng 1980a
and 1980b
, Yehuda et al. 1986
).
Given the higher prevalence of iron deficiency without anemia in
children, we recently used a murine model to study the behavioral and
biochemical effects of chronic marginal iron intakes during early
development. Using this model, we demonstrated that marginal iron
status can result in persistent changes in brain iron, as well as
disruptions in both motor and cognitive performance (Kwik-Uribe et al. 1999
and 2000
). Having observed these outcomes, the
objective of our current work was to begin to examine mechanisms that
may underlie the observed behavioral changes.
Iron, which is localized within dopamine (DA)-rich brain regions, has
been shown to have a role in DA metabolism and function. In addition to
inducing changes in DA-dependent behaviors (Youdim et al. 1984
, Youdim and Yehuda 1985
), iron deficiency
has been reported to disrupt the concentrations of DA and its
metabolites within the brain (Beard et al. 1994
,
Nelson et al. 1997
). Studies have also shown that iron
deficiency can cause a down-regulation of DA
D2 receptors in the caudate-putamen of
iron-deficient rats (Ashkenazi et al. 1982
,
Ben-Shachar and Youdim 1990
, Youdim et al. 1984
). Given these findings identifying iron-induced
disruptions in DA-mediated behaviors and DA metabolism, one
objective of the current study was to determine whether chronic
marginal iron intakes during early development could induce similar
changes in DA metabolism within the caudate and cortex of marginally
iron-deficient mice.
In addition to altering DA metabolism, iron deficiency has been
suggested to disrupt brain function by inducing changes in brain fatty
acid composition. Because iron is an essential cofactor for lipid and
cholesterol synthesis, several animal studies have shown that a severe
iron deficiency during early development can result in disruptions in
brain lipid composition (Larkin et al. 1986
,
Oloyede et al. 1992
) and hypomyelination (Yu et al. 1986
). In the central nervous system, myelin is a
lipid-rich membrane composed of oligodendrocytes. These
oligodendrocytes are enriched in iron and transferrin (Connor and Benkovic 1992
); furthermore, transferrin has been
identified as an essential factor for myelination (Espinosa de los Monteros et al. 1999
). Given that behavioral changes have
been related to disruptions in brain fatty acid composition [reviewed
in Wainwright (1992)
], we wanted to determine whether
chronic marginal iron intakes during the period of oligodendrocyte
maturation and myelination could produce changes in myelin fatty acid
composition.
Previous work with our murine model demonstrated that chronic marginal
iron intakes can result in significantly lower brain iron
concentrations (Kwik-Uribe et al. 1999
and 2000
). Such
changes may result not only in some of the biochemical changes
described above, but could also contribute to changes in the activity
and binding of proteins critical to cellular iron homeostasis. Iron can
modulate the expression of a number of proteins including transferrin
receptor, ferritin, erythroid 5-aminolevulinate synthase
(eALAS)3and m-aconitase by altering the binding activity of specific iron
regulatory proteins (IRP) to iron-responsive elements (IRE) within
the 3' or 5' untranslated regions (UTR) of each protein’s mRNA
sequence (Eisenstein and Blemings 1998
). Two binding
proteins are known to exist, IRP-1 and IRP-2. IRP-1 is a bifunctional
protein that can act as a cytosolic aconitase (c-aconitase) or as an
iron regulatory protein, depending on cellular iron status. When
cellular iron concentrations drop, the iron-sulfur cluster (4Fe-4S)
in the active site of c-aconitase disassembles; thus, the protein
(now an apoprotein) loses its enzymatic activity to become the IRE
binding protein, IRP-1. The binding of this protein to
IRE-containing mRNAs can simultaneously result in the increased
translation of transferrin receptor (by increasing the stability of the
message) and a decreased translation of ferritin, eALAS and
m-aconitase (by blocking ribosomal assembly). Several recent in
vivo studies demonstrated the ability of dietary iron intakes to
modulate the activity of m-aconitase in the liver (Chen et al. 1997
and 1998
); therefore, we wanted to determine whether
similar changes in m- or c-aconitase activity in the brain could be
produced as a consequence of chronic marginal iron intakes during
development.
Given the diverse physiologic roles of iron, it is likely that iron
deficiency affects behavioral performance through multiple mechanisms.
The goal of this study was to determine whether the behavioral
disturbances reported previously (Kwik-Uribe et al. 1999
and 2000
) could be attributed in part to changes in the
iron-sensitive biochemical functions described above; furthermore,
we wanted to determine to what extent these changes could be overcome
by the postnatal consumption of iron-supplemented diets. We
hypothesized that chronic marginal iron intakes would result in changes
in both DA metabolism and myelin fatty acid composition. Furthermore,
given the recent demonstration that liver IRP-1 is responsive to
dietary iron intakes (Chen et al. 1997
and 1998
), we
hypothesized that the brain would be similarly responsive to these
changes in iron status, producing both decreased c- and m-aconitase
enzyme activities in response to the marginal iron deficiency. In
contrast, we expected that succinate dehydrogenase, another
mitochondrial enzyme containing an Fe-S cluster but no IRE, would
not demonstrate changes in enzyme activity in response to disruptions
in tissue iron concentrations. Finally, we examined the reversibility
of any observed biochemical changes after the restoration of adequate
iron status in the marginally iron-deficient offspring.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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The animal protocol used was in accordance with NRC
(1996)
guidelines and was approved by the University of
California, Davis Animal Use and Care Committee. Virgin female
Swiss-Webster mice were purchased from a commercial supplier
(Charles River, Willmington, NC) at 3 wk of age. Mice were housed in
groups of 2–3 in suspended stainless steel cages and maintained on a
normal 12-h light:dark cycle. All mice were adapted to a control
purified diet containing 75 µg Fe/g diet (Table 1
) for 1 wk before the onset of the study. After this acclimation period,
the mice were randomly assigned to a diet group and fed this diet
throughout the duration of the study. After 8 wk of consuming the diet,
the females were mated and a successful pregnancy was identified by the
presence of a vaginal plug (designated gestation d 0, GD 0). On GD 17,
pregnant mice were transferred from the stainless steel cages to
plastic hanging maternity cages. Cages were filled with a shallow layer
of sawdust shavings and a small ball of cotton was provided for use as
nesting material. When necessary, litter size was reduced to 8 pups
(1:1 male-to-female ratio) within wk 1 after birth. At weaning
(postnatal d 21; PND 21), 1 male and female pup from each litter and
their corresponding dam were killed for assessment of iron status. The
remaining pups (3 males and 3 females/litter) were separated and
same-sex littermates were housed in suspended stainless steel cages
(3 pups/cage). The mice were earmarked for identification purposes and
were assigned to one of three treatment groups. Housing constraints
made individual food intake measurements for offspring impossible;
thus, food intake was measured daily on a per cage basis. Individual
weight gain was measured weekly from PND 21 through PND 75.
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The purified diets were based on egg-white as the protein source
and contained either 14 µg Fe/g diet (marginal iron
diet) or 75 µg Fe/g diet (control iron diet) (Table 1)
. All other minerals were consistent with recommendations of the
NRC (1996)
, and mineral concentrations were verified by
inductively coupled plasma spectroscopy (trace scan ICP; ThermoJarrel
Ash, Franklin, MA) before the onset of the study. The marginal Fe diet
used in this study was previously shown to result in lower iron status
in offspring without resulting in significant changes in hematological
iron markers in adult offspring (Kwik-Uribe et al. 1999
). All mice consumed deionized water ad libitum throughout
the duration of the study.
Design.
Dams. After 1 wk of consuming the purified control diet, weight-matched females were fed either the control (n = 21) or marginal iron (n = 45) diet. To further deplete iron stores, each mouse in the study was subjected to a tail bleed every 3–5 d starting at wk 5 of the study. Blood (100 µL) was collected into heparinized collection tubes at each draw. Depending on the weight of the mouse, 6–9 blood collections were done over the 3-wk draw period; thus the total volume of blood collected represented 45–55% of the animal’s total blood volume. One week after the last tail bleed, mice were mated with a Swiss-Webster male fed a commercial diet (Harlan-Teklad Rodent Chow, Madison, WI). All mice were pregnant within 3 wk of the start of breeding. All females were fed their respective diets from the start of the study through PND 21 of their offspring. Weights of each female were recorded weekly from the start of the study and every 3 d during gestation. To ensure an adequate number of offspring for the study, only dams with 8 live pups at PND 21 were considered eligible for the study.
Offspring. Offspring were weaned on PND 21 and assigned to one of three experimental groups. Offspring born to marginal iron females were either maintained in the marginal iron group (14 µg Fe/g diet-marginal iron group; n = 16 litters/sex) or were switched to the control iron diet (75 µg Fe/g diet-replete group; n = 13 litters/sex). Offspring born to control dams consumed the control diet (75 µg Fe/g diet) ad libitum (75 µg Fe/g diet-control group; n = 13 litters/sex). Diets were fed from PND 21 through PND 75 and food intake was recorded daily on a per cage basis.
Male and female offspring in this study were also subjected to
neurobehavioral testing at multiple time points throughout the study.
The results of these behavioral outcomes are reported elsewhere
(Kwik-Uribe et al. 2000
).
Tissue sampling and mineral analysis.
Male and female mice were killed by cervical dislocation on PND 75.
Tissues from one male and one female from each litter were assigned to
each of the following measurements: 1) caudate and
cortex DA concentrations, 2) myelin fatty acid
composition, or 3) enzyme activities. To minimize
artifactual changes in DA and DA metabolites, caudate and cortex
samples used for DA analysis were isolated according to methods
previously described (Kwik-Uribe et al. 1999
) and placed
into liquid nitrogen within 2–3 min of cervical dislocation. The
remaining brain regions were pooled and used for determining brain
mineral concentrations as described below. Blood used for hematocrit
and hemoglobin concentrations was collected from trunk blood. For the
remaining mice, blood was collected from the heart into heparinized
syringes after surgical exposure of the heart. After blood collection
(and brain removal in the case of mice examined for DA activity), mice
were perfused through the heart with ice-cold sodium chloride (8.8
g/L) and whole brain (where available) and liver removed. Tissues used
for myelin isolation and enzymatic assay were handled according to the
procedures described below. When each mouse was killed, tissues used
for mineral analysis were frozen in liquid nitrogen and stored at
-20°C until analyzed. For tissue iron, zinc, copper and manganese
concentrations, mineral analysis was done using inductively coupled
plasma spectroscopy (trace scan ICP; ThermoJarrel Ash) after wet ashing
with nitric acid as previously described (Clegg et al. 1981
). The measurement accuracy for the elements in the
National Bureau of Standards bovine liver standard 1577b (National
Institute of Standards and Technology, Gaithersburg, MD) was 101.2
± 4.8% relative standard deviation for analyzed metal
concentrations >0.05 µg/g, with analytical detection
limits of 0.010 µg/g.
Myelin isolation.
Brain myelin was isolated according to a modification of the procedure
described by Farooq et al. (1981)
. The whole-brain
sample was homogenized in 10 volumes of 0.32 mol/L sucrose using a
hand-held glass homogenizer. This homogenate was then layered onto
14 volumes of 0.8 mol/L sucrose and centrifuged for 70 min at 78,000
x g in a swinging bucket rotor. The myelin
interface was collected and added to 30 mL of ice-cold ultrapure
water. This solution was inverted several times, kept on ice for 20 min
and then centrifuged at 11,000 x g for 20 min in a
fixed angle rotor. The myelin pellet was resuspended in the same volume
of 0.32 mol/L sucrose used in the initial homogenization. The 78,000
x g and 11,000 x g
centrifugation steps described above were repeated. One additional
washing with 30 mL of ice-cold water and centrifugation at 11,000
x g were done to ensure that a clean myelin
fraction was obtained. The final pellet was resuspended in 0.5 mL of
ultrapure water and stored at -80°C until the time of analysis. All
isolation steps were done at 4°C.
Myelin fatty acid analysis.
Lipids were isolated from the myelin sample according to the method of
Folch et al. (1957)
. The final ratio of
chloroform/methanol/water was maintained at 8:4:3 (v/v/v). To minimize
oxidation, 0.02 g/L BHT was added to the chloroform and methanol before
use in the extraction procedure. Phosphatidylcholine (15:0) was used as
the internal standard. Lipid samples were purged with nitrogen gas and
stored at -80°C until the time of analysis. All samples were
analyzed by gas chromatography-mass spectrometry within 2 wk of the
lipid extraction.
For the total fatty acid analysis, the samples were transmethylated for 60 min at 95°C. The fatty acid methyl esters (FAME) formed were neutralized with K2CO3, reextracted with hexane containing 0.05 g/L BHT, dried and resuspended in a known volume of hexane. Separation of the FAME was performed using a Hewlett-Packard gas chromatograph (Model 6890, Hewlett-Packard, Palo Alto, CA), equipped with a 60 m x 0.25 mm x 0.25 µm DB-23 capillary column (J&W Scientific, Folsom, CA) and a flame-ionization detector. Hydrogen was used as the carrier gas and nitrogen was used as the make-up gas. The flow rate was 1.0 mL/min and the split-ratio was 50:1. For the separation, the injector temperature was set at 270°C and the detector temperature was set to 280°C. The oven temperature was increased from 165 to 215°C at 2.75°C/min. The fatty acids were identified by comparison of the retention times to FAME standards (Nu-Chek-Prep, Elysian, MN). Data are expressed as a g/100 g total lipid.
Isolation of mitochondria and cytosol fractions from brain and liver samples.
Mitochondrial and cytosolic fractions were isolated from fresh brain
and liver according to a modification of the procedure described by
Chen et al. (1998)
. In brief, fresh tissue samples were
homogenized in 10 volumes of freshly prepared HEPES, dithiothreitol,
glycerol, citrate buffer (HDGC: 20 mmol/L HEPES, pH 7.5, 1 mmol/L
dithiothreitol, 100 g/L glycerol and 2 mmol/L trisodium citrate, 0.5
mg/L leupeptin, 0.7 mg/L pepstatin, and 0.2 mmol/L
phenylmethylsulfonylfluoride). After removal of an aliquot of the
homogenate for percentage recovery analysis, the homogenate was
centrifuged twice at 600 x g for 15 min. The
supernatant from these spins was then centrifuged at 12,000 x g for 20 min to obtain the crude mitochondrial pellet;
the supernatant from this spin was retained for later isolation of the
cytosolic fraction. The mitochondrial pellet was washed three times
with HDGC buffer to minimize the amount of cytosolic contamination and
finally resuspended in HDGC buffer for storage. The microsome-free
cytosolic fraction was obtained by centrifugation of the mitochondrial
supernatant at 100,000 x g for 70 min. The
mitochondrial and cytosolic fractions, as well as an aliquot of the
homogenate were stored at -80°C until analysis.
Assays.
Mitochondrial and cytosolic aconitase activity (EC 1.1.1.42) were
measured according to the procedure described by Rose and O’Connell (1966)
. Succinate dehydrogenase activity (EC
1.3.5.1) was measured according to the procedure described by
Ackrell et al. (1978)
. Preliminary work (unpublished
data) demonstrated that the marginal iron diet used in this study does
not affect cytochrome c oxidase activity or ATP production in brain or
liver samples; therefore, the recovery and the relative mitochondrial
contamination of each fraction were determined by measuring the
activity of the mitochondrial marker, cytochrome c oxidase (EC 1.9.3.1)
according to the procedure of Wharton and Tzagollof
(1967)
. Cytosol recovery and contamination were calculated by
measuring the activity of the cytosolic marker, lactate dehydrogenase
(EC 1.1.2.3) (Wroblewski and LaDue 1955
). The
Bio-Rad assay (Bio-Rad, Hercules, CA) was used to measure protein
concentration, using bovine serum albumin as the standard. Hemoglobin
concentrations were determined by using a standard kit (Sigma Chemical,
St. Louis, MO), which detects the absorbance of cyanomethohemoglobin at
540 nm. All assays were performed within 5 wk of sample isolation.
Analysis of dopamine and metabolites.
Before the analysis of monoamines, tissues were mixed with a dilution solution containing 0.12 mol/L perchloric acid, 0.54 mmol/L disodium EDTA. 0.96 mmol/L sodium bisulfite and 0.010 L ethanol per liter to a final concentration of 1 mg wet tissue per 1 µL of dilution solution. The samples, kept on ice, were sonicated for 10 s and then centrifuged at 15,000 x g for 15 min at 4°C. The supernatant fluid was filtered and 5 µL of this solution was injected onto the column (C-18 column, Spheri-5, RP-18, 250 x 4.6 mm, Perkin-Elmer, Norwalk, CT) for analysis.
Detection of monoamines in caudate and cortex samples was accomplished using reverse-phase HPLC with electrochemical detection (Bioanalytical Systems, West Lafayette, IN). The mobile phase contained 0.11 mol/L citric acid, 1.62 mmol/L 1-octane sulfonic acid, 0.94 mmol/L disodium-EDTA and 3.6% acetonitrile, pH 3.15. The flow rate was 1 mL/min. A glassy carbon electrode was used for electrochemical detection at 850 mV. The concentrations of 3,4-dihydroxyphenylalanine, DA, 3,4-dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA) were calculated on the basis of an external standard mixture containing known concentrations of the analytes (all from Sigma Chemical).
Statistical analysis.
Statistical analysis of maternal variables was done using one-way
ANOVA (StatView, version 5.4, Abacus Concepts, Berkeley CA). Data for
offspring were analyzed using one- (treatment) and two-way
(treatment and sex) ANOVA. When data were collected on more than one
offspring from a litter (e.g., body weight or hemoglobin), the results
were averaged to give a litter mean for each sex. If there was no
effect of sex in the ANOVA, the data for male and female offspring were
pooled for further analysis and presentation. Fisher’s Protected Least
Significant Difference test was used to determine significant
differences among groups and an 
of P 
0.05
was defined as statistically significant for all tests. Data throughout
the text and tables are expressed as means ± SEM.
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
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Weights in male and female offspring were not affected by dietary
treatment at weaning (PND 21); however, as the mice aged, the weights
of marginal iron males and females were an average of 5–8% lower than
the weights recorded for age-matched control and replete offspring
(data not shown). Body weight differences among the dietary groups were
no longer evident for either sex at PND 75, and total weight gain from
weaning to PND 75 did not differ among groups (Table 2
).
|
. The calculation of food efficiency over the entire study period
(for PND 21–75: total weight gain per cage/total grams food consumed
per cage) demonstrated that both marginal iron male and female
offspring had significantly lower food efficiency than either control
or replete mice (Table 2)
.
Hemoglobin levels at PND 75 did not differ between dietary groups
(Table 2)
. In addition, there were no differences in plasma iron
concentrations or in hematocrits (data not shown).
Tissue mineral status.
Brain.
At PND 75, brain iron concentrations were affected by marginal iron
intakes (Table 3
). Marginal iron males and females had 16–19% lower brain iron
concentrations than controls. At this age, there was a significant
effect of diet and sex on brain iron status. The effect of sex was
largely a result of the concentrations measured in replete offspring.
Brain iron in replete males did not differ from the level measured in
control males; however, in contrast, iron remained significantly lower
in the brains of replete females. Replete females had brain iron
concentrations that did not differ from those measured in marginal
females.
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Liver.
Dietary treatment had a significant effect on liver mineral
concentrations at PND 75 (Table 3)
. Liver iron concentrations were 62
and 80% lower for marginal iron males and females, respectively,
relative to control mice at this age. Postnatal iron supplementation
resulted in liver iron concentrations in replete males and females that
were significantly higher than concentrations measured in both marginal
iron and control offspring. Liver manganese concentrations were
significantly elevated in marginal iron males and females relative to
control and replete offspring (Table 3)
. Total liver copper and zinc
concentrations were unaffected by dietary treatment (data not shown).
Myelin fatty acid composition.
The consumption of marginal iron diets during this period of
development resulted in significant differences in myelin fatty acid
composition (Table 4
). Because there was no effect of sex (P = 0.460), nor
an interaction between sex and treatment (P = 0.400),
the data for both sexes were pooled for ease of analysis and
presentation. Several (n-6) fatty acids were elevated in the myelin of
marginal iron mice; however, both arachidonic acid [20:4(n-6)] and
adrenic acid [22:4(n-6)] were 5 and 10% lower, respectively. In
addition, docosahexaenoic acid [22:6(n-3)] was significantly lower in
marginal iron mice. Calculation of the ratios of 20:4(n-6)/18:2(n-6)
and 22:6(n-3)/18:3(n-3) revealed that these ratios were significantly
lower (14 and 31% lower, respectively; both P < 0.05)
in the marginal iron mice (data not shown). The only difference in the
(n-9) class of fatty acids was a slight, yet significant lowering of
oleic acid [18:1(n-9)]; however, calculation of the ratios of
20:1(n-9)/20:0, 22:1(n-9)/22:0 and 24:1(n-9)/24:0 demonstrated that all
of these ratios were significantly lower (10–16%; all P
< 0.05) in marginal iron offspring. The combined differences in
the different families of fatty acid resulted in an overall difference
in saturated, monounsaturated (MUFA), and polyunsaturated fatty acids
(PUFA) (Table 5
). Marginal iron mice had significantly more saturated fatty acids,
whereas MUFA and PUFA were lower; however, this lowering was
significant only for PUFA (MUFA, P = 0.091). These
differences in composition were not due to differences in total brain
weight or total grams of lipid because these variables were unaffected
by dietary treatment (data not shown).
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|
Concentrations of dopamine and dopamine metabolites.
The long-term consumption of marginal iron diets caused significant
regional changes in the concentration of DA and DA metabolites
(Table 6
). In the caudate at PND 75, marginal iron males and females had
significantly higher HVA concentrations. These changes were accompanied
by a significantly higher ratio of (DOPAC + HVA)/DA in the caudate of
the marginal iron mice.
|
There were disruptions in DA metabolism in the cortex of marginal iron
offspring; however, the changes were not as dramatic as those measured
in the caudate. In the cortex, both marginal iron and replete males had
lower DOPAC and HVA concentrations (Table 6)
. Although DOPAC levels
were significantly lower in both marginal iron and replete males, the
decline in HVA concentrations approached significance only in the
marginal iron males (P = 0.0971). Calculation of (DOPAC
+ HVA)/DA revealed that this ratio was significantly lower in the
cortex of both marginal iron and replete males. Marginal iron females
did not show any differences in cortex neurotransmitter concentrations;
however, repletion in the females resulted in a significant increase in
the concentration of DOPAC and in the ratio of (DOPAC + HVA)/DA.
Enzyme activity.
Dietary treatment did not affect mitochondrial cytochrome c oxidase or
cytosolic lactate dehydrogenase enzyme activities in either the brain
or liver at PND 75 (Table 7
). The recovery of mitochondria from liver samples and brain samples
(determined by the percentage of total cytochrome c oxidase activity)
was in the range 25–39% and 21–34%, respectively. Contamination of
these fractions with cytosol (determined by lactate dehydrogenase
activity) was 0.5–1.3% for brain and 0.8–1.4% for liver. Recovery
of the cytosolic fraction ranged from 69 to 77% for liver and 62–74%
for the brain. For both brain and liver cytosol, the percentage of
mitochondrial contamination was < 1%. Due to the variation in
recovery and contamination of each sample, aconitase and succinate
dehydrogenase enzyme activity data were corrected for the amount of
mitochondrial or cytosolic contamination in the sample, and these data
are presented in Table 7
. There was no effect of sex (P
= 0.6211) or a sex x dietary treatment interaction
(P = 0.3994); thus, enzyme activities for males and
females were pooled for the calculation of a litter mean.
|
; thus, neither marginal iron or replete mice had enzyme
activities that differed from those measured in control mice. In
contrast, liver aconitase activities were 23–27% lower in marginal
iron mice. The activity of these enzymes in replete offspring did not
differ from the activity measured in control mice. The activity of the
other Fe-S–containing enzyme, succinate dehydrogenase, was not
affected by dietary treatment in either brain or liver. |
DISCUSSION |
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|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Chronic marginal iron intakes during pre- and early postnatal
development in mice significantly lowered brain iron concentrations;
furthermore, these changes in brain iron were accompanied by a
significant rise in brain manganese concentrations. One mechanism by
which iron can enter the brain is through transferrin-dependent
pathways. Recent work examining the biochemical consequences of iron
status on regional brain iron concentrations found significant
increases in both regional transferrin and transferrin receptor levels
as a consequence of developmental iron deficiency (Piñero et al. 2000
). Although these proteins were not measured in this
study, it is likely that in an attempt to normalize brain iron
concentrations, a similar increase in transferrin and transferrin
receptor expression occurred in the brains of the marginal iron mice.
Given that manganese has been shown to bind to transferrin and
subsequently be taken up into the cell via the
transferrin-transferrin receptor complex (Aschner and Gannon 1993
, Suarez and Eriksson 1993
), an increase in
these proteins would likely not only contribute to an increase in the
uptake of available iron, but would also provide an opportunity for
enhanced manganese uptake into the brain. Because this
transferrin-dependent mechanism does not facilitate the uptake of
metals such as copper and zinc, the uptake of these metals (via
transferrin) would not be expected to be enhanced by marginal iron
deficiency. Additional transferrin-independent pathways for the
uptake of iron into the brain have been demonstrated and are known to
facilitate manganese absorption into the brain (Takeda et al. 1998
and 2000
). The lactoferrin receptor, melanotransferrin
receptor and divalent cation transporter have been localized in the
brain and implicated as potentially important proteins involved in
transferrin-independent iron uptake [reviewed in Qian and Wang (1998)
]; however, the mechanism of response to
disruptions in brain iron status and to what extent these proteins can
mediate the uptake and transport of other metals in the brain in
response to these changes in iron status remain to be determined.
Previous studies have shown that severe iron deficiency can result in
significant disruptions in DA metabolism. Our ex vivo findings of an
increase in both HVA concentrations and in the ratio (DOPAC + HVA)/DA
in the caudate of iron-deficient mice are consistent with recent
reports. Several studies (Beard et al. 1994
,
Nelson et al. 1997
) using in vivo microdialysis
techniques have demonstrated an increase in both extracellular DA and
HVA concentrations resulting from postnatal iron deficiency. Our
findings derived from ex vivo analysis, however, are in contrast to
work by others demonstrating no difference in DA or DA metabolites
using similar ex vivo measurements (Nelson et al. 1997
,
Youdim and Green 1976
and 1978
). Differences between our
findings and earlier studies (Youdim and Green 1976
and 1978
) may be ascribed in part to differences in analytical
techniques; however, this does not explain the contrast between our
findings and those of Nelson et al. (1997)
because they
employed an analytical approach with similar sensitivity. However, the
differences in our findings may be attributed to the differences
between our model systems. In studies of more severe iron deficiency,
timing and duration are readily recognized as important determinants of
the effect of iron deficiency. To our knowledge, the current study is
the first designed to examine the effect of chronic marginal iron
deficiency during early development on catecholamine metabolism in the
brain; therefore, the duration and the timing of the marginal iron
deficiency used in this study may be critical to the demonstration of
altered DA metabolism ex vivo.
The alterations in DA metabolism observed in the current study are
among the first shown to be induced by chronic marginal iron intakes
during early development. Although the underlying biochemical
disturbance(s) in DA metabolism remain unclear, previous work has shown
that a more severe iron deficiency can result in a down-regulation
of D2-receptors in the caudate
(Ben-Shachar et al. 1986
, Youdim and Yehuda 1985
, Youdim and Ben-Shachar 1987
), as well
as alter activity of DA transporters responsible for presynaptic DA
reuptake (Nelson et al. 1997
). With the binding and
reuptake of DA disrupted, the brain may attempt to remove accumulating
DA by increasing its conversion to inactive metabolites, such as HVA
and DOPAC (Beard et al. 1994
, Nelson et al. 1997
). Although only changes in HVA concentrations in the
caudate were observed in this study, an increase in the extraneuronal
concentration of DOPAC in the caudate of marginal iron mice cannot be
ruled out. Because studies have demonstrated both intra- and
extraneuronal synthesis of DOPAC (Wesrink and Tuintie 1986
), it is possible that the measurement of total tissue
DOPAC concentrations may have obscured the detection of
dietary-induced differences in the concentration of DOPAC between
these two sites. An increase in extraneuronal DOPAC without changes in
total DOPAC concentrations was observed previously (Nelson et al. 1997
).
In addition to the changes in caudate DA metabolism, our study
demonstrated changes in the metabolism of DA within the cortex. The
findings of lower DOPAC concentrations and a 30% drop in the ratio
(DOPAC + HVA)/DA are consistent with recent reports (Nelson et al. 1997
) and lend further support to the concept of marginal
iron–induced disruptions in DA metabolism. If D2
receptor function or DA reuptake [as suggested by Beard et al. (1994)
] were affected in the current study, the extraneuronal
accumulation of HVA or DOPAC may have stimulated a negative feedback
response, thus eventually resulting in decreased DA release and a
concomitant decrease in the conversion of DA to its metabolites, as was
observed in this study. The differences in cortex DA metabolism
described in marginal iron mice are in an opposite direction of those
measured in the caudate and thus likely represent regional differences
in the brain’s capacity to compensate for alterations in DA
metabolism. Given that DA concentrations in the cortex are < 10%
of those measured in the caudate, the cortex may not experience such
dramatic disturbances in DA metabolism as does the DA-enriched
caudate. This regional variation in concentration may facilitate the
cortex’s ability to down-regulate DA metabolism in response to
possible disturbances in receptor number or reuptake capacity.
Given the importance of proper fatty acid composition in brain
development and maturation, it is possible that the iron-induced
changes in behavior and brain function are a consequence of altered
brain fatty acid composition. Consistent with our hypothesis, marginal
iron deficiency resulted in significant changes in myelin fatty acid
composition. Similar disruptions of long-chain (n-3) and (n-6)
fatty acids have been reported elsewhere as a consequence of more
severe dietary iron restriction in studies in animals (Larkin et al. 1986
, Oloyede et al. 1992
, Stangl and Kirchgessner 1998
) and humans (Smuts et al. 1995
). In addition to these changes, several disruptions in the
family of (n-9) fatty acids were noted, including a significant
lowering of 18:1(n-9) and the ratio of 24:1(n-9)/24:0 in the myelin of
marginal iron offspring. The accumulation of 18:1(n-9), 24:1(n-9) and
22:4(n-6) (which was also lower in marginal iron mice) parallels myelin
formation; thus, the accretion of these fatty acids has been considered
a "good marker" with which to track myelinogenesis (Martinez 1992
). Although the extent of myelination was not measured
directly in this study, these data suggest that myelination was
affected in these marginal iron offspring, and these findings are
consistent with reports in the literature of "immature myelin"
(Erikson et al. 1997
) and hypomyelination (Yu et al. 1986
) as functional consequences of severe developmental
iron deficiency.
The consistent decrease in the level of unsaturated and elongated
(n-3), (n-6) and (n-9) fatty acids suggests that the pathways governing
the incorporation and/or the utilization of these fatty acids are
impaired by iron deficiency. Moderate degrees of iron deficiency have
been demonstrated to alter the fatty acid composition and the relative
abundance of serum lipoproteins (Stangl and Kirchgessner 1998
). In addition, iron is a structural component of both the
6-desaturase (Okayasu 1981
) and the 9-desaturase
(stearyl CoA desaturase; Strittmatter and Enoch 1978
);
however, only the liver 9-desaturase has been shown to be reduced as
a result of dietary iron deficiency (Rao et al. 1980
).
Given the importance of both liver and brain fatty acid sources in the
accumulation of fatty acids in the brain (Clandinin 1999
, Sastry 1985
), disruptions in the packaging
of fatty acids into serum lipoproteins and/or the activity of synthetic
enzymes (in the brain and/or liver) could result in significant
perturbations in the availability of the appropriate fatty acids during
the period of postnatal development when the accumulation of these
fatty acids is most dramatic. Although only myelin was examined in this
study, similar changes in whole-brain fatty acid composition have
been reported (Larkin et al. 1986
, Oleyede et al.
1992
). It is possible then to speculate that the disruptions in
fatty acid composition observed as a consequence of chronic marginal
iron intakes during early development affected not only myelin, but
also the fatty acid composition of the brain as a whole. The functional
consequence of these changes is unknown, but given the importance of
fatty acid composition to the structural integrity and function of the
membrane (e.g., receptors or membrane-bound enzymes), these changes
in fatty acid composition are likely to affect a broad range of
neurochemical functions.
Although liver aconitase activity was responsive to changes in iron
status, there was no effect of dietary treatment on aconitase activity
in the brain. This tissue-specific response in activity may be
attributed to several things. Although iron concentrations were
significantly lower in the brains of marginal iron offspring, it could
be that this change was not of sufficient magnitude to elicit
detectable changes in enzyme activity. It is also possible that the
lack of change in c-aconitase activity reflects a difference in
regulatory protein abundance in the brain. Although IRP-1 (apo
c-aconitase) is the most abundant regulatory protein in most mammalian
brains studied to date, work by Samaniego et al. (1994)
showed that IRP-2 is the more abundant regulatory protein in mouse
brain. Because IRP-2 has no aconitase activity, changes in the binding
activity of this protein would not be reflected in changes in enzyme
activity. Future work examining brain IRE binding activity measurements
will help to clarify this issue.
It is important to note that changes in both c- and m-aconitase
activity of the liver were detected in this study, which is one of the
first to demonstrate changes in the activity of both proteins in
response to dietary iron status. Recent studies by Chen et al. (1997
and 1998
) showed that diets ranging from 2 to 107
µg Fe/g diet can significantly change m-aconitase
activity; however, c-aconitase activity was unaffected in these
studies despite an increase in IRP RNA binding. The difference in our
findings from those reported may reflect differences in study design.
The studies by Chen et al. (1997
and 1998
) were done in
postnatal rats that had been fed the low iron diets for a maximum of 3
wk. In the present study, the marginal iron diets were fed over a 13-wk
period that encompassed both the pre- and postnatal developmental
periods. The timing and duration of the iron deprivation may have
contributed to the observed outcomes.
Although the consumption of marginal iron diets resulted in biochemical
disturbances in both sexes, it is important to note that these changes
were not always uniform. Although gender did not contribute to
variations in myelin fatty acid composition or enzyme activity, brain
iron and regional DA concentrations were affected differently in males
and females. Although it is unclear at present what factors are
contributing to these differences, gender-specific responses in
iron deficiency have been identified previously with this model
(Kwik-Uribe et al. 1999
and 2000
) and have been reported
by others (Dallman et al. 1975
). A sexually dimorphic
response exists for DA because ovarian hormones modulate DA metabolism
and function (Becker 1990
, Castner and Becker 1993
, Castner et al. 1993
, Davis
1977
, Di-Paolo et al. 1982a
and 1982b
), as well
as activate directly the transcription of specific DA receptors
(Di-Paolo et al. 1982c
and 1982d
). Although no studies
that directly examine the relationship between iron status and
alterations in the abundance and/or function of ovarian hormones have
been done to date, several studies have shown that the ovarian hormones
can induce the tissue-specific transcription of iron-containing
chaperone glycoproteins (Poola 1997
), ferritin
(Zhu et al. 1995
) and lactoferrin (Grant et al. 1999
, Shigeta et al. 1996
). These data suggest
that changes in circulating hormone levels, either as a result of
iron-induced metabolic disturbances or normal cyclic fluctuations,
may contribute to the appearance of gender-specific biochemical
responses. Recognition of the existence of this sexually dimorphic
response to the same dietary condition stresses the importance of
designing studies that examine both sexes. Including males and females
in the study design is essential not only for elucidating the
biochemical nature of these gender-based differences, but also
because it may necessitate the development of alternate strategies for
the identification and treatment of gender-specific outcomes
associated with iron deficiency.
An area of concern when examining iron deficiency is knowing to what
extent iron deficiency–induced changes are reversible upon iron
repletion. Nearly 8 wk of postnatal iron supplementation was able to
increase brain iron concentrations in both marginal iron males and
females; however, only in the males was there a complete restoration of
brain iron to control values. Although these data do demonstrate the
success of postnatal iron repletion in improving brain iron
concentrations, these findings are tempered by the demonstration that
some biochemical and behavioral (Kwik-Uribe et al. 2000
)
alterations persisted in these mice despite increased brain iron. Thus,
strictly examining brain iron concentrations as an index of the success
of postnatal iron repletion may be premature, given the continued
presence of these biochemical and behavioral disruptions. The extent to
which an earlier start to supplementation (before PND 21), a longer
duration of supplementation and a higher level of supplemental iron
could contribute to reversing these changes warrants additional study.
This information has important public health implications because it
will lend insight into whether a finite developmental window exists
during which the biochemical and behavioral consequences of
developmental iron deficiency can be truly reversed.
In conclusion, this study demonstrates that chronic marginal iron intakes during pre- and early postnatal development can result in significant alterations in brain iron concentrations, DA metabolism and myelin fatty acid composition in mice. Our previous work with this model demonstrated that these intakes are also associated with pronounced changes in behavioral and cognitive development; thus, the biochemical changes reported in this study may act in concert to contribute to these behavioral outcomes. Furthermore, it does not appear that in this model, brain aconitase activities are regulated in response to dietary iron restriction and lower brain iron concentrations. Finally, by demonstrating that postnatal iron supplementation was associated with a reversal of some, but not all iron deficiency–induced biochemical changes within the brain, we provide strong evidence for the critical need to ensure adequate iron nutrition during early brain development for normal behavioral and biochemical function.
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
3 Abbreviations used: DA, dopamine; DOPAC,
3,4,-dihydroxyphenylacetic acid; eALAS, erythroid 5-aminolevulinate
synthase; FAME, fatty acid methyl esters; GD, gestation day; HDGC,
HEPES, dithiothreitol, glycerol and citrate buffer; HVA, homovanillic
acid; IRE, iron-responsive element; IRP, iron regulatory protein;
MUFA, monounsaturated fatty acids; PND, postnatal day; PUFA,
polyunsaturated fatty acids; UTR, untranslated region.
Manuscript received April 11, 2000. Initial review completed May 25, 2000. Revision accepted July 17, 2000.
|
REFERENCES |
|---|
|
TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
1. Ackrell B.A.C., Kearney E. B., Singer T. P. Mammalian succinate dehydrogenase. Methods Enzymol 1978;53:466-483[Medline]
2. Alaimo K., McDowell M. A., Briefel R. R., Bischof A. M., Caughman C. R., Loria C. M., Johnson C. L. Dietary intake of vitamins, minerals, and fiber of persons ages 2 months and over in the United States: Third National Health and Nutrition Examination Survey, Phase 1, 1988–91. Adv. Data 1994;258:1-28
3. Ashkenazi R., Ben-Shachar D., Youdim M. B. Nutritional iron and dopamine binding sites in the rat brain. Pharmacol. Biochem. Behav. 1982;17(suppl. 1):43-47
4. Aschner M., Gannon M. Manganese (Mn) transport across the rat blood-brain barrier: saturable and transferrin-dependent transport mechanisms. Brain Res. Bull. 1993;33:345-349
5. Beard J. L., Chen Q., Connor J., Jones B. C. Altered monoamine metabolism in caudate-putamen of iron-deficient rats. Pharmacol. Biochem. Behav. 1994;48:621-624[Medline]
6. Becker J. B. Direct effect of 17 beta-estradiol on striatum: sex differences in dopamine release. Synapse 1990;5:157-164[Medline]
7. Ben-Shachar D., Ashkenazi R., Youdim M. B. Long-term consequence of early iron-deficiency on dopaminergic neurotransmission in rats. Int. J. Dev. Neurosci. 1986;4:81-88[Medline]
8. Ben-Shachar D., Youdim M. B. Neuroleptic-induced supersensitivity and brain iron: I. Iron deficiency and neuroleptic-induced dopamine D2 receptor supersensitivity. J. Neurochem. 1990;54:1136-1141[Medline]
9. Castner S. A., Becker J. B. Sex-related differences and hormonal influences on amphetamine-induced stereotyped behaviors and immediate early gene expression in striatum. Soc. Neurosci. Abstr. 1993;19:823
10. Castner S. A., Xiao L., Becker J. B. Sex differences in striatal dopamine: in vivo microdialysis and behavioral studies. Brain Res 1993;610:127-134[Medline]
11.
Chen O. S., Blemings K. P., Schalinske K. L., Eisenstein R. S. Dietary iron intake rapidly influences iron regulatory proteins, ferritin subunits and mitochondrial aconitase in rat liver. J. Nutr. 1998;128:525-535
12.
Chen O. S., Schalinske K. L., Eisenstein R. S. Dietary iron intake modulates the activity of iron regulatory proteins and the abundance of ferritin and mitochondrial aconitase in rat liver. J. Nutr. 1997;127:238-248
13. Clandinin M. T. Brain development and assessing the supply of polyunsaturated fatty acid. Lipids 1999;34:131-137[Medline]
14. Clegg M. S., Keen C. L., Lonnerdal B., Hurley L. S. Influences of ashing techniques on the analysis of trace elements in animal tissues. Biol. Trace Elem. Res. 1981;3:107-115
15. Connor J. R., Benkovic S. A. Iron regulation in the brain: histochemical, biochemical, and molecular considerations. Ann. Neurol. 1992;32:S51-S61
16. Dallman P. R., Siimes M. N., Manies E. C. Brain iron: persistent deficiency following short term iron deprivation in the young rat. Br. J. Haemotol. 1975;31:209-215[Medline]
17. Davis C. F., Davis B. F., Halaris A. E. Variations in the uptake of 3H-dopamine during the estrous cycle. Life Sci 1977;20:1319-1332[Medline]
18. Di Paolo T., Bédard P. J., Dupont A., Poyet P., Labrie F. Effects of estradiol on intact and denervated striatal dopamine receptors and on dopamine levels: a biochemical and behavioral study. Can. J. Physiol. Pharm. 1982a;60:350-357[Medline]
19. Di Paolo T., Dupont A., Daigle M. Effect of chronic estradiol treatment on dopamine concentrations in discrete brain nuclei of hypophysectomized female rats. Neurosci. Lett. 1982b;32:295-300[Medline]
20. Di Paolo T., Poyet P., Labrie F. Effect of prolactin and estradiol on rat striatal dopamine receptors. Life Sci 1982c;31:2921-2929[Medline]
21. Di Paolo T., Poyet P., Labrie F. Prolactin and estradiol increase striatal dopamine receptor density in intact, castrated and hypophysectomized rats. Prog. Neuro-Psychopharmacol. Biol. Psychiatry 1982d;6:377-382[Medline]
22. Edgerton V. R., Bryant S. L., Gillespie C. A., Gardner G. W. Iron deficiency anemia and physical performance and activity of rats. J. Nutr. 1972;102:381-400
23.
Eisenstein R. S., Blemings K. P. Iron regulatory proteins, iron responsive elements and iron homeostasis. J. Nutr. 1998;128:2295-2298
24.
Erikson K. M., Piñero D. J., Connor J. R., Beard J. L. Regional brain iron, ferritin and transferrin concentrations during iron deficiency and iron repletion in developing rats. J. Nutr. 1997;127:2030-2038
25. Espinosa de los Monteros A., Kumar S., Zhao P., Huang C. J., Nazarian R., Pan T., Scully S., Chang R., de Vellis J. Transferrin is an essential factor for myelination. Neurochem. Res. 1999;24:235-248[Medline]
26. Farooq M., Cammer W., Snyder D. S., Raine C. S., Norton W. T. Properties of bovine oligodendroglia isolated by a new procedure using physiologic conditions. J. Neurochem. 1981;36:431-440[Medline]
27. Felt B. T., Lozoff B. Brain iron and behavior of rats are not normalized by treatment of iron deficiency anemia during early development. J. Nutr. 1996;126:693-701
28. Folch J., Lees M., Sloane-Stanley G. H. A simple method for the isolation and purification of total lipids from animal tissues. J. Biol. Chem. 1957;226:479-509
29. Grant D. J., Shi H., Teng C. T. Tissue and site-specific methylation correlates with expression of the mouse lactoferrin gene. J. Mol. Endocrinol. 1999;23:45-55[Abstract]
30.
Hurtado E. K., Claussen A. H., Scott K. G. Early childhood anemia and mild or moderate mental retardation. Am. J. Clin. Nutr. 1999;69:115-119
31. Idjradinata P., Pollitt E. Reversal of developmental delays in iron-deficient anaemic infants treated with iron. Lancet 1993;341:1-4[Medline]
32. Kwik-Uribe C. L., Golub M. S., Keen C. L. Behavioral consequences of marginal iron deficiency during development in a murine model. Neurotoxicol. Teratol. 1999;21:661-672[Medline]
33.
Kwik-Uribe C. L., Golub M. S., Keen C. L. Behavioral consequences of marginal iron deficiency during development in a murine model. J. Nutr. 2000;130:2040-2048
34. Larkin E. C., Jarratt B. A., Rao G. A. Reduction of relative levels of nervonic to lignoceric acid in the brain of rat pups due to iron deficiency. Nutr. Res. 1986;6:309-317
35. Martinez M. Tissue levels of polyunsaturated fatty acids during early human development. J. Pediatr. 1992;120:S129-S138[Medline]
36.
Massaro T. F., Widmayer P. The effect of iron deficiency on cognitive performance in the rat. Am. J. Clin. Nutr. 1981;34:864-870
37. National Research Council Guide for the Care and Use of Laboratory Animals 1996 Institute of Laboratory Animal Resources. National Academy Press Washington, DC.
38.
Nelson C., Erikson K., Piñero D. J., Beard J. L. In vivo dopamine metabolism is altered in iron-deficient anemic rats. J. Nutr. 1997;127:2282-2288
39. Okayasu T. [Purification and characterization of linoleoyl-CoA desaturase from rat liver microsomes (author’s translation)]. Hokkaido Igaku Zasshi 1981;56:43-54[Medline]
40. Oloyede O. B., Folayan A. T., Odutuga A. A. Effects of low-iron status and deficiency of essential fatty acids on some biochemical constituents of rat brain. Biochem. Int. 1992;27:913-922[Medline]
41.
Piñero D. J., Li N. Q., Connor J. R., Beard J. L. Variations in dietary iron alter brain iron metabolism in developing rats. J. Nutr. 2000;130:254-263
42.
Pollitt E., Watkins W. E., Husaini M. A. Three-month nutritional supplementation in Indonesian infants and toddlers benefits memory function 8 y later. Am. J. Clin. Nutr. 1997;66:1357-1363
43. Poola I. An estrogen inducible 104 kDa chaperone glycoprotein binds ferric iron containing proteins: a possible role in intracellular iron trafficking. FEBS Lett 1997;416:139-142[Medline]
44. Qian Z. M., Wang Q. Expression of iron transport proteins and excessive iron accumulation in the brain in neurodegenerative disorders. Brain Res. Rev. 1998;27:257-267[Medline]
45. Rao G. A., Manix M., Larkin E. C. Reduction of essential fatty acid deficiency in rats fed a low iron fat free diet. Lipids 1980;15:55-60[Medline]
46. Rose I. A., O’Connell E. L. Mechanism of aconitase action. I. The hydrogen transfer reaction. J. Biol. Chem. 1966;242:1870-1879
47.
Samaniego F., Chin J., Iwai K., Rouault T. A., Klausner R. D. Molecular characterization of a second
iron-responsive element binding protein, iron regulatory protein 2.
Structure, function, and post-translational regulation. J. Biol. Chem. 1994;269:30904-30910
48. Sastry P.S. Lipids of nervous tissue: composition and metabolism. Prog. Lipid Res. 1985;24:69-176[Medline]
49. Seshadri S., Gopaldas T. Impact of iron supplementation on cognitive functions in preschool and school-aged children: the Indian experience. Am. J. Clin. Nutr. 1989;50:675-684
50. Shigeta H., Newbold R. R., McLachlan J. A., Teng C. Estrogenic effect on the expression of estrogen receptor, COUP-TF, and lactoferrin mRNA in developing mouse tissues. Mol. Reprod. Dev. 1996;45:21-30[Medline]
51. Smuts C. M., Tichelaar H. Y., van Jaarsveld P. J., Badenhorst C. J., Kruger M., Laubscher R., Mansvelt E. P., Benade A. J. The effect of iron fortification on the fatty acid composition of plasma and erythrocyte membranes in primary school children with and without iron deficiency. Prostaglandins Leukot. Essent. Fatty Acids 1995;52:59-67[Medline]
52. Soewondo S., Husaini M., Pollitt E. Effects of iron deficiency on attention and learning processes in preschool children: Bandung, Indonesia. Am. J. Clin. Nutr. 1989;50:667-673
53. Stangl G. I., Kirchgessner M. Different degrees of moderate iron deficiency modulate lipid metabolism of rats. Lipids 1998;33:889-895[Medline]
54. Strittmatter P., Enoch H.G. Purification of stearyl-CoA desaturase from liver. Methods Enzymol 1978;52:188-193[Medline]
55. Suarez N., Erikson H. Receptor-mediated endocytosis of a manganese complex of transferrin into neuroblastoma (SHSY5Y) cells in culture. J. Neurochem. 1993;6:127-131
56. Takeda A., Devenyi A., Connor J. R. Evidence for non-transferrin-mediated uptake and release of iron and manganese in glial cell cultures from hypotransferrinemic mice. J. Neurosci. Res. 1998;51:454-462[Medline]
57. Takeda A., Ishiwatari S., Okada S. Influence of transferrin on manganese uptake in rat brain. J. Neurosci. Res. 2000;59:542-552[Medline]
58. Wainwright P. E. Do essential fatty acids play a role in brain and behavioral development?. Neurosci. Biobehav. Rev 1992;16:193-205[Medline]
59. Weinberg J., Dallman P. R., Levine S. Iron deficiency during early development in the rat: behavioral and physiological consequences. Pharmacol. Biochem. Behav. 1980;12(4):493-502[Medline]
60. Weinberg J., Levine S., Dallman P. R. Long-term consequences of early iron deficiency in the rat. Pharmacol. Biochem. Behav. 1979;11:631-638[Medline]
61. Wesrink B. H., Tuintie M. H. Chronic use of intracerebral dialysis for the in vivo measurement of 3,4-dihydrophenylethelamine and its metabolite, 3,4-dihydroxyphenylaceitc acid. J. Neurochem. 1986;46:181-185[Medline]
62. Wharton D. C., Tzagoloff A. Cytochrome oxidase from beef heart mitochondria. Methods Enzymol 1967;50:245-250
63. Williamson A. M., Ng K. T. Activity and T-maze performance in iron deficient rats. Physiol. Behav. 1980a;24:1157-1160[Medline]
64. Williamson A. M., Ng K. T. Behavioral effects of iron deficiency in the adult rat. Physiol. Behav. 1980b;24:561-567[Medline]
65. Wroblewski F., LaDue J. S. Lactic dehydrogenase activity in blood. Proc. Soc. Exp. Biol. Med. 1955;10:210-213
66. Yehuda S., Youdim M. E., Mostofsky D. I. Brain iron-deficiency causes reduced learning capacity in rats. Pharmacol. Biochem. Behav. 1986;25:141-144[Medline]
67. Youdim M. B., Ashkenazi R., Ben-Shachar D., Yehuda S. Modulation of dopamine receptor in the striatum by iron: behavioral and biochemical correlates. Adv. Neurol. 1984;40:159-170[Medline]
68. Youdim M. B., Ben-Shachar D. Minimal brain damage induced by early iron deficiency: modified dopaminergic neurotransmission. Isr. J. Med. Sci. 1987;23:19-25[Medline]
69. Youdim M. B., Green A. R. Biogenic monoamine metabolism and functional activity in iron-deficient rats: behavioral correlates. Ciba Found. Symp. 1976;57:201-202
70. Youdim M. B., Green A. R. Iron deficiency and neurotransmitter synthesis and function. Proc. Nutr. Soc. 1978;37:173-179[Medline]
71. Youdim M. B., Yehuda S. Iron deficiency induces reversal of dopamine dependent circadian cycles: differential response to d-amphetamine and TRH. Peptides 1985;6:851-855[Medline]
72. Yu G. S., Steinkirchner T. M., Rao G. A., Larkin E. C. Effect of prenatal iron deficiency on myelination in rat pups. Am. J. Pathol. 1986;125:620-624[Abstract]
73. Zhu L. J., Bagchi M. K., Bagchi I. C. Ferritin heavy chain is a progesterone-inducible marker in the uterus during pregnancy. Endocrinology 1995;136:4106-4115[Abstract]
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C. L. Keen, M. S. Clegg, L. A. Hanna, L. Lanoue, J. M. Rogers, G. P. Daston, P. Oteiza, and J. Y. Uriu-Adams The Plausibility of Micronutrient Deficiencies Being a Significant Contributing Factor to the Occurrence of Pregnancy Complications J. Nutr., May 1, 2003; 133(5): 1597S - 1605. [Abstract] [Full Text] [PDF]
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E. A. Malecki Limited Role of Transferrin in Manganese Transport to the Brain J. Nutr., May 1, 2001; 131(5): 1584 - 1584. [Full Text]
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C. Kwik-Uribe Response to letter of Dr. Elise Malecki J. Nutr., May 1, 2001; 131(5): 1585 - 1585. [Full Text]
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