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Journal of Gerontology: BIOLOGICAL SCIENCES © The Author 2010. Published by Oxford University Press on behalf of The Gerontological Society of America.
Cite journal as: J Gerontol A Biol Sci Med Sci. 2010 December;65A(12):1312–1321 All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org.
doi:10.1093/gerona/glq149 Advance Access published on September 2, 2010
1312
C
OGNITIVE function declines with age, even in other-
wise healthy individuals. In the last decades, identify-
ing biologic determinants of age-related cognitive decline
has become an increasingly important goal of aging re-
search. The putative role of nutritional factors in modifying
the risk of cognitive impairment has widely been studied
(1–3). In this respect, disturbed iron homeostasis, which
may be genetically or environmentally determined, has
been coined as one suspected risk factor for age-related
cognitive decline (4).
Iron deficiency is the most common nutritional defi-
ciency worldwide, with a prevalence of 5%–20% among
adults in Western countries (5–8). A depletion of body iron
stores may result from insufficient dietary intake, ham-
pered absorption, or excessive losses (9,10). In addition,
regular whole blood donation may also lower body iron
concentrations (8).
As a constituent of various enzymes, iron is essential for
several physiological functions, including oxygen trans-
port and DNA synthesis (11). The brain in particular has
a high demand for iron not only because it is the main
oxygen-consuming organ in the human body but also be-
cause many neurobiologic processes, including myelina-
tion, neurotransmitter synthesis, and synaptic plasticity,
are iron dependent (12–14). Consequently, one of the
major symptoms of iron deficiency is reduced cognitive
performance (4,10,13,14).
Although the effects of iron deficiency on cognitive
functioning have frequently been investigated in children
and young adults (15–19), research performed in older
persons is rather limited (20–22). Iron deficiency in older
individuals may be due to poor dietary habits, gastrointes-
tinal malignancies, or diseases characterized by chronic
inflammation (9,23–25).
Serum Iron Parameters, HFE C282Y Genotype, and
Cognitive Performance in Older Adults: Results From the
FACIT Study
Olga J. G. Schiepers,
1
Martin P. J. van Boxtel,
1
Renate H. M. de Groot,
1,2,3
Jelle Jolles,
1,2
Wim L. A. M. de Kort,
4
Dorine W. Swinkels,
5
Frans J. Kok,
6
Petra Verhoef,
6,7,8
and Jane Durga
6,7,9
1
School for Mental Health and Neuroscience (MHeNS)/European Graduate School for Neuroscience (EURON), Department of
Psychiatry and Neuropsychology, Maastricht University, The Netherlands.
2
AZIRE Research Institute, Faculty of Psychology and Education, VU University Amsterdam, The Netherlands.
3
Centre for Learning Sciences and Technologies, Open University, Heerlen, The Netherlands.
4
Sanquin Blood Bank South East Region, Nijmegen, The Netherlands.
5
Department of Laboratory Medicine, Laboratory of Clinical Chemistry 441, Radboud University Nijmegen Medical Centre,
The Netherlands.
6
Division of Human Nutrition, Wageningen University, The Netherlands.
7
Top Institute Food and Nutrition, Wageningen, The Netherlands.
8
Unilever Research and Development, Vlaardingen, The Netherlands.
9
Cognitive Sciences Group, Nutrition and Health Department, Nestlé Research Centre, Lausanne, Switzerland.
Address correspondence to Olga J. G. Schiepers, MSc, Department of Psychiatry and Neuropsychology, Maastricht University, P.O. Box 616, 6200 MD
Maastricht, The Netherlands. Email: olga.schiepers@np.unimaas.nl
Although iron homeostasis is essential for brain functioning, the effects of iron levels on cognitive performance in older
individuals have scarcely been investigated. In the present study, serum iron parameters and hemochromatosis (HFE)
C282Y genotype were determined in 818 older individuals who participated in a 3-year randomized, placebo-controlled
double-blind trial examining the effects of folic acid on carotid intima-media thickness. All participants had slightly el-
evated homocysteine levels and were vitamin B12 replete. Cognitive functioning was assessed at baseline and after 3
years by means of a neuropsychological test battery. At baseline, increased serum ferritin was associated with decreased
sensorimotor speed, complex speed, and information-processing speed and increased serum iron was associated with
decreased sensorimotor speed. Cognitive performance over 3 years was not associated with HFE C282Y genotype or iron
parameters. In conclusion, serum iron parameters do not show a straightforward relationship with cognitive functioning,
although elevated iron levels may decrease cognitive speed in older individuals susceptible to cognitive impairment.
Key Words: Cognitive performance—Iron parameters—HFE—Longitudinal study—Older adults.
Received April 20, 2010; Accepted July 30, 2010
Decision Editor: Rafael de Cabo, PhD
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IRON PARAMETERS AND COGNITIVE PERFORMANCE
1313
Elevated body iron levels might also impair brain func-
tioning. Because body iron concentrations tend to increase
with age, particularly in women who reached the meno-
pause (26), increased iron concentrations are more frequent
in older persons as compared with young adults; elevated
iron levels may be present in up to 20% of community-
dwelling individuals aged 50 years or older (6,8,27).
Elevated iron concentrations may also be observed in car-
riers of the C282Y mutation of the hemochromatosis gene
(HFE), which causes increased iron absorption (26,28). The
HFE C282Y mutation has a prevalence of around 10% in
communities of Northern European descent (28,29). This
mutation has been associated with neurodegenerative disor-
ders (12,30), including Parkinson’s disease (31) and Al-
zheimer’s disease (32,33). It should be noted, however, that
a number of studies did not find any evidence for such a
relationship in patients with Alzheimer’s disease (34) or
Parkinson’s disease (35). In addition, it has also been sug-
gested that the HFE C282Y mutation might have a protec-
tive role in Alzheimer’s disease (36).
Despite the fact that both iron deficiency and elevated
iron levels frequently occur in older individuals and are as-
sociated with negative effects on cognitive functioning,
only a small number of studies have investigated the effects
of iron parameters on cognitive performance in later stages
of life. The results of these cross-sectional studies are
mixed. Whereas Gao and colleagues (20) did not find any
associations between plasma iron and cognitive function-
ing, Lam and colleagues (22) found an inverted U-shaped
relationship between serum iron and cognitive functioning
in men and an inverse relationship in women. In addition,
La Rue and colleagues (21) reported that serum transferrin
was positively correlated with cognitive performance in
older individuals.
The objective of the present study was to examine the
cross-sectional and longitudinal associations between iron
parameters and cognitive functioning in a large sample of
healthy older adults. This study investigated linear and qua-
dratic associations between serum iron parameters and cog-
nitive performance as well as the relationship between the
HFE C282Y mutation and cognitive performance.
Methods
Study Population
The study population consisted of 818 men and women who
participated in the Folic Acid and Carotid Intima-Media Thick-
ness study. This randomized, double-blind placebo-controlled
trial was originally designed to investigate the effects of 3-year
folic acid supplementation on the risk of cardiovascular dis-
ease as measured by carotid intima-media thickness (37). The
study sample included a relatively large proportion of blood
donors (54%), as participants were recruited from blood bank
registries as well as from municipal registries. All participants
were aged between 50 and 70 years, and, specifically for
women, had reached the menopause at least 2 years prior.
Exclusion criteria were plasma total homocysteine concentra-
tions less than 13 mmol/L or greater than 26 mmol/L, use of
B-vitamin supplements or drugs that could affect atheroscle-
rotic progression (eg, lipid-lowering or hormone replacement
therapies), or self-reported intestinal disease. We also excluded
individuals with elevated homocysteine concentrations due
to factors other than suboptimal folate concentrations, in-
cluding serum vitamin B12 concentrations less than 200
pmol/L, self-reported medical diagnosis of renal or thyroid
disorders, or self-reported use of medications that influence
folate metabolism. The Medical Ethics Committee at
Wageningen University approved the study, and all partici-
pants gave written informed consent.
Cognitive Functioning
Cognitive functioning on the domains of memory, senso-
rimotor speed, complex speed, information-processing
speed, and word fluency was assessed at baseline and at
3-year follow-up by means of a neuropsychological test bat-
tery, consisting of the Visual Verbal Word Learning Task
(38), the Stroop Color–Word Interference Test (39), the
Concept Shifting Test (40), the Letter Digit Substitution
Test (41), and the Verbal Fluency Test (42). A detailed
description of the cognitive test battery and the method used
for creating cognitive performance indices based on the raw
test scores can be found elsewhere (37).
Blood Measurements
The iron parameters measured were total serum iron; to-
tal iron-binding capacity, which is a measure of the serum
concentration of the iron transport protein transferrin
(43,44); transferrin saturation, which is expressed as the ra-
tio (×100%) of serum iron concentration and total iron-
binding capacity; serum ferritin, an indicator of total body
iron stores (45); and non–transferrin-bound iron (46,47).
At baseline and at 3-year follow-up, fasting venous blood
samples were collected, centrifuged within 2 hours, and the
serum supernatant was stored in multiple aliquots at −80°C.
Within 15 months of storage, samples were thawed for serum
measurements. Serum iron and total iron-binding capacity
were measured using Hitachi 747 (Roche Diagnostics, Basel,
Switzerland). Serum ferritin was determined on the Immulite
1 of DPC (Diagnostic Products Corporation, Los Angeles, CA)
using a two-site immunometric assay (reference values:
15–190 mg/L for postmenopausal women and 15–280 mg/L
for men). Non–transferrin-bound iron, which was measured
at baseline only, was determined by a fluorescence-based
one-step chelation method (48). Serum high-sensitivity
C-reactive protein was determined at baseline with ELISA
using polyclonal antibodies (Dako, Glostrup, Denmark).
An automated hematology analyzer (Sysmex, Hamburg,
Germany) was used to measure serum hemoglobin. For
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SCHIEPERS ET AL.
1314
active blood donors, blood samples were collected at least
6 weeks after the most recent blood donation.
Genotyping
Genomic DNA was extracted from whole blood samples
using a Qiamp 96 DNA blood kit (Qiagen, Venlo, The
Netherlands). DNA samples were stored at −80°C until
further analysis. HFE C282Y genotype was determined by
an automated method using minor-groove–binding DNA
oligonucleotides (MGB probes) (49). The presence of a
C282Y allele was confirmed by conventional polymerase
chain reaction with restriction fragment length polymor-
phism analysis (50,51). Apolipoprotein E (APOE) genotype
was determined as described elsewhere (37).
Other Measurements
Level of education, measured at baseline by classifying
formal schooling according to the Dutch educational system,
was categorized into low, middle, or high, that is, corre-
sponding to primary education, junior vocational training,
and senior vocational or academic training, respectively (52).
Alcohol consumption (grams per day) and current smoking
(yes or no) were ascertained at baseline by means of self-
report questionnaires, which were reviewed by a trained
research assistant. Body mass index (BMI; kilograms per
square meter) was calculated from height and weight, and
physical activity was estimated using the Physical Activity
Scale for the Elderly (53).
Statistical Analysis
Cross-sectional analyses.—The cross-sectional associa-
tions between iron parameters and cognitive functioning
were assessed by means of hierarchical linear regression
analysis. The iron parameters considered relevant in rela-
tion to cognitive performance were total serum iron, ferri-
tin, and non–transferrin-bound iron. These parameters
represent the different sources of iron in the blood, that is,
total circulating iron, a reflection of total stored body iron,
and circulating iron not bound to the plasma transport pro-
tein transferrin, respectively (45–47). Transferrin saturation
and total iron-binding capacity were not included in the re-
gression analyses not only because they are indirect mea-
sures of body iron levels but also because including these
variables in the statistical models would have introduced
multicollinearity.
Separate regression models were fitted for the five cogni-
tive performance indices. The covariates age, sex, level of
education, alcohol consumption, smoking, BMI, physical
activity, C-reactive protein, hemoglobin, and APOE E4
carrier status were entered in Step 1, followed by the iron
parameters in Step 2. Similar regression analyses were per-
formed to examine the associations between the HFE C282Y
mutation and cognitive performance. The variables age, level
of education, alcohol consumption, smoking, BMI, and phys-
ical activity were confounders in our study. Although sex,
C-reactive protein, hemoglobin, and APOE E4 carrier status
were no actual confounders in our analyses, we included
these variables as covariates to enable comparison with other
studies, investigating the associations between body iron
levels and cognitive performance (6,22,54–56). We also
tested for a possible confounding effect of homocysteine as
all participants had slightly elevated plasma total homocysteine
levels. However, the results were similar regardless if homo-
cysteine was included in the analyses. Therefore, we did not
include this variable in the final statistical models.
To examine the possible nonlinear relationships between
iron parameters and cognitive performance, regression
models were fitted for each cognitive performance index,
with quadratic terms for iron parameters as the independent
variables, adjusting for covariates and linear terms for iron
parameters in Step 1.
Longitudinal analyses.—First, we tested whether treatment
with folic acid was an effect modifier in our data set as folic
acid was found to exert a positive effect on cognitive perfor-
mance (37), and previous research suggested that folate might
interact with iron metabolism (57). We found that folic acid
supplementation was not an effect modifier in our data set; the
interaction terms for iron parameters and treatment condition
were not statistically significant (Supplementary Table 1).
Furthermore, the serum iron parameters did not significantly
differ between the placebo group and the treatment group at
the end of the study (p = .972 for serum iron and p = .892 for
ferritin), indicating that folic acid supplementation did not
influence body iron levels in our study. Therefore, the longi-
tudinal analyses were performed in the total sample.
Using linear mixed models, we investigated the associa-
tions between iron parameters and cognitive performance
over 3 years of follow-up, adjusting for covariates. This
analysis method takes into account the correlation between
repeated measurements and allows the inclusion of partici-
pants with missing observations at follow-up (58). Separate
models were fitted for each iron parameter in relation to
each of the five cognitive performance indices. An unstruc-
tured covariance structure was used. Time (measured in
years since baseline) was included to estimate the change in
cognitive performance over 3 years of follow-up. The longi-
tudinal effect of the iron parameters was estimated by the
two-way interaction between time and the specific iron
parameter, which represents the rate of change in cognitive
performance over 3 years as a function of this iron parame-
ter. The longitudinal associations between the HFE C282Y
mutation and cognitive performance were examined in a
similar manner.
In secondary analyses, we stratified the study population
by sex, donor status, and APOE E4 carrier status to deter-
mine whether the cross-sectional and longitudinal associa-
tions between iron parameters on the one hand and cognitive
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IRON PARAMETERS AND COGNITIVE PERFORMANCE
1315
functioning on the other differed between men and women,
blood donors and non-donors, or carriers and noncarriers of
the APOE E4 allele. One-sample t tests were used to deter-
mine whether serum iron, serum ferritin, and cognitive func-
tioning changed over the 3-year follow-up period. Chi-square
tests and independent samples t tests were used to investigate
whether serum iron, total iron-binding capacity, and non–
transferrin-bound iron, as well as the background variables
age, sex, level of education, alcohol consumption, smoking,
BMI, physical activity, C-reactive protein, hemoglobin, and
APOE E4 status differed between carriers and noncarriers of
the HFE C282Y mutation. Because of heterogeneity of error
variances, the nonparametric Mann–Whitney test was per-
formed to test for differences in serum ferritin and transferrin
saturation between carriers and noncarriers of the HFE
C282Y mutation. Hardy–Weinberg equilibrium was assessed
using a chi-square test. Normality of the standardized resid-
uals of the regression analyses was ascertained by means of
normal P–P plots.
The statistical power of the cross-sectional and longitudi-
nal analyses was more than .90 (small effect size, f
2
= .02).
Statistical differences were considered significant at p
values < .05. All analyses were performed using SPSS 16.0
(SPSS Inc., Chicago, IL).
Results
Participants
Table 1 shows the baseline characteristics of the partici-
pants. Forty-three individuals (5.3%) showed depleted iron
stores, as indicated by serum ferritin concentrations below
the lower normal limit (ie, 15 mg/L). Thirty-two individuals
(3.9%) showed serum hemoglobin concentrations charac-
teristic of anemia according to World Health Organization
criteria, that is, lower than 7.5 mmol/L for women and lower
than 8.1 mmol/L for men. The combination of both low fer-
ritin and low hemoglobin levels, that is, iron deficiency ane-
mia, was present in only seven participants (0.9%). In total,
53 participants (6.5%) showed serum ferritin concentrations
above the upper normal limit (ie, 190 mg/L for women and
280 mg/L for men). Among non-donors, the prevalence of
low serum ferritin was 0.8% and the prevalence of high se-
rum ferritin was 13.1%, and among blood donors, these per-
centages were 11.3% and 0.9%, respectively.
Eighty individuals were identified as carriers of the HFE
C282Y mutation (10.5%); 2 individuals were homozygous
(0.3%) and 78 persons were heterozygous (10.2%). The allele
frequencies of the HFE C282Y polymorphism did not sig-
nificantly differ from the expected distribution predicted by
the Hardy–Weinberg equilibrium (p = .860) and were compa-
rable with the frequencies reported in other population-based
studies (28,29). Serum iron, transferrin saturation, and non–
transferrin-bound iron were significantly increased in carriers
of the HFE C282Y mutation as compared with noncarriers,
whereas total iron-binding capacity was decreased in carriers
of the HFE C282Y mutation as compared with noncarriers
(Table 1). Serum ferritin and hemoglobin concentrations, as
well as the background variables, did not significantly differ
between carriers and noncarriers of the HFE C282Y mutation
(Table 1). Table 2 presents the serum iron parameters in
Table 1. Baseline Characteristics of the Study Population According to HFE C282Y Genotype
Total Sample HFE C282Y Noncarriers HFE C282Y Carriers p*
n
818 685 80
Age (years) 60.3 ± 5.6 60.3 ± 5.6 59.8 ± 5.6 .508
Female sex (%) 28.4 27.9 30.0 .690
Level of education, low/middle/high (%) 22.4/38.1/39.5 21.8/38.4/39.9 28.8/31.2/40.0 .282
Alcohol consumption (g/day)
†
12.5 (4.4–23.5) 12.5 (4.4–23.4) 14.3 (3.7–26.1) .447
Current smoker (%) 20.4 20.0 23.8 .431
BMI (kg/m
2
) 26.6 ± 3.6 26.5 ± 3.6 26.6 ± 3.5 .846
Physical activity (PASE score) 152.8 ± 68.6 153.3 ± 69.3 153.1 ± 65.4 .981
Blood donor, current/former/never (%) 54.2/14.7/31.2 54.5/14.7/30.8 53.8/15.0/31.2 .993
APOE E4 alleles, 0/1/2 (%)
‡
67.9/29.2/2.8 69.4/28.0/2.6 58.8/38.8/2.5 .134
Serum C-reactive protein (mg/dL)
†,§
1.1 (0.6–2.3) 1.1 (0.6–2.3) 1.1 (0.6–2.1) .956
Serum hemoglobin (mmol/L) 8.9 ± 0.7 8.9 ± 0.7 9.0 ± 0.7 .088
Serum iron parameters
Serum iron (mmol/L) 18.5 ± 6.4 18.2 ± 6.2 21.4 ± 7.3 <.001
Total iron-binding capacity (mmol/L) 60.0 ± 8.1 60.4 ± 8.1 56.9 ± 7.8 <.001
Transferrin saturation (%) 31.4 ± 11.5 30.6 ± 10.8 38.7 ± 15.8 <.001
Ferritin (mg/L)
†
67.0 (35.0–131.0) 65.0 (34.0–125.0) 86.5 (47.8–138.8) .063
Non–transferrin-bound iron (mmol/L)
ǁ‖
2.4 ± 0.9 2.4 ± 0.9 2.8 ± 1.0 <.001
Notes
: Values are means ± SD. BMI = body mass index; PASE = Physical Activity Scale for the Elderly.
* p Values for the differences between carriers and noncarriers of the HFE C282Y mutation using chi-square tests, independent samples t tests, or nonparametric
Mann–Whitney tests.
†
Median value (interquartile range) is given because of skewed data distribution.
‡
n = 814 in the total sample, n = 682 in HFE C282Y noncarriers, and n = 80 in HFE C282Y carriers.
§
n = 803 in the total sample, n = 678 in HFE C282Y noncarriers, and n = 78 in HFE C282Y carriers.
ǁ
n = 808 in the total sample, n = 678 in HFE C282Y noncarriers, and n = 78 in HFE C282Y carriers.
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SCHIEPERS ET AL.
1316
carriers and noncarriers of the HFE C282Y mutation, strati-
fied by APOE E4 carrier status.
Cross-Sectional Associations Between Serum Iron
Parameters and Cognitive Functioning
The regression analyses including quadratic terms for
the iron parameters did not reveal any curvilinear relation-
ships between iron parameters and cognitive functioning
(data not shown). Cross-sectional linear regression analy-
ses indicated that higher serum ferritin levels were signifi-
cantly associated with decreased sensorimotor speed,
complex speed, and information-processing speed, after
adjustment for age, sex, level of education, alcohol con-
sumption, smoking, BMI, physical activity, C-reactive
protein, hemoglobin, and APOE E4 carrier status (Table 3).
In addition, higher serum iron was associated with de-
creased sensorimotor speed (Table 3). In order to better
understand the strength of the associations, when the pre-
dictive value of serum iron for cognitive performance is
compared with the relationship with age in the same regres-
sion model, an increase of 10 mmol/L serum iron corre-
sponds to a lower performance on sensorimotor speed
similar to an individual 5.9 years older. Likewise, a 100
mg/L increase in serum ferritin corresponds to the sensorimo-
tor speed and information-processing speed of someone 1.2
years older and the complex speed of an individual 1.3
years older. In contrast to serum iron and serum ferritin,
non–transferrin-bound iron was not significantly associ-
ated with cognitive performance.
The observed associations between iron parameters and
cognitive performance did not differ between men and
women, except for the relationship between ferritin and sen-
sorimotor speed, which was significant in men (b = −.089,
p = .029) but not in women (b = .048, p = 0.498). When the
analyses were stratified by donor status, only non-donors
showed a negative association between serum iron and sen-
sorimotor speed (b = −.313, p = .003 as compared with
b = −.093, p = .409 in donors), which was stronger than the as-
sociation found in the total sample. Statistical significance of
the other associations between iron parameters and cognitive
performance that were found in the total sample was elimi-
nated upon stratification by donor status. Stratification by
APOE E4 carrier status showed that the observed relation-
ship between ferritin and sensorimotor speed was significant
only in carriers of one or two APOE E4 alleles (n = 80) (b =
−.150, p = .023 as compared with b = −.044, p = .287 in the
noncarrier group); in comparison with the total sample, the
negative relationship between ferritin and sensorimotor
speed was more pronounced in APOE E4 carriers. In APOE
E4 carriers, the negative association between serum iron and
sensorimotor speed was similar to the relationship observed
in the total sample, although it was not statistically signifi-
cant. Overall, the cross-sectional associations between iron
parameters and cognitive performance in the analyses strati-
fied by sex, donor status, or APOE E4 carrier status pointed
Table 2. Serum Iron Parameters in Carriers and Noncarriers of the HFE C282Y Mutation at Baseline, Stratified by APOE E4 Carrier Status
Serum Iron Parameters
HFE C282Y Noncarriers HFE C282Y Carriers
APOE E4 Noncarriers APOE E4 Carriers p* APOE E4 Noncarriers APOE E4 Carriers p
n
473 209 47 33
Serum iron (mmol/L) 18.2 ± 6.5 18.1 ± 5.8 .966 21.2 ± 7.7 21.6 ± 6.9 .819
Total iron-binding capacity (mmol/L) 60.5 ± 8.2 60.2 ± 7.7 .691 55.5 ± 6.4 58.8 ± 9.2 .064
Transferrin saturation (%) 30.6 ± 11.1 30.6 ± 9.9 .958 39.0 ± 16.3 38.4 ± 15.3 .862
Ferritin (mg/L)
†
67.0 (35.0–131.0) 63.0 (30.0–119.0) .251 91.0 (50.0–139.0) 79.0 (26.0–147.0) .479
Non–transferrin-bound iron (mmol/L)
‡
2.4 ± 0.9 2.4 ± 0.8 .369 2.8 ± 1.0 2.9 ± 1.1 .661
Hemoglobin (mmol/L) 8.9 ± 0.7 8.8 ± 0.6 .086 9.1 ± 0.6 9.0 ± 0.7 .728
Notes
: Values are means ± SD.
* p Values for independent samples t tests or nonparametric Mann–Whitney tests.
†
Median value (interquartile range) is given because of skewed data distribution.
‡
HFE C282Y−/APOE E4–, n = 469; HFE C282Y−/APOE E4+, n = 206; HFE C282Y+/APOE E4−, n = 46; HFE C282Y+/APOE E4+, n = 32.
Table 3. Associations Between Iron Parameters and Cognitive Performance at Baseline in Healthy Older Adults*
Cognitive Performance Indices n
Standardized Regression Coefficient (b)
Serum Iron p Ferritin p Non–Transferrin-Bound Iron p
Memory 794 −.019 .807 .002 .951 .070 .362
Sensorimotor speed 789 −.185 .012 −.073 .033 .141 .054
Complex speed 788 −.081 .296 −.077 .019 .081 .266
Information-processing speed 791 −.109 .141 −.069 .046 .078 .291
Word fluency 794 −.050 .519 −.062 .092 .057 .462
Note: *Adjusted for the covariates age, sex, level of education, alcohol consumption, smoking, body mass index, physical activity, APOE E4 carrier status, serum
C-reactive protein, and hemoglobin concentration in hierarchical linear regression analyses.
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IRON PARAMETERS AND COGNITIVE PERFORMANCE
1317
in the same direction as the associations observed in the total
sample, with few differences between the groups, although
they tended not to reach statistical significance.
In post hoc analyses, we stratified by serum C-reactive
protein concentration (normal ≤3 mg/dL, elevated >3 mg/dL
(59)) to ascertain whether serum ferritin was associated with
cognitive functioning in the absence of inflammation. Higher
serum ferritin predicted slower sensorimotor speed (p =
.008), complex speed (p = .007), and information-processing
speed (p = .018) in individuals with normal C-reactive pro-
tein concentrations (n = 659) but not in persons with elevated
C-reactive protein levels indicative of inflammation (n = 144)
(p = .574, p = .777, and p = .945, respectively).
Longitudinal Associations Between Serum Iron
Parameters and Cognitive Functioning
Cognitive performance significantly declined over the
3-year follow-up period on the domains of sensorimotor
speed (mean change [95% CI] = −0.08 [−0.11 to −0.05],
p = .000), complex speed (mean change [95% CI] = −0.06
[−0.10 to −0.02], p = .004), and information-processing
speed (mean change [95% CI] = −0.11 [−0.15 to −0.08],
p = .000), whereas memory improved significantly (mean
change [95% CI] = 0.39 [0.34–0.44], p = .000) due to the
effect of procedural learning. Word fluency did not signifi-
cantly change over 3 years (mean change [95% CI] = 0.03
[−0.03 to 0.09], p = .320). Ferritin concentrations increased
significantly over the 3-year follow-up period (mean change
[95% CI] = 16.6 mg/L [6.7–26.4], p = .001), whereas serum
iron showed a nonsignificant decrease (mean change [95%
CI] =−0.5 mmol/L [−1.0 to 0.01], p = .055). Three-year
changes in serum iron and ferritin did not differ between the
two experimental groups (p = .268 for serum iron and p =
.707 for ferritin) or between men and women (p = .637 for
serum iron and p = .480 for ferritin). In addition, the longi-
tudinal changes in serum iron and ferritin did not differ sig-
nificantly between blood donors and non-donors (p = .965
for serum iron and p = .088 for ferritin), although blood
donors showed a larger 3-year increase in ferritin than
non-donors (mean change [95% CI] = 24.4 mg/L [8.1–40.7]
in donors and 7.1 mg/L [−2.4 to 16.7] in non-donors).
Linear mixed models revealed no significant longitudinal
associations between any of the iron parameters and cognitive
functioning (Table 4), implying that the rate of cognitive
change over 3 years did not vary according to body iron
concentrations. However, stratifying our analyses by donor
status indicated that higher serum iron significantly pre-
dicted less decline in sensorimotor speed over 3 years in
non-donors (parameter estimate = .005, p = .010 as com-
pared with parameter estimate = −.001, p = .253 in blood
donors) and less decline in word fluency over 3 years in
blood donors (parameter estimate = .006, p = .012 as com-
pared with parameter estimate = −.004, p = .165 in non-
donors), indicating effect modification by donor status.
Stratification by sex or APOE E4 carrier status did not
reveal any differences between men and women or between
carriers and noncarriers of the APOE E4 allele. Overall, the
longitudinal associations between iron parameters and cog-
nitive performance in the analyses stratified by sex, donor
status, or APOE E4 carrier status were fairly inconsistent in
terms of size and direction.
Associations Between the HFE C282Y Mutation and
Cognitive Functioning
To investigate the influence of lifelong exposure to
elevated iron levels on cognitive performance in later life,
we assessed the associations between the HFE C282Y muta-
tion and cognitive functioning on each of the five domains.
The HFE C282Y mutation was not associated with cognitive
performance in both the cross-sectional and longitudinal
analyses (Supplementary Table 2).
Discussion
In the present study, none of the serum iron parameters,
nor HFE C282Y genotype, were related to cognitive perfor-
mance over 3 years of follow-up. However, the results from
the cross-sectional analyses suggest that in older individ-
uals serum ferritin and serum iron may be negatively related
to the speed of cognitive functioning. Whereas higher ferri-
tin concentrations were associated with decreased cognitive
functioning across the three different speed measures at
Table 4. Longitudinal Associations Between Iron Parameters and Cognitive Performance Over 3 Years of Follow-up in Healthy Older Adults*
Cognitive Performance Indices n
Parameter Estimate for Longitudinal Effect
Serum Iron p Ferritin p Non–Transferrin-Bound Iron
†
p
Memory 800 .002 .307 −.001 .292 .000 .965
Sensorimotor speed 799 .001 .396 .000 .806 .001 .925
Complex speed 798 −.002 .086 −.001 .221 −.016 .052
Information-processing speed 799 .001 .501 .000 .578 −.005 .446
Word fluency 800 .002 .215 .000 .991 .018 .121
Notes
: *Adjusted for the covariates age, sex, level of education, alcohol consumption, smoking, body mass index, physical activity, APOE E4 carrier status, serum
C-reactive protein, and hemoglobin concentration in linear mixed models.
†
Non–transferrin-bound iron was measured at baseline only. Memory, n = 794; sensorimotor speed, n = 793; complex speed, n = 792; information-processing
speed, n = 793; word fluency, n = 794.
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SCHIEPERS ET AL.
1318
baseline, serum iron appeared to be negatively related to
sensorimotor speed only. Memory processes, on the other
hand, did not seem to be related to ferritin nor any other
serum iron parameter. In addition, non–transferrin-bound
iron and the HFE C282Y mutation were not associated with
cognitive functioning in the cross-sectional analyses.
Carriers of the HFE C282Y mutation tend to show higher
body iron concentrations than noncarriers (28). As genetic
factors cannot be influenced by cognitive functioning, in-
vestigating the associations between HFE genotype and
cognitive performance has the benefit of reducing con-
founding and ruling out the possibility of reverse causation
(60). In the present study, we found that the HFE C282Y
mutation was associated with significantly increased con-
centrations of serum iron and non–transferrin-bound iron,
as well as a statistically nonsignificant increase in serum
ferritin. Contrary to expectation, we did not find any asso-
ciations between HFE C282Y genotype and cognitive func-
tioning. A possible explanation for the lack of such a
relationship is the relatively small percentage of carriers of
the HFE C282Y mutation (10.5%), which might have re-
duced the probability of detecting potential associations. In
addition, no data were available concerning another com-
mon polymorphism of the HFE gene, H63D, which has
been found to interact with the HFE C282Y genotype in
determining individual iron levels (28,61). Future studies
investigating the associations between HFE genotype and
cognitive functioning might increase statistical power by
including both polymorphisms of the HFE gene in their
analyses. Furthermore, it should be noted that the generaliz-
ability of our study was limited by the nature of the study
population; the present study sample was not representative
of the general population, as participants had slightly ele-
vated plasma total homocysteine concentrations and were
vitamin B12 replete.
Non–transferrin-bound iron has been hypothesized to be
involved in neurodegenerative disorders characterized by
iron deposition in the brain (47,62). The putative relationship
between non–transferrin-bound iron and cognitive perfor-
mance, however, has not been investigated before. The pres-
ent results do not offer support for an association between
non–transferrin-bound iron and cognitive performance or
age-related cognitive decline. Serum non–transferrin-bound
iron concentrations are generally very low in healthy individ-
uals, whereas individuals heterozygous for the HFE C282Y
mutation show slightly elevated non–transferrin-bound iron
concentrations (63). In hemochromatosis homozygotes,
non–transferrin-bound iron is typically present in much
larger amounts (63). However, as the present study included
only two individuals homozygous for the HFE C282Y muta-
tion, the range of serum non–transferrin-bound iron concen-
trations might have been too small for any associations with
cognitive performance to become manifest. In addition, non–
transferrin-bound iron was only measured at baseline,
thereby limiting the interpretation of the longitudinal analyses
investigating the association of this iron parameter with cog-
nitive functioning over 3 years.
Although elevated serum ferritin concentrations gener-
ally reflect increased body iron stores (45), serum ferritin
levels also tend to be higher in conditions of inflammation,
as ferritin is an acute-phase reactant (23,54). In the present
study, we controlled for this confounding effect of inflam-
mation by including serum C-reactive protein concentration
as a covariate in the statistical models. Post hoc analyses
showed that the inverse relationship between ferritin and
cognitive speed was independent of C-reactive protein con-
centration, indicating that the observed cross-sectional as-
sociation between serum ferritin and cognitive speed could
not be attributed to the presence of inflammation.
The present finding that higher serum ferritin levels were
related to slower sensorimotor speed in carriers, but not in
noncarriers of the APOE E4 allele, suggests that APOE E4
carrier status may modify the effect of elevated body iron
stores on cognitive functioning. Although APOE E4 carrier
status has been implicated in age-related cognitive decline
and neurodegenerative processes (64,65), it is unclear which
mechanisms might be responsible for the putative interplay
between APOE E4 carrier status and serum ferritin in
affecting cognitive performance.
To date, only a few other population-based studies have
investigated the relationship between iron parameters and
cognitive performance in older individuals. These cross-
sectional studies have yielded conflicting results. Whereas
Gao and colleagues (20) did not find any associations be-
tween serum iron and cognitive performance in a relatively
small sample of 94 men and 94 women, La Rue and col-
leagues (21) reported a positive correlation between serum
transferrin and cognitive functioning, that is, memory, vi-
suospatial skills, and abstract reasoning, in a small sample
of 67 men and 70 women. However, this association was
not corrected for potential confounders, such as age, sex,
BMI, and alcohol consumption.
A recent cross-sectional study performed by Lam and
colleagues (22) in a large population-based sample consist-
ing of 602 men and 849 women has shown an inverse linear
association between serum iron and performance on mem-
ory tests in older women. Interestingly, in older men, Lam
and colleagues found an inverted U-shaped relationship be-
tween serum iron and memory performance. Because we
hypothesized that both low and high body iron levels would
be associated with cognitive impairment, we also expected
to find an inverted U-shaped relationship between body iron
levels and cognitive performance. However, although the
number of men in our sample (n = 586) was comparable
with the number of men included in the study by Lam and
colleagues, thereby yielding similar statistical power, no
curvilinear associations became apparent between the iron
parameters and cognitive functioning in the present study,
neither in the total sample nor after stratification by sex. The
lack of curvilinear associations in our study may be due to
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IRON PARAMETERS AND COGNITIVE PERFORMANCE
1319
the relatively small percentage of individuals with body iron
levels below or above the normal limits. Therefore, possible
nonlinear associations between iron parameters and cogni-
tive functioning may have remained undetected. Indeed, se-
rum iron concentrations in the study by Lam and colleagues
showed higher means and a broader range as compared with
our study (21.7 ± 7.2 mmol/L in men and 19.4 ± 6.2 mmol/L
in women as compared with 19.0 ± 6.8 mmol/L in men and
17.1 ± 4.8 mmol/L in women in our study).
It is worth noting that the prevalence of depleted iron
stores in our study sample was slightly higher than that re-
ported in other population-based studies in older individ-
uals (ie, 5.3% as compared with 0.3%–3%) (6,27). In
addition, our study showed a lower percentage of ferritin
levels above the upper normal limit than other studies per-
formed in older community-dwelling individuals, which
used similar or even higher serum ferritin cutoff values (ie,
6.5% as compared with 12%–20%) (6,27). This may be ex-
plained by the large number of blood donors in our study
sample, as regular whole blood donation has been shown to
lower body iron concentrations (8). Indeed, whereas 0.8%
of non-donors showed ferritin levels below the lower nor-
mal limit and 13.1% showed ferritin levels above the upper
normal limit, the prevalence among blood donors was
11.3% and 0.9%, respectively.
Upon stratification of the cross-sectional analyses by do-
nor status, we found that higher serum iron was associated
with decreased sensorimotor speed in non-donors but not in
blood donors. When the longitudinal analyses were strati-
fied by donor status, we found that higher serum iron not
only predicted less decline in sensorimotor speed over 3
years in non-donors but also less decline in word fluency
over 3 years in blood donors. Although these findings are
not unequivocal, they do suggest that donor status may in-
fluence the nature of the associations between serum iron
parameters and cognitive performance. The underlying
mechanism has yet to be elucidated.
We observed a significant increase in serum ferritin con-
centrations over the 3-year follow-up period, which is con-
sistent with earlier reports indicating that body iron stores
increase with aging (26). Although the difference was not
statistically significant, serum ferritin showed a greater
3-year increase in donors as compared with non-donors.
This difference may be related to the potential discontinua-
tion of blood donation in regular whole blood donors during
the course of the study. Unfortunately, we were not able to
verify this assumption as we did not monitor donor status
during the 3-year follow-up period. Serum iron tended to
decrease during the follow-up period, but this change was
not statistically significant. Although the factors underlying
the 3-year change in serum iron are not exactly clear, it is
worth noting that they are not likely to be due to diurnal
variation in serum iron levels (66), as we collected the
3-year blood samples at the same time of day as the baseline
samples.
In the present study, we used serum iron parameters as
a proxy measure for brain iron levels, even though the
exact correlation between central and peripheral iron
levels is unclear. Nonetheless, epidemiological studies
have found evidence for a positive association between
the two, by showing a significant correlation between iron
concentrations in serum and cerebrospinal fluid in older
individuals (67). On the other hand, it has also been sug-
gested that brain iron levels may be relatively well iso-
lated from peripheral iron levels, for example, in carriers
of the HFE C282Y mutation (68). Thus, given the inabil-
ity to measure cerebrospinal fluid or brain iron levels in
volunteers, the use of serum iron parameters should be
considered a shortcoming.
The main strengths of the present study are the use of
longitudinal data, the measurement of several iron parame-
ters as well as HFE C282Y genotype, the use of a large
community-based sample, and a very low attrition rate in
the longitudinal phase (2%) (37). In addition, the cognitive
test battery administered in the present study has been
proven a sensitive and robust tool for detecting subtle
changes in specific domains of cognitive functioning (38–
42). Furthermore, the inclusion of both men and women, as
well as blood donors and non-donors in our study, enabled
us to investigate the relationship between iron parameters
and cognitive functioning within these individual groups.
The relevance of taking into account donor status in population-
based studies is emphasized by the present finding that
regular whole blood donation may modify the associations
between iron parameters and cognitive performance. In-
deed, the lack of documenting donor status might have con-
founded several other population-based studies investigating
these associations, including those performed by Lam and
colleagues (22), Gao and colleagues (20), and La Rue and
colleagues (21).
In conclusion, the lack of any longitudinal associations
between iron parameters and cognitive performance, as
well as the lack of a relationship between HFE C282Y
genotype and cognitive functioning, suggests that there is
no clear-cut relationship between serum iron parameters
and cognitive functioning or age-related cognitive decline
in older community-dwelling individuals. However, the
present study offers indications for a more intricate rela-
tionship between body iron levels and cognitive perfor-
mance, which may be present only in a subsample of the
community, for example, in individuals carrying the APOE
E4 allele.
To our knowledge, our study is the first to address the
putative associations between the HFE C282Y mutation
and cognitive performance in healthy older individuals, as
well as the possible interactions between iron parameters
and APOE E4 carrier status or donor status in relation to
cognitive functioning. Prospective studies using large
population-based samples are needed to further investigate
the associations between iron parameters and cognitive
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SCHIEPERS ET AL.
1320
performance and to establish whether this association may
differ across selected groups, for example, based on sex,
donor status, APOE E4 carrier status, or other risk factors
associated with cognitive decline. In addition, more research
is necessary to identify the exact mechanisms by which iron
parameters may influence cognitive functioning.
Funding
This work was supported by the Netherlands Organization for Health
Research and Development (grant number 200110002); Sanquin Blood
Bank (grant number 02-001); Wageningen University; and Top Institute
Food and Nutrition.
Supplementary material
Supplementary material can be found at: http://biomed.gerontologyjournals
.org/
Acknowledgment
The authors would like to thank Dr. Berry van Tits, Department of
General Internal Medicine, Radboud University Nijmegen Medical
Centre, Nijmegen, The Netherlands, for the measurement of non–transferrin-
bound iron.
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