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Macular Pigment, Visual Function, and Macular

Journal of Alzheimer’s Disease xx (20xx) x–xx
DOI 10.3233/JAD-140507
IOS Press
Macular Pigment, Visual Function, and
Macular Disease among Subjects with
Alzheimer’s Disease: An Exploratory Study
John M. Nolana,∗ , Ekaterina Loskutovaa , Alan N. Howardb,c , Rachel Morana , Riona Mulcahyd ,
Jim Stacka , Maggie Bolgerd , Jessica Dennisona , Kwadwo Owusu Akuffoa , Niamh Owensa ,
David I. Thurnhame and Stephen Beattya
a Macular Pigment Research Group, Department of Chemical and Life Sciences, Waterford Institute of Technology,
Waterford, Ireland
b Howard Foundation, Cambridge, UK
c Downing College, University of Cambridge, Cambridge, UK
d Waterford Regional Hospital, Age-Related Care Unit, Waterford, Ireland
e Northern Ireland, Centre for Food and Health (NICHE), University of Ulster, Coleraine, UK
Accepted 2 May 2014
Background: The macula (central retina) contains a yellow pigment, comprising the dietary carotenoids lutein (L), zeaxanthin
(Z), and meso-zeaxanthin, known as macular pigment (MP). The concentrations of MP’s constituent carotenoids in retina and
brain tissue correlate, and there is a biologically-plausible rationale, supported by emerging evidence, that MP’s constituent
carotenoids are also important for cognitive function.
Objective: To investigate if patients with Alzheimer’s disease (AD) are comparable to controls in terms of MP and visual
Methods: 36 patients with moderate AD and 33 controls with the same age range participated. MP was measured using
dual-wavelength autofluorescence (Heidelberg Spectralis® ); cognitive function was assessed using a battery of cognition tests
(including Cambridge Neuropsychological Test Automated Battery). Visual function was recorded by measuring best corrected visual acuity (BCVA) and contrast sensitivity (CS). Serum L and Z concentrations (by HPLC) and age-related macular
degeneration (AMD, by retinal examination) status were also assessed.
Results: In the AD group, central MP (i.e., at 0.23◦ ) and MP volume were significantly lower than the control group (p < 0.001
for both), as were measures of BCVA, CS, and serum L and Z concentrations (p < 0.05, for all).
Conclusion: AD patients were observed to exhibit significantly less MP, lower serum concentrations of L and Z, poorer vision,
and a higher occurrence of AMD when compared to control subjects. A clinical trial in AD patients designed to investigate the
impact of macular carotenoid supplementation with respect to MP, visual function, and cognitive function is merited.
Keywords: Age-related macular degeneration, Alzheimer’s disease, cognitive function, contrast sensitivity, lutein,
meso-zeaxanthin, visual function, zeaxanthin
∗ Correspondence to: Professor John Nolan, Macular Pigment
Research Group, Vision Research Centre, Carriganore House,
Waterford Institute of Technology, West Campus, Carriganore,
Waterford, Ireland. Tel.: +353 51 834074; E-mail:
ISSN 1387-2877/14/$27.50 © 2014 – IOS Press and the authors. All rights reserved
This article is published online with Open Access and distributed under the terms of the Creative Commons Attribution Non-Commercial License.
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
Alzheimer’s disease (AD) is a chronic and progressive neurodegenerative condition, characterized
by a loss of cognitive abilities with impaired executive functioning and change in personality or behavior.
Dementia is often and mistakenly used as a synonym
for AD, but in fact is an umbrella term describing a
variety of conditions that involve the deterioration of
cognitive functions, of which AD is the most common
form (accounting for 50–75% of cases) [1, 2]. Reports
show that AD is the leading cause of dementia, affecting more than 35 million people worldwide [2]. In the
United States, a report from 2012 estimated that 5.4
million people currently suffer from AD [3]. Of note,
the incidence of AD increases exponentially with age
Carotenoids are naturally-occurring plant pigments
and important constituents of a healthy diet, because
of their established contribution to the antioxidant
defense system in the macula and their putative contribution to the antioxidant defense system of the brain
[4, 5]. The carotenoids lutein (L), zeaxanthin (Z) and
meso-zeaxanthin (MZ) are found at the macula (the
central retina) where they accumulate preferentially
relative to the other 42 dietary carotenoids [6, 7]. This
deposit of L, Z, and MZ at the macula is collectively
referred to as macular pigment (MP), and MP can be
measured in vivo (in units of optical density [OD]), [8]
and in vitro (using high performance liquid chromatography [HPLC]) [9].
Research has identified that L and Z are also present
in the brain (albeit in small amounts, picomolar concentrations), including in the cerebellum, pons, frontal
and occipital cortices (MZ analyses were not performed in these studies, because such an analysis
requires a separate assay), [10, 11] and their presence in
these tissues has been confirmed in a recent study [12].
Also, a study in rhesus monkeys reported a positive
relationship between retinal and brain concentrations
of L and Z, and significantly so for L concentrations at
the macula with L concentrations within the cerebellum, occipital cortex, and pons [11].
Furthermore, plasma concentrations of L and Z are
known to be lower in AD patients when compared with
control subjects, with L concentrations correlating significantly and inversely with dementia severity [13,
14]. Moreover, it has been shown that supplemental
L results in improved performance in a range of tests
used to assess cognitive function in unimpaired older
women [15]. Renzi et al. have shown that MP levels
also relate significantly and positively to performance
on a number of measures of cortical function, in healthy
elderly subjects [16]. Indeed, a positive relationship
between MP and several measures of cognitive function (e.g., Mini-Mental State Examination (MMSE),
Montreal cognitive assessment (MoCA© ), prospective
memory tests, trail-making tasks, and choice reaction tests) was recently confirmed in a large sample
(n = 4,453 adults ≥50 years) from the Republic of Ireland [17].
The rationale for the protective, or even cognitionenhancing, effect of the carotenoids in the brain rests
primarily on their antioxidant properties [16]. However, other mechanisms whereby the carotenoids in
the brain may afford protection, or enhance cognitive
function, include: their anti-inflammatory properties;
and their role in maintaining the structural integrity
of gap junctions; amongst other possible and yetto-be identified mechanisms. Indeed, it is tempting
to draw parallels between the putative protective
effect of macular carotenoids for AD and age-related
macular degeneration (AMD), another age-related disorder affecting the central nervous system (CNS) (the
retina being part of the CNS), especially given the
antecedents that these two conditions share [18, 19].
Furthermore, MP’s positive relationship with critical fusion frequency (which describes a speed with
which signals are processed in the CNS) suggests that
MP’s constituent carotenoids may play a role in CNS
processing [20]. In other words, it is reasonable to
hypothesize that MP’s constituent carotenoids (L, Z,
and MZ) may confer protection against AD, and if so,
measures of MP may represent an accessible clinical
biomarker of concentrations of these potentially important compounds within the brain. However, no study
to date has investigated MP levels in patients with AD.
The current study, known as the Carotenoids and AgeRelated Dementia Study (CARDS), was designed to
investigate whether patients with AD were comparable to controls (of the same age range) in terms of MP,
visual function, and AMD status.
This study was conducted in accordance with full
sensitivity to the ethical requirements of the patients
and control subjects recruited. The study objectives
and methodology complied fully with the widelyrecognized international text and codes of practice,
such as the Declaration of Helsinki. A protocol was
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
(analysis conducted offsite at Biomnis Ireland, Three
Rock Road, Sandyford Business Estate, Dublin 18,
Cognitive function assessment
Cognition was assessed using a selection of validated measures. The MMSE was used to measure the
severity of cognitive impairment. This is a rapid, 30
item questionnaire that is commonly used to screen
for dementia and track changes over time. A semantic
fluency score was obtained using ‘Animal” as the category (as many exemplars as possible in one minute)
and phonemic fluency was measured using the ‘FAS
Test’ (as many words as possible starting with each
letter, one minute per letter). Three tasks were chosen
from the Cambridge Neuropsychological Test Automated Battery (CANTAB) [21]. All were administered
using a finger-operated touch-screen tablet PC using
a set of scripted instructions. The Paired Associates
Learning task was selected to assess visual memory
and learning [22, 23]. In this task the subject is presented with a set of white boxes, some of which contain
a pattern. The objective is to remember the location
of each pattern. The test gradually increases in difficulty until the final stage is reached. If a mistake is
made then the subject is reminded of the location of
the patterns and given another opportunity to respond.
The task ends after the final stage is completed or if
the subject exceeds a specified number of attempts
at any given stage. The scores generated are Total
Errors and Total Errors Adjusted. Total Errors is a
sum of the errors made across all stages, whereas the
adjusted score includes an adjustment made for any
stages not reached, allowing it to be comparable to all
subjects even if the task was ended prematurely due to
cognitive limitation. The Verbal Recognition Memory
test assesses immediate and delayed verbal memory
and learning under immediate and delayed free-recall
and forced-choice recognition conditions [24, 25]. The
subject is instructed to immediately recall as many
words as possible after being presented with a list of
stimuli (on the basis of frequency, word length, and
imageability). This process is repeated three times and
scores are provided for the number of words correctly
recalled in each separate phase, as well as a total correct score. After a short delay, the subjects must then
complete a recognition phase with a matched set of
distractor stimuli. This stage provides scores based on
the total number of correct selections and rejections
(of distractor stimuli), as well as false positives. The
CANTAB Motor Screening Task was used to assess
developed specifically for this study by the Principal
Investigator (JMN) and Consultant Geriatrician (RM)
at Waterford Regional Hospital to ensure that informed
consent was obtained appropriately, and in keeping
with the ethical code germane to obtaining consent
from vulnerable subjects (which includes patients with
36 patients with mild to moderate AD (predominantly moderate) attending the Age-Related Care Unit
at Waterford Regional Hospital, Waterford, Ireland
were recruited into the study. Mild to moderate AD
was defined as an average MMSE score of 14 to 24
with documented difficulties carrying out everyday
tasks, and some alteration in behavior. Other screening tests included the clock drawing test and semantic
fluency score. Co-morbid diagnoses were documented
including vascular risk factors. Current medications
were verified including cholinesterase inhibitors and
glutamate receptor antagonists. Social and collateral
histories were taken for all patients. Non-contrast computed tomography (CT) brain scan was performed to
rule out stroke disease.
Thirty-three control subjects were also recruited into
the study via newspaper and radio advertisements, and
by word of mouth in the local community. Five (15%)
of the subjects recruited into the control group were
spouses/partners of the subjects with AD, which was
desirable for performing comparison statistics with
the AD group, because of shared environmental variables, but we acknowledge subject recruitment bias
represents a weakness inherent in this trial. However,
any relevant differences between groups were controlled for during statistical analyses. Ethical approval
was granted from the local Waterford South East (of
Ireland) Region Ethics Committee prior to the study
Demographic, medical, ophthalmic, and lifestyle
A demographic, medical, ophthalmic and lifestyle
case history was obtained for each subject at their
study visit. Body mass index was calculated (kg/m2 )
with subject height (m) measured with the Leicester Height Measure, and weight (kg) measured with
the SECA weighing scales (SECA, Birmingham, UK).
Smoking status was classed as either current smoker
(i.e., smoked ≥100 cigarettes in lifetime and at least
one cigarette within the last 12 months) or nonsmoker (smoked ≤100 cigarettes in lifetime and none
within the last 12 months). Diabetes was assessed by
self-report and also by measuring HbA1c in blood
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
motor speed and accuracy by instructing the subject to
touch the center of a series of crosses that are presented
on the screen [26].
Best corrected visual acuity
Contrast sensitivity
Macular pigment measurement
The Heidelberg Spectralis® HRA+OCT Multicolor
(Heidelberg Engineering GmbH, Heidelberg, Germany) was used to measure MP. The Spectralis utilizes
confocal scanning laser ophthalmoscopy imaging with
diode lasers and uses dual-wavelength autofluorescence (AF) for measuring MP [29]. Dual-wavelength
AF in this device uses two excitation wavelengths;
one that is well-absorbed by MP (488 nm, blue) and
one that is not well absorbed by the pigment (518 nm,
green). The AF method utilized by the Spectralis
has previously been compared with the customized
heterochromatic flicker photometry technique for measuring MP, and the measurements recorded from
these two devices exhibited excellent concordance
During the measurement, the subject’s head is
aligned using a head-chin strap and he/she is instructed
to fixate on an internal fixation target. A 30-s video is
recorded in simultaneous blue AF and green AF imaging mode for MP measurement acquisition. The images
in the video are then aligned and averaged using the
Heidelberg Eye Explorer software (HEYEX, version, and a MP density map is created. Central MP
at 0.23 degrees eccentricity and MP volume (calculated as MP average times the area under the curve out
to 8 degrees eccentricity) are reported here.
BCVA was measured with a computerized LogMAR
ETDRS test chart (Test Chart 2000 Xpert; Thomson
Software Solutions) viewed at 6 meters (m). The Sloan
Early Treatment Diabetic Retinopathy Study (ETDRS)
letterset was used for this test. At the first incompletely
read line, the letters of the line were randomized three
times using the testing software’s randomization function and an average of three scores was taken. BCVA
was recorded as visual acuity rating.
Age-Related Macular Degeneration by a consultant
ophthalmologist with a special interest in retinal disease and with a published track record in grading this
condition [28]. In brief, the presence of soft drusen
and/or hypo-/hyper-pigmentary changes at the macula
were classed as early AMD.
CS refers to one’s ability to discern an object from
its background, and depends on the difference in luminance between the former and the latter, and can be
loosely interpreted as ‘faintness appreciation’. Letter
contrast sensitivity (CS) was assessed using the computerized LogMAR ETDRS test chart (Test Chart 2000
Pro; Thomson Software Solutions) at five different spatial frequencies (1.2, 2.4, 6.0, 9.6, 15.15 cpd) [27].
Thirty (43%) of the 69 subjects could not perform the
high (15.15 cpd) spatial frequency test, and therefore
this measure was excluded from analysis. The Sloan
optotypes were chosen and subjects were asked to read
the letters aloud while fixating on the chart at a distance
of 4 m. The letter set was randomized during the test at
each change of contrast. The percentage contrast of letter optotypes was decreased in 0.15 log CS steps until
the lowest contrast value for which subjects saw at least
three letters was reached. The test was then repeated for
the other spatial frequencies. Each letter has a nominal log CS value of 0.03. Missed letters at any contrast
level were noted. The resultant log CS value for the
subject at a particular spatial frequency was calculated
by adding any extra letter(s) and/or subtracting missed
letters from best log CS value corresponding to the
lowest percentage contrast.
Retinal photograph assessment
45 degree monoscopic color photographs, centered
on the macula, were taken in both eyes using a Zeiss
Visucam 200 (Carl Zeiss Meditec AG, Jena, Germany).
Retinal photographs were assessed for the presence
or absence of early AMD, in accordance with the
International Classification and Grading System for
Dietary intake of lutein and zeaxanthin
A subject’s weekly intake of carotenoid-rich foods
(eggs, broccoli, corn, dark leafy vegetables) was
inputted into the L/Z screener to give a carotenoidbased diet score. Values are weighted for frequency
of intake of the food and for bioavailability of L
and Z within these foods. A ranking score reflecting the relative intakes was generated. Evaluation
of the L/Z screener against the Willett food frequency questionnaire yielded a positive correlation
that was strongly significant (p < 0.01). The range of
scores on the L/Z screener is 0 to 75. After adding
foods with known concentrations of the L and Z into
the screener, the following estimates can be made:
a low dietary carotenoid intake score ranges from
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
Serum carotenoid assessment
Standards and solvents
The L and Z reference standards were purchased from CaroteNature (GmbH Thomas Studer,
CEO Gerbestrasse 12 Postfach 1164 CH-3072 Ostermundigen Switzerland). The internal standard (IS)
␣-tocopheryl acetate and all solvents used for
extraction and HPLC analysis were supplied by SigmaAldrich (Ireland) and Fisher Scientific (Ireland).
ing 0.35 ml glass inserts (Sigma-Aldrich). Separations
were carried out using a method slightly modified from
Yeum et al (see below) [32]. The sample (0.1 ml) was
injected via autosampler onto a C30 carotenoid column (250 × 4.6 mm, 3 ␮m YMC) with a guard column.
HPLC mobile phase A consisted of 83% methanol,
15% MTBE, and 2% water with 0.1% BHT and mobile
phase B consisted of 90% MTBE, 8% methanol, 2%
water with 0.1% BHT. At a flow rate of 1 ml/min, the
gradient initiated at 5% solvent B and increased to
20% in the first 12 min. Solvent B was increased to
55% over 8 min before increasing again to 95% over
the next 7 min. From 27–30 min, solvent B was held
at 95% B followed by the system resuming to initial
setting at 33 min. The L and total Z (co-eluted Z and
MZ) peaks eluted at approximately 10.3 and 12.1 min,
respectively. The IS eluted at 8.8 min. Separations were
carried out at 16◦ C.
0–15 (≤2 mg/day); a medium dietary carotenoid intake
score ranges from 16–30 (3–13 mg/day); and a high
dietary carotenoid intake score ranges from 31–75
(>13 mg/day).
Non-fasting blood samples were collected in 9 ml
vacuette tubes containing a ‘Z Serum Sep Clot Activator’. The blood samples were allowed to clot at room
temperature for approximately 1 h and then centrifuged
at 725 g for 15 min in a Gruppe GC 12 centrifuge
(Desaga Sarstedt) to separate the serum from the whole
blood. The resulting serum samples were stored at
−70◦ C until the time of extraction.
Serum (0.4 ml) was micropipetted into clear 1.5 ml
Eppendorf tubes labelled according to subject and visit
number. IS (0.2 ml), ␣-tocopheryl acetate (250 mg/l
ethanol) and 0.3 ml of butylated hydroxytoluene
(BHT) (250 mg/l ethanol) were added and extracted
into 0.5 ml of heptane using a Vortex Genie-2
(Scientific Industries) at the highest setting for
2 min, followed by centrifugation with a AccuSpin
Micro 17 (Fisher Scientific Ireland) for 5 min at
400 g.
An aliquot of the upper heptane layer (0.4 ml) was
removed to a light-resistant Eppendorf tube, and the
heptane extraction was repeated once more, adding
a further 0.5 ml of heptane to the original residue.
The combined extracts were dried under nitrogen and
stored at −70◦ C until HPLC analysis [31].
The chromatographic analysis was performed on an
Agilent 1260 Series (Agilent Technologies Limited)
equipped with a quaternary pump, autosampler, thermostat column compartment and a photodiode array
detector monitoring a wavelength of 450 nm for serum
carotenoids and 292 nm for the IS. The dried samples
were reconstituted in 0.2 ml of 90% methanol and 10%
methyl-tert-butyl ether (MTBE), vortexed at the lowest
setting for 1 min and pipetted into 2.5 ml vials contain-
The statistical package IBM SPSS version 21 was
used for all statistical analyses. The primary outcome
measures for this study were MP, measures of vision
function variables (i.e., BCVA and CS) and AMD status. Between group differences (AD versus controls)
in terms of these outcome measures were first analyzed using independent samples t-tests or chi-squared
tests, as appropriate. The general linear model, or
logistic regression where appropriate, was then used
to control for other, possibly confounding, variables,
which exhibits significant between group differences
(e.g., age, diet, and education). For analyses where
the outcome variable was vision-related, we also controlled for MP. The 5% level of significance was used
throughout the analysis, without adjustment for multiple comparisons.
Table 1 presents the demographic, lifestyle, vision,
and cognition data of the AD and control subjects
recruited into the study. The table presents information on outcome variables (i.e., serum L and Z, MP,
vision, and AMD status) and on demographic, possibly confounding, variables (e.g., age, body mass index,
smoking status). As seen in Table 1, there were statistically significant between group differences in terms
of MP, age, diet score, serum L and Z, education, and
AMD prevalence, so we controlled for these variables
in all subsequent analyses where appropriate.
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
Table 1
Demographic, lifestyle, vision, and cognition data of the AD and control subjects
AD (n = 36)
Control (n = 33)
80 ± 7.8
5 (13.9%)
2 (5.5%)
8 (22.3%)
8 (22.3%)
7 (19.4%)
6 (16.7%)
24.9 ± 5.6
179 ± 214.5
15 ± 8.4
0.217 ± 0.112
0.049 ± 0.034
10 ± 4.3
76 ± 6.6
2 (6.1%)
9 (27.2%)
11 (33.4%)
6 (18.1%)
5 (15.2%)
0 (0%)
26.2 ± 3.4
221 ± 160.0
23 ± 14.0
0.295 ± 0.175
0.074 ± 0.041
14 ± 4.3
0.40 ± 0.20
3700 ± 2833
88.4 ± 11.4
1.49 ± 0.22
1.47 ± 0.29
1.18 ± 0.31
0.91 ± 0.34
0.58 ± 0.17
6776 ± 2834
95.8 ± 8.4
1.77 ± .23
1.76 ± 0.26
1.43 ± 0.24
1.19 ± 0.27
231 ± 36
321 ± 34
277 ± 32
324 ± 29
224 ± 27
320 ± 23
275 ± 26
333 ± 24
Age (years)
Body mass index (kg/m2 )
Exercise (total exercise per week)
Diet (estimated lutein and zeaxanthin intake)
Serum lutein (␮mol/l)
Serum zeaxanthin (␮mol/l)
Education (total years in education)
Smoking (% current)
Gender (% female)
Diabetes (% with diabetes)
MP 0.23
MP vol
CS1.2 (cpd)
CS2.4 (cpd)
CS6.0 (cpd)
CS9.6 (cpd)
AMD (% with AMD)
Retinal thickness
Central min thickness
Central max thickness
Central mean thickness
Average thickness
Semantic fluency score
Phonemic fluency score
MOT (mean latency)
MOT (mean error)
VRM (phase 1)
VRM (phase 2)
VRM (phase 3)
VRM (correct words)
VRM delayed stage (correct words)
VRM delayed stage (recognition total correct)
VRM delayed stage (recognition total false positive)
PAL (total errors)
PAL (total errors adjusted)
18.8 ± 3.7
6.1 ± 3.2
15.7 ± 10.0
1860 ± 799
11.9 ± 3.14
1.4 ± 1.2
2.5 ± 1.6
3.3 ± 2.1
1.40 ± 1.17
1.3 ± 3.73
17 ± 3.3
4.6 ± 3.5
135.5 ± 14.3
24.6 ± 11.4
29.0 ± 1.7
15.4 ± 5.1
33.5 ± 13.8
1322 ± 571
9.5 ± 2.8
5.2 ± 2.7
7.4 ± 2.7
8.2 ± 2.9
5.24 ± 2.69
7.2 ± 4.6
23 ± 1.4
0.68 ± 0.91
68 ± 39
17.1 ± 11.02
Data displayed are mean ± standard deviation for interval data and percentages for categorical data. Variables, variables analyzed in the study;
AD, subjects recruited into the study confirmed as having mild to moderate Alzheimer’s disease; Control, subjects free of mild to moderate
AD and of similar age to the AD subjects; Sig., the statistical difference (p value) between AD and control subjects assessed using independent
samples t-tests or chi-squared depending on the variable of interest; Exercise, total exercise for any sporting activity measured as minutes per
week; Diet, estimate of dietary intake of L and Z; Smoking, current (smoked ≥100 cigarettes in lifetime and at least one cigarette within the
last 12 months) or non-smoking (smoked ≤100 cigarettes in lifetime and none within the last 12 months); Diabetes, % of subjects with diabetes
as confirmed by self-report and by HbA1c analysis; MP 0.23, central macular pigment measured at 0.23 degrees eccentricity measured using
the Heidelberg Spectralis® . MP vol, a volume of MP calculated as MP average times the area under the curve out to 8 degrees eccentricity
(measured using the Heidelberg Spectralis® ). BCVA, best corrected visual acuity. CS 1.2, CS 2.4, CS 6.0 and CS 9.6, letter contrast sensitivity
measured using the Thomson Software Solutions at 1.2, 2.4, 6.0, and 9.6 cycles per degree. AMD, age-related macular degeneration; Central
min thickness, the minimum thickness within a 1 mm diameter of the fovea. Central max thickness, the maximum thickness within a 1 mm
diameter of the fovea; Central mean thickness, average thickness within a 1 mm diameter of the fovea; Average thickness, average thickness at
2 mm nasally; MMSE, Mini Mental State Examination; Semantic fluency score, a semantic fluency (categorical verbal fluency) score obtained
from the number of animals named by the subject in 1 minute; Phonemic fluency score, A phonemic fluency (word fluency) score generated by
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
education (p = 0.05 and p = 0.014, for L and Z, respectively). The significance disappears, however, if we
also control for diet in these analyses, and this is likely
due to “confounding”, as diet is significantly related to
the dependent variable (L or Z) and to AD status.
Macular pigment
Central MP (i.e., at 0.23◦ ) and MP volume were
both significantly lower in the AD group when compared to the control group (see Table 1 and Figs. 1
and 2; p < 0.001 for both). Of note, for MP at 0.23◦ ,
the statistical significance of this relationship persisted
(p = 0.002) after controlling for age, diet, education,
and presence of AMD. This was also true for MP
volume (p = 0.001).
Fig. 1. Boxplots of macular pigment optical density at 0.23◦ for the
Alzheimer’s disease (AD) and control groups.
Visual function
Best corrected visual acuity
BCVA was significantly lower in the AD group when
compared to the control group (see Table 1 and Fig. 3;
p = 0.004). The statistical significance of this relationship persisted (p = 0.028) after controlling for age, but
was attenuated to borderline significance (p = 0.077)
after controlling for MP, age, diet, education, and presence of AMD.
Fig. 2. Boxplots of macular pigment optical density volume for the
Alzheimer’s disease (AD) and control groups.
Serum L and Z concentrations
Serum concentrations of L and Z in the AD group
were significantly lower than serum concentrations of
these carotenoids in the control group (p = 0.036 and
p = 0.01, respectively). The statistical significance of
this relationship persisted after controlling for age and
Contrast sensitivity
CS (at all spatial frequencies measured) was significantly lower in the AD group when compared to the
control group (see Table 1 and Fig. 4). The statistical
significance of this relationship persisted after controlling for MP, age, diet, education, and presence of AMD
(significance ranging from p < 0.001 to 0.018).
Prevalence of AMD was significantly higher in
the AD group when compared to the control group
(Table 1, p = 0.019). However, after controlling for age,
education, MP, and diet, this observed between-group
effect is no longer significant (p = 0.147); as with the
analysis of L and Z reported above, there is a likely con-
the total number of words produced for the each of the letters F, A, and S, in 1 minute; MOT (mean latency), motor screening task measures
the subject’s speed of response; MOT (mean error), motor screening task measures the accuracy of the subject’s pointing at cross targets; VRM
(phase 1), VRM (phase 2), VRM (phase 3), VRM (correct words), VRM delayed stage (correct words), VRM delayed stage (recognition total
correct), VRM delayed stage (recognition total false positive), Verbal Recognition Memory tests which assess immediate and delayed memory
of verbal information under free recall and forced choice recognition conditions; PAL (total errors) and PAL (total errors adjusted), Paired
Associates Learning tests which measure visual memory and new learning of the subjects; PAL (total errors), a sum of the errors made across all
stages; PAL (total errors adjusted), the adjusted score and includes an adjustment made for any stages not reached, allowing it to be comparable
to all subjects even if the task was ended prematurely due to cognitive limitation.
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
Firstly, with regard to our finding of a higher occurrence of AMD in the AD group, we know that AMD
and AD are neurodegenerative disorders that share
several antecedents, which can be classed as sociodemographic, cardiovascular and genetic [19, 33, 34].
For certain, these degenerative disorders are clustered
towards the end of life and are thought to be the result
of cumulative and lifelong oxidative injury (consistent
with the free radical theory of ageng) [35]. Furthermore, AMD and AD are characterized by the formation
of drusen in the retina and senile plaques in the CNS,
respectively [18]. The pathologic changes observed
in these conditions are the result of oxidation [36,
37] and inflammation [38, 39] within their respective
tissues, and their molecular compositions are comparable. With regard to risk factors for AMD and AD, age
is the principal common risk factor, but female sex and
poor socio-economic background are also important
[33, 34]. Also, with regard to cardiovascular risk factors common to AMD and AD, hypertension, tobacco
use, obesity, and dyslipidemia are each associated with
increased risk for developing these conditions [40, 41].
With regard to the genetic risk factors, AD and AMD
also share associations with several genetic polymorphisms that influence molecular pathways important in
the pathogenesis of each of these conditions, including
the complement system, lipid homeostasis, and vascular endothelial function [42–44]. Of note, our finding
of a higher occurrence of AMD in patients with AD
is consistent with previous reports which have shown
that patients with AMD have an elevated risk for AD
[45], and also consistent with observations that cognitive function is reduced amongst sufferers of AMD
In summary, the commonalities between AD and
AMD, including genetic and environmental risk factors, help explain, at least in part, our finding of a
higher occurrence of AMD in the AD group when
compared to controls, and perhaps suggest a role for
a shared perspective for exploring means of preventing or retarding the onset or progression of these
disorders. Indeed, there is consistency across studies
investigating the protective role of antioxidants, which
include the macular carotenoids, for retinal health and
AMD, which had demonstrated a reduced progression
to advanced AMD following supplemental antioxidants [47, 48]. Furthermore, there is good reason to
believe that augmentation of MP may play a role in
the prevention of AMD [41]. Indeed, the rationale
behind this notion is biologically plausible and there
is an emerging and evidence-based consensus that
supplementation with all three macular carotenoids
Fig. 3. Boxplots of best corrected visual acuity for the Alzheimer’s
disease (AD) and control groups.
Fig. 4. Contrast sensitivity curves for the Alzheimer’s disease (AD)
and control groups.
founding effect here. When controlling just for age,
however, the group effect exhibits borderline significance (p = 0.069).
Our study has demonstrated that patients with mild
to moderate AD compared to a control group have 1) a
relative lack of MP; 2) significantly poorer visual function; and 3) higher occurrence of AMD. For the most
part, these findings persist, even after controlling for
confounding variables. We discuss below the implications of these findings, and propose explanations,
where possible, for the observed associations.
J.M. Nolan et al. / Alzheimer’s Disease and Macular Pigment
substantial quantities of L and Z) in the human brain
were present in the occipital and frontal cortices [10].
Of interest, a recent study by Johnson et al. confirmed
the presence of L and Z in several parts of the human
brain including frontal cortex, occipital cortex, temporal cortex, and in large amounts in the cerebellum
In the report by Johnson et al., serum L and Z
concentrations were most consistently related to better cognitive performance in the elderly population
studied (>80 years), including Global Deterioration
Scale, Controlled Oral Word Association Test, Wechsler Adult Intelligence Scale-III Similarities Subtest
and the Behavioral Dyscontrol Scale [12]. Consistent
with the above findings (and suggestive of a beneficial)
role for carotenoids with respect to cognitive function), a positive relationship between MP and several
measures of cognitive function (e.g., MMSE, MoCA,
Prospective Memory Tests, Trail-Making Tasks, and
Choice Reaction Tests) was recently confirmed in a
large sample (n = 4,453 adults ≥50 years) from the
Republic of Ireland [17]. Also, a recent study from the
US has reported positive and significant relationships,
in older people, between MP and global cognition,
verbal learning and fluency, recall, processing speed,
perceptual speed [56].
Finally, our finding that AD subjects have significantly poorer vision when compared to controls
needs to be emphasized. In brief, the AD subjects
had significantly poorer visual function, as reflected in
measures of BCVA and CS, than control subjects, and
the observed differences are clinically meaningful. We
investigated if the poor vision observed in AD patients
when compared to controls was due to the higher prevalence of AMD seen in these patients, and we found that
AMD was not a significant predictor of visual function
(likely due the fact that the AMD observed in these
patients was early stage, and therefore not visually consequential). In other words, our data suggests that the
poor vision observed in AD patients was not due to
their high prevalence of AMD, as AD patients without AMD also had significantly poorer vision when
compared to the control group. This is a novel finding
and supports the view that appropriate strategies should
be put in place to try and protect and enhance visual
function in these vulnerable patients. Of importance,
it has already been shown that enrichment of MP with
macular carotenoid supplementation enhances visual
function in subjects with and without retinal disease
[49, 57–60].
In conclusion, there is an established evidence base
that MP, made up of its constituent carotenoids L, Z
is likely to be the most promising strategy designed
to delay or prevent the onset or progression of AMD
[49, 50].
However, questions remain with respect to advice
given by eye care professionals regarding antioxidant
supplementation in patients with AMD or at risk of
developing this condition, and a lack of clarity persists
around several issues including a daily recommended
intake of each of the macular carotenoids and whether
the observed benefits in AREDS2 will pertain outside
of the context of a clinical trial [51].
It is known that plasma concentrations of L and Z are
lower in AD patients when compared with control subjects, with L concentrations correlating significantly
and inversely with dementia severity [13, 14]. Moreover, a recent publication using the Third National
Health and Nutrition Examination Survey (NHANES
III) database and the NHANES III Linked Mortality
File found that high serum concentrations of lycopene,
L and Z (but not other carotenoids) were associated
with a significantly lower risk of mortality attributable
to AD [52]. These findings have been confirmed in
our current study in that the AD subjects had significantly less (on average) serum concentrations of
L and Z when compared to the control group. It is
important to point out that (as expected) dietary intake
of L and Z (which was also significantly less in the
AD subjects) correlated well with serum concentrations of L and Z in our study (r = 0.572, p < 0.001 and
r = 0.445, p < 0.001), suggesting that the lower circulating serum concentrations of these carotenoids in AD
patients when compared to controls is due (at least in
part) to poor diets in patients with AD.
With the above in mind, our finding that patients
with AD have significantly less MP when compared to
controls (even after controlling for dietary differences)
is all the more provocative, and may reflect a parallel
and relative lack of MP’s constituent carotenoids in
brain tissue. Of interest, it is known that MP correlates with concentrations of the macular carotenoids
in primate brain tissue, [11] and it is therefore tempting to hypothesize that measures of MP (which can
be uniquely performed in vivo [53, 54]) should be
explored as a possible biomarker for concentrations
of these compounds in brain tissue and/or cognitive
function in health and/or disease.
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of individually measured carotenoids in the human
brain was published by Craft et al., who reported that
between 66% and 77% of the carotenoids (including
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and MZ, protects against AMD progression, [61] and
there is a growing body of evidence that MP also plays
a role in prevention of this condition. The presence of L
and Z in brain tissue has also been confirmed, [10] and
brain carotenoid concentrations are positively related
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main finding that AD patients have significantly less
MP and poorer vision when compared to controls merits further investigation, and a clinical trial designed
to investigate the impact of macular carotenoid supplementation with respect to MP, visual function and
cognitive function among AD sufferers is merited. Furthermore, the possibility that measures of MP may have
a role as a non-invasive biomarker of cognitive function
and/or cognitive impairment, or risk thereof, warrants
further study.
We would like to thank the Howard Foundation,
Cambridge, CB22 5LA, United Kingdom for supporting this research. We would like to acknowledge Dr.
Robert Coen from the Mercer’s Institute for Successful Ageing, St. James’s Hospital, Dublin, Ireland for
his assistance and advice with the measurements of
cognitive function. We would like to acknowledge
Cambridge Cognition, UK for guidance with respect to
the assessment of cognitive function. Also, we would
like to thank all the staff at the Waterford Regional
Hospital, Age-Related Care Unit and at the Vision
Research Centre, Waterford Institute of Technology for
assisting this study.
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