Apolipoprotein E (APOE) genotype has dissociable
effects on memory and attentional–executive
network function in Alzheimer’s disease
David A. Wolka,b,c,1, Bradford C. Dickersond,e,f,g, and the Alzheimer’s Disease Neuroimaging Initiative
aDepartment of Neurology,bAlzheimer’s Disease Core Center, andcPenn Memory Center, University of Pennsylvania, Philadelphia, PA 19104; and
dFrontotemporal Dementia Unit,eDepartment of Neurology,fMassachusetts Alzheimer’s Disease Research Center, andgAthinoula A. Martinos Center for
Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02115
Edited by Robert W. Mahley, J. David Gladstone Institutes, San Francisco, CA, and approved April 23, 2010 (received for review February 12, 2010
The ε4 allele of the apolipoprotein E (APOE) gene is the major
genetic risk factor for Alzheimer’s disease (AD), but limited work
has suggested that APOE genotype may modulate disease pheno-
type. Carriers of the ε4 allele have been reported to have greater
medial temporal lobe (MTL) pathology and poorer memory than
noncarriers. Less attention has focused on whether there are do-
mains of cognition and neuroanatomical regions more affected in
noncarriers. Further, a major potential confound of prior in vivo
studies is the possibility of different rates of clinical misdiagnosis
for carriers vs. noncarriers. We compared phenotypic differences in
cognition and topography of regional cortical atrophy of ε4 car-
riers (n = 67) vs. noncarriers (n = 24) with mild AD from the Alz-
heimer’s Disease Neuroimaging Initiative, restricted to those with
a cerebrospinal fluid (CSF) molecular profile consistent with AD.
Between-group comparisons were made for psychometric tests
and morphometric measures of cortical thickness and hippocampal
volume. Carriers displayed significantly greater impairment on
measures of memory retention, whereas noncarriers were more
impaired on tests of working memory, executive control, and lex-
ical access. Consistent with this cognitive dissociation, carriers
exhibited greater MTL atrophy, whereas noncarriers had greater
frontoparietal atrophy. Performance deficits in particular cognitive
domains were associated with disproportionate regional brain at-
rophy within nodes of cortical networks thought to subserve these
cognitive processes. These convergent cognitive and neuroana-
tomic findings in individuals with a CSF molecular profile consis-
tent with AD support the hypothesis that APOE genotype mod-
ulates the clinical phenotype of AD through influence on specific
large-scale brain networks.
cognition|neuroimaging|dementia|cortical thickness|medial temporal
ory deficits accompanied by progressive impairment in several
other cognitive domains, including executive functioning, lan-
guage, visuospatial function, and praxis (1). This presentation
reflects pathologic alterations within critical nodes of the large-
scale neural network subserving episodic memory as well as
alterations within other brain networks (2, 3). Although the
prevailing view of AD as predominantly an episodic memory
disorder is well supported (4), there are many clear examples of
clinical and pathological heterogeneity (5–9). Although much of
this work has focused on atypical focal presentations, such as
visual variant of AD/posterior cortical atrophy (6), progressive
aphasia (7, 10), or the executive variant of AD (5), phenotypic
heterogeneity has been found even in less-selected AD pop-
ulations (8, 9). Despite its potential importance for diagnosis, in-
tervention, disease monitoring and, ultimately, our understanding
of disease pathophysiology, there are surprisingly few data re-
garding potential genetic or environmental factors that may un-
derlie clinical or pathologic heterogeneity in AD.
rototypically, Alzheimer’s disease (AD) presents clinically as
a syndrome involving insidiously progressive episodic mem-
Apolipoprotein E (APOE) is the major genetic risk factor for
AD. This gene on chromosome 19, which codes for a lipid
transport protein, has three major alleles (ε2, ε3, and ε4). Car-
riers of at least one ε4 allele have an increased risk of developing
AD, as well as an associated dose-related decrease in age of
onset (11, 12). The mechanism by which this protein exerts its
modulatory effect on AD remains unclear and may be related,
among other hypotheses, to its function in cell membrane main-
tenance and repair, its effect on amyloid β (Aβ) deposition and
clearance, and/or a potential regulatory role for tau phosphory-
Although APOE clearly affects disease risk, controversy exists
as to whether APOE allelic variants are consistently associated
with phenotypic variants of AD. Autopsy and amyloid imaging
studies have reported greater Aβ plaque deposition in carriers of
the ε4 allele, even after controlling for disease severity (16).
Quantitative neuroimaging investigations have reported greater
medial temporal lobe (MTL) atrophy, particularly involving the
hippocampus, in AD patients who are ε4 carriers vs. noncarriers
(17–21), although this has not been a universal finding (22, 23).
Conflicting results have also been reported from the limited
investigations of cortical anatomy, with some studies reporting
no difference and others reporting more robust regional atrophy
in ε4 carriers (20, 23). Finally, there are a few reports of greater
atrophy in noncarriers either in select regions, such as the frontal
lobe, or in global measures of brain volume (17, 19–21).
Data regarding APOE-related differences in the cognitive phe-
notype of AD have been similarly variable. Perhaps the most
consistent finding is the presence of greater impairment of delayed
recall on episodic memory tasks in ε4 carriers relative to non-
carriers (24–27), although, again, conflicting results have been
reported (17, 18). Findings are inconsistent regarding whether
there are domains of greater cognitive impairment in noncarriers
relative to carriers, with some indication that noncarriers may
display greater difficulty on tasks of attention, executive, or verbal
functions (17, 25, 26).
In addition to the presence of conflicting data in the literature,
there are some important gaps. First, given the limited specificity
of standard diagnostic approaches (28) and the potential for
Data used in the preparation of this article were obtained from the ADNI database (www.
loni.ucla.edu\ADNI). As such, the investigators within the ADNI contributed to the design
and implementation of ADNI and/or provided data but did not participate in analysis or
writing of this report. A complete listing of ADNI investigators is available at www.loni.
Author contributions: D.A.W., B.C.D., and ADNI designed research; D.A.W., B.C.D., and
ADNI performed research; D.A.W. and B.C.D. analyzed data; and D.A.W. and B.C.D. wrote
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
1To whom correspondence should be addressed. E-mail: firstname.lastname@example.org.
This article contains supporting information online at www.pnas.org/lookup/suppl/doi:10.
| June 1, 2010
| vol. 107
| no. 22 www.pnas.org/cgi/doi/10.1073/pnas.1001412107
different rates of misdiagnosis in ε4 carriers vs. noncarriers, it is
possible that some discrepant findings may be explained by the
inclusion of patients with non-AD dementias. New in vivo bio-
markers can be used to increase the likelihood that putative AD
patient samples actually harbor AD neuropathology (29, 30).
Second, although there have been previous investigations of
cognitive and neuroanatomic differences between AD patients
who are APOE ε4 carriers vs. noncarriers, no prior work has
brought these lines of research together to identify an underlying
neuroanatomic basis of these genetically influenced differences
in the cognitive phenotype of AD.
In the present study, we investigated cognitive and neuroana-
tomic phenotypic variability between patients with mild AD who
carry at least one APOE ε4 allele (“carriers”) vs. those who do not
(“noncarriers”). To mitigate against concerns of misdiagnosis, this
group of patients was restricted to those with a cerebrospinal fluid
(CSF) molecular profile consistent with pathological AD. In ad-
dition to exploratory analyses, we used a hypothesis-driven ap-
proach to the measurement ofneuroanatomic differences between
of AD” regions of interest (ROIs) previously defined from a sepa-
rate sample of AD patients (31). We hypothesized that carriers
would express more atrophy in cortical regions that are part of the
episodic memory network, whereas noncarriers would express
more atrophy in cortical regions that are part of networks sub-
serving complex attention and executive function (32).
Demographic and General Clinical Data. Remarkably, despite ε4
carrier status being associated with an earlier age of onset, carriers
and noncarriers did not differ in age [t(89) < 1.0] (Table 1); nor
did the groups differ on global measures of disease severity [Mini-
Mental State Examination (MMSE): t(89) < 1.0; Clinical De-
mentia Rating Scale Sum of Boxes (CDR-SB): t(89) = 1.5, P >
0.1]. Noncarriers were generally more educated than carriers
[t(89) = 2.1, P < 0.05]. Of the carriers, 44 (65.7%) had one ε4
allele, whereas 23 (34.3%) had two. Finally, the t-tau/Aβ1–42ratio
did not differ between the groups [t(89) < 1.0].
Differences in Memory Performance. An interesting profile of
memory performance distinguished the two groups (Fig. 1 and
Table 1). On the first immediate recall trial of the Auditory
Verbal Learning Test (AVLT), noncarriers showed a statistical
trend toward poorer performance than the carriers [F(1, 86) =
3.66, P = 0.06]. However, by the fifth immediate recall trial the
groups did not differ [F(1, 85) < 0.01], suggesting relatively
equivalent overall learning. In stark contrast, 30-min delayed
recall was markedly poorer in the carrier group [F(1, 86) = 6.8,
P = 0.05]. Two measures thought to be particularly specific to
temporo-limbic memory dysfunction, recognition memory (d′)
and memory retention [percent retention = (delayed recall/trial
5 immediate recall) × 100] were also more impaired in the car-
riers [d′: F(1, 86) = 9.3, P < 0.01; percent retention: F(1, 85) =
9.7, P < 0.01].
DifferencesinNonmemoryPerformance.In the nonmemory domains,
there was a general pattern of subtly poorer performance in the
noncarriers, with several measures reaching statistical significance
(Fig. 1 and Table 1). Noncarriers performed less well than carriers
on Trails A [F(1, 86) = 4.6, P < 0.05] and Trails B [F(1, 82) = 7.0,
P < 0.05], measures usually thought to represent visuomotor speed
and executive function (sequencing), respectively. Backward Digit
Span, another test of executive function, was also poorer in the
noncarriers [F(1, 85) = 4.8, P < 0.05]. In addition, noncarriers
displayed poorer naming on the 30-item Boston Naming Test
(BNT) [F(1, 85) = 7.4, P < 0.01.]. None of the other measures
reached statistical significance.
Differences in Regional Cortical Atrophy. For the between-group
ROI analysis, covariates of age and disease severity (CDR-SB)
were applied. All ROI values were converted to z scores on the
basis of morphometric measures of the control cohort in the
Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset.
The carriers displayed reduced cortical thickness in the MTL
Table 1.Demographic and psychometric data of AD patients based on APOE carrier status
Variable APOE ε4 carriers (n = 67)APOE ε4 noncarriers (n = 24)
Gender, n (male/female)
Formal education (yr)
AVLT trial 1 recall
AVLT trial 5 recall
AVLT 5-min delayed recall
AVLT 30-min delayed recall
AVLT percent retention
AVLT recognition (d′)
Digit Span Forward
Digit Span Backward
Trails A (sec)
Trails B (sec)
Category fluency test
2.00 (2.8) *
Values are presented as mean (SD) except where noted. Note that data were missing for four patients for
Trails B, two patients for Digit Symbol and AVLT 5-min delayed recall, and one patient for BNT, Digit Span
Backward, and AVLT trial 5 recall and percent retention.
*P < 0.05.
†P = 0.06.
‡P < 0.01.
Wolk et al.PNAS
| June 1, 2010
| vol. 107
| no. 22
and had smaller hippocampal volume than the noncarriers.
However, only the latter comparison reached statistical signif-
icance [F(1, 65) = 7.1, P < 0.01] (Fig. 2). In contrast, almost all
other ROIs and total mean cortical thickness were reduced in
the noncarriers (Table S1). This difference reached statistical
significance in several regions, including the superior parietal
lobule [F(1, 65) = 4.2, P < 0.05], precuneus [F(1, 65) = 4.7, P <
0.05], and angular gyrus [F(1, 65) = 6.3, P < 0.05]. Additionally,
the superior frontal gyrus [F(1, 65) = 3.5, P = 0.07] and overall
mean cortical thickness [F(1, 65) = 3.8, P = 0.06] approached
In addition to the ROI analysis, an exploratory between-group
comparison was performed across the entire cortical mantle
and midline parietal and dorsolateral frontal regions, along with
lateral temporal regions, were thinner in the noncarrier group.
caudal temporal and occipital regions relative to the noncarrier
group. Note that because this analysis only interrogates thickness
of the cortex, the hippocampus itself is not included.
Regional Cortical Atrophy–Behavioral Relationships. The above anal-
yses suggest that ε4 carrier status modulates both the cognitive and
neuroanatomic phenotype of AD. To better understand how the
cognitive differences relate to the underlying neuroanatomy, a se-
ries of stepwise regressions were performed. In each case the
dependent variable was one of the cognitive measures that sta-
tistically differed between the two groups (AVLT trial 1 recall,
AVLT 30-min delayed recall, AVLT recognition memory, BNT,
Backward Digit Span, Trails A, and Trails B), and the in-
dependent variables were the above ROIs. To avoid the influence
of APOE-genotype group differences driving these correlations,
APOE status was entered first as a covariate in the model, along
with age and years of formal education. In each case, the best
model included one ROI. In the case of tasks performed less well
by the carriers (30-min delayed recall, recognition memory), hip-
pocampus (β = 0.42, P < 0.01) and MTL (β = 0.25, P < 0.05) were
retained in the respective models. In contrast, non-MTL structures
correlated with performance on the cognitive tests in which the
noncarriers performed less well. For BNT, the best model in-
cluded inferior frontal sulcus (β = 0.32, P < 0.01), although there
was also a trend for temporal pole in this model (β = 0.22, P =
0.09). For Trails A, Trails B, and AVLT trial 1 recall, inclusion
of angular gyrus produced the best models (β = −0.38, P < 0.01;
β = −0.46, P < 0.001; and β = 0.38, P < 0.01, respectively). No
ROIs were included in the Backward Digit Span regression.
APOEgenotype seemstomodify notonly therisk forADbutalso
the cognitive and neuroanatomic phenotype of the disease. With
respect to cognition, ε4 carriers in this cohort were impaired to
a greater extent than noncarriers on specific episodic memory
measures usually considered to be dependent on the MTL mem-
ory system. In contrast, noncarriers displayed greater impairment
in cognitive processes requiring sustained attention, working
memory, executive function, and lexical access. The two groups
demonstrated anatomic dissociations consistent with these cog-
nitive differences: ε4 carrier AD patients exhibited more prom-
inent MTL atrophy, whereas noncarriers expressed more robust
atrophy in a broad set of cortical regions, including some that
(B) nonmemory measures, presented as ADNI control-referenced z scores
(Trails A/B and BNT were natural log and square root transformed, re-
spectively). Error bars represent ±SEM;#, P = 0.06, *, P < 0.05, **, P < 0.01 for
Cognitive profile differences of APOE carriers versus noncarriers.
carriers. Between-group comparison of morphometric values for specific
ROIs, including (B) MTL ROIs (rostral medial temporal cortex and hippo-
campus) and (C) isocortical ROIs (angular gyrus and superior frontal gyrus).
Error bars represent ±SEM. Cortical surface inset illustrates localization of
ROIs (A);#, P = 0.07, *, P < 0.05 for ANCOVA models.
Atrophy pattern profile differences of APOE carriers versus non-
which mild AD ε4 carriers demonstrated thinner cortex than noncarriers
(blue) and in which noncarriers demonstrated thinner cortex than carriers
(red-yellow). Map is thresholded at P < 0.1 to illustrate relatively subtle
effects. Bar graphs illustrate group differences in (A) superior frontal gyrus,
(B) angular gyrus, and (D) MTL defined on these maps. The precentral gyrus
(C) is included as a control region to illustrate similarities between groups.
Error bars represent ±SEM.
Exploratory analysis across the entire cerebral cortex of regions in
| www.pnas.org/cgi/doi/10.1073/pnas.1001412107Wolk et al.
Perhaps the most important advance of the present work
relative to prior in vivo studies is that our cohort was restricted
to a relatively large sample of mild AD patients with a CSF
molecular profile consistent with AD based on a previously
established cutoff with high diagnostic accuracy for autopsy-
determined cases of dementia (30). Although the pathologic
diagnosis cannot be confirmed in the present cohort, the in-
clusion of only patients with a CSF t-tau/Aβ1–42in the “AD
range” should significantly mitigate the concern of misdiagnosis
that may be present in samples defined on a purely clinical basis.
For example, a reasonable criticism of prior work demonstrating
poorer memory and greater hippocampal atrophy in ε4 carriers
relative to noncarriers is that the former group is associated
with a greater proportion of patients with true pathologic AD,
whereas the latter group may contain more individuals with non-
AD pathologies, which may be expected to affect memory and
MTL structures less prominently. Restriction of the cohort in
this manner may have excluded some patients with pathological
AD given the imperfect sensitivity of the test (30); however, this
minority of AD patients is unlikely to significantly alter the
present results unless it is postulated that APOE genotype
would have a differential effect on these patients relative to
those with an AD CSF profile.
Modulatory Influence of APOE on Expression of AD. The present
findings echo threads of some of the extant literature. Several
studies have reported that ε4 carriers display poorer episodic
memory (24–27) and smaller hippocampal or other MTL volumes
(17–21, 33) than noncarriers. Within the present CSF-restricted
sample in which carriers and noncarriers were well matched for
age and mild disease severity, we observed similar findings.
It stands to reason that if carriers and noncarriers are indeed
well matched for disease severity, but ε4 carriers have poorer
memory, that noncarriers should display greater impairment in
nonmemory cognitive domains. Although several studies have
not found psychometric measures favoring carriers (18, 20, 27),
a few reports accord well with the present data. For example, van
der Vlies et al. (25) reported remarkably similar findings in which
noncarriers performed more poorly than carriers on an object
naming task and parts A and B of the Trail Making Test. Two
additional reports of poorer scores in noncarriers on measures of
attention/concentration, performance intelligence quotient, and
other verbal tasks, including naming, provide further support for
this differential pattern of cognitive impairment (17, 26).
APOE ε4 noncarriers displayed greater cortical thinning in
frontoparietalregions that form nodes of two interacting networks
“frontoparietal control” system (32, 34). Although these networks
may index partially dissociable cognitive operations, a variety of
working memory and complex attention tasks are associated
with activation in both systems. As would be predicted by such
involvement, noncarriers performed most poorly on tasks that
depend on these processes. Although almost all prior studies ex-
amining the role of APOE genotype on structural imaging alter-
(18) recently reported data from a survey of the entire cortical
mantle that produced anatomic results similar to those of the
present work. Consistent with our findings, they reported greater
dorsal fronto-parietal atrophy in the noncarrier group but did not
sample size. In contrast, another recent study surveying the whole
brain using voxel-based morphometry identified relatively more
prominent MTL atrophy in carriers but did not find areas where
Finally, two older studies of select regions reported evidence of
smaller frontal lobe volumes in noncarriers relative to carriers (19,
21), but again with no psychometric differences, likely owing to
small sample size.
One implication of the present findings is that the clinical
phenotype of AD reflects an amalgamation of relatively selective
regional brain pathology, the distribution of which may be
influenced in part by APOE genotype. In previous work, we
demonstrated that a “signature” set of localized cortical regions
is atrophied consistently across multiple samples of very mild and
mild clinically defined AD patients (31, 36). Although these
regions seem to be affected in a generalizable way across AD
patients, the present work suggests that there is variability in the
degree to which these regions are affected and that one factor
influencing the relative balance of regional atrophy is APOE
genotype. As in other neurodegenerative diseases with hetero-
geneity of clinico-pathologic relationships, such as fronto-
temporal dementia, the cognitive phenotype seems to reflect the
topographic distribution and severity of regional brain pathology
rather than the type of pathology (37). Yet, as demonstrated in
this study and another recent investigation (20), molecular
influences driven at least in part by genetic variants dictate the
degree to which distinct brain systems are affected by a class of
neuropathology. Of course, other genetic and nongenetic factors
may further influence the cognitive profile and topography of
brain involvement in AD, including education, cerebrovascular
disease, and other comorbid medical conditions, and, perhaps,
individual differences in premorbid cognitive capacities.
Differential Effects of APOE on Distinct Memory Processes. Episodic
memory, often thought of as a monolithic process, perhaps best
illustrates this amalgamation in that both groups displayed im-
paired memory but in qualitatively different ways. The ability to
learn from repetition on a supraspan list learning task such as the
AVLT is likely dependent on auditory–verbal working memory,
strategic–control processes for elaborative encoding, and the
transfer of this information into the long-term store (38). Al-
though these processes have all been shown to be impaired in AD
(39, 40), there have been few demonstrations of subgroups of AD
patients with dissociated deficits in these component processes of
memory (41); for example, one recent comprehensive in-
vestigation reported that some AD patients present with more
prominent amnesic deficits on tests of delayed recall and recogni-
deficits (42). In the present study, despite the poorer delayed
memory of ε4 carriers, the noncarriers actually performed less well
a supraspan word list learning task is probably more dependent on
auditory–verbal working memory (“short-term memory”) and
possibly executive–strategic processes that might be used during
encoding rather than specific episodic (“long-term”) memory pro-
cesses.Consistentwiththis notion,impairmentonthismeasure did
not correlate with MTL atrophy but rather was most strongly as-
sociated with atrophy of the angular gyrus in the posterior parietal
cortex/inferior parietal lobule. This localization is congruent with
findings from lesion studies of auditory–verbal short-term memory
impairment (43, 44) and current concepts from functional neuro-
imaging regarding the phonologic store in working memory (45).
In contrast, despite equivalent learning after repetition as
measured by the fifth immediate recall trial, ε4 carriers displayed
a more rapid rate of forgetting over the delay interval. As
expected, delayed memory measures were strongly associated
with MTL structures, the region most affected in carriers. Thus,
although the two genetic subgroups of AD patients both dem-
onstrate memory impairment and actually display similar learn-
ing, their memory deficits are likely due to different underlying
mechanisms, which we believe arise from the differential genetic
effects on the frontoparietal working memory/executive control
system(s) vs. the MTL episodic memory system.
Wolk et al.PNAS
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| vol. 107
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MRI Methodology. The quantitative MRI-based neuroanatomic
analytic approach taken here has both strengths and limitations.
separate sample from the present study and obtained from an
exploratory map across the entire cerebral cortex that identified
regions that were prominently atrophic in mild AD compared
with age-matched controls. As opposed to traditional methods
that use a priori ROIs defined using macroscopic anatomic
landmarks, these “AD-signature” ROIs were defined on the av-
erage cortical surface template from foci of atrophy at the group
level, and these ROIs were then mapped using the surface-based
spherical coordinate registration to new individual subjects. This
is a unique approach that is conservative because it restricts the
analysis to ROIs where the average disease effect is relatively
large; regions where the AD-related atrophy is not as prominent
or where variance is higher are not included in the analysis, po-
tentially leading to false-negative findings. Furthermore, if the
localization of genotype-related atrophy effects is not fully over-
lapping with the disease-signature ROIs, the effects may be
underestimated or missed. Yet effects that are found are likely to
begeneralizable, because theyareidentifiedusingan unbiasedset
of ROIs. Additionally, disease-specific ROIs have the advantage
over traditional landmark-based approaches in that disease pro-
cesses may not respect these boundaries. Secondarily, we used
a more liberal exploratory analysis to survey the entire cerebral
cortex. Although subject to false-positive results due to non-
for the possibility that regionally specific effects may be near to
but not exactly colocalized with a priori ROIs, providing com-
Although most of these points are still theoretical, not having
yet received systematic study, we have shown in two studies that
the generation of spatially localized ROIs from exploratory
analyses in one sample can be powerful in predicting effects in
another sample (36), sometimes detecting effects not obvious
from an exploratory analysis alone (46). Finally, we and others
have demonstrated that traditional volumetric measures of MTL
structures may conflate age-related changes in surface area and
AD-related changes in cortical thickness (measured here) be-
cause these types of changes may be at least partly independent
but both contribute in a nonredundant fashion to volumetric
atrophy of a cortical structure (47, 48) or to genetically related
variance in the volume of the structure (49).
We found that the presence or absence of the APOE ε4 allele
influences the cognitive and anatomic phenotypic expression of
AD in a dissociable manner. The mechanism by which APOE
produces this dissociation is unclear. A variety of lines of evi-
dence support the role of the ε4 allele in facilitating Aβ pro-
duction and deposition, as well as reducing the effectiveness of
neuronal repair mechanisms in the setting of toxic insults (50).
However, more specific effects of ε4 carrier status on memory
and MTL dysfunction may result from Aβ-independent path-
ways. The ε4 isoform is more susceptible to proteolytic cleavage
in neurons leading to toxic fragments that have been demon-
strated to directly contribute to neurodegeneration and are as-
sociated with memory loss in mouse models (51). Associated
mitochondrial dysfunction and impaired glucose utilization may
alter neural recruitment during memory processes in carriers (50,
52). Further, the ε4 allele seems to promote tau phosphorylation
and neurofibrillary tangle (NFT) production (53). Given the
predilection of NFT deposition in MTL structures early in AD it
is, perhaps, not surprising that ε4 carriers would display poorer
memory with greater MTL atrophy than noncarriers.
Less clear are mechanisms that actually support or enhance
cognitive function and cortical integrity in ε4 carriers. Amyloid
imaging and autopsy studies have demonstrated a similar topo-
graphic distribution, but with more extensive and greater Aβ
plaque deposition in isocortical regions, including frontal and
parietal lobes, in carriers relative to noncarriers (23, 54). Thus,
the less-prominent atrophy of these brain regions in ε4 carriers
may be mediated through other mechanisms, perhaps related to
differential response of isocortical neurons to AD pathology or
even developmental influences of APOE genotype, which may
relate to individual differences in cognitive performance (55, 56),
neuroanatomy (57), or brain function (52) at a young age. For
example, several reports in young adults or children have sug-
gested that noncarriers perform less well on measures of execu-
tive functioning and processing speed but better on tests of
memory, foreshadowing the more prominent dissociation in the
context of AD described here (55, 56, 58). These observations
hint that APOE genotype may work in complex dissociable ways
to modulate functional–anatomic brain networks subserving
cognition throughout the lifespan and also the differential vul-
nerability of these networks to AD later in life (59). More work is
clearly needed in this area. Regardless, the foregoing results have
important implications for the early detection and monitoring of
AD, because APOE carrier status seems to exert a strong in-
fluence on the cognitive and anatomic expression of the disease.
Materials and Methods
Participants, psychometric testing, and MRI analytic methods are summarized
briefly here, with details provided in SI Materials and Methods.
We selected patients with a diagnosis of very mild to mild AD (n = 193),
further limited to patients who had CSF testing consistent with AD (t-tau/
Aβ1–42 ≥ 0.39) as previously established in ADNI and an autopsy-based
dataset (30), and then divided into those with at least one APOE ε4 allele
(“carriers”, n = 67) and those without (“noncarriers”, n = 24).
We examined baseline cognitive testing, which included the Rey AVLT, the
test[AnimalsandVegetables], andBNT.On thebasisofpriorworksuggesting
a greater memory deficit in ε4 carriers, we were particularly interested in
examination of the AVLT, which allows for fractionation of different aspects
of episodic memory. The AVLT consists of five learning trials in which a list of
15 words is read and the subject is asked to immediately recall as many items
as possible. After an interference list of 15 novel words is read and recalled,
subjects are then asked to recall words from the initial list (5-min delayed
recall). A 30-min delayed recall trial and recognition test follow. For the
recognition test, subjects are presented with a list of the 15 studied words
and 15 nonstudied foils and are asked to circle all words previously studied.
To account for false alarms (FA) to nonstudied items, we calculated a mea-
sure of discriminability, d-prime (d′), in a standard fashion based on classic
signal detection theory (60). Because d′ is undefined when either proportion
is 0 or 1, we used standard formulas to convert these values: Hits = (no. of
hits + 0.5)/(no. of studied items + 1) and FA = (no. of FA + 0.5)/(no. of un-
studied items + 1).
T1-weighted MRI data were analyzed using a cortical surface-based re-
construction method to generate measures of cortical thickness, which were
then analyzed using two complementary approaches. First we examined
group differences in hippocampal volume and thickness of ROIs previously
determined to be reliably associated with AD, constituting the “cortical sig-
nature” of AD (31, 36). Unlike most ROI analyses, these regions were defined
in a data-driven manner on the basis of analysis of several datasets, as op-
posed to being determined strictly by anatomic boundaries. These ROIs in-
clude medial temporal cortex, inferior temporal gyrus, temporal pole,
angular gyrus, supramarginal gyrus, superior parietal lobule, precuneus, su-
perior frontal gyrus, and inferior frontal sulcus. In addition to the ROI ap-
proach, an exploratory analysis across the entire cortical mantle was pursued.
Statistical analyses were performed in a standard fashion using SPSS, using
analysis of covariance (ANCOVA) with age, years of formal education, and
CDR-SB as covariates. Stepwise linear regression analyses were performed by
entering age, education, and group status (carrier, noncarrier) into the
models with anatomic ROIs as independent variables. Statistical analysis of
the whole-cortex comparison was performed as described previously using
a general linear model (31, 36).
ACKNOWLEDGMENTS. This work was primarily funded by the ADNI
(Principal Investigator: Michael Weiner; National Institutes of Health Grant
U01 AG024904). ADNI is funded by the National Institute on Aging (NIA),
National Institute of Biomedical Imaging and Bioengineering, and the
| www.pnas.org/cgi/doi/10.1073/pnas.1001412107Wolk et al.
Foundation for the National Institutes of Health, through generous Download full-text
contributions from the following companies and organizations: Pfizer Inc.,
Wyeth Research, Bristol-Myers Squibb, Eli Lilly and Company, GlaxoSmith-
Kline, Merck & Co. Inc., AstraZeneca AB, Novartis Pharmaceuticals Corpora-
tion, the Alzheimer’s Association, Eisai Global Clinical Development, Elan
Corporation plc, Forest Laboratories, and the Institute for the Study of Ag-
ing, with participation from the US Food and Drug Administration. The
grantee organization is the Northern California Institute for Research and
Education, and the study is coordinated by the Alzheimer’s Disease Cooper-
ative Study at the University of California, San Diego. This analysis was also
supported by NIA Grants R01-AG29411, R21-AG29840, P50-AG005134, K23-
AG028018, and P30AG010124 and the Alzheimer’s Association.
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Wolk et al.PNAS
| June 1, 2010
| vol. 107
| no. 22