Mapping the effect of APOE epsilon4 on gray matter loss in Alzheimer's disease in vivo.
ABSTRACT Previous studies suggest that in Alzheimer's disease (AD) the Apolipoprotein E (APOE) epsilon4 allele is associated with greater vulnerability of medial temporal lobe structures. However, less is known about its effect on the whole cortical mantle. Here we aimed to identify APOE-related patterns of cortical atrophy in AD using an advanced computational anatomy technique. We studied 15 AD patients carriers (epsilon4+, age: 72+/-10 SD years, MMSE: 20+/-3 SD) and 14 non-carriers (epsilon4-, age: 69+/-9, MMSE: 20+/-5) of the epsilon4 allele and compared them to 29 age-and-sex matched controls (age: 70+/-9, MMSE: 28+/-1). Each subject underwent a clinical evaluation, a neuropsychological battery, and high-resolution MRI. UCLA's cortical pattern matching technique was used to identify regions of local cortical atrophy. epsilon4+ and epsilon4- patients showed similar performance on neuropsychological tests (p>.05, t-test). Diffuse cortical atrophy was detected for both epsilon4+ (p=.0001, permutation test) and epsilon4- patients (p=.0001, permutation test) relative to controls, and overall gray matter loss was about 15% in each patients group. Differences in gray matter loss between carriers and non-carriers mapped to the temporal cortex and right occipital pole (20% greater loss in carriers) and to the posterior cingulate, left orbitofrontal and dorsal fronto-parietal cortex (5-15% greater loss in non-carriers). APOE effect in AD was not significant (p>.74, ANOVA), but a significant APOE by region (temporal vs fronto-parietal cortex) interaction was detected (p=.002, ANOVA), in both early and late-onset patients (p<.05, ANOVA). We conclude that the epsilon4 allele modulates disease phenotype in AD, being associated with a pattern of differential temporal and fronto-parietal vulnerability.
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ABSTRACT: Objectives To investigate whether APOE ε4 carriers have higher hippocampal atrophy rates than non-carriers in Alzheimer's disease (AD), mild cognitive impairment (MCI) and controls, and if so, whether higher hippocampal atrophy rates are still observed after adjusting for concurrent whole-brain atrophy rates. Methods MRI scans from all available visits in ADNI (148 AD, 307 MCI, 167 controls) were used. MCI subjects were divided into “progressors” (MCI-P) if diagnosed with AD within 36 months or “stable” (MCI-S) if a diagnosis of MCI was maintained. A joint multi-level mixed-effect linear regression model was used to analyse the effect of ε4 carrier-status on hippocampal and whole-brain atrophy rates, adjusting for age, gender, MMSE and brain-to-intracranial volume ratio. The difference in hippocampal rates between ε4 carriers and non-carriers after adjustment for concurrent whole-brain atrophy rate was then calculated. Results Mean adjusted hippocampal atrophy rates in ε4 carriers were significantly higher in AD, MCI-P and MCI-S (p≤0.011, all tests) compared with ε4 non-carriers. After adjustment for whole-brain atrophy rate, the difference in mean adjusted hippocampal atrophy rate between ε4 carriers and non-carriers was reduced but remained statistically significant in AD and MCI-P. Conclusions These results suggest that the APOE ε4 allele drives atrophy to the medial-temporal lobe region in AD.PLoS ONE 05/2014; · 3.53 Impact Factor
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ABSTRACT: Purpose To determine the effect of the apolipoprotein E (APOE) genotype on atrophy rates of specific brain gray matter regions hypothesized to be key components of cognitive networks disrupted in Alzheimer disease. Materials and Methods The Alzheimer's Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All subjects and their legal representatives gave written informed consent prior to data collection. The authors analyzed data from 237 subjects (mean age, 79.9 years; 40% female) with mild cognitive impairment (MCI) in the ADNI database and assessed the effect of the APOE ε4 and ε2 alleles on regional brain atrophy rates over a 12-48-month period. Brain regions were selected a priori: 15 experimental and five control regions were included. Regional atrophy rates were derived by using a fully automated algorithm applied to T1-weighted magnetic resonance (MR) imaging data. Analysis consisted of mixed-effects linear regression with repeated measures; results were adjusted for multiple testing with Bonferroni correction. Results Thirteen of 15 experimental regions showed a significant effect of ε4 for higher atrophy rates (P < .001 for all). Cohen d values ranged from 0.26 to 0.42, with the largest effects seen in the amygdalae and hippocampi. The transverse temporal cortex showed a trend (P = .02, but did not survive Bonferroni correction) for a protective effect (Cohen d value = 0.15) of ε2. No control region showed an APOE effect. Conclusion The APOE ε4 allele is associated with accelerated rates of atrophy in 13 distinct brain regions in limbic and neocortical areas. This suggests the possibility of a genotype-specific network of related brain regions that undergo faster atrophy in MCI and potentially contribute to cognitive decline. © RSNA, 2014 Online supplemental material is available for this article.Radiology 12/2013; · 6.34 Impact Factor
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ABSTRACT: Atrophy of the hippocampus and surrounding temporal regions occurs in Alzheimer's disease (AD). APOE ε4, the major genetic risk factor for late-onset AD, has been associated with smaller volume in these regions before amyloidosis can be detected by AD biomarkers. To examine APOE ε4 effects in relation to aging, we performed a longitudinal magnetic resonance imaging study involving cognitively normal adults (25 APOE ε4 carriers and 31 ε3 homozygotes), initially aged 51-75 years. We used growth curve analyses, which can provide information about APOE ε4-related differences initially and later in life. Hippocampal volume was the primary outcome; nearby medial temporal regions were secondary outcomes. Brain-derived neurotrophic factor, val66met was a secondary covariate. APOE ε4 carriers had significantly smaller initial hippocampal volumes than ε3 homozygotes. Rate of hippocampal atrophy was not greater in the APOE ε4 group, although age-related atrophy was detected in the overall sample. The findings add to the growing evidence that effects of APOE ε4 on hippocampal size begin early in life, underscoring the importance of early interventions to increase reserve.Neurobiology of aging. 05/2014;
Mapping the effect of APOE ε4 on gray matter loss in Alzheimer's disease in vivo
M. Pievania,b, P.E. Rasserc,d, S. Galluzzia, L. Benussie, R. Ghidonie, F. Sabattolia, M. Bonettif, G. Binettie,
P.M. Thompsong, G.B. Frisonia,h,i,⁎
aLENITEM Laboratory of Epidemiology, Neuroimaging and Telemedicine, IRCCS Centro San Giovanni di Dio - FBF, Brescia, Italy
bNeuroimaging Research Unit, Scientific Institute and University Ospedale San Raffaele, Milan, Italy
cSchizophrenia Research Institute, Sydney, Australia
dPriority Centre for Brain and Mental Health Research and School of Design, Communication and I.T., University of Newcastle, Newcastle, Australia
eLaboratory of Neurobiology, IRCCS Centro San Giovanni di Dio - FBF, Brescia, Italy
fService of Neuroradiology, Istituto Clinico Citta' di Brescia, Brescia, Italy
gLaboratory of Neuroimaging, Department of Neurology, UCLA School of Medicine, Los Angeles, CA, USA
hPsychogeriatric Ward, IRCCS Centro San Giovanni di Dio, FBF, Brescia, Italy
iA.Fa.R. Associazione Fatebenefratelli per la Ricerca, Roma, Italy
a b s t r a c ta r t i c l ei n f o
Received 8 October 2008
Revised 12 December 2008
Accepted 7 January 2009
Available online 21 January 2009
Previous studies suggest that in Alzheimer's disease (AD) the Apolipoprotein E (APOE) ε4 allele is associated
with greater vulnerability of medial temporal lobe structures. However, less is known about its effect on the
whole cortical mantle. Here we aimed to identify APOE-related patterns of cortical atrophy in AD using an
advanced computational anatomy technique. We studied 15 AD patients carriers (ε4+, age: 72±10 SD years,
MMSE: 20±3 SD) and 14 non-carriers (ε4−, age: 69±9, MMSE: 20±5) of the ε4 allele and compared them to
29 age-and-sex matched controls (age: 70±9, MMSE: 28±1). Each subject underwent a clinical evaluation, a
neuropsychological battery, and high-resolution MRI. UCLA's cortical pattern matching technique was used
to identify regions of local cortical atrophy. ε4+ and ε4− patients showed similar performance on
neuropsychological tests (pN.05, t-test). Diffuse cortical atrophy was detected for both ε4+ (p=.0001, per-
mutation test) and ε4− patients (p=.0001, permutation test) relative to controls, and overall gray matter loss
was about 15% in each patients group. Differences in gray matter loss between carriers and non-carriers
mapped to the temporal cortex and right occipital pole (20% greater loss in carriers) and to the posterior
cingulate, left orbitofrontal and dorsal fronto-parietal cortex (5–15% greater loss in non-carriers). APOE effect
in AD was not significant (pN.74, ANOVA), but a significant APOE by region (temporal vs fronto-parietal
cortex) interaction was detected (p=.002, ANOVA), in both early and late-onset patients (pb.05, ANOVA). We
conclude that the ε4 allele modulates disease phenotype in AD, being associated with a pattern of differential
temporal and fronto-parietal vulnerability.
© 2009 Elsevier Inc. All rights reserved.
Alzheimer's disease (AD) is a clinically heterogeneous disease,
neuropathologically characterized by the accumulation of beta-
amyloid plaques (Abeta) and neurofibrillary tangles (NFT) in the
brain (Braak and Braak,1991; Delacourte et al.,1999; Price and Morris,
1999; Thal et al., 2002; Haroutunian et al., 1999; Haroutunian et al.,
1998). Multiple genes and environmental factors are believed to be
involved in the pathogenesis and development of the disorder,
through a complex interplay still largely unknown. To date the
major genetic risk factor known for AD is the ε4 allele of the
Apolipoprotein E (APOE) gene, that is present with a higher frequency
in AD subjects than in the normal population (Strittmatter et al.,1993;
Poirier et al., 1993; Corder et al., 1993; Tang et al., 1998; Kukull et al.,
2002; Saunders et al., 2000), and lowers the mean age of onset of the
disease in a dose-dependent fashion (Poirier et al.,1993; Blacker et al.,
1997; Meyer et al., 1998; Goldstein et al., 2001).
ApoE, the protein coded by the APOE gene, is a lipid transport
protein implicated in maintenance and repair of neuronal cells
(Mahley, 1988), and current in vitro and animal model data strongly
suggest that the ε4 allele is less efficient than other isoforms in these
functions,through mechanisms that involve neuronal growth(Nathan
et al.,1994), synaptic remodeling (Buttini et al., 2002) and cholinergic
function (Buttini et al., 2002). The findings of faster brain atrophy rate
(Chen et al., 2007; Moffat et al., 2000) and reduced hippocampal
NeuroImage 45 (2009) 1090–1098
⁎ Corresponding author. Laboratory of Epidemiology, Neuroimaging and Telemedi-
cine, IRCCS Centro San Giovanni di Dio - FBF, The National Centre for Research and Care
of Alzheimer's and Mental Diseases, via Pilastroni 4, 25125 Brescia, Italy. Fax: +39 02
E-mail address: email@example.com (G.B. Frisoni).
URL: http://www.irccs-fatebenefratelli.it (G.B. Frisoni).
1053-8119/$ – see front matter © 2009 Elsevier Inc. All rights reserved.
Contents lists available at ScienceDirect
journal homepage: www.elsevier.com/locate/ynimg
volumes in healthy APOE ε4 carriers (Burggren et al., 2008; Plassman
et al.,1997) seem to provide some invivo evidence to the hypothesis of
a pathogenic role of this allele in AD.
Less clear is whether the APOE ε4 allele has a role in modulating
the expression of the disease. Post-mortem studies reported a greater
accumulation of AD pathological hallmarks in the neocortex of
patients carrying the ε4 allele than those with no ε4 allele (Polvikoski
et al., 1995; Tiraboschi et al., 2004; Nagy et al., 1995). In vivo data
however agree only partially with these findings. Indeed, they
reported greater atrophy in carriers in specific regions of the brain,
namely in the hippocampus, entorhinal cortex, and temporal pole
(Hashimoto et al., 2001; Geroldi et al., 1999; Juottonen et al., 1998;
Lehtovirta et al., 1995). Conversely, frontal (Geroldi et al., 1999) and
whole brain (Hashimoto et al., 2001; Yasuda et al., 1998) volumes
seem to be relatively preserved in carriers than non-carriers. These
findings, which seem to suggest a region-specific effect of the ε4 allele
on brain atrophy rather than an overall greater disease severity in
carriers (Hashimoto et al., 2001), are not conclusive (Lehtovirta et al.,
1995; Jack et al.,1998) and are limited by the small number of studies
Here we aim to resolve discordances in previous MRI studies by
investigating APOE-related patterns of atrophy over the whole cortex.
Compared with prior studies, which were based on manually outlined
regions of interest, here we used a recently developed semi-
automated MRI analysis technique (Thompson et al., 2004) able to
analyze the whole cortical mantle at thousands of homologous
cortical points. We hypothesized that patterns of atrophy in AD
patients would differ according to APOE genotype, with carriers
showing greater involvement of the temporal lobe and non-carriers in
the remainder of the cortex.
Participants and assessment
Subjects and genetic analysis
Subjects were recruited among outpatients seen at the IRCCS
Centro San Giovanni di Dio Fatebenefratelli (National Center for
Alzheimer's Disease), in Brescia, Italy, between November 2002 and
August 2005. Patients were enrolled in a study on neurodegenerative
dementias aimed at detecting in vivo structural brain changes in
various diseases, including Alzheimer's disease, frontotemporal
dementia, Parkinson's disease, and dementia with Lewy bodies.
All patients underwent a standardized protocol including clinical,
physical, neurological and neuropsychological evaluations. Each
subject underwent MRI scan and laboratory exams, comprising
complete blood count, chemistry profile, thyroid function, B12 and
folic acid, and EKG. History was taken with a structured interview
from patients' relatives (usually spouses or children), and was focused
on those symptoms that might help in the differential diagnosis of the
dementias (hallucinations, gait, language, and behavioural distur-
bances). Physical and neurologic examinations were performed by a
geriatrician and a neurologist. Neuropsychological assessments were
performed by a psychologist and included the evaluation of global
cognitive status by Mini Mental State Examination (MMSE; Folstein
et al., 1975) and a neuropsychological battery assessing: verbal and
non-verbalmemory withRey's word list immediateanddelayed recall
tests (Carlesimo et al., 1996) and Rey figure delayed recall test
(Caffarra et al., 2002); attention and executive functions with the Trail
Making Test (Reitan, 1958; Amodio et al., 2002); language with the
Phonological and Semantic fluency (Novelli et al.,1986) and Token (De
Renzi and Vignolo,1962; Spinnlerand Tognoni,1987) tests; and visuo-
spatialabilitieswiththeReyfigurecopy(Caffarraet al.,2002). Severity
of dementia was measured by the Clinical Dementia Rating score
(Hughes et al., 1982).
GenomicDNAwas extracted fromwhole-blood samples of subjects
according to standard procedures. APOE genotyping was carried out
by PCR amplification and HhaI restriction enzyme digestion. The
genotype was resolved on 4% Metaphor Gel (BioSpa, Italy) and
visualized by ethidium bromide staining (Hixson and Vernier, 1990).
Twenty-nine patients were diagnosed with AD according to the
NINCDS criteria (McKhannet al.,1984) and wereincluded in the study.
Subjects were divided into two groups based on the presence (ε4+,
n=15) or absence of the ε4 allele (ε4−, n=14). All the carriers were
heterozygous (ε3ε4) for the ε4 allele whereas non-carriers were
homozygous for the ε3 allele (ε3ε3) except for one subject who
carried one ε2 allele.
A group of twenty-nine healthy persons was selected for
comparisons with patients from those enrolled in a study on normal
brain structure with MRI (ArchNor, Normative Archive of Structural
Brain Magnetic Resonance Imaging), as described in detail elsewhere
(Riello et al., 2005). Subjects were outpatients of the Neuroradiology
Units of the Città di Brescia Hospital in Brescia, undergoing brain MR
scan for reasons other than memory disturbance, cognitive impair-
ment, degenerative diseases, or head trauma, and whose MR scan was
negative. In detail, clinical exclusion criteria were: MR scan for
memory problems or cognitive impairment, MR scan for clinical
suspicion of neuro-degenerative diseases (Parkinson's disease, pro-
gressive supranuclear palsy, Huntington's disease, multiple system
atrophy, etc.), patient undergoing MR for suspected stroke, history of
transient ischemic attack or stroke, head trauma, alcohol and
substance abuse, cortico-steroid therapy, and loss of weight greater
than 5 kg in the last 6 months, and cognitive impairment on
neuropsychological testing. Radiological exclusion criteria included:
brain mass, white matterhyperintensitieswith signs and symptoms of
multiple sclerosis, aneurysm larger than 10 mm, arteriovenous
malformation, malformations of the central nervous system, enlarged
cisterna magna, meningioma, severe cerebrovascular disease, severe
atrophy, and large arachnoid cysts. Each subject underwent multi-
dimensional assessment including clinical, neurological, and neurop-
sychological evaluation. Controls were matched 1:1 to AD patients
according to age and sex.
Written informed consensus was obtained by all the subjects. No
compensation was provided for study participation. The local ethics
committee approved the study.
MR images wereacquired at the Neuroradiology Unitof the Città di
Brescia Hospital in Brescia with a Philips Gyroscan 1.0 T scanner. The
acquisition protocol included T1-weighted and FLAIR sequences.
High-resolution gradient echo T1-weighted sagittal 3D sequences
were acquired using the following parameters: TR=20 ms, TE=5 ms,
flip angle=30°, field of view=220 mm, acquisition matrix=256×256
and slice thickness=1.3 mm. Axial dual echo FLAIR sequences were
acquired as follows: TR=5000 ms, TE=100 ms, flip angle=90°, field of
view=230 mm, acquisition matrix=256×256, slice thickness=5 mm.
T1-weighted images were usedforcortical graymatteranalyses, FLAIR
sequences to assess subcortical cerebrovascular disease with the age-
related white matter changes scale (Wahlund et al., 2001, total score
ranging between 0 and 30).
Cortical gray matter was studied using the cortical pattern
matching technique developed at the Laboratory of Neuroimaging
(LONI) of the University of California at Los Angeles (Thompson et al.,
The 3D images were reoriented along the AC-PC line and voxels
below the cerebellumwere removed with the MRIcro software (www.
psychology.nottingham.ac.uk//cr1/mricro.html). The anterior com-
missure was manually set as the origin of the spatial coordinates for
M. Pievani et al. / NeuroImage 45 (2009) 1090–1098
an anatomical normalization algorithm implemented as part of the
Statistical Parametric Mapping (SPM99) software package (www.fil.
ion.ucl.ac.uk/spm). A 12-parameter affine transformation was used to
normalize each image to a customized template in stereotaxic space,
created from the MRI scans of the first 40 consecutively enrolled
controls of the ArchNor project.
Cortical gray matter mapping
Individual brain masks for each hemisphere were extracted from
normalized images with the automatic method EMS (expectation
maximization segmentation; www.medicalimagecomputing.com/
EMS) (Van Leemput et al., 1999a,b), visually inspected, and manually
corrected with DISPLAY, a three-dimensional visualization program
that enables simultaneous viewing of sagittal, coronal and axial slices
of the brain (http://www.bic.mni.mcgill.ca/software/Display/Display.
html), and allows the manual correction of errors between brain and
non-brain tissue. The resulting masks were applied to normalized
images to obtain ‘skull-stripped’ images of each hemisphere. A 3D
model of hemispherical cortical surfaces was automatically extracted
using intensity information (MacDonald et al., 1994). Normalized
images were segmented into gray matter (GM), white matter and
cerebrospinal fluid using an algorithm that employs partial volume
correction and bias field correction (Shattuck et al., 2001).
Sulcal lines were traced by a single tracer (MP) on the cortical
surfaces according to a previously validated anatomical delineation
http://www.loni.ucla.edu/∼esowell/new_sulcvar.html). For each sub-
ject, 17 sulci were manually outlined on the lateral surface of each
brain hemisphere, and a set of 12 sulci were traced on the medial
surface; additional 3D lines were drawn to outline interhemispheric
gyral limits. The reliability of manual outlining was assessed prior to
experimental subject tracing with a standard protocol requiring the
same rater to trace all lateral and medial sulci of 6 test brains (Sowell
et al., 2002). At the end of the reliability phase, the mean 3D difference
of the tracer from the gold standard was b3 mm everywhere for the
medial sulci and b4.5 mm everywhere for the lateral sulci.
Sulcal curves and cortical surfaces were flattened and averaged
across subjects to create a population specific template based on all
subjects in the study (Thompson et al., 2000). Averaged sulci were
then used as landmarks to warp each subject's anatomy into the
template. The same deformation was applied to the segmented
images, thus allowing measurement of GM at thousands of homo-
logous cortical locations. Gray matter density (GMD) was computed at
each cortical point as the proportion of GM tissue classified as GM in a
sphere centered at that point, with a radius of 15 mm, and then
averaged within each group to obtain the GMD mean. All morpho-
logical measurements were performed without knowledge of
A map of the average percentage GM reduction was created for
each AD patient group (ε4+ and ε4−) computing the ratio at each
cortical point between the mean GMD value at that point in the
patient group and the GMD mean of the controls. This ratio allows
visualization of the relative deficit in GM of APOE groups as a
proportion, or percentage, of the normal values seen in healthy
controls. Differences in severity of GM reduction between ε4 carriers
and non-carriers were assessed by computing at each cortical point,
the absolute difference between percentage GM reduction in ε4+ and
ε4−. The resulting map shows the percentage differences between
Gray matter loss in the Brodmann areas.
area (BA) atlas (Rasser et al., 2004; Rasser et al., 2005) was applied to
the left and right hemisphere average models. Briefly, this involved
the extraction of a three-dimensional model of the right cerebral
hemisphere (MacDonald et al., 1994) of the Colin27 single-subject
average brain MRI template (Holmes et al.,1998) followed by labeling
with BA as delineated bythe Caretsoftwarepackage(http://brainmap.
wustl.edu/caret) (Van Essen et al., 2001; Van Essen, 2002). BAs were
then deformed to the average right and left hemisphere templates
using cortical pattern matching, followed by the tabulation of each
subject's average gray matter loss in each BA.
A deformable Brodmann
Cortical pattern matching analyses were carried out in two steps,
first comparing each patient group (APOE ε4+ and APOE ε4−) with
controls and then comparing ε4+ patients with ε4− patients. For the
first set of comparisons, we ran a regression at each cortical point
between GMD and diagnosis. For the second comparison, we ran a
regression entering percentage GM deficits and APOE (ε4+ and ε4−) as
binary variables. The p-values representing the significance of the
variable effect (diagnosis, APOE) were mapped onto the whole cortex,
after setting a significance threshold of p=.05. Overall p-values for the
uncorrected statistical maps were computed by running permutation
tests. This test computes the chance of the observed pattern occurring
by accident by running n=10,000 permutations of the variables of
interest (diagnosis and APOE) at a threshold of p=.01 (Thompson
et al., 2003).
In order to investigate the hypothesis of a region-specific effect of
APOE on brain atrophy, we defined two regions on the BA atlas: (1) the
temporal cortex, including the medial and lateral temporal lobes
(superior, middle and inferior temporal gyrus, entorhinal, perirhinal
and presubicular cortex, anterior temporal pole, and the fusiform
gyrus), (2) the frontal and parietal neocortex (dorsolateral frontal and
parietal cortex, orbitofrontal and subgenual cortex, anterior and
posterior cingulate, and retrosplenial cortex; Fig.1). The main effect of
APOE and cortical region on brain atrophy was investigated using an
Fig.1. Definition of the two regions-of-interest used to test APOE regional effect, delineated on BA atlas (Rasser et al., 2004; Rasser et al., 2005): the temporal cortex (blue colour) and
the fronto-parietal neocortex (green colour). See text for details.
M. Pievani et al. / NeuroImage 45 (2009) 1090–1098
analysis of variance (ANOVA) model, where APOE (ε4+ vs ε4−) was the
between-subject factor, region (temporal vs fronto-patietal cortex)
was the within-subject factor, and percentage GM reduction was the
In order to assess whether age at onset of the disease had an
impact on APOE effect, the analyses were repeated separately in early
(b65 years, n=14) and late-onset (N65 years, n=15) patients, by
comparing younger and older patients with their age-matched
Sociodemographic, clinical and neuropsychological data
Table 1 shows that APOE ε4 carriers and non-carrier patients were
comparable in age (p=.358 on t-test), duration of dementia (p=.519),
cerebrovascular burden (p=.203), and severity of the disease (p=.287
on chi-square), CDR scores being indicative of mild dementia in the
most of the patients (Table 1). The ε4+ group had a greater proportion
of women than ε4− (p=.009) and a lower educational level (p=.033;
Table 1). Because some previous studies showed gender differences in
gray matter volumes of healthy and AD subjects (Luders et al., 2006;
Sowell et al., 2007; Juottonen et al., 1998), we replicated the analyses
considering only women in order to ensure that these differences did
not influence our results.
Controls were similar to ε4+ and ε4− patients with regard to age
(pN.457 on t-test) and sex (pN.114 on chi-square test, Table 1). Years of
education were comparable to that of ε4 non-carriers (p=.572) and
higher than that of ε4 carriers (pb.001, Table 1). Global cognition was
lower in patients compared with controls on the MMSE test (pb.001,
Table 1) and in all the domains investigated by the neuropsychological
battery (pb.038, Table 2). The degree of impairment was similar in ε4+
and ε4− patients on both MMSE scores (p=.862) and neuropsycho-
logical tests (pN.063; Table 2).
Carriers and non-carriers vs controls
Both ε4+ and ε4− showed widespread cortical atrophy, involving
most of the neocortex and sparing only the somatosensory and motor
areas, the anteriorcingulate gyrus, and the medial orbitofrontal cortex
(thresholded at pb.01 uncorrected, Fig. 2, top panel). In ε4+ patients,
regions of significant atrophy mapped to the whole left and right
temporal lobes, and to the occipital lobes, retrosplenial and posterior
cingulate area (Fig. 2, top left panel). The same regions were affected in
the ε4− group, but involvement of the temporal lobe was less selective
and conversely fronto-parietal atrophy appeared more diffuse (Fig. 2,
top right panel). Patterns of atrophy in the medial wall involved the
posterior cingulate and retrosplenial cortex in both groups. The
comparisons between patients and controls were highly significant
after correction for multiple comparisons (p=.0001 for both ε4+ vs
controls and ε4− vs controls, permutation test).
Percentage maps showed that overall severity of atrophy was
similar, with ε4+ and ε4− showing an average GM reduction of 15% vs
14% in the left, and 16% vs 17% in the right hemisphere respectively
(pN.80 on t-test). Regionally, the most severe GM reductions (N20%)
in carriers were in the entorhinal cortex, anterior temporal pole,
superior and middle temporal gyrus, and in the ventral and dorsal
occipital lobe bilaterally (Fig. 2, bottom left panel). Non-carriers were
more severely affected bilaterally in the superior and middle frontal
gyri, superior temporal gyrus, retrosplenial cortex, posterior cingulate
and orbitofrontal medial right cortex (Fig. 2, bottom right panel).
Carriers vs non-carriers
Direct comparisons between maps of percentage reduction in the
ε4+ and ε4− groups revealed APOE-associated regions of atrophy.
These analyses detected greater involvement of the medial and lateral
temporal lobes, andof the rightoccipital pole (pb.01, uncorrected; Fig.
3A, left) in the ε4+ group. The opposite effect (greater atrophy in non-
carriers than carriers) was detected in the posterior cingulate and left
lateral orbitofrontal cortex (pb.01 uncorrected; Fig. 3A, right), and in
the right dorsolateral cortex (pb.05 uncorrected). Differences sig-
nificant at the uncorrected threshold of pb.01 corresponded to
approximately 20% greater GM loss in the ε4 carriers than non-
carriers (Fig. 3B, left), whereas the opposite effect amounted to about
5–15% greater GM loss for non-carriers than carriers (Fig. 3B, right).
Statistical maps were not significant after controlling for multiple
comparisons (pN.33; permutation test).
Analyses in Brodmann areas
GM loss in the temporal cortex region defined on BAs was 19% in
carries and 16% in non-carriers relative to controls. In the fronto-
parietal cortex, carriers exhibited a reduction of 14.5% vs 16% in non-
carriers (Fig. 3C). The ANOVA model showed a significant effect of
region (p=.001) in the whole sample but not of APOE (p=.740) on GM
Socio-demographic, clinical and volumetric data of Alzheimer's disease patient carriers
(ɛ4+) and non carriers (ɛ4−) of the APOE ɛ4 allele and age-matched controls
ControlsAlzheimer's disease patients
Mini-mental state exam
Clinical dementia rating
Disease duration (years)
White matter disease§
Values denote mean (standard deviation) or number (percentage). p denotes
significance of differences between ɛ4+ and ɛ4− on χ2test for dichotomous variables,
and Student t-test or Mann–Whitney U-test – depending on the samples distribution
– for continuous variables. ɛ4+ and ɛ4− patients differed from controls in their MMSE
score (pb.001 on t-test). Educational level was lower in ɛ4+ that in controls (pb.001
on Mann–Whitney). There were no differences between patients and controls
relatively to sex (pN.103 on χ2test) and white matter disease (pN.135 on t-test).
§On the age-related white matter changes scale (Wahlund et al., 2001).
Neuropsychological features of Alzheimer's disease patients carrying (ɛ4+) and non
carrying (ɛ4−) the APOE ɛ4 allele and control subjects
ControlsAlzheimer's disease patients
Rey list immediate recall
Rey list delayed recall
Rey figure recall
Rey figure copy36 (1) 13 (14)10 (9) .564
Attention and executive functions
Trail making test A
Trail making test B
Trail making test B–A
Test scores are age-, sex-, and education-adjusted.
Values denote mean (standard deviation). p denotes significance on Student t-test
between ɛ4 carriers and non-carriers. ɛ4+ and ɛ4− patients performed significantly
poorer than controls in memory (pb.001), language (pb.002 and pb.037), visuo-spatial
abilities (pb.001), and attention-executive functions (pb.001).
M. Pievani et al. / NeuroImage 45 (2009) 1090–1098
loss. However, the interaction between APOE status and brain region
was significant (p=.002, ANOVA; Fig. 3C). When patients were
separated into younger (ε4+: n=7, ε4−: n=7) and elderly (ε4+: n=8,
ε4−: n=7), the interaction term in the ANOVA model was significant in
both early (p=.013) and late-onset (p=.050) patients (Supplementary
The analyses carried out on the women samples (ε4+: n=14; ε4−:
n=7) provided similar results. Patterns of atrophy remained highly
significant in both carriers (p=.0001 on permutation test) and non-
carriers (p=.0003) relative to controls, and confirmed that regional
differences in GM loss between carriers and non-carriers mapped to
the temporal and fronto-parietal cortex (pb.01 uncorrected). These
differences were not significant after controlling for multiple
comparisons (pN.57, permutation test). The interaction term between
APOE and region remained significant (p=.008, ANOVA. Supplemen-
In the present study we found that APOE modulates AD pathology,
the ε4 allele being associated with a pattern of increased susceptibility
of the temporal cortex together with lower vulnerability in the fronto-
parietal neocortical regions.
The finding of a significant interaction between APOE and region
affected is in line with previous studies suggesting a region-specific
effect of APOE on brain atrophy (Hashimoto et al., 2001; Geroldi et al.,
1999), rather than greater disease severity in ε4 carriers. This
modulating effect became evident when the analyses were driven
by a-priori hypotheses consistent with previous data (Geroldi et al.,
1999; Hashimoto et al., 2001). Although early studies did not assess
the interaction between APOE and region, the findings of greater
atrophy of the medial and lateral temporal cortex in ε4 carriers
(Juottonen et al., 1998; Lehtovirta et al., 1995; Pennanen et al., 2006;
Hämäläinen et al., 2008; Thomann et al., 2008) together with milder
involvement of whole brain volumes (Yasuda et al., 1998; Lehtovirta
et al., 1995) are consistent with the hypothesis of a modulating effect
of APOE. Lehtovirta did not actually report a significant difference
betweencarriers andnon-carriersin the frontal lobe, notwithstanding
therewas a trend forlarger frontalvolumes together withsignificantly
smaller hippocampal volumes in carriers (Lehtovirta et al.,1995). It is
likely that the interaction effect detected here would be stronger if
patients carrying two ɛ4 alleles were included, as APOE effect on brain
atrophy has been reported to be proportional to allele dose (Yasuda
et al., 1998; Geroldi et al., 1999). The lack of ɛ4 homozygous in our
sample may indeed have reduced the statistical power of our findings.
The mechanism through which APOE affects regional atrophy
might involve the role of apoE on the deposition of NFT. The temporal
cortex is highly susceptible to NFT deposition whereas other
neocortical areas are less vulnerable (Braak and Braak, 1991; Arnold
et al., 1991). An association between APOE ɛ4 and increased NFT
deposition in the temporal cortex has been demonstrated in vivo in
transgenic mice (Brecht et al., 2004; Tesseur et al., 2000), and from
neuropathological examinations (Tiraboschi et al., 2004; Nagy et al.,
1995). The effect of APOE on atrophy in the temporal region might
Fig. 2. Patterns of GM loss in Alzheimer's disease patients carrying (ε4+) and non-carrying (ε4−) the APOE ε4 allele compared with age-matched controls. Top: statistical maps,
showing areas of significantly reduced cortical GM in (a) ε4+ vs controls and (b) ε4− vs controls. Red regions correspond to a threshold of pb.01 uncorrected. Maps were significant
after correction for multiple comparisons (p=.0001 for both comparisons, permutation test). Bottom: GM reduction in (c) ε4+ and (d) ε4− compared with controls, expressed as a
percentage of the difference in GM between patients and controls. Values greater than 15% (yellow to red regions) denote statistically significant atrophic areas and red regions
correspond to areas of severe GM reduction (greater than 25%).
M. Pievani et al. / NeuroImage 45 (2009) 1090–1098
Fig. 3. (A, B) APOE-related patterns of cortical atrophy. The maps show regions more (left) and less (right) vulnerable to atrophy in ε4+ patients. Top: significance maps for the comparisons (left) ε4+ vs ε4−, and (right) ε4− vs ε4+. Red regions
correspond to a threshold of pb.01 uncorrected. Maps were not significant after correction for multiple comparisons at a threshold of pb.01 (pN.33, permutation test). Bottom: Extent of increased (left) and reduced (right) vulnerability in ε4+,
expressed as a percentage of the difference in GM reduction between carriers and non-carriers. (C) Graph showing the interaction between APOE status (ε4+ vs ε4−) and cortical region (temporal vs fronto-parietal neocortex) in AD patients. p
denotes significance of the interaction on ANOVA. Error bars denote standard errors.
M. Pievani et al. / NeuroImage 45 (2009) 1090–1098
therefore be mediated by greater NFT deposition. Furthermore, the ε4
allele in the temporal lobe has been associated with impaired synaptic
activity (Buttini et al., 2002), reduced neurite outgrowth (Sun et al.,
1998), more severe Abeta deposition (Tiraboschi et al., 2004; Nagy
et al., 1995) and cholinergic deficits (Buttini et al., 2002). There are
thus several possible mechanisms in addition to (or concurrent with)
NFT deposition through which the ε4 allele may modulate temporal
lobe atrophy in AD. Less straightforward is the interpretation of how
APOE ε4 may be associated with a lesser degree of atrophy in the
frontal and parietal neocortex; previous studies indeed reported a
detrimental effectof the ε4 allele onAbeta deposition and cholinergic/
synaptic activity in the fronto-parietal cortex as well (Buttini et al.,
2002; Soininen et al., 1995; Beffert et al., 1999). These data may thus
indicate that the effect of APOE ɛ4 on atrophy may not be a simple
consequence of Abeta deposition and of cholinergic/synaptic deficits.
Furthermore, the relative preservation of the fronto-parietal cortex
may alternatively suggest that APOE ε4 could be less detrimental in
some respects. The ε4 allele indeed may be more efficient than other
isoforms in aspects related to development, such as in promoting
cognitive development (Yu et al., 2000), although region-specific
effects in the frontal and parietal neocortex have never been reported.
A recent study has shown that – contrary to expectation – ε4 carriers
had a better long-term outcome after brain injury (Willemse-van Son
et al., 2008). These data, together with findings of longer survival,
slower cognitive and functional decline, slower atrophy rate in AD
patients who were ε4 carriers (Frisoni et al., 1995; Hoyt et al., 2005;
Stern et al.,1997; Sluimer et al., 2008), may indicate that ε4 effect may
be less detrimental than other isoforms in the long term (Teasdale,
2008). As experiments from basic and molecular studies are usually
carried out over a relatively short period of time, they may lack the
ability to address some aspects of the diseases that can be captured in
In the present study, carriers and non-carriers showed comparable
cognitive deficits in all the domains investigated. This is to some
extent in contrast with earlier studies reporting greater memory
deficits in ε4 carriers (Smith et al.,1998), and conversely more severe
impairment in non-memory domains in AD patients lacking the ε4
allele (Lehtovirta et al., 2006; Van Der Vlies et al., 2007). The majority
of previous studies that reported neuropsychological testing scores
together with MRI indexes of atrophy found lower performance on
memory tests in ε4 carriers (Lehtovirta et al., 1995; Juottonen et al.,
1998), and one reported a significant association between number of
ε4 alleles and score on attention and intelligence scales (Hashimoto
et al., 2001). A possible explanation for the discrepancies with
previous studies may lie in differences in the sampling of the ε4
group: the association between the ε4 allele and atrophy seems to be
gene-dose dependent (Yasuda et al., 1998; Geroldi et al., 1999), and
previous studies included a subgroup of patients who were homo-
zygous for the ε4 allele. Thus, the lack of patients carrying two ε4
alleles in our study may explain why we did not find a significant
effect of APOE on cognition in our sample.
This study has both strengths and limitations. The major strength
involves the spatial accuracy of our mapping technique that allows to
compare anatomical features over the whole cortical mantle between
subjects. Commonly used methods such as manual regions of interest
tracing suffer the disadvantage of being spatially less detailed and
typically they are strongly dependent on a priori hypothesis. As for
limitations, although the sample size of our AD groups was
comparable to that of previous studies, confirmation is required in
larger samples to take into account factors that may have influenced
our results tosome degree, such as age, sex, and education differences.
In this study indeed there was a larger proportion of women in
carriers than non-carriers, and educational level differed between
groups. A previous study (Juottonen et al.,1998) reported that atrophy
of the entorhinal cortex was more pronounced in female patients
carrying at least one ε4 allele than in men. Conversely, some authors
showed greater vulnerability of the frontal and parietal cortex in men
and persons with a higher educational level (Kidron et al., 1997).
Although it is generally agreed that these factors may play a role in
modulating susceptibility to AD (Lahiri et al., 2004; Azad et al., 2007),
it is less clear whether they can affect disease phenotype. In the
present study, control subjects were overall matched to patients and
this should have attenuated differences due to sociodemographic
the results remained unchanged thus confirming that the effect
observed was not due to differences in sex and/or education. Clearly,
further studies including groups well-balanced in their sociodemo-
graphic features are recommended. Another limitation of the study is
that APOE genotype was not available for all controls. Thus, we could
not investigate changes modulated by APOE from those representing
APOE-related morphological traits.
In the present study, we provided an independent confirmation of
previous findings about a modulating effect of APOE on brain atrophy,
the ε4 allele being associated with greater susceptibility of the
temporal cortex, and conversely less vulnerability in the frontal-
parietal cortex. These data suggest that the ε4 allele modulates AD
phenotype. The mechanism underlying APOE ε4 effect on cortical
atrophy however may be quite complex and involve several processes
related to AD pathology.
Funding support for this work was provided in part by grants from
the Italian Ministry of Health, Ricerca Finalizzata 'Sviluppo di
indicatori di danno cerebrovascolare clinicamente significativo alla
risonanza magnetica strutturale' (grant no. 196/2002) and 'Archivio
normativo italiano di morfometria cerebrale con risonanza magnetica
(40+)' (grant ICS 030.13/RF00.343). P.T. was funded by NIH grants
EB008281, EB007813, AG016570.
Appendix A. Supplementary data
Supplementary data associated with this article can be found, in
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