Functional brain abnormalities in young adults at
genetic risk for late-onset Alzheimer’s dementia
Eric M. Reimana,b,c,d,e, Kewei Chena,d,f,g, Gene E. Alexanderd,h, Richard J. Casellid,i, Daniel Bandya,d, David Osborned,j,
Ann M. Saundersk,l, and John Hardym,n
aPositron Emission Tomography Center, Banner Good Samaritan Medical Center, Phoenix, AZ 85006; Departments ofbPsychiatry andfRadiology, University
of Arizona, Tucson, AZ 85724; Departments ofgMathematics andhPsychology, Arizona State University, Tempe, AZ 85287; Departments ofiNeurology and
jPsychology, Mayo Clinic, Scottsdale, AZ 85259;kDepartment of Medicine (Neurology), Joseph and Kathleen Bryan Alzheimer’s Disease Research Center,
Duke University, Durham, NC 27710;mDepartment of Neuroscience, Mayo Clinic, Jacksonville, FL 32224;cTranslational Genomics Research Institute,
Phoenix, AZ 85004; anddArizona Alzheimer’s Disease Consortium, 1111 East McDowell Road, Phoenix, AZ 85006
Edited by Marcus E. Raichle, Washington University School of Medicine, St. Louis, MO, and approved October 29, 2003 (received for review
September 12, 2003)
Fluorodeoxyglucose positron emission tomography (PET) studies
have found that patients with Alzheimer’s dementia (AD) have
abnormally low rates of cerebral glucose metabolism in posterior
cingulate, parietal, temporal, and prefrontal cortex. We previously
found that cognitively normal, late-middle-aged carriers of the apo-
lipoprotein E ?4 allele, a common susceptibility gene for late-onset
Alzheimer’s dementia, have abnormally low rates of glucose metab-
consider whether ?4 carriers have these regional brain abnormalities
as relatively young adults. Apolipoprotein E genotypes were estab-
lished in normal volunteers 20–39 years of age. Clinical ratings,
performed in 12 ?4 heterozygotes, all with the ?3??4 genotype, and
to generate an aggregate surface-projection map that compared
regional PET measurements in the two groups. The young adult ?4
carriers and noncarriers did not differ significantly in their sex, age,
educational level, clinical ratings, or neuropsychological test scores.
Like previously studied patients with probable AD and late-middle-
aged ?4 carriers, the young ?4 carriers had abnormally low rates of
glucose metabolism bilaterally in the posterior cingulate, parietal,
temporal, and prefrontal cortex. Carriers of a common Alzheimer’s
susceptibility gene have functional brain abnormalities in young
adulthood, several decades before the possible onset of dementia.
apolipoprotein E ? positron emission tomography ? glucose metabolism ?
brain mapping ? surrogate markers
develop and test effective primary prevention therapies, it would
be helpful to characterize brain changes associated with the
susceptibility to AD as early as possible before the onset of
cognitive impairment (2).
Fluorodeoxyglucose positron emission tomography (PET) stud-
ies have found that patients with AD have abnormally low cerebral
metabolic rates for glucose (CMRgl) in posterior cingulate, pari-
etal, temporal, and prefrontal cortex and a progressive decline in
these rates over time (3–8). We (2, 9, 10) and others (11, 12) have
been using PET to detect and track these functional brain abnor-
malities before the onset of dementia in carriers of the apolipopro-
associated with up to half of cases of late-onset AD (13–15).
Previously, we found that cognitively normal 50- to 65-year-old ?4
patients with probable AD and abnormal rates of regional CMRgl
decline over time (2, 9, 10). We now consider whether ?4 carriers
have these regional brain abnormalities as relatively young adults,
several decades before the possible onset of dementia. Our analysis
lzheimer’s dementia (AD) afflicts ?10% of those over the
age of 65 and almost half of those over the age of 85 (1). To
in ?20–23% of Caucasian populations (16) and ?11–36% of
different ethnic groups (17).
Subjects. We used newspaper advertisements to recruit 135 20- to
39-year-old normal volunteers, who agreed that they would not be
given information about their APOE genotype, provided their
informed consent, and were studied under guidelines approved by
human subjects committees at Banner Good Samaritan Medical
Center and the Mayo Clinic (Rochester, MN). Venous blood
analysis involving restriction fragment length polymorphisms (18).
Twelve ?4 heterozygotes and 15 control subjects without the ?4
allele satisfied our eligibility criteria and participated in our brain
imaging studies. Thirteen of the control subjects had the ?3??3
genotype, and 2 had the ?2??3 genotype; 12 were individually
matched to the ?4 carriers for sex, age (within 3 years), and
educational level (within 2 years), and 3 were matched to the ?4
carriers for their mean age and educational level. Subjects denied
an impairment in memory or other cognitive skills, did not satisfy
criteria for a current psychiatric disorder, did not use centrally
had a normal neurological examination. One subject in each group
of the subjects’ APOE genotypes obtained data from medical and
family histories, a neurologic examination, and a structured psy-
chiatric interview (19). The subjects completed the Folstein mod-
ified Mini-Mental State Examination (20) and the Hamilton De-
pression Rating Scale (21), and all but one control subject
completed a battery of neuropsychological tests (22).
Brain Imaging. Volumetric T1-weighted magnetic resonance imag-
ing and fluorodeoxyglucose PET were performed as described (2,
9, 23). PET was performed with the 951?31 ECAT scanner
(Siemens, Knoxville, TN), a transmission scan, the i.v. injection of
of emission scans as the subjects, who had fasted for at least 4 h, lay
quietly in a darkened room with their eyes closed and directed
forward. For whole brain measurements, CMRgl (mg?min per
100 g) was calculated by using the PET images, an image-derived
radiotracer input function, plasma glucose levels, and a graphic
This paper was submitted directly (Track II) to the PNAS office.
Abbreviations: PET, positron emission tomography; AD, Alzheimer’s dementia; CMRgl,
cerebral metabolic rate for glucose; APOE, apolipoprotein E.
eTo whom correspondence should be addressed. E-mail: email@example.com.
lPresent address: GlaxoSmithKline R&D, Research Triangle Park, NC 27709.
nPresent address: Laboratory of Neurogenetics, National Institute on Aging, National
Institutes of Health, Bethesda, MD 20892.
© 2003 by The National Academy of Sciences of the USA
January 6, 2004 ?
vol. 101 ?
method (24). Regional analyses were performed by using the PET
images (in counts) acquired during the last 30 min.
To test the hypothesis that young adult ?4 carriers have
abnormally low CMRgl in the same regions as patients with AD,
a fully automated algorithm, previously used in the study of
patients with probable AD (6) and late-middle-aged ?4 carriers
(9), was used to compare PET images in the two subject groups.
Each subject’s PET image was deformed according to the
coordinates of a standard atlas of the brain (25). Measurements
in each voxel were normalized to that in the pons, which has been
reported to be the region least affected in patients with probable
AD (26). Data on the outer and medial surface of each hemi-
sphere were extracted. A 3D stereotactic surface projection
t-score map of metabolic differences between groups was cal-
culated and superimposed on a map of metabolic reductions in
previously studied patients with probable AD (mean age 64) and
a spatially standardized, volume-rendered MRI (Fig. 1) (6, 9).
Significance levels of P ? 0.001, uncorrected for multiple
comparisons, were initially used to test the hypothesis that the ?4
carriers had abnormally low rates of glucose metabolism in
posterior cingulate, parietal, temporal, and prefrontal cortex; a
Monte Carlo procedure, implemented and tested in the Positron
Emission Tomography Center (27), was then used to correct
maximal significance levels for multiple comparisons in each of
the regions of interest previously associated with metabolic
reductions in the patients with probable AD. Data were ex-
tracted from the locations associated with the most significant
differences between the ?4 carriers and controls (see Table 3) to
in the two subject groups (Fig. 2). (Data from some of the most
superior and inferior regions of the brain were not sampled in
every subject because of limitations in the PET system’s field of
Demographic characteristics and clinical ratings of the ?4 car-
riers and control subjects are shown in Table 1. Their neuro-
psychological scores are shown in Table 2. There were no
significant differences in demographic characteristics or scores
on the Hamilton Depression Rating Scale, modified Mini-
Mental State Examination, or neuropsychological tests. There
were no significant differences between the ?4 carriers and
control subjects in their whole brain CMRgl (mean ? SD, 6.4 ?
0.8 vs. 6.5 ? 0.8 mg?min per 100 g; P ? 0.82 by two-tailed,
unpaired t test) or pons (5.9 ? 0.7 vs. 5.8 ? 0.6 mg?min per 100 g;
P ? 0.64).
Like previously studied patients with probable AD (6, 8) and
our previously studied 50- to 65-year-old cognitively normal ?4
CMRgl in patients with probable AD. In this analysis, a 3D surface-projection map of abnormally low CMRgl in the young adult ?4 carriers was superimposed on
a map of abnormally low CMRgl in previously studied patients with the probable AD and a spatially standardized and volume-rendered MRI of the brain
blue areas are regions in which CMRgl was abnormally low in both the young adult ?4 carriers and patients with probable AD, and the muted blue areas are
regions in which CMRgl was abnormally low only in the ?4 carriers. (Lines point to the locations of the ?4 carriers’ most significant CMRgl reductions and
correspond to the brain atlas coordinates in Table 3.) Like patients with AD, the young adult ?4 carriers had abnormally low CMRgl bilaterally in the posterior
cingulate, parietal, temporal, and prefrontal cortex.
Regions of the brain with abnormally low CMRgl in young adult carriers of the APOE ?4 allele and their relation to brain regions with abnormally low
Reiman et al. PNAS ?
January 6, 2004 ?
vol. 101 ?
no. 1 ?
homozygotes (9) and heterozygotes (10), the group of young
adult ?4 carriers had abnormally low CMRgl in the posterior
cingulate, parietal, temporal, and prefrontal cortex (Fig. 1 and
Table 3). With the exception of the right temporal cortex, these
abnormalities remained significant after correction for multiple
comparisons (Table 3). Whereas ?4 carriers may have lower
CMRgl in other cortical regions (P ? 0.001, uncorrected for
multiple comparisons, Fig. 1), these additional metabolic reduc-
tions need to be confirmed in an independent comparison. For
each of the locations specified in Table 3, the mean CMRgl was
8.0–10.5% lower in the ?4 carriers than in the controls. These
reductions were smaller than those previously reported in pa-
tients with probable AD (6), and there was considerable overlap
between the ?4 carrier and noncarrier groups’ individual mea-
surements (Fig. 2). The ?4 carriers did not have abnormally high
CMRgl, even at the more liberal significance level of P ? 0.05,
uncorrected for multiple comparisons.
In a post hoc analysis, the subjects’ coregistered MRI and
PET images, an automated brain mapping algorithm that
permitted us to investigate the effects of partial volume
averaging on PET measurements in each voxel (SPM99,
Wellcome Department of Cognitive Neurology, University
College, London) (28) and an algorithm intended to account
for these effects (29) were used to generate and compare
statistical brain maps of metabolic differences between the two
subject groups with and without correction for individual
differences in brain tissue volume. Because the pattern of
metabolic differences between the two groups remained
present after correction for partial volume averaging, and was
not significantly different from the pattern identified without
this correction, the functional brain abnormalities observed in
the young adult ?4 carriers could not be solely attributed to
alterations in the regional volume of brain tissue.
In another post hoc analysis, PET images from the 20- to
39-year-old subjects and previously studied 50- to 65-year-old
subjects (10) were used to characterize and compare the effects
and controls. Overall, the ?4 carriers had significantly lower
CMRgl than the controls in the posterior cingulate, parietal,
temporal, and prefrontal cortex, and older age was significantly
correlated with lower CMRgl in extensive areas of cerebral
cortex (P ? 0.001, uncorrected for multiple comparisons). With
possible exceptions in localized areas of the left prefrontal and
posterior cingulate cortex (P ? 0.005, uncorrected for multiple
comparisons), the ?4 carriers did not have significantly steeper
age-related CMRgl declines than those in the ?4 noncarriers.
Thus, whereas 2-year follow-up studies have demonstrated ab-
normally high rates of regional CMRgl decline in older ?4
carriers before the onset of cognitive impairment (2, 12), this
cross-sectional comparison did not demonstrate abnormally
steep posterior cingulate, parietal, or temporal CMRgl declines
in ?4 carriers between young adulthood (when the abnormalities
are already present) and late middle age.
We previously found that cognitively normal late-middle-aged
carriers of the APOE ?4 allele, a common AD susceptibility
gene, have functional brain abnormalities in the same brain
regions as patients with probable AD. We now find that
cognitively normal ?4 carriers have functional brain abnor-
malities as relatively young adults, several decades before the
differences between the ?4 carriers (?4) and controls who do not carry the ?4 allele (NC) (P ? 0.001, uncorrected for multiple comparisons).
Regional?pontine CMRgl in young adult APOE ?4 carriers and controls. Measurements were normalized to that in the pons, which appears to be the
Table 1. Characteristics of the young adult ?4 carriers and control subjects
CharacteristicCarriers, n ? 12Controls, n ? 15
Handedness right, yes?no
Years of education
Reported family history
Any first-degree relative, yes?no
Any first- or second-degree relative, yes?no
Score on Hamilton Depression Scale
Score on Mini-Mental State Examination
30.7 ? 5.4
16.0 ? 1.7
31.2 ? 5.0
16.1 ? 1.5
1.0 ? 1.9
29.9 ? 0.3
1.1 ? 1.8
29.9 ? 0.3
Plus-minus values are means ? SD.
*The P value was calculated with an unpaired two-tailed t test.
†The P value was calculated with Pearson ?2two-tailed test, with continuity correction for n ? 5.
www.pnas.org?cgi?doi?10.1073?pnas.2635903100Reiman et al.
possible onset of dementia. These abnormalities were detected
even though the young adult ?4 carriers were restricted to
persons with one copy of this allele, who tend to have a lower
risk of AD and a later age of onset of dementia than those with
two copies of this allele ?4, even though at least half of ?4
heterozygotes are unlikely to develop AD, and even though the
average age of onset of dementia in those ?4 heterozygotes
who develop the disorder appears to be in the seventh decade
of life, about four decades older than the average age of
subjects in this study (13–15).
In separate studies, we have found abnormally low CMRgl
bilaterally in the posterior cingulate, parietal, temporal, and
prefrontal cortex in patients with AD (8), cognitively normal
?4 homozygotes and heterozygotes at 50–65 years of age (9,
10), and cognitively normal ?4 heterozygotes at 20–39 years of
age at the time of their baseline scans. As noted (9, 10), the
CMRgl abnormalities could reflect reductions in the activity
or density of terminal neuronal fields that innervate the
implicated regions (30), the activity of synaptic glial cells (31),
an impairment in glucose metabolism unrelated to local
neuronal activity (32, 33), or a combination of these factors. As
in patients with probable AD (29), the CMRgl abnormalities
in the young ?4 carriers could not be solely attributed to
alterations in brain volume.
The CMRgl reductions in our young adult ?4 carriers may be
the earliest brain abnormalities yet found in living persons at
risk for late-onset AD. In postmortem studies, the character-
istic histopathological features of AD include neuritic plaques,
neurofibrillary tangles, and a loss of synapses. Whereas the
type, density, and topographic distribution of this histopathol-
ogy is likely to be extremely limited in normal young adults,
postmortem studies have raised the possibility that the initial
stage of AD histopathology [the selective involvement of
neurofibrillary tangles in transentorhinal cortex (34, 35)] may
be present several decades before the onset of dementia. In a
study of young adults (mean age 38, range 22–46 years), this
initial histopathological stage was observed in a higher fre-
quency of persons with the ?3??4 genotype than in controls
with no copies of the ?4 allele (36). Estimating the longitudinal
progression of AD histopathology from cross-sectional data, a
related study of persons 40–90 years of age suggested that this
initial histopathological stage may precede AD by ?50 years
(37). MRI studies have found significantly smaller hippocam-
pal volumes in patients with AD and mild cognitive impair-
Table 2. Neuropsychological scores in young ?4 heterozygotes and control subjects
?4 Carriers, n ? 12 Controls, n ? 14
P value Mean (?SD) score
Complex figure test
Boston naming test
Controlled oral word association test
WMS-R Orientation Subtest
51.9 ? 6.7
11.2 ? 2.6
10.6 ? 3.1
52.6 ? 8.5
11.8 ? 2.5
11.7 ? 2.2
35.6 ? 1.0
20.3 ? 5.6
54.4 ? 3.2
35.4 ? 0.9
21.0 ? 7.6
56.1 ? 2.7
11.6 ? 1.5
10.8 ? 1.5
11.3 ? 3.0
11.6 ? 2.2
11.6 ? 2.1
43.3 ? 8.7
13.9 ? 0.3
11.0 ? 2.4
10.9 ? 3.3
12.1 ? 2.5
11.2 ? 2.5
11.5 ? 2.1
44.4 ? 10.0
13.9 ? 0.3
AVLT, Auditory Verbal Learning Test; WAIS-R, Wechsler Adult Intelligence Scale-Revised; WMS-R, Wechsler
Memory Scale-Revised. The P value was calculated with unpaired two-tailed t tests, uncorrected for multiple
Table 3. Location and magnitude of most significant reductions CMRgl
Atlas coordinates,* mm
The reductions were identified by an automated search of posterior cingulate, parietal, temporal, and
prefrontal cortex, regions previously found to be affected in patients with AD.
*The coordinates were obtained from Talairach and Tournoux (25). x is the distance in mm to the right (?) or left
superior (?) or inferior (?) to a horizontal plane through the anterior and posterior commissures.
†P ? 0.001 before correction for multiple comparisons.
‡Significance levels were corrected for multiple comparisons in each of the regions of interest previously
associated with CMRgl reductions in the patients with probable AD. Details of the correction procedure, which
included 20,000 Monte Carlo simulations, are available on request.
Reiman et al. PNAS ?
January 6, 2004 ?
vol. 101 ?
no. 1 ?
ment, correlations between reduced hippocampal volume and
the severity of cognitive impairment, and progressive declines
in hippocampal volume during the course of the illness (10,
23). Based on our study of late-middle-aged ?4 homozygotes
and controls and a review of the MRI literature, we suggested
that the reduction in posterior cingulate CMRgl is apparent
before the onset of memory decline in persons at risk for AD
and that hippocampal volumes begin to decline some time
later, in conjunction with the onset of memory decline and
shortly before the onset of dementia (23).
The causal connections, if any, between the CMRgl abnor-
malities and the histopathological features of AD remain to be
clarified. For instance, it is possible that the CMRgl abnormal-
ities are attributable to AD histopathology. In a PET study of
baboons, neurotoxic lesions of entorhinal and perirhinal cortex
were associated with reduced rates of glucose metabolism in
posterior cingulate, parietal, and temporal cortex (38), raising
a reduction in the activity or density of projections arising in the
vicinity of entorhinal cortex, the location of earliest and most
extensive AD-related histopathology (34, 39). Still, it remains to
be shown that the CMRgl abnormalities could be attributed to
the very limited histopathology that may or may not be present
in the cognitively normal young adult ?4 carriers. Alternatively,
it is possible that the CMRgl abnormalities found in young adult
?4 carriers increase vulnerability to AD histopathology. Because
there may be some correspondence between the cortical asso-
ciation areas preferentially affected metabolically and his-
topathologically in AD (40, 41), our findings raise the possibility
that functional alterations provide a foothold for the subsequent
onset of neuropathology in brain regions that are preferentially
vulnerable to this disorder. If so, it may be possible to identify
neurobiological processes that are involved in the predisposition
to AD and precede the onset of previously known neuropathol-
ogy, providing particularly early targets for a prevention therapy.
The functional brain abnormalities observed in the young
adult ?4 carriers could reflect a very early age-related decline
in CMRgl or an abnormality in prenatal or early postnatal
neurological development. In comparison with the other iso-
forms, the E4 isoform of APOE has been associated with
higher cholesterol levels, increased aggregation of amyloid,
less protection against amyloid-induced oxidative neurotoxic-
ity, less efficient repair of neurons and synapses, less protec-
tion against the hyperphosphorylation of the microtubule-
associated protein tau, the formation of neurofibrillary
tangles, and a reduction in the outgrowth of neurons (13, 16,
42–45). Although any of these processes could have a role in
the development of AD, some could have an additional role in
Although it remains possible that the CMRgl abnormalities
reflect aspects of the ?4 allele unrelated to AD, PET studies
suggest that these abnormalities are related to the development
of this disorder. Although there may be some differences (46,
47), patients with probable AD had a similar pattern of reduc-
tions in regional CMRgl whether or not they had the ?4 allele
(48, 49). In patients with probable AD, the CMRgl abnormalities
predicted the subsequent progression of dementia and the
histopathological diagnosis of AD (7), were progressive (3–5, 8),
and were correlated with dementia severity (6). In older ?4
carriers who did not have dementia, CMRgl continued to decline
in these and other brain regions and did so at higher rates than
in control subjects who did not have this allele (2, 12). In those
?4 carriers who had memory concerns, some of the metabolic
abnormalities predicted a subsequent decline in memory (12).
Our ongoing longitudinal PET study of late-middle-aged, cog-
nitively normal ?4 carriers, and studies in patients with mild
cognitive impairment who have an increased annual risk of AD
(50), promise to clarify the extent to which the PET abnormal-
ities are related to the risk of AD.
Although some studies do not detect a significant effect of
early life factors (51, 52), it has been suggested that early life
factors may contribute to the risk of late-onset AD (53–56). In
a sample of nuns, those with lower measures of linguistic ability
at a mean age of 22 years had lower cognitive function, a higher
frequency of neuropathologically confirmed AD, and a higher
density of neurofibrillary tangles in the hippocampus and
cortex when they were assessed about six decades later (53). In
a sample of Scottish residents, those with lower scores on a test
of mental ability at the age of 11 had a higher frequency of
late-onset dementia by the age of 75 (54). In several studies,
lower educational levels were associated with an increased risk
of AD (55, 56). The relationship between lower levels of
intelligence and education and an increased risk of AD could
be attributable to very early neurological alterations that lead
to each of these conditions, differential cognitive reserve
capacities in neuropathologically affected or unaffected brain
regions (57), possible neuroprotective effects of cognitive
stimulation (58), or a combination of these and other contrib-
In a post hoc cross-sectional analysis, PET images from our
young adults and previously studied late-middle-aged subjects
(10) were used to characterize and compare the effects of age on
regional CMRgl in cognitively normal ?4 heterozygotes and
controls. Consistent with previous studies (9, 59–63), the late-
middle-aged adults had lower CMRgl than young adults in
extensive areas of the cerebral cortex, most prominently in the
medial frontal lobe. In contrast to 2-year follow-up findings that
regional CMRgl continues to decline at an abnormally high rate
in older ?4 carriers with and without memory concerns (2, 12),
the CMRgl differences between young adulthood and late
middle age were not significantly greater in the ?4 carriers than
in the controls. Although there may be other explanations to
reconcile these findings, we have previously postulated that the
rates of age-related CMRgl decline in different regions vary
depending on a person’s age, AD risk and stage, and their
interactions (10). Longitudinal studies are needed to further
characterize the course of CMRgl declines across the adult
lifespan, the extent to which they are accelerated in ?4 carriers
cognitive impairment and dementia.
This study has several limitations. For instance, because
subjects in this study were selected by using newspaper adver-
tisements, were mostly Caucasian and female, and had relatively
high educational levels, additional studies are needed to deter-
mine whether our findings can be confirmed in young adult ?4
carriers with other demographic features. Although CMRgl
abnormalities have been reported in some of the same brain
regions in relatives of patients with an early-onset, autosomal
dominant form of AD (64) and a patient with mild cognitive
impairment who subsequently developed AD (65), additional
studies are needed to determine whether the same pattern of
functional brain abnormalities is related to the risk of AD in
persons with no copies of the ?4 allele. Finally, whereas the ?4
carriers and control subjects had significant differences in their
regional PET measurements, there was considerable overlap
between groups in their individual measurements. Neither ge-
netic testing for APOE alleles nor PET are clinically indicated
to predict a cognitively normal person’s risk of AD. This
information does not yet determine with sufficient accuracy
whether or when a person might develop AD; this information
may be associated with psychological and social risks; and
established prevention therapies are not yet available (66).
If, as we believe, the functional brain abnormalities observed in
www.pnas.org?cgi?doi?10.1073?pnas.2635903100Reiman et al.
it may be possible to discover primary prevention therapies that
target the contributing processes at an unusually early age, decades
before the onset of cognitive decline, and perhaps at a more
tractable stage of disease or level of susceptibility.
We thank Anita Prouty, Christine Burns, Sandra Yee-Benedetto,
Heather Wheeler, Debra Intorcia, Sandra Goodwin, Leslie Mullen,
Susan Poulton, Dr. Wavrant-DeVrieze Fabienne, Louis Giordano, Alisa
Domb, and Bernadette Romo for technical assistance; Dr. David Kuhl
for permission to use PET data from the University of Michigan, Ann
Arbor; Dr. Satoshi Minoshima for permission to use image-analysis
software; and Dr. Michael Lawson and Connie Boker for their encour-
agement. This study was supported by Alzheimer’s Association Grants
IIRG-98-068 (to E.M.R.) and IIRG-98-078 (to R.J.C.), the Arizona
Alzheimer’s Research Center (E.M.R. and R.J.C.), National Institute of
Mental Health and National Institute on Aging Grants RO1
MH57899-01 and P30 AG19610-02 (to E.M.R.), the Banner Health
Foundation, and the Mayo Clinic Foundation.
1. Evans, D. A., Funkenstein, H. H., Albert, M. S., Scherr, P. A., Cook, N. R.,
Chown, M. J., Hebert, L. E., Hennekens, C. H. & Taylor, J. O. (1989) J. Am. Med.
Assoc. 262, 2551–2556.
2. Reiman, E. M., Caselli, R. J., Chen, K., Alexander, G. E., Bandy, D. & Frost, J.
(2001) Proc. Natl. Acad. Sci. USA 98, 3334–3339.
3. McGeer, E. G., Peppard, R. P., McGeer, P. L., Tuokko, H., Crockett, D., Parks,
R., Akiyam, H., Calne, D. B., Beattie, B. L. & Harrop, R. (1990) Can. J. Neurol.
Sci. 17, 1–11.
4. Smith, G. S., de Leon, M. J., George, A. E., Kluger, A., Volkow, N. D., McRae,
T., Golomb, J., Ferris, S. H., Reisberg, B., Ciaravino, J., et al. (1992) Arch. Neurol.
5. Mielke, R., Herholz, K. & Grond, M. (1994) Dementia 5, 36–41.
6. Minoshima, S., Frey, K. A., Koeppe, R. A., Foster, N. L. & Kuhl, D. E. (1995)
J. Nucl. Med. 36, 1238–1248.
7. Silverman, D. H., Small, G. W., Chang, C. Y., Lu, C. S., Kung De Aburto, M. A.,
Chen, W., Czernin, J., Rapoport, S. I., Pietrini, P., Alexander, G. E., et al. (2001)
J. Am. Med. Assoc. 286, 2120–2127.
8. Alexander, G. E., Chen, K., Pietrini, P., Rapoport, S. & Reiman, E. M. (2002)
Am. J. Psychiatry 159, 738–745.
9. Reiman, E. M., Caselli, R. J., Yun, L. S., Chen, K., Bandy, D., Minoshima, S.,
Thibodeau, S. N. & Osborne, D. (1996) N. Engl. J. Med. 334, 752–758.
10. Reiman, E. M., Caselli, R. J., Alexander, G. E. & Chen, K. (2001) Clin. Neurosci.
Res. 1, 194–206.
11. Small, G. W., Mazziotta, J. C., Collins, M. T., Baxter, L. R., Phelps, M. E.,
Mandelkern, M. A., Kaplan, A., La Rue, A., Adamson, C. F., Chang, L., et al.
(1995) J. Am. Med. Assoc. 273, 942–947.
12. Small, G. W., Ercoli, L. M., Silverman, D. H., Huang, S. C., Komo, S.,
Bookheimer, S. Y., Lavretsky, H., Miller, K., Siddarth, P., Rasgon, N. L., et al.
(2000) Proc. Natl. Acad. Sci. USA 97, 6037–6042.
13. Strittmatter, W. J., Saunders, A. M., Schmechel, D., Pericak-Vance, M., Enghild,
J., Salvesen, G. S. & Roses, A. D. (1993) Proc. Natl. Acad. Sci. USA 90, 1977–1981.
14. Corder, E. H., Saunders, A. M., Strittmatter, W. J., Schmechel, D. E., Gaskell,
P. C., Small, G. W., Roses, A. D., Haines, J. L. & Pericak-Vance, M. A. (1993)
Science 261, 921–923.
15. Saunders, A. M., Strittmatter, W. J., Schmechel, D., George-Hyslop, P. H.,
D. R., Alberts, M. J., et al. (1993) Neurology 43, 1467–1472.
16. Mahley, R. W. (1988) Science 240, 622–630.
17. Hallman, D. M., Boerwinkle, E., Saha, N., Sandholzer, C., Menzel, H. J., Csazar,
A. & Utermann, G. (1991) Am. J. Hum. Genet. 49, 338–349.
18. Hixson, J. E. & Vernier, D. T. (1990) J. Lipid Res. 31, 545–548.
19. Spitzer, R. L., Williams, J. B. W., Gibbon, M. & First, M. D. (1990) User’s Guide
for the Structured Clinical Interview for DSM-III-R (SCID) (Am. Psychiatric Press,
20. Folstein, M. F., Folstein, S. E. & McHugh, P. R. (1975) J. Psychiatr. Res. 12,
21. Hamilton, M. (1960) J. Neurol. Neurosurg. Psychiatry 23, 56–62.
22. Lezak, M. D. (1983) Neuropsychological Assessment (Oxford Univ. Press, New
York), 2nd Ed.
23. Reiman, E. M., Uecke, A., Caselli, R. J., Lewis, S., Bandy, D., de Leon, M. J., De
Santi, S., Convit, A., Osborne, D., Weaver, A., et al. (1998) Ann. Neurol. 44,
24. Chen, K., Bandy, D., Reiman, E., Huang, S. C., Lawson, M., Feng, D., Yun, L. S.
& Palant, A. (1998) J. Cereb. Blood Flow Metab. 18, 716–723.
25. Talairach, J. & Tournoux, P. (1988) Coplanar Stereotaxic Atlas of the Human Brain
(Thieme, New York).
26. Minoshima, S., Frey, K. A., Foster, N. L. & Kuhl, D. E. (1995) J. Comput. Assist.
Tomogr. 19, 541–547.
27. Chen, K. C., Reiman, E. M., Bandy, D. & Alexander, G. E. (2003) in Modeling
and Control in Biomedical Systems, eds. Feng, D. D. & Carson E. R. (Elsevier,
Hong Kong), pp. 11–15.
28. Frackowiak, R. S. J., Friston K. J., Frith, C. D., Dolan, R. J. & Mazziotta, J. C.
(1997) Human Brain Function (Academic, San Diego).
29. Ibanez, V., Pietrini, P., Alexander, G. E., Furey, M. L., Teichberg, D., Rajapakse,
J. C., Rapoport, S. I., Schapiro, M. B. & Horwitz, B. (1998) Neurology 50,
30. Schwartz, W. J., Smith, C. B., Davidsen, L., Savaki, H., Sokoloff, L., Mata, M.,
Fink, D. J. & Gainer, H. (1979) Science 205, 723–725.
31. Magistretti, P. J. & Pellerin, L. (1996) Cereb. Cortex 6, 50–61.
32. Piert, M., Koeppe, R. A., Giordani, B., Berent, S. & Kuhl, D. E. (1996) J. Nucl.
Med. 37, 201–208.
33. Mark, R. J., Pang, Z., Geddes, J. W., Uchida, K. & Mattson, M. P. (1997)
J. Neurosci. 17, 1046–1054.
34. Braak, H. & Braak, E. (1991) Acta Neuropathol. 82, 239–259.
35. Braak, H. & Braak, E. (1997) Neurobiol. Aging 18, 351–357.
36. Ghebremedhin, E., Schultz, C., Braak, E. & Braak, H. (1998) Exp. Neurol. 153,
37. Ohm, T. G., Mu ¨ller, H., Braak, H. & Bohl, J. (1994) Neuroscience 64, 209–217.
38. Meguro, K., Blaizot, X., Kondoh, Y., Le Mestric, C., Baron, J. C. & Chavoix, C.
(1999) Brain 122, 1519–1531.
39. Hyman, B. T., Van Hoesen, G. W., Kromer, L. J. & Damasio, A. R. (1986) Ann.
Neurol. 20, 472–481.
40. Shoghi-Jadid, K., Small, G. W., Agdeppa, E. D., Kepe, V., Ercoli, L. M., Siddarth,
P., Read, S., Satyamurthy, N., Petric, A., Huang, S. C., et al. (2002) Am. J. Geriatr.
Psychiatry 10, 24–35.
41. Mathis, C. A., Bacskai, B. J., Kajdasz, S. T., McLellan, M. E., Frosch, M. P.,
Hyman, B. T., Holt, D. P., Wang, Y., Huang, G. F., Debnath, M. L., et al. (2002)
Biorg. Med. Chem. Lett. 12, 295–298.
42. Wisniewski, T., Castano, E. M., Golabek, A., Vogel, T. & Frangione, B. (1994)
Am. J. Pathol. 145, 1030–1035.
43. Miyata, M. & Smith, J. D. (1996) Nat. Genet. 14, 55–61.
44. Strittmatter, W. J., Weisgraber, K. H., Goedert, M., Saunders, A. M., Huang, D.,
Corder, E. H., Dong, L. M., Jakes, R., Alberts, M. J., Gilbert, J. R., et al. (1994)
Exp. Neurol. 125, 1663–1671.
45. Nathan, B. P., Bellosta, S., Sanan, D. A., Weisgraber, K. H., Mahley, R. W. &
Pitas, R. E. (1994) Science 264, 850–852.
46. Mielke, R., Zerres, K., Uhlhaas, S., Kessler, J. & Heiss, W. D. (1998) Neurosci.
Lett. 254, 49–52.
47. Higuchi, M., Arai, H., Nakagawa, T., Higuchi, S., Muramatsu, T., Matsushita, S.,
Kosaka, Y., Itoh, M. & Sasaki, H. (1997) NeuroReport 8, 2639–2643.
48. Corder, E. H., Jelic, V., Basun, H., Lannfelt, L., Valind, S., Winblad, B. &
Nordberg, A. (1997) Arch. Neurol. 54, 273–277.
49. Hirono, N., Mori, E., Yasuda, M., Ishii, K., Ikejiri, Y., Imamura, T., Shimomura,
T., Hashimoto, M., Yamashita, H. & Sasaki, M. (1998) Alzheimer Dis. Assoc.
Disord. 12, 362–367.
50. Petersen, R. C., Smith, G. E., Ivnik, R. J., Tangalos, E. G., Schaid, D. J.,
Thibodeau, S. N., Kokmen, E., Waring, S. C. & Kurland, L. T. (1995) J. Am. Med.
Assoc. 273, 1274–1278.
51. Munoz, D. G., Ganapathy, G. R., Eliasziw, M. & Hachinski, V. (2000) Arch.
Neurol. 57, 85–89.
52. Caselli, R. J., Hentz, J. G., Osborne, D., Graff-Radford, N. R., Barbieri, C. J.,
Alexander, G. E., Hall, G. R., Reiman, E. M., Hardy, J. & Saunders, A. M. (2002)
J. Am. Geriatr. Soc. 50, 49–54.
53. Snowdon, D. A., Kemper, S. J., Mortimer, J. A., Greiner, L. H., Wekstein, D. R.
& Markesbery, W. R. (1996) J. Am. Med. Assoc. 275, 528–532.
54. Whalley, L. J., Starr, J. M., Athawes, R., Hunter, D., Pattie, A. & Deary, I. J.
(2000) Neurology 55, 1455–1460.
55. Evans, D. A., Beckett, L. A., Albert, M. S., Hebert, L. E., Scherr, P. A.,
Funkenstein, H. H. & Taylor, J. O. (1993) Ann. Epidemiol. 3, 71–77.
56. Stern, Y., Gurland, B., Tatemichi, T. K., Tang, M. X., Wilder, D. & Mayeux, R.
(1994) J. Am. Med. Assoc. 271, 1004–1010.
57. Alexander, G. E., Furey, M. L., Grady, C. L., Pietrini, P., Brady, D. R., Mentis,
M. J. & Schapiro, M. B. (1997) Am. J. Psychiatry 154, 165–172.
58. Kesslak, J. P., So, V., Choi, J., Cotman, C. W. & Gomez-Pinilla, F. (1998) Behav.
Neurosci. 112, 1012–1019.
59. Kuhl, D. E., Metter, E. J., Riege, W. H. & Phelps, M. E. (1982) J. Cereb. Blood
Flow Metab. 2, 163–171.
60. Salmon, E., Maquet, P., Sadzot, B., Degueldre, C., Lemaire, C. & Franck G.
(1991) Acta Neurol. Belg. 91, 288–295.
(1995) J. Nucl. Med. 36, 1141–1149.
62. Coffey, C. E., Wilkinson, W. E., Parashos, I. A., Soady, S. A., Sullivan, R. J.,
Patterson, L. J., Figiel, G. S., Webb, M. C., Spritzer, C. E. & Djang, W. T. (1992)
Neurology 42, 527–536.
63. Terry, R. D., DeTeresa, R. & Hansen, L. A. (1976) Arch. Psychiatr. Nervenkr. 223,
64. Kennedy, A. M., Frackowiak, R. S., Newman, S. K., Bloomfield, P. M., Seaward,
J., Roques, P., Lewington, G., Cunningham, V. J. & Rossor, M. N. (1995)
Neurosci. Lett. 186, 17–20.
65. Pietrini, P., Azari, N. P., Grady, C. L., Salerno, J. A., Gonzales-Aviles, A., Heston,
L. L., Pettigrew, K. D., Horwitz, B., Haxby, J. V. & Schapiro, M. B. (1993)
Dementia 4, 94–101.
66. American College of Medical Genetics, American Society of Human Genetics
Working Group on ApoE and Alzheimer Disease (1995) J. Am. Med. Assoc. 274,
Reiman et al.PNAS ?
January 6, 2004 ?
vol. 101 ?
no. 1 ?