Posterior atrophy predicts time to dementia in patients with amyloid-positive mild cognitive impairment
Pyun et al. Alzheimer's Research & Therapy
Posterior atrophy predicts time to dementia in patients with amyloid-positive mild cognitive impairment
Jung-Min Pyun 0 1 4
Young Ho Park 0 1 4
Hang-Rai Kim 3
Jeewon Suh 1
Min Ju Kang 1
Beom Joon Kim 1
Young Chul Youn 5
Jae-Won Jang 2
SangYun Kim 1 4
the Alzheimer's Disease Neuroimaging Initiative
0 Equal contributors
1 Department of Neurology, Seoul National University Bundang Hospital , 82, Gumi-ro 173 Beon-gil, Bundang-gu, Seongnam-si, Gyeonggi-do 13620 , Republic of Korea
2 Department of Neurology, Kangwon National University Hospital , 156, Baengnyeong, Chuncheon, Kangwon 24341 , Republic of Korea
3 Graduate School of Medical Science & Engineering , KAIST, Daejeon , Republic of Korea
4 Department of Neurology, Seoul National University College of Medicine , Seoul , Republic of Korea
5 Department of Neurology, Chung-Ang University Hospital , Seoul , Republic of Korea
Background: In patients with amyloid-positive mild cognitive impairment (MCI), neurodegenerative biomarkers such as medial temporal lobe atrophy (MTA) are useful to predict disease progression to dementia. Although posterior atrophy (PA) is a well-known neurodegenerative biomarker of Alzheimer's disease, little is known about PA as a predictor in patients with amyloid-positive MCI. Methods: We included 258 patients with amyloid-positive MCI with at least one follow-up visit, and who had low cerebrospinal fluid (CSF) β-amyloid1-42 concentration. Data were obtained from the Alzheimer's Disease Neuroimaging Initiative study. We assessed PA and MTA on magnetic resonance imaging (MRI) using visual rating scales and retrospectively determined progression to dementia during the follow-up period of up to 3 years (median 24 months). The Cox proportional hazards model was used to analyze hazard ratios (HRs) of PA and MTA for disease progression. Additionally, subjects were divided into four groups according to brain atrophy pattern (no atrophy, MTA only, PA only, both MTA and PA), and HRs for disease progression were compared with the no atrophy reference group. Analyses were conducted with and without adjustment for CSF phosphorylated tau181p (p-tau) and baseline demographics. Results: A total of 123 patients (47.7%) showed MTA and 174 patients (67.4%) showed PA. Of the total cohort, 139 cases (53.9%) progressed to dementia. PA and MTA were associated with an increased risk for progression to dementia (HR 2.244, 95% confidence interval (CI) 1.497-3.364, and HR 1.682, 95% CI 1.203-2.352, respectively). In the analysis according to atrophy pattern, HR (95% CI) for progression was 2.998 (1.443-6.227) in the MTA only group, 3. 126 (1.666-5.864) in the PA only group, and 3.814 (2.045-7.110) in both MTA and PA group. These results remained significant after adjustment. Conclusions: In patients with amyloid-positive MCI, PA could predict progression to dementia independently of MTA.
Posterior atrophy; Biomarkers; Disease progression; Mild cognitive impairment; Alzheimer's disease
Dyshomeostasis of β-amyloid (Aβ) is an initiating factor
of Alzheimer’s disease (AD) pathology [
]. Aβ positivity,
defined as Aβ deposition on positron emission
tomography (PET) or a low level of cerebrospinal fluid (CSF)
β-amyloid1–42 (Aβ1–42), is known to predict clinical
progression from mild cognitive impairment (MCI) to
]. However, using only Aβ positivity for
the prediction of disease progression is limited by the
fact that Aβ positivity in CSF begins at least 15 years
before expected clinical symptom onset . Therefore,
neurodegenerative biomarkers that reflect sequential
pathologic processes after Aβ positivity could be useful
in predicting progression from MCI to dementia in the
near future [
Neurodegeneration is the process of neuronal injury,
and can be evaluated by atrophy observed on structural
magnetic resonance imaging (MRI), hypometabolism on
[18F]-fluorodeoxyglucose-PET, positive tau PET, or
increased CSF tau [
]. Medial temporal lobe atrophy
(MTA) on MRI is one of the most well-known
neurodegenerative markers [
], and can predict progression from
MCI to dementia [
]. In a study with MCI patients
with Aβ positivity, those with MTA were more likely to
progress to dementia, which indicates the predictive
value of MTA in amyloid-positive MCI .
Recently, an increasing number of studies have
suggested that another neurodegenerative marker, posterior
atrophy (PA) on MRI, could also predict conversion to
dementia in MCI [
]. In particular, evidence has
shown that, whereas MTA is related to low levels of CSF
Aβ1–42, PA is associated with high levels of CSF total tau
(t-tau) and phosphorylated tau181p (p-tau); this might
support a prognostic value of PA in terms of disease
progression among patients with amyloid-positive MCI
. The current study therefore aimed to assess the
predictive value of PA for progression to dementia in
Data used in the preparation of this article were
obtained from the Alzheimer’s Disease Neuroimaging
Initiative (ADNI) database (adni.loni.usc.edu). The
ADNI was launched in 2003 as a public-private
partnership, led by Principal Investigator Michael W. Weiner,
MD. The primary goal of ADNI has been to test whether
serial MRI, PET, other biological markers, and clinical
and neuropsychological assessments can be combined to
measure the progression of MCI and early AD. For
upto-date information, see www.adni-info.org.
Data used in this study were downloaded from the
ADNI database on 25 May, 2017. We included patients
with late MCI who had had a baseline MRI scan, amyloid
positivity on a CSF study [
], and at least one or more
follow-up visits after initial assessment. The primary
outcome of this study was progression to dementia during
the follow-up period of up to 3 years. A final total of 258
patients, 143 from the ADNI1 cohort and 115 from the
ADNI2 cohort, were included in this study.
Diagnosis of late MCI was made according to the
presence of objective memory impairment but without
meeting the criteria for dementia. Namely, all subjects had
a Mini Mental State Examination (MMSE) score of 24 or
higher, a global Clinical Dementia Rating (CDR) score of
0.5, a CDR memory score of 0.5 or higher, and a score
indicating impairment on the delayed recall of Story A of
the Wechsler Memory Scale-Revised (≥16 years of
education: ≤ 8; 8–15 years of education: ≤ 4; 0–7 years of
education: ≤ 2), which is 1.5 standard deviations below the
mean score of cognitively normal subjects.
CSF measurements and cutoffs
Baseline CSF Aβ1–42, t-tau, and p-tau were measured
centrally using the multiplex xMAP Luminex platform
(Luminex Corp, Austin, TX, USA) with Innogenetics
(INNO-BIA AlzBio3, Ghent, Belgium; for research
useonly reagents) immunoassay kit-based reagents, as
described by Shaw and colleagues [
]. Qualification of
the analytical performance of CSF samples from ADNI
was controlled, showing within-center coefficient of
variation (%CV) 95% confidence interval (CI) value
(mean) of 4.0–6.0% (5.3%) for Aβ1–42, 6.4–6.8% (6.7%)
for t-tau, and 5.5–18.0% (10.8%) for p-tau [
Intercenter %CV 95% CI ranged from 15.9 to 19.8% (17.9%)
for Aβ1–42, 9.6–15.2% (13.1%) for t-tau, and 11.3–18.2%
(14.6%) for p-tau [
]. Amyloid positivity was defined as
CSF Aβ1–42 of less than 192 pg/ml [
Brain MRI scans were acquired as previously described
]. Participants in the ADNI1 cohort were scanned using
either a 1.5 T or 3 T MRI scanner. All subjects in the
ADNI2 cohort were scanned using a 3 T MRI scanner.
MTA was evaluated using a five-point rating scale
developed by Scheltens et al. [
]. According to the height of the
hippocampal formation and the width of the choroidal
fissure and the temporal horn, atrophy was rated from 0 (no
atrophy) to 4 (severe atrophy) (Additional file 1: Table S1).
The largest vertical height of hippocampal formation was
defined as dentate gyrus, hippocampus proper, subiculum,
and parahippocampal gyrus.
PA was assessed using a four-point rating scale developed
by Koedam et al. (0 = no atrophy; 1 = mild widening of the
sulci without evident volume loss of gyri; 2 = substantial
widening of the sulci and volume loss of the gyri; 3 =
severe end-stage atrophy) [
]. The evaluated
anatomical regions included the posterior cingulate sulcus,
precuneus, parieto-occipital sulcus, and the cortex of
the parietal lobes. MRI scans were assessed in the
three different orientations by following anatomical
landmarks: widening of the posterior cingulate and
parieto-occipital sulcus and atrophy of the precuneus
in the sagittal orientation, widening of the posterior
cingulate sulcus and the sulcal dilatation in the
parietal lobes in the axial orientation, and widening of
the posterior cingulate sulcus and parietal lobes in
the coronal orientation. In case of different rating
scores between different MRI planes, the higher score
was used for analysis.
All MRI scans were evaluated by three raters
(board-certified neurologists, Young Ho Park, Hang-Rai Kim, Jeewon
Suh, with 7, 5, and 4 years of experience in dementia) who
were blinded to the clinical information. In case of
disagreement, the three raters reviewed the MRI scans
together for adjustment.
Intra-rater reliability was assessed by the re-rating of
25 randomly determined MRI scans at a separate sitting,
blinded to their own prior rating. Inter-, and intra-rater
reliabilities were measured by calculating the intraclass
For rating scores of both MTA and PA, scores of the
right and left hemispheres for each patient were
summed and the mean value was used. These scores
were dichotomized as normal (no atrophy) or abnormal
(atrophy). For MTA in those younger than 75 years old
a rating score of 1.5 or more was considered abnormal,
and in those aged 75 years or older a score of 2 or more
was considered abnormal [
]. For PA, a score of 1.5 or
more was considered abnormal in all patients [
For quantitative analysis we used data downloaded
from the ADNI database. Regional volumes were
measured automatically by the Freesurfer image
analysis suite, which is freely available for download
(http://surfer.nmr.mgh.harvard.edu/). ADNI1 1.5 T data
were run with Freesurfer version 4.3, and ADNI1 3 T
data and ADNI2 data were run with Freesurfer version
5.1. Each scan was segmented according to an atlas
defined by Freesurfer [
]. We compared volumes of
the hippocampus, parahippocampal cortex, entorhinal
cortex, and fusiform gyrus in temporal regions as well
as the superior and inferior parietal cortex, precuneus,
supramarginal gyrus, and postcentral gyrus in parietal
regions between groups with and without progression
to dementia, using the Mann–Whitney test or Student’s
t test as appropriate.
For comparison of demographic and clinical variables
between groups with and without progression to dementia,
we used the Pearson chi-squared test, Mann–Whitney
test, or Student’s t test as appropriate. We assessed the
hazard ratio (HR) of MTA, PA, CSF t-tau, p-tau, baseline
demographics, and neuropsychological profiles using
univariate Cox regression analysis with follow-up time as a
time variable and progression to dementia as a status
variable. Additionally, we categorized MRI atrophy pattern
into the following four groups: no atrophy, MTA only, PA
only, and both MTA and PA. The HR of each group for
disease progression was calculated using univariate Cox
analysis. The proportional assumption was examined by
log-log survival plots.
The multivariate Cox analysis was performed to
identify independent determinants of disease progression
with relevant covariates. The clinically or statistically
relevant covariates with a p value < 0.2 in univariate Cox
regression analysis were included. If there was more
than one variable that was clinically highly correlated,
we included only one of them in the model. Also,
according to the atrophy pattern, two different models
were implemented. In model 1, HRs of the MTA group
and PA group were analyzed with adjustment for
clinically or statistically relevant covariates. In model 2, HRs
of the four groups according to atrophy pattern (no
atrophy, MTA only, PA only, both MTA and PA) were
analyzed with adjustment for relevant covariates.
Multicollinearity between the covariates was tested by
calculating the variance inflation factor [
]. We used SPSS
21 (SPSS Inc., Chicago, Illinois, USA) for
multicollinearity and inter- and intra-rater reliabilities analyses, and R
(version 3.3.1; http://www.R-project.org) for the
remainder of the analyses. Demographic analysis was performed
using wilcox.test, chisq.test, or t.test function, and Cox
regression analysis was performed using the Coxph
function in R with survival package version 2.41-3.
A total of 258 patients participated in the study. The
median age of patients was 74.1 years, and 101 (39.1%) were
female. A total of 176 patients (68.2%) had at least one
APOE ε4 allele. Of the total cohort, 123 patients (47.7%)
showed MTA and 174 patients (67.4%) showed PA.
Dividing patients according to atrophy pattern, we identified 51
patients (19.8%) with no atrophy, 33 patients (12.8%) with
MTA only, 84 patients (32.6%) with PA only, and 90
patients (34.9%) with both MTA and PA. During the
follow-up period (median 24 months) 139 patients (53.9%)
progressed to dementia, and 119 patients did not.
Demographic, cognitive, and biomarker characteristics
according to progression to dementia, categorized as stable MCI
and progressive MCI, are summarized in Table 1. Patients
Data are presented as the median (interquartile range) unless otherwise specified
a Data for 7 subjects were not available
b Data for 1 subject were not available
c Stable MCI vs. progressive MCI
Aβ β-amyloid, ADAS-cog Alzheimer’s Disease Assessment Scale-cognitive subscale, CDR SB Clinical Dementia Rating Sum of Boxes, CSF cerebrospinal fluid, MCI mild
cognitive impairment, MMSE Mini-Mental State Examination, MRI magnetic resonance imaging, MTA medial temporal lobe atrophy, PA posterior atrophy, p-tau tau
phosphorylated at threonine 181, SD standard deviation, t-tau total tau
with disease progression to dementia had poorer
cognitive performances at baseline, higher levels of CSF
t-tau and CSF p-tau, and more frequent MTA and PA
compared with those without progression. The
interrater reliability for MTA (0.84–0.87) and PA (0.70–
0.87) was good. The intra-rater reliability for MTA
(0.83–0.98) was excellent and for PA (0.73–0.98) was
good (Additional file 2: Table S2). The volumes of the
hippocampus, entorhinal cortex, fusiform gyrus,
superior and inferior parietal cortex, precuneus, and
supramarginal gyrus were significantly decreased in
progressive MCI as compared to stable MCI
(Additional file 3: Table S3).
In the univariate Cox regression analysis, the presence
of MTA and PA showed significantly increased HR (95%
CI) of progression to dementia with a value of 1.682
(1.203–2.352) and 2.244 (1.497–3.364), respectively
(Fig. 1). In the analysis according to MRI atrophy pattern,
patients with only MTA, only PA, and both MTA and PA
were associated with a higher risk for disease progression
compared with those with no atrophy (Table 2). Higher
levels of CSF t-tau and CSF p-tau were related with more
disease progression. Baseline cognitive performances with
lower MMSE scores, higher CDR Sum of Boxes (CDR
SB), and higher Alzheimer’s Disease Assessment
Scalecognitive subscale 11 (ADAS-cog 11) scores were also
associated with progression to dementia. The proportional
assumption was satisfied for MTA and PA based on
loglog survival plots (Additional file 4: Figure S1).
Multivariate Cox analysis included clinically (age, sex)
and statistically relevant variables (education duration,
APOE ε4 allele, ADAS-cog 11, CDR-SB, and CSF p-tau)
(Table 2). Although MMSE and CSF t-tau were
statistically relevant and variance inflation factors were less
than 1.719 for all variables, indicating a low degree of
collinearity, we excluded them from the multivariate
Cox analysis because they were clinically highly
correlated with ADAS-cog 11 and CSF p-tau, respectively.
HR (95% Cl)
HR (95% Cl)
* Data for 7 subjects were not available
** Data for 1 subject were not available
a p < 0.05
b p < 0.001
Model 1: adjusted for MTA, PA, age, sex, education, APOE ε4 carrier, ADAS-cog 11, CDR SB, and CSF p-tau
Model 2: adjusted for MRI atrophy pattern (no atrophy, MTA only, PA only, both MTA and PA), age, sex, education, APOE ε4 carrier, ADAS-cog 11, CDR SB, and
ADAS-cog Alzheimer’s Disease Assessment Scale-cognitive subscale, CDR SB Clinical Dementia Rating Sum of Boxes, CI confidence interval, CSF cerebrospinal fluid,
HR hazard ratio, MMSE Mini Mental State Examination, MRI magnetic resonance imaging, MTA medial temporal lobe atrophy, NI not included, PA posterior atrophy,
p-tau tau phosphorylated at threonine 181, t-tau total tau
The adjusted covariates did not alter the significance of
the HRs (95% CI) of MTA (1.424 (0.997–2.034)) or PA
(1.895 (1.239–2.897)). Moreover, the HR of groups with
only MTA, only PA, and both MTA and PA remained
significant. Notably, there was little difference between
the HRs of MTA only, PA only, and both MTA and PA.
On the contrary, the significant relationships between
CSF p-tau and disease progression disappeared after
adjustment with other covariates.
The ability to predict progression from MCI to dementia
is increasingly important with the prospect of
diseasemodifying therapies. This study demonstrated that
patients with amyloid-positive MCI with PA or MTA are
more likely to progress to dementia. Furthermore,
patients with amyloid-positive MCI with PA only (in the
absence of MTA) also showed an increased risk for
disease progression. This indicates that PA, as well as
MTA, is a predictive marker of conversion from
amyloid-positive MCI to dementia.
To understand the pathophysiology of AD,
considerable effort has been made to identify AD-related focal
regions or functional connectivity between regions in
the brain [
]. According to pathological staging by
Braak and Braak, the neurofibrillary changes (tau
pathology) start from the medial temporal lobe and
spread to neocortical association areas . Many
neuroimaging studies have demonstrated these pathological
changes, showing low glucose metabolism and cortical
atrophy, most prominently in the medial temporal lobe
and parietal lobe, including the bilateral precuneus,
posterior cingulate cortex, and angular gyrus [
21, 24, 26
MTA within these regions is widely recognized as an
imaging marker of AD [
]. Additionally, the parietal
lobe has been highlighted as an area involved in the
pathological changes and dysfunction in AD [
The parietal cortex is originally known for its
visuospatial and sensorimotor functions [
]. However, the
parietal cortex is also involved in other functions, such
as episodic memory retrieval [
]; notably, episodic
memory retrieval impairment is a typical feature of AD.
Functional MRI (fMRI) studies with memory-related
tasks have revealed that the parietal cortex, especially
the precuneus and superior and inferior parietal lobules,
is involved in memory retrieval [
resting-state fMRI studies have revealed that patients
with MCI display lower levels of neuronal activity in the
posterior cingulate cortex, precuneus, and inferior
parietal lobe (components of default mode network)
compared with healthy controls [
cortical connectivity, these regions comprise the
“posterior medial network” (PM network), along with the
retrosplenial cortex and parahippocampal cortex [
PM network and anterior temporal network are two
largely segregated pathways with different anatomical
regions and different memory-guided behaviors, and
were proposed by Ranganath and Ritchey [
]. The PM
network is involved in episodic memory, spatial
navigation, and scene perception. Dominant disruption of this
network has been observed in patients with AD
compared with healthy participants and patients with other
types of dementia [
21, 22, 34
Systematic assessment of PA using a visual rating scale
was suggested by Koedam and colleagues [
visual rating scale, used to rate MRI images for PA within
the posterior cingulate gyrus, precuneus, and parietal
lobe, is simple, easily implemented in clinical settings,
and has a good discrimination ability between healthy
individuals and patients with AD [
]. The visual rating
scale has been validated using voxel-based morphometry
(VBM), with good reliability [
]. Furthermore, in a
study of patients with pathologically proven definite AD,
30% of patients showed only PA without MTA, which
indicates that PA could be used as an independent
imaging marker of AD [
From the perspective of cognitive reserve, MCI
patients with both MTA and PA are expected to
progress more rapidly to dementia than patients with MTA
only or patients with PA only [
]. However, progression
rates were not different between patients with both
MTA and PA, patients with MTA only, and patients
with PA only in our study. Similar results have been
reported regarding clinical progression of patients with
]. In those studies, which grouped patients
with AD into three subtypes according to cortical
atrophy patterns, patients with diffuse atrophy did not show
more rapid progression than patients with medial
temporal dominant atrophy or parietal dominant
atrophy. Rather, patients with parietal dominant atrophy
showed a faster progression rate [
]. Although we
do not know the reason, MTA and PA might not have
additive effects on clinical progression in patients with
With respect to VBM analysis in previous studies with
patients with MCI, gray matter differences between
patients with progressive and stable MCI were assessed
using two-sided t tests in early studies [
the two-sided t tests discard information about varying
lengths of follow-up times among patients. To overcome
this problem, time-to-event statistical methods were
used in VBM analysis of patients with MCI [
studies revealed that the patients with progressive MCI
showed volume loss in the medial temporal lobes as well
as the temporoparietal cortex and frontal lobes
compared with patients with stable MCI [
]. A recent
study, which used a VBM survival analysis and assessed
the effects of amyloid deposition on progression to
dementia in patients with MCI, found that the pattern of
decreased gray matter volume that was predictive of
progression was similar in amyloid-positive and
amyloid-negative patients [
]. Although our study
demonstrated the usefulness of visually assessed PA for
predicting progression to dementia in patients with
amyloid-positive MCI, visually assessed PA might also
be useful in patients with amyloid-negative MCI. In our
previous study of patients with MCI without information
about amyloid positivity, visual rating of PA had
predictive value for progression to dementia [
Notably, our population showed a relatively large
proportion of APOE ε4 carriers (62%). This might be due to
characteristics of our amyloid-positive population. Other
studies with amyloid-positive MCI also reported a large
percentage of APOE ε4 carriers [
5, 43, 44
considerably higher prevalence of amyloid positivity has been
previously reported among APOE ε4 carriers compared
to APOE ε4 noncarriers [
]. The relationship between
APOE ε4 and amyloid positivity has been investigated
extensively for its important pathological role and
contributing risk to AD. APOE ε4 is known to increase
AD risk by decreasing Aβ clearance and promoting Aβ
]. Apolipoprotein E4 has lower affinity to
Aβ than apolipoprotein E3, thus showing inefficient
removal of Aβ across the blood-brain barrier and
increased oligomerization of Aβ [
]. This aspect
could support the large proportion of APOE ε4 carriers
of our amyloid-positive MCI population.
The significant association found between increased
CSF p-tau levels and disease progression in our study is
consistent with previous studies [
]. However, this
significance disappeared in multivariate analysis,
contrary to PA or MTA. This could indicate that brain
atrophy might correlate more strongly with clinical
progression than CSF biomarkers. Several studies have
shown similar correlations between MRI, CSF, and
cognitive performance [
]. One possible explanation
for the stronger relationship of brain atrophy with
progression (compared to the relationship of CSF
biomarkers with progression) is that MRI may be a more
stable biomarker for neuronal injury than CSF tau
proteins, which can be influenced by diurnal variation
and transient brain injury [
]. Otherwise, disease
progression with brain atrophy could be affected by
factors other than tauopathy, such as aging, traumatic
brain injury, toxic factors, and vascular factors [
There are some limitations to our study that should be
noted. First, we defined amyloid positivity by CSF Aβ1–42
levels only, and did not include a population with
positive amyloid PET. This may have led to a selection bias.
However, several studies have shown there to be a good
agreement between CSF Aβ1–42 levels and amyloid PET,
which could minimize the potential bias in our study
]. Second, the visual rating scale may not be
precise compared with volumetric quantitative
measurements. Although we compared volumetric measures of
temporal and parietal regions between stable and
progressive MCI, we could not perform voxel- or
surfacebased analysis because our sample comprised ADNI1 and
ADNI2 cohorts with different magnetic field strength.
This study showed that PA in amyloid-positive MCI is
significantly associated with disease progression to
dementia, independent of the presence of MTA. This is
indicative of the predictive value of PA for disease
progression in patients with amyloid-positive MCI.
Additional file 1: Table S1. Visual rating of medial temporal lobe
atrophy. (DOCX 14 kb)
Additional file 2: Table S2. Inter- and intra-rater reliability. (DOCX 16 kb)
Additional file 3: Table S3. Comparison of volumetric measures of
temporal and parietal regions according to disease progression to
dementia. (DOCX 19 kb)
Additional file 4: Figure S1. Log-log survival plots of PA (A) and MTA
(B). MTA medial temporal lobe atrophy, PA posterior atrophy. (TIF 83 kb)
Aβ: β-Amyloid; AD: Alzheimer’s disease; ADAS-cog: Alzheimer’s Disease
Assessment Scale-cognitive subscale; ADNI: Alzheimer’s Disease
Neuroimaging Initiative; CDR: Clinical Dementia Rating; CDR SB: Clinical
Dementia Rating Sum of Boxes; CI: Confidence interval; CSF: Cerebrospinal
fluid; CV: Coefficient of variation; fMRI: Functional magnetic resonance
imaging; HR: Hazard ratio; MCI: Mild cognitive impairment; MMSE: Mini
Mental State Examination; MRI: Magnetic resonance imaging; MTA: Medial
temporal lobe atrophy; PA: Posterior atrophy; PET: Positron emission
tomography; PM: Posterior medial; p-tau: Phosphorylated tau181p; t-tau: Total
tau; VBM: Voxel-based morphometry
Data collection and sharing for this project was funded by the Alzheimer’s
Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant
U01 AG024904) and DOD ADNI (Department of Defense award number
W81XWH-12-2-0012). ADNI is funded by the National Institute on Aging, the
National Institute of Biomedical Imaging and Bioengineering, and through
generous contributions from the following: AbbVie, Alzheimer’s Association;
Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.;
Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Eisai Inc.; Elan
Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La
Roche Ltd. and its affiliated company Genentech, Inc.; Fujirebio; GE
Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research &
Development, LLC.; Johnson & Johnson Pharmaceutical Research &
Development LLC.; Lumosity; Lundbeck; Merck & Co., Inc.; Meso Scale
Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis
Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Takeda
Pharmaceutical Company; and Transition Therapeutics. The Canadian
Institutes of Health Research is providing funds to support ADNI clinical sites
in Canada. Private sector contributions are facilitated by the Foundation for
the National Institutes of Health (www.fnih.org). The grantee organization is
the Northern California Institute for Research and Education, and the study is
coordinated by the Alzheimer’s Therapeutic Research Institute at the
University of Southern California. ADNI data are disseminated by the
Laboratory for Neuro Imaging at the University of Southern California.
The Medical Research Collaborating Center of Seoul National University
Bundang Hospital contributed to statistical analyses.
Data used in the preparation of this article were obtained from the
Alzheimer’s Disease Neuroimaging Initiative (ADNI) database
(adni.loni.usc.edu). 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 can be found at: http://adni.loni.usc.edu/wp-content/uploads/
Availability of data and materials
YHP, JWJ, and SYK designed the study and participated in data analysis and
interpretation. YHP, JWJ, and JMP participated in data analysis and
interpretation, drafted the manuscript, and revised the manuscript for
important intellectual content. JS, HRK, and BJK participated in data analysis.
All authors read and approved the final manuscript.
Ethics approval and consent to participate
The study procedures were approved by the institutional review board of all
participating centers (http://adni.loni.usc.edu/wp-content/uploads/
how_to_apply/ADNI_Acknowledgement_List.pdf) and written informed
consent was obtained from all participants or authorized representatives.
The authors declare that they have no competing interests.
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