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Significance There has been an emerging interest in sleep and its association with β-amyloid burden as a risk factor for Alzheimer’s disease. Despite the evidence that acute sleep deprivation elevates β-amyloid levels in mouse interstitial fluid and in human cerebrospinal fluid, not much is known about the impact of sleep deprivation on β-amyloid burden in the human brain. Using positron emission tomography, here we show that acute sleep deprivation impacts β-amyloid burden in brain regions that have been implicated in Alzheimer’s disease. Our observations provide preliminary evidence for the negative effect of sleep deprivation on β-amyloid burden in the human brain.
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β-Amyloid accumulation in the human brain after one
night of sleep deprivation
Ehsan Shokri-Kojori
, Gene-Jack Wang
, Corinde E. Wiers
, Sukru B. Demiral
, Min Guo
, Sung Won Kim
Elsa Lindgren
, Veronica Ramirez
, Amna Zehra
, Clara Freeman
, Gregg Miller
, Peter Manza
, Tansha Srivastava
Susan De Santi
, Dardo Tomasi
, Helene Benveniste
, and Nora D. Volkow
Laboratory of Neuroimaging, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD 20892;
Piramal Pharma
Inc., Boston, MA 02108; and
Department of Anesthesiology, Yale School of Medicine, New Haven, CT 06510
Edited by Michael E. Phelps, University of California, Los Angeles, CA, and approved March 13, 2018 (received for review December 14, 2017)
The effects of acute sleep deprivation on β-amyloid (Aβ) clearance
in the human brain have not been documented. Here we used PET
F-florbetaben to measure brain Aβburden (ABB) in
20 healthy controls tested after a night of rested sleep (baseline)
and after a night of sleep deprivation. We show that one night of
sleep deprivation, relative to baseline, resulted in a significant in-
crease in Aβburden in the right hippocampus and thalamus. These
increases were associated with mood worsening following sleep
deprivation, but were not related to the genetic risk (APOE geno-
type) for Alzheimers disease. Additionally, baseline ABB in a
range of subcortical regions and the precuneus was inversely as-
sociated with reported night sleep hours. APOE genotyping was
also linked to subcortical ABB, suggesting that different Alz-
heimers disease risk factors might independently affect ABB in
nearby brain regions. In summary, our findings show adverse ef-
fects of one-night sleep deprivation on brain ABB and expand on
prior findings of higher Aβaccumulation with chronic less sleep.
beta amyloid
Alzheimers disease
Beta-amyloid (Aβ) is present in the brains interstitial fluid
(ISF) and is considered a metabolic waste product(1).
Mechanisms by which Aβis cleared from the brain are not
completely understood (2), although there is evidence that sleep
plays an important role in Aβclearance (3). In rodents, chronic
sleep restriction led to increases in ISF Aβlevels (4) and in a
Drosophila model of Alzheimers disease (AD), chronic sleep
deprivation (SD) resulted in higher Aβaccumulation (5). In
healthy humans, imaging studies have revealed associations be-
tween self-reports of less sleep duration or poor sleep quality and
higher Aβburden (ABB) in the brain (68), which is a risk factor
for AD. This association has been considered bidirectional be-
cause increased ABB could also lead to impairments in sleep (9,
10). Notably, increased ABB in the brain has been associated
with impairment of brain function (11, 12). Thus, strategies that
prevent Aβaccumulation in the brain could promote healthy
brain aging and be useful in preventing AD. In this respect, there
is increasing evidence that sleep disturbances might contribute to
AD, in part by facilitating accumulation of Aβin the brain (13).
To better characterize ABB dynamics, studies have focused on
the effects of sleep patterns on ABB in the CNS. In rodents, it
has been shown that Aβclearance from the brains ISF pre-
dominately occurred during sleep (4), which was ascribed to the
glymphatic pathway, operating most efficiently during sleep (3,
14, 15). Clinical studies have also shown that Aβlevels in the
cerebrospinal fluid (CSF) are the highest before sleep and the
lowest after wakening, while CSF Aβclearance was counteracted
by SD (16). However, there are some inconsistencies between
animal models and findings in humans (17), and Aβincreases in
human CSF could reflect factors other than ABB increases in the
brain itself (1821). Notably, the effects of acute SD on Aβ
clearance in the human brain have not been documented. This
observation will be important for understanding the contribution
of sleep to Aβclearance from the brain and the regional speci-
ficity of such effects.
Here we evaluated the effects of one-night SD on ABB in
healthy controls to investigate whether sleep affects clearance of
Aβfrom the human brain. For this purpose, we used positron
emission tomography (PET) with which it is now possible to
measure ABB in the living human brain. There are several val-
idated PET radiotracers for this purpose, including
florbetaben (FBB) (22, 23). It is believed that such radio-
tracers predominantly bind to insoluble Aβ
plaques (2427),
but there is recent evidence that they also bind to soluble Aβ
forms (28). Thus, we reasoned that PET and FBB could be used
to detect increases in ABB because of acute SD, directly in the
human brain (3). First, we aimed to assess the effect of one-night
SD on brain ABB with PET-FBB in healthy controls (n=20, 22
72 y old, 10 females) (Table S1), and compared the measures to
baseline brain ABB captured at the same time of the day but
following a night of rested sleep [referred to as rested-
wakefulness (RW)]. Second, we aimed to replicate in our sam-
ple the previously reported association between sleep history and
brain ABB (when measured after RW) (68). For our first aim,
we hypothesized that one night of SD would increase ABB in the
hippocampus, which shows some of the earliest structural and
functional changes in AD (29, 30). For our second aim, we hy-
pothesized that history of poor sleep would be associated with
There has been an emerging interest in sleep and its associa-
tion with β-amyloid burden as a risk factor for Alzheimers
disease. Despite the evidence that acute sleep deprivation el-
evates β-amyloid levels in mouse interstitial fluid and in human
cerebrospinal fluid, not much is known about the impact of
sleep deprivation on β-amyloid burden in the human brain.
Using positron emission tomography, here we show that acute
sleep deprivation impacts β-amyloid burden in brain regions
that have been implicated in Alzheimers disease. Our obser-
vations provide preliminary evidence for the negative effect of
sleep deprivation on β-amyloid burden in the human brain.
Author contributions: N.D.V. conceived study; E.S.-K., G.-J.W., C.E.W., S.B.D., S.W.K.,
S.D.S., D.T., H.B., an d N.D.V. desig ned research; E. S.-K., G.-J.W. , C.E.W., S.B.D ., M.G.,
S.W.K., E.L., V.R., A.Z., C.F., G.M., P.M., T.S., S.D.S., D.T., H.B., and N.D.V. performed re-
search; E.S.-K. analyzed data; and E.S.-K. and N.D.V. wrote the paper.
Conflict of interest statement: S.D.S. was an employee of Piramal Pharma Inc. , which
partly supported the radiotracer for this study.
This article is a PNAS Direct Submission.
This open access article is distributed under Creative Commons Attribution-NonCommercial-
NoDeriv atives L icense 4.0 ( CC BY-NC- ND).
To whom correspondence may be addressed. Email:, gene-, or
This article contains supporting information online at
1073/pnas.1721694115/-/DCSupplemental. PNAS Latest Articles
higher ABB in the hippocampus, precuneus, and medial pre-
frontal cortex (6, 8, 31).
Acute SD Effects. To compare the differences in FBB binding
[quantified as relative standard uptake value (SUVr) and used as
a marker of ABB] (Methods) after acute SD versus that obtained
after RW, we used a voxelwise paired ttest in statistical para-
metric mapping (SPM) (Methods). This analysis showed that
images obtained after SD compared with those obtained after
RW had significantly higher FBB binding (ABB increases) in a
right lateralized cluster (Fig. 1A) that comprised hippocampal,
parahippocampal, and thalamic regions (Table S2). Of note, the
increases in FBB SUVr in this cluster were robust and observed
in 19 of 20 participants (Fig. 1B) from RW (mean =1.35,
standard deviation =0.06) to SD (mean =1.42, standard de-
viation =0.07; a 5% increase, P<0.0001). To further confirm
this finding, we quantified FBB SUVr in an a priori hippocampal
region of interest (ROI) (Methods and Fig. 1D) and compared
the measures after SD to those after RW. This ROI analysis also
showed a significant increase in FBB SUVr in the right hippo-
campus ROI from RW to SD (P=0.046, two-tailed, Cohensd=
0.48) but not in the left hippocampus (P=0.4). The magnitude
of the Aβchanges in the hippocampal cluster varied significantly
between subjects (Fig. 1B)(0.58% to +16.1%). We found that
this variability was not associated with gender, age, or apolipo-
protein E (APOE)-based odds ratio for AD (ORAD) (Methods)
(P>0.3). Notably, changes in FBB SUVr in the subcortical
cluster were significant in both males (P=0.0008) and females
(P=0.003). In addition, reported sleep hours (SH) and total
score (TS) for sleep quality (Pittsburgh Sleep Questionnaire
Inventory, PSQI) (Methods) were not associated with these SD-
related increases. Thus, the mechanisms accounting for the ob-
served between-subject variability are still unclear. Subjective
behavioral assessment revealed that SD negatively impacted
mood compared with RW (Methods and Fig. S1). We assessed if
the effects of SD on mood were correlated with increases in ABB
in the right hippocampal cluster. This analysis showed that mood
worsening was negatively associated with changes in FBB SUVr
[r(16) =0.50, P=0.03] (Fig. 1C) such that participants with
larger increases in ABB in the hippocampal cluster (Fig. 1A) had
more mood worsening after SD. Because the quantification of
ABB using FBB SUVr can be sensitive to blood perfusion ef-
fects, we quantified FBB accumulation using measures of bind-
ing potential (BPnd), which are less sensitive to blood perfusion
effects than SUVr measures. BPnd in the cluster where we ob-
served the SD effect (Methods and Fig. 1A) was also significantly
higher in SD relative to RW [t(19) =3.57, P=0.002] (Fig. S2A).
Moreover, SD-related changes in BPnd were significantly cor-
related with those observed with FBB SUVr [r(18) =0.53, P=
0.016] (Fig. S2B), further supporting that SD-related increases in
FBB SUVr are not primarily driven by perfusion effects.
Sleep, APOE, and ABB. Prior studies had reported an association
between reported SH and sleep quality and (cortical) ABB in
healthy middle-aged and older individuals (68). We tested
whether we would corroborate those observations in our sample
using the measures obtained during RW. We found that reported
average SH inversely correlated with FBB SUVr [r(18) =0.5,
P=0.024] and with BPnd [r(18) =0.57, p=0.009] at RW in the
subcortical cluster that showed increases in ABB with SD (Fig.
2A), thus supporting long-term susceptibility of these regions to
increased ABB with less SH. Voxelwise regression analysis of
FBB SUVr on SH showed that less SH was associated with
higher FBB SUVr in the bilateral putamen, parahippocampus,
and right precuneus (Fig. 2Band Table S3). Interestingly, the
SH-related brain areas were more extensive than the areas as-
sociated with (acute) SD-induced ABB increases. For regional
ABB, SH-related subcortical regions (Table S3) had minimal
overlap with subcortical areas related to ORAD (Fig. 2B),
which included the bilateral lentiform nucleus and pallidum
(Table S4). These observations suggested that different brain
R² = 0.2535
-6 -4 -2 0 2 4
Mood Change: SD-RW
*p = 0.046
Fig. 1. Effects of one-night SD on ABB. (A) Voxelwise paired ttest between RW and SD conditions highlighting the hippocampus as well as other subcortical
structures (P
<0.05, cluster-size corrected) (Table S1). (B) Subject-level changes in FBB SUVr (in the red cluster identified in A) from RW to SD. There was no
significant effect of gender, or gender ×sleep interaction (P>0.15). (C) Association between changes in mood from RW to SD and changes in the FBB SUVr
for the cluster identified in A. Mood change was quantified using the principal component of the changes in self-report measures from RW to SD, which
accounted for 35.5% of the variance. Self-report measures of alert, friendly, happy, social, and energetic significantly decreased, and measures of tired and
difficulty staying awake significantly increased from RW to SD (P<0.001, two-tailed) (see also Fig. S1). (D) Average FBB SUVr in a priori hippocampus ROIs
across subjects. Error bars show standard deviation (Methods).
| Shokri-Kojori et al.
regions could be independently affected by different AD-risk
factors (i.e., sleep vs. APOE). This observation is consistent
with prior findings reporting that the APOE genotype did not
moderate the relationship between sleep measures and ABB in
the brain (7).
Our findings provide preliminary evidence for the role of SD on
Aβaccumulation in the human brain. The increases in ABB after
SD in the hippocampus, which is considered among the most-
sensitive brain regions to AD neuropathology (29), is consistent
with epidemiological data identifying impaired sleep as a risk
factor for AD (9, 10) and with recent evidence showing that
disruption of deep sleep increases Aβin human CSF (32). We
also showed Aβincreases in the thalamus after SD, which is a
brain region that shows increases in Aβin the early stages of AD
(33). The regional increases in ABB that we observed from RW
to SD might reflect decreased clearance of Aβ, presumably from
lack of sleep, thus supporting the role of glymphatic system in
clearing Aβfrom the brain during sleep. While this effect was
observed in rodents (3), no study as of now has been able to
directly measure Aβclearance reflecting glymphatic function in
the human brain. Other mechanisms have been shown to stim-
ulate Aβclearance during sleep, such as γ-oscillations during the
rapid eye-movement cycle (34). Alternatively, Aβincreases in the
hippocampus after SD could reflect increases in Aβsynthesis
associated with endogenous neuronal activity during SD (35), or
sleep-related changes in hippocampal neurogenesis (36, 37).
While we are interpreting our findings of increases in ABB after
SD to reflect Aβaccumulation due to lack of glymphatic clear-
ance (or other unknown mechanisms), we cannot rule out the
possibility that they reflect increases in the synthesis of Aβ(38)
from lack of sleep. Preclinical studies that monitor Aβclearance
during sleep using PET radiotracers alongside optical imaging of
ISF are needed to corroborate whether Aβligands and PET have
potential as markers of glymphatic function in the human brain.
Future work should also study the extent that elevated ABB in
the brain is related to increases in Aβlevels in the peripheral
tissue following SD (18, 20).
Detection of Aβplaques with PET is clinically relevant for the
diagnosis of AD, while elevated brain ABB in mild cognitive
impairment (MCI) has been suggested as a risk factor for pro-
gression to AD (22, 39). ABB increases as a function of aging
and AD severity, with an estimated 17% increase from younger
to older adults (40). Relative to healthy elderly, estimated in-
creases of 21% and 43% have been reported in individuals with
MCI and AD, respectively (40). In our study, the increases in
ABB due to one-night SD were smaller (5%) (Fig. 1 Aand B)
and were observed in a subcortical cluster that included the
hippocampus. At this stage, we are uncertain whether such SD-
related increases in ABB may subside following rested sleep. In
addition, the magnitude of the observed effects should be
interpreted with caution considering the methodological limita-
tions and potential confounds, such as the effects of blood-flow
changes and the limited sensitivity of current PET radiotracer to
soluble Aβ(28). While, prior studies have reported associations
with chronic poor sleep and higher average ABB across large a
priori-selected cortical areas (68), our results highlight the
relevance of studying subcortical regions for the associations
between ABB and sleep.
It has been shown in rodents that Aβplaques can form very
rapidly (41), while Aβplaques in their earliest stages show the
highest levels of neuritic dystrophy (42), thus suggesting that
increases in ABB due to one-night SD could adversely impact
the brain. Chronic poor sleep could then result in higher baseline
ABB levels, helping to explain the association with higher ABB
at RW (in the cluster showing SD effects) (Fig. 1A) and less
reported SH (Fig. 2A). In addition, SH negatively correlated with
ABB in the precuneus, putamen, and parahippocampus (Fig. 2B
and Table S3). These findings are consistent with studies show-
ing that chronic sleep restriction lead to elevated cortical Aβ
oligomers levels (that are neurotoxic) in the mouse cortex (43),
which might in part reflect up-regulation of β-secretase 1 (44).
However, a confounder is that increased ABB could in turn
exacerbate sleep problems (10).
It is noteworthy that ABB increases in the hippocampus are
less pronounced in MCI (45) or early-stage AD than in the
precuneus (22). Instead, changes in hippocampal volume, glu-
cose metabolism (30), and the bloodbrain barrier (46) were
most evident in patients with early-stage AD. Thus, it is possible
R² = 0.2522
Sleep Hours (SH)
Fig. 2. Relationship between SH, APOE genotype, and ABB. (A) Regression
of FBB SUVr (indexing ABB) for the red cluster shown in Fig. 1Aat RW
against SH. (B) Three-dimensional rendering of the areas showing an asso-
ciation between higher FBB SUVr at RW and lower SH (red clusters, P
0.05, cluster-size corrected) (Table S3), as well as areas showing an associa-
tion between higher FBB SUVr and higher APOE-based genetic risk for AD
(quantified as log of ORAD) (green clusters, P
<0.05, cluster-size cor-
rected, except the right-sided subcortical cluster, which was cluster size-
corrected at q
<0.05) (Table S4). The subcortical clusters related to SH and
ORAD had minimal spatial overlap (18 voxels, <3%) (Tables S3 and S4).
Notably, FBB SUVr within the SH-related subcortical clusters (red, B) was not
associated with ORAD (P=0.25) and FBB SUVr within the ORAD-related
subcortical clusters (green, B) was not associated with SH (P=0.2).
Shokri-Kojori et al. PNAS Latest Articles
that the increases in ABB in the hippocampus with sleep dis-
ruptions might trigger local neurotoxicity without necessarily
resulting in marked plaque accumulation. The precuneus was not
significantly affected by SD; however, we found an association
between reported SH and ABB in this region (Fig. 2Band Table
S3), again suggesting that distinct processes might mediate the
effects of acute vs. chronic SD on regional ABB. Future work
should investigate the extent to which the effects of acute SD and
less SH might reflect distinct mechanisms (i.e., neuro-
inflammation triggered by chronic poor sleep) (47, 48) or sen-
sitivity of FBB to different forms of Aβ(soluble oligomers vs.
plaques) (28). One limitation of this work includes the inability
of PET-FBB to distinguish soluble from insoluble Aβ(27, 28,
49). We suggested that the interruption of glymphatic clearance
by SD would increase ABB in the brain, yet our findings do not
demonstrate the mechanisms that account for the Aβaccumu-
lation with SD. In our study, estimates of ABB were obtained
using FBB SUVr, which is sensitive to physiological factors such
as blood flow, which could have been impacted by SD (50, 51).
However, recent evidence suggests that blood-flow effects are
small on FBB SUVr estimated with later time points (52)
(Methods). We also corroborated the FBB SUVr findings with
BPnd measures that are less sensitive to blood-flow effects
(Fig. S2).
In our study, we did not predict the laterality effect for the SD-
related increases in ABB, and while this could reflect the sen-
sitivity of the glymphatic system to orientation of the head during
sleep (14), we did not record head position. Consistent with the
recognized role of the hippocampus and thalamus in mood dis-
orders (53), the association between SD-related increases in
ABB and mood worsening (Fig. 1C) supported the functional
significance of elevated ABB. This association could reflect the
previously reported contribution of the hippocampus in modu-
lating mood changes that follow SD (54). The effects of SD on
the hippocampus have also been implicated in the memory im-
pairment associated with SD, although we did not measure ef-
fects of SD on memory in our study. Even though our sample was
small (n=20), we were able to identify a significant effect of SD
on brain ABB with no significant interaction with gender. Be-
cause of the small sample size of our study, future studies are
needed to assess the generalizability to a larger and more diverse
population and to more reliably characterize potential
gender effects.
In summary, this study documents an effect of one-night SD
on ABB in the hippocampus, thus providing preliminary evi-
dence that sleep, among other factors, could influence Aβ
clearance in the human brain. Our results highlight the relevance
of good sleep hygiene for proper brain function and as a po-
tential target for prevention of AD (31, 55).
Participants. Twenty-two healthy individuals were recruited at the National
Institutes of Health, of which 20 (10 females, age: 39.8 y ±10.4, range: 22
72 y old) completed two PET scan sessions to measure ABB. All participants
provided informed consent to participate in the study that was approved by
the Institutional Review Board at the NIH (Combined Neurosciences White
Panel). Exclusion criteria were: (i) urine positive for psychotropic drugs; (ii )
history of alcohol or drug use disorders; (iii ) present or past history of
neurological or psychiatric disorder, including evidence of cognitive im-
pairment; (iv) use of psychoactive medications in the past month (i.e., opiate
analgesics, stimulants, sedatives); (v) currently taking prescription medica-
tions (i.e., antihistamines, antihypertensive, antibiotics); (vi ) medical condi-
tions that may alter cerebral function; (vii ) cardiovascular and metabolic
diseases; and (viii) history of head trauma with loss of consciousness longer
than 30 min. Table S1 summarizes physiological and neuropsychological
assessment to ensure participants were healthy and were not cognitively
Structural MRI. Participants also underwent MRI in a 3.0 T Magnetom Prisma
scanner (Siemens Medical Solutions) using a 32-channel head coil to collect
T1-weighted 3D MPRAGE (TR/TE =2,400/2.24 ms, 0.8-mm isotropic resolu-
tion) and T2-weighted spin-echo multislice (TR/TE =3,200/564 ms, 0.8-mm in-
plane resolution). MRI was processed using the minimal preprocessing
pipeline of the Human Connectome Project (56). Specifically, FreeSurfer v5.3
(Martinos Center for Biomedical Imaging; https://surfer.nmr.mgh.harvard.
edu/) was used for anatomical data segmentation. In addition, each MRI
image underwent gradient distortion correction, field map processing,
spatial normalization to the stereotactic space of the Montreal Neurological
Institute (MNI) with 2-mm isotropic resolution, and brain masking using
routines from University of Oxfords Center for Functional Magnetic Reso-
nance Imaging of the Brain Software Library release 5.0 (https://fsl.fmrib.ox. FreeSurfer segmentation (wmparc.nii) in the MNI space
was used for generating a subject-specific mask of the hippocampus (label
numbers: 17 and 53 for left and right hippocampus, respectively).
PET Data Acquisition. The PET scans were performed using a high-resolution
research tomography Siemens scanner on two separate scan days with FBB.
FBB was injected through an intravenous catheter in about 1 min using a
Harvard pump. Dynamic scanning started immediately after FBB in-
jection, with 1.23-mm isotropic resolution using list-mode acquisition.
During the PET imaging procedures, the participants rested quietly under
dim illumination. To ensure that subjects did not fall asleep, they were
monitored throughout the procedure and asked to keep their eyes open
(no fixation cross). Information about head movement was collected
using a cap with small light reflectors and a Polaris Vicra (Northern Digital)
head-tracking system to minimize motion-related image blurring. Before
FBB injection, a transmission scan was obtained using cesium-137 to correct
for attenuation.
FBB-PET Scans. Each participant underwent two FBB-PET scans to measure
ABB, one scan on a day following RW and another scan on a day following a
night of SD. For this purpose, participants stayed overnight at the Clinical
Center at the NIH before their scheduled SD or RW scans. For the SD condition,
participants were instructed to wake up at 8:00 AM on the morning before
the SD night. Upon arrival, participants were continuously accompanied by a
nurse to ensure that they stayed awake for the SD condition during their stay.
For the RW conditions, nurses observed whether patients were asleep every
hour from 10:00 PM to 7:00 AM. On the day of RW, the participants were
woken up at 7:00 AM. On both days, participants remained under supervision
of the nurse and were brought to the PET imaging center before the scan,
which started around 1:30 PM. Thus, participants remained awake for a total
of about 31 h (including the scan length) during the SD condition. No food
was given after midnight and caffeinated beverages were discontinued 24 h
before the study. Patients had a light breakfast and lunch on the scan day. The
order of RW and SD scans was counterbalanced across subjects and were, on
average, 15 d apart (standard deviation =19 d). In preparation for the scans,
a catheter was placed for radiotracer injection. Dynamic scanning started
right after intravenous injection of about 9.5 mCi (or less) of FBB, which
lasted for 120 min. During FBB scans, participants were encouraged to listen
to music to stay awake.
PET Data Analysis. FBB uptake in the brain was quantified using the SUVr
using the whole cerebellum as reference region for images obtained from
later time points (90110 min) (57, 58). We chose the SUVr method given the
recent evidence (for a radiotracer from the same family as FBB) that the
SUVr approach of estimating tracer accumulation, relative to other non-
invasive kinetic modeling approaches, had one of the highest correlations,
with arterial input compartment modeling results (R
=0.95), and had
comparable accuracy, while maintaining much simpler modeling require-
ments and not suffering from voxel-level noise on model fitting (59). Despite
the concern that SUVr estimates of radiotracer accumulation are affected by
confounds such as blood-flow changes, recent work has suggested a limited
influence of blood-flow changes on FBB SUVr measures obtained from the
later time points, similar to the range used in our study (i.e., 90110 min)
(52). SUVr images for FBB were coregistered with individual subjectsT1-
weighted images and resampled into 2-mm isotropic resolution before be-
ing transformed into the MNI space using the same normalization param-
eters that were generated for T1-weighted (and T2-weighted) images. For
statistical parametric mapping, images were smoothed with a 4-mm kernel
and masked at 0.5 SUVr to remove voxels outside the brain. We also per-
formed a follow-up BPnd analysis to address the concern that FBB SUVr
might have been affected by confounds, such as changes in blood flow and
tracer clearance properties (52, 60). Specifically, regional BPnd was
| Shokri-Kojori et al.
calculated using a noninvasive simplified reference tissue model (SRTM) (61,
62) that was fitted to the time activity curve (0120 min) derived from the
subcortical cluster showing a significant effect of SD on FBB SUVr (Fig. 1A).
We also corroborated SRTM-based BPnd findings using the reference Logan
approach (Fig. S2) (59, 63). Kinetic modeling of dynamic PET data was per-
formed in the PMOD Kinetic Modeling Tool v3.605 (PMOD Technologies).
For consistency with the SUVr approach, the whole cerebellum was used as
the reference region for the BPnd analyses.
Pittsburgh Sleep Quality Index. The PSQI questionnaire (64) was administered
to all participants (n=20). For the analyses, we used the number of SH and
the TS quality score from the PSQI, because prior studies have linked these
sleep measures to brain ABB (6, 65, 66). While SH is a self-report of partici-
pantsSH at night (excluding times spent awake in bed), TS is a composite of
scores of sleep quality, latency, hours, efficiency, medication, disturbances
because of ones health or sleep partners, and daytime life quality (lower TS
indicates better sleep quality).
APOE Genotyping. SNPs of the APOE gene (rs7412 and rs429358) have been
shown to influence brain glucose metabolism and ABB (67, 68). Accordingly,
in all participants we genotyped rs7412 and rs429358 SNPs of APOE and
computed a log of ORAD for each participant, following the methods of a
previous study (69), normalized relative to the population risk for AD. We
used ORAD to evaluate whether APOE influenced the association between
sleep and ABB.
Mood Questionnaires. Mood questionnaires were collected periodically (five
times) throughout the RW and SD scans in 18 of the 20 participants. Ques-
tionnaires were acquired at least an hour apart, prior (three measures),
during (one measure), and after (one measure) the PET scans. On a scale of 0
10, subjects rated whether they felt alert, tired, hungry, friendly, happy, sad,
anxious, irritable, social, confused, bored, comfortable, energetic, caffeine
craving, and difficulty staying awake. The scores across the five time-points
were averaged for each mood measure for each scan day. The first principle
component of the standardized SDRW difference scores for the 15 self-
report mood measures was computed to summarize the change in mood
from RW to SD into one component. This component accounted for 35.5%
of the variance of the mood change measures (SDRW) and was positively
correlated with changes in ratings of feeling alert, friendly, happy, social,
and energetic (P<0.01, two-tailed), and negatively correlated with changes
in ratings of feeling tired, anxious, and irritable from RW to SD (P<0.01,
two-tailed). Higher scores along this component reflected positive changes
in mood from RW to SD.
Statistical Parametric Mapping. SPM8 (Wellcome Trust Centre for Neuro-
imaging) (70) was used for performing a voxelwise paired ttest between SD
and RW in FBB SUVr and voxelwise correlation between behavioral or
genotyping measures and PET data. All effects were thresholded at P
0.015 in SPM8 and a minimum cluster size of 300 voxels (2-mm isotropic). We
chose this threshold based on the low sensitivity of FBB to soluble Aβ(28),
but effects were corrected for multiple comparisons for cluster size using the
random field theory (71) (family-wise error, FWE), or unless indicated, with
false-discovery rate (FDR) in SPM8.
Data Availability. Subject-level measures used in the manuscript are available
in Dataset S1. Please contact corresponding authors for additional
ACKNOWLEDGMENTS. We thank Joanna Fowler for the insightful com-
ments; Christopher Wong, Lori Talagala, and Minoo McFarland for their
assistance with behavioral and imaging data collection; David Goldman, Hui
Sun, and Melanie Schwandt for assistance with APOE genotyping; Jeih-San
Liow and Santi Bullich for insights about PET data analysis; and Kimberly
Herman, Tom Lionetti, and Rosa Clark for assistance with monitoring
participants. This work was supported by NIH/National Institute on Alcohol
Abuse and Alcoholism intramural research program (Grant Y1AA3009).
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| Shokri-Kojori et al.
... Sleep disorders are indeed associated with worse outcomes in older adults, such as increased Aβ burden, more symptoms of depression and cognitive decline (Winer et al., 2021). Positron emission tomography with 18 F-florbetaben showed that one night of sleep deprivation induced a 5% increase in Aβ levels (Shokri-Kojori et al., 2018). In rodents, Aβ clearance in the brain interstitial fluid (ISF) occurs mainly during sleep, which is ascribed to the glymphatic pathway that operates most efficiently during sleep (Xie et al., 2013;Lee et al., 2015). ...
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Introduction Alzheimer’s disease (AD) is a progressive neurodegenerative disease that results in cognitive impairment and is often accompanied by anxiety. In this study, we investigated whether the activation of VTA Vgat neurons could reduce anxiety in APP/PS1 mice. We hypothesized that acute social defeat stress (SDS) would lead to anxiety in APP/PS1 mice, and that the activation of VTA Vgat neurons would alleviate this anxiety. Methods We exposed APP/PS1 mice to acute SDS and assessed anxiety using the open field test and elevated plus-arm test. Activated VTA Vgat neurons was tested by cfos staining. Sleep quality was detected using electroencephalogram after SDS or non-SDS procedure. Sleep duration, sleep latency, and non-rapid eye movement (NREM) percentage were analyzed. VTA Vgat neurons were chemogenetically activated by deschloroclozapine. Results Our results showed that acute SDS led to anxiety in APP/PS1 mice, as evidenced by increased anxiety-related behaviors in the open field and elevated plus-arm tests. Activation of VTA Vgat neurons by SDS led to an increase in sleep duration, primarily due to a decrease in sleep latency and an increase in NREMs. However, the quality of sleep was poor. Chemogenetical activation of VTA Vgat neurons improved sleep quality and relieved SDS-induced anxiety. Furthermore, the anxiety state correlated negatively with sleep duration and NREM percentage and correlated positively with theta power density in APP/PS1 mice. Discussion Our study provides evidence that the activation of VTA Vgat neurons alleviates SDS-induced anxiety in APP/PS1 mice, suggesting that poor sleep quality may exacerbate anxiety in AD. These findings may have important implications for the treatment of anxiety in AD, as targeting VTA Vgat neurons could be a potential therapeutic approach.
... Alternating periods of damaged protein accumulation followed quickly by brain washing may be a key process in maintaining healthy neural tissue. Sleep deprivation exaggerates Aβ accumulation in the brain [54]. The reduced waste removal can be caused by a single night of sleeplessness or light exposure, e.g., in night shift workers. ...
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The brain lacks a classic lymphatic drainage system. How it is cleansed of damaged proteins, cellular debris, and molecular by-products has remained a mystery for decades. Recent discoveries have identified a hybrid system that includes cerebrospinal fluid (CSF)-filled perivascular spaces and classic lymph vessels in the dural covering of the brain and spinal cord that functionally cooperate to remove toxic and non-functional trash from the brain. These two components functioning together are referred to as the glymphatic system. We propose that the high levels of melatonin secreted by the pineal gland directly into the CSF play a role in flushing pathological molecules such as amyloid-β peptide (Aβ) from the brain via this network. Melatonin is a sleep-promoting agent, with waste clearance from the CNS being highest especially during slow wave sleep. Melatonin is also a potent and versatile antioxidant that prevents neural accumulation of oxidatively-damaged molecules which contribute to neurological decline. Due to its feedback actions on the suprachiasmatic nucleus, CSF melatonin rhythm functions to maintain optimal circadian rhythmicity, which is also critical for preserving neurocognitive health. Melatonin levels drop dramatically in the frail aged, potentially contributing to neurological failure and dementia. Melatonin supplementation in animal models of Alzheimer’s disease (AD) defers Aβ accumulation, enhances its clearance from the CNS, and prolongs animal survival. In AD patients, preliminary data show that melatonin use reduces neurobehavioral signs such as sundowning. Finally, melatonin controls the mitotic activity of neural stem cells in the subventricular zone, suggesting its involvement in neuronal renewal.
... In humans, there are similar findings, as even the effects of acute sleep deprivation for one night or slowwave sleep disruption are sufficient to cause amyloid-β accumulation in the CSF, as well as in chronic sleep-deprived patients with insomnia, increasing the risk for dementia [114,200]. Also, a recent publication exploring the connection between AQP4 and human sleep-awake regulation effects on cognitive function after sleep loss showed that NREM slow waves regulate CSF flow machinery [134]. ...
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According to the World Health Organization, about one-third of the population experiences insomnia symptoms, and about 10-15% suffer from chronic insomnia, the most common sleep disorder. Sleeping difficulties associated with insomnia are often linked to chronic sleep deprivation, which has a negative health impact partly due to disruption in the internal synchronisation of biological clocks. These are regulated by clock genes and modulate most biological processes. Most studies addressing circadian rhythm regulation have focused on the role of neurons, yet glial cells also impact circadian rhythms and sleep regulation. Chronic insomnia and sleep loss have been associated with glial cell activation, exacerbated neuroinflammation, oxidative stress, altered neuronal metabolism and synaptic plasticity, accelerated age-related processes and decreased lifespan. It is, therefore, essential to highlight the importance of glia-neuron interplay on sleep/circadian regulation and overall healthy brain function. Hence, in this review, we aim to address the main neurobiological mechanisms involved in neuron-glia crosstalk, with an emphasis on microglia and astrocytes, in both healthy sleep, chronic sleep deprivation and chronic insomnia.
... Studies have shown Aβ levels in cerebrospinal fluid (CSF) increase throughout the day and fall away overnight, as well as a relationship between fragmented sleep and increased amyloid burden [26]. Additionally, other studies have linked sleep deprivation with increased Aβ and extracellular tau, both linked to the pathology of AD [27][28][29]. In humans, sleep deprivation has been shown to promote neuroinflammation through the increased production of pro-inflammatory cytokines including the interleukins IL-1β, IL-6 and IL-17 [30]. ...
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The need to identify new potentially druggable biochemical mechanisms for Alzheimer’s disease (AD) is an ongoing priority. The therapeutic limitations of amyloid-based approaches are further motivating this search. Amino acid metabolism, particularly tryptophan metabolism, has the potential to emerge as a leading candidate and an alternative exploitable biomolecular target. Multiple avenues support this contention. Tryptophan (trp) and its associated metabolites are able to inhibit various enzymes participating in the biosynthesis of β-amyloid, and one metabolite, 3-hydroxyanthranilate, is able to directly inhibit neurotoxic β-amyloid oligomerization; however, whilst certain trp metabolites are neuroprotectant, other metabolites, such as quinolinic acid, are directly toxic to neurons and may themselves contribute to AD progression. Trp metabolites also have the ability to influence microglia and associated cytokines in order to modulate the neuroinflammatory and neuroimmune factors which trigger pro-inflammatory cytotoxicity in AD. Finally, trp and various metabolites, including melatonin, are regulators of sleep, with disorders of sleep being an important risk factor for the development of AD. Thus, the involvement of trp biochemistry in AD is multifactorial and offers a plethora of druggable targets in the continuing quest for AD therapeutics.
Dysfunction of the glymphatic system, an intracranial clearance pathway that drains misfolded proteins, has been implicated in the onset of Parkinson's disease (PD). Recently, the coupling strength of global blood-oxygen-level-dependent (gBOLD) signals and cerebrospinal fluid (CSF) inflow dynamics have been suggested to be an indicator of glymphatic function. Using resting-state functional magnetic resonance imaging (MRI), we quantified gBOLD-CSF coupling strength as the cross-correlation between baseline gBOLD and CSF inflow signals to evaluate glymphatic function and its association with the clinical manifestations of PD. We found that gBOLD-CSF coupling in drug-naïve PD patients was significantly weaker than that in normal controls, but significantly stronger in patients less affected by sleep disturbances than in those more affected by sleep disturbances, based on the PD sleep scale. Furthermore, we collected longitudinal data from patients and found that baseline gBOLD-CSF coupling negatively correlated with the rate of change over time, but positively correlated with the rate of change in UPDRS-III scores. In conclusion, severe gBOLD-CSF decoupling in PD patients may reflect longitudinal motor impairment, thereby providing a potential marker of glymphatic dysfunction in PD.
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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder pathologically characterized by brain parenchymal abundance of amyloid-beta (Aβ) and the accumulation of lipofuscin material that is rich in neutral lipids. However, the mechanisms for aetiology of AD are presently not established. There is increasing evidence that metabolism of lipoprotein-Aβ in blood is associated with AD risk, via a microvascular axis that features breakdown of the blood-brain barrier, extravasation of lipoprotein-Aβ to brain parenchyme and thereafter heightened inflammation. A peripheral lipoprotein-Aβ/capillary axis for AD reconciles alternate hypotheses for a vascular, or amyloid origin of disease, with amyloidosis being probably consequential. Dietary fats may markedly influence the plasma abundance of lipoprotein-Aβ and by extension AD risk. Similarly, apolipoprotein E (Apo E) serves as the primary ligand by which lipoproteins are cleared from plasma via high-affinity receptors, for binding to extracellular matrices and thereafter for uptake of lipoprotein-Aβ via resident inflammatory cells. The epsilon APOE ε4 isoform, a major risk factor for AD, is associated with delayed catabolism of lipoproteins and by extension may increase AD risk due to increased exposure to circulating lipoprotein-Aβ and microvascular corruption.
Sleep loss pervasively affects the human brain at multiple levels. Age-related changes in several sleep characteristics indicate that reduced sleep quality is a frequent characteristic of aging. Conversely, sleep disruption may accelerate the aging process, yet it is not known what will happen to the age status of the brain if we can manipulate the sleep conditions. To tackle this question, we employed an approach of brain age to investigate whether sleep loss would cause age-related changes in the brain. We included MRI data of 134 healthy volunteers (mean chronological age of 25.3, between the age of 19 and 39, 42 females/92 males) from five datasets with different sleep conditions. Across three datasets with the condition of total sleep deprivation (> 24 hours of prolonged wakefulness), we consistently observed that total sleep deprivation increased brain age by 1-2 years regarding the group mean difference with the baseline. Interestingly, after one night of recovery sleep, brain age was not different from baseline. We also demonstrated the associations between the change in brain age after total sleep deprivation and the sleep variables measured during the recovery night. By contrast, brain age was not significantly changed by either acute (3 hours’ time-in-bed for 1 night) or chronic partial sleep restriction (5 hours’ time-in-bed for 5 continuous nights). Taken together, the convergent findings indicate that acute total sleep loss changes brain morphology in an aging-like direction in young participants and that these changes are reversible by recovery sleep. SIGNIFICANCE STATEMENT: Sleep is fundamental for humans to maintain normal physical and psychological functions. Experimental sleep deprivation is a variable-controlling approach to engaging the brain among different sleep conditions for investigating the brain’s responses to sleep loss. Here, we quantified the brain’s response to sleep deprivation by using the change of brain age predictable with brain morphological features. In three independent datasets, we consistently found increased brain age after total sleep deprivation, which was associated with the change in sleep variables. Moreover, no significant change in brain age was found after partial sleep deprivation in another two datasets. Our study provided new evidence to explain the brain-wide effect of sleep loss in an aging-like direction.
Although both nonrapid eye movement (NREM) sleep loss and rapid eye movement (REM) sleep loss exacerbate Alzheimer's disease (AD) progression, they exert different effects. Microglial activation can be beneficial or detrimental to AD patients under different conditions. However, few studies have investigated which sleep stage is the main regulator of microglial activation or the downstream effects of this activation. We aimed to explore the roles of different sleep phases in microglial activation and to investigate the possible effect of microglial activation on AD pathology. In this study, thirty-six 6-month-old APP/PS1 mice were equally divided into 3 groups: the stress control (SC), total sleep deprivation (TSD), and REM deprivation (RD) groups. All mice underwent a 48-hour intervention before their spatial memory was assessed using a Morris water maze (MWM). Then, microglial morphology, activation- and synapse-related protein expression, and inflammatory cytokine and amyloid β (Aβ) levels in hippocampal tissues were measured. We found that the RD and TSD groups exhibited worse spatial memory in the MWM tests. In addition, the RD and TSD groups showed greater microglial activation, higher inflammatory cytokine levels, lower synapse-related protein expression and more severe Aβ accumulation than the SC group, but there were no significant differences between the RD and TSD groups. This study demonstrates that disturbance of REM sleep may activate microglia in APP/PS1 mice. These activated microglia may promote neuroinflammation and engulf synapses but show a weakened ability to clear plaques.
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We aimed to investigate the association of subjective sleep characteristics and plasma Alzheimer’s disease (AD) biomarkers in older cognitively unimpaired adults with higher amyloid-β (Aβ) burden. Unimpaired cognition was determined by education-adjusted performance for the Mini-Mental State Examination and exclusion of dementia and mild cognitive impairment via standardized neuropsychological tests. We used Pittsburgh Sleep Quality Index (PSQI) to assess subjective sleep quality. The participants also underwent examination of plasma AD biomarkers and ¹⁸F-florbetapir PET scan. Correlation and multiple linear regression analyses were used to investigate the association between subjective sleep characteristics and AD biomarkers. A total of 335 participants were included and 114 were Aβ-PET positive. Multivariable regression analysis showed sleep duration > 8 h and sleep disturbance were associated with Aβ deposition in total participants. Two multiple linear regression models were applied and the results revealed in participants with Aβ-PET (+), falling asleep at ≥ 22:00 to ≤ 23:00 was associated with higher levels of Aβ42 and Aβ42/40. Other associations with higher Aβ42/40 and standard uptake value ratio contained sleep efficiency value, sleep efficiency ≥ 75%, no/mild daytime dysfunction and PSQI score ≤ 5. Higher p-Tau-181 level was associated with sleep latency > 30 min in Aβ-PET (+) group and moderate/severe sleep disturbance in Aβ-PET (–) group. Our data suggests sleep duration ≤ 8 h and no/mild sleep disturbance may be related to less Aβ burden. In participants with Aβ deposition, falling asleep at 22:00 to 23:00, higher sleep efficiency (at least ≥ 75%), no/mild daytime dysfunction, sleep latency ≤ 30 min, and good sleep quality may help improve AD pathology.
Introduction: Past research on Alzheimer's disease (AD) has focused on biomarkers, cognition, and neuroimaging as primary predictors of its progression, albeit additional ones have recently gained attention. When turning to the prediction of the progression from one stage to another, one could benefit from the joint assessment of imaging-based biomarkers and risk/protective factors. Methods: We included 86 studies that fulfilled our inclusion criteria. Results: Our review summarizes and discusses the results of 30 years of longitudinal research on brain changes assessed with neuroimaging and the risk/protective factors and their effect on AD progression. We group results into four sections: genetic, demographic, cognitive and cardiovascular, and lifestyle factors. Discussion: Given the complex nature of AD, including risk factors could prove invaluable for a better understanding of AD progression. Some of these risk factors are modifiable and could be targeted by potential future treatments.
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The amyloid-β protein (Aβ) protein plays a pivotal role in the pathogenesis of Alzheimer’s disease (AD). It is believed that Aβ deposited in the brain originates from the brain tissue itself. However, Aβ is generated in both brain and peripheral tissues. Whether circulating Aβ contributes to brain AD-type pathologies remains largely unknown. In this study, using a model of parabiosis between APPswe/PS1dE9 transgenic AD mice and their wild-type littermates, we observed that the human Aβ originated from transgenic AD model mice entered the circulation and accumulated in the brains of wild-type mice, and formed cerebral amyloid angiopathy and Aβ plaques after a 12-month period of parabiosis. AD-type pathologies related to the Aβ accumulation including tau hyperphosphorylation, neurodegeneration, neuroinflammation and microhemorrhage were found in the brains of the parabiotic wild-type mice. More importantly, hippocampal CA1 long-term potentiation was markedly impaired in parabiotic wild-type mice. To the best of our knowledge, our study is the first to reveal that blood-derived Aβ can enter the brain, form the Aβ-related pathologies and induce functional deficits of neurons. Our study provides novel insight into AD pathogenesis and provides evidence that supports the development of therapies for AD by targeting Aβ metabolism in both the brain and the periphery.
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Background: Sleep is an important physiological process and beneficial in the removal of brain metabolites and functional recovery. Prior studies have shown that sleep disorders are significant risk factors for Alzheimer's disease (AD). Objective: The present study was designed to characterize the effect of short-term total sleep deprivation (TSD) on plasma amyloid-β (Aβ) concentrations. Methods: A clinical trial was conducted between March 1, 2016, and April 1, 2016. Twenty volunteers (age 27.3±3.4 years) with normal cognitive function and sleeping habits were recruited from the local population. Participants underwent 24 h of TSD. Periprocedural blood samples were collected to compare the changes of plasma Aβ42, Aβ40, low-density lipoprotein receptor-related protein (sLRP-1), soluble receptors for advanced glycation end products (sRAGE), and serum superoxide dismutase (SOD) and malonaldehyde (MDA). Results: TSD increased morning plasma Aβ40 levels by 32.6% (p < 0.001) and decreased the Aβ42/Aβ40 ratio by 19.3% (p < 0.001). A positive relationship was found between TSD duration and plasma Aβ40 level (r = 0.51, p < 0.001) and Aβ40/Aβ42 ratio (r = 0.25, p = 0.003). Plasma concentrations of sLRP1 (p = 0.018) and sRAGE (p = 0.001) decreased significantly after TSD. Aβ40 and Aβ42 plasma concentrations correlated with plasma levels of sLRP1 and sRAGE. Serum SOD decreased after TSD (p = 0.005), whereas serum MDA was increased (p = 0.001). Conclusion: Sleep deprivation can lead to an elevation of plasma Aβ40 and decrease of the Aβ42/Aβ40 ratio. The underlying mechanisms may be related to increased oxidative stress and impaired peripheral Aβ clearance as pathomechanisms of AD.
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Electrical oscillations generated by neural circuits are disrupted in Alzheimer's disease. Restoring these oscillations in mouse models activates immune cells to clear disease-associated amyloid-[beta] protein from the brain. See Article p.230
Sleep disturbances are associated with future risk of Alzheimer's disease. Disrupted sleep increases soluble amyloid-β, suggesting a mechanism for sleep disturbances to increase Alzheimer's disease risk. We tested this response in humans using indwelling lumbar catheters to serially sample cerebrospinal fluid while participants were sleep-deprived, treated with sodium oxybate, or allowed to sleep normally. All participants were infused with ¹³C6-leucine to measure amyloid-β kinetics. We found that sleep deprivation increased overnight amyloid-β-38, amyloid-β-40, and amyloid-β-42 levels by 25-30% via increased overnight amyloid-β production relative to sleeping controls. These findings suggest that disrupted sleep increases Alzheimer's disease risk via increased amyloid-β production. This article is protected by copyright. All rights reserved.
Accurate amyloid PET quantification is necessary for monitoring amyloid-beta accumulation and response to therapy. Currently, most of the studies are analyzed using the static standardized uptake value ratio (SUVR) approach because of its simplicity. However, this approach may be influenced by changes in cerebral blood flow (CBF) or radiotracer clearance. Full tracer kinetic models require arterial blood sampling and dynamic image acquisition. The objectives of this work were: (1) to validate a non-invasive kinetic modeling approach for 18F-florbetaben PET using an acquisition protocol with the best compromise between quantification accuracy and simplicity and (2) to assess the impact of CBF changes and radiotracer clearance on SUVRs and non-invasive kinetic modeling data in 18F-florbetaben PET. Methods: Data from twenty subjects (10 patients with probable Alzheimer's dementia/ 10 healthy volunteers) were used to compare the binding potential (BPND) obtained from the full kinetic analysis to the SUVR and to non-invasive tracer kinetic methods (simplified reference tissue model (SRTM), and multilinear reference tissue model 2 (MRTM2)). Different approaches using shortened or interrupted acquisitions were compared to the results of the full acquisition (0-140 min). Simulations were carried out to assess the effect of CBF and radiotracer clearance changes on SUVRs and non-invasive kinetic modeling outputs. Results: A 0-30 and 120-140 min dual time-window acquisition protocol using appropriate interpolation of the missing time points provided the best compromise between patient comfort and quantification accuracy. Excellent agreement was found between BPND obtained using full and dual time-window (2TW) acquisition protocols (BPND,2TW=0.01+ 1.00 BPND,FULL, R2=0.97 (MRTM2); BPND,2TW= 0.05+ 0.92·BPND,FULL, R2=0.93 (SRTM)). Simulations showed a limited impact of CBF and radiotracer clearance changes on MRTM parameters and SUVRs. Conclusion: This study demonstrates accurate non-invasive kinetic modeling of 18F-florbetaben PET data using a dual time-window acquisition protocol, thus providing a good compromise between quantification accuracy, scan duration and patient burden. The influence of CBF and radiotracer clearance changes on amyloid-beta load estimates was small. For most clinical research applications, the SUVR approach is appropriate. However, for longitudinal studies in which a maximum quantification accuracy is desired, this non-invasive dual time-window acquisition protocol and kinetic analysis is recommended.
See Mander et al. (doi:10.1093/awx174) for a scientific commentary on this article. Sleep deprivation increases amyloid-β, suggesting that chronically disrupted sleep may promote amyloid plaques and other downstream Alzheimer’s disease pathologies including tauopathy or inflammation. To date, studies have not examined which aspect of sleep modulates amyloid-β or other Alzheimer’s disease biomarkers. Seventeen healthy adults (age 35–65 years) without sleep disorders underwent 5–14 days of actigraphy, followed by slow wave activity disruption during polysomnogram, and cerebrospinal fluid collection the following morning for measurement of amyloid-β, tau, total protein, YKL-40, and hypocretin. Data were compared to an identical protocol, with a sham condition during polysomnogram. Specific disruption of slow wave activity correlated with an increase in amyloid-β40 (r = 0.610, P = 0.009). This effect was specific for slow wave activity, and not for sleep duration or efficiency. This effect was also specific to amyloid-β, and not total protein, tau, YKL-40, or hypocretin. Additionally, worse home sleep quality, as measured by sleep efficiency by actigraphy in the six nights preceding lumbar punctures, was associated with higher tau (r = 0.543, P = 0.045). Slow wave activity disruption increases amyloid-β levels acutely, and poorer sleep quality over several days increases tau. These effects are specific to neuronally-derived proteins, which suggests they are likely driven by changes in neuronal activity during disrupted sleep.
Cerebral small vessel diseases (SVDs) range broadly in etiology but share remarkably overlapping pathology. Features of SVD including enlarged perivascular spaces (EPVS) and formation of abluminal protein deposits cannot be completely explained by the putative pathophysiology. The recently discovered glymphatic system provides a new perspective to potentially address these gaps. This work provides a comprehensive review of the known factors that regulate glymphatic function and the disease mechanisms underlying glymphatic impairment emphasizing the role that aquaporin-4 (AQP4)-lined perivascular spaces (PVSs), cerebrovascular pulsatility, and metabolite clearance play in normal CNS physiology. This review also discusses the implications that glymphatic impairment may have on SVD inception and progression with the aim of exploring novel therapeutic targets and highlighting the key questions that remain to be answered.
Objective: To evaluate the association between sleep duration and the risk of incident dementia and brain aging. Methods: Self-reported total hours of sleep were examined in the Framingham Heart Study (n = 2,457, mean age 72 ± 6 years, 57% women) as a 3-level variable: <6 hours (short), 6-9 hours (reference), and >9 hours (long), and was related to the risk of incident dementia over 10 years, and cross-sectionally to total cerebral brain volume (TCBV) and cognitive performance. Results: We observed 234 cases of all-cause dementia over 10 years of follow-up. In multivariable analyses, prolonged sleep duration was associated with an increased risk of incident dementia (hazard ratio [HR] 2.01; 95% confidence interval [CI] 1.24-3.26). These findings were driven by persons with baseline mild cognitive impairment (HR 2.83; 95% CI 1.06-7.55) and persons without a high school degree (HR 6.05; 95% CI 3.00-12.18). Transitioning to sleeping >9 hours over a mean period of 13 years before baseline was associated with an increased risk of all-cause dementia (HR 2.43; 95% CI 1.44-4.11) and clinical Alzheimer disease (HR 2.20; 95% CI 1.17-4.13). Relative to sleeping 6-9 hours, long sleep duration was also associated cross-sectionally with smaller TCBV (β ± SE, -1.08 ± 0.41 mean units of TCBV difference) and poorer executive function (β ± SE, -0.41 ± 0.13 SD units of Trail Making Test B minus A score difference). Conclusions: Prolonged sleep duration may be a marker of early neurodegeneration and hence a useful clinical tool to identify those at a higher risk of progressing to clinical dementia within 10 years.
Aims: To clarify the correlation between chronic sleep restriction (CSR) and sporadic Alzheimer disease (AD), we determined in wild-type mice the impact of CSR, on cognitive performance, beta-amyloid (Aβ) peptides, and its feed-forward regulators regarding AD pathogenesis. Methods: Sixteen nine-month-old C57BL/6 male mice were equally divided into the CSR and control groups. CSR was achieved by application of a slowly rotating drum for 2 months. The Morris water maze test was used to assess cognitive impairment. The concentrations of Aβ peptides, amyloid precursor protein (APP) and β-secretase 1 (BACE1), and the mRNA levels of BACE1 and BACE1-antisense (BACE1-AS) were measured. Results: Following CSR, impairments of spatial learning and memory consolidation were observed in the mice, accompanied by Aβ plaque deposition and an increased Aβ concentration in the prefrontal and temporal lobe cortex. CSR also upregulated the β-secretase-induced cleavage of APP by increasing the protein and mRNA levels of BACE1, particularly the BACE1-AS. Conclusions: This study shows that a CSR accelerates AD pathogenesis in wild-type mice. An upregulation of the BACE1 pathway appears to participate in both cortical Aβ plaque deposition and memory impairment caused by CSR. BACE1-AS is likely activated to initiate a cascade of events that lead to AD pathogenesis. Our study provides, therefore, a molecular mechanism that links CSR to sporadic AD.
As the older segment of our population grows, cognitive decline and dementia will increase in prevalence, with Alzheimer's disease (AD) as the cause in most cases. Until a cure exists, prevention through the identification and manipulation of modifiable risk factors for dementia, in general, or AD, in particular, will be our only means of reducing dementia prevalence or delaying its onset. Furthermore, it is likely that eventual treatments for AD, when available, will depend on the ability to identify individuals at greatest risk for developing AD. Sleep disturbances are common in later life – roughly half of older adults experience regular insomnia (Ohayon, 2002) and about as many have some degree of sleep-disordered breathing (SDB) (Ancoli-Israel et al. , 1991) – and accumulating evidence suggests they may contribute to cognitive decline, at least in part, by promoting the development of AD pathology (Spira et al. , 2014). Because they are treatable, sleep disturbances are an important potential target for ongoing study in AD prevention. Moreover, understanding the mechanisms underlying an effect of sleep on subsequent cognitive decline and AD would allow for better identification of opportunities and optimal timing for treatment of sleep disorders, and ultimately perhaps, AD prevention.