Effects of BDNF Val66Met polymorphism on brain
metabolism in Alzheimer’s disease
Cunlu Xua,b, Zhenhua Wanga,b, Ming Fana, Bing Liua, Ming Songa,
Xiantong Zhenband Tianzi Jianga; Alzheimer’s Disease Neuroimaging
Earlier studies showed that the Val66Met polymorphisms
of the brain-derived neurotrophic factor differentially affect
gray matter volume and brain region activities. This study
used resting positron emission tomography to investigate
the relationship between the polymorphisms of Val66Met
and the regional cerebral metabolic rate in the brain.
We analyzed the positron emission tomography images of
215 patients from the Alzheimer’s Disease Neuroimaging
Initiative and found significant differences in the
parahippocampal gyrus, superior temporal gyrus,
prefrontal cortex, and inferior parietal lobule when
comparing Met carriers with noncarriers among both the
normal controls and those with mild cognitive impairment.
For those with Alzheimer’s disease, we also found
additional differences in the bilateral insula between the
carriers and noncarriers. NeuroReport 21:802–807? c 2010
Wolters Kluwer Health | Lippincott Williams & Wilkins.
NeuroReport 2010, 21:802–807
Keywords: Alzheimer’s disease, brain-derived neurotrophic factor, cerebral
metabolic rate for glucose, polymorphism, positron emission tomography
aLIAMA Center for Computational Medicine, National Laboratory of Pattern
Recognition, Institute of Automation, Chinese Academy of Sciences,
Beijing andbSchool of Information Science and Engineering, Lanzhou University,
Correspondence to Professor Tianzi Jiang, PhD, LIAMA Center for Computational
Medicine, National Laboratory of Pattern Recognition, Institute of Automation,
Chinese Academy of Sciences, Beijing 100190, China
Tel: +86 10 8261 4469; fax: +86 10 6255 1993; e-mail: firstname.lastname@example.org
Cunlu Xu, Zhenhua Wang, and Ming Fan contributed equally to this study
Received 22 April 2010 accepted 2 June 2010
Alzheimer’s disease is a neurodegenerative disorder
characterized by severe cognitive impairment and neuro-
fibrillary tangles , and shows disrupted functional
neuronal metabolic activity in specific brain regions
[2–4]. Several neuroimaging studies have reported that
patients with Alzheimer’s disease have lower cerebral
metabolism in the bilateral posterior cingulated cortex,
precuneus, and temporal–parietal cortex  and in the
temporal, parietal, and prefrontal lobes , compared
with clinically normal controls.
Brain-derived neurotrophic factor (BDNF) is a member
of the ‘neurotrophin’ family of growth factors related to
the nerve growth factor, which is critical for the survival
and maintenance of sympathetic and sensory neurons
. Without the nerve growth factor, the sympathetic
and sensory neurons will undergo apoptosis. In the BDNF
gene, which is located on chromosome 11p14, the
Val66Met allele is another candidate for a common single
nucleotide polymorphism, which affects Alzheimer’s
disease [6,7]. The BDNF Met allele has been reported
to be related to cognitive function , human memory
function,  and anxiety-related behavior . A func-
tional MRI study on adolescents experiencing anxiety
and depression reported that Met carriers showed greater
activation in the hippocampus and the amygdala in
response to emotional stimuli than was observed for non-
In brain morphology studies, the hippocampus and the
temporal cortex exhibited a progressive loss in gray
matter from the effect of the BDNF Met allele according
to an Alzheimer’s disease study . Moreover, the
BDNF Met allele is associated with reduced volumes in
the prefrontal cortex, hippocampus, parahippocampal
gyrus, and amygdala in normal individuals and patients
with schizophrenia and major depression . It has been
already shown that the effect of the Val66Met poly-
morphism on reduced gray matter occurs in some specific
regions, such as the prefrontal lobe  and the
All of the above reports pointed out that each specific
BDNF Val66Met polymorphism causes different effects
in the development of Alzheimer’s disease. Although
these inferences are helpful, glucose metabolism in the
brain, as measured by PET technology, is what has
typically been used to assess the severity of brain disease;
so establishing glucose metabolism alterations would
yield more specific information connecting Alzheimer’s
disease with genetic differences. However, the effects of
*Data used in the preparation of this article were obtained from the Alzheimer’s
Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI).
As such, the investigators within the ADNI contributed to the design and
implementation of ADNI and/or provided data but did not participate in analysis or
writing of this report. ADNI investigators include (complete listing available at
0959-4965 ? c 2010 Wolters Kluwer Health | Lippincott Williams & Wilkins
BDNF polymorphisms on glucose uptake in the brain
remain unknown. Therefore, the purpose of this study
is to explore what effects the Val66Met polymorphism
has on abnormal glucose consumption in Alzheimer’s
disease, mild cognitive impairment, and normal control
Materials and methods
The data used in this article were obtained from the
Alzheimer’s Disease Neuroimaging Initiative (ADNI)
database (www.loni.ucla.edu/ADNI). The initial goal of the
ADNI was to recruit 800 adults, aged 55–90 years, to
participate in the research; approximately 200 cognitively
normal older individuals were to be followed for 3 years,
400 people with mild cognitive impairment to be followed
for 3 years, and 200 people with early Alzheimer’s disease
to be followed for 2 years. See www.adni-info.org for up-
All PET data were acquired using standardized ap-
proaches: the participant lay quietly in a dimly lit room
with their eyes open and with minimal sensory stimula-
tion. A 30-min dynamic emission scan, consisting of six
5-min frames, was acquired starting 30min after an
intravenous injection of 5.0±0.5mCi of [18F] fluoro-
deoxyglucose. The original data were processed with a
reconstructing algorithm. To eliminate the effect of
multiple centers and different tracers, we used the
[18F] 2-fluoro-2-deoxy-D-glucose image data only. A total
of 268 participants had their fluorodeoxyglucose (FDG)-
PET data recorded as a baseline scan. After combining
our dataset with blood genotype data and discarding some
improperly processed images, we had 215 participants
who corresponded with the BDNF dataset. Details are as
below: we studied 68 patients with Alzheimer’s disease,
[Mini-mental state examination (MMSE) score between
20 and 25], 85 with mild cognitive impairment (MMSE
score above 24), and 62 normal controls (MMSE score
above 24) (Table 1).
Of course, BDNF has three subtypes, namely Val/Val, Val/
Met, and Met/Met. Therefore, we divided each clinical
group into two subgroups: the Met/Met and Val/Met
carriers that were combined as the first subgroup because
the number of Met/Met individuals was much smaller
than that of the other two groups. Thus, the second
subgroup was composed of the Val/Val individuals.
Therefore, we had six different groups as follows: normal
control Met carriers and noncarriers, mild cognitive
impairment Met carriers and noncarriers, and Alzheimer’s
disease Met carriers and noncarriers. Their demographical
characteristics are summarized in Table 1.
All the baseline data we used were downloaded from the
Laboratory for Neuro Imaging website of ADNI and
processed using the Statistical Parametric Mapping
[Wellcome Department of Cognitive Neurology, Univer-
sity College London, London, UK (http://www.fil.ion.ucl.
ac.uk/spm/software)], which is a toolbox based on Matlab
7.0.1 [The MathWorks Inc., Massachusetts, USA (http://
www.mathworks.com/products/)]. The preprocessing steps
were as follows: (i) realignment and co-registration: we
realigned the other five frames to the first frame using
the anterior cingulated, posterior cingulated theory to
eliminate head rotation, and co-registered each PET
image to its own structural magnetization prepared rapid
gradient echo for the exact location of metabolism;
(ii) standardization: each participant’s six 5-min images
were averaged into a single file, and then each voxel
was divided by the average value of the entire image;
(iii) normalization and smoothing: each FDG-PET image
was linearly and nonlinearly deformed to the Montreal
Neurological Imaging template, spatially normalized into
a 3?3?3mm voxel size, and smoothed to a spatial
resolution of 8mm full-width at half-maximum using
a Gaussian Kernel.
We used the analysis of variance to test the differences in
age and sex in all the groups. Student t-tests were used to
test the FDG-uptake differences between the clinical
Alzheimer’s disease and normal control groups and those
between the mild cognitive impairment and normal
control groups on a voxel-by-voxel basis, generating
PET data characteristics
AD (n=68) MCI (n=85)Normal controls (n=62)
Values are expressed as mean (SD).
(e4) means the numbers of participants who carry APOE e4 allele.
AD, Alzheimer’s disease; APOE, apolipoprotein E; MCI, mild cognitive impairment.
aThe P value was obtained by using analysis of variance.
bThe P value was obtained by using Pearson’s w2test.
Effects of BDNF on brain metabolism Xu et al.
statistical parametric maps of group-related reductions in
the regional-whole brain cerebral metabolic rate for
glucose (CMRglu). The effects of age and apolipoprotein
E e4 (APOE e4) are remarkable in Alzheimer’s disease
, so we set APOE e4 and age as covariates in addition
to sex. In addition, we applied an analysis of covariance
to check the differences in FDG uptake using the clinical
groups and the Val66Met genotypes as fixed factors
with age and sex as covariates. A False Discovery Rate-
corrected approach was used for multiple comparison
corrections, and clusters with fewer than 30 voxels were
discarded to reduce the possible influences of noise.
We found no significant difference between Met carriers
and Met noncarriers in the participants’ ages, sex, or
APOE e4 for the three clinical groups (Table 1).
The effects of Val66Met on the regional uptake within
In the normal control group, Met carriers had a lower
CMRglu in the right parahippocampal gyrus and the
superior temporal gyrus than the noncarriers, and a higher
CMRglu in the superior and middle frontal gyrus
(prefrontal cortex) (P<0.005, uncorrected) (Fig. 1a).
The findings in the mild cognitive impairment group
showed a similar metabolism pattern, but with a small
difference from those in the normal control group;
glucose consumptions in the right parahippocampal gyrus,
right insula, and right inferior temporal gyrus were lower
in Met carriers than in noncarriers. Moreover, a higher
metabolism appeared primarily in the middle occipital
gyrus and inferior parietal lobule (BA40) when comparing
Met carriers with noncarriers (P<0.005, uncorrected)
(Fig. 1b). In addition, the Met carriers’ metabolism was
lower in the bilateral insula compared with the non-
carriers (P<0.005, uncorrected) in the Alzheimer’s
disease group, as shown in Fig. 1c.
We comprehensively investigated the effects of the
Val66Met polymorphism on brain function in Alzheimer’s
disease, mild cognitive impairment, and normal control
using FDG-PET. Our findings indicated that the BDNF
Met allele affects glucose metabolism in some specific
regions, such as the memory-related regions, including
the temporal, parietal, and occipital cortices and the
hippocampus, and emotion-related insula. To our know-
ledge, this study is the first to find an effect of this
polymorphism of the BDNF gene on the CMRglu in
Alzheimer’s disease, mild cognitive impairment, and
Hypermetabolism was found in Met carriers compared
with noncarriers both in the normal control and the mild
cognitive impairment group in regions including the
superior and middle frontal gyrus cortex in the normal
control group, and the temporal-parietal, inferior parietal
lobule, and middle occipital gyrus in the mild cognitive
impairment group. These findings are in accordance with
several related studies. One study reported hyperactivity
in the frontal and posterior parietal cortexes in healthy
Met carriers during a spatial working memory task .
Another Alzheimer’s disease-related study reported that
the Met allele could contribute to atrophy in the
prefrontal cortex . A morphological study on healthy
adults suggested that a decrease in the gray matter occurs
in the right inferior parietal lobule in Met carriers .
Moreover, dysfunction  and atrophy  in the
prefrontal cortex and in the inferior parietal lobule have
been observed in Alzheimer’s disease. Our findings
suggest that the functional abnormalities observed in
the PET may emerge before structural degeneration and
that the dysfunction is derived from damage to the brain
structure, which could in turn exacerbate its structural
deterioration. The hypermetabolisms found in our study
could possibly be compensatory activities to offset the
dysfunction resulting from damage to the brain structure.
In addition, Met carriers showed a reduced uptake of
glucose compared with noncarriers in the normal control
and mild cognitive impairment groups, and the reduc-
tions were primarily in the right hippocampal gyrus and
the left temporal cortex. The hippocampus, which is
considered to be a memory-related region, shows atrophy
in patients with Alzheimer’s disease . Our findings
indicated that these uptake reductions could be a
functional reflection of structural deterioration in mild
cognitive impairment individuals. A recent study sug-
gested a reduced activation in Met carriers in the bilateral
hippocampus and parahippocampal gyrus during a memory-
related task . Some other studies have also found that
Met carriers had gray matter atrophy in the hippocampal
cortex and parahippocampal gyrus compared with non-
carriers [13,15]. This atrophy may result from disrupted
activation in these regions. The above studies support our
findings of reduced CMRglu in these regions. We found
a lower CMRglu in Met carriers than in noncarriers in
the bilateral insula in the mild cognitive impairment and
Alzheimer’s disease groups. The insula, a relay area for
multiple neurocognitive systems , plays important
roles in interoception, emotion, and risky decision-
making . The reduced uptake in the insula indicates
that the Met allele may affect the emotions and
perceptions of Alzheimer’s disease patients.
Our findings show a similar uptake pattern between the
normal control and mild cognitive impairment groups in
the parahippocampal gyrus and temporal cortex, and for
the mild cognitive impairment and Alzheimer’s disease
groups in the insula. A possible explanation is that mild
cognitive impairment is considered to be a transitional
stage between normal control and Alzheimer’s disease
and has some clinical manifestations of both normal
2010, Vol 21 No 12
08 1624 32
08 16 24 32
08 1624 32
The effect of Val66Met polymorphism in clinical disease and normal controls. (a) In the normal control group, reduced cerebral metabolic rate for
glucose (CMRglu) was found in the parahippocampal gyrus (right), and the superior temporal gyrus (left) in the Met carriers compared with the
noncarriers; in contrast, hyperCMRglu in the superior and prefrontal cortex was found in the Met carriers. (b) In the mild cognitive impairment group,
reduced CMRglu in the parahippocampal gyrus (right), insula (right) and superior temporal gyrus (left) was found in the Met carriers; in contrast,
hyperCMRglu was found in the middle occipital gyrus (right) and inferior parietal lobule (right) (BA40) in the Met carriers. (c) In the Alzheimer’s
disease group, only reduced CMRglu was found in the bilateral insula in the Met carriers compared with the noncarriers.
Effects of BDNF on brain metabolism Xu et al.
control and Alzheimer’s disease, suggesting that the
patterns of effects of the BDNF Val/Met are sensitive
to the pathological progression. Most importantly, in our
findings, regions such as the frontal and temporal cortices
and the parahippocampal gyrus that showed abnormal
metabolism as evidenced by CMRglu are the core regions
of the default-mode network, which has been found to be
damaged in the early stages of Alzheimer’s disease .
Therefore, our studies on the regional metabolic differ-
ences caused by the effect of the BDNF polymorphisms
could provide valuable evidence in support to the earlier
findings. More importantly, our understanding of the
pathophysiologic mechanisms of Alzheimer’s disease and
mild cognitive impairment will be greatly helped by
seeing them from a functional imaging perspective and
by using the FDG-PET approach.
In conclusion, we have provided new evidence in favor
of an association between a specific polymorphism of
the BDNF gene and Alzheimer’s disease using FDG-PET.
Our study suggests that the polymorphism of the BDNF
gene could be a putative candidate genetic factor that
affects the CMRglu in the prefrontal cortex, inferior
parietal lobule, parahippocampal gyrus, temporal cortex,
The authors thank Edmund F. and Rhoda E. Perozzi for
reviewing the English and content of this study. This
work was supported by the National Key Basic Research
and Development Program (973) Grant 2007CB512305
and the National Natural Science Foundation of China,
Grant No. 60903101. The grantee organization is the
Northern California Institute for Research and Educa-
tion, and the study is coordinated by the Alzheimer’s
Disease Cooperative Study at the University of California,
San Diego, USA. Data collection and sharing for this
project was funded by the Alzheimer’s Disease Neuro-
imaging Initiative (ADNI) (National Institutes of Health
Grant U01 AG024904). ADNI is funded by the National
Institute on Aging, the National Institute of Biomedical
Imaging and Bioengineering, and through the generous
contributions from the following: Abbott, AstraZeneca
AB, Bayer Schering Pharma AG, Bristol-Myers Squibb,
Eisai Global Clinical Development, Elan Corporation,
Genentech, GE Healthcare, Glaxo SmithKline, Inno-
genetics, Johnson and Johnson, Eli Lilly and Co.,
Medpace, Inc., Merck and Co., Inc., Novartis AG, Pfizer
Inc., F. Hoffman-La Roche, Schering-Plough, Synarc, Inc.,
and Wyeth, and nonprofit partners, the Alzheimer’s
Association and Alzheimer’s Drug Discovery Foundation,
with participation from the US Food and Drug Ad-
ministration. Private sector contributions to ADNI are
facilitated by the Foundation for the National Institutes
of Health (http://www.fnih.org). ADNI data are dissemi-
nated by the Laboratory for NeuroImaging at the
University of California, Los Angeles, USA. This research
was also supported by the National Institutes of Health
grants P30 AG010129, K01 AG030514, and the Dana
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