Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 1
ORIGINAL RESEARCH ARTICLE
published: 20 August 2009
of the corpus callosum (Pfefferbaum et al., 2001; Sullivan and
Because WM is malleable and its bulk refl ects a dynamic equi-
librium of growth and decline, age differences in the WM structure
may stem from alteration in mechanisms that are responsible for
maintaining that equilibrium. One potentially important factor in
this process is brain-derived neurotrophic factor (BDNF). BDNF is
a multipurpose protein that plays important roles in many events,
including neuronal differentiation, proliferation of dendritic
arbor, synaptic plasticity, and, most notably for the topic of this
report, axonal sprouting (Egan et al., 2003; Binder and Scharfman,
2004). In addition, BDNF has metabotropic effects (Lebrun et al.,
2006), and is protective against ischemia (Yanamoto et al., 2004;
Nomura et al., 2005; Schäbitz et al., 2007; Mochizuki et al., 2008).
Thus, adequate BDNF activity may be critical for maintaining WM
Brain-derived neurotrophic factor production declines with
age (Sohrabji and Lewis, 2006) and is reduced by age-depend-
ent vascular risk factors such as hypertension (Lee et al., 2006),
hypoperfusion (Irikura et al., 1996), and poor glucose metabo-
lism (Krabbe et al., 2007). Although experimental study of BDNF
effects on brain aging is hampered by impossibility to manipulate
human BDNF levels in vivo, natural occurring ‘mendelian rand-
omization’ (Katan, 1986) of individuals into groups by BDNF avail-
ability presents an opportunity for an inquiry into BDNF effects.
These natural groups are determined by a variant in the gene that
controls BDNF production, BDNF val66met. The low-activity met
Cerebral white matter (WM) changes throughout the lifespan. Its
volume increases from childhood to young adulthood, remains
stable during middle age, and shrinks in senescence (Pfefferbaum
et al., 1994; Bartzokis, 2004; Hasan et al., 2008; Raz and Kennedy,
2009). In late adulthood, WM accumulates pathological changes
(de Leeuw et al., 2001), and the myelin sheath exhibits structural
defects (Peters, 2002). Deterioration of the WM leads to loss of
orientation differences in water diffusivity, refl ected on diffusion
tensor imaging (DTI) (Pierpaoli and Basser, 1996). DTI studies
of normal aging show that the microstructural integrity of WM
is also reduced with age, with a greater difference observed in
anterior than posterior regions (Pfefferbaum, et al., 2000, 2005;
O’Sullivan et al., 2001; Sullivan et al., 2001; Head et al., 2004; Salat
et al., 2005; Sullivan and Pfefferbaum, 2006; Ardekani et al., 2007;
Kochunov et al., 2007; Madden et al., 2007; Hugenschmidt et al.,
2008; Stadlbauer et al., 2008; Kennedy and Raz, in press). The
mechanisms of these differences are not entirely understood, but
are believed to refl ect cerebrovascular properties of the WM and
are partly under genetic control. Notably, the regions of the brain
that are late to myelinate (Flechsig, 1901) may be most vulnerable
to the effects of normal aging (Bartzokis, 2004; Raz, 2004). Frontal
regions for example develop relatively late (Sowell et al., 1999) and
show greater infl uence of environmental than genetic factors in
comparison to the posterior regions. Specifi cally, the proportion
of genetic to environmental contributions to fractional anisotropy
(FA) is estimated as 3:1 for the splenium but only 1:1 for the genu
BDNF val66met polymorphism infl uences age differences in
microstructure of the corpus callosum
Kristen M. Kennedy1, Karen M. Rodrigue1, Susan J. Land2 and Naftali Raz3*
1 Center for Brain Health, School of Behavioral and Brain Sciences, The University of Texas at Dallas, Dallas, TX, USA
2 Department of Obstetrics and Gynecology, Wayne State University, Detroit, MI, USA
3 Department of Psychology, Institute of Gerontology, Wayne State University, Detroit, MI, USA
Brain-derived neurotrophic factor (BDNF) plays an important role in neuroplasticity and promotes
axonal growth, but its secretion, regulated by a BDNF gene, declines with age. The low-activity
(met) allele of common polymorphism BDNF val66met is associated with reduced production
of BDNF . We examined whether age-related reduction in the integrity of cerebral white matter
(WM) depends on the BDNF val66met genotype. Forty-one middle-aged and older adults
participated in the study. Regional WM integrity was assessed by fractional anisotropy (FA)
computed from manually drawn regions of interest in the genu and splenium of the corpus
callosum on diffusion tensor imaging scans. After controlling for effects of sex and hypertension,
we found that only the BDNF 66met carriers displayed age-related declines in the splenium
FA, whereas no age-related declines were shown by BDNF val homozygotes. No genotype-
related differences were observed in the genu of the corpus callosum. This fi nding is consistent
with a view that genetic risk for reduced BDNF affects posterior regions that otherwise are
considered relatively insensitive to normal aging. Those individuals with a genetic predisposition
for decreased BDNF expression may not be able to fully benefi t from BDNF-based plasticity
and repair mechanisms.
Keywords: brain, diffusion tensor imaging, genetics, MRI, white matter, aging, brain-derived neurotrophic factor, single
William J. Jagust, University of
California Berkeley, USA
Edith V. Sullivan, Stanford University
Medical School, USA
Lars Nyberg, Umea University,
Naftali Raz, Institute of Gerontology,
Wayne State University, 87 E Ferry St,
226 Knapp Bldg, Detroit, MI
Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 2
Kennedy et al. Age, BDNF , corpus callosum
allele of that polymorphism is linked to reduced volume of the hip-
pocampus (Pezawas et al., 2004; Szeszko et al., 2005; Bueller et al.,
2006; Chepenik et al., 2009), parahippocampal (Takahashi et al.,
2008) and prefrontal (Pezawas et al., 2004; Nemoto et al., 2006;
Takahashi et al., 2008) cortices but not of the amygdala (Sublette
et al., 2008). Carriers of BDNF 66met also evidence suboptimal
cognitive performance (e.g., Egan et al., 2003; Bath and Lee, 2006;
Miyajima et al., 2008; Raz et al., 2009). However, to the best of
our knowledge, there are no reports of BDNF effects on the WM
microintegrity in a healthy aging population. In addition, although
there is evidence of exacerbation of BDNF val66met by vascular
risk (e.g., Raz et al., 2009), little is known of such conjoint effects
on brain structure.
In this study we asses the infl uence of BDNF val66met genotype
and vascular risk on the microstructural integrity of the genu and
the splenium of the corpus callosum. In a limited-scale study, the
densely myelinated corpus callosum (Lamantia and Rakic, 1990)
is an excellent candidate region to explore effects of genetic factors
on the WM. Moreover, the genu and the splenium are well suited
for a comparison as WM microintegrity declines more with age
in the former than in the latter (Sullivan and Pfefferbaum, 2006;
Raz and Kennedy, 2009). We hypothesized that older participants
and individuals with hypertension would evidence reduced FA in
both regions, and that carriers of the BDNF 66met allele would
show additional reduction in FA. We also tested for interactive or
synergistic effects of age, hypertension and reduced BDNF avail-
ability on WM integrity.
MATERIALS AND METHODS
The participants were screened for history of neurological and psy-
chiatric conditions, head trauma with loss of consciousness, alcohol
and drug abuse, diabetes, thyroid problems, and cardiovascular
disease (except controlled essential hypertension). Participants were
screened for dementia and depression with the MMSE (Folstein
et al., 1975) and the Center for Epidemiological Study Depression
Scale (CES-D; Radloff, 1977), with cut-offs of 26 and 15, respec-
tively. All participants were strongly right-handed (75% and above
on the Edinburgh Handedness Questionnaire; Oldfi eld, 1971).
Participants provided written informed consent in accord with
university and hospital review board guidelines.
The sample was part of a larger sample of 77 adult volunteers
(age 19–84, 49 women) who underwent MRI scanning and cognitive
testing as described elsewhere (Kennedy and Raz, 2009; Kennedy
and Raz, in press). Genetic material was available on 41 Caucasian
participants (all of which are included in this study), 25 women
and 16 men, 43–81 years old (mean 64.17 ± 10.06 years), and had
an average education at college level (mean 16.34 ± 2.68 years). Of
the 25 women, 17 were in the val and 8 were in the met group, and
of the men, 9 were in the val group, and 7 were in the met group.
Sample demographic information is presented in Table 1. There
were no sex differences in age, CES-D or MMSE scores, systolic
or diastolic blood pressure (all t ≤ 1 ns). Men attained on average
two more years of formal education than women [t(39) = 2.48,
p < 0.02]. The sample included 17 individuals with hypertension,
defi ned as described below. Only 2 (4.9%) participants smoked
tobacco products and 30 (73%) reported exercising regularly. Thus,
the participants of this study were healthier and better educated
than the general population (American Heart Association, 2004).
DNA isolations and genotyping assays were conducted in the Wayne
State University Applied Genomics Technology Center. For geno-
typing quality control, 10% direct repeats and DNA sequencing
for verifi cation were performed. We used both control DNA and
no-template controls, and ran all 5′-nuclease assays on an Applied
Biosystems 7900. After isolating DNA from buccal cultures obtained
in mouthwash samples, we used a Gentra Autopure LS under the
standard buccal cell protocol.
Polymorphism for BDNF val66met (rs6265) was interrogated
using Taqman SNP Genotyping assays, with DNA sequencing
reactions carried out using the 0.5× protocol for ABI PRISM
BigDye Terminator Cycle Sequencing Ready Reaction Kit (Applied
Biosystems). The sequencing extension products, purifi ed with
Sephadex, were analyzed on an ABI PRISM 3700 DNA Analyzer
using a 50-cm capillary array.
The allelic distribution of the BDNF val66met polymorphism fi t
the Hardy–Weinberg equilibrium (χ2 = 2.05, p = 0.15), with 63% of
participants being val homozygotes (n = 26), and 37% val/met het-
erozygotes (n = 15), whereas no participants had the rare met/met
genotype. The val/val and the val/met individuals did not differ in
age (p = 0.86), education level (p = 0.48), MMSE (p = 0.51), CES-D
(p = 0.17) scores, or systolic (p = 0.22) or diastolic (p = 0.29) blood
pressure (see Table 1 for sample demographics by genotype).
BLOOD PRESSURE MEASURES
Each participant had systolic and diastolic blood pressure meas-
ured with an analog mercury sphygmomanometer (Model 12–525;
Country Technology, Gays Mills, WI, USA) equipped with a stand-
ard brachial cuff (Omron Professional). Participants sat in a com-
fortable chair in a climate-controlled offi ce. Blood pressure was
measured on three separate days, once from each arm, and averaged
Table 1 | Sample demographic information by BDNF genotype and total sample: mean ± ± SD.
Age Edu MMSE CES-D Systolic BP Diastolic BP
63.96 ± 10.79
64.53 ± 8.99
64.17 ± 10.06
16.11 ± 2.82
16.73 ± 2.46
16.34 ± 2.68
28.35 ± 1.16
28.60 ± 1.18
28.44 ± 1.16
3.42 ± 3.59
5.33 ± 5.16
4.12 ± 4.24
127 .40 ± 11.93
132.65 ± 14.57
129.32 ± 13.03
74.37 ± 8.84
77 .08 ± 5.52
75.36 ± 7 .83
N, sample size; edu, years of education; MMSE, mini-mental status exam; CES-D, center for epidemiological study depression scale; BP , blood pressure mmHg. The
groups did not differ signifi cantly on any of the demographic variables (all p-values > 0.17).
Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 3
Kennedy et al. Age, BDNF , corpus callosum
FIGURE 1 | Demarcation of the corpus callosum regions of interest
(ROIs): genu (red) and splenium (blue). The ROIs are displayed on a
fractional anisotropy map.
across samples and sessions. Current and prior hypertensive status
and medication information was collected from an interview and
a comprehensive health questionnaire completed before entrance
to the study. Only participants who had controlled hypertension
or were normotensive were allowed into the study. Hypertension
was operationally defi ned as systolic blood pressure greater than
140 mmHg and diastolic pressure greater than 90 mmHg (Joint
National Committee on Prevention, Detection, Evaluation, and
Treatment of High Blood Pressure, 1997). Individuals whose blood
pressure exceeded the cutoff were referred to their physician.
MR images were acquired on a 1.5-T Magnetom Sonata scanner
(Siemens Medical Systems, Erlangen, Germany). The DTI data were
acquired with a single shot echo-planar imaging sequence acquired
in the axial plane with six directions, b = 0 and 1000 mm2/s, 10 aver-
ages, TE = 97 ms, TR = 5400 ms, acquisition matrix = 192 × 192,
FOV = 345 mm, voxel size = 1.8 × 1.8 × 3 mm3. Duration of acqui-
sition was 6.25 min.
The data were processed with the DTI module of Analyze software
(BIR, Mayo Clinic, Rochester, MN, USA). Each DTI scan was fi rst
binned into the baseline (b = 0) and six gradient encoded volumes
(each containing 33 slices) using the Dicom Tool module and these
seven separated scans were imported into the DTI module. After
the diffusion gradient orientation information was entered for each
volume, the data were thresholded to reduce extracerebral noise, the
tensor was computed, and individual FA maps were generated.
Region of interest measurement
Images for manual tracing of regions of interest (ROIs) were dis-
played on a 21′ monitor and on a 21′ LCD digitizing tablet (Wacom
Cintiq model 21UX; Wacom Inc., Vancouver, WA, USA) and mag-
nifi ed ×2. Each ROI was traced manually with a stylus on the T2-
weighted (b = 0) baseline image for each participant in native space
and supplemented with simultaneous side-by-side views from the
FA and FA color map images in the same native coordinate space
to maximize neuroanatomic validity. The saved ROI was applied to
the FA maps and mean and standard deviation FA obtained within
each ROI, for each participant separately on three slices, and then
averaged across the three slices.
The ROIs were specifi cally drawn well within the inner portions
of the WM regions to minimize the potential of partial volum-
ing effects that can occur in the border voxels at the interface of
gray/white and CSF/white boundaries. Test–retest reliability was
determined for one operator (Kristen M. Kennedy) by tracing eight
images (for each ROI) on two separate occasions, 2 weeks apart.
Reliability of mean FA for each ROI was assessed by an intrac-
lass correlation, formula ICC (3) (Shrout and Fleiss, 1979), and
exceeded 0.90 (genu ICC3 = 0.91, splenium ICC3 = 0.99). The
target ROIs, the genu and splenium of the corpus callosum, were
demarcated as described below.
The operator drew a small ROI on the genu and the splenium
(Figure 1), medially-to-laterally on the axial plane, with reference
to the sagittal and coronal planes assisted by the OrthoReview func-
tion in Analyze ROI module. We took special care to exclude, both
visually and by monitoring the standard deviations, pixels that
could refl ect cerebro-spinal fl uid from the ventricles. The genu
and the splenium were measured on the same three axial slices in
which both were optimally visible.
The data were analyzed in the General Linear Model framework
with SYSTAT 12 (Systat Software, Inc., Chicago, IL, USA). Age,
centered at the sample mean, was a continuous predictor. Sex,
hypertension status, and allelic variant of BDNF val66met (val
vs. val/met) entered the model simultaneously as categorical pre-
dictors. The callosal ROI (genu and splenium) was the repeated
measure, and FA was the dependent variable. Second-order interac-
tions among all predictors were also included in the models, but if
found nonsignifi cant (p > 0.15) they were deleted from the model
to conserve power. All interactions involving repeated measures
used p-values adjusted by Huynh–Feldt correction factor.
The analysis revealed a signifi cant main effect of ROI [F(1,
35) = 44.30, p < 0.0001], with splenium FA (0.79 ± 0.04) exceed-
ing that of the genu (0.74 ± 0.06), and a trend for the main effect of
age F(1, 35) = 3.95, p = 0.055. None of the other between- subjects
main effects reached signifi cance: sex F < 1 ns; hypertension F(1,
35) = 1.16, p = 0.29; and BDNF genotype F < 1 ns. However,
Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 4
Kennedy et al. Age, BDNF , corpus callosum
there was a signifi cant ROI × age × BDNF genotype interaction,
F(1, 35) = 4.99, p = 0.03, indicating that the magnitude of the
age differences in FA varied between the ROIs and depended on
BDNF val66met genotype. The interactions age × BDNF genotype
(F < 1), ROI × sex (F < 1), and ROI × hypertension (F < 1) were
not signifi cant.
To decompose the ROI × age × BDNF genotype interaction
depicted in Figure 2, we regressed regional FA on age for each BDNF
met allele group. In the BDNF val66 homozygotes (BDNF 66met-),
there was a nonsignifi cant trend for an age effect in the genu FA
(b = −0.00217 ± 0.00108; t = −2.02, r = −0.38, p = 0.055), and no
age difference in splenium FA (b = −0.0004 ± 0.00063; t = 0.64,
r = −0.13, p = 0.53). In heterozygotes (BDNF 66met carriers),
there was also no age effect on genu FA: b = −0.00154 ± 0.00173,
t = −0.90, r = −0.24, p = 0.39; however, a signifi cant decline in
splenium FA was observed: b = −0.00309 ± 0.00129, t = −2.40,
r = −0.55, p = 0.03. Removal of an outlier (74-year-old man) did
not change the results for genu (t = −0.24, p = 0.81) or splenium
(t = −2.43, p = 0.03). The contribution of nonlinear (quadratic)
trends in all four regressions was not signifi cant. Comparison of
age slopes of the four regression models revealed that all of the
90% confi dence limits except one, overlapped. Only the slope of
regression of the splenium FA among the val/val homozygotes was
reliably fl atter than the rest.
The results of this small-scale investigation show that at least in one
region, the splenium of the corpus callosum, age-related reduction
in WM integrity depends on variation in a major neurotrophin
gene. Only persons who carried a low-activity allele of the BDNF
Val66Met polymorphism evidenced age-related decline in FA.
Whereas the observed effects of age on the genu FA were unclear,
the dependence of age-related differences in the splenium on BDNF
genotype was apparent. Age had no effect on splenium FA in BDNF
val66 homozygotes and was associated with a signifi cantly lower
FA in the splenium of BDNF 66met carriers. There was a nonsig-
nifi cant trend for the effect of age on the genu FA in the val group.
However, examination of the correlations for each ROI and BDNF
group suggests that for the genu FA, the strength of association was
comparable between groups (r = −0.38 vs. −0.24) and the difference
in signifi cance refl ects low statistical power of the study. In spite of
that, this preliminary investigation is, to the best of our knowledge,
the fi rst reported fi nding of BDNF val66met effect on regional WM
integrity in healthy aging.
White matter aging is usually more prominent in the ante-
rior (prefrontal white and genu) than posterior (parietal white
and splenium) brain regions (Raz et al., 2005, 2007; Sullivan and
Pfefferbaum, 2006), whereas in the presence of pathological proc-
esses or risk factors, a more generalized pattern involving dete-
rioration of the posterior brain regions is observed as well (Raz
et al., 2007). The fi nding reported here adds the low-activity BDNF
met allele to the list of such risk factors. Further, these results are
in accord with the report that the posterior region of the CC is
under signifi cantly greater genetic control than anterior regions
(Pfefferbaum et al., 2001).
Although investigation of relevant polymorphisms is an increas-
ingly popular means for explicating specifi c components of the
observed genetic contribution to brain and cognition (de Geus et al.,
2008; Green et al., 2008; Mattay et al., 2008), association studies
of specifi c polymorphisms and WM microstructure are still rare.
The three extant studies report a negative infl uence of ApoE ε4 on
parahippocampal (Nierenberg et al., 2005) and frontal (Bartzokis
et al., 2006) WM and on the splenium (Persson et al., 2006) and genu
(Bartzokis et al., 2006) in older adults. In young adults, neuroregu-
lin-1 has been found to affect FA in the internal capsule (McIntosh
et al., 2008) and the medial frontal WM (Winterer et al., 2008). As
mentioned, to date, no association studies examined the effects of
BDNF genetic variation on cerebral WM in healthy adults.
Diffusion-derived indices of WM integrity refl ect many aspects
and components of the WM structure (Song et al., 2002; Davis
et al., 2009), and they may be differentially affected by aging.
Myelin is a product of metabolically intensive processes (Peters,
2002; Bartzokis, 2004), and BDNF, in its capacity as a metabotropic
factor and promoter of axonal growth, affects lifespan destiny of
the WM. Thus far, BDNF has been implicated in repair and main-
tenance of the WM in demyelinating disease (Stadelmann et al.,
2002; Azoulay et al., 2008), although the role of BDNF val66met
in that process is unclear (Weinstock-Guttman et al., 2007). The
FIGURE 2 | The effects of BDNF 66met allele on age-related differences in
fractional anisotropy of genu (upper panel) and splenium (lower panel)
of the corpus callosum. Black solid line and circles correspond to val
homozygotes; red broken line and triangles correspond to val/met
Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 5
Kennedy et al. Age, BDNF , corpus callosum
differential vulnerability of the anterior and posterior portions of
the corpus callosum may stem from its cytological characteristics.
Axon density, degree of myelination, and axonal diameter vary
along the anterior-posterior axis of the corpus callosum (Lamantia
and Rakic, 1990). The anterior portion is densely populated by
small myelinated and unmyelinated axons, whereas the posterior
portion contains a higher proportion of large myelinated axons
and is the only segment to contain giant axons (i.e., 0.90 µm). The
splenium also has the lowest percentage of unmyelinated axons
(3.5%) in the corpus callosum (Lamantia and Rakic, 1990). Given
this highly segregated organization, it stands to reason that the seg-
ments of the corpus callosum would be differentially sensitive to
aging (Aboitiz et al., 1996) and to clinical and genetic risk factors.
Because the splenium is the most heavily myelinated part of the
corpus callosum, the impact of reduced capacity for axonal repair
(e.g., due to dearth of BDNF) may be most apparent there.
Contrary to our hypothesis, we found neither a signifi cant effect
of hypertension, nor a joint effect of that vascular risk factor and
the genetic variation on WM integrity. The reasons for this are
unclear, but may include relatively low statistical power as well
as selection of healthier-than-average hypertensive individuals. In
addition, this study is limited to a cross-sectional design and deri-
vation of the index of WM integrity from a relatively early version
of the DTI sequence. Notably, the lack of signifi cant effects of age
in the presence of nonsignifi cant trends in the expected direction
can be attributed to the low statistical power and curtailment of
age range to middle-aged and older adults. All these limitations are
being addressed in the longitudinal study of a larger sample that is
currently underway in our laboratory.
The positive effect of homozygosity for the high-activity BDNF val
allele on a selected region of the cerebral WM, the splenium of the
corpus callosum, suggests that with adequate BDNF availability
older adults may benefi t from the plasticity and repair mechanisms
to maintain healthy aging, whereas carriers of the met allele may
be at risk for more widespread WM deterioration. Maintenance of
these repair mechanisms in the posterior corpus callosum in older
age may be important for the preservation of cognitive functions
dependent on interhemispheric transfer via this region – spatial,
mnemonic, and visual processing.
This study was supported in part by National Institutes of Health
grants R37 AG-011230 and T32 HS-013819, and by a Dissertation
Award from the American Psychological Association. A portion of
this paper was presented at the Society for Neuroscience Annual
Meeting in November 2008.
Aboitiz, F., Rodrigues, E., Olivares, R., and
Zaidel, E. (1996). Age-related changes
in fi bre composition of the human
corpus callosum: sex differences.
Neuroreport 7, 1761–1764.
American Heart Association (2004). Heart
Disease and Stroke Statistics – 2005
Update. Dallas, TX, American Heart
Ardekani, S., Kumar, A., Bartzokis, G., and
Sinha, U. (2007). Exploratory voxel-
based analysis of diffusion indices
and hemispheric asymmetry in nor-
mal aging. Magn. Reson. Imaging 25,
Azoulay, D., Urshansky, N., and Karni, A.
(2008). Low and dysregulated BDNF
secretion from immune cells of MS
patients is related to reduced neu-
roprotection. J. Neuroimmunol. 195,
Bartzokis, G. (2004). Age-related myelin
breakdown: a developmental model
of cognitive decline and Alzheimer’s
disease. Neurobiol. Aging 25, 5–18.
Bartzokis, G., Lu, P. H., Geschwind, D. H.,
Edwards, N., Mintz, J., and Cummings,
J. L. (2006). Apolipoprotein E
genotype and age-related myelin
breakdown in healthy individuals:
implications for cognitive decline
and dementia. Arch. Gen. Psychiatry
Bath, K. G., and Lee, F. S. (2006). Variant
BDNF (Val66Met) impact on brain
structure and function. Cogn. Affect
Behav. Neurosci. 6, 79–85.
Binder, D. K., and Scharfman, H. E.
(2004). Brain-derived neurotrophic
factor. Growth Factors 22, 123–131.
Bueller, J. A., Aftab, M., Sen, S., Gomez-
Hassan, D., Burmeister, M., and
Zubieta, J. K. (2006). BDNF Val66Met
allele is associated with reduced hip-
pocampal volume in healthy subjects.
Biol. Psychiatry 59, 812–815.
Chepenik, L. G., Fredericks, C.,
Papademetris, X., Spencer, L.,
Lacadie, C., Wang, F., Pittman, B.,
Duncan, J. S., Staib, L. H.,
Duman, R. S., Gelernter, J., and
Blumberg, H. P. (2009). Effects of the
Brain-Derived Neurotrophic Growth
Factor Val66Met variation on hip-
pocampus morphology in bipolar
Davis, S. W., Dennis, N. A., Buchler, N. G.,
White, L. E., Madden, D. J., and
Cabeza, R. (2009). Assessing the effects
of age on long white matter tracts
using diffusion tensor tractography.
Neuroimage 46, 530–541.
de Geus, E., Goldberg, T., Boomsma, D. I.,
and Posthuma, D. (2008). Imaging the
genetics of brain structure and func-
tion. Biol. Psychol. 79, 1–8.
de Leeuw, F. E., de Groot, J. C., Achten, E.,
Oudkerk, M., Ramos, L. M.,
Heijboer, R., Hofman, A., Jolles, J.,
van Gijn, J., and Breteler, M. M.
(2001). Prevalence of cerebral white
matter lesions in elderly people: a
population based magnetic resonance
imaging study. The Rotterdam Scan
Study. J. Neurol. Neurosurg. Psychiatry
Egan, M. F., Kojima, M., Callicott, J. H.,
Goldberg, T. E., Kolachana, B. S.,
Bertolino, A., Zaitsev, E., Gold, B.,
Goldman, D., Dean, M., Lu, B., and
Weinberger, D. R. (2003). The BDNF
val66met polymorphism affects activ-
ity-dependent secretion of BDNF and
human memory and hippocampal
function. Cell 112, 257–269.
Flechsig, P. (1901). Developmentalmyel
ogenetic localisation of the cerebral
cortex in the human subject. Lancet
Folstein, M. F., Folstein, S. E., and
McHugh, P. R. (1975). ‘Mini-mental
state’. A practical method for grad-
ing the cognitive state of patients
for the clinician. J. Psychiat. Res. 12,
Green, A. E., Munafò, M. R.,
Deyoung, C. G., Fossella, J. A., Fan, J.,
and Gray, J. R. (2008). Using genetic
data in cognitive neuroscience: from
growing pains to genuine insights. Nat.
Rev. Neurosci. 9, 710–720.
Hasan, K. M., Kamali, A., Kramer, L. A.,
Papanicolaou, A. C., Fletcher, J. M.,
and Ewing-Cobbs, L. (2008). Diffusion
tensor quantifi cation of the human
midsagittal corpus callosum subdivi-
sions across the lifespan. Brain Res.
Head, D., Buckner, R. L., Shimony, J. S.,
Girton, L. E., Akbudak, E.,
Conturo, T. E., McAvoy, M.,
Morris, J. C., and Snyder, A. Z. (2004).
Differential vulnerability of anterior
white matter in nondemented aging
with minimal acceleration in dementia
of the Alzheimer type: evidence from
diffusion tensor imaging. Cereb. Cortex
Hugenschmidt, C. E., Peiffer, A. M.,
Kraft, R. A., Casanova, R., Deibler, A. R.,
Burdette, J. H., Maldjian, J. A., and
Laurienti, P. J. (2008). Relating imag-
ing indices of white matter integrity
and volume in healthy older adults.
Cereb. Cortex 18, 433–442.
Irikura, K., Morii, S., Miyasaka, Y.,
Yamada, M., Tokiwa, K., and Yada, K.
(1996). Impaired autoregulation in
an experimental model of chronic
cerebral hypoperfusion in rats. Stroke
Joint National Committee on Prevention,
Detection, Evaluation, and Treatment
of High Blood Pressure (1997). The
sixth report of the Joint National
Committee on Prevention, Detection,
Evaluation, and Treatment of High
Blood Pressure. Arch. Intern. Med.
Katan, M. B. (1986). Apolipoprotein E iso-
forms, serum cholesterol and cancer.
Lancet 327, 507–508.
Kennedy, K. M., and Raz, N. (2009). Aging
white matter and cognition: differ-
ential effects of regional variations
in diffusion properties on memory,
executive functions, and speed.
Neuropsychologia 7, 916–927.
Kennedy, K. M., and Raz, N. (in press).
Pattern of normal age-related
Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 6
Kennedy et al. Age, BDNF , corpus callosum
regional differences in white matter
microstructure is modifi ed by vascu-
lar risk. Brain Res.
Kochunov, P., Thompson, P. M.,
Lancaster, J. L., Bartzokis, G., Smith, S.,
Coyle, T., Royall, D. R., Laird, A., and
Fox, P. T. (2007). Relationship between
white matter fractional anisotropy
and other indices of cerebral health
in normal aging: tract-based spatial
statistics study of aging. Neuroimage
Krabbe, K. S., Nielsen, A. R., Krogh-
Madsen, R., Plomgaard, P.,
Rasmussen, P., Erikstrup, C.,
Fischer, C. P., Lindegaard, B.,
Petersen, A. M., Taudorf, S.,
Secher, N. H., Pilegaard, H.,
Bruunsgaard, H., and Pedersen, B. K.
(2007). Brain-derived neurotrophic
factor (BDNF) and type 2 diabetes.
Diabetologia 50, 431–438.
Lamantia, A. S., and Rakic, P. (1990).
Cytological and quantitative charac-
teristics of four cerebral commissures
in the rhesus monkey. J. Comp. Neurol.
Lebrun, B., Bariohay, B., Moyse, E., and
Jean, A. (2006). Brain-derived neuro-
trophic factor BDNF and food intake
regulation: a minireview. Auton.
Neurosci. 126–127, 30–38.
Lee, T. H., Yang, J. T., Kato, H., and Wu, J. H.
(2006). Hypertension downregulates
the expression of brain-derived neu-
rotrophic factor in the ischemia-vul-
nerable hippocampal CA1 and cortical
areas after carotid artery occlusion.
Brain Res. 1116, 31–38.
Madden, D. J., Spaniol, J., Whiting, W. L.,
Bucur, B., Provenzale, J. M., Cabeza, R.,
White, L. E., and Huettel, S. A. (2007).
Adult age differences in the functional
neuroanatomy of visual attention:
a combined fMRI and DTI study.
Neurobiol. Aging 28, 459–476.
Mattay, V. S., Goldberg, T. E., Sambataro, F.,
and Weinberger, D. R. (2008).
Neurobiology of cognitive aging:
insights from imaging genetics. Biol.
Psychol. 79, 9–22.
McIntosh, A. M., Moorhead, T. W., Job, D.,
Lymer, G. K., Muñoz Maniega, S.,
McKirdy, J., Sussmann, J. E., Baig, B. J.,
Bastin, M. E., Porteous, D., Evans, K. L.,
Johnstone, E. C., Lawrie, S. M., and
Hall, J. (2008). The effects of a neu-
regulin 1 variant on white matter
density and integrity. Mol. Psychiatry
Miyajima, F., Ollier, W., Mayes, A.,
Jackson, A., Thacker, N., Rabbitt, P.,
Pendleton, N., Horan, M., and Payton, A.
(2008). Brain-derived neurotrophic fac-
tor polymorphism Val66Met infl uences
cognitive abilities in the elderly. Genes
Brain Behav. 7, 411–417.
Mochizuki, N., Takagi, N., Kurokawa, K.,
Onozato, C., Moriyama, Y.,
Tanonaka, K., and Takeo, S. (2008).
Injection of neural progenitor cells
improved learning and memory
dysfunction after cerebral ischemia.
Exp. Neurol. 211, 194–202.
Nemoto, K., Ohnishi, T., Mori, T.,
Moriguchi, Y., Hashimoto, R., Asada, T.,
and Kunugi, H. (2006). The Val66Met
polymorphism of the brain-derived
neurotrophic factor gene affects age-
related brain morphology. Neurosci.
Lett. 397, 25–29.
Nierenberg, J., Pomara, N., Hoptman, M. J.,
Sidtis, J. J., Ardekani, B. A., and
Lim, K. O. (2005). Abnormal white
matter integrity in healthy apolipopro-
tein E epsilon4 carriers. Neuroreport
Nomura, T., Honmou, O., Harada, K.,
Houkin, K., Hamada, H., and
Kocsis, J. D. (2005). I.V. infusion of
brain-derived neurotrophic factor
gene-modifi ed human mesenchymal
stem cells protects against injury in a
cerebral ischemia model in adult rat.
Neuroscience 136, 161–169.
Oldfield, R. C. (1971). The assess-
ment and analysis of handedness.
Neuropsychologia 9, 97–113.
O’Sullivan, M., Jones, D. K., Summers, P. E.,
Morris, R. G., Williams, S. C. R., and
Markus, H. S. (2001). Evidence for
cortical ‘disconnection’ as a mecha-
nism of age-related cognitive decline.
Neurology 57, 632–638.
Persson, J., Lind, J., Larsson, A., Ingvar, M.,
Cruts, M., Van Broeckhoven, C.,
Adolfsson, R., Nilsson, L. G., and
Nyberg, L. (2006). Altered brain white
matter integrity in healthy carriers of
the APOE epsilon4 allele: a risk for
AD? Neurology 66, 1029–1033.
Peters, A. (2002). Structural changes in the
normally aging cerebral cortex of pri-
mates. Prog. Brain Res. 136, 455–465.
Pezawas, L., Verchinski, B. A., Mattay, V. S.,
Callicott, J. H., Kolachana, B. S.,
Straub, R. E., Egan, M. F., Meyer-
Lindenberg, A., and Weinberger, D. R.
(2004). The brain-derived neuro-
trophic factor val66met polymor-
phism and variation in human
cortical morphology. J. Neurosci. 24,
Pfefferbaum, A., Adalsteinsson, E., and
Sullivan, E. V. (2005). Frontal circuitry
degradation marks healthy adult
aging: evidence from diffusion tensor
imaging. Neuroimage 26, 891–899.
Pfefferbaum, A., Mathalon, D. H.,
Sullivan, E. V., Rawles, J. M.,
Zipursky, R. B., and Lim, K. O.
(1994). A quantitative magnetic
resonance imaging study of changes
in brain morphology from infancy
to late adulthood. Arch. Neurol. 51,
Pfefferbaum, A., Sullivan, E. V., and
Carmelli, D. (2001). Genetic regulation
of regional microstructure of the cor-
pus callosum in late life. Neuroreport
Pfefferbaum, A., Sullivan, E. V.,
Hedehus, M., Lim, K. O.,
Adalsteinsson, E., and Moseley, M.
(2000). Age-related decline in brain
white matter anisotropy measured
with spatially corrected echo-pla-
nar diffusion tensor imaging. Magn.
Reson. Med. 44, 259–268.
Pierpaoli, C., and Basser, P. J. (1996).
Toward a quantitative assessment of
diffusion anisotropy. Magn. Reson.
Med. 36, 893–906.
Radloff, L. S. (1977). The CES-D scale:
a self-report depression scale for
research in the general population.
Appl. Psychol. Meas. 1, 385–401.
Raz, N. (2004). The aging brain observed
in vivo: differential changes and their
modifi ers. In Cognitive Neuroscience
of Aging: Linking Cognitive and
Cerebral Aging, R. Cabeza, L. Nyberg,
and D. Park, eds (New York, NY,
Oxford University Press), pp. 17–55.
Raz, N., and Kennedy, K. M. (2009).
A systems approach to age-related
change: neuroanatomical changes,
their modifi ers, and cognitive corre-
lates. In Imaging the Aging Brain, W.
Jagust and M. D’Esposito, eds (New
York, NY, Oxford University Press),
Chap. 4, pp. 151–268.
Raz, N., Lindenberger, U., Rodrigue, K. M.,
Kennedy, K. M., Head, D.,
Williamson, A., Dahle, C., Gerstorf, D.,
and Acker, J. D. (2005). Regional brain
changes in aging healthy adults: gen-
eral trends, individual differences
and modifiers. Cereb. Cortex 15,
Raz, N., Rodrigue, K. M., Kennedy, K. M.,
and Acker, J. D. (2007). Vascular
health and longitudinal changes in
brain and cognition in middle-aged
and older adults. Neuropsychology 212,
Raz, N., Rodrigue, K. M., Kennedy, K. M.,
and Land, S. (2009). Genetic and vascu-
lar modifi ers of age-sensitive cognitive
skills: effects of COMT, BDNF, ApoE
and hypertension. Neuropsychology
Salat, D. H., Tuch, D. S., Greve, D. N., van
der, Kouwe, A. J. W., Hevelone, N. D.,
Zaleta, A. K., Rosen, B. R., Fischl, B.,
Corkin, S., Rosas, H. D., and Dale, A. M.
(2005). Age-related alterations in white
matter microstructure measured by
diffusion tensor imaging. Neurobiol.
Aging 26, 1215–1227.
Schäbitz, W. R., Steigleder, T., Cooper-
Kuhn, C. M., Schwab, S., Sommer, C.,
Schneider, A., and Kuhn, H. G. (2007).
Intravenous brain-derived neuro-
trophic factor enhances poststroke
sensorimotor recovery and stimulates
neurogenesis. Stroke 38, 2165–2172.
Shrout, P. E., and Fleiss, J. L. (1979).
Intraclass correlations: uses in assess-
ing raters reliability. Psychol. Bull. 86,
Sohrabji, F., and Lewis, D. K.
(2006). Estrogen-BDNF inter-
actions: implications for neu-
rodegenerative diseases. Front
Neuroendocrinol 27, 404–414. doi:
Song, S. K., Sun, S. W., Ramsbottom, M. J.,
Chang, C., Russell, J., and Cross, A. H.
(2002). Dysmyelination revealed
through MRI as increased radial (but
unchanged axial) diffusion of water.
Neuroimage 17, 1429–1436.
Sowell, E. R., Thompson, P. M.,
Holmes, C. J., Jernigan, T. L., and
Toga, A. W. (1999). In vivo evidence
for post-adolescent brain maturation
in frontal and striatal regions. Nat.
Neurosci 2, 859–861.
Stadelmann, C., Kerschensteiner, M.,
Misgeld, T., Brück, W., Hohlfeld, R.,
and Lassmann, H. (2002). BDNF and
gp145trkB in multiple sclerosis brain
lesions: neuroprotective interactions
between immune and neuronal cells?
Brain 125, 75–85.
Stadlbauer, A., Salomonowitz, E.,
Strunk, G., Hammen, T., Ganslandt, O.
(2008). Age-related degradation in the
central nervous system: assessment
with diffusion tensor imaging and
quantitative fi ber tracking. Radiology
Sublette, M. E., Baca-Garcia, E.,
Parsey, R. V., Oquendo, M. A.,
Rodrigues, S. M., Galfalvy, H.,
Huang, Y. Y., Arango, V., and Mann, J. J.
(2008). Effect of BDNF val66met pol-
ymorphism on age-related amygdala
volume changes in healthy subjects.
Prog. Neuropsychopharmacol. Biol.
Psychiatry 32, 1652–1655.
Sullivan, E. V., Adalsteinsson, E.,
Hedehus, M., Ju, C., Moseley, M.,
Lim, K. O., and Pfefferbaum, A.
(2001). Equivalent disruption of
regional white matter microstructure
in ageing healthy men and women.
Neuroreport 12, 99–104.
Sullivan, E. V., and Pfefferbaum, A.
(2006). Diffusion tensor imaging
and aging. Neurosci. Biobehav. Rev.
Szeszko, P. R., Lipsky, R., Mentschel, C.,
Robinson, D., Gunduz-Bruce, H.,
Sevy, S., Ashtari, M., Napolitano, B.,
Bilder, R. M., Kane, J. M., Goldman, D.,
and Malhotra, A. K. (2005). Brain-
derived neurotrophic factor val66met
polymorphism and volume of the hip-
pocampal formation. Mol. Psychiatry
Takahashi, T., Suzuki, M., Tsunoda, M.,
Kawamura, Y., Takahashi, N.,
Tsuneki, H., Kawasaki, Y., Zhou, S. Y.,
Kobayashi, S., Sasaoka, T., Seto, H.,
Frontiers in Human Neuroscience www.frontiersin.org August 2009 | Volume 3 | Article 19 | 7 Download full-text
Kennedy et al. Age, BDNF , corpus callosum
Kurachi, M., and Ozaki, N. (2008).
Association between the brain-
derived neurotrophic factor Val66Met
polymorphism and brain morphology
in a Japanese sample of schizophrenia
and healthy comparisons. Neurosci.
Lett. 4351, 34–39.
Weinstock-Guttman, B., Zivadinov, R.,
Tamaño-Blanco, M., Abdelrahman, N.,
Badgett, D., Durfee, J., Hussein, S.,
Feichter, J., Patrick, K., Benedict,
R., and Ramanathan, M. (2007).
Immune cell BDNF secretion is asso-
ciated with white matter volume in
multiple sclerosis. J. Neuroimmunol.
Winterer, G., Konrad, A., Vucurevic, G.,
Musso, F., Stoeter, P., and Dahmen,
N. (2008). Association of 5′ end
neuregulin-1 (NRG1) gene variation
with subcortical medial frontal micro-
structure in humans. Neuroimage 40,
Yanamoto, H., Xue, J. H., Miyamoto, S.,
Nagata, I., Nakano, Y., Murao, K.,
and Kikuchi, H. (2004). Spreading
depression induces long-lasting
brain protection against infarcted
lesion development via BDNF gene-
dependent mechanism. Brain Res.
Conflict of Interest Statement: The
authors declare that the research was
conducted in the absence of any com-
mercial or financial relationships that
could be construed as a potential confl ict
Received: 23 May 2009; paper pending pub-
lished: 08 June 2009; accepted: 31 July 2009;
published online: 20 August 2009.
Citation: Kennedy KM, Rodrigue KM,
Land SJ and Raz N (2009) BDNF
val66met polymorphism influences age
differences in microstructure of the corpus
callosum. Front. Hum. Neurosci. 3:19. doi:
Copyright © 2009 Kennedy, Rodrigue,
Land and Raz. This is an open-access
article subject to an exclusive license
agreement between the authors and the
Frontiers Research Foundation, which
permits unrestricted use, distribution, and
reproduction in any medium, provided the
original authors and source are credited.