Reduced Fractional Anisotropy in the Uncinate
the Met-Allele of the Val66Met Brain-Derived
Neurotrophic Factor Genotype
A. Carballedo,1F. Amico,1I. Ugwu,1A.J. Fagan,2C. Fahey,3D. Morris,3J.F. Meaney,2
A. Leemans,4and T. Frodl1*
1Department of Psychiatry, Institute of Neuroscience, University of Dublin, Trinity College Dublin, Dublin, Ireland
2Centre of Advanced Medical Imaging, St. James’s Hospital, Trinity College Dublin, Dublin, Ireland
3Neuropsychiatric Genetics Research Group, Department of Psychiatry, Institute of Molecular Medicine, University of Dublin,
Trinity College Dublin, Dublin, Ireland
4Image Sciences Institute, University Medical Center Utrecht, Utrecht, The Netherlands
Manuscript Received: 12 January 2012; Manuscript Accepted: 18 April 2012
Experimental studies support a neurotrophic hypothesis of
major depressive disorder (MDD). The aim of this study was
to determine the effect of Val66Met brain-derived neurotrophic
factor (BDNF) polymorphism on the white matter fiber tracts
connecting hippocampus and amygdala with the prefrontal
lobe in a sample of patients with MDD and healthy controls.
directions were obtained with MRI 3 Tesla scanner. Determin-
istic tractography was applied with ExploreDTI and Val66Met
BDNF SNP (rs6265) was genotyped. Fiber tracts connecting the
hippocampus and amygdala with the prefrontal lobe, namely
fractional anisotropy (FA) in the UF compared to those patients
homozygous for val-allele and compared to healthy subjects
carrying the met-allele. A significant three-way interaction
was detected between region of the cingulum (dorsal, rostral,
and parahippocampal regions), brain hemisphere and BDNF
genotype. Larger FA was detectable in the left rostral cingulum
for met-allele carriers when compared to val/val alelle carriers.
We provide evidence for the importance of the neurotrophic
involvement in limbic and prefrontal connections. The met-
allele of the BDNF polymorphism seems to render subjects
more vulnerable for dysfunctions associated with the UF, a
tract known to be related to negative emotional–cognitive proc-
essing bias, declarative memory problems, and autonoetic self
? 2012 Wiley Periodicals, Inc.
Key words: diffusion
fasciculus; fornix; cingulum; Val66Met brain-derived neuro-
trophic factor (BDNF) genotype; major depression (MDD);
tensor imaging (DTI);uncinate
Major depressive disorder (MDD) [Erickson et al., 2011] is a
common, complex, and recurrent disorder of gene–environment
interactions with an estimated heritability of 0.36–0.66 [Sullivan
et al., 2000] and a lifetime prevalence of 16% [Kessler et al., 2003].
proportion of them related to MDD [Isacsson, 2000; Prince et al.,
2007; Bailey et al., 2011; Thomson, 2012]. The World Health
Grant sponsor: Science Foundation Ireland; Grant sponsor: Health
Research Board Ireland.
None of the authors has a competing financial interest with regard to this
manuscript or has biomedical financial interests or potential conflicts of
T. Frodl, Department of Psychiatry, Institute of Neuroscience, University
ofDublin, Trinity CollegeDublin, Dublin2,Ireland. E-mail:email@example.com
Article first published online in Wiley Online Library
(wileyonlinelibrary.com): 14 May 2012
How to Cite this Article:
Carballedo A, Amico F, Ugwu I, Fagan AJ,
Fahey C, Morris D, Meaney JF, Leemans A,
in the Uncinate Fasciculus in Patients With
Major Depression Carrying the Met-Allele of
the Val66Met Brain-Derived Neurotrophic
Am J Med Genet Part B 159B:537–548.
? 2012 Wiley Periodicals, Inc.
Organisation (WHO) estimates that more people die each year
from suicide than in all the armed conflicts worldwide [McKenzie
et al., 2003]. It is then pressing to define the pathophysiological
mechanisms of MDD in order to develop potentially better treat-
ment strategies in the future.
Attempts to elucidate the pathophysiology of depression have
increased over the years and several genetic polymorphisms are
brain derived neurotrophic factor(BDNF) [Verhagen et al.,2010].
BDNF is part of the neurotrophin family, which also includes
neurotrophin 3, neurotrophin 4/5, their high affinity receptors
(receptor tyrosine kinase A [NTRK1], receptor tyrosine kinase B
[NTRK2], and receptor tyrosine kinase C [NTRK3]), and the low-
affinity nerve growth factor receptor (p75NTR) [Alderson et al.,
et al., 2005]. It codes for a precursor peptide (pre-pro-BDNF),
which is successively cleaved to generate pro-BDNF and mature
BDNF, both of which are secreted and extracellularly active [Pang
to valine (val) substitution at codon 66 in the pro-region of the
BDNF [Egan et al., 2003]. Interestingly, the met variant has been
dendrites and vesicles as well as a reduction in activity-dependent
secretion, the process that plays a major role in the regulation of
extracellular level of BDNF [Egan et al., 2003]. BDNF is expressed
throughout the brain in cortical and subcortical areas, particularly
in the hippocampus [Lu and Gottschalk, 2000; Dennis and Levitt,
2005]. BDNF seems to be required for neuroplastic changes and
brain development and further supports the neurotrophic and
neurogenic hypothesis of depression [Frodl et al., 2007]. The
literature describing structural imaging findings related to BDNF
Val66Met polymorphism is not unequivocal. Based on previous
carriers may beatriskofdevelopingsmallerhippocampalvolumes
and thus may be more susceptible to developing major depression
as suggested by structural MRI studies [Frodl et al., 2007]. Even
otherwise healthy Met carriers with high trait depression showed a
reduction in gray matter volume of the mean hippocampus when
compared with subjects homozygotic for the val-allele [Joffe et al.,
2009]. Moreover, another study suggested that the met-allele also
affects other brain regions such as the amygdala and the para-
hippocampal gyrus [Montag et al., 2009]. A very recent study has
provided preliminary evidence of a neuroprotective role of the
val-allele BDNF homozygotes had significantly larger right hippo-
campal volumes compared to nondepressed subjects homozygotic
for the val-allele. However, there was no significant difference
between the depressed and healthy met carriers [Kanellopoulos
et al., 2011].
By contrast, a more recent study found no main effect of this
genetic variant on hippocampal, amygdala, and orbitomedial pre-
frontal cortex volumes, but demonstrated the importance of early
adversity in modifying BDNF effects [Gerritsen et al., 2011].
Similarly, Cole et al.  found no evidence of a genetic effect
either healthy individuals or MDD patients despite very large
sample sizes. Karnik et al.  again found that genotype for
the Val66Met BDNF had no significant effect on hippocampal
the brain [Basser et al., 1994; Tournier et al., 2011]. DTI is a novel
imaging technique that can evaluate both the direction and the
diffusion characteristics within the white matter tracts in the brain
tractography [Mori et al., 1999; Basser et al., 2000], to study white
[Le Bihan, 2003; Mori and Zhang, 2006]. DTI enables quantifica-
tion of the rate of diffusion of water in brain tissue where water
diffusion isnotrandombutratherhinderedbybarriers suchascell
white matter tracts, where axons are aligned in bundles, water
diffuses more readily along axonal paths than across them. Frac-
tional anisotropy (FA) is a scalar value between zero and one that
Nobuhara et al., 2006b]. Reduced FA in the absence of gross
of the white matter tracts [Coplan et al., 2010]. Recent DTI studies
have suggested that patients with MDD show reduced FA values
compared to healthy controls. A significant reduction in FA has
been found in the dorsolateral prefrontal cortex and in widespread
regions ofthe frontal and temporal lobes [Alexopoulosetal.,2002;
Taylor et al., 2004; Nobuhara et al., 2006a; Ma et al., 2007; Yang
of patients with MDD compared to healthy controls, indicating
microstructural white matter alterations in MDD (for a detailed
et al. ). These results may explain disease-related micro-
stuctural changes taking place during depressive episodes.
highlighted above. We aimed at determining the effect of the
to analyze the fiber bundles connecting the hippocampus and
amygdala with the prefrontal lobe, namely the uncinate fasciculus,
fornix, and cingulum, and compared the microstructural proper-
ties of these tracts between patients with MDD and healthy com-
A cohort 79 volunteers with ages between 18 and 65 years were
from inpatient wards and outpatient clinics attached to the De-
in Dublin. Healthy volunteers without history of psychiatric
illness (N¼42) were recruited from the local community via
announcements. The patients had a DSM-IV diagnosis of MDD
at the time of the study without any other comorbidity, confirmed
538 AMERICAN JOURNAL OF MEDICAL GENETICS PART B
conditions to ensure that healthy volunteers had no personal
history of neurological or psychiatric disorders (axis I or axis II),
and also no history of severe medical illness, head injury or
substance and alcohol abuse. Exclusioncriteriaalso includedacute
suicidality, previous treatment with hydrocortisone or electrocon-
vulsive therapy, and previous head injury with loss of conscious-
ness. Demographic variables, inclusion and exclusion criteria, and
clinical details were assessed using a standardized questionnaire as
well as through DSM-IV Structured Clinical Interviews forpsychi-
atric disorders and personality (SCID-I, II) [Spitzer et al., 1992;
Williams et al., 1992]. In the patient group, information about
structured interview. Thirteen of the patients were currently drug-
mirtazapine. There was no significant difference with regards to
these medication groups between patients carrying the met-allele
and those homozygous for the val-allele of the BDNF polymor-
5, val/val: none; 8, SSRI: 8, dual: 6).
Written informed consent was obtained from all participants after
out by the Declaration of Helsinki, and was approved by the ethics
teaching hospitals of Trinity College Dublin.
Self and observer rated scales were also completed for all partic-
ipants included in the study. The rating scales that were used
comprised: the Hamilton Rating Scale for Depression [Hamilton,
1969], Beck’s Depression Inventory (BDI-II) [Beck et al., 1996],
Montgomery Asberg Depression Rating Scale (MADRAS)
[Montgomery and Asberg, 1979], and the Structured Clinical
Interview for DSM-IV (SCID-II) personality questionnaire.
Diffusion Tensor Imaging (DTI)
Magnetic resonance imaging studies were carried out using an
at three Tesla (Best, The Netherlands). High angular resolution
diffusion imaging (HARDI) with 61 (split up in one non-diffusion
diffusion directions was obtained (Field Of View (FOV):
200?257?126mm3, 60 slices, no gap, spatial resolution:
1.8?1.8?2.1mm3, TR/TE¼12,561/59msec, flip angle¼90?,
half k-space acquisition was used (half scan factor¼0.68), SENSE
parallel imaging factor¼2.5, b-values¼0, 1,200sec/mm2, with
SPIR fat suppression and dynamic stabilization in an image acqui-
sition time of 15min 42sec).
DTI Data Pre-Processing
Data were pre-processed with ExploreDTI [Leemans et al., 2009]
(www.exploredti.com/) using the following steps:
- First,data qualityassessment wasperformedbyloopingthrough
the individual images to check for gross artifacts, such as signal
dropouts and interleave artefacts caused by sudden subject
motion. No participants had to be excluded based on these
- Second, each data set was corrected for subject motion and eddy
current induced geometric distortions with the appropriate
reorientation of the diffusion gradient directions [Leemans
and Jones, 2009]. In this correction procedure, the data were
transformed rigidly to MNI space (voxel size: 2?2?2mm2) by
applying cubic interpolation with only a single resampling step
(concatenating the transformation matrices) [Klein et al., 2010;
Leemans et al., 2005; Mori et al., 2008; Rohde et al., 2004]. In
doing so, no additional confounds, such as partial volume effect
(PVE) related modulations of the estimated DTI measures [Vos
by transforming the DTI data to a common atlas space, unifor-
mity of brain angulation was maximized across subjects, which
facilitates the reconstruction of the fiber bundles of interest.
- Finally, the diffusion tensor was estimated with the RESTORE
approach [Chang et al., 2005] and the FA was computed as
described previously [Pierpaoli and Basser, 1996].
Deterministic tractography [Basser et al., 2000] was applied as
implemented in ExploreDTI [Leemans et al., 2009]. First, whole
brain tractography was performed on each data set with a uniform
2mm seed point resolution, 1mm step size, and an FA tract
or not allowing a tract to pass through with the ‘‘NOT’’ operator).
NOT was consistently placed, for example, in the midline to avoid
crossing fibers from other bundles, for example, from the corpus
callosum. The ROI definitions were adjusted to recent established,
dorsal and parahipocampal regions; Fig. 1).
For the UF, which connects the anterior temporal lobe with
orbital and polar frontal cortex, the ‘‘AND’’ ROIs were placed on
the most posterior coronal slice in which the temporal lobe is
separated from the frontal lobe. The first ROI included the entire
temporal lobe and the second ROI was placed at the same coronal
level and included the entire projections toward the frontal lobe.
fronto-occipital fasciculus and the cingulum.
The cingulum was divided into three regions: rostral (left and
chosen to be less than 8cm in order to minimize them to partly
overlap. For the rostral cingulum, the first ROI was placed on the
most inferior axial slicewhere the bodyof the corpus callosumwas
clearly seen in full profile. The second ROI was located in the axial
CARBALLEDO ET AL.
the midline. NOT regions were placed sagitally to exclude fibers
projecting laterally and/or medially. The dorsal cingulum was
identified placing the first ROI on the most posterior coronal slice,
where the genu of the corpus callosum was seen in full profile.
The second ROI was located on the most anterior coronal slice
at the midpoint between where the splenium of the corpus
callosum was seen in full profile and the third ROI on the coronal
slice at the midpoint between these two ROIs. NOT regions were
The parahippocampal cingulum was first identified on the
sagittal and coronal slices that provided the clearest profile of
the hippocampus. The first ROI was then traced around the
hippocampus in the sagittal plane. The second and the third
ROI were then traced on the adjacent medial and lateral slices.
NOT regions were placed on the slice below the lower body of the
The crus of the fornix contain fibers from the hippocampus
and the parahippocampal cortex. The first ROI was placed in the
coronal section at the level of the middle hippocampal body;
thesecond ROI wasplacedin the coronal sectionat the level where
the body of the fornix and both crus are clearly visible.
directionally color encoded FA maps (examples of which are
to diagnosis. For all subjects, the same numbers and locations of
ROIs were used as a start and these ROIs were predefined in the
anatomical T1 and FA images. Inter-rater reliability was calculated
after two raters independently performed the tractography in
20 participants. Intraclass correlations were between 0.90 and
0.95 for mean FA values in the tracts. After performing the
FIG. 1. DTI images for the left uncinate fasciculus, left fornix, left rostral cingulum, left dorsal cingulum, and left parahippocampal region using
540AMERICAN JOURNAL OF MEDICAL GENETICS PART B
tractography for all tracts for all individuals, the mean FA of tracts
were extracted and read into SPSS for further data analysis.
ROIs per tract were used to extract the white matter fiber tracts
of UF and crus fornix, and three circular AND-ROIs were used for
thecingulum(rostral, dorsal, andparahipocampalregions; Fig.1).
The Val66Met BDNF SNP (rs6265) was genotyped in this sample
using a Taqman?SNP Genotyping Assay on a 7900HT Sequence
Detection System (Applied Biosystems, Carlsbad, CA). The call
rate for the Taqman genotyping was >95% and all samples were in
Hardy–Weinbergequilibrium (P>0.05). Along with the testsam-
ples, a number of HapMap CEU DNA sample positive controls
(www.hapmap.org) and non-template negative controls were gen-
otyped for each SNP for quality control purposes. For positive
controls, all genotypes were found to be concordant with available
Morphometric measurements in both groups were normally dis-
homogenous (using Levine’s test). Differences in demographic
variables were tested using Student’s T-test, Chi-square test for
gender distribution and Mann–Whitney U-test for differences in
P<0.05/3¼0.016, since three ANCOVAs for different regions
variance (ANCOVA) to assess the main and interaction effects of
the within-subjects factor hemisphere (left and right), and the
between-subjects factors diagnosis (depression and control), and
BDNF-genotype (met-allele carriers and val/val) using age and
gender as co-variates. For the cingulum, an additional factor was
added for the subregions of the cingulum (rostral, dorsal, and
parahippocampal). Post hoc tests were performed using Sidak–
Bonferroni test following significant interactions between group
variables following the omnibus ANCOVA.
Demographics and Clinical Data
There were no differences in demographic details between patients
and controls, the details of which are presented in Table I. Patients
to healthy control individuals (met/met: 2 patients and 0 controls;
met/val: 13 patients and 8 controls; and val/val: 22 patients and 34
controls; Pearson’s c2¼5.5, df¼2, P¼0.065). Scores for depres-
sive illnessderived from Hamilton Rating Scale, Beck’s Depression
Inventory and MADRS were significantly different between the
patients group and the controls group, as it should be expected.
Scores for depressive illness as well as illness duration, cumulative
illness duration and age of onset did not differ between patients
carrying the met-allele compared to those homozygous for the
No significant main effects of diagnosis (F¼2.0, df¼1.73,
P¼0.17) and of BDNF (F¼1.6, df¼1.73, P¼0.22) alone were
seen in the UF. There was a significant interaction between BDNF
alleles and diagnosis (F¼8.6, df¼1.73, P¼0.004). Post hoc anal-
ysis using Sidak–Bonferroni correction showed that patients car-
rying the BDNF met-allele had smaller FA in the UF compared to
those patients homozygous for theval-allele(P¼0.009,corrected)
and compared to healthy subjects carrying the met-allele
(P¼0.015, corrected), whereby it was not significant compared
to healthy subjects being homozygous for the val-allele (P¼0.1,
corrected; Fig. 2). No significant effect was found between patients
being homozygous for the val-allele compared to healthy controls
homozygous for the val-allele (P¼0.72, corrected) or to healthy
controls carrying the met-allele (P¼0.99, corrected). No signifi-
cant main hemisphere effects were found. All results were Sidak
TABLE I. Demographic Characteristics for Patients and Controls
Weight [Gonca Akbulut et al., 2011]
Height [Chiang et al., 2011]
Illness duration (years)
Cumulative illness duration (years)
CARBALLEDO ET AL.
In the fornix no significant main effects of diagnosis (F¼0.28,
df¼1.73, P¼0.60) and of BDNF (F¼2.9, df¼1.73, P¼0.09)
were found. No significant interaction was found between BDNF
main hemisphere effect in the fornix. Left fornix FA was smaller
than the right fornix FA (F¼8.2, df¼1.73, P¼0.006).
A significant three-way interaction was detected between region of
significant diagnosis effect (F¼0.40, df¼1.73, P¼0.54) and no
significant interactions were found between diagnosis and BDNF
genotype (F¼0.001, df¼1.73, P¼0.97). No other significant
interactions, including brain hemisphere and region of the cingu-
lum, were detected. Left cingulum FA value though was smaller
than the right cingulum FA (F¼9.1, df¼1.73, P¼0.003).
rostral cingulum (F¼6.9, df¼1.77, P¼0.010) and a tendency or
trend in the left dorsal cingulum (F¼2.8, df¼1.77, P¼0.09),
meaning larger FA values for met-allele carriers in those two left
regions of the cingulum when compared to those homozygous for
the val-allele (Fig. 3).
Effects of Medication
There were no significant effects of medication group and no
significant interactions between medication group and BDNF
genotype on the FA of UF, fornix, or cingulum.
Additional Statistical Considerations
Results did not change and no additional results were found when
volumes of tracts were added as covariate in order to correct
for tract volume. Although tract FA values were normally distrib-
uted, we examined the data using the median of FA with non-
parametric Whitney U tests and this confirmed the findings
of DTI. The BDNF Val66Met (rs6265) nonsynonymous polymor-
et al., 2009] in human studies. BDNF plays an important role in
neuroplasticity [Grande et al., 2010] and has been repeatedly
associatedwithreducedbrain structures suchasthehippocampus,
main effect of this genetic varianton hippocampalvolumehasalso
Gerritsen et al., 2011]. The results of our study show that the
Val66Met polymorphism of BDNF plays an important role in
alterations of the UF, which it seems to be altered in MDD.
MDD patients carrying the met-allele have smaller FA in the UF
compared to patients homozygous for the val-allele and compared
to controls either carrying the met-allele or controls homozygous
for the val-allele. Further evidence for changes of the UF in MDD
came from a study showing reduced FA in connections between
the subgenual anterior cingulate cortex to amygdala in the right
hemisphereandbetween therightandleftuncinate tosupragenual
cingulum [Cullen et al., 2010].
The function of the UF is not fully known yet though it is
traditionally considered to be part of the limbic system [Hasan
et al., 2009]. The capacity for autonoetic self-awareness, that is re-
experiencing previous events as part of one’s past as a continuous
in auditory–verbal memory and declarative memory to the integ-
FIG. 2. FA values for the BDNF met-allele carriers and val/val genotype in the patients and the controls, for the left UF (A) and for the right UF (B)
df¼1.48, P¼0.003). In the right UF, patients carrying the met-allele show also smaller FA values than those patients homozygous for the
val-allele (F¼8.6, df¼1.35, P¼0.006), met-carrier healthy controls (F¼8.7, df¼1.22, P¼0.008) and healthy controls homozygous for the
542AMERICAN JOURNAL OF MEDICAL GENETICS PART B
with frontal regions [Taylor et al., 2007]. In a recent animal study
it was shown that maternal deprivation resulted in a reduction of
BDNF in the amygdala [R? eus et al., 2011] indicating that BDNF is
important in the amygdala in stress related disorders like MDD.
Functional MRI studies have demonstrated disconnectivity be-
tween prefrontal and limbic brain regions during emotion proc-
essing. A study in 15 unmedicated patients with MDD and 15
healthy volunteers found decreased cortical regulation of limbic
activation in response to negative stimuli [Anand et al., 2005].
significantly reduced amygdala–prefrontal functional connectivity
MDD had more negative functional connectivity between the
amygdala and frontal cortex than controls, this being corrected
by treatment with SSRIs [Chen et al., 2008]. These functional MRI
studies are consistent with findings of a behavioral processing bias
and support the finding that alterations of the UF play a role in
MDD. Further evidence for this comes from neuropsychological
studies investigating the effect of Val66Met BDNF on cognitive
function in healthy subjects and in patients with MDD [Forlenza
et al., 2011].
The other two tracts studied are closely related to the limbic
system. They are the fimbria/fornix, which projects from the
hippocampus to the septal region and mamillary bodies, and
the cingulum, which connects the enthorinal cortex and the
we found that met-allele carriers have larger FA values than those
homozygous for the val-allele and in particular for the regions of
the fornix and the left dorsal and left rostral cingulum. These
associations with the BDNF genotype seem to be not specific of
patients and thus they may be indicative of strong gene related
which show larger hippocampal volumes in BDNF met-allele
to structural MRI, studies have also shown no association between
Val66Met polymorphism and hippocampal volume in healthy
controls and in patients with MDD [Jessen et al., 2009; Benjamin
et al., 2010; Soliman et al., 2010; Richter-Schmidinger et al., 2011].
Others have reported reduced hippocampal volumes in subjects
or healthy [Bueller et al., 2006; Frodl et al., 2007].
et al.  detected an increase in FA values in MDD patients in
superior frontal gyrus to right pallidum and left superior parietal
gyrus to right superior occipital gyrus using tractography analysis.
Previous studies did not use tractography and found with voxel-
based or tract-based whole brain methods heterogenous results,
with the majority of studies showing decreased FA, however in
FIG. 3. FAvaluesfortheBDNFmet-alleleandval/valgenotypeintheleftandtherightdorsalcingulumandintheleftandtherightrostralcingulum;
showing the patient group and the control group separately. A significant difference of BDNF alleles was detectable in the left rostral cingulum
(F¼6.9, df¼1.77, P¼0.010) and a tendency or trend in the left dorsal cingulum (F¼2.8, df¼1.77, P¼0.09), meaning larger FA values for
the online version of this article, available at http://wileyonlinelibrary.com/journal/ajmgb]
CARBALLEDO ET AL.
different brain regions. This heterogeneity in findings may also be
due to differences in the applied approaches, as voxel based DTI
of atlas template [Van Hecke et al., 2008, 2011; Sage et al., 2009].
Some studies in late life depression consistently reported reduced
FA values in prefrontal brain regions [Bae et al., 2006; Nobuhara
et al., 2006b; Li et al., 2007; Murphy et al., 2007; Yang et al., 2007;
Shimony et al., 2009]. Reduced FA in the cingulate cortex has been
also detected [Murphy et al., 2007; Cullen et al., 2010; Taylor et al.,
2010]. In addition, Yang et al.  and Murphy et al. 
reported a reduction in FA values in the parahippocampal gyrus.
Blood et al.  found increased FA values in the right ventral
tegmental area and reduced FA values in dorsolateral prefrontal
white matter in MDD patients, whereas Abe et al.  did not
find alterations of FA between patients with MDD and healthy
BDNF polymorphism, our results need further exploration and
replication. Recent attempts to do so have been undertaken by
Chiang et al. They have shown that the Val-BDNF variant was
associated with lower FA values in the splenium of the corpus
callosum, left optic radiation, inferior fronto-occipital fasciculus,
and superior corona radiate but the UF was not one of the main
tracts included on the analysis [Chiang et al., 2011]. Montag et al.
 in their recent study of 99 healthy participants could not
find significant differences in DTI derived metrics between the
Met carriers and val/val carriers.
The identification of single candidate genes associated with
MDD has not been easy due to the likelihood of MDD being
a polygenic disorder associated with interactions between genetic
variants and environmental exposures [Uher, 2009]. However,
some studies have concentrated in the study of other relevant
polymorphisms. For instance, the association between the seroto-
nin transporter-linked polymorphism (5-HTTLPR/rs25531) and
MDD [Serretti et al., 2007]. Moreover, microstructural white
matter abnormalities have also been associated with this
5-HTTLPR/rs25531 polymorphism and MDD, both in depressed
and healthy individuals. Pacheco et al.  found a significant
main effect of 5-HTTLPR polymorphism on the microstructure
of the left UF,such that as the number of the S/Lg alleles increased,
the FA in the left UF decreased in healthy individuals. Alexopoulos
et al.  highlighted that depressed elderly S-carriers also had
lower FA values than L-allele homozygotes in frontolimbic brain
areas, including the dorsal and rostral anterior cingulate, posterior
cingulate, dorsolateral prefrontal, and medial prefrontal regions
and thalamus. S-alleles carriers had a lower remission rate than
L-allele homozygotes [MacQueen and Frodl, 2011].
The sample size of such a study needs discussion. The sample
survive Sidak–Bonferroni corrections. While there had been some
control design, which is sensitive to population stratification. This
with each BDNF allele did not differ for age, gender, origin, illness
of subjects with the BDNF met-allele. It could be argued that equal
numbers of individuals with the genetic subtype should have been
antidepressants affect diffusion parameters in the brain still is a
significant effect of medication group (no medication, SSRI, dual
differ with respect to current medication, so that medication is
unlikely to present a major problem. Also there was no significant
effect of medication group and no significant interaction between
medication group and BDNF genotype on the FA measures.
in the patient group. As little is known about the effect of different
antidepressants on white matter structure, an influence on the
retrieved imaging results cannot be excluded.
Another possible limitation is that with basic deterministic
tracking it is impossible to accurately reconstruct all the major
pathways, especially where fibers branch and cross [Tuch et al.,
2002]. The various methods being developed for resolving fiber-
crossing information are intriguing in that they partly ameliorate
the limitations of the tensor model [Behrens et al., 2007; Wheeler-
Kingshott and Cercignani, 2009; Wobrock et al., 2009; Jeurissen
et al., 2011; Vos et al., 2011a]. The use of HARDI, however, can
resolve more complex diffusion geometries than standard DTI,
such as in regions where fibers cross or mix and may be a useful
approach for future investigations.
In summary, the results of our study are the first to provide
evidence of microstructural white matter changes in MDD, in the
at the same time the Met66Val BDNF polymorphism that has
previously been described as closely related to MDD. MRI and
neuropsychological studies support the finding of alterations
of the uncinate fasciculus in MDD. We show that the Val66Met
in subjects with MDD or not. The met-allele of the BDNF poly-
morphism seems therefore to render subjects more vulnerable for
memory problems and autonoetic self awareness.
This work was supported by the Science Foundation Ireland
(SFI-Stokes Professor Grant to T.F.) and an infrastructure grant
from Health Research Board Ireland for developing of the Centre
of Advanced Medical Imaging at St. James’s Hospital, Dublin.
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