Shared Memory Multiprocessors Πολυεπεξεργαστές Μοιραζόμενης Μνήμης
BDNF and TNF-α polymorphisms in memory
Transcript of BDNF and TNF-α polymorphisms in memory
BDNF and TNF-a polymorphisms in memory
B. S. Yogeetha • L. M. Haupt • K. McKenzie • H. G. Sutherland •
R. K. Okolicsyani • R. A. Lea • B. H. Maher • R. C. K. Chan •
D. H. K. Shum • L. R. Griffiths
Received: 22 April 2013 / Accepted: 23 July 2013 / Published online: 6 August 2013
� Springer Science+Business Media Dordrecht 2013
Abstract Here, we investigate the genetic basis of human
memory in healthy individuals and the potential role of two
polymorphisms, previously implicated in memory function.
We have explored aspects of retrospective and prospective
memory including semantic, short term, working and long-
term memory in conjunction with brain derived neurotro-
phic factor (BDNF) and tumor necrosis factor-alpha (TNF-
a). The memory scores for healthy individuals in the
population were obtained for each memory type and the
population was genotyped via restriction fragment length
polymorphism for the BDNF rs6265 (Val66Met) SNP and
via pyrosequencing for the TNF-a rs113325588 SNP.
Using univariate ANOVA, a significant association of the
BDNF polymorphism with visual and spatial memory
retention and a significant association of the TNF-a poly-
morphism was observed with spatial memory retention. In
addition, a significant interactive effect between BDNF and
TNF-a polymorphisms was observed in spatial memory
retention. In practice visual memory involves spatial
information and the two memory systems work together,
however our data demonstrate that individuals with the
Val/Val BDNF genotype have poorer visual memory but
higher spatial memory retention, indicating a level of
interaction between TNF-a and BDNF in spatial memory
retention. This is the first study to use genetic analysis to
determine the interaction between BDNF and TNF-a in
relation to memory in normal adults and provides impor-
tant information regarding the effect of genetic determi-
nants and gene interactions on human memory.
Keywords Brain-derived neurotropic factor
(BDNF) � Memory � Genotype � Retrospective
memory � Prospective memory � Gene interactions
Introduction
Memory is a polygenic trait coordinated by neural mech-
anisms that varies between individuals. In practice, mem-
ory is a collection of complex systems, working together
for information storage, processing and retrieval and is a
key factor in every phase of human cognitive development
and crucial for everyday living. The mechanics of human
memory is complex, with multiple subsystems performing
different functions mediated by different brain regions. The
classification of memory types is based on the type of
information processed and is defined as declarative or
explicit memory and non-declarative or implicit memory.
Explicit memory is involved in conscious recall/recogni-
tion of facts, ideas or events and takes place in the medial
temporal lobe and/or hippocampus region of the brain [1].
In contrast, implicit memory is unconscious and expressed
as a change in behavior, not as recollections [2]. Due to the
ease of accessibility to explicit memory, it serves as the
B. S. Yogeetha � L. M. Haupt � K. McKenzie �H. G. Sutherland � R. K. Okolicsyani � R. A. Lea �B. H. Maher � L. R. Griffiths (&)
Genomics Research Centre, Griffith Health Institute and School
of Medical Science, Griffith University, Gold Coast, QLD 4222,
Australia
e-mail: [email protected]
R. C. K. Chan
Neuropsychology and Applied Cognitive Neuroscience
Laboratory, Key Laboratory of Mental Health, Institute of
Psychology, Chinese Academy of Sciences, Beijing, China
D. H. K. Shum
Behavioural Basis of Health Program, Griffith Health Institute
and School of Applied Psychology, Griffith University, Gold
Coast, QLD, Australia
123
Mol Biol Rep (2013) 40:5483–5490
DOI 10.1007/s11033-013-2648-6
ideal basis for memory tests. Explicit memory can be
further sub-divided into episodic memory and semantic
memory [3]. Episodic memory is described as detailed
experiences composed of familiarity with and recollection
of a previous event; whereas semantic memory involves
general knowledge of contextual events.
Episodic memory is composed of three subsystems: short
term, working and long-term memory. Short-term memory
is acquired through verbal, visual or auditory means (sen-
sory memory systems) and important information is selec-
ted by attention and further processed in working memory.
Working memory is a short-term memory system, where
accessible information is maintained for short periods of
time in an active, conscious state. In long-term memory,
information enters by means of rehearsal and subsequent
encoding [1, 4]. A further important classification of
memory is based on temporal direction of the memories and
is classified as retrospective or prospective memory. Ret-
rospective memory is where the content to be remembered
(people, words, events etc.) is in the past i.e. the recollection
of past episodes. It includes semantic, episodic and
declarative memory. In general it can be explicit or implicit.
Prospective memory is where the content to be remembered
is in the future and may be defined as ‘‘remembering to
remember’’ or remembering to perform an intended action.
Prospective memory may be either event-based or time-
based, often triggered by a cue, such as going to the doctor
(action) at 4 pm (cue), or remembering to post a letter
(action) after seeing a mailbox (cue) [5].
Brain-derived neurotropic factor (BDNF) is a member
of a family of neurotropic factors and plays an important
role in regulation, differentiation, and maintenance of
neuronal populations in the peripheral and central nervous
systems [6, 7]. BDNF has also been implicated in synaptic
remodeling of neurons, playing a crucial role in transmitter
synthesis, metabolism, release and post-synaptic ion
channel fluxes [8] during signal transduction. This crucial
role of BDNF in modulating hippocampal synaptic activity
and plasticity, is considered to have a significant effect on
cognitive function, in particular hippocampal related epi-
sodic memory [9]. This gene has also been implicated in
Long Term Potential (LTP) synaptic plasticity induction
and episodic memory performance [10–12]. BDNF seems
to be a major player in the mechanisms governing the
dynamics of memory. Previous data suggests BDNF is
involved in the consolidation of various type of memory in
different brain areas, in particular for persistence of long-
term memory storage in the hippocampus [13]. BDNF may
also be involved in counteracting the natural processes of
memory decay which involves rapid forgetting of memo-
ries described in aging and some neurodegenerative dis-
orders. A recent in vivo study on its structure showed that
the human BDNF gene has 11 exons containing nine
functional promoters localised specifically within the brain
[14].
In this study we have examined the BDNF SNP rs6265,
located within the 50 pro-BDNF sequence, which is a G to
A substitution at nucleotide 196 that results in a valine
(Val) 66 to methionine (Met) amino acid change. This
functional polymorphism does not affect mature BDNF
protein function, but alters the intracellular tracking and
packaging of pro-BDNF, mediating mature peptide secre-
tion [11]. This SNP has been found to be positively asso-
ciated with episodic memory in a Genome wide association
study (GWAS) conducted in a Swiss population [15]. Early
studies found abnormal hippocampal activation in carriers
of A (met) allele in comparison to G (Val) allele [11], since
then various studies have produced conflicting data on this
SNP with studies finding reduced activation in allele A
(met) carriers [16–19] and others with contrasting reduced
hippocampal activation in GG (Val) homozygotes [20–22].
Researchers have also suggested that the G allele is asso-
ciated with improved cognitive performance in early life,
but in later life it may contribute towards a faster rate of
cognitive decline thereby predisposing an individual to
cognitive impairment [23]. These contrasting data have
been suggested in a review article to be due to varied
sample sizes of individual studies and or population dif-
ferences in factors such as age and gender [24].
Tumor necrosis factor (TNF-a) is a cytokine predomi-
nantly generated by immune cells; however, it is also
expressed by glia and brain neurons, and has been associated
with memory formation and consolidation [25]. Several
studies have indicated specific involvement of TNF-a in
spatial learning and memory [26]. TNF-a has been identified
as necessary for synaptic efficacy; though high concentra-
tions are considered neurotoxic, low concentrations are
suggested to impair synaptic strength, and physiological
amounts were found to enhance synaptic efficacy via
increased surface expression of 2-aminomethyl phenylacetic
acid (AMPA). AMPA receptors mediate synaptic transmis-
sion within the central nervous system [25]. The functional
role of TNF-a on the nervous system is a matter of con-
troversy, with evidence indicating both deleterious and
protective effects of TNF-a during and/or after neuronal
damage [27–30]. Here, we examined the TNF-a marker
rs113325588, located on chromosome 6 in the 50UTR region
of the gene that results in an A to G substitution.
The TNF-a marker rs113325588, has not been previously
examined with regards to memory in healthy individuals,
however, BDNF and TNF-a are known to have an association/
interaction during memory formation. TNF-a was shown to
significantly and permanently alter the level of BDNF in the
brain, although this was found to not occur uniformly [9] and
TNF-a deprivation was shown to reduce hippocampal BDNF
levels [26]. In this study we examined these BDNF and TNF-a
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polymorphisms for their potential role in various memory
types including retrospective and prospective memory in
healthy individuals, and we also examined the potential
interaction between these polymorphisms.
Materials and methods
Subjects
In this study we have expanded upon previous data utilis-
ing participant memory scores and DNA extracted from
saliva samples to investigate the association between
BDNF and TNF-a, polymorphisms associated with retro-
spective and prospective memory function. As previously,
participants were recruited from within Griffith University
student and staff cohort, and from the local population. All
subjects enlisted within the study provided informed con-
sent and ranged in age from 16 to 51 years (Female
21.89 ± 5.8, Male 23.23 ± 6.6). The majority of partici-
pants were Caucasians of European descent living in
Australia who had varying levels of education. Individuals
who had suffered from head injuries and psychiatric illness
were excluded from analysis in an effort to obtain a normal
distribution of cognitive memory function unaffected by
external factors. Exclusion criteria also included those
familiar with or who had studied eastern Asian languages
in high school, due to the fact that the Shum Visual
Learning Test (SVLT) for retrospective visual learning and
memory incorporates Chinese characters and assumes no
knowledge of Chinese [31].
Retrospective memory tests
All participants were evaluated independently for their
memory abilities using a range of tests outlined previously
and summarised below [31]. All tests have acceptable
psychometric properties. The semantic memory of the
patients was assessed, with general knowledge questions
such as ‘‘How many weeks in a year?’’, based on the
information subset from the Wechler Adult Intelligence
Scale (WAS-IIII) with a value given for the total number of
questions correctly answered [32]. Memory scores for
verbal and visual short and long-term memory were
obtained using the Hopkins Verbal Learning Test (HVLT),
the Visual reproduction test and the SVLT. The HVLT [33,
34]: required the participant to listen to and memorise
words from a 12-word list, with the number of items cor-
rectly recalled recorded and averaged following three trials
(1–3). To obtain the long-term verbal memory measure, the
same test was repeated again after a 20-min delay to get a
Hopkins delayed score (trial 4). The Hopkins retained score
was used as a measure of long-term memory (the Hopkins
delayed score (trail 4) divided by the highest of trial 2 or 3).
The Visual Reproduction test was comprised of a series of
five designs, which were shown to participants, one at a
time for 10 s and the participants were then asked to draw
from memory. Each item was scored according to stand-
ardised scoring criteria where the presence and accuracy of
the various elements in the figure were assessed. The total
scores represented the Visual Reproductions I raw score.
Then, 25–35 min after the immediate recall trials, the
participants were given a delayed recall trial, and were
asked to draw freely recalled designs, in any order they
chose. This ‘‘free recall’’ component was the primary
Visual Reproductions II score measure. The SVLT is a
computerised test for assessing visual short- and long-term
memory. Chinese characters are used as visuo-spatial
stimuli, during this test, as Chinese characters have com-
plex elements and cannot be easily verbalised by non-
Chinese speakers [35]. The three learning trials are added
to give a learning index, which gives a measure of short-
term memory. A delayed recognition trial after a 20-min
interval served as a measure of long-term memory. To test
working memory, the Letter and Number Sequencing Test
(LNST) adapted from the WAIS-III [36] assessed partici-
pant verbal working memory. The participants were pre-
sented via audio a list of letters and numbers (e.g., F–4–B–
7) and were asked to repeat the numbers in ascending
order, and then the letters in alphabetical order (e.g. 4–7–
B–F). The measure obtained for this test was the total
number of trials correctly recalled.
Prospective memory tests
The comprehensive assessment of prospective memory
(CAPM) is a self-report questionnaire that analyses pro-
spective memory failures using a five-point scale ranging
from 1 (never) to 5 (very often) [37, 38]. The questionnaire
is comprised of three sections which measure how often
prospective memory slips occur, the perceived importance
of such slips in memory and the perceived rationale for
prospective remembering and forgetting. As described
previously, the CAPM Total Score was calculated using the
participant evaluation total for instrumental activities of
daily living (IALD) and basic activities of daily living
(BALD), divided by the total number of items minus those
that were not valid, giving a score between 0 and 5 [31]. The
Memory for Intentions Screening Test (MIST) prospective
memory test has been demonstrated as a valid measure of
prospective memory [39] whereby participants carry out
eight different prospective memory tasks within 30 min
whilst completing a puzzle that functions as a distracter task
[40]. The distractor task can be verbal of physical such as
‘‘In 2 min, ask me what time this session ends today’’, or
‘‘In 10 min, use that paper to write down the number of
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medications you are currently taking’’ [40, 41]. The mea-
sure obtained for this test is the MIST Prospective total
score, scored from 0 to 16. The MIST delayed scores were
also utilised in this study where a specified task was to be
completed in the future. Each participant was scored based
on their completion of the task, 2 points for the correct
information at the correct time (Correct time and response),
1 if they made one mistake (Correct time, incorrect
response OR correct response, incorrect time), and 0 if they
did not respond or completed the task at the wrong time
with the wrong information (No Response). The PRMQ
provides a self-report measure of prospective and retro-
spective memory slips in everyday life. It consists of sixteen
items, eight asking about prospective memory failures, and
eight concerning retrospective failures [42]. In this study
the PRMQ prospective scores were calculated by adding the
questionnaire rankings together and giving a final score
between 16 and 80 (the higher the score, the more often the
participants expected to omit prospective memory tasks
from everyday life).
DNA extraction and genotyping
All DNA extractions were completed as previously descri-
bed [31]. Briefly, saliva samples were collected and extrac-
ted as per the manufacturer’s protocol (DNA Genotek). DNA
stock solutions of 20 ng/lL were stored at 4 �C until geno-
typing analyses. For the BDNF rs6265 SNP, genotypes were
determined by PCR followed by RFLP. For PCR, primer
sequences were: forward, 50-CCTACAGTTCCACCAGGT
GAGAAGAGT-30 and reverse (50-GCTGCCGTTACCCA
CTCACT-30) (IDT). Following PCR the 480 bp amplicon
was analyzed by RFLP using the AflIII restriction enzyme.
Briefly, 10 lL of PCR product was digested using 5 units of
enzyme at 37 �C for 16 h. The digested product was elec-
trophoresed and fragments analysed on a 3 % agarose gel at
90 V for 50 min prior to being visualised under UV. To
validate observed genotypes, several samples underwent
Sanger sequencing and were analysed on an ABI 3130
Genetic Analyser (Life Technologies). Genotypes for the
TNF-a SNP rs113325588 were obtained by pyrosequencing
using the QIAGEN PyroMark Q24 (Qiagen) using the PCR
primers 50 ACCACAGCAATGGGTAGGAGA and 50
CTTTCATTCTGACCCGGAGA and the sequencing pri-
mer 50 TCTACATGGCCCTGT. Pyrosequencing was per-
formed as per the manufacturer’s instructions. Briefly, 15 lL
of PCR product was added to a mixture containing 2 lL of
streptavidin high performance Sepharose beads (GE
Healthcare), 40 lL binding buffer (Qiagen) and diluted to a
final volume of 80 lL using dH–2O. The denatured biotin-
labeled PCR amplicons were then combined with the
sequencing primer and incubated at 80 �C for 2 min prior to
being loaded into the PyroMark Q24 process chamber.
Genotypes were assigned to the sample pyrograms by the
PyroMark Q24 software (Qiagen).
Statistical analysis
For data analysis and interpretation, individuals possessing
a BDNF GG genotype (Val/Val) were analysed as one
genotype category while all the other individuals (GA, Val/
Met and AA, Met/Met) were combined as one category
[43]. For TNF-a, individuals with the genotypes AA and
AG formed one category and the GG genotype formed the
second category. Univariate ANOVA was used to compare
the mean scores for each memory measure between
genotype categories for both BDNF and TNF-a. Hardy–
Weinberg equilibrium (HWE) was confirmed in the cohorts
and all analysis was performed with Statistical Package for
the Social Science (SPSS) for Windows (version 17.0) with
an alpha level of 0.05 adopted used for significance.
Results
Genotyping
The population cohort examined consisted of 181 partici-
pants, 66.5 % of these were female (mean age,
21.89 ± 5.8 years) the remaining male participants were of
a mean age of 23.23 ± 6.6. The majority of the population
had English as their first language (91.4 %) and was of
Caucasian/Australian origin (76.7 %).
Observed genotype frequencies for study population of
181 participants for BDNF 6265 showed 113 samples to be
homozygous GG (Val/Val, 62.4 %), 56 were heterozygous
GA (Val/Met, 30.9 %), and 12 were homozygous AA
(Met/Met, 6.6 %) (Table 1). The observed population fre-
quencies for GA and AA genotypes are significantly dif-
ferent to the genotype frequencies from the CEU HapMap
population of (CEPH collection of Utah residents of
northern and western European ancestry) of GG (63.7 %),
GA (33.6 %) and AA (2.7 %), with our study population
demonstrating an increased number of individuals with the
A allele. The population examined was in HWE with a P
value of 0.17.
The observed genotype distribution for TNF-a marker
rs113325588 (Table 1) showed 133 samples identified as
GG homozygotes (73.4 %), 46 (25.4 %) as AG heterozy-
gotes, and only 2 samples (1 %) were identified as AA
homozygotes. Population allele frequencies for this SNP
were unavailable from HapMap, as only a single hetero-
zygote male has previously been reported for this SNP.
With our data confirming the cohort examined was in HWE
with a P value 0.36, this data for the first time examines
this SNP in a Caucasian population.
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Univariate ANOVA analysis was conducted for each
memory trait to test for statistically significant differences
between the dichotomous genotype groups for both genes.
Table 2 summarizes this data for both markers as well as
the combination of the BDNF and TNF-a markers. No
significant association was observed for any of the pro-
spective memory tests including CAMP, MIST, MIST-
delayed and PRMQ. For the retrospective memory tests,
there was no significant association observed for the
Hopkins learning, delayed and retained memory tests.
However, BDNF showed a significant association for
SVLT overall learning (P = 0.045). A significant associ-
ation was observed for BDNF with Visual reproduction II
(P = 0.001), and delayed SVLT (P = 0.034). For TNF-a,
significant association was demonstrated with SVLT
(P = 0.031). When we compared the mean test scores for
each of the genotype groups of BDNF and TNF-a, the
BDNF GG (Val/Val) group was revealed to have poorer
VR II scores (Fig. 1A) and higher SVLT scores when
compared to A Met allele carriers (Fig. 1B). In addition,
individuals with the GG genotype of TNF-a were shown to
have poorer SVLT scores when compared to both the AG
and AA genotypes (Fig. 1C).
We next examined the combined effect of observed
genotypes for any significant association with the memory
scores. This revealed no significant interaction between
BDNF and TNF for the prospective memory, Hopkins
learning, and delayed and retained memory scores. How-
ever, a significant association was observed when we
combined BDNF and TNF-a genotype data for SVLT
(P = 0.011), with significant interaction observed between
TNF-a and BDNF in SVLT (Table 2).
Discussion
In this study we applied genetic analyses to investigate the
role of BDNF and TNF-a polymorphisms in retrospective
and prospective memory. Significant association for the
VR II and the delayed SVLT tests were observed in the
cohort of healthy controls examined. VR II is the test for
visual memory (i.e. what—shapes and colours) and SVLT
is a test for Visio-spatial memory and learning (i.e.
where—locations and movement) [44].
Specifically, the visual reproduction test examines an
individual’s abilities including vision, attentiveness, and
the acquisition of immediate memory output. These are
examined in conjunction with retention ability from
immediate to recent memory where a delay component is
used to evaluate delayed memory at least 30 min after the
visual presentation [45]. Research on construct validity of
memory testing procedures has suggested that a delayed
VR is more closely associated with memory abilities while
an immediate VR is more closely associated with visual-
perpetual-motor ability (visual cognitive, visual analytic)
[46].
In contrast, the SVLT is a test for visual learning that
examines visuo-spatial memory and learning abilities. This
test uses Chinese characteristics, which presents visuo-
spatial relationships between lines, dashes, strokes and dots
[35]. The SVLT delayed test determines the retention of
learning after a 20 min delay. As both these tests are
delayed, the information is processed in working memory
for retention in long-term memory. Although in practice
these two systems (visual and spatial memory) work
together in some capacity, correlational studies have sug-
gested a separation between visual and spatial abilities in
both healthy and brain damaged patients [47].
Results of the current study indicated significant asso-
ciation between BDNF and TNF-a markers with the VR II
and SVLT delayed tests. In contrast, no significant asso-
ciation was observed with any of the prospective memory
tests, suggesting that both the BDNF and TNF-a SNPs
examined exert significant effect only on retrospective
memory and not on prospective memory. The GG (Val/
Val) genotype group of BDNF was shown to have poorer
Table 1 General characteristics
and genotype distributions of
the study population
Female Male Total
n 121 (66.8 %) 60 (33.1 %) 181
Age (in years) 21.89 ± 5.8 23.23 ± 6.6
WASI IQ 110.53 ± 10.1 113.95 ± 12.63
BDNF distribution (n = 181)
Homozygous G allele (Val/Val) 77 (42.5 %) 36 (19.8 %) 113 (62.4 %)
Homozygous A allele (Met/Met) 8 (4.4 %) 4 (2.2 %) 12 (6.6 %)
Heterozygous GA allele (Val/Met) 36 (19.8 %) 20 (11.0 %) 56 (30.9 %)
TNF distribution (n = 181)
Homozygous GG allele 90 (49.7 %) 43 (23.7 %) 133 (73.4 %)
Homozygous AA allele 2 (1 %) 0 (0) 2 (1 %)
Heterozygous AG allele 29 (16.0 %) 17 (9.3 %) 46 (25.4 %)
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VR II scores when compared with the other genotype
group (Val/Met and Met/Met, Fig. 1A). TNF-a genotype
did not show any association with VR II, indicating that the
TNF-a SNP has no significant effect on visual memory.
However, the GG (Val/Val) genotype group of BDNF was
shown to have poorer VR II scores when compared with
Fig. 1 Visual reproduction II and Shum Visual Learning Test results
in relation to BDNF and TNF-a genotypes. A Individuals with the
BDNF GG (Val/Val) genotype show poorer mean VR II test scores
than BDNF A allele carriers (Val/Met and Met/Met). B Individuals
with the BDNF GG (Val/Val) genotype show higher mean SVLT test
scores than BDNF A allele carriers (Val/Met and Met/Met).
C Individuals with the TNF-a GG genotype show poorer mean
SVLT test scores than TNF-a A allele carriers (AG and AA)
Table 2 Summary of univariate analysis of variance for BDNF and
TNF-a
Memory test Source F static P value Partial
g2
Visual reproduction I BDNF 0.311 0.578 0.002
TNF-a 1.951 0.164 0.011
BDNF* TNF-a 0.097 0.755 0.001
Visual reproduction II BDNF 8.987 0.003* 0.049
TNF-a 0.080 0.777 0.000
BDNF* TNF-a 0.079 0.779 0.000
MIST prospective BDNF 1.548 0.215 0.009
TNF-a 0.812 0.369 0.005
BDNF* TNF-a 0.001 0.971 0.000
MIST delay BDNF 1.079 0.300 0.006
TNF-a 2.460 0.119 0.014
BDNF* TNF-a 2.423 0.121 0.014
Hopkins learning BDNF 0.059 0.809 0.000
TNF-a 0.184 0.668 0.001
BDNF* TNF-a 0.144 0.705 0.001
Hopkins trail 4 delay BDNF 3.594 0.060 0.020
TNF-a 1.586 0.210 0.009
BDNF* TNF-a 0.831 0.363 0.005
Hopkins retained BDNF 0.947 0.332 0.005
TNF-a 0.798 0.373 0.005
BDNF* TNF-a 0.026 0.873 0.000
SVLT overall learning BDNF 4.073 0.045* 0.025
TNF-a 2.783 0.097 0.017
BDNF* TNF-a 0.888 0.347 0.006
SVLT delayed BDNF 4.562 0.034* 0.028
TNF-a 4.758 0.031* 0.029
BDNF* TNF-a 6.636 0.011* 0.041
CAPM total BDNF 0.006 0.940 0.000
TNF-a 0.348 0.556 0.002
BDNF* TNF-a 0.019 0.890 0.000
PRMQ prospective BDNF 0.487 0.486 0.003
TNF-a 0.129 0.720 0.001
BDNF* TNF-a 0.076 0.784 0.000
PRMQ retrospective BDNF 0.037 0.848 0.000
TNF-a 0.324 0.570 0.002
BDNF* TNF-a 0.000 0.998 0.000
WAIS LNST BDNF 1.225 0.270 0.007
TNF-a 3.110 0.080 0.018
BDNF* TNF-a 0.085 0.772 0.000
WAIS information BDNF 1.186 0.278 0.007
TNF-a 3.691 0.056 0.021
BDNF* TNF-a 4.212 0.042* 0.024
** Scores adjusted for age, gender and WAIS IQ score
5488 Mol Biol Rep (2013) 40:5483–5490
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the other genotype groups (Val/Met and Met/Met, Fig 1A)
suggesting that BDNF G (Val) allele carriers have poorer
visual memory when compared to A (Met) allele carriers.
When we combined the data from both the VR II and
SVLT-delayed tests, the BDNF GG (Val/Val) genotype
group of BDNF, demonstrated significant association with
SVLT delayed test with participants obtaining a higher
score (Fig. 1B). This indicates higher memory retention of
G (Val) allele in spatial memory compared to the A (Met)
allele, contradictory to data demonstrating poorer memory
retention of the BDNF G (Val) allele in visual memory
(Fig. 1A). In practice, visual memory involves spatial
information and the two memory systems work together,
this conflicting role of the gene associated with a GG (Val/
Val) genotype may relate to an interactive effect of TNF-aon BDNF in spatial memory retention. Interestingly, a
previous study demonstrated the influence of TNF-a on
BDNF synthesis, permanently altering brain BDNF levels
and affecting spatial learning and memory [9, 26]. Our data
supports this finding indicating there are significant gene
interactions between TNF-a and BDNF. We also observed
that individuals with a GG genotype of TNF-a demon-
strated poorer SVLT scores when compared to A allele
carriers (AG, and AA, Fig. 1C).
The BDNF rs6265 SNP was chosen for analysis in this
study as it has previously shown associations with aspects
of memory function and many other neurological phe-
nomena and is well characterized in terms of its affect on
mature BDNF secretion. The TNF-a rs113325588 SNP
resides in the promoter region and may impact on
expression of the gene altering localised and downstream
signaling. Although the sample size of this study is low,
with the acknowledged risk of a false positive or negative
result, these results are interesting and warrant further
testing. Individuals are currently being recruited for this
purpose with positive associations for these SNPs in some
of the aspects of memory examined in this study justifying
genotyping other SNPs from BDNF and TNF-a loci to
allow a more haplotype-based analysis in these future
studies.
In this study, we identify a plausible genetic link
between BDNF genotype and visual memory as well as
between specific genotype combinations in BDNF and
TNF-a with spatial memory. Specifically, we suggest that
spatial memory is mediated by TNF-a during spatial
memory retention. In addition, a previously unidentified
interaction between these two genes may be a contributing
factor to previous conflicting data surrounding the BDNF
SNP rs6265. With BDNF known to influence neurode-
generative events, an understanding of the gene interac-
tions in healthy individuals may shed more light on the
identification of the specific genes and their associated
genotypes dysregulated in neurodegenerative disorders.
Acknowledgments This research was supported by the Genomics
Research Centre (GRC), Griffith Health Institute (GHI) and the
School of Medical Science at Griffith University Gold Coast campus.
References
1. Schwartz BL (2011) Memory : foundations and applications.
SAGE, Thousand oaks
2. Squire LR, Kandel ER (1999) Memory: from mind to molecules.
Scientific American Library (Freeman and Co.), New York
3. Scheffler I (1965) Conditions of knowledge. Scott Foresman and
Company, Glenview
4. LuZL et al (2005) Fast decayof iconic memory in observers with mild
cognitive impairments. Proc Natl Acad Sci USA 102(5):1797–1802
5. Schoeke A, Bittlin T et al (2007) Cognitive psychology and
cognitive neuroscience. Books4x Company, ISBN 1449986438
6. Binder DK, Scharfman HE (2004) Brain-derived neurotrophic
factor. Growth Factors 22(3):123–131
7. Huang EJ, Reichardt LF (2003) Trk receptors: roles in neuronal
signal transduction. Annu Rev Biochem 72:609–642
8. Ashe PC, Berry MD, Boulton AA (2001) Schizophrenia, a neu-
rodegenerative disorder with neurodevelopmental antecedents.
Prog Neuropsychopharmacol Biol Psychiatry 25(4):691–707
9. Aloe L et al (1999) Learning abilities, NGF and BDNF brain
levels in two lines of TNF-alpha transgenic mice, one charac-
terized by neurological disorders, the other phenotypically nor-
mal. Brain Res 840(1–2):125–137
10. de Quervain DJ et al (2003) A functional genetic variation of the
5-HT2a receptor affects human memory. Nat Neurosci 6(11):
1141–1142
11. Egan MF et al (2003) The BDNF val66met polymorphism affects
activity-dependent secretion of BDNF and human memory and
hippocampal function. Cell 112(2):257–269
12. Weinstock-Guttman B et al (2011) The rs2030324 SNP of brain-
derived neurotrophic factor (BDNF) is associated with visual cog-
nitive processing in multiple sclerosis. Pathophysiology 18(1):43–52
13. Bekinschtein P et al (2008) BDNF and memory formation and
storage. Neuroscientist 14(2):147–156
14. Pruunsild P et al (2007) Dissecting the human BDNF locus:
bidirectional transcription, complex splicing, and multiple pro-
moters. Genomics 90(3):397–406
15. Papassotiropoulos A et al (2006) Common Kibra alleles are associ-
ated with human memory performance. Science 314(5798):475–478
16. Banner H et al (2011) The brain-derived neurotrophic factor
Val66Met polymorphism is associated with reduced functional
magnetic resonance imaging activity in the hippocampus and
increased use of caudate nucleus-dependent strategies in a human
virtual navigation task. Eur J Neurosci 33(5):968–977
17. Cerasa A et al (2010) The effects of BDNF Val66Met polymorphism
on brain function in controls and patients with multiple sclerosis: an
imaging genetic study. Behav Brain Res 207(2):377–386
18. Gasic GP et al (2009) BDNF, relative preference, and reward
circuitry responses to emotional communication. Am J Med
Genet B 5(6):762–781
19. Hashimoto R et al (2008) Dose-dependent effect of the Val66Met
polymorphism of the brain-derived neurotrophic factor gene on
memory-related hippocampal activity. Neurosci Res 61(4):360–367
20. Lu Y, Christian K, Lu B (2008) BDNF: a key regulator for
protein synthesis-dependent LTP and long-term memory? Neu-
robiol Learn Mem 89(3):312–323
21. Schofield PR et al (2009) Disturbances in selective information
processing associated with the BDNF Val66Met polymorphism:
evidence from cognition, the P300 and fronto-hippocampal sys-
tems. Biol Psychol 80(2):176–188
Mol Biol Rep (2013) 40:5483–5490 5489
123
22. Dennis NA et al (2011) Brain-derived neurotrophic factor
val66met polymorphism and hippocampal activation during epi-
sodic encoding and retrieval tasks. Hippocampus 21(9):980–989
23. Harris SE et al (2006) The brain-derived neurotrophic factor
Val66Met polymorphism is associated with age-related change in
reasoning skills. Mol Psychiatry 11(5):505–513
24. Dodds CM et al (2013) Overestimation of the effects of the
BDNF val66met polymorphism on episodic memory-related
hippocampal function: a critique of a recent meta-analysis.
Neurosci Biobehav Rev 21(13):00026–00027
25. Das UN (2003) Can memory be improved? A discussion on the
role of ras, GABA, acetylcholine, NO, insulin, TNF-alpha, and
long-chain polyunsaturated fatty acids in memory formation and
consolidation. Brain Dev 25(4):251–261
26. Golan H et al (2004) Involvement of tumor necrosis factor alpha in
hippocampal development and function. Cereb Cortex 14(1):97–105
27. Chen LE et al (1996) Tumor necrosis factor promotes motor
functional recovery in crushed peripheral nerve. Neurochem Int
29(2):197–203
28. Dawson DA, Martin D, Hallenbeck JM (1996) Inhibition of tumor
necrosis factor-alpha reduces focal cerebral ischemic injury in the
spontaneously hypertensive rat. Neurosci Lett 218(1):41–44
29. Eddy LJ, Goeddel DV, Wong GH (1992) Tumor necrosis factor-
alpha pretreatment is protective in a rat model of myocardial
ischemia-reperfusion injury. Biochem Biophys Res Commun
184(2):1056–1059
30. Rothwell NJ, Luheshi GN (1996) Brain TNF: damage limitation
or damaged reputation? Nat Med 2(7):746–747
31. Donges B et al (2012) Role of the apolipoprotein E and catechol-
O-methyltransferase genes in prospective and retrospective
memory traits. Gene 506(1):135–140
32. Wechsler D, Matarazzo JD (1972) Wechsler’s measurement and
appraisal of adult intelligence. Williams & Wilkins, Baltimore
33. Benedict RH et al (1998) Hopkins Verbal Learning Test–revised:
normative data and analysis of inter-form and test-retest reli-
ability. The Clinical Neuropsychologist 12(1):43–55
34. Brandt J (1991) The Hopkins Verbal Learning Test: development
of a new memory test with six equivalent forms. The Clinical
Neuropsychologist 5(2):125–142
35. Shum DH, O’Gorman JG, Eadie K (1999) Normative data for a
new memory test: the Shum Visual Learning Test. Clin Neuro-
psychol 13(2):121–135
36. Wechsler D (1987) Wechsler memory scale: WMS-R. Psycho-
logical Corp., Harcourt Brace Jovanovich, San Antonio
37. Chau LT et al (2007) Reliability and normative data for the
comprehensive assessment of prospective memory (CAPM).
Neuropsychol Rehabil 17(6):707–722
38. Fleming J et al (2009) Validity of the comprehensive assessment
of prospective memory (CAPM) for use with adults with trau-
matic brain injury. Brain Impairment 10(01):34–44
39. Raskin SA (2009) Memory for Intentions Screening Test: psycho-
metric properties and clinical evidence. Brain Impair 10(1):23–33
40. Woods SP et al (2008) Psychometric characteristics of the memory
for Intentions Screening Test. Clin Neuropsychol 22(5):864–878
41. Raskin SA (2009) Memory for intentions screening test: psycho-
metric properties and clinical evidence. Brain Impair 10(01):23–33
42. Crawford JR et al (2003) The Prospective and Retrospective
Memory Questionnaire (PRMQ): normative data and latent
structure in a large non-clinical sample. Memory 11(3):261–275
43. Gajewski PD et al (2011) The Met-allele of the BDNF Val66Met
polymorphism enhances task switching in elderly. Neurobiol
Aging 32(12):30
44. Klauer KC, Zhao Z (2004) Double dissociations in visual and
spatial short-term memory. J Exp Psychol Gen 133(3):355–381
45. Hori T et al (2013) Visual reproduction on the wechsler memory
scale-revised as a predictor of Alzheimer’s disease in Japanese
patients with mild cognitive impairments. Dement Geriatr Cogn
Disord 35(3–4):165–176
46. Larrabee GJ et al (1985) Construct validity of various memory
testing procedures. J Clin Exp Neuropsychol 7(3):239–250
47. Sala SD et al (1999) Pattern span: a tool for unwelding visuo-
spatial memory. Neuropsychologia 37(10):1189–1199
5490 Mol Biol Rep (2013) 40:5483–5490
123