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: l.griffiths@griffith.edu.au

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

5484 Mol Biol Rep (2013) 40:5483–5490

123

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

Mol Biol Rep (2013) 40:5483–5490 5485

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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 %)

Mol Biol Rep (2013) 40:5483–5490 5487

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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

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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.

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