Is there a significant interaction between life
adversity and the brain-derived neurotrophic
factor gene in mood disorders?
Celia Shiles
Supervisor: Dr. Georgina Hosang
Abstract
Background
A growing body of research has shown that gene-environmental interactions may play an important
role in the development of mood disorders. The aim of this review was to systematically examine
the evidence for an interaction between a variant in the Brain-derived neurotrophic factor gene
[BDNF] and life adversity [LA] in mood disorders.
Methods
The databases Medline, Embase and PsychINFO were used and the search terms were synonyms for
BDNF Val66Met variant, Life Adversity and Mood disorders. Only studies that investigated the
interaction between BDNF Val66Met variant and LA in mood disorders were included.
Results
Eight out of the eleven studies found some type of significant interaction between BDNF Val66Met
variant and LA. There was no simple reason for some studies finding an interaction and others not.
It is more likely to be a combination of differences in study designs that cause this discrepancy.
Limitations
The main limitations of this review are the publication bias, some missing data and the
heterogeneity of the studies made it difficult to directly compare them.
Discussion
To our knowledge this is the first systematic review of this topic. It has shown that this area of
research should be pursued further and it can also offer some recommendations for future studies.
Introduction
Mood disorders are psychiatric illnesses in which the main feature is excessively high or low mood,
such as depression and bipolar disorder. These are crippling illnesses that affect a surprisingly large
number of people, with 15% of the population suffering from depression and 1% from bipolar
disorder at some point in their lifetime (Peveler, Carson et al. 2002). Tragically they are not only
disabling but often fatal, as 10% of people with depression and 15% of people with bipolar disorder
die by suicide (Peveler, Carson et al. 2002). Furthermore they are a large drain on the economy as
depression alone is estimated to cost the UK economy over £9 billion per year (Thomas and Morris
2003). Further research into understanding the development of mood disorders is essential in order
to reduce this burden.
Studies show that genetics play a crucial role in an individual’s susceptibility to developing a mood
disorder, for example twin studies suggest that the heritability of bipolar disorder is 85% and major
depression is 40% (McGuffin, Katz et al. 1991; McGuffin, Katz et al. 1996; McGuffin, Rijsdijk et al.
2003; Kendler, Gatz et al. 2006).
The role of Brain-Derived Neurotrophic Factor protein in mood disorders
A gene that may have an important role in the pathology of mood disorders is the Brain-Derived
Neurotrophic Factor [BDNF] gene. This gene codes for the BDNF protein, which is a growth factor
that is involved in the proliferation, differentiation, survival and synaptic plasticity of neurons
(Duman and Monteggia 2006; Groves 2007). There are three lines of evidence to suggest that the
BDNF protein is involved in the pathology of mood disorders. Firstly BDNF protein appears to be
lowered in people with mood disorders. Human studies have found lower hippocampal BDNF
protein in suicide patients with depression at post mortem (Dwivedi, Rizavi et al. 2003; Karege,
Vaudan et al. 2005). Furthermore lower serum BDNF protein has been found in patients with
depression and bipolar disorder (Cunha, Frey et al. 2006; Sen, Duman et al. 2008). Secondly,
antidepressants appear to increase BDNF protein in humans and animals. Raised BDNF protein has
been found in patients taking antidepressants in the serum and in the hippocampus at post mortem
(Karege, Vaudan et al. 2005; Sen, Duman et al. 2008). In addition, rats have increased BDNF protein
after many antidepressant treatments including Serotonin Selective Reuptake Inhibitors,
Noradrenaline Reuptake Inhibitors, Monoamine Oxidase Inhibitors, Electro Convulsive Therapy,
Transcranial Magnetic Stimulation and exercise (Nibuya, Morinobu et al. 1995; Russo-Neustadt,
Beard et al. 1999; Müller, Toschi et al. 2000; Chen, Dowlatshahi et al. 2001; Caspi, Sugden et al.
2003; Coppell, Pei et al. 2003; Dias, Banerjee et al. 2003; de Foubert, Carney et al. 2004; Russo-
Neustadt, Alejandre et al. 2004). Thirdly, BDNF protein injections into the midbrain, hippocampus
and lateral ventricles of mice showed an antidepressant effect that is equal to antidepressants
(Siuciak, Lewis et al. 1997; Shirayama, Chen et al. 2002; Hoshaw, Malberg et al. 2005). Furthermore
this effect can be blocked by suppressing the main BDNF protein receptor, TrkB (Shirayama, Chen et
al. 2002).
Contrastingly some studies have found pro-depressant effects of increased BDNF protein,
particularly in relation to the ventral tegmental area and the nucleus accumbens (Duman and
Monteggia 2006; Groves 2007). Transgenic mice have been used in an attempt to clarify the role of
BNDF protein but the results so far have been unclear with heterozygous, conditional knockout mice
showing some depressive symptoms and some non-depressive symptoms (Monteggia, Luikart et al.
2007). In summary the three strands of evidence for the role of BDNF protein in the pathology of
mood disorders indicate that there is decreased hippocampal and serum BDNF protein in mood
disorders, which is increased by antidepressant treatment and furthermore BDNF protein injections
have antidepressant effects.
Brain-Derived Neurotrophic Factor gene in mood disorders
Since evidence suggests that BDNF protein has a significant role in the pathology of mood disorders,
it is has been investigated whether certain alleles of the BDNF gene produce an increased genetic
susceptibility for mood disorders. There are two key alleles for BDNF polymorphism rs6265;
Methionine [Met] and Valine [Val]. In vitro hippocampal neurons virally infected with the Met allele
and Met/Met mice have significantly decreased activity dependent secretion of BDNF protein (Egan,
Kojima et al. 2003; Chen, bath et al. 2008). In addition, human Met carriers have significantly
smaller hippocampal volumes on MRI scan, which is associated with mood disorders ((Pezawas,
Verchinski et al. 2004; Frodl, Möller et al. 2008). Thus it would be expected that people with the
Met allele would have a higher genetic susceptibility to mood disorders. However a meta-analysis of
population studies demonstrates no significant difference in the number of people with mood
disorders between carriers of the Met or Val allele for the BDNF Val66Met variant (Willis-Owen,
Fullerton et al. 2005; Kanazawa, Glatt et al. 2007; Surtees, Wainwright et al. 2007). In a similar way,
much research has been undertaken to uncover other susceptibility genes for mood disorders with
disappointing results (Levinson 2006; Farmer, Elkin et al. 2007). One reason for this may be that
genetic studies have not taken into account gene-environmental interactions.
Gene-environment interactions in mood disorders
Gene-environmental interactions are how environmental factors moderate the effect of genes. The
best known example of a gene-environmental interaction in psychiatry is concerned with the effect
of 5-HTTLPR polymorphism in the Serotonin Transporter gene on depression (Caspi, Sugden et al.
2003). There is a significantly higher risk of developing depression after stressful life events among
individuals with at least one Short allele of the 5-HTTLPR compared to an individual with two Long
alleles. However this finding has not always been replicated (Munafò, Durrant et al. 2009; Uher and
McGuffin 2010).
Life Adversity
A growing body of research has focused on the relationship between the environmental factor Life
Adversity [LA] and the BDNF polymorphism rs6265 ((Duman and Monteggia 2006). LA covers
stressful and traumatic experiences throughout the lifespan including childhood abuse,
bereavement or marital difficulties (Hammen 2005; Johnson 2005). After experiencing LA, people
have an increased likelihood of developing a mood disorder (Hammen 2005; Johnson 2005). In
addition, research indicates that LA decreases BDNF protein as stressed mice have lower
hippocampal BDNF protein (Ueyama, Kawai et al. 1997; Rasmusson, Shi et al. 2002; Roceri, Hendriks
et al. 2002; Pizarro, Lumley et al. 2004; Roceri, Cirulli et al. 2004) and traumatic events are
associated with decreased serum BDNF protein in patients with bipolar disorder (Kauer-Sant'Anna,
Tramontina et al. 2007). Therefore according to the Neurotrophic Hypothesis, LA induces a decrease
in BDNF protein, which may lead to hippocampal atrophy which in turn is associated with mood
disorders (Duman and Monteggia 2006; Groves 2007; Stein, Savitz et al. 2008).
Aim of this systematic review
Consequently it would be logical to hypothesis that a person with the Met allele for BDNF Val66Met
variant who is exposed to LA is at higher risk of developing depression than a person with the Val
allele who is exposed to LA (Duman and Monteggia 2006). Therefore the aim of this systematic
review is to address the question, ‘Is there is a significant interaction between LA and BDNF Val66Met
variant in mood disorders?’
This is a crucial question since a better understanding of the
relationship between LA and the BDNF Val66Met variant in mood disorders may result in much
needed preventative treatment or drug targets, which could help alleviate the huge burden of mood
disorders.
Method
Search terms: synonyms for Mood
Disorders, Life Adversity and BDNF
Databases: PsychINFO, Medline and
EMBASE
Removal of 71 duplicates
104 studies
Inclusion: BDNF Val66Met variant - Life
Adversity interaction in mood disorders
Exclusion: Studies looking at only one
symptom
Removal of 93 studies
11 studies:
3 on adult adversity
6 on childhood adversity
2 on both adult and childhood adversity
Diagram 1 shows the selection strategy for this systematic review.
Search Strategy
The databases (1) PsychINFO, (2) Medline and (3) Embase were used and the search terms were
looked for in the title, abstract, heading word, table of contents, key concepts, original title, tests
and measures (Diagram 1).
The search terms were synonyms for mood disorders, LA and the BDNF Val66Met variant. They were
as follows:
1. Mood disorders (bipolar disorder, bipolar affective disorder, bipolar mood disorder, bipolar
depression, manic, manic depression, manic depressive psychosis, affective disorder,
cyclothymic personality, affective psychosis, major depression and mania or depression or
major depressive disorder or major depression or unipolar depression).
2. Stressful Life Events (gene-environmental interaction, childhood maltreatment, childhood
adversity, child stress, child abuse, child neglect, stressful life events, life events, life stress,
adversity, negative life events or adverse life events.
3. BDNF Val66Met variant (BDNF, Brain derived neurotrophic factor, rs6265 or Val66Met)
Selection Strategy of Studies
The total number of search results was 175 studies; 101 in Embase, 42 in PsycInfo and 32 in Medline.
After duplicates were removed, 104 studies remained. The inclusion criteria were studies that
investigated the interaction between BDNF Val66Met variant and LA. For example several studies
had investigated BDNF Val66Met variant - Another Gene - LA interaction and these studies were only
included if they had reported their findings on the interaction between BDNF Val66Met variant and
LA. Additionally studies were excluded if they did not investigate the sets of symptoms required for
a mood disorder. For example studies that concentrated on single symptoms, such as dissociation or
rumination, were excluded.
Quality Appraisal of Studies
The selected studies were carefully read and split into studies that had investigated LA during
adulthood and those that had investigated LA during childhood. The data extracted from the studies
included: study type, sample size, sample characteristics, percentage of sample who were Met
carriers, measurement of LA, measurement of mood disorder and the result (Table 1 and 2). The
studies were quality appraised using this data.
Results
The selection strategy found eleven studies in total; three had investigated adult LA (Kim, Stewart et
al. 2007; Drachmann Bukh, Bock et al. 2009; Hosang, Uher et al. 2010), six had investigated
childhood LA (Kaufman, Yang et al. 2006; Wichers, Kenis et al. 2008; Aguilera, Arias et al. 2009;
Nederhof, Bouma et al. 2010; Carver, Johnson et al. 2011; Grabe, Schwahn et al. 2012) and two had
investigated both adult and childhood LA (Lavebratt, Aberg et al. 2010; Juhasz, Dunham et al. 2011)
(Table 1 and 2). The studies were very diverse in design.
One of the main differences between the studies was that some were case control studies,
comparing people with a diagnosis of a mood disorder to those without such a diagnosis. Whereas
other studies focused on the symptoms of depression across the population rather than the
diagnosis of a mood disorder. The difference in the statistical analysis of these two types of studies
may affect the likelihood of finding an interaction (Munafò, Durrant et al. 2009).
Another difference was that some of the studies used previously diagnosed clinical cases of mood
disorders, whereas other studies used a community sample. Therefore the former studies are likely
to have included more severe forms of mood disorder and consequently have a higher chance of
finding a significant interaction. However the latter studies are perhaps more representative of the
spectrum within the mood disorder diagnosis observed in the community. For example Lavebratt et
al (2010) found that two thirds of the clinically depressed cases in their study had not sought care
and only 26% had seen a psychiatrist.
There were also discrepancies in the severity and amount of LA reported in the samples. This would
affect the results as samples including more severe and larger amounts of LA are more likely to find
a significant interaction.
Another disparity between studies was that some had measured mood disorders and LA using
interviews whereas others had used questionnaires. Research shows interviews to be a more
reliable measurement of LA and mood disorders (Monroe 2008). In addition, a systematic review of
the interaction between the Serotonin Transporter gene and stressful life events found a lower rate
of positive findings in studies using questionnaires to measure stressful life events in comparison to
those that used interviews (Uher and McGuffin 2010).
Therefore the reliability of these
measurements may have affected the results in the studies included in this review.
There was also variety in what LA was measured as many different questionnaires were used
including the Childhood Trauma Questionnaire, the Risky Families Questionnaire, the Recent Life
Events questionnaire and the Life Threatening Experiences questionnaire. In addition, the index
period for adult LA differed, some studies asked about any LA during the last six months whilst
others asked about the last twelve months. This may affect the results as the depressogenic effect
of adult LA is thought to decrease with time after the event (Kendler, Karkowski et al. 1998).
The studies had also investigated many different mood disorders including Bipolar Disorder,
Depression and Dysthymia.
One of the most crucial aspects affecting the reliability of the results is the sample size, which ranged
considerably. However larger studies were more likely to use questionnaires and therefore they
could be as reliable as smaller studies using interviews. These types of multiple differences amongst
the studies made it difficult to compare them directly and thus a meta-analysis would not be
feasible. However it was possible to take these diversities into consideration and get a general sense
of the results.
Adult Life Adversity
Within the five studies that investigated adult LA, three had found a significant interaction and two
had not (Table 1). All of these studies had their pros and cons but none were clearly more or less
reliable than the others. Lavebratt et al (2010) and Juhasz et al (2011) did not find a significant
interaction between LA and BDNF Val66Met variant and used larger, more representative samples.
However the unreliability of using a questionnaire for LA instead of an interview plus the lessened
impact of measuring LA during the last 12 months instead of the last 6 months may have led to a
negative result. It would be useful to know the exact probability values of these studies to ascertain
the direction of the interaction between adult LA and the BDNF Val66Met variant.
Conversely the positive finding of two of the studies that did find an interaction are not statistically
strong, p=0.05 (Drachmann Bukh, Bock et al. 2009) and p=0.04 (Hosang, Uher et al. 2010), and
therefore it is possible that they are due to chance. Furthermore, although Hosang et al (2011)
measured LA with an interview, the subjects were asked to recall events that happened before their
worse bipolar episode. This could be a long time ago and therefore may have increased recall bias.
Kim et al (2007) found a very significant interaction (p<0.001) but had used a comparatively small
sample of cases. However this may have been compensated for by the much higher percentage of
Met carriers for the BDNF Val66Met variant within the Korean sample and the higher levels of LA
amongst the sample due to it being an old aged sample (65+).
In conclusion, these results are encouraging that there is an interaction between BDNF Val66Met
variant and adult LA but there is still the possibility that the positive results are due to chance and
clearly needs to be investigated further.
Childhood adversity
Within the eight studies that investigated child LA, four studies found an interaction, three studies
did not and one only found an interaction with childhood sexual abuse (Table 2). Some of these
studies had more severe limitations than the others. The sample used by Carver et al (2011) was
very small with only 35 cases of depression and therefore should be interpreted with caution
considering the large number of participants required to detect gene-environment interactions.
Furthermore a small proportion of the sample reported experiencing child LA, perhaps due to the
sample being 75% undergraduate students and thus more likely to have experienced a privileged
childhood. However this should decrease the chances of finding an interaction but it was still found.
Likewise Wichers et al (2008) used a weaker method as the most explicit items on the Childhood
Trauma Questionnaire about sexual and physical abuse were removed for ethical reasons. However
again this would be expected to decrease the likelihood of finding an interaction but it was found
(Wichers, Kenis et al. 2008).
Nederhof et al’s (2010) result should be interpreted with care as they averaged the depression
scores of three questionnaires that had been completed over 5 years.
Consequently one
questionnaire during a depressive episode and two questionnaires during healthy periods could
have on average lead to a non-depressed score. Another point to take into consideration is that
although Kaufmann et al (2006) did not find a significant interaction; they did find a trend as the
probability value was 0.09. Therefore perhaps if they had used a larger sample they might have
found a significant interaction.
After taking into account the limitations of some of these studies, the results suggest that there is an
interaction between BDNF Val66Met variant and childhood LA but it is not clear cut.
Discussion
In summary, eight out of the eleven studies found some type of significant interaction between
BDNF Val66Met variant and LA. Therefore this is certainly an area of research that should be pursued
further. There was no simple reason for some studies finding an interaction and others not. It is
more likely to be a combination of differences in study designs that caused this discrepancy.
There are three main limitations to this review. Firstly only published studies were included and
therefore there is likely to be some publication bias (Olson, Rennie et al. 2002). Secondly some of
the data is missing from the table of results, for example some of the exact probability values are
missing for studies that did not find a significant interaction. Thirdly the heterogeneity of the studies
made it very difficult to directly compare them. However the main strength of this review is that to
our knowledge it is the first systematic review of the studies. It has shown that this is an area that
should be researched further and in addition it can offer some recommendations for future studies
based on the limitations and strengths of the current literature.
Recommendations for overcoming limitations
The selection of a sample is important in this type of study. Crucially the sample needs to be large,
with thousands of subjects if possible to detect gene-environment interactions (Uher and McGuffin
2010). This is because the effect size of the interaction between BDNF Val66Met variant and LA
maybe small and therefore the sample size needs to be larger to increase the power to detect this
interaction. Other factors can increase the power of the study such as using a sample with a high
percentage of Met carriers, for example an Asian sample (Kim et al, 2010). Also a high prevalence
and severity of LA and mood disorder within the sample would increase the power, for example an
old age sample (Kaufman, Yang et al. 2006; Kim, Stewart et al. 2007). Additionally the studies in this
review predominantly use Caucasian participants therefore future studies may be able to investigate
the interaction in other ethnic groups.
Future studies should use a reliable measurement for mood disorders and LA as this is thought to
have a big impact on the estimation of regression coefficients (Liu and Salvendy 2009). Mood
disorders should be assessed by interview using the DSM-IV or ICD-10 criteria to confirm a diagnosis
of the bipolar disorder or major depression. LA should preferably be measured by a prospective
study to avoid recall bias, although such a study would be time consuming, costly and therefore
challenging. A LA interview is more reliable than questionnaires as often covers more life events and
make a better assessment of how the events affected the individual. Multiple informants, such as
interviewing parents or partners, also add to the reliability. Alternatively Kaufmann et al (2006)
reliably measured LA by selecting children who had been taken away from their parents by social
services due to severe abuse. Furthermore Uher et al (2010) suggested that independent events,
such as the onset of a physical illness or a natural disaster, could be used.
In addition future studies could confirm that the LA occurs before the onset of the mood disorder.
This is important in order to help establish causation as it is possible that a mood disorder could
cause some LA such as losing a job or divorce. Again a prospective study would be preferable but is
often not possible. Asking patients about the six months before their mood disorder episode began,
instead of asking about six months before the interview, may clarify the timeline (Hosang, Uher et al.
2010). An alternative method used by Drachmann et al (2009) is to only include life events that
were likely to be independent of depression as judged by the interviewer.
Recommendations for future areas of research
Aguliera et al’s (2009) study suggests that there may be differences in the type of LA that interacts
with the BDNF Val66Met variant as they only found a significant interaction with childhood sexual
abuse. Therefore future studies may be able to explore this area further.
Several of the studies in this review had investigated the interaction between LA, BDNF Val66Met
variant and another polymorphism, often the 5-HTTLPR, which produced mixed results. More
research into these types of multiple interactions would help to build a more accurate picture of
how a mood disorder develops as multiple genes and environmental factors are likely to be involved
(Fergusson, Horwood et al. 2011). Furthermore, genes may affect risk differently when in the
presence of different alleles of other genes. For example Grabe et al’s (2012) study suggested that
the Met allele may increase the risk of developing a depressive disorder when in the presence of the
Long allele of the 5-HTTLPR Serotonin Transporter gene polymorphism but has a protective impact
against depressive disorders when in the presence of the Short allele.
Conclusion
In conclusion, to our knowledge this is the first systematic review to examine the evidence for and
interaction between the BDNF Val66Met variant and LA in mood disorders. The results suggest that
there is an interaction and thus research in this area should certainly be pursued further in order to
acquire a more definitive result. This review also gives recommendations for future research aimed
at overcoming the limitations of previous studies. More research in this area is crucial as geneenvironmental interaction studies are a promising and alternative approach to genetic studies in
psychiatry. In the future this type of information may help to identify individuals at risk of
developing a mood disorder and therefore preventative treatment could be provided. Furthermore
it could help to identify new drug targets. Consequently this type of research may in the future help
to alleviate the enormous burden of mood disorders.
Study
Hosang et
al, 2010
Type of
Study
Case-control
Sample
Size
Sample Characteristics
487 with
mood
disorder
Clinical Sample
598
controls
66% female within cases
Percentage of
Met carriers
36%
Ethnicity not reported
Adult Adversity
Measurement
Mood Disorder
Measurement
Interview using the List of Diagnosis bipolar disorder
Threatening Experiences based on ICD-10 criteria
during 6 months prior to
worst depressive or manic SCAN interview
episode
58% female within controls
Result
P=0.04 for
depressive
episode
P>0.05 for
manic
episode
Mean age at worse episode
= 37 (SD 11)
Drachman
n et al,
2009
Cases
290 with
mood
disorder
Clinical Sample
45%
Interview for Recent Life Diagnosis of first episode
P=0.05
Events in past 6 months. depression based on ICD-10
(Included only events that criteria
were likely to be
SCAN interview
independent of
depression + of moderatesevere stress)
70%
Interview using List of
Diagnosis depression using
Threatening Experiences Geriatric Mental State
during past 12 months
diagnostic schedule
Caucasian
65.5% women
Mean age = 38.5 (quartiles:
28.3-52.4)
Kim et al,
2010
Case-control
101 with
mood
disorder
Community Sample
631
controls
% of females not reported
Korean
Age = 65+
P<0.001
Lavebratt Case-control
et al, 2010
Juhasz et
al, 2011
Continuous
475 with
mood
disorder
Community Sample
2286
controls
% of females not reported
1269
28%
Questionnaire - Recent
Diagnosis depression based P>0.05
Life Events during past 12 on DSM IV criteria.
months.
Depression cases included
major depression,
dysthymia and mixed
anxiety depression.
Controls had no symptoms
of depression and had
never received psychiatric
health care.
Not reported
Questionnaire - Life
Lifetime depression
Threatening Experiences
Questionnaire - Brief
during past 12 months
Symptom Inventory
Swedish
Age range: 24-60.
Community Sample
Caucasian
70% female
P>0.05
Mean age = 34.04 (28SD,
age range:18-60)
Table 1 shows the results of studies that had investigated the interaction between the BDNF Val66Met variant and Adult Adversity in mood disorders (SD =
Standard Deviation, SCAN = Schedules for Clinical Assessment in Neuropsychiatry).
Study
Type of
Study
Lavebratt Caseet al, 2010 control
Sample
Size
Sample
Characteristics
475 with
mood
disorder
Community Sample
2286
controls
% of females not
reported
Genotype
(percentage of
Met carriers)
28%
Swedish
Casecontrol
35 with
mood
disorders
98 controls
Community Sample
of students
Mixed ethnicity
74% female
Mean Age = 18.71
Mood Disorder Measurement
Result
Questionnaire of childhood Diagnosis depression based on DSM P=0.01
adversity
IV criteria
Depression cases included major
depression, dysthymia and mixed
anxiety depression. Controls had no
symptoms of depression and had
never received psychiatric health
care.
Age range: 24-60
Carver et
al, 2011
Childhood Adversity
Measurement
36%
Risky Families Questionnaire Diagnosis depression
Structured clinical interview based
on DSM IV
P=0.04
Wichers et Continuous 394
al, 2008
Community Sample
25%
Belgium
Childhood Trauma
Questionnaire excluding
most explicit items
Depressive symptoms
Childhood Adversity
Questionnaire
Lifetime Depression
100% female
P=0.018
16 item questionnaire, 5 times
during 15 months plus 2 structured
clinical interviews (SCID).
Age range 18-46
Juhasz et
al, 2011
Continuous 1269
Community Sample
Not reported
Caucasian
(derived from Childhood
Trauma Questionnaire with
additional items e.g.
parental loss)
70% female
Mean age = 34.04
(28SD, range:18-60)
Aguliera
Continuous 534
et al, 2009
Community Sample
77% student
Spanish
% female not
reported
mean age=22.9 (5.4
SD) 18-50
40%
Childhood Trauma
Questionnaire
P=0.0036
Questionnaire - Brief Symptom
Inventory
Depressive Symptoms
Questionnaire - Symptom Check List
Any abuse
p>0.05
Sexual
abuse:
P=0.0001
Kaufman Continuous 109
Sample from social
et al, 2007
maltreated services
24%
Interview with multiple
informants. Sufficiently
severe for child to be
removed from parents in
the last 6 months.
Depressive symptoms
The Mood and Feelings
questionnaire and semi-structured
interview for children.
Child Behaviour questionnaire for
parent or foster parent.
Licenced child psychologist and
psychiatrist reviewed all clinical
material.
P=0.09
33%
Childhood Trauma
Questionnaire
Depressive Symptoms
Questionnaire - Beck depression
Inventory
P>0.05
37%
Parent interview for
Depressive Symptoms
childhood adverse events at
Questionnaire - Youth Self Report
age 11
for last 6 months. At age 11, 13.5
Parent questionnaire for
and 16. Score averaged over the 3
Long term difficulties at age questionnaires
13.5
87 nonMixed ethnicity
maltreated
51% female
Mean age 9
Grabe et
al, 2012
Continuous 2035
Community Sample
German
52.5% female
Mean age = 55.6
(SD13.8) 29.4-89.8
Nederhof Continuous 1096
et al, 2010
Community Sample
Dutch
52% female
Age range 11-16
Table 2 shows the results of studies that investigated the interaction between BDNF Val66Met variant and Child Adversity in mood disorders.
P=0.65
References
Aguilera, M., B. Arias, et al. (2009). "Early adversity and 5-HTT/BDNF genes: New evidence of geneenvironment interactions on depressive symptoms in a general population." Psychological
Medicine 39(9): 1425-1432.
Carver, C. S., S. L. Johnson, et al. (2011). "Childhood adversity interacts separately with 5-HTTLPR and
BDNF to predict lifetime depression diagnosis." Journal of Affective Disorders 132(1-2): 8993.
Caspi, A., K. Sugden, et al. (2003). "Influence of Life Stress on Depression: Moderation by a
Polymorphism in the 5-HTT Gene." Science 301(5631): 386-389.
Chen, B., D. Dowlatshahi, et al. (2001). "Increased hippocampal bdnf immunoreactivity in subjects
treated with antidepressant medication." Biological Psychiatry 50(4): 260-265.
Chen, Z.-Y., K. bath, et al. (2008). "Impact of genetic variant BDNF (Val66Met) on brain structure and
function." Novartis Found Symp. 289: 180-195.
Coppell, A. L., Q. Pei, et al. (2003). "Bi-phasic change in BDNF gene expression following
antidepressant drug treatment." Neuropharmacology 44(7): 903-910.
Cunha, A. B. M., B. N. Frey, et al. (2006). "Serum brain-derived neurotrophic factor is decreased in
bipolar disorder during depressive and manic episodes." Neuroscience Letters 398(3): 215219.
de Foubert, G., S. L. Carney, et al. (2004). "Fluoxetine-induced change in rat brain expression of
brain-derived neurotrophic factor varies depending on length of treatment." Neuroscience
128(3): 597-604.
Dias, B. G., S. B. Banerjee, et al. (2003). "Differential regulation of Brain Derived Neurotrophic Factor
transcripts by antidepressant treatments in the adult rat brain." Neuropharmacology 45(4):
553-563.
Drachmann Bukh, J., C. Bock, et al. (2009). "Interaction between genetic polymorphisms and
stressful life events in first episode depression." Journal of Affective Disorders 119(1-3): 107115.
Duman, R. S. and L. M. Monteggia (2006). "A Neurotrophic Model for Stress-Related Mood
Disorders." Biological Psychiatry 59(12): 1116-1127.
Dwivedi, Y., H. S. Rizavi, et al. (2003). "Altered Gene Expression of Brain-Derived Neurotrophic Factor
and Receptor Tyrosine Kinase B in Postmortem Brain of Suicide Subjects." Arch Gen
Psychiatry 60(8): 804-815.
Egan, M. F., M. Kojima, et al. (2003). "The BDNF val66met Polymorphism Affects Activity-Dependent
Secretion of BDNF and Human Memory and Hippocampal Function." Cell 112(2): 257-269.
Farmer, A., A. Elkin, et al. (2007). "The genetics of bipolar affective disorder." Current Opinion in
Psychiatry 20(1): 8-12 10.1097/YCO.1090b1013e3280117722.
Fergusson, D. M., L. J. Horwood, et al. (2011). "Life stress, 5-HTTLPR and mental disorder: findings
from a 30-year longitudinal study." The British Journal of Psychiatry 198(2): 129-135.
Frodl, T., H. J. Möller, et al. (2008). "Neuroimaging genetics: new perspectives in research on major
depression?" Acta Psychiatrica Scandinavica 118(5): 363-372.
Grabe, H. J., C. Schwahn, et al. (2012). "Genetic epistasis between the brain-derived neurotrophic
factor Val66Met polymorphism and the 5-HTT promoter polymorphism moderates the
susceptibility to depressive disorders after childhood abuse." Progress in NeuroPsychopharmacology and Biological Psychiatry 36(2): 264-270.
Groves, J. O. (2007). "Is it time to reassess the BDNF hypothesis of depression?" Mol Psychiatry
12(12): 1079-1088.
Hammen, C. (2005). "Stress and depression." Annual Review of Clinical Psychology 1(1): 293-319.
Hosang, G. M., R. Uher, et al. (2010). "Stressful life events and the brain-derived neurotrophic factor
gene in bipolar disorder." Journal of Affective Disorders 125(1-3): 345-349.
Hoshaw, B. A., J. E. Malberg, et al. (2005). "Central administration of IGF-I and BDNF leads to longlasting antidepressant-like effects." Brain Research 1037(1–2): 204-208.
Johnson, S. L. (2005). "Life events in bipolar disorder: Towards more specific models." Clinical
Psychology Review 25(8): 1008-1027.
Juhasz, G., J. S. Dunham, et al. (2011). "The CREB1-BDNF-NTRK2 pathway in depression: Multiple
gene-cognition- environment interactions." Biological Psychiatry 69(8): 762-771.
Kanazawa, T., S. J. Glatt, et al. (2007). "Meta-analysis reveals no association of the Val66Met
polymorphism of brain-derived neurotrophic factor with either schizophrenia or bipolar
disorder." Psychiatric Genetics 17(3): 165-170
110.1097/YPG.1090b1013e32801da32802e32802.
Karege, F., G. Vaudan, et al. (2005). "Neurotrophin levels in postmortem brains of suicide victims and
the effects of antemortem diagnosis and psychotropic drugs." Molecular Brain Research
136(1–2): 29-37.
Kauer-Sant'Anna, M., J. Tramontina, et al. (2007). "Traumatic life events in bipolar disorder: impact
on BDNF levels and psychopathology." Bipolar Disorders 9: 128-135.
Kaufman, J., B. Z. Yang, et al. (2006). "Brain-derived neurotrophic factor-5-HTTLPR gene interactions
and environmental modifiers of depression in children." Biological Psychiatry 59(8): 673-680.
Kendler, K. S., M. Gatz, et al. (2006). "A Swedish National Twin Study of LIfetime Major Depression."
The American Journal of Psychiatry 163(1): 109-114.
Kendler, K. S., L. M. Karkowski, et al. (1998). "Stressful Life Events and Major Depression: Risk Period,
Long-Term Contextual Threat, and Diagnostic Specificity." The Journal of Nervous and
Mental Disease 186(11): 661-669.
Kim, J. M., R. Stewart, et al. (2007). "Interactions Between Life Stressors and Susceptibility Genes (5HTTLPR and BDNF) on Depression in Korean Elders." Biological Psychiatry 62(5): 423-428.
Lavebratt, C., E. Aberg, et al. (2010). "Variations in FKBP5 and BDNF genes are suggestively
associated with depression in a Swedish population-based cohort." Journal of Affective
Disorders 125(1-3): 249-255.
Levinson, D. F. (2006). "The Genetics of Depression: A Review." Biological Psychiatry 60(2): 84-92.
Liu, Y. and G. Salvendy (2009). "Effects of measurement errors on psychometric measurements in
ergonomics studies: Implications for correlations, ANOVA, linear regression, factor analysis,
and linear discriminant analysis." Ergonomics 52(5): 499-511.
McGuffin, P., R. Katz, et al. (1991). "Nature, nurture and depression: a twin study." Psychological
Medicine 21(02): 329-335.
McGuffin, P., R. Katz, et al. (1996). "A Hospital-Based Twin Register of the Heritability of DSM-IV
Unipolar Depression." Arch Gen Psychiatry 53(2): 129-136.
McGuffin, P., F. Rijsdijk, et al. (2003). "The Heritability of Bipolar Affective Disorder and the Genetic
Relationship to Unipolar Depression." Arch Gen Psychiatry 60(5): 497-502.
Monroe, S. M. (2008). "Modern Approaches to Conceptualizing and Measuring Human Life Stress."
Annual Review of Clinical Psychology 4(1): 33-52.
Monteggia, L. M., B. Luikart, et al. (2007). "Brain-Derived Neurotrophic Factor Conditional Knockouts
Show Gender Differences in Depression-Related Behaviors." Biological Psychiatry 61(2): 187197.
Müller, M. B., N. Toschi, et al. (2000). "Long-Term Repetitive Transcranial Magnetic Stimulation
Increases the Expression of Brain-Derived Neurotrophic Factor and Cholecystokinin mRNA,
but not Neuropeptide Tyrosine mRNA in Specific Areas of Rat Brain."
Neuropsychopharmacology 23(2): 205-215.
Munafò, M. R., C. Durrant, et al. (2009). "Gene × Environment Interactions at the Serotonin
Transporter Locus." Biological Psychiatry 65(3): 211-219.
Nederhof, E., E. M. C. Bouma, et al. (2010). "Interaction between childhood adversity, brain-derived
neurotrophic factor val/met and serotonin transporter promoter polymorphism on
depression: The trails study." Biological Psychiatry 68(2): 209-212.
Nibuya, M., S. Morinobu, et al. (1995). "Regulation of BDNF and trkB mRNA in rat brain by chronic
electroconvulsive seizure and antidepressant drug treatments." The Journal of Neuroscience
15(11): 7539-7547.
Olson, C. M., D. Rennie, et al. (2002). "Publication Bias in Editorial Decision Making." JAMA: The
Journal of the American Medical Association 287(21): 2825-2828.
Peveler, R., A. Carson, et al. (2002). "Depression in medical patients." BMJ 325(7356): 149-152.
Pezawas, L., B. A. Verchinski, et al. (2004). "The Brain-Derived Neurotrophic Factor val66met
Polymorphism and Variation in Human Cortical Morphology." The Journal of Neuroscience
24(45): 10099-10102.
Pizarro, J. M., L. A. Lumley, et al. (2004). "Acute social defeat reduces neurotrophin expression in
brain cortical and subcortical areas in mice." Brain Research 1025(1–2): 10-20.
Rasmusson, A. M., L. Shi, et al. (2002). "Downregulation of BDNF mRNA in the hippocampal dentate
gyrus after re-exposure to cues previously associated with footshock."
Neuropsychopharmacology : official publication of the American College of
Neuropsychopharmacology 27(2): 133-142.
Roceri, M., F. Cirulli, et al. (2004). "Postnatal repeated maternal deprivation produces agedependent changes of brain-derived neurotrophic factor expression in selected rat brain
regions." Biological Psychiatry 55(7): 708-714.
Roceri, M., W. Hendriks, et al. (2002). "Early maternal deprivation reduces the expression of BDNF
and NMDA receptor subunits in rat hippocampus." Molecular Psychiatry 7(6): 609-616.
Russo-Neustadt, A., R. C. Beard, et al. (1999). "Exercise, Antidepressant Medications, and Enhanced
Brain Derived Neurotrophic Factor Expression." Neuropsychopharmacology 21(5): 679-682.
Russo-Neustadt, A. A., H. Alejandre, et al. (2004). "Hippocampal Brain-Derived Neurotrophic Factor
Expression Following Treatment with Reboxetine, Citalopram, and Physical Exercise."
Neuropsychopharmacology 29(12): 2189-2199.
Sen, S., R. Duman, et al. (2008). "Serum Brain-Derived Neurotrophic Factor, Depression, and
Antidepressant Medications: Meta-Analyses and Implications." Biological Psychiatry 64(6):
527-532.
Shirayama, Y., A. C.-H. Chen, et al. (2002). "Brain-Derived Neurotrophic Factor Produces
Antidepressant Effects in Behavioral Models of Depression." The Journal of Neuroscience
22(8): 3251-3261.
Siuciak, J. A., D. R. Lewis, et al. (1997). "Antidepressant-Like Effect of Brain-derived Neurotrophic
Factor (BDNF)." Pharmacology Biochemistry and Behavior 56(1): 131-137.
Stein, D. J., J. Savitz, et al. (2008). "Brain-derived neurotrophic factor: the neurotrophin hypothesis of
psychopathology." CNS Spectrums 13(11): 945-949.
Surtees, P. G., N. W. J. Wainwright, et al. (2007). "No association between the BDNF Val66Met
polymorphism and mood status in a non-clinical community sample of 7389 older adults."
Journal of Psychiatric Research 41(5): 404-409.
Thomas, C. M. and S. Morris (2003). "Cost of depression among adults in England in 2000." The
British Journal of Psychiatry 183(6): 514-519.
Ueyama, T., Y. Kawai, et al. (1997). "Immobilization stress reduced the expression of neurotrophins
and their receptors in the rat brain." Neuroscience Research 28(2): 103-110.
Uher, R. and P. McGuffin (2010). "The moderation by the serotonin transporter gene of
environmental adversity in the etiology of depression: 2009 update." Mol Psychiatry 15(1):
18-22.
Wichers, M., G. Kenis, et al. (2008). "The BDNF Val⁶⁶Met x 5-HTTLPR x child adversity
interaction and depressive symptoms: An attempt at replication." American Journal of
Medical Genetics, Part B: Neuropsychiatric Genetics 147(1): 120-123.
Willis-Owen, S. A. G., J. Fullerton, et al. (2005). "The Val66Met Coding Variant of the Brain-Derived
Neurotrophic Factor (BDNF) Gene Does Not Contribute Toward Variation in the Personality
Trait Neuroticism." Biological Psychiatry 58(9): 738-742.