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Advances in Biology
Volume 2014 (2014), Article ID 719723, 15 pages
http://dx.doi.org/10.1155/2014/719723
Review Article

The Brain Derived Neurotrophic Factor and Personality

1Department of Psychology, University of Bonn, Kaiser-Karl-Ring 9, D-53111 Bonn, Germany
2Center for Economics & Neuroscience, University of Bonn, Germany

Received 5 December 2013; Revised 14 February 2014; Accepted 14 February 2014; Published 27 March 2014

Academic Editor: Allan V. Kalueff

Copyright © 2014 Christian Montag. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The study of the biological basis of personality is a timely research endeavor, with the aim of deepening our understanding of human nature. In recent years, a growing body of research has investigated the role of the brain derived neurotrophic factor (BDNF) in the context of individual differences across human beings, with a focus on personality traits. A large number of different approaches have been chosen to illuminate the role of BDNF for personality, ranging from the measurement of BDNF in the serum/plasma to molecular genetics to (genetic) brain imaging. The present review provides the reader with an overview of the current state of affairs in the context of BDNF and personality.

1. What Is Personality?

1.1. Why Study Human Personality?

The study of the individual differences of humans is as old as mankind. The first Greek philosophers, such as Hippocrates, were interested in finding an answer to the question of why humans differ. According to Hippocrates, the essence of individuality was found in four bodily fluids; for example, black bile was associated with a melancholic personality structure [1, 2]. Since then, generations of scientists have strived to shed light on human personality.

Beyond the scientist’s pure curiosity in this topic, the study of personality yields important insights into the nature of humans. Here, it has been put forward that an understanding of the healthy aspects of personality must inform the understanding of psychopathological conditions, because the latter are much harder to study given imbalances, for example, in the neurotransmitter systems of humans (e.g., [3, 4]). Many personality traits, such as neuroticism, are known to be of large importance for public health outcomes [5]. Therefore, an understanding of personality is also a key to disentangling the complex nature of psychopathology.

1.2. A Short Definition of Personality

Definitions of personality are numerous in the literature (e.g., [68]). In my opinion, the most common denominator among these definitions represents the concept of “traits,” referring to the stability of personality dimensions, such as being cooperative or curious over long time periods across the lifespan. These personality characteristics influence the way a person thinks, behaves, and reacts emotionally towards a large number of environmental stimuli [6]. Of note, and for a better understanding of the above introduced term “traits,” it needs to be mentioned that in some situations a person will always show a particular emotional reaction such as being sad, for example, when a beloved person has died or a relationship has broken up. This relates to the present mood of a person and of course is strongly influenced by the demands of a situation. Clearly, the loss of a loved person would overwhelm nearly all humans from an emotional point of view. Using the concept “traits,” personality psychologists describe the overall pattern of states over a long time period, being conceptually independent of one incident. In simple terms, a trait is a disposition, for example, to be more sad or more happy across a large number of different circumstances (and in terms of the above-mentioned example to deal with personal losses; e.g., [9]). Nevertheless, the concepts “traits” and “states” are logically intertwined. This is supported by the correlations between mean-state and trait measures ranging between 0.39 and 0.64 [10].

1.3. Individual Differences in Emotional Reactions as the Evolutionarily Oldest Part of Personality

More specifically, individual differences in personality as related to the emotional reactions mentioned above [6] are of interest in the present review because “brain derived neurotrophic factor” (BDNF) is known to strongly influence negative emotionality [11]. Individual differences in emotional reactions towards environmental demands can also be studied in other mammalian species, not only humans, because the primary emotional systems (on which BDNF can act as a transmitter) are evolutionarily conserved across phylogenetic parts of the mammalian brain [12]. Therefore, animal research can be an excellent guide for human research in the context of individual differences in emotional reactions. Emotional reactions arising from primary emotional systems reflect “ancestral tools for living” [13, page 533], because they helped our ancestors (and help us today) respond adequately to dangers in the environment to seek food or explore the environment carefully and to find a mating partner to pass on one’s own DNA to the next generation. Complex emotions or feelings (these terms are still a matter of great debate; see [14]), such as guilt or shame, result from a complex interaction of the primary emotional systems, such as SEEK, FEAR, RAGE, PLAY, CARE/LUST, SADNESS (primary emotional systems are written in capitals to not confuse them with similar sounding terms in the literature (according to [15])), with cortical areas of the brain [16]. The conservation of the primary emotional systems across the mammalian species makes it very likely that the neuroanatomy and activity of these systems is strongly influenced by genetics (otherwise these emotional systems would not be that similar over the species). This is a crucial point, and I deal with the molecular genetics of BDNF and personality later on.

The idea of (primary) emotional systems as an evolutionary heritage has already been outlined by Darwin in 1872 in his work on emotional expressions in man and animals [17]. It has also been indirectly outlined in the context of brain organization by MacLean in his triune brain concept [18]. In MacLean’s theory the brain has been described as the only organ in the human body which clearly mirrors the evolutionary development bottom up, from the reptilian brain to the mammalian brain (where (social) emotions are anchored) to the neocortex. To illustrate this idea, I invite you to undertake a short mind game: imagine yourself standing in front of the Grand Canyon. The deeper you see into the Canyon (the deeper you see into your brain structures) the older the structures are from an evolutionary point of view. As primary emotional systems can be found in ancient brain structures, individual differences in these systems should reflect the oldest part of personality. From a psychobiological point of view, personality could be described as arising from individual differences in the neuroanatomy of the brain.

1.4. Some Notes on Personality Theories

A large number of personality theories exist. As an introduction to the most important personality theories is beyond the scope of the present review article, I refer to short introductions on the biological personality theories of Eysenck, Gray, Cloninger, and Panksepp in two of my own recently published review articles [19, 20]. Nevertheless, two personality theories are briefly introduced in the following text, because they are of substantial interest in the context of the following BDNF-personality literature.

Most of the studies in BDNF-personality-research deal with the Five Factor Model of Personality [8, 21] or with the Biosocial Theory of Personality [7, 22].

The Five-Factor Model of Personality has been derived from a lexical approach. By factor-analyzing words describing human characteristics (e.g., taken from dictionaries) five personality dimensions emerged named openness to experience, conscientiousness, agreeableness, extraversion, and neuroticism (easily remembered by the acronym OCEAN). Extraversion and neuroticism particularly turned out to be of special relevance in a large number of studies, because of their relevance for a better understanding of positive and negative emotionality in humans [23, 24] and also related psychopathological disorders (e.g., [25]). Among other terms, extraverted humans can be best described as outgoing, seeking social interactions, and impulsive. Neurotics tend to be anxious, moody, and emotionally unstable. These examples illustrate the closeness between personality and emotional tendencies.

In contrast to the Five Factor Model of Personality, the Biosocial Theory of Personality by Cloninger et al. [7] has a strong theoretical biological background. Cloninger divides human personality into temperament and character traits. According to his theory temperament traits are strongly influenced by genetics from early on in life, and character traits are more influenced by the environment in adolescence/adulthood. Most importantly, Cloninger’s theory makes assumptions about the underlying neurotransmitter system involved in his temperament dimensions novelty seeking, harm avoidance, and reward dependence. According to Cloninger, high novelty seeking (being curious and impulsive) is associated with low dopamine levels, high harm avoidance (being anxious) is linked to high serotonin levels, and high reward dependence (being dependent on social approval) is linked to low norepinephrine. Although Cloninger’s model has only been partly empirically supported, it is still of large value as a theoretical framework.

Some BDNF studies have also used classical personality self-report questionnaires to measure extraversion and neuroticism, such as that by Eysenck [26], which is not presented here in detail. For a better understanding of the studies presented below, I would note that correlations between Eysenck’s constructs neuroticism and extraversion and the same dimensions measured with the Five Factor Model are very high.

2. Classical Biological Targets to Understand Personality

The most important targets across the last few decades in studying the biological basis of individual differences in personality have clearly been the neurotransmitters dopamine and serotonin. A potential reason for a focus on these biogenic amines lies in the importance of the most prescribed psychopharmaceuticals to treat schizophrenia and affective disorders. Schizophrenic patients are usually treated with dopamine antagonists to diminish the positive symptoms of psychosis such as hallucinations [27]. As a consequence, dopamine has become an important target to understand schizotypy personality traits (e.g., [28]). Due to the role of dopamine in reward [29] and motivation [30], dopamine also represents a classical target to understand individual differences in extraversion [31] or as mentioned novelty seeking [7], because both extraversion and novelty seeking are linked to individual differences in reward processing (e.g., [3234]).

Another candidate often investigated to better understand human personality is the hormone cortisol. Cortisol plays a pivotal role in the stress axis of the human body. When the human body is confronted with a stressful situation the hypothalamic-pituitary-adrenal (HPA) axis is activated and as a consequence cortisol is secreted from the adrenal cortex [35]. Given the important influence of cortisol on the regulation of corticotropin releasing hormone (CRH) and adrenocorticotropic hormone (ACTH) secretion in the human brain and the observation of an altered HPA axis in depression [36], cortisol became an important target to study individual differences in personality with mixed results (e.g., [37, 38]). Besides these key players, in the last few years a growing interest can also be observed in neuropeptides such as oxytocin to understand human personality (e.g., [39, 40]).

3. The Brain Derived Neurotrophic Factor

A reasonably new target in studying individual differences in personality is the brain derived neurotrophic factor (BDNF). BDNF belongs to the neurotrophin family and its secretion has been strongly linked to neurogenesis, including dendritic spine formation and synaptic plasticity [4144]. Two forms of BDNF can be distinguished, proBDNF and matureBDNF. Simply put, the proBDNF molecule represents the precursor of the matureBDNF form. Both BDNF forms signal via different receptor types. ProBDNF is known to target the receptor; matureBDNF targets the tyrosine kinase B (TrkB) receptor. A Yin and Yang theory has been proposed to explain the dissociative effects of proBDNF and matureBDNF on the human brain [45]. While higher levels of proBDNF have been linked to depression [46], and even atrophic effects in the brain [47], matureBDNF is linked to positive effects on nerve growth in the brain [48].

In my opinion, the interest in BDNF for personality research can be traced to the antidepressant effects of BDNF. It has been demonstrated that (mature) BDNF levels (the debate on what kind of BDNF is usually dealt with in studies measuring BDNF will be discussed at the end of Section 4 in this review) are diminished in depressed patients (e.g., [49]), as well as in suicidal individuals [50], and show a rise after successful treatment [51, 52]. Moreover, it has been put forward in the so called neurotrophin hypothesis of depression [53] that stress could be associated with a downregulation of BDNF [54]. As a consequence the “brain fertilizer” BDNF is not secreted in sufficient amounts, which could in part explain why mood disorders occur together with atrophic effects of the hippocampus in depression [55, 56]. Of relevance for an understanding of the healthy aspects of the personality traits neuroticism or harm avoidance, negative correlations have been observed between these personality traits and hippocampal gray matter volumes ([57] see also review by Montag et al. [4]). This makes a role for BDNF in personality likely.

4. Linking BDNF Levels to Personality Traits

Although a large number of studies have dealt with the question of whether BDNF levels are associated with depressive conditions (mostly they are), only a small number of studies have investigated the role of BDNF levels in related personality traits in subclinical healthy participants. Of note, these studies differ somewhat with respect to the administered self-report personality questionnaires and also in terms of the BDNF variables under investigation, ranging from serum to plasma to whole blood BDNF. As most studies analyse BDNF levels from blood drawn from the periphery of the human body, the question arises as to how peripheral BDNF levels relate to central BDNF levels. Although this important question cannot be conclusively answered, it has been demonstrated in a recent animal model that peripheral BDNF is itself able to exert antidepressant effects [58]. Moreover, BDNF levels can cross the blood brain barrier and can therefore migrate from the body to the brain (e.g. [59]). In addition, Karege et al. [60] were able to show a strong positive correlation between cortical BDNF and serum BDNF in the peripheral parts of the body in young rats ( , ). Following these findings, the investigation of peripheral BDNF levels is possibly related to BDNF functioning in the central nervous system. Of note, a study by Martin et al. [61] questioned the correlation between hippocampal BDNF and plasma BDNF in the periphery as a result of their animal data.

A literature search using the key words “BDNF” and “personality” in Google Scholar and pubmed.com on 5 November, 2013, revealed seven studies investigating the link between peripheral (plasma, serum, or whole blood) BDNF levels and individual differences in personality traits. Summing up the findings, these studies show an inverse relationship between peripheral BDNF levels and traits related to negative emotionality ([6264]). Fitting with this, another study showed a positive correlation between BDNF levels and extraversion, but the inverse association with negative emotionality could not be demonstrated here [65]. The positive association between the personality trait extraversion and BDNF could only be observed with the variable plasma BDNF.

The basic finding presented above (high levels of BDNF being associated with low scores on negative emotion-related personality traits) clearly needs to be taken as an oversimplification, because two studies revealed this association while investigating serum BDNF levels [62, 63], one study revealed this link with plasma BDNF [64], and one study showed a more complicated interaction effect with the variables “stressful life events,” “sex,” and “whole blood BDNF levels” [66]. One earlier study by Terracciano et al. [67] even reported a positive association between plasma BDNF levels and two facets of neuroticism. The detailed results of these studies are presented in Table 1.

tab1
Table 1: Overview on studies investigating BDNF levels in the context of personality traits (presented in alphabetical order of first authors).

The importance of distinguishing plasma and serum BDNF levels for the summary and interpretation of the results becomes apparent when considering the research findings on these two different aspects of BDNF levels (serum represents plasma without blood clotting factors). BDNF measured in the serum indicates BDNF being attached to platelets, which could represent a storage site or depot for BDNF. Support for this idea came from Fujimura et al. [90], who observed that after stimulation of BDNF in the platelets with agonists, such as thrombin/collagen or stress, only about half of BDNF was released. Adding to this Terracciano et al. [63] reported a positive correlation between platelet count and BDNF in the serum ( , ). In sum, serum BDNF levels are known to be rather stable. In contrast, BDNF levels in the plasma have been observed to be very unstable with respect to retest-reliability measures, and these levels vary across the day, especially in males [91]. Choi et al. [92] also reported that plasma variation (with a decline of plasma BDNF over the day) could be observed in males but not in females. Of importance, for serum BDNF levels no diurnal variation could be observed for both sexes. These findings might explain the contradictory results (BDNF correlates positively with neuroticism) reported by Terracciano et al. [67] in relation to plasma BDNF, although Yasui-Furukori et al. [64] recently reported the often observed inverse association between the more unreliable plasma BDNF and harm avoidance in their Japanese sample. Besides this, numbers from Terracciano et al. [63] show that plasma and serum BDNF levels only have moderate correlations ( , ).

Considering the issues mentioned here and taking into account the findings from the depression research, I cautiously propose a continuum model from healthiness to psychopathological behavior, with lower BDNF levels being associated with higher degrees of traits linked to negative emotionality. But the correlations observed in the reviewed studies are all very small. Therefore, BDNF taken alone explains only small parts of a complex phenotype such as personality. As Lu et al. [45] noted, the different effects of pro- and matureBDNF on the brain might cause one to ask what form of BDNF is investigated in the studies dealing with (peripheral) BDNF levels. An answer to this question is given by Katoh-Semba et al. [93, page 371]: “Posttranscriptionally, BDNF protein is well known to be in the processed mature form upon release from cells. Therefore, if circulating BDNF is derived from external sources, it is reasonable that the protein bound to platelets is already processed into the observed mature form.” Moreover, Katoh-Semba et al. [93] reported for their sample that 99% of BDNF in the serum represents mature BDNF.

A question not answered until now is as follows: do changing BDNF levels (such as seen in remission from depression, Molendijk et al. [94]) also go along with changes in personality? My answer to this question is purely speculative, because no studies directly addressed this topic to my best knowledge. Of interest, Jylhä et al. [95] reported no effects of antidepressant treatment on personality, thereby indirectly pointing towards no association between changing BDNF levels and a change of personality. Underlining this notion, personality usually is stable from middle age on [8]. Therefore, it is unlikely that changing BDNF levels can drastically change personality. How can the above presented BDNF-personality link then be understood? Personality traits such as neuroticism could be connected to tonic (basic or steady) BDNF levels, which in turn could be strongly determined by the genetic makeup of a person and form the biochemical sediment. In contrast, states (also depressive states) could be more linked to phasic BDNF bursts shaking BDNF levels for a shorter time period. These phasic BDNF bursts might be triggered by pharmaceuticals but also sport exercise or psychotherapy. Logically, tonic and phasic BDNF levels are hard to disentangle, because they total up in the actual amount of measured BDNF levels.

Besides this line of thought (and as outlined later on), BDNF is influenced strongly by other transmitter systems, too. Thereby, it is possible that BDNF is only indirectly linked to personality. Again, these thoughts are very speculative and my present ideas just reflect a superficial answer to this complex question.

5. Linking a Genetic Variation of the BDNF Gene to Personality Traits

5.1. Main Effects of BDNF Val66Met on Human Personality

Besides measuring the levels of peripheral BDNF, a large body of research has also investigated the BDNF gene in the context of personality traits. The BDNF gene is located on chromosome 11p14.1. The most prominent polymorphism on this gene is called BDNF Val66Met (rs6265) located on codon 66 of the BDNF gene. The functionality of this single nucleotide polymorphism has been supported, with the BDNF Val66Met polymorphism being responsible for an exchange of amino acids from valine (Val) to methionine (Met) in the to-be-built neurotrophin. The BDNF 66Met allele has been associated with diminished activity-dependent secretion of BDNF in a study by Egan et al. [96]. Fitting with this, genetic imaging studies have reported an association with the Met-allele and diminished volume of the hippocampus [97, 98], an effect also extending to the parahippocampus and the amygdala [99, 100] in healthy participants. Contradictory findings also exist (e.g., in a sample of depressed patients by [101]). A recent meta-analysis by Kambeitz et al. [102] showed that the 66Met allele is indeed associated with smaller hippocampus volume, although the effects are rather small. Genetic imaging studies using fMRI, such as that by Montag et al. [103], revealed that (right) amygdala activity while processing (un)pleasant pictures is modulated by the BDNF Val66Met polymorphism. 66Met+ carriers responded with higher amygdala activity to all emotional stimuli (pleasant and unpleasant). Mukherjee et al. [104] investigated the role of BDNF Val66Met for the processing of fearful faces. Here the 66Met allele was associated with overactivity of a neural network comprising the anterior cingulate cortex, the bilateral insula, and the brainstem. A study by Lau et al. [105] compared the processing of emotional faces in nonmedicated patients suffering from anxiety disorders with healthy controls. Here, the Met66 allele could only be associated with higher neural activity in response to the emotional stimuli in the patient group.

Following from the functionality of the BDNF single nucleotide polymorphism (SNP) and the results from genetic imaging, one would expect theoretically that the 66Met allele is associated with higher negative emotionality. I explain my thoughts on this theoretical assumption in detail: as the 66Met allele is associated with lower activity-dependent BDNF secretion, lower hippocampus volume should be observed due to lower secretion of BDNF. The idea of lower hippocampus volume in 66Met allele carriers has found some empirical support in the meta-analyses of Kambeitz et al. [102]. Moreover, lower hippocampus volume has been associated with higher harm avoidance and neuroticism scores in a series of studies (e.g., [4, 57]), and so the 66Met allele should be indirectly associated with higher negative emotionality. Of note is a recent meta-analysis by Terracciano et al. [106] showing no link between BDNF Val66Met and serum BDNF levels, therefore weakening the line of argument that the BDNF Val66Met polymorphism might be a partial cause of lower hippocampus volume due to the lower activity-dependent BDNF secretion. Clearly, BDNF levels are not only influenced by this single SNP but also from a complex mix of diverse factors, including both genetic (not only the BDNF gene) and environment factors. The line of argument/hypothesis is also depicted in Figure 1. We shall see if this overall hypothetical framework is supported by the empirical findings.

719723.fig.001
Figure 1: The role of BDNF for personality—a simplified framework.

Until now, a large number of studies have been conducted to investigate the role of the BDNF Val66Met polymorphism on human personality. To start off, the results of these studies are very heterogeneous and only in part support the 66Met allele negative emotionality link.

The studies by Jiang et al. [77] and Montag et al. [80] both give support for this link, although they differ in one important aspect. Jiang et al. [77] combined all carriers of at least one 66Met allele into a 66Met+ group and tested these against the 66Met− (Val66Val carriers). These groups are often tested in research articles, because in Caucasians the group of homozygous Met66Met carriers only occurs with a prevalence of 3%. Nevertheless, Montag et al. [80] tested these low-frequency homozygous carriers against carriers of the 66Val allele. This low-frequency group ( out of ) showed significantly elevated scores on the subscales “anticipatory worry” and “fear of uncertainty” from Cloninger’s temperament dimension harm avoidance. No effect could be observed for the contrast 66Met+ versus 66Met−. Interestingly, a prominent knock in mice model by Chen et al. [107] also demonstrated that especially mice carrying the homozygous Met66Met variant showed the highest anxiety related behavior in paradigms such as the open field test and the lowest dendritic arborization and hippocampus volume. This model hints at the Met66Met genotype constellation being of most relevance to anxiety. This stands somewhat in contrast to the genetic imaging findings presented above. Until now, no study has investigated if this special group of Met66Met carriers differs from the Val66Val and Val66Met in terms of Met dosage in the human neuroanatomy. This will be an interesting research endeavor for the future.

Other studies investigating the influence of BDNF Val66Met on personality clearly find empirical support for the Val allele—negative emotionality—link (e.g., [79, 83]). Some studies could not even find any effects on personality (e.g., [86, 87, 89]) and mood [108]. Two meta-analyses have been conducted to investigate the effect of BDNF Val66Met on negative emotionality related personality traits over all studies [85, 109]. The newest study, including 13 samples from 2003 to 2009, by Terracciano et al. [85] revealed no effects of BDNF Val66Met on negative emotionality. Independently of this, the effects of this SNP have to be classified as very small on human personality, because human personality represents a complex endophenotype, being influenced by a very large number of genetic variants. The fact that human personality is usually normally distributed hints towards the fact that clearly one or two genetic variations alone cannot be responsible for a person being anxious or extraverted [19]. Despite studies dealing with the main effects of BDNF Val66Met on human personality, studies also need to deal with the potential interactive effects of BDNF Val66Met and other polymorphisms or genetic by environment effects need to reviewed to get a fuller picture of the molecular genetics of BDNF and personality.

Two more interesting points should be highlighted at this point. The effect of BDNF Val66Met could not only be observed on personality traits but also on perceptions of social support. Here, a study by Taylor et al. [110] reported that elderly participants carrying the 66Met+ variant reported less social support. Another interesting approach in the investigation of the BDNF gene and personality has been introduced by Joffe et al. [78]. They combined personality assessment and the investigation of the BDNF gene with structural brain imaging. They reported that 66Met allele carriers could be characterized by an inverse relationship between lower hippocampus gray matter volume and neuroticism, whereas this correlation was absent in Val66Val carriers. This again outlines the complexity of an understanding of the link between molecular genetics, brain structure, and human personality. Finally, a study investigating BDNF Val66Met in the context of schizotypal personality revealed no significant association after correction for multiple testing [111]. Please see Table 2 for a more complete overview on molecular genetic BDNF personality studies (including studies from the next section).

tab2
Table 2: Overview on genetic association studies investigating the BDNF Val66Met polymorphism and personality.
5.2. Interaction Effects of BDNF Val66Met with Other Polymorphisms on Human Personality

A number of studies have also investigated interaction effects between BDNF Val66Met and other polymorphisms on human personality. Here, a clear focus has been on an interaction between the above-mentioned BDNF genetic variant and dopaminergic or serotonergic genetic variants. This is not a surprise, because interactions of BDNF with dopamine or serotonin have been shown in animal models before.

Serotonin and BDNF are known to interact. Martinowich et al. [11] summarized in their review that BDNF and serotonin influence each other in both directions. While the secretion of BDNF is of importance for the survival and plasticity of serotonergic neurons, the administration of selective serotonin reuptake inhibitors are known to elevate BDNF levels. Following the close relationship between the two different systems BDNF and serotonin on a biochemical level in the brain, it is a logical consequence to search for interaction effects between BDNF Val66Met and serotonergic polymorphisms on a molecular genetic level. Arias et al. [69] observed in their sample that despite the lack of a BDNF Val66Met main effect on anxiety-related personality traits, an interaction effect could be observed between BDNF Val66Met and 5-HTTLPR on harm avoidance. The serotonin transporter polymorphism (5-HTTLPR) represents another classic genetic target in biological psychiatry, because the short variant (s-variant) of this insertion deletion polymorphism has been associated with lower mRNA expression and higher neuroticism scores [112, 113]. Given the important role of the serotonin transporter in psychopharmacology (as selective serotonin reuptake inhibitors (SSRIs) are often prescribed to treat depression), it is understandable why the gene coding for the serotonin transporter called SLC6A4 is heavily investigated. In the study by Arias et al. [69] participants carrying the homozygous Met66Met variant together with the s/s variant of the 5-HTTLPR showed the highest harm avoidance scores. Of note, these results are hard to replicate, because this genotypic configuration rarely occurs. In the study by Arias et al. only out of participants could be observed in this particular group. The findings by Arias et al. mirror my first intuitive expectation that the risk variants of each gene loci should somehow add up and be associated with highest negative emotionality. This idea is far too simplistic though, when one considers the whole literature on BDNF Val66Met and 5-HTTLPR. Prominent studies by Pezawas et al. [114] showed that the 66Met allele might even represent a protective factor for depression when also being a carrier of the risk variant of 5-HTTLPR (the s-allele). This was derived, among others, from a volume reduction in the rostral anterior cingulate cortex in carriers of the Val66Val/s+ configuration. Adding to the heterogeneity of the data, the study by Terracciano et al. [85] reported that carriers of the homozygous Val66Val variant, together with the LL variant of 5-HTTLPR, showed the lowest neuroticism scores and differed in that point with all other genotypic constellations.

Besides the interaction of BDNF and serotonin, an interaction between BDNF and dopamine can also be observed. Animal research has revealed that BDNF modulates the mesolimbic dopaminergic pathways in the context of learning from social defeat [115]. Earlier studies also indicated the importance of BDNF for the plasticity of dopaminergic neurons in the substantia nigra [116]. Following the same logic as with BDNF and serotonin, the investigation of interaction effects of BDNF and dopaminergic gene targets represents an interesting research endeavor. Here, a larger number of genetic targets on the side of the dopaminergic system have been investigated until now. BDNF Val66Met has been demonstrated to interact in a series of studies with the so called DRD2/ANKK1 Taq Ia polymorphism, known for its influence on D2 receptor density in structures of the striatum (e.g., [117]). Carriers of at least one 66Met allele carrying also the A1+ variant (being constructed by the A1/A1 and A1/A2 carriers) were associated with lowest novelty seeking scores and highest harm avoidance scores at the same time [81]. Fittingly, this interaction effect could be transferred to the anterior cingulate cortex in a genetic imaging study: again, carriers of the 66Met+/A1+ variant represented the “special” group, because they were associated with the lowest ACC gray matter volume. Finally, Walter et al. were able to extend these findings to alexithymia. Again, the genetic constellation 66Met+/A1+ represented the vulnerability constellation.

Besides the interaction of BDNF Val66Met with a genetic variation of the DRD2/ANKK1 Taq Ia polymorphism on personality, interaction effects have been observed in the dopamine context with a genetic variation of the dopamine transporter (DAT) gene [74] and the catechol-o-methyltransferase (COMT) gene [118]. In further detail, besides the BDNF Val66Met polymorphism, Hünnerkopf et al. [74] investigated the variable number of tandem repeat (VNTR) polymorphism of the gene SLC6A3 coding for DAT. Again, an association between the gene loci and negative emotion-related personality traits could be observed. More specifically, carriers of at least one 66Met allele together with the DAT 9+ variant reported the lowest neuroticism scores. The DAT 9+ allele has been associated with both higher and lower mRNA expressions of this gene up to now (e.g., [119, 120]). Therefore, the functional consequences of this VNTR polymorphism are still unclear.

Another important genetic target for a better understanding of dopaminergic neurotransmission represents the COMT Val158Met polymorphism. This genetic variation of the COMT gene is known to influence the catabolism of dopamine. The Met allele of this SNP has been associated with lower catabolism of dopamine [121] and putatively higher dopamine levels in the prefrontal cortex due to the paucity of dopamine transporters in this brain area (COMT exerts its effects mainly in the synaptic cleft; see [122]). In the In Kang et al. study the sensation seeking scale was administered [123]. One of its subscales measuring boredom susceptibility was influenced by an interaction effect between BDNF Val66Met and COMT Val158Met in the female subsample. Here, carriers of the configuration COMT Val158Val/BDNF Val66Val and COMT 158Met+/BDNF 66Met+ both showed lowest boredom susceptibility scores.

The interaction studies between two genetic loci in the present section outline the complexity of the molecular genetic underpinnings of personality and clearly show that risk alleles do not necessarily add up to elevate negative emotionality.

5.3. Interaction Effects of BDNF Val66Met and Environmental Influences on Human Personality

The last aspect to be discussed in the present review belongs to studies dealing with gene by environmental effects on personality traits, which have become a strong focus of research in recent years.

One of the most important studies in the field for gene by environmental effects represents the Caspi et al. [124] study investigating an interaction effect between 5-HTTLPR and stressful life events to predict depression in adulthood. Caspi and colleagues demonstrated that the s-allele is only associated with depression in adulthood when the participants of the study experienced adversity in particular in early life. Following from this seminal finding, several studies ensued investigating gene by environmental effects also with a focus on personality (e.g., [20, 125127]). Focusing on the BDNF gene, Kim et al. [76] reported that carriers of the homozygous Val66Val variant under the influence of negative stressors reported higher harm avoidance scores. Notably, no main effects of BDNF Val66Met on personality could be observed in this study. A BDNF Val66Met by early life stress interaction effect was reported by Gatt et al. [128]: In contrast to Kim et al. [76], they found evidence for the 66Met allele to be the vulnerability factor for neuroticism under high early life stress. Again, it is of importance to keep in mind that the studies differed in terms of measured stress (recent life stress versus early life stress) and also with respect to ethnicity. The 66Met allele occurs more often in the Asian population compared to Caucasian samples, and this can have effects on the power of the statistical analyses. Interestingly, Suzuki et al. [84] reported in another Asian sample (Japan) an interaction effect between BDNF Val66Met genotype and maternal care more in line with the data of Gatt et al. [128], who investigated Caucasians. Here, careless maternal behavior was associated with both higher harm avoidance and lower self-directedness scores particularly for carriers of the Met66Met variant ( out of participants carried here the less frequent Met66Met variant). As one can see from these numbers, the occurrence of the homozygous Met66Met clearly is higher in Asian populations compared to Caucasian populations (3%). Besides the investigation of BDNF by life stress interaction effects on personality, much research deals with the prediction of affective disorders in this field (e.g., [129, 130]).

6. Conclusions and Outlook

The present review highlighted the role of the brain derived neurotrophic factor for personality. One particularly robust finding from the BDNF personality research extends the observation from depression research, namely, that low BDNF levels are associated with higher negative emotionality in the form of higher degrees of neuroticism and harm avoidance. In sum, bearing in mind the limitations discussed in Section 4, this link seems to be valid for personality traits related to negative emotionality, as well as for psychopathology. In contrast, the meta-analysis on the link between the prominent BDNF Val66Met and BDNF serum levels [106] and between BDNF Val66Met and personality traits, such as harm avoidance/neuroticism [85], revealed no robust association. This does not mean that this association does not exist, because BDNF exerts its influence on human personality in a complicated pattern of interactions with other transmitter systems and is also modulated by the environment. Clearly, the effects of BDNF taken alone are rather small, as has been pointed out both by studies investigating BDNF levels and the BDNF gene. Moreover, most findings of BDNF research link BDNF to negative, but not positive, personality traits (only a few exceptions exist in the literature, as reported by Jiang et al. [77] or Montag et al. [81]). Future studies will probably detect new genetic variants for human personality of larger interest than BDNF Val66Met. Such potential genetic variations have already been observed in the near of or on the BDNF (e.g., in the near of the BDNF gene in a GWAS study by Terracciano et al. [131] or on the BDNF gene by Jiang et al. [77]). Besides this, genes coding for the receptor structures TrkB and , on which BDNF acts as a transmitter, are largely under-studied in the context of personality research.

Along this line of research, the study of BDNF gene activity in the context of personality will be of large importance in the near future. The latest development in the study of the BDNF gene goes one step beyond the studies reviewed here to understand exactly how environmental factors influence gene activity. The new emerging field of epigenetics will be of tremendous importance to better understand gene by environmental effects on psychological phenotypes [132]. A recent review article by Roth and Sweatt [133] outlined that early life environmental stressors shape the gene activity of BDNF. Here, rats that experienced abusive parents were associated with a hypermethylation of the BDNF gene, which means that the gene cannot be read sufficiently. This hypermethylation was accompanied by low BDNF mRNA levels, indicating lower BDNF levels. Most of the epigenetic studies are still conducted in animal models. In the near future, personality psychologists will surely also conduct their research in this fascinating new area, combining nature and nurture in one model.

7. Limitations of This Review

The present study dealt with a rather narrow view on BDNF, namely, its link to human personality traits. Clearly, an influence of BDNF has been shown in the literature beyond personality on a wide range of endophenotypes including cognition (e.g., [134] see reviews on pleiotropy by [135, 136]), which has not been highlighted in the present paper. I hope that all relevant “personality BDNF studies” are presented in the study. As 600 papers deal with the BDNF Val66Met polymorphism and 13.060 with BDNF right now, this is very unlikely (numbers retrieved via pubmed.com by entering in “BDNF” or “BDNF Val66Met” on 5 November 2013). Therefore, I regret any omissions. Finally, personality is influenced by a complex concert of different neurotransmitters and neuropeptides. In this context, some findings above illustrated how BDNF interacts with molecules such as dopamine. Reviews with a focus on other molecular systems of the brain are warranted to get deeper insights into the biological basis of personality.

Conflict of Interests

The author declares that there is no conflict of interests regarding the publication of this paper.

Acknowledgment

The author thanks Andrew Cooper for language editing.

References

  1. M. Bujalkova, S. Straka, and A. Jureckova, “Hippocrates' humoral pathology in nowaday's reflections,” Bratislavske Lekarske Listy, vol. 102, no. 10, pp. 489–492, 2001. View at Scopus
  2. A. Katsambas and S. G. Marketos, “Hippocratic messages for modern medicine (the vindication of Hippocrates),” Journal of the European Academy of Dermatology and Venereology, vol. 21, no. 6, pp. 859–861, 2007. View at Publisher · View at Google Scholar · View at Scopus
  3. M. Bateson, B. Brilot, and D. Nettle, “Anxiety: an evolutionary approach,” Canadian Journal of Psychiatry, vol. 56, no. 12, pp. 707–715, 2011. View at Scopus
  4. C. Montag, M. Eichner, S. Markett, C. M. Quesada, J. C. Schoene-Bake, and M. Melchers, “An interaction of a NR3C1 polymorphism and antenatal solar activity impacts both hippocampus volume and neuroticism in adulthood,” Frontiers in Human Neuroscience, vol. 7, article 243, 2013. View at Publisher · View at Google Scholar
  5. B. B. Lahey, “Public health significance of neuroticism,” American Psychologist, vol. 64, no. 4, pp. 241–256, 2009. View at Publisher · View at Google Scholar · View at Scopus
  6. G. W. Allport, Pattern and Growth in Personality, Holt, Rinehart and Winston, New York, NY, USA, 1961.
  7. C. R. Cloninger, D. M. Svrakic, and T. R. Przybeck, “A psychobiological model of temperament and character,” Archives of General Psychiatry, vol. 50, no. 12, pp. 975–990, 1993. View at Scopus
  8. R. R. McCrae and O. P. John, “An introduction to the five-factor model and its applications,” Journal of personality, vol. 60, no. 2, pp. 175–215, 1992. View at Scopus
  9. T. Robinson and S. Marwit, “An investigation of the relationship of personality, coping, and grief intensity among bereaved mothers,” Death Studies, vol. 30, no. 7, pp. 677–696, 2006. View at Publisher · View at Google Scholar · View at Scopus
  10. A. A. Augustine and R. J. Larsen, “Is a trait really the mean of states? Similarities and differences between traditional and aggregate assessments of personality,” Journal of Individual Differences, vol. 33, no. 3, p. 131, 2012.
  11. K. Martinowich, H. Manji, and B. Lu, “New insights into BDNF function in depression and anxiety,” Nature Neuroscience, vol. 10, no. 9, pp. 1089–1093, 2007. View at Publisher · View at Google Scholar · View at Scopus
  12. J. Panksepp, Affective Neuroscience: the Foundations of Human and Animal Emotions, Oxford University Press, 1998.
  13. J. Panksepp, “Affective neuroscience of the emotional Brain Mind: evolutionary perspectives and implications for understanding depression,” Dialogues in Clinical Neuroscience, vol. 12, no. 4, pp. 533–545, 2010. View at Scopus
  14. J. Panksepp, “Affective consciousness: core emotional feelings in animals and humans,” Consciousness and Cognition, vol. 14, no. 1, pp. 30–80, 2005. View at Publisher · View at Google Scholar · View at Scopus
  15. K. L. Davis and J. Panksepp, “The brain's emotional foundations of human personality and the Affective Neuroscience Personality Scales,” Neuroscience and Biobehavioral Reviews, vol. 35, no. 9, pp. 1946–1958, 2011. View at Publisher · View at Google Scholar · View at Scopus
  16. J. Panksepp, “Cross-Species affective neuroscience decoding of the primal affective experiences of humans and related animals,” PLoS ONE, vol. 6, no. 9, Article ID e21236, 2011. View at Publisher · View at Google Scholar · View at Scopus
  17. C. Darwin, The Expression of the Emotions in Man and Animals, Oxford University Press, 1998.
  18. C. Holden, “Paul MacLean and the triune brain,” Science, vol. 204, no. 4397, pp. 1066–1068, 1979. View at Scopus
  19. C. Montag, M. Jurkiewicz, and M. Reuter, “The role of the catechol-O-methyltransferase (COMT) gene in personality and related psychopathological disorders,” CNS & Neurological Disorders-Drug Targets, vol. 11, no. 3, pp. 236–250, 2012.
  20. C. Montag, M. Reuter, M. Jurkiewicz, S. Markett, and J. Panksepp, “Imaging the structure of the human anxious brain: a review of findings from neuroscientific personality psychology,” Reviews in the Neurosciences, vol. 24, no. 2, pp. 167–190, 2013.
  21. P. T. Costa and R. R. McCrae, Neo PI-R Professional Manual, vol. 396, Psychological Assessment Resources, Odessa, Ukraine, 1992.
  22. C. R. Cloninger, “A systematic method for clinical description and classification of personality variants: a proposal,” Archives of General Psychiatry, vol. 44, no. 6, pp. 573–588, 1987. View at Scopus
  23. R. J. Larsen and T. Ketelaar, “Extraversion, neuroticism and susceptibility to positive and negative mood induction procedures,” Personality and Individual Differences, vol. 10, no. 12, pp. 1221–1228, 1989. View at Scopus
  24. C. L. Rusting and R. J. Larsen, “Extraversion, neuroticism, and susceptibility to positive and negative affect: a test of two theoretical models,” Personality and Individual Differences, vol. 22, no. 5, pp. 607–612, 1997. View at Scopus
  25. D. Watson, R. O. M. A. N. Kotov, and W. Gamez, “Basic dimensions of temperament in relation to personality and psychopathology,” Personality and Psychopathology, pp. 7–38, 2006.
  26. H. J. Eysenck, Eysenck Personality Inventory, Educational and Industrial Testing Service, San Diego, Calif, USA, 1968.
  27. P. Seeman, “Dopamine receptors and the dopamine hypothesis of schizophrenia,” Synapse, vol. 1, no. 2, pp. 133–152, 1987. View at Scopus
  28. A. Soliman, G. A. O'Driscoll, J. Pruessner et al., “Stress-induced dopamine release in humans at risk of psychosis: a [11C] raclopride PET study,” Neuropsychopharmacology, vol. 33, no. 8, pp. 2033–2041, 2008. View at Publisher · View at Google Scholar · View at Scopus
  29. R. A. Wise and P. P. Rompre, “Brain dopamine and reward,” Annual Review of Psychology, vol. 40, pp. 191–225, 1989. View at Scopus
  30. R. A. Wise, “Dopamine, learning and motivation,” Nature Reviews Neuroscience, vol. 5, no. 6, pp. 483–494, 2004. View at Scopus
  31. R. A. Depue and P. F. Collins, “Neurobiology of the structure of personality: dopamine, facilitation of incentive motivation, and extraversion,” Behavioral and Brain Sciences, vol. 22, no. 3, pp. 491–517, 1999. View at Publisher · View at Google Scholar · View at Scopus
  32. R. A. Bevins, “Novelty seeking and reward: implications for the study of high-risk behaviors,” Current Directions in Psychological Science, vol. 10, no. 6, pp. 189–193, 2001. View at Scopus
  33. M. X. Cohen, J. Young, J.-M. Baek, C. Kessler, and C. Ranganath, “Individual differences in extraversion and dopamine genetics predict neural reward responses,” Cognitive Brain Research, vol. 25, no. 3, pp. 851–861, 2005. View at Publisher · View at Google Scholar · View at Scopus
  34. J. J. Simon, S. Walther, C. J. Fiebach et al., “Neural reward processing is modulated by approach- and avoidance-related personality traits,” NeuroImage, vol. 49, no. 2, pp. 1868–1874, 2010. View at Publisher · View at Google Scholar · View at Scopus
  35. C. Tsigos and G. P. Chrousos, “Hypothalamic-pituitary-adrenal axis, neuroendocrine factors and stress,” Journal of Psychosomatic Research, vol. 53, no. 4, pp. 865–871, 2002. View at Publisher · View at Google Scholar · View at Scopus
  36. M. A. Schlesser, G. Winokur, and B. M. Sherman, “Hypothalamic-pituitary-adrenal axis activity in depressive illness. Its relationship to classification,” Archives of General Psychiatry, vol. 37, no. 7, pp. 737–743, 1980. View at Scopus
  37. C. Kirschbaum, D. Bartussek, and C. J. Strasburger, “Cortisol responses to psychological stress and correlations with personality traits,” Personality and Individual Differences, vol. 13, no. 12, pp. 1353–1357, 1992. View at Scopus
  38. L. M. Oswald, P. Zandi, G. Nestadt, J. B. Potash, A. E. Kalaydjian, and G. S. Wand, “Relationship between cortisol responses to stress and personality,” Neuropsychopharmacology, vol. 31, no. 7, pp. 1583–1591, 2006. View at Publisher · View at Google Scholar · View at Scopus
  39. C. Montag, C. J. Fiebach, P. Kirsch, and M. Reuter, “Interaction of 5-HTTLPR and a variation on the oxytocin receptor gene influences negative emotionality,” Biological Psychiatry, vol. 69, no. 6, pp. 601–603, 2011. View at Publisher · View at Google Scholar · View at Scopus
  40. H. Tost, B. Kolachana, S. Hakimi et al., “A common allele in the oxytocin receptor gene (OXTR) impacts prosocial temperament and human hypothalamic-limbic structure and function,” Proceedings of the National Academy of Sciences of the United States of America, vol. 107, no. 31, pp. 13936–13941, 2010. View at Publisher · View at Google Scholar · View at Scopus
  41. C. R. Bramham and E. Messaoudi, “BDNF function in adult synaptic plasticity: the synaptic consolidation hypothesis,” Progress in Neurobiology, vol. 76, no. 2, pp. 99–125, 2005. View at Publisher · View at Google Scholar · View at Scopus
  42. M. E. Greenberg, B. Xu, B. Lu, and B. L. Hempstead, “New insights in the biology of BDNF synthesis and release: implications in CNS function,” Journal of Neuroscience, vol. 29, no. 41, pp. 12764–12767, 2009. View at Publisher · View at Google Scholar · View at Scopus
  43. H. W. Horch and L. C. Katz, “BDNF release from single cells elicits local dendritic growth in nearby neurons,” Nature Neuroscience, vol. 5, no. 11, pp. 1177–1184, 2002. View at Publisher · View at Google Scholar · View at Scopus
  44. Y. Ji, P. T. Pang, L. Feng, and B. Lu, “Cyclic AMP controls BDNF-induced TrkB phosphorylation and dendritic spine formation in mature hippocampal neurons,” Nature Neuroscience, vol. 8, no. 2, pp. 164–172, 2005. View at Publisher · View at Google Scholar · View at Scopus
  45. B. Lu, P. T. Pang, and N. H. Woo, “The yin and yang of neurotrophin action,” Nature Reviews Neuroscience, vol. 6, no. 8, pp. 603–614, 2005. View at Publisher · View at Google Scholar · View at Scopus
  46. L. Zhou, J. Xiong, Y. Lim, et al., “Upregulation of blood proBDNF and its receptors in major depression,” Journal of Affective Disorders, vol. 150, no. 3, pp. 776–784. View at Publisher · View at Google Scholar
  47. H. K. Teng, K. K. Teng, R. Lee, et al., “ProBDNF induces neuronal apoptosis via activation of a receptor complex of p75NTR and sortilin,” The Journal of Neuroscience, vol. 25, no. 22, pp. 5455–5463, 2005.
  48. R. Lee, P. Kermani, K. K. Teng, and B. L. Hempstead, “Regulation of cell survival by secreted proneurotrophins,” Science, vol. 294, no. 5548, pp. 1945–1948, 2001. View at Publisher · View at Google Scholar · View at Scopus
  49. F. Karege, G. Perret, G. Bondolfi, M. Schwald, G. Bertschy, and J.-M. Aubry, “Decreased serum brain-derived neurotrophic factor levels in major depressed patients,” Psychiatry Research, vol. 109, no. 2, pp. 143–148, 2002. View at Publisher · View at Google Scholar · View at Scopus
  50. A. Deveci, O. Aydemir, O. Taskin, F. Taneli, and A. Esen-Danaci, “Serum BDNF levels in suicide attempters related to psychosocial stressors: a comparative study with depression,” Neuropsychobiology, vol. 56, no. 2-3, pp. 93–97, 2008. View at Publisher · View at Google Scholar · View at Scopus
  51. B. Chen, D. Dowlatshahi, G. M. MacQueen, J.-F. Wang, and L. T. Young, “Increased hippocampal BDNF immunoreactivity in subjects treated with antidepressant medication,” Biological Psychiatry, vol. 50, no. 4, pp. 260–265, 2001. View at Publisher · View at Google Scholar · View at Scopus
  52. E. Shimizu, K. Hashimoto, N. Okamura et al., “Alterations of serum levels of brain-derived neurotrophic factor (BDNF) in depressed patients with or without antidepressants,” Biological Psychiatry, vol. 54, no. 1, pp. 70–75, 2003. View at Publisher · View at Google Scholar · View at Scopus
  53. R. S. Duman and L. M. Monteggia, “A neurotrophic model for stress-related mood disorders,” Biological Psychiatry, vol. 59, no. 12, pp. 1116–1127, 2006. View at Publisher · View at Google Scholar · View at Scopus
  54. J. O. Groves, “Is it time to reassess the BDNF hypothesis of depression?” Molecular Psychiatry, vol. 12, no. 12, pp. 1079–1088, 2007. View at Publisher · View at Google Scholar · View at Scopus
  55. Y. I. Sheline, M. H. Gado, and H. C. Kraemer, “Untreated depression and hippocampal volume loss,” American Journal of Psychiatry, vol. 160, no. 8, pp. 1516–1518, 2003. View at Publisher · View at Google Scholar · View at Scopus
  56. P. Videbech and B. Ravnkilde, “Hippocampal volume and depression: a meta-analysis of MRI studies,” American Journal of Psychiatry, vol. 161, no. 11, pp. 1957–1966, 2004. View at Publisher · View at Google Scholar · View at Scopus
  57. H. Yamasue, O. Abe, M. Suga et al., “Gender-common and -specific neuroanatomical basis of human anxiety-related personality traits,” Cerebral Cortex, vol. 18, no. 1, pp. 46–52, 2008. View at Publisher · View at Google Scholar · View at Scopus
  58. H. D. Schmidt and R. S. Duman, “Peripheral BDNF produces antidepressant-like effects in cellular and behavioral models,” Neuropsychopharmacology, vol. 35, no. 12, pp. 2378–2391, 2010. View at Publisher · View at Google Scholar · View at Scopus
  59. W. Pan, W. A. Banks, M. B. Fasold, J. Bluth, and A. J. Kastin, “Transport of brain-derived neurotrophic factor across the blood-brain barrier,” Neuropharmacology, vol. 37, no. 12, pp. 1553–1561, 1998. View at Publisher · View at Google Scholar · View at Scopus
  60. F. Karege, M. Schwald, and M. Cisse, “Postnatal developmental profile of brain-derived neurotrophic factor in rat brain and platelets,” Neuroscience Letters, vol. 328, no. 3, pp. 261–264, 2002. View at Publisher · View at Google Scholar · View at Scopus
  61. B. Martin, M. Pearson, L. Kebejian et al., “Sex-dependent metabolic, neuroendocrine, and cognitive responses to dietary energy restriction and excess,” Endocrinology, vol. 148, no. 9, pp. 4318–4333, 2007. View at Publisher · View at Google Scholar · View at Scopus
  62. U. E. Lang, R. Hellweg, and J. Gallinat, “BDNF serum concentrations in healthy volunteers are associated with depression-related personality traits,” Neuropsychopharmacology, vol. 29, no. 4, pp. 795–798, 2004. View at Publisher · View at Google Scholar · View at Scopus
  63. A. Terracciano, M. Lobina, M. G. Piras et al., “Neuroticism, depressive symptoms, and serum BDNF,” Psychosomatic Medicine, vol. 73, no. 8, pp. 638–642, 2011. View at Publisher · View at Google Scholar · View at Scopus
  64. S. Tsuchimine, N. Yasui-Furukori, A. Kaneda et al., “No association between polymorphism in tyrosine hydroxylase and personality traits in healthy Japanese subjects,” Psychiatry and Clinical Neurosciences, vol. 64, no. 2, pp. 196–198, 2010. View at Publisher · View at Google Scholar · View at Scopus
  65. K. Okuno, R. Yoshimura, N. Ueda et al., “Relationships between stress, social adaptation, personality traits, brain-derived neurotrophic factor and 3-methoxy-4-hydroxyphenylglycol plasma concentrations in employees at a publishing company in Japan,” Psychiatry Research, vol. 186, no. 2-3, pp. 326–332, 2011. View at Publisher · View at Google Scholar · View at Scopus
  66. V. Trajkovska, M. Vinberg, S. Aznar, G. M. Knudsen, and L. V. Kessing, “Whole blood BDNF levels in healthy twins discordant for affective disorder: association to life events and neuroticism,” Journal of Affective Disorders, vol. 108, no. 1-2, pp. 165–169, 2008. View at Publisher · View at Google Scholar · View at Scopus
  67. A. Terracciano, B. Martin, D. Ansari et al., “Plasma BDNF concentration, Val66Met genetic variant and depression-related personality traits,” Genes, Brain and Behavior, vol. 9, no. 5, pp. 512–518, 2010. View at Publisher · View at Google Scholar · View at Scopus
  68. A. Minelli, R. Zanardini, C. Bonvicini et al., “BDNF serum levels, but not BDNF Val66Met genotype, are correlated with personality traits in healthy subjects,” European Archives of Psychiatry and Clinical Neuroscience, vol. 261, no. 5, pp. 323–329, 2011. View at Publisher · View at Google Scholar · View at Scopus
  69. B. Arias, M. Aguilera, J. Moya et al., “The role of genetic variability in the SLC6A4, BDNF and GABRA6 genes in anxiety-related traits,” Acta Psychiatrica Scandinavica, vol. 125, no. 3, pp. 194–202, 2012. View at Publisher · View at Google Scholar · View at Scopus
  70. L. De Beaumont, A. J. Fiocco, G. Quesnel, S. Lupien, and J. Poirier, “Altered declarative memory in introverted middle-aged adults carrying the BDNF val66met allele,” Behavioural Brain Research, vol. 253, pp. 152–156, 2013.
  71. P. Gong, S. Xi, S. Li, et al., “Effect of Val66Met polymorphism in BDNF on attentional bias in an extroverted Chinese Han population,” Acta Neurobiologiae Experimentalis, vol. 73, pp. 280–288, 2013.
  72. B. J. Ham, H. B. An, S. M. Cho et al., “An association study of the brain-derived neurotrophic factor genes polymorphisms and personality traits,” Korean Journal of Biological Psychiatry, vol. 12, no. 2, pp. 216–220, 2005.
  73. K. Hiio, L. Merenäkk, N. Nordquist et al., “Effects of serotonin transporter promoter and BDNF Val66Met genotype on personality traits in a population representative sample of adolescents,” Psychiatric Genetics, vol. 21, no. 5, pp. 261–264, 2011. View at Publisher · View at Google Scholar · View at Scopus
  74. R. Hünnerkopf, A. Strobel, L. Gutknecht, B. Brocke, and K. P. Lesch, “Interaction between BDNF Val66Met and dopamine transporter gene variation influences anxiety-related traits,” Neuropsychopharmacology, vol. 32, no. 12, pp. 2552–2560, 2007. View at Publisher · View at Google Scholar · View at Scopus
  75. K. Itoh, K. Hashimoto, C. Kumakiri, E. Shimizu, and M. Iyo, “Association between brain-derived neurotrophic factor 196 G/A polymorphism and personality traits in healthy subjects,” American Journal of Medical Genetics: Neuropsychiatric Genetics, vol. 124, no. 1, pp. 61–63, 2004. View at Scopus
  76. S. J. Kim, S.-J. Cho, H. M. Jang et al., “Interaction between brain-derived neurotrophic factor Val66Met polymorphism and recent negative stressor in harm avoidance,” Neuropsychobiology, vol. 61, no. 1, pp. 19–26, 2009. View at Publisher · View at Google Scholar · View at Scopus
  77. X. Jiang, K. Xu, J. Hoberman et al., “BDNF variation and mood disorders: a novel functional promoter polymorphism and Val66Met are associated with anxiety but have opposing effects,” Neuropsychopharmacology, vol. 30, no. 7, pp. 1353–1361, 2005. View at Publisher · View at Google Scholar · View at Scopus
  78. R. T. Joffe, J. M. Gatt, A. H. Kemp et al., “Brain derived neurotrophic factor Val66Met polymorphism, the five factor model of personality and hippocampal volume: Implications for depressive illness,” Human Brain Mapping, vol. 30, no. 4, pp. 1246–1256, 2009. View at Publisher · View at Google Scholar · View at Scopus
  79. U. E. Lang, R. Hellweg, P. Kalus et al., “Association of a functional BDNF polymorphism and anxiety-related personality traits,” Psychopharmacology, vol. 180, no. 1, pp. 95–99, 2005. View at Publisher · View at Google Scholar · View at Scopus
  80. C. Montag, U. Basten, C. Stelzel, C. J. Fiebach, and M. Reuter, “The BDNF Val66Met polymorphism and anxiety: support for animal knock-in studies from a genetic association study in humans,” Psychiatry Research, vol. 179, no. 1, pp. 86–90, 2010. View at Publisher · View at Google Scholar · View at Scopus
  81. C. Montag, S. Markett, U. Basten et al., “Epistasis of the DRD2/ANKK1 Taq Ia and the BDNF Val66Met polymorphism impacts novelty seeking and harm avoidance,” Neuropsychopharmacology, vol. 35, no. 9, pp. 1860–1867, 2010. View at Publisher · View at Google Scholar · View at Scopus
  82. J. Savitz, L. Van Der Merwe, and R. Ramesar, “Personality endophenotypes for bipolar affective disorder: a family-based genetic association analysis,” Genes, Brain and Behavior, vol. 7, no. 8, pp. 869–876, 2008. View at Publisher · View at Google Scholar · View at Scopus
  83. S. Sen, R. M. Nesse, S. F. Stoltenberg et al., “A BDNF coding variant is associated with the NEO personality inventory domain neuroticism, a risk factor for depression,” Neuropsychopharmacology, vol. 28, no. 2, pp. 397–401, 2003. View at Scopus
  84. A. Suzuki, Y. Matsumoto, N. Shibuya et al., “The brain-derived neurotrophic factor Val66Met polymorphism modulates the effects of parental rearing on personality traits in healthy subjects,” Genes, Brain and Behavior, vol. 10, no. 4, pp. 385–391, 2011. View at Publisher · View at Google Scholar · View at Scopus
  85. A. Terracciano, T. Tanaka, A. R. Sutin et al., “BDNF Val66Met is associated with introversion and interacts with 5-HTTLPR to influence neuroticism,” Neuropsychopharmacology, vol. 35, no. 5, pp. 1083–1089, 2010. View at Publisher · View at Google Scholar · View at Scopus
  86. M. Tochigi, T. Otowa, M. Suga et al., “No evidence for an association between the BDNF Val66Met polymorphism and schizophrenia or personality traits,” Schizophrenia Research, vol. 87, no. 1-3, pp. 45–47, 2006. View at Publisher · View at Google Scholar · View at Scopus
  87. S.-J. Tsai, C.-J. Hong, Y. W.-Y. Yu, and T.-J. Chen, “Association study of a brain-derived neurotrophic factor (BDNF) Val66Met polymorphism and personality trait and intelligence in healthy young females,” Neuropsychobiology, vol. 49, no. 1, pp. 13–16, 2004. View at Publisher · View at Google Scholar · View at Scopus
  88. N. T. Walter, C. Montag, S. A. Markett, and M. Reuter, “Interaction effect of functional variants of the BDNF and DRD2/ANKK1 gene is associated with alexithymia in healthy human subjects,” Psychosomatic Medicine, vol. 73, no. 1, pp. 23–28, 2011. View at Publisher · View at Google Scholar · View at Scopus
  89. S. A. G. Willis-Owen, J. Fullerton, P. G. Surtees, N. W. J. Wainwright, S. Miller, and J. Flint, “The Val66Met coding variant of the brain-derived neurotrophic factor (BDNF) gene does not contribute toward variation in the personality trait neuroticism,” Biological Psychiatry, vol. 58, no. 9, pp. 738–742, 2005. View at Publisher · View at Google Scholar · View at Scopus
  90. H. Fujimura, C. A. Altar, R. Chen et al., “Brain-derived neurotrophic factor is stored in human platelets and released by agonist stimulation,” Thrombosis and Haemostasis, vol. 87, no. 4, pp. 728–734, 2002. View at Scopus
  91. A. Piccinni, D. Marazziti, A. Del Debbio et al., “Diurnal variation of plasma brain-derived neurotrophic factor (BDNF) in humans: an analysis of sex differences,” Chronobiology International, vol. 25, no. 5, pp. 819–826, 2008. View at Publisher · View at Google Scholar · View at Scopus
  92. S.-W. Choi, S. Bhang, and J.-H. Ahn, “Diurnal variation and gender differences of plasma brain-derived neurotrophic factor in healthy human subjects,” Psychiatry Research, vol. 186, no. 2-3, pp. 427–430, 2011. View at Publisher · View at Google Scholar · View at Scopus
  93. R. Katoh-Semba, R. Wakako, T. Komori et al., “Age-related changes in BDNF protein levels in human serum: differences between autism cases and normal controls,” International Journal of Developmental Neuroscience, vol. 25, no. 6, pp. 367–372, 2007. View at Publisher · View at Google Scholar · View at Scopus
  94. M. L. Molendijk, B. A. A. Bus, P. Spinhoven et al., “Serum levels of brain-derived neurotrophic factor in major depressive disorder: State-trait issues, clinical features and pharmacological treatment,” Molecular Psychiatry, vol. 16, no. 11, pp. 1088–1095, 2011. View at Publisher · View at Google Scholar · View at Scopus
  95. P. Jylhä, M. Ketokivi, O. Mantere et al., “Do antidepressants change personality?—a five-year observational study,” Journal of Affective Disorders, vol. 142, no. 1, pp. 200–207, 2012.
  96. M. F. Egan, M. Kojima, J. H. Callicott et al., “The BDNF Val66Met polymorphism affects activity-dependent secretion of BDNF and human memory and hippocampal function,” Cell, vol. 112, no. 2, pp. 257–269, 2003. View at Publisher · View at Google Scholar · View at Scopus
  97. L. Pezawas, B. A. Verchinski, V. S. Mattay et al., “The brain-derived neurotrophic factor Val66Met polymorphism and variation in human cortical morphology,” Journal of Neuroscience, vol. 24, no. 45, pp. 10099–10102, 2004. View at Publisher · View at Google Scholar · View at Scopus
  98. J. A. Bueller, M. Aftab, S. Sen, D. Gomez-Hassan, M. Burmeister, and J.-K. Zubieta, “BDNF Val66Met Allele is associated with reduced hippocampal volume in healthy subjects,” Biological Psychiatry, vol. 59, no. 9, pp. 812–815, 2006. View at Publisher · View at Google Scholar · View at Scopus
  99. C. Montag, B. Weber, K. Fliessbach, C. Elger, and M. Reuter, “The BDNF Val66Met polymorphism impacts parahippocampal and amygdala volume in healthy humans: incremental support for a genetic risk factor for depression,” Psychological Medicine, vol. 39, no. 11, pp. 1831–1839, 2009. View at Publisher · View at Google Scholar · View at Scopus
  100. M. E. Sublette, E. Baca-Garcia, R. V. Parsey et al., “Effect of BDNF Val66Met polymorphism on age-related amygdala volume changes in healthy subjects,” Progress in Neuro-Psychopharmacology and Biological Psychiatry, vol. 32, no. 7, pp. 1652–1655, 2008. View at Publisher · View at Google Scholar · View at Scopus
  101. J. Cole, D. R. Weinberger, V. S. Mattay et al., “No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression,” Genes, Brain and Behavior, vol. 10, no. 7, pp. 756–764, 2011. View at Publisher · View at Google Scholar · View at Scopus
  102. J. P. Kambeitz, S. Bhattacharyya, L. M. Ilankovic, I. Valli, and D. A. Collier, “Effect of BDNF Met66Val-Polymorphism on declarative memory and its neural substrate: a meta-analysis,” Neuroscience & Biobehavioral Reviews, vol. 36, no. 9, pp. 2165–2177, 2012.
  103. C. Montag, M. Reuter, B. Newport, C. Elger, and B. Weber, “The BDNF Val66Met polymorphism affects amygdala activity in response to emotional stimuli: Evidence from a genetic imaging study,” NeuroImage, vol. 42, no. 4, pp. 1554–1559, 2008. View at Publisher · View at Google Scholar · View at Scopus
  104. P. Mukherjee, H. C. Whalley, J. W. McKirdy et al., “Effects of the BDNF Val66Met polymorphism on neural responses to facial emotion,” Psychiatry Research: Neuroimaging, vol. 191, no. 3, pp. 182–188, 2011. View at Publisher · View at Google Scholar · View at Scopus
  105. J. Y. F. Lau, D. Goldman, B. Buzas et al., “BDNF gene polymorphism (Val66Met) predicts amygdala and anterior hippocampus responses to emotional faces in anxious and depressed adolescents,” NeuroImage, vol. 53, no. 3, pp. 952–961, 2010. View at Publisher · View at Google Scholar · View at Scopus
  106. A. Terracciano, M. G. Piras, M. Lobina, A. Mulas, O. Meirelles, and A. R. Sutin, “Genetics of serum BDNF: meta-analysis of the Val66Met and genome-wide association study,” World Journal of Biological Psychiatry, vol. 14, no. 8, pp. 583–589, 2011. View at Publisher · View at Google Scholar
  107. Z.-Y. Chen, D. Jing, K. G. Bath et al., “Genetic variant BDNF (Val66Met) polymorphism alters anxiety-related behavior,” Science, vol. 314, no. 5796, pp. 140–143, 2006. View at Publisher · View at Google Scholar · View at Scopus
  108. P. G. Surtees, N. W. J. Wainwright, S. A. G. Willis-Owen et al., “No association between the BDNF Val66Met polymorphism and mood status in a non-clinical community sample of 7389 older adults,” Journal of Psychiatric Research, vol. 41, no. 5, pp. 404–409, 2007. View at Publisher · View at Google Scholar · View at Scopus
  109. A. Frustaci, G. Pozzi, F. Gianfagna, L. Manzoli, and S. Boccia, “Meta-analysis of the brain-derived neurotrophic factor gene (BDNF) Val66Met polymorphism in anxiety disorders and anxiety-related personality traits,” Neuropsychobiology, vol. 58, no. 3-4, pp. 163–170, 2008. View at Publisher · View at Google Scholar · View at Scopus
  110. W. D. Taylor, S. Züchner, D. R. McQuoid, D. C. Steffens, D. G. Blazer, and K. R. R. Krishnan, “Social support in older individuals: the role of the BDNF Val66Met polymorphism,” American Journal of Medical Genetics, B: Neuropsychiatric Genetics, vol. 147, no. 7, pp. 1205–1212, 2008. View at Publisher · View at Google Scholar · View at Scopus
  111. X. Ma, J. Sun, J. Yao et al., “A quantitative association study between schizotypal traits and COMT, PRODH and BDNF genes in a healthy Chinese population,” Psychiatry Research, vol. 153, no. 1, pp. 7–15, 2007. View at Publisher · View at Google Scholar · View at Scopus
  112. K.-P. Lesch, D. Bengel, A. Heils et al., “Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region,” Science, vol. 274, no. 5292, pp. 1527–1531, 1996. View at Publisher · View at Google Scholar · View at Scopus
  113. T. Canli and K.-P. Lesch, “Long story short: the serotonin transporter in emotion regulation and social cognition,” Nature Neuroscience, vol. 10, no. 9, pp. 1103–1109, 2007. View at Publisher · View at Google Scholar · View at Scopus
  114. L. Pezawas, A. Meyer-Lindenberg, A. L. Goldman et al., “Evidence of biologic epistasis between BDNF and SLC6A4 and implications for depression,” Molecular Psychiatry, vol. 13, no. 7, pp. 709–716, 2008. View at Publisher · View at Google Scholar · View at Scopus
  115. O. Berton, C. A. McClung, R. J. DiLeone et al., “Essential role of BDNF in the mesolimbic dopamine pathway in social defeat stress,” Science, vol. 311, no. 5762, pp. 864–868, 2006. View at Publisher · View at Google Scholar · View at Scopus
  116. C. Hyman, M. Hofer, Y.-A. Barde et al., “BDNF is a neurotrophic factor for dopaminergic neurons of the substantia nigra,” Nature, vol. 350, no. 6315, pp. 230–232, 1991. View at Publisher · View at Google Scholar · View at Scopus
  117. E. G. Jönsson, M. M. Nöthen, F. Grünhage et al., “Polymorphisms in the dopamine D2 receptor gene and their relationships to striatal dopamine receptor density of healthy volunteers,” Molecular Psychiatry, vol. 4, no. 3, pp. 290–296, 1999. View at Scopus
  118. J. I. Kang, D.-H. Song, K. Namkoong, and S. J. Kim, “Interaction effects between COMT and BDNF polymorphisms on boredom susceptibility of sensation seeking traits,” Psychiatry Research, vol. 178, no. 1, pp. 132–136, 2010. View at Publisher · View at Google Scholar · View at Scopus
  119. S. Fuke, “The VNTR polymorphism of the human dopamine transporter (DAT!) gene affects gene expression,” Pharmacogenomics Journal, vol. 1, no. 2, pp. 152–156, 2001. View at Scopus
  120. G. M. Miller and B. K. Madras, “Polymorphisms in the 3′-untranslated region of human and monkey dopamine transporter genes affect reporter gene expression,” Molecular Psychiatry, vol. 7, no. 1, pp. 44–55, 2002. View at Publisher · View at Google Scholar · View at Scopus
  121. H. M. Lachman, D. F. Papolos, T. Saito, Y.-M. Yu, C. L. Szumlanski, and R. M. Weinshilboum, “Human catechol-O-methyltransferase pharmacogenetics: description of a functional polymorphism and its potential application to neuropsychiatric disorders,” Pharmacogenetics, vol. 6, no. 3, pp. 243–250, 1996. View at Publisher · View at Google Scholar · View at Scopus
  122. R. M. Bilder, J. Volavka, H. M. Lachman, and A. A. Grace, “The catechol-O-methyltransferase polymorphism: relations to the tonic-phasic dopamine hypothesis and neuropsychiatric phenotypes,” Neuropsychopharmacology, vol. 29, no. 11, pp. 1943–1961, 2004. View at Publisher · View at Google Scholar · View at Scopus
  123. M. Zuckerman, “The psychophysiology of sensation seeking,” Journal of personality, vol. 58, no. 1, pp. 313–345, 1990. View at Scopus
  124. A. Caspi, K. Sugden, T. E. Moffitt et al., “Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene,” Science, vol. 301, no. 5631, pp. 386–389, 2003. View at Publisher · View at Google Scholar · View at Scopus
  125. L. Mandelli, N. Antypa, F. A. Nearchou et al., “The role of serotonergic genes and environmental stress on the development of depressive symptoms and neuroticism,” Journal of Affective Disorders, vol. 142, no. 1–3, pp. 82–89, 2012. View at Publisher · View at Google Scholar
  126. M. Pluess, J. Belsky, B. M. Way, and S. E. Taylor, “5-HTTLPR moderates effects of current life events on neuroticism: differential susceptibility to environmental influences,” Progress in Neuro-Psychopharmacology and Biological Psychiatry, vol. 34, no. 6, pp. 1070–1074, 2010. View at Publisher · View at Google Scholar · View at Scopus
  127. S. Wagner, Ö. Baskaya, K. Lieb, N. Dahmen, and A. Tadić, “The 5-HTTLPR Polymorphism modulates the association of serious life events (SLE) and impulsivity in patients with Borderline Personality Disorder,” Journal of Psychiatric Research, vol. 43, no. 13, pp. 1067–1072, 2009. View at Publisher · View at Google Scholar · View at Scopus
  128. J. M. Gatt, C. B. Nemeroff, C. Dobson-Stone et al., “Interactions between BDNF Val66Met polymorphism and early life stress predict brain and arousal pathways to syndromal depression and anxiety,” Molecular Psychiatry, vol. 14, no. 7, pp. 681–695, 2009. View at Publisher · View at Google Scholar · View at Scopus
  129. M. Aguilera, B. Arias, M. Wichers et al., “Early adversity and 5-HTT/BDNF genes: new evidence of gene-environment interactions on depressive symptoms in a general population,” Psychological Medicine, vol. 39, no. 9, pp. 1425–1432, 2009. View at Publisher · View at Google Scholar · View at Scopus
  130. M. Wichers, G. Kenis, N. Jacobs et al., “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, vol. 147, no. 1, pp. 120–123, 2008. View at Publisher · View at Google Scholar · View at Scopus
  131. A. Terracciano, S. Sanna, M. Uda et al., “Genome-wide association scan for five major dimensions of personality,” Molecular Psychiatry, vol. 15, no. 6, pp. 647–656, 2010. View at Publisher · View at Google Scholar · View at Scopus
  132. T.-Y. Zhang and M. J. Meaney, “Epigenetics and the environmental regulation of the genome and its function,” Annual Review of Psychology, vol. 61, pp. 439–466, 2010. View at Publisher · View at Google Scholar · View at Scopus
  133. T. L. Roth and J. D. Sweatt, “Epigenetic marking of the BDNF gene by early-life adverse experiences,” Hormones and Behavior, vol. 59, no. 3, pp. 315–320, 2011. View at Publisher · View at Google Scholar · View at Scopus
  134. E. Dempster, T. Toulopoulou, C. McDonald et al., “Association between BDNF val66 met genotype and episodic memory,” American Journal of Medical Genetics: Neuropsychiatric Genetics, vol. 134, no. 1, pp. 73–75, 2005. View at Publisher · View at Google Scholar · View at Scopus
  135. T. E. Goldberg and D. R. Weinberger, “Genes and the parsing of cognitive processes,” Trends in Cognitive Sciences, vol. 8, no. 7, pp. 325–335, 2004. View at Publisher · View at Google Scholar · View at Scopus
  136. Y. Kovas and R. Plomin, “Generalist genes: implications for the cognitive sciences,” Trends in Cognitive Sciences, vol. 10, no. 5, pp. 198–203, 2006. View at Publisher · View at Google Scholar · View at Scopus