Genetic Polymorphisms

Mikhail Votinov^1,2 and Katharina Sophia Goerlich¹

¹ Department of Psychiatry, Psychotherapy and Psychosomatics, RWTH Aachen University, Aachen, Germany

² Institute of Neuroscience and Medicine (INM‐10), Jülich, Germany

The Study of Genetics

DNA molecules consist of two strands that are coiled around each other like a twisted ladder, forming a double helix. The two DNA strands are called polynucleotides since they consist of smaller units called nucleotides. Each nucleotide is composed of a nitrogen‐containing nucleobase: either adenine (A) and thymine (T), creating A–T pairs, or cytosine (C) and guanine (G), creating G–C pairs, as well as sugar (deoxyribose) and a phosphate group.

Polymorphisms are variations of a particular DNA sequence. The most common type of polymorphisms involves variation at a single base pair. These are called single nucleotide polymorphisms (SNPs). For example, an SNP may replace the cytosine (C) with thymine (T) at a certain DNA locus. When such SNPs occur within a gene, they may change the amino acid sequence of the gene's protein product or change the timing, location, or level of gene expression. Another type of polymorphism is a variation (e.g., repeats) in tandems of two or more adjacent nucleotides (see Figure 1).

Despite intense research on the role of genetics in human health and behavior in the past decades, we are still far from fully understanding the complex interactions between genes and behavior. Here, we provide an overview of several genes whose polymorphisms have been extensively studied due to their role in the regulation of molecular mechanisms and modulation of neurotransmitter systems in the brain, leading to changes in human cognition and behavior.

Dopamine System

Numerous studies across a wide range of species demonstrated that the dopaminergic system plays a key role in reward, behavioral flexibility, working memory (WM), positive reinforcement, and learning processes. Malfunction in this system is associated with behavioral abnormalities and diseases such as impulsive behaviors, addiction, Parkinson's disease, and schizophrenia.

Schematic illustration of overview of DNA structure and types of gene polymorphisms 225 × 128 mm. — **Figure 1** Overview of DNA structure and types of gene polymorphisms 225 × 128 mm (300 × 300 DPI).

Dopamine (DA) is a monoamine neurotransmitter that is produced by DA neurons in two regions of the midbrain, the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc), and projected to a broad number of brain regions. There are three major dopaminergic projections in the central nervous system: the nigrostriatal pathway, regulating motor functions; the mesocorticolimbic pathway, which plays a key role in reward, motivation, learning, emotions, and memory; and the tuberoinfundibular pathway, involved in prolactin secretion regulation and sensory processing.

DA transmission in the brain is mediated by five (D1–D5) subtypes of DA receptors, dopamine transporters (DAT), and enzyme catabolizers, which show different patterns of distribution across brain regions and therefore affect different cognitive functions. For instance, the concentration of D1 receptors is higher in prefrontal areas, while D2 receptor concentration is most prevalent in the striatum. DAT density is highest in subcortical regions, and catechol‐O‐methyltransferase (COMT) plays a major role in DA clearance in the prefrontal cortex (PFC).

Genetic polymorphisms of the DA system include SNPs and variable number tandem repeat (VNTR) polymorphisms of the metabolizing enzymes, receptors and transporters, which modulate tonic DA (the average amount of DA available over a relatively long period of time) or phasic DA levels (the amount of DA being released in a given burst of neuronal firing). The most important genes modulating DA transmission comprise the enzyme catabolizers COMT and monoamine oxidase A (MAOA), dopamine‐ and cAMP‐regulated phosphoprotein (DARPP‐32), the dopamine receptor D2 (DRD2) and D4 (DRD4) genes, and DAT.

Serotonin System

A further important monoamine neurotransmitter is serotonin (5HT or 5‐hydroxytryptamine), which is produced in the raphe nuclei of the midbrain and transported to the limbic system, cerebellum, and cortex. The serotonin system plays an important role in sensory processing, sleep, memory, mood, and arousal. Pathology in this system has been associated with diseases such as depression, antisocial behavior, bipolar disorder, and schizophrenia.

The best‐investigated gene modulating serotonin transmission is the serotonin transporter‐linked polymorphic region (5‐HTTLPR) gene. Genetic variations in this gene have been linked to personality traits such as impulsivity and neuroticism and to a range of psychiatric illnesses as well as the treatment success of such disorders.

5HT, catecholamines, and histamine are metabolized by the COMT and monoamine oxidase (MAO) enzymes. There are two MAO isoforms (MAOA and MAOB) that are encoded by distinct genes on the X chromosome. MAOA and MAOB differ in their substrate specificity, anatomical distribution, regulation by pharmacological agents, and influence on behavior. Serotonin is mostly degraded by MAOA, while DA is degraded by both MAOA and MAOB.

Opioid System

The opioid system has been extensively studied due to its association to pain, analgesia, reward sensitivity, and substance abuse. There are several endogenous opioids—dynorphins, enkephalins, endorphins, and endomorphins—which bind with high affinity to particular μ‐, δ‐, and κ‐opioid receptors. Important genes modulating the opioid system are the μ‐opioid receptor gene (OPRM1) and prodynorphin (PDYN), a gene coding for dynorphin opioid peptides, which have a high affinity to κ‐opioid receptors. Genetic variations in these genes have been associated with individual differences in the reward processing as well as different forms of addiction, such as nicotine and alcohol dependence.

Neuroendocrine System

The hypothalamus and pituitary gland are the center of integration for the nervous and the endocrine system. The neuroendocrine system plays a role in social behavior, mating, pair bonding, trust, aggression, and empathy. A well‐studied gene modulating the neuroendocrine system is the oxytocin receptor (OXTR) gene, which has been implicated in a wide range of social behaviors.

In addition to the genes mentioned above, the proteins apolipoprotein E (ApoE) and the brain‐derived neurotrophic factor (BDNF) have been extensively investigated due to their involvement in memory, aging, depression, anxiety, and mood disorders. ApoE is a major cholesterol carrier that supports lipid transport and injury repair in the brain, whose allele number 4 ApoE ε4 is the most important genetic risk factor for Alzheimer's disease (AD) and dementia. BDNF is a protein involved in the proliferation, neurogenesis, differentiation, survival of neuronal cells, and neuroplasticity, which is involved in the pathogenesis of a wide range of psychiatric disorders. Table 1 provides an overview of the here discussed genes and polymorphisms and their involvement in functional domains of cognition and behavior.

Polymorphisms and Behavior

Reward Processing

Rewards may be defined as events that generate approach and consummatory behavior, evoking positive emotions and leading to learning of this behavior. Rewards that are crucial for survival such as eating, drinking, and reproduction are called primary rewards. Rewards that are attributed to, for instance, money, gambling, and aesthetic stimuli are called secondary rewards.

Table 1 A list of genes associated with neurotransmitter systems and their related polymorphisms and the proposed mechanism of those polymorphisms on cognitive function.

Gene	Polymorphism	Mechanism	Functional domain
Dopamine system
COMT (catechol‐O‐methyltransferase) Enzyme with high availability in prefrontal cortex that degrades catecholamines	SNP Val158Met (rs4680) Substitution of methionine (Met) in place of valine (Val) at codon 158	Met/Met carriers have a 2–4 fold decrease of COMT activity, compared with the Val/Val genotype, leading to higher extracellular dopamine levels in the prefrontal cortex	Reward, working memory, learning, attention
DRD2 (dopamine receptor D2)/ANKK1 (ankyrin repeat and kinase domain) Closely linked to the dopamine receptor D2 (DRD2) on chromosome band 11q23.1	DRD2/ANKK1‐Taq1A (rs1800497) Located in a putative substrate‐binding domain of the ANNK1 gene, resulting in a Glu713Lys substitution	This polymorphism modulates the density of DA D2 receptors. A1 allele carriers show a reduction in striatal D2 receptor density compared to the noncarriers	Reward, learning, neuroticism, addiction, schizophrenia
DRD4 (dopamine receptor D4) Located on chromosome 11p, predominantly expressed in prefrontal cortex	48‐bp tandem repeat (VNTR) Codes for the third cytoplasmic loop of the receptor	The 7‐repeat variant has been linked to decreased postsynaptic inhibition and lower dopaminergic tone	Impulsivity, novelty seeking, addiction, obsessive–compulsive disorder, ADHD
DAT (dopamine transporter) SLC6A3 High availability in striatum, regulates dopamine signaling at the synapse through reuptake of dopamine into presynaptic terminals, thus terminating signaling	40‐bp VNTR (rs28313670) Located in the3′‐untranslated (UTR) region of the gene with repeat numbers between 3 and 13	This polymorphism produces two common alleles with 9 and 10 repeats (9R and 10R), which affect the basal level of expression of the transporter. The 9R allele is associated with increased DAT activity in human adults	Reward, addiction, learning, working memory, cognitive flexibility, ADHD
DARPP‐32 (dopamine‐ and cAMP‐regulated phosphoprotein) PPP1R1B (protein phosphatase 1 regulatory inhibitor subunit 1B), located on chromosome 17q12	DARPP‐32 Richly expressed protein in the striatum, regulated by D1 and D2 dopamine receptors in opposing directions	The protein modulates striatal dopamine cellular excitability and synaptic plasticity related to the dopamine receptors. AA homozygotes have higher D1 dopamine receptor efficacy	Learning, cognitive flexibility, anger
Serotonin system
5‐HTT/SLC6A4 (serotonin transporter gene)	5‐HTTLPR Short and long repeats in the 5‐HTT‐linked polymorphic region. The short variation has 14 repeats of a sequence, the long variation has 16 repeats	The short allele is associated with lower levels of serotonin uptake and lower transcriptional efficiency of the serotonin transporter protein compared with the long allele	Impulsivity, aggression, antisocial behavior, anxiety, depression, bipolar disorder
MAOA (monoamine oxidase A) An enzyme that metabolizes catecholamines, 5HT and histamine	30‐bpVNTR Located 1.2 kb upstream from exon 1 in the 5’ UTR of MAOA gene	Common are 3 and 4 repeats, less frequent are 2, 3.5, and 5 repeats. The alleles with 3.5 or 4 repeats (high activity alleles) have 2–10 times more transcriptional activity than those with 2 or 3 copies (low‐activity alleles)	Aggression, antisocial behavior, depression, reward, addiction
Opioid system
OPRM1	SNP (rs1799971) Often referred to as A118G, situated in exon 1	The variant leads to the conversion of the amino acid asparagine to aspartate at codon 40	Addiction, alcoholism, Smoking
PDYN (prodynorphin) Codes the dynorphin opioid peptides, which have a high affinity to κ receptors	This polymorphism is located in the PDYN gene promoter region with one to four repeats of a 68‐bp element containing one binding site per repeat for the transcription factor AP‐1(c‐Fos/c‐Jun)	Alleles with 3 or 4 repeats are associated with higher levels of dynorphins expression than alleles with 1 or 2 repeats	Reward, addiction, alcoholism, memory
Neuroendocrine system
OXTR (oxytocin receptor)	SNP (rs53576), which consists of a G to A change within the third intron	Research usually compares individuals homozygous for the G allele (GG) with individuals with A allele carriers (AA/AG)	Prosocial behavior, empathy, trust, mating, depression, personality traits
Proteins
ApoE (apolipoprotein E) Produces a protein that, when combined with fat, becomes a lipoprotein	ApoE‐ε2, ApoE‐ε3, ApoE‐ε4 Three allelic variants of ApoE as defined by the two SNPs rs429358 and rs7412	ApoE ε4 is associated with an increased risk of developing Alzheimer's disease, ApoE ε2 with a reduced risk, relative to the more common ε3 allele	Memory, Alzheimer's disease, mild cognitive impairment
BDNF (brain‐derived neurotrophic factor) Supports neuronal growth and differentiation, induces long‐lasting changes in synaptic plasticity	BDNF Val66Met Substitution of methionine (Met) for valine (Val) at codon 66 of the pro‐BDNF protein	The Met allele results in reduced activity‐dependent release of BDNF and inefficient BDNF trafficking	Memory, aging, depression

The ability to predict future rewards and losses and to assess the value of upcoming outcomes is a fundamental aspect of learning and adaptive behavior. Numerous neurophysiological and neuroimaging studies demonstrated that anticipating and receiving rewards activates the brain's reward circuitry, including the dopaminergic midbrain, striatum, and PFC. Given the fundamental role of DA in reward processing, studies investigating reward anticipation and feedback, approach motivation, goal‐directed behavior, and pathological aspects of the reward system focused on several genetic variations in the dopaminergic system to reveal how those variations modulate reward‐related behavior. These investigations confirmed significant effects of polymorphisms in the COMT, DAT, DRD2/Taq1A, and DRD4 genes on reward behavior and its underlying brain activity.

One of the best‐investigated genetic variations in the dopaminergic system is the COMT Val158Met polymorphism, which contributes to a degradation of DA in PFC and modulates activity in the cortico‐striatal loop connecting the frontal cortex and the brain’s core reward center, the striatum. Imaging genomics studies found that there is a linear relationship between the number of met158 alleles and ventral striatal activity and that the activation of the ventral striatum and anterior cingulated cortex is modulated by the COMT polymorphism. Further, an interaction between the COMT Val158Met polymorphism and stressful life events was observed, such that Met/Met carriers (who have higher levels of DA in PFC) with low exposure to lifetime stress showed a lower sensitivity to reward than Met/Met carriers with high exposure to lifetime stress. A study investigating how the interaction between the COMT and DAT genes influences reward processing revealed that both variants modulated activation in PFC and striatum and that the combinations COMT Met/Met DAT 10R and COMT Val/Val 9R were associated with blunted responses to rewards in the ventral striatum. People with the 22q11.2 deletion syndrome (a microdeletion on chromosome 22q11.2, where the gene coding for COMT is located) displayed reduced activity in medial frontal regions during reward anticipation.

Studies of the DAT1 gene revealed that carriers of the 9‐repeat allele, associated with high levels of DA in the striatum, showed greater activity in the ventromedial striatum during reward anticipation than homozygotes for the 10‐repeat allele. Individual differences in extraversion and the presence of the DRD2 Taq1A allele predicted a significant amount of intersubject variability in the magnitudes of reward‐related brain activity. Moreover, the DRD2 gene was linked to the interindividual variations in neural responses to expectations of reward and negative emotional processing, as well as stress‐induced DA release.

These studies demonstrated that genetic variations in the COMT gene as well as the DAT1 and DRD2 genes alter the processing of rewards in the brain. However, effects of polymorphisms in other neurotransmitter systems have also been observed. For example, T homozygotes carriers of the oxytocin (OXTR) gene demonstrated relatively decreased activation in the mesolimbic circuitry when anticipating rewards. Moreover, individuals with the HH genotype of the 68‐bp VNTR PDYN gene showed higher activation in the medial orbitofrontal cortex (mOFC) when anticipating monetary rewards and stronger functional coupling of mOFC with the ventral striatum and ventral medial PFC than individuals with the LL genotype, indicating an increased sensitivity for upcoming rewards.

Besides leading to individual differences in how rewards are processed in the healthy brain, genetic variations in neurotransmitters implicated in the reward system, genetic variations may contribute to a hyper‐ or hyposensitivity to rewards that can become pathological. Hypersensitivity to potential rewards may lead to an excessive increase in approach behavior in the presence of rewards, while a decreased sensitivity may lead to seeking ever more stimulating experiences in order to compensate for low levels of reward experience. Such malfunctions of the reward system can contribute to pathological forms of reward behavior, such as sensation seeking, risk‐taking, pathological gambling (PG), anhedonia, and addiction.

Drugs induce a pleasurable state and are therefore experienced as rewarding and thus reinforcing. In addition, repeated self‐administration of drugs causes cellular and molecular changes in neurons as well as homeostatic adaptations, which further contribute to increased tolerance of the drug and, eventually, addiction. Drugs act via different systems: opioid drugs via binding with μ‐opioid receptors, cocaine and amphetamine through the DAT, and ethanol through GABAa receptors and the inhibition of NMDA glutamate receptors. Understanding genetic risk factors for individual vulnerability to addiction is of high importance for the development of prevention strategies.

There is evidence that individual variations in the opioid OPRM1 and PDYN genes are related to the development of opioid and ethanol substance dependence. Methamphetamine and heroin‐dependent individuals exhibited a significantly higher frequency of the 3‐ or4‐repeat allele 68‐bp VNTR polymorphism in the PDYN gene than healthy individuals. Similarly, several other PDYN polymorphisms (e.g., rs1022563, rs2235749) were associated with cocaine, heroin, and alcohol. Comparable findings were observed for an SNP of theμ‐opioid receptor gene OPRM1 (rs1799971), which has been linked to heroin abuse, alcoholism, and smoking. A recent meta‐analysis confirmed that the OPRM1 SNP contributes to mechanisms of addiction liability and is shared across different addictive substances. Moreover, studies investigating DA receptor candidate genes suggested that the DRD2 A1 allele (DRD2 Taq1A polymorphism) was associated with a higher consumption of alcohol and heroin.

A well‐studied example of addiction not including substance abuse (i.e., behavioral addiction) is PG. In the recently released fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM‐5), pathological gambling (renamed “disordered gambling”) was moved from the “Impulse Control Disorders Not Elsewhere Classified” category into the new “Substance‐Related and Addictive Disorders” category. PG is a chronic, progressive disorder that is associated with the urge to gamble continuously despite harmful negative consequences or a desire to stop. Often, gambling is used as a model for investigating mechanism of developing a behavioral addiction. The heritability of PG is estimated to be 50–60%. PG shares genetic vulnerability factors with alcohol dependence and depressive disorder, with the genetic correlation between PG and alcohol dependence ranging from 0.29 to 0.44, with men showing a higher correlation than women.

Genetic studies have associated PG with the DRD2 TaqA1 polymorphism, the 10/10 alleles of the DAT1 gene, and polymorphisms of DRD2/ANKK1, revealing that pathological gamblers with genetic predispositions toward lower availability of DA and D2 receptor density are at a higher risk of cognitive flexibility difficulties. Other candidate genes that have been the focus of genetic association studies of PG are the serotonin transporter gene and the MAOA genes. Allelic frequency of the 3‐copy allele MAOA polymorphism was observed to be significantly higher in male gamblers than in men without PG, and the less functional S allele of the 5‐HTTPLR polymorphism was more frequent in male gamblers. However, the only genome‐wide association study of PG to date in 1,312 twins found no single candidate gene reaching genome‐wide significance, rendering current results of genetic variations underlying PG preliminary and in need of replication.

Substance abuse and behavioral addictions are highly comorbid with other maladaptive behaviors, such as impulsivity, risk‐taking, and sensation and novelty seeking. Impulsivity is characterized as the inability to withhold an action for the time needed to estimate consequences. An example of an impulsive choice is when an individual preferentially chooses an immediately available small reward rather than enduring a certain time delay for a larger reward (“delay discounting”), a behavior that is frequently observed in individuals with substance use disorders. Independent twin and longitudinal twin studies have demonstrated a heritability of impulsivity in the range of 40–50% and implicated the DA‐related genes COMT, DRD2, DRD4, and DAT in impulsivity, delay discounting, and risk‐taking. However, the most extensively studied polymorphism in the context of impulsivity is the serotonin transporter5‐HTTLPR, revealing that carriers of the less active S allele score higher on attentional impulsiveness and are less sensitive to punishment‐related information.

Learning

Based on the reinforcing role of rewards in learning processes, the dopaminergic system is also a key component of learning and motivation, as evidenced by a wealth of findings across a range of different species from rats to humans. In the striatum, DA is critical for reinforcing actions that are most likely to lead to a reward. Demonstrating this, striatal activation has been observed to predict the amount of learning effects regarding WM updating. In response to positive “prediction errors” (events that are better than expected), DA cells burst fire, whereas the same cells remain silent in response to negative prediction errors (events that are worse than expected). Reinforcement learning models assume that these bursts and dips act as teaching signals by modifying synaptic plasticity in the structures involved. Studies in rodents have shown that phasic (but not tonic) stimulation of dopaminergic cells induces behavioral conditioning, and conversely, selective genetic disruption of phasic dopaminergic burst firing produces behavioral learning deficits, demonstrating a direct influence between DA activity on learning in animals.

In humans, several genes controlling dopaminergic function in the frontostriatal circuitry have been investigated in the context of learning, including COMT, DARPP‐32, DAT1, DRD2, and DRD4. The COMT Val158Met polymorphism has repeatedly been found to influence cognitive processing in a variety of tasks requiring prefrontal function, and a recent meta‐analysis confirmed the involvement of the COMT Val158Met polymorphism in reward learning. Genetic polymorphisms modulating DARPP‐32 mRNA expression and cognition in humans are associated with changes in activation in the striatum and with frontostriatal connectivity. Biophysical models showed that DARPP‐32 serves to integrate DA signals across time, demonstrating a key role of this gene in probabilistic reinforcement learning. The DAT1 polymorphism is predictive of neural and behavioral responses to cognitive flexibility and has further been shown to modulate striatal activity as a function of WM load in an updating task. The DRD2 gene polymorphism affects D2 receptor density in the striatum, the brain region in which D2 receptors are by far most prevalent. DRD2 has been demonstrated to be strongly predictive of learning from negative reward prediction errors, that is, avoiding responses that lead to negative outcomes. Lastly, the DRD4 gene is associated with dopaminergic function in PFC, in which the D4 receptor is primarily expressed, and has been found predictive of error‐related prefrontal activity and subsequent behavioral adjustments.

Besides the DA system, also the serotonin system has been implicated in individual differences in learning and decision making, revealing a differential association of the serotonin transporter 5‐HTTLPR polymorphism with reflexive and reflective optimal learning. Moreover, the Val66Met polymorphism of the neurotrophin BDNF, which is involved in regulating synaptic plasticity in many brain areas including the hippocampus, has been suggested to affect sensorimotor cortex activity as well as motor learning in humans. Individuals with the BDNF Met allele have been reported to show increased cognitive performance and to commit more errors during short‐term learning during a driving‐based motor learning task. Furthermore, a recent study provided first evidence that dynorphins contribute to individual differences in reversal learning: carriers of the HH genotype (alleles with 3 or 4 repeats) of the nucleotide tandem repeat (68‐bp VNTR) functional polymorphism of the prodynorphin (PDYN) made more perseverative errors than carriers of the LL genotype in a reversal learning task requiring flexible adaptation to stimulus–response associations and showed less engagement of the orbitofrontal cortex (OFC) and cortico‐striatal circuitry as well as lower effective connectivity of the OFC with the anterior midcingulate cortex and the anterior insula/ventrolateral PFC during reversal learning and the processing of negative feedback.

Taken together, individual differences in human learning capacity have been robustly associated with genetic variations in the DA system. While many studies have linked single DA‐related candidate genes to individual differences in learning, it has to be considered that the well‐studied COMT val/met polymorphism can itself be moderated by other dopaminergic polymorphisms such as DAT1 and DRD2 as well as within the COMT gene itself, requiring future investigations taking more complex gene × gene interactions into account. Besides the COMT Val158Met polymorphism, individual differences in learning seem further modulated by the BDNF Val66Met polymorphism and the PDYN VNTR polymorphism.

Memory

The apolipoprotein E (ApoE) gene is the most important known genetic risk factor for AD, a chronic neurodegenerative disease causing dementia. ApoE has three major alleles: ApoE ε2, ε3, and ε4. ApoE ε4 is associated with an increased risk of AD, ApoE ε2 with a reduced risk, relative to the more common ε3 allele. Healthy carriers of APOE ε4 show an accelerated decline in memory tests starting at the age of 55–60 years. While the underlying mechanism of this effect of ApoE ε4 is not fully understood, evidence suggests an interaction with amyloid: AD is characterized by buildups of aggregates of the peptide beta‐amyloid. ApoE enhances proteolytic breakdown of this peptide, and ApoE ε4 appears less effective than the other alleles at promoting these reactions, resulting in increased vulnerability to AD in individuals carrying the ApoE ε4 allele. Regarding protective factors, evidence suggests that a high education level, active leisure activities and exercise, and maintenance of vascular health are beneficial in reducing the risk of AD and cognitive decline, particularly in APOE ε4 carriers.

Besides ApoE, individual differences in memory performance are influenced by the neurotrophin BDNF, whose levels of expression are particularly high in the hippocampus, the brain’s memory center, in which the consolidation of information from short‐term to long‐term memory takes place. The BDNF Val66Met polymorphism produces a nonconservative substitution of amino acids at codon 66 of the gene, involving a valine (Val) being replaced by a methionine (Met). The presence of a copy of the Met allele is associated with less activity‐dependent BDNF secretion, as well as abnormal BDNF localization. A number of behavioral and neuroimaging studies observed that Met homozygotes perform worse on verbal episodic memory tests as well as on visual sensory memory tests than Val homozygotes and that carriers of the Met allele activate the hippocampus less during memory encoding and retrieval, suggesting weaker memory trace formation in carriers of the Met allele.

The extracellular enzyme COMT is known to degrade DA in the synapses. In humans, COMT is mostly expressed in the PFC and thus has a direct influence on prefrontal DA level. The COMT Val158Met polymorphism, which is known to affect prefrontal DA levels and D1 receptor binding, influences cognitive processing in various tasks that depend on prefrontal function. Regarding memory performance, COMT Val158Met modulates the activity and connectivity of brain regions within the WM network. This effect is stronger with increasing age, contributing to an age‐related decline in memory performance. The relation between DA and WM depends on a person's baseline DA level and is thus characterized by an invertedU‐shape function: administration of DA increases WM performance in individuals with low WM capacity but decreases performance in those with high WM capacity. These differences likely reflect differences in baseline DA levels, with low DA levels in individuals with low WM capacity and high DA levels in those with high WM capacity, such that additional DA administration either optimizes the DA level or exceeds it, depending on a person's baseline DA. Thus, there is an optimum concentration of DA in the PFC to perform WM tasks. These findings demonstrate that individual differences in WM performance are genetically determined by DA level and modified by the COMT Val158Met polymorphism.

A number of animal studies and some human studies have shown that memory is further modulated by dynorphins. Dynorphins are members of the opioid peptide family that are located in the hippocampus, amygdala, hypothalamus, striatum, and spinal cord and preferentially bind to κ‐opioid receptors. Their functions are related to memory, learning, emotional control, pain, and stress response. Individuals with the minor dynorphin alleles rs1997794 and rs910080 have been observed to show better episodic memory performance than homozygote carriers of the major allele. Furthermore, carriers of the prodynorphin T allele at rs1997794 showed reduced fear extinction and a significantly diminished functional connectivity between amygdala and ventromedial PFC, demonstrating a role of dynorphin κ‐opioid receptor signaling in fear memory and extinction in humans.

In sum, differences in individual memory capacities seem to be significantly influenced by the ε4 allele of the ApoE gene, the BDNF Val66Met polymorphism, basic DA levels and the COMT Val158Met polymorphism, and minor alleles of the opioid peptide dynorphin.

Personality

Personality traits are individual differences in general patterns of thoughts, feelings, and behavior that form the core of an individual's nature. Although it is known that both genetic and environmental factors as well as interactions between them contribute to the development of one's personality in a complex manner, the stable core of a person's nature—the behavioral continuity that makes someone unique, recognizable, and predictable—is owned to over 80% to genetic factors (McGue, Bacon, & Lykken, 1993). In the following, we will provide an overview of the current knowledge regarding genetic influences on personality.

Extraversion and introversion are part of one‐dimensional continuum of the “big 5” personality traits. Extraversion is linked to positive emotionality and describes people who are outgoing and fun loving and who love to socialize, whereas introverts have lower social engagement and energy levels than extroverts and prefer to spend time alone. Whether someone is more extraverted or introverted seems is partly determined by variations in the BDNF Val66Met polymorphism and the COMT Val158Met polymorphism coding dopaminergic activity in the brain, as recent genome‐wide association studies revealed.

Neuroticism, the tendency to experience negative emotions, such as anger, anxiety, or depression, appears to be linked to a variety of genetic influences. This personality trait has been associated with low BDNF serum concentrations and variations in the BDNF Val66Met polymorphism as well as with interactions between BDNF Val66Met and the dopamine D2 receptor gene (DRD2)/ANKK1 and the serotonin transporter promoter polymorphism5‐HTTLPR. A meta‐analysis summarizing 26 genetic association studies confirmed a significant association between 5‐HTTLPR and neuroticism, demonstrating that individual differences in neuroticism are linked to serotonin transmission in the brain. Moreover, high neuroticism and low extraversion have been linked to several functional variants of the COMT gene, indicating an association of these two traits with dopaminergic activity.

Harm avoidance, a further personality trait that is characterized by excessive worrying and fear of uncertainty, has been found to be influenced by a combination of the BDNF Val66Met and the dopamine‐coding DRD2/ANKK1 TaqIa polymorphisms. Moreover, higher levels of harm avoidance in women have been associated with the neuropeptide oxytocin as well as with MAOA, an enzyme encoding the MAOA gene catalyzing serotonin, DA, and norepinephrine.

Neuroticism, harm avoidance, and low levels of extraversion belong to the anxiety‐related personality traits, which—in extreme form—may predispose individuals to develop psychopathological conditions. Meta‐analytic evidence on the serotonin‐coding 5‐HTTLPR polymorphism and psychiatric disorders suggests that the relationship between 5‐HTTLPR and anxiety‐related personality traits is mediated by hyperreactivity of the amygdala during the processing of emotions. Particularly the S allele of the 5‐HTTLPR polymorphism appears to be the “risk allele” for a variety of mood disorders, such as anxiety, depression, and bipolar disorder, putatively due to decreased transcriptional activity of the 5‐HTTLPR S allele. In contrast, increased transcriptional activity of the 5‐HTTLPR L allele has been associated with nicotine dependence and attention‐deficit hyperactivity disorder (ADHD). Not only the development of psychiatric disorders but also their treatment seems to be partially dependent upon the 5‐HTTLPR polymorphism: treatment responses in disorders such as posttraumatic stress disorder (PTSD), major depressive disorder, and alcohol dependence reportedly vary by 5‐HTTLPR allele, suggesting a significant influence of the 5‐HTTLPR polymorphism on treatment success.

A further personality trait describing how a person deals with feelings is alexithymia. Alexithymia characterizes individual differences in the ability to consciously experience and regulate one's emotions. The more alexithymic an individual, the more difficulty they will experience identifying, describing, and verbalizing their feelings to others. Similarly to anxiety‐related personality traits, alexithymia is linked to aberrant functioning and structure of the amygdala and other brain areas involved in emotion processing and thus constitutes a further risk factor for a range of psychiatric conditions. Preliminary evidence suggests that alexithymia may be linked to the serotonin polymorphism 5‐HTTLPR (with carriers of the L/L allele having significantly higher alexithymia levels than S/S and L/S carriers) and to the dopamine‐coding COMT Val108/158Met polymorphism (with carriers of the Val/Val genotype having significantly higher alexithymia levels than Met/Met or Met/Val carriers). Furthermore, an interaction between BDNF and the dopamine DRD2/ANKK1 gene has been reported to contribute to individual differences in alexithymia. However, these findings were based on rather small sample sizes and thus warrant replication in future research.

As opposed to alexithymia, which refers to one's own emotions, trait empathy describes individual differences in people's sensitivity to the feelings of others, that is, their capacity to share and understand other persons' feelings. Many studies have linked empathic abilities to oxytocin, a neuropeptide implicated in a wide range of social behaviors. Individuals homozygous for the G allele of OXTR SNP rs53576 exhibit greater empathy for others and show more activity in their own pain‐related brain areas when seeing others suffering. Moreover, cognitive empathy (the capacity to understand another's perspective or mental state) and affective empathy (the ability to respond with an appropriate emotion to another's mental state) have been linked to different SNPs of OXTR, suggesting on the one hand an involvement of several OXTR SNPs in empathy and on the other hand a genetically differential disposition for cognitive and affective empathic abilities. In addition, this disposition seems to be influenced by gender: more empathic concern for others, an aspect of affective empathy, appears to be significantly linked to OXTR SNP rs53576 in women, but in men, this association may be weaker or even absent. Moving beyond genetic association studies, treatment studies intranasally administering oxytocin indicated some promise of this neuropeptide in treating psychiatric symptoms involving deficits in social functioning, such as autism, social anxiety disorders, borderline personality disorder (BPD), and schizophrenia, possibly by increasing the saliency of social stimuli, thus helping social attunement. Besides oxytocin, other genes appearing to influence human empathic abilities are the BDNF Val66Met polymorphism, which correlates with self‐reported empathy; the serotonin transporter polymorphism 5‐HTTLPR, which has been linked to levels of emotional reactivity (affective empathy); and the dopamine D4 receptor gene (DRD4 exon 3 polymorphism), which has been related to cognitive empathy.

Impulsivity, antisocial behavior, aggression, and violence form a group of negative personality traits, which have been linked to the MAOA gene located on the X chromosome, giving rise to this gene being popularly referred to as the “warrior gene.” This term is based on repeated observations that the low‐activity MAOA genotype in men, causing MAO deficiency, is associated with offending behavior, conduct problems, and hostility and that male carriers of this genotype who experienced early abuse are more prone to exhibiting antisocial behaviors throughout their lifetime. A recent meta‐analysis on the 30‐base pair variable number of tandem repeats of MAOA‐uVNTR confirmed the link between the MAOA gene and antisocial behavior in humans. Regarding the question whether the effect of the MAOA gene on antisocial and aggressive behavior is driven by modulations in the DA or serotonin system, recent research suggests an inconclusive role of DA release in relation to MAOA. In contrast, a disrupted serotonergic system linked to the low functioning MAOA genotype has been concluded to predispose individuals to aggressive behavior by increasing impulsive reactivity to negative affect.

The important role of the serotonin system in impulsivity, antisocial behavior, and aggression is corroborated by other studies investigating the relationship between serotonin and psychiatric disorders marked by such behaviors. Several studies showed that the serotonin5‐HTTLPR polymorphism predisposes individuals not only to mood disorders such as anxiety and depression as addressed above but also to psychiatric problems involving impulsivity and aggressive behaviors, such as BPD. Children and teenagers in the ages of 9–15 years, who are carriers of the two S alleles of the serotonin 5‐HTTLPR polymorphism, have the highest levels of BPD traits, even when controlling for depressive symptoms, providing evidence for a developmental etiological risk for BPD among youth. Such findings were replicated in adults with BPD, showing the carriers of the two S alleles of 5‐HTTLPR suffered from the most severe affective symptoms of BPD.

In summary, research has linked a number of candidate genes to personality traits and the risk for developing psychiatric illness. However, no known gene is either necessary or sufficient to produce mental disease. Instead, there are many susceptibility genes with small effects, each increasing an individual’s risk of illness to a small percentage. This is illustrated, for instance, by a recent genome‐wide association study of 36,989 cases by the Schizophrenia Working Group of the Psychiatric Genomics Consortium, which found that 108 genetic loci were involved in the heritability of schizophrenia. Moreover, genes interact with each other and with environmental factors, and phenotypes are thus more than the sum of independent genetic and environmental factors. Certain life events may interact with brain vulnerabilities created by particular genes to produce behavioral patterns. For instance, a recent study aiming to identify genetic contributions to delinquency in teenagers found that such behaviors were not linked to one specific gene and also not to gene × gene interactions, but instead to four‐way interactions between three genes (BDNF Val66Met, 5‐HTTLPR, MAOA) and the environmental risk factors family conflict and sexual abuse, suggesting that genotypes per se do not confer risk for delinquent behaviors of the teenagers but rather alter their susceptibility to environmental factors. Importantly, this was not only true for negative but for positive environmental factors as well: interactions between the same genes and a positive child–parent relationship were associated with the lowest delinquency scores, highlighting the power of a positive environment on human behavior and demonstrating that it is ultimately the interaction with the environment a person is surrounded with that eventually determines their behavior, despite the presence of potential risk genes.

Conclusion

Despite their limitations, candidate gene and genome‐wide association studies have demonstrated their potential in helping scientists understand the effects of changes in our genetic endowment on brain functions and systems on various aspects of human cognition and behavior as well as their potential as risk factors for a range of diseases. With the costs of full genomic sequencing becoming more and more affordable, the collection of big sets of genomics data and their integration with behavioral, environmental, clinical, and functional and structural neuroimaging data will become possible in the near future. Together with modern technologies of “big data” processing, analysis, sharing, and visualization, such future studies will enable us to move to another level of understanding the highly complex patterns of interactions between multiple genes and between our genetic disposition and the environment in which we grow up and surround ourselves with. Understanding the complex patterns of genetics and behavior will provide indispensable knowledge regarding the workings of the human mind and the mechanisms underlying our mental health.

Author Biographies

Mikhail Votinov is a postdoctoral researcher at Research Center Jülich (Germany) in the Institute of Neuroscience and Medicine (INM‐10). He received his PhD in neuroimaging and cognitive neuroscience from Kyoto University (Japan), Faculty of Medicine. His research investigates genetic and hormonal influences on the neural mechanisms underlying reward processing, decision making, and social interactions.

Katharina Sophia Goerlich is a postdoctoral researcher at RWTH Aachen University (Germany) in the Department of Psychiatry, Psychotherapy, and Psychosomatics. She received her PhD in neuropsychiatry from the University of Groningen (Netherlands), Faculty of Medical Science. Her research investigates the neural mechanisms underlying the processing of social and emotional information in the brain and in what way these mechanisms are influenced by personality differences and psychopathology.

Reference

McGue, M., Bacon, S., & Lykken, D. T. (1993). Personality stability and change in early adulthood: A behavioral genetic analysis. Developmental psychology, 29(1), 96.