DRD4 and DAT1 in ADHD: Phenotype to pharmacogenetics.

Darko Turic1, James Swanson2 & Edmund Sonuga-Barke 1,3*

1. Institute for Disorder of Impulse & Attention, School of Psychology,

University of Southampton.

2. Child Development Centre, University of California, Irvine.

3. Department of Experimental Clinical & Health Psychology, Ghent

University.

* Correspondence to Edmund Sonuga-Barke, Institute for Disorder of

Impulse & Attention, School of Psychology, University of Southampton,

Southampton, SO17 1BJ. UK. ejb3@soton.ac.uk.

Abstract

Attention deficit/hyperactivity disorder (ADHD) is a common and potentially

very impairing

neuropsychiatric disorder of childhood that is associated with numerous

behavioural problems. Statistical genetic studies of twins have shown ADHD

to be highly heritable, with the combination of genes and gene by

unmeasured environment interactions accounting for 80% of phenotypic

variance". The initial molecular genetic molecular studies based on candidate

genes were remarkably success. For these studies DRD4 and DAT1 genetic

variants were initially identified as good candidate genes because of the

efficacy of dopaminergic compounds in the treatment of ADHD. Case-control

and family-based association studies provide strong evidence for the role of

variants of DRD4 and DAT1 in the pathogenesis of ADHD, although effect

sizes for both genes are small. Evidence relating DRD4 and DAT1

genotypes to ADHD endophenotypes, or implicating them in gene x

environment interactions, is so far weak and inconsistent. DRD4 and

DAT1 polymorphisms are interesting candidates for phamacogenetic

studies because of the primary dopaminergic mechanism of action of

stimulant drugs

that are considered to be DA agonists. The recent application of non-

candidate gene strategies (e.g. genome wide association scans) has failed to

identify additional genes with substantial genetic main effects. This is the

usual pattern observed for most other physical and mental disorders

evaluated with current state-of-the-art methods, and the significance and

possible reasons for this are discussed.

INTRODUCTION

Attention deficit/hyperactivity disorder (ADHD) is a common psychiatric

disorder of childhood affecting around five percent of the population

(Polanczyk, de Lima et al. 2007). It is characterised by an early onset and

persistent pattern of inattention, impulsivity, and hyperactivity symptoms. The

condition is associated with several co-morbid conditions (e.g., disrupted peer

and family relationship) and adverse outcomes that emerge with age (e.g.,

educational failure and antisocial behaviour). It has an early onset and is

most frequently recognized in middle childhood (Taylor & Sonuga-BarkeLasky

Su, Anney et al, 2008). There is an overrepresentation of boys over girls by

approximately 3:1 (Reiff and Stein 2003). ADHD can persist into adulthood

and increases the risk for anti-social personality disorder (Mannuzza, Klein et

al. 1989), later criminality (Satterfield, Hoppe et al. 1982; Satterfield, Faller et

al. 2007) as well as drug and alcohol misuse (Barkley 1998; Barkley, Fischer

et al. 2004).

Pharmacological, neurobiological and genetic studies support the notion that

ADHD has a neuro-developmental basis with a strong genetic and non-

genetic components components (see Swanson, Kinsbourne, et al, 2008),

implicating neurotransmission dysregulation within brain circuits underpinning

cognition and motivation (Swanson, Kinsbourne et al. 2007; Sonuga-Barke,

2005). Disruption of multiple neurotransmitters systems has been proposed.,

but However, the primary focus has been on the catecholamines dopamine

(DA) and norepinephrine. While oOthers have focused on norepinephrine

(see Plitska and McCracken, 1996 or Arnstein and Li, 2005), but our focus

here here we will focus hereis on evidence that variation and disruption of the

dopamine DA system contributes to the aetiology and response to treatment

of ADHD.

1. DOPAMINE DYSREGULATION IN ADHD

Dopamine neurotransmission: The catecholamine dopamine (DA)DA is a

key

neurotransmitter in the biology of a wide range of brain processes (Seeman

and Madras 1998; Schultz 2002; Schultz 2007;). It is central to the control of

movement Lees, Hardy et al. 2009), cognition (Aultman and Moghaddam

2001; Floresco and Phillips 2001), reward (Volkow, Wang et al. 2009),

emotional and motivational responses (Wender 1975; Pezze and Feldon

2004; Hranilovic, Bucan et al. 2008) including the experience of pleasure and

pain in response to positive and negative environmental events (e.g., Giuliano

and Allard 2001; Pecina and Berridge 2005; Hyman, Malenka et al. 2006).

DA is synthesized from the amino acid tyrosine, which is first converted to L-

dihydroxyphenylalanine (L-DOPA), and then to DA by the enzyme DOPA

decarboxylase. DA neurons are clustered in several mid brain regions,

including substantia nigra and the ventral tegmentum (Bjorklund and Dunnett

2007). (There are both parallel (Alexander et al., 1990; Middleton and Strick,

2002) and converging pathways in cortico-basal ganglia loops (Takada et al.,

1998; Bar-Gad and Bergman, 2001; Haber, 2003). It appears that the parallel

organization is not completely maintained through trans-thalamic circuits

(Kolomiets et al., 2001; McFarland and Haber, 2002) and that thalamic nuclei

may modulate information processing between segregated circuits (Castro-

Alamancos and Connors, 1997). These project to large parts of the brain via

three major pathways: The nigro-striatal pathway extends from substantia

nigra to caudate nucleusputamen. It plays an essential role in voluntary

movement (Barbeau 1974). The meso-cortico-limbic pathway projects from

ventral tegmentum to mesolimbic and meso-cortical regions. It is associated

with cognition, reward and emotion processing (Mogenson, Jones et al. 1980;

Wise 2004; Wise 2004). DA within these pathways have been shown to

modulate functionally and structurally segregated cortico-basal ganglia loops

(Alexander et al., 1990; Middleton and Strick, 2002; Takada et al., 1998; Bar-

Gad and Bergman, 2001; Haber, 2003). These circuits are involved in well-

defined brain networks involved in the processes of attention as well as

motivation, and disruption of either or both contribute to the aetiology of

ADHD (see Sonuga-Barke, 2002; Volkow, Wang et al, 2009).

TSuchhe parallel organization is now thought to not completely

maintainedcomplete (Kolomiets et al., 2001; McFarland and Haber, 2002) with

thalamic nuclei allowing the passage of signals across different circuits (Haber

& Calzavra, 2009). .

In addition there is aThe tubero-infundibular pathway that plays a role in

neuronal control of the hypothalmic-pituatory endocrine system (Ben-

Jonathan et al., 2002). These pathways are involved in well-defined brain

networks involved in the processes of attention as well as motivation, and

disruption of either or both contribute to the aetiology of ADHD (see Sonuga-

Barke, 2002; Volkow, Wang et al, 2009).

DA is released into the synaptic cleft by action potentials via a calcium

dependent mechanism. Calcium influx triggers fusion of the neurotransmitter

vesicles with the pre-synaptic membrane. DA is then released into the

synaptic cleft from where it disperses and binds to postsynaptic receptors.

Receptors bind neurotransmitter molecules and open nearby ion channels in

the postsynaptic cell membrane. This alters the local trans-membrane

potential of the cell. DA exerts its effects by binding to DA receptors which

are functionally categorised into two families: D1-like (stimulatory) and D2-like

(inhibitory). Members of the D1 family (D1/D5) couple to Gs class of G

proteins and activate adenylyl cyclise. D2 type receptors (D2/D3/D4) couple to

Gi protein which inhibits the production of cAMP (Callier, Snapyan et al.

2003). Pre-synaptic receptors (auto-receptors) monitor extracellular DA levels

and modulate the impulse dependant release and synthesis of DA (Altar,

Boyar et al. 1987). Blockade of these receptors leads to an increased

production, and pre-synaptic release, of DA, . Swhile their stimulation causes

the opposite effect (Marinelli, Rudick et al. 2006; see below for a discussion of

the role of pre-synaptic receptors in the action of methylphenidate). DA

clearance from the synaptic cleft is regulated by the products of three genes:

DA transporter (SLC6A3/DAT1), Mono-amine Oxidase-A (MAO-A) and

Catechol-O-Methyl Transferase (COMT). DAT1 is responsible for the rapid

uptake of DA from the synaptic cleft while MAO-A and COMT are involved in

DA catabolism (Longstaff, 2000).

Non-genetic evidence for DA dysregulation in ADHD

Neuro-chemical studies support a role for neurotransmitter dysregulation in

ADHD pathophysiology (Zametkin and Liotta 1998). Serotonergic,

noradrenergic and glutamatergic pathways have all also been implicated

(Gizer, Ficks et al. 2009). Initial interest in DA in ADHD came from the long

standing observation that psycho-stimulant medication such as

methylphenidate, assumed to alter the activity of this neuro-transmitter,

provided an effective treatment for many ADHD patients (Wender 1975).

Since then methylphenidate has been shown to inhibit the activity of the DA

transporter and increase extra-synaptic levels of DA (Volkow, Wang et al.

2004; Volkow, Wang et al. 2005). There is evidence that it has little effect on

pre-synaptic

DA release (Patrick, Caldwell et al. 1987) but this is has been questioned by

(Seeman and Madras 2002). Another psychostimulant amfetamine, has

been shown to increase DA levels by extenuating (affectingmodifying) its

release (Fan, Xu et al. 2009). It interacts with DA transporters to promote DA

efflux from the presynaptic neuron into the synaptic cleft (Kuczenski and

Segal 1975;

Kuczenski and Segal, 1997).

Other evidence in support of the DA dysregulation hypothesis of ADHD

comes from two main sources (other than the genetic evidence described

later). First, ADHD animal models display dysregulation of DA function.

(Giros, Jaber et al. 1996; Xu, Moratalla et al.1994; Granon, Passetti et al.

2000; Accili, Fishburn et al. 1996; Leo, Sorrentino et al. 2003). The earliest

animal model was developed by administration of 6-hydroxydopamine to

neonatal rats that results in depletion of DA (Shaywitz, Yager, Klopper, 1976).

After treatment with 6-OHDA the activity of animals is initially greater than that

of controls. This but then declines , as a result of profound depletion of brain

dopamineDA. Genetic models also provide evidence. The ADHD type

characteristics of the spontaneously hypertensive rat (SHR; Mook, Jeffrey et

al. 1993; Sagvolden 2000; Wong, Buckle et al. 2000; Wyss, Fisk et al. 1992)

is reduced by DA agents (Boix, Qiao et al. 1998; Myers, Musty et al. 1982),

while those of the . The hyperactivity of the Naples high-excitability/low

excitability (NHE/NLE) strain is associated with larger DA neurons and altered

DA functioning in limbic and cortical areas of forebrain (Gonzalez-Lima and

Sadile 2000; Papa, Sellitti et al. 2000; Sadile, Lamberti et al. 1993; Sadile,

Pellicano et al. 1996). In the case of the The ADHD features of the coloboma

mouse, these are associated with altered activity within specific surface

proteins that mediate the process of docking and fusion of DA synaptic

vesicles to the pre-synaptic plasma membrane (Hess, Collins et al. 1996).

This results from a 2-cM deletion of mouse chromosome 2 containing several

genes including SNAP-25. These effects can be reversed by either transgenic

insertion or stimulant medication (Steffensen, Henriksen et al. 1999).

Second, neuro-chemical imaging studies using Positron Emission

Tomography (PET) and Single Photon Emission Computed Tomography

(SPECT) suggest altered regulation of striatal DAT DA transporter levels.

Studies vary greatly

in their methodological rigour and, perhaps because of this there are

inconsistencies between them (Gonon 2009; Volkow et al., 2009). On the

one hand, upregulation of striatal DA transporter densities, consistent with

lower levels of extracellular DA, have been reported in studies with small

samples of mostly methylphenidate treated cases (Dougherty, Bonab et al.

1999; Krause, Dresel et al. 2000; Larisch, Sitte et al. 2006; Cheon, Ryu et al.

2003). Other studies with larger sample sizes found no evidence of altered

DA transpoter activity (van Dyck, Quinlan et al. 2002). While the largest and

methodologically most robust study with a large sample of treatment naïve

adults with ADHD but without a history of comorbid SUD (Volkow, Wang et al.

2009) reported down-regulation of striatal DAT consistent with higher levels of

extra-cellular DA. This has been confirmed in recent study in drug naïve

ADHD patients (Hesse, Ballaschke et al. 2009) finiding decreased striatal DA

transporter availability in the basal ganglia. Given the methodological

strength of these most recent findings studies with drug naïve patients it

seems likely

that initial reports suggesting DAT upregulation were due to the

methodological

limitations of the study. Leaving aside their directionThe altered levels of DA

transporters are

difficult to interpret given the reciprocal and adaptive nature of the relationship

between DA transporter densities and DA synthesis and release (Madras,

Miller et al. 2002; Volkow, Wang et al. 2009). Likewise the DAT DA

transporter blocking effect

of psycho-stimulants could be differently interpreted as either; i) a

compensation for the deficit of DA (Swanson and Volkow 2002) or; ii) by the

modulation of synaptic activity through dopamine (D2) auto-receptors

(Seeman and Madras 1998).

2. GENETICS OF ADHD: BACKGROUND

Research has consistently shown a strong genetic component in ADHD

etiology. Twin studies suggest a heritability between 0.7 and 0.8 (Stevenson

1992; Swanson, Sergeant et al. 1998; Biederman and Faraone, 2005). These

effects are similar for boys and girls (Nadder, Silberg et al. 1998; Saudino,

Ronald et al. 2005). The non-heritable component appears to be attributable

almost exclusively to non-shared environmental influences (Thapar,

Harrington et al. 2001; Larsson, Larsson et al. 2004; but also see Poderman

et al, 2009 for a discussion of “contrast” effects in twin studies). Although,

heritability estimates themselves do encompass the influence of the

environment through gene-environment interaction and correlation (Rutter,

2007; see below for discussion in relation to DAT1 and DRD4).

There are two commonly used approaches in molecular genetic

studies: candidate gene approaches based on theoretical involvement of

neuron-biological pathways leading to specific hypotheses; and non-

hypothesis driven genome-wide approaches that consider all genes as

equally plausible candidates. Candidate gene approaches use either case-

control or family based (e.g., linkage) association designs. In case-control

studies the frequency of candidate alleles or genotypes are compared in

ADHD cases and controls. Family based approaches look for patterns of

genetic transmission disequilibrium (Spielman et al, 1993) across generations

within affected families to examine whether the probability of transmission of

an allele from parents to an affected offspring differs from the expected

Mendelian pattern of inheritance. There are pros and cons to these

approaches. Family based studies have an advantage over case-control

studies as they are designed to be immune to population stratification

(Spielman and Ewens, 1996). , Hhowever the use of transmission

disequilibrium test (TDT) employed in family based studies is subject to

selection effects due to missing parents and genotyping errors (Clayton, 1999;

Weinberg, 1999). Morton and Collins (1998) argue that stratification, which

reduces the accuracy and power of the case-control design, is a problem only

under rare circumstances while the impact of

genotyping errors in family based approaches may have been underestimated

(Mitchell AA, Cutler DJ, & Chakravarti A, 2003). Genome wide non-

hypothesis based approaches (see Risch and Merikangas, 1996) have also

employed association (GWAS) and linkage designs models. In genome wide

linkage studies related individuals, either siblings or those in extended

pedigrees, are studied in an attempt to localize chromosomal regions which

may harbour genes influencing a trait by examining the familial co-segregation

of the phenotype and genetic markers (Lander and Schork 1994). It is

assumed that GWAS designs are more powerful in detecting common alleles

with small effects than linkage approaches (Risch and Merikangas 1996).

GWAS

studies require very large numbers of markers, (i.e., perhaps even millions;

see

Clark and Li, 2007), in order to cover whole genome.

In both candidate gene and genome wide approaches the ADHD

phenotype can be characterized as a diagnostic category or a quantitative

trait (Fisher RA, 1918). The identification of a quantitative trait loci (QTL)s has

been interpreted as the operation of multiple genes of varying effect so that,

broadly speaking, a continuous trait (rather than a diagnostic category) can be

influenced by a few oligogenes with a moderate effect on the phenotype, or by

many polygenes each with very small effect, or by a combination of the two.

While most studies have defined the ADHD phenotype in terms of diagnostic

categories categories, measures of activity, impulsivity and attention are

continuously distributed in the general population (Mill, Xu et al. 2005Pinto

and Tryon 1996; Burns, Walsh et al , 1997) and researchers have argued for

the use of dimensional approaches could in the ADHD field (Hudziak,

Achenbach et al. 2007). Although statistically powerful (Curran, Mill et al,

2001Asherson, ) and despite the fact that they have been successfully applied

both in human and animal behavioural studies (e.g Spence, Liang et al.

2009), QTL approaches have so far attracted relatively little interest in the

ADHD field. This is probably because the quantification of ADHD when

measured using common rating scales focuses only on the severity of

psychopathology, rather than fully dimensional and does not capture the

entire range of the underlying dimensions of attention/inattention and

reflectivity/impulsivity (see Cornish, Manly et al. 2005; Polderman, de Geus et

al. 2009; Swanson, Wigal et al. 2009)

The first ADHD genome scan identified four regions (5p13, 10q26,

12q23, and 16p13) showing some evidence of linkage with LOD scores > 1.5

(Fisher, Francks et al. 2002). A recent meta-analysis of seven ADHD linkage

scans (Bakker, van der Meulen et al. 2003; Ogdie, Macphie et al. 2003;

Arcos-Burgos, Castellanos et al. 2004; Hebebrand, Dempfle et al. 2006;

Asherson, Zhou et al. 2008; Faraone, Doyle et al. 2008; Romanos, Freitag et

al. 2008) identified the genomic region on chromosome 16, between 16q21

and 16q24 as most consistent linkage evidence across the studies (Zhou,

Dempfle et al. 2008). Ten other regions on chromosomes 5, 6, 7, 8, 9, 15, 16,

and 17 had nominal significant levels for linkage (Zhou, Dempfle et al. 2008).

Two genome wide linkage studies in humans employing QTL methods have

identified linkage to chromosomes 1p36 and 3q13 for ADHD traits (Doyle,

Ferreira et al. 2008; Zhou, Dempfle et al. 2008). Interestingly the

chromosomal region 1p36 overlaps with a dyslexia QTL raising a possibility

that pleiotropy might play role in the genetic origins of ADHD and dyslexia

(Zhou, Dempfle et al. 2008). Initial GWAS studies with hundreds of thousands

of markers and thousands of patients have so far failed to identify genome

wide significant association between ADHD and these markers (Neale et al.,

2008; Hong, Su et al. 2008; McCarthy, Abecasis et al. 2008). See Dermitzakis

and Clark (2009); Clark and Li (2007) for a more general discussion of why

GWAS approaches have not been more productive).

In contrast candidate gene approaches have been more successful.

The first two evaluated functional variants of DA genes and showed

association of ADHD with DAT1(Cook, Stein et al. 1995) and DRD4 (LaHoste,

Swanson et al. 1996). Since then other candidates within the DA system (e.g,

Payton, Holmes et al. 2001) and other neurotransmitter systems (e.g., Hawi,

Dring et al. 2002; Turic, Langley et al. 2005) have been proposed but few of

these have produced robust and replicable effects. Several meta-analyses for

single and multiple loci have been published that review this data (e.g.

Faraone, Perlis et al. 2005; Purper-Ouakil, Wohl et al. 2005; Yang, Chan et al.

2007).

3. ADHD AND THE DOPAMINE RECEPTOR D4 GENE

DRD4, its distribution and functional polymorphisms: DA receptor D4

(DRD4) is a member of D2 class of receptors. The D2-like receptors regulate

several signalling events including inhibition of adenylate cyclase, stimulation

of arachidonic acid release and modulation of potassium channels (Jaber,

Robinson et al. 1996; Oak, Oldenhof et al. 2000; Neve, Seamans et al. 2004;

Tarazi, Zhang et al. 2004). The human D4 receptor gene maps to

chromosome 11p15.5. It consists of four exons and encodes a putative 387-

amino acid protein with seven trans-membrane domains (Van Tol, Bunzow et

al. 1991). DRD4 is highly expressed in pyramidal neurons and inter-neurons

in prefrontal cortex. There are lower concentrations in basal ganglia,

hippocampus and thalamus (Mrzljak, Bergson et al. 1996; Ariano, Wang et al.

1997; Gan, Falzone et al. 2004; Tarazi, Zhang et al. 2004; Noain, Avale et al.

2006).

Genetic variations in the DRD4 sequence have been examined in

relation to various neuro-psychiatric disorders. These have focused on a

variable number tandem repeat (VNTR) polymorphism in exon 3, consisting of

a 48-bp repeat unit. This codes for an amino-acid sequence located in the

third cytoplasmic loop of the receptor, thought to be involved in G-protein

coupling (Van Tol, Wu et al. 1992). In the human population, this VNTR

displays a high degree of variability with multiple and nucleotide variation

within each repeat (Chang, Kidd et al. 1996; Ding, Chi et al, 2004; Lichter,

Barr et al, 1993). The most common repeat variants are the 4R, 7R and 2R

alleles respectively. The frequency of these alleles varies widely among

different ethnic groupings

(Ding, Chi et al. 2002). The 7R allele, for example, has an extremely low

prevalence in Asian populations (<2%) yet a high frequency in native

populations in the Americas (~48%;Chang, Kidd et al. 1996). As yet there is

no commonly accepted explanation of this variability at the DRD4 locus. The

common and probable ancestral allele has four repeats (4R) originating ~

300,000 years ago, whereas the 7R allele, often associated with psychiatric

disorders, is ‘younger’ by up to 10 times (Wang, Ding et al. 2004; Wang,

Kodama et al. 2006).The 7R allele may have arisen as a rare mutational

event and then become a high frequency allele through positive selection

(Ding, Chi et al. 2002) at a time (the upper Paleolithic) of the major expansion

of human population (Chen, Burton et al, 1999). In this way individuals with

novelty seeking personality traits may have driven the expansion of the 7R

variant (Ding, Chi et al. 2002) or it may have conferred a reproductive

advantage in male-competitive societies (Harpending and Cochran 2002). In

China, the loss of the 7R may have been due to selective reproduction of

males without the 7R allele (ref; 4). At the same time there appears to be

selective forces working to balance these processes as the prevalence of the

7R allele is probably near fixation point (ref; 5).

The neuro-functional significance of the DRD4 7R allele is not fully

understood. In vitro studies indicate that the sensitivity to DA of the 7R allele

is half that of the 2R and 4R variants (Van Tol, Wu et al. 1992; Asghari,

Sanyal et al. 1995). Moreover, DRD4 mRNA is distributed in prefrontal cortex

(Primus, Thurkauf et al. 1997; De La Garza and Madras 2000; Noain, Avale et

al. 2006) but also to a lesser extent in parietal and temporal lobes, cingulate

cortex, cerebellum (Primus et al, 1997; Mrzljak et al, 1996). It is found in the

basal ganglia although its density relative to DRD2 is low (De La Garza and

Madras 2000). This suggests it plays a role in cognitive and also potentially

motivational processes (Dolan 2002; Durston, de Zeeuw et al. 2009) Crucially

DRD4 and DAT1 seem not to be co-localized within brain regions (unlike

DRD2 and DAT1) suggesting a different role for these two DA receptors (De

La Garza and Madras 2000). Synthesis and clearance of DA are elevated in

mice lacking the DRD4 gene (Rubinstein, Phillips et al. 1997). Also, mice

lacking a functional DRD4 receptor display cortical hyper-excitability

(Rubinstein, Cepeda et al. 2001; Avale, Falzone et al. 2004) and

hypersensitivity to single administrations of alcohol, methamphetamine, and

cocaine (Rubinstein, Phillips et al. 1997).

DRD4 in ADHD; categorical diagnoses and quantitative traits: The

developing understanding of the neuro-functional significance of DRD4 7R

has led to the investigation of its association with disorders with a putative DA

basis. In relation to ADHD, therefore most studies have focused on the 7R

polymorphism. An additional 120-bp duplication polymorphism located in the

5’ flanking region of DRD4 (Seaman, Fisher et al. 1999) has also been

studied recently (e.g., Kereszturi, Kiraly et al. 2007) as well as a SNP (-521

C/T; rs1800955) in the same region (e.g., Yang, Jang et al. 2008). The

association between the 7R allele DRD4 polymorphism and ADHD is well

replicated. However the findings are not completely consistent and the

absolute size of the effects are small although relative to the maximum size

possible if all cases had the allele (which is limited by the allele proportion in

the population), in some ethnic groups it may be considered large (see Grady

et al, 2005). (; i.e., if the allele probability is .20 in the population, then the

maximum is 1/.2 = 5, and 1.9/5 is about 40%.). In their groundbreaking study,

LaHoste, Swanson et al. (1996) first reported the association between DRD4

7R and ADHD. Many studies have followed this lead and the first meta-

analysis of this association was published in 2001 (Faraone, Doyle et al.

2001) including both family-based (14 studies, 1665 probands) and case–

control studies (8 studies, 1266 children with ADHD and 3068 controls). This

gave an odds ratio of 1.9 for case-control studies (95% confidence interval =

1.5–2.2, p < 0.001) and 1.4 for family-based studies (95% confidence interval

= 1.1–1.6, p = 0.02). Five more meta/pooled analyses of the 7R and ADHD

have been published. All of them have demonstrated a significant n

association although the effect size has reduced in size as more studies have

been conducted and the total sample size has increased (Maher, Marazita et

al. 2002; Faraone, Perlis et al. 2005; Wohl, Purper-Ouakil et al. 2005; Li,

Sham et al. 2006; Gizer, Ficks et al. 2009). The most recent meta-analysis

showed a fixed effects significance of p<0.00001 with evidence of significant

heterogeneity between studies (Gizer, Ficks et al. 2009). In contrast to the 7R,

the 4R allele may confer a protective effect (OR = 0.9, 95% CI 0.84–0.97; Li,

Sham et al. 2006).

Several studies have examined DRD4 in relation to ADHD as a quantitative

trait. Curran, Mill et al. (2001) first reported association between the DRD4-7R

and ADHD-trait scores. Lasky-Su, Lange et al. (2008) found evidence for

association between two SNPs in the promoter region of DRD4 and the

quantitative phenotype (mainly inattentive) generated from the ADHD

symptoms. In contrast (Mill, Xu et al. 2005) and (Todd, Neuman et al. 2001)

failed to find evidence for association between DRD4 and ADHD trait

symptoms in general population. None of these studies used a measure the

full range of attentional abilities in the population and this could account for

negative results (see Swanson et al., 2009).

DRD4 and putative ADHD endophenotypes: Endophenotypes are

conceptualised as “sitting ‘between”’ genes and the clinical expression of the

disorder (Gottesman and Gould 2003). To be of value in genetic studies they

should be heritable, co-segregate with a psychiatric illness, yet be present

even when the disease is not (i.e. state independent), and be found in non-

affected family members at a higher rate than in the population (Gottesman

and Gould 2003). Endophenotypes are postulated to be influenced by fewer

genes than the clinical phenotype and consequently the size of the effects of

genetic loci contributing to endophenotypes is postulated to be larger than to

disease susceptibility. The fewer the genes that give rise to an

endophenotype, the better the chances of revealing their genetic mode of

action (Gottesman and Gould 2003). The concept has been controversial with

the suggestion that genetic effects are no greater in those studies employing

endophenotypes than those using standard clinical phenotypes (Flint and

Munafo 2007). There is a range of candidate endophenotypes in ADHD

(Willcutt, Doyle et al. 2005). The best evidence has been found in relation to

response inhibition (e.g. Slaats-Willemse, Swaab-Barneveld et al. 2003;

Rommelse 2008), temporal processing, (e.g. Bidwell, Willcutt et al. 2007),

verbal and visuospatial working memory , (e.g. Rommelse 2008) and delay

aversion (Bitsakou, Psychogiou et al. 2009). A number of recent studies have

found associations between DRD4 7R and performance on putative

endophenotypes of ADHD, although the effects are inconsistent (Kebir,

Tabbane et al. 2009). The first study of this sort in ADHD was conducted by

(Swanson, Oosterlaan et al. 2000) who demonstrated the then seemingly

paradoxical effect that in a small ADHD sample the cases with the 7-present

genotype showed better neuropsychological performance (faster and less

variable reaction time on 3 tasks) than those with the 7-absent genotype. This

direction of finding has been replicated (Manor, Tyano et al, 2002; Langley,

Marshall et al, 2004) although some studies have also shown DRD4 7R ed it

be as related to worse performance (Waldman 2005). The association

between DRD4 7R and neuropsychological performance is not task specific

but the strongest and most consistent effects seem to be in relation to high

reaction time variability and the absence of 7R (Kebir, Tabbane et al. 2009).

There has also been some evidence for altered speed of processing

(Waldman 2005). and cognitive impulsiveness on non-reaction tasks in 7R

carriers (Langley, Marshall et al. 2004). However, there is no but no effect of

genotype on response inhibition (Langley, Marshall et al. 2004)

DRD4 and gene-environment interactions: Results of behavioural genetic

studies are consistent with a role for environmental factors in ADHD and in

personality characteristics in general (see Sheese, Voelker et al. 2007).

Gene-environment interaction (GxE)) has been an increasing focus of study.

Here specific gene variants are shown to only exert a risk effect on disorder if

they are accompanied by exposureed to a particular environmental risk factor

(Rutter and Silberg 2002; Moffitt, Caspi et al. 2005). In relation to ADHD

these studies can be divided up into two sortstypes: Those focusing on the

role for

pre- and perinatal physical environmental risk factors (e.g., maternal smoking

and alcohol consumption during pregnancy (e.g. Brookes, Mill et al. 2006) and

those focusing on the post-natal social environment (e.g., expressed emotion

and social deprivation) ; (Weindrich, Laucht et al. 1992). There have been a

small number of replicated effects for GxE with DRD4 specifically and the

results are currently unconvincing; but this may be due to insufficient

statistical power in studies. Neuman, Lobos et al. (2007) reported an

interaction between maternal smoking during pregnancy and the 7R allele but

Langley, Turic et al. (2008) failed to replicate this. Other DRD4 7R GxE

findings include effects of season of birth (Seeger, Schloss et al. 2004). DRD

7R has also been shown to moderate the effects of parenting on externalizing

behavior including ADHD (Bakermans-Kranenburg, Van Ijzendoorn et al.

2008; Sheese, Voelker et al. 2007).

4. ADHD AND THE SLC6A3/DAT1 GENE

DAT1, its distribution and functional polymorphisms: The DA transporter

is a plasma membrane protein that belongs to the large family of the Na+/Cl-

dependent transporters. It is responsible for terminating neurotransmission by

rapid reuptake of DA into pre-synaptic terminals (Amara and Kuhar 1993). It

has been shown to control the intensity and duration of DA neurotransmission

by resetting the DA concentration in the extra-cellular space (Gainetdinov,

Jones et al. 1998; Frazer, Gerhardt et al. 1999). In situ hybridization and

immunochemistry studies have shown that DAT1 mRNA is primarily present

in DA-synthesising neurons of the substantia nigra and ventral tegmentum al

area (VTA) and that the corresponding protein coincides with DAergic

innervation of regions including ventral mesencephalon, medial forebrain

bundle and dorsal and ventral striatum (Ciliax, Heilman et al. 1995; Freed,

Revay et al. 1995). The human DAT1 gene maps to chromosome 5p15.3.

Sequence analysis of the 3’UTR of this gene revealed a variable number of

tandem repeat (VNTR) polymorphism with a 40-bp unit repeat length, ranging

from 3 to 11 repeats (Vandenbergh, Persico et al. 1992). In humans the 9R

and 10R are most common (Mitchell, Howlett et al 2000). Reporter gene

studies (Fuke, Suo et al. 2001) and studies of RNA expression in human

tissues (Mill, Asherson et al. 2002) have shown that expression is significantly

higher for the 10R than for other alleles suggesting this variant may be

functional. However Miller and Madras, (2002) found greater gene expression

for vectors containing the 9R sequence and others (Greenwood and Kelsoe

2003) demonstrating that neither the 9R or the 10R allele had an effect on

transcription. Furthermore, a brain imaging study (Heinz, Goldman et al.

2000) showed higher density of striatal DAT1 in the 10R homozygotes

compared with the 9/10 genotype, but another in vivo experiment yielded

conflicting results showing that the 9R carriers (9/9 homozygotes and 9/10

heterozygotes) had significantly higher striatal DAT1 availability (van Dyck,

Malison et al. 2005). However, the density of DAT is not fixed. Turnover of

DA transporter protein takes about two days (Kimmel, Carroll et al. 2000), and

plasticity has been documented – e.g., the effects of drugs on DA transporter

density has been established in studies of cocaine (Xia, Goebel et al. 1992)

and methylphenidate (Volkow et al, 2009]. In as much as the brain “strives for”

biochemical equilibrium, the impact of exposure to high levels of synaptic DA

is thought to result in a compensatory increase in DAT to keep DA levels in a

narrow range (1). Thus, exposure to stimulants that block DA transporters

and increase synaptic DA are thought to increase the density of DA

transporters. However, this must be measured when the drugs are not

present in the brain, since occupancy of DA transporters would interfere with

estimates of DA transporter density.

DAT1 in ADHD; Categorical diagnoses and quantitative traits: The DAT1

gene was the first DA candidate gene examined in candidate gene

association studies (Cook, Stein et al. 1995). Using a family based

association study the authors reported an association between the 10R allele

and ADHD. Since the first publication a number of studies have also reported

the association between the DAT1 10R and ADHD (e.g. Gill, Daly et al. 1997;

Chen, Chen et al. 2003) however this has not always been replicated (e.g.,

Roman, Schmitz et al. 2001; Todd, Jong et al. 2001). Overall the evidence

from meta-analyses is less supportive than for DRD4. For instance, Curran

and colleagues reported a small positive but non-significant OR of 1.16

(Curran, Mill et al. 2001), while Maher and colleagues reported a non-

significant OR (Maher, Marazita et al. 2002). The most recent study (Gizer,

Ficks and Waldman 2009) found significant association (OR=1.12; p=0.028),

but also significant heterogeneity between studies It has been suggested that

specific haplotypes rather than single markers are associatied with ADHD

(Asherson, Brookes et al 2007) . Muglia, Jain et al. (2002) tested for an

association between DAT1 and ADHD considering the disorder as categorical

as well as a QTL, finding no association for either measure. Unlike Muglia et

al (2002), Cornish, Manly et al. (2005), who evaluated ADHD as a continuous

trait not as severity of psychopathology, and Mill, Xu et al. (2005) found an

association between DAT1 10R-allele and ADHD symptom score measure.

Most recently Cornish, Wilding et al. (2008) used a QTL approach to assess

the association between the DAT1 high-risk genotype, visual search and

vigilance, and ADHD symptoms in a community sample of boys 6-11 years of

age. DAT1 genotypes were only related to ADHD symptoms. In contrast,

Todd, Huang et al. (2005) found that the lower frequency allele (9R), along

with the DRD4 7R allele was over transmitted in ADHD families.

DAT1 and putative ADHD endophenotypes: The data linking DAT1 to

putative endophenotypes of ADHD is probably less compelling than that found

for DRD4, given the dynamic properties of DA transporter densities.

However,

once again high reaction time variability seems to be the most replicated

cognitive marker associated with the 10-repeat homozygosity (e.g. Loo,

Specter et al 2003). It is far from clear what causes such inconsistent results,

but it has been suggested that endophenotypes like delay aversion (Sonuga-

Barke et al., 2008) may be better suited when studying DAT1 and ventral

striatum-

related functions. It is also possible that any association between DAT1 and

neuropsychological performance may be age specific (Rommelse, Altink et al.

2008). This is in line with the idea that the over-transmission of an already

high frequency allele (i.e., DAT1 10R) is possible only if this is in linkage

disequilibrium with a causative allele.

DAT1 and gene environment interactions: DAT1 has been implicated in a

broader range of GxE effects than DRD4. In the first study of its kind in ADHD

Kahn and colleagues (Kahn, Khoury et al. 2003) reported that

hyperactivityimpulsivity symptom scores in young children were associated

with 10/10 genotype, but only in children exposed to prenatal smoking. It

should be noted that the number of cases of children affected by both genetic

and environmental risks was small. This was recently replicated in males

(Becker, El-Faddagh et al. 2008). In contrast, Neuman, Lobos et al. (2007)

reported an association between the DAT1 9R and prenatal smoking while

other have found no effect at all (Langley, Turic et al. 2008). Brookes, Mill et

al. (20006) examined alcohol consumption during pregnancy and found

interaction with a DAT1 haplotype. In terms of psychosocial factors it has

been reported that family adversity moderates the impact of the DAT1

genotype on the expression of ADHD symptoms (Laucht, Skowronek et al.

2007). SonugaBarke, Oades et al. (2009) reported that DAT1 moderated the

effect of parenting expressed emotion on the development of conduct

problems in ADHD. Stevens et al. (2009) showed that the risk of ADHD was

increased only in those children who had experienced severe early

institutional deprivation and were either homozygote for the 10R or carried a

DAT1 haplotypes combining a 40-bp VNTR in 3'UTR and a 30-bp VNTR in

intron 8.

5. CLINICAL IMPLICATIONS

Pharmacogenetics of DRD4 and DAT1 in ADHD: Individual differences in

drug response are well documented throughout medicine, including

psychiatry. A specific drug can be highly beneficial to some patients while in

others it can produce little or no effect, for still others they can have serious

side-effects. The therapeutic value of medication (stimulants) in ADHD

patients were first reported more than 70 years ago (Bradley, 1937). Since

then multiple randomised controlled trials have been published confirming

without doubt the therapeutic effects of stimulants (e.g., methylphenidate &

damphetamines; e.g Malone and Swanson 1993; Wilens, Biederman et al.

1996; Chavez, Sopko et al. 2009; Patrick, Straughn et al. 2009). More

recently non-stimulants (e.g., atomoxetine) have also been licensed (ref). , but

the optimal clinical dose appears to vary 6-fold or more across individuals.

(This is another source of variance that may a better target for

pharmacogenetic studies, since the "response rate" seems to be so high --

85% to 90% -- when titration includes a range of doses for each stimulant and

multiple stimulants).

More recently non-stimulants such as atomoxetine have also been licensed

for the treatment of ADHD (Garnock-Jones and Keating 2009). While these

treatments are, at least in the short term, very efficacious (e.g., "response rate

of -- 85% to 90% -- when titration includes a range of doses for each

stimulant and multiple stimulants), and generally well

tolerated there is still a range in the degree of responses (Sonuga-Barke, Van

Lier

et al. 2008). The ; reduction of levels of ADHD to levels of healthy controls is

relatively uncommon in clinical trials or in normal clinical practice (ref). ).

Furthermore, there is likely to be much greater variability in the long term

effect of stimulants and the optimal clinical dose appears to vary 6-fold or

more across individuals. These two dimensions of treatment response will be

important sources of variance that may be interesting targets for future

pharmacogenetic studies (especially given the high “response rates”).

There

have been a number of attempts to identify predictors of response with the

aim of improving the tailoring of treatments to patient characteristics and

needs. Factors such as age, gender, comorbidity and clinical have been

considered, although evidence of significant effects is limited (Sonuga-Barke,

Coghill et al. 2007; Cornforth et al., in press). In general Ppharmacogenetic

research in

psychiatry focuses on studies of gene x drug interactions can help in the

validation of therapeutic targets, the detection of factors determining response

and the identification of genetically induced side-effects. The long term goal is

to develop more effectively tailored treatment and integrated personalised

therapeutics. The therapeutic effects of stimulants on the neuronal level will

depend on their ability to alter the release, uptake and/or enzymatic

inactivation of neuro-transmitters (see discussion of the effects of

methylphenidate and amfetamine above; Giros, Jaber et al. 1996; Seeman

and Madras 1998). Given that, as we have reviewed, these functions effects

appear

to vary as a function of DRD4 and DAT1 variants, polymorphisms in these

genes are important candidate genes for pharmacogenetic investigation. The

working hypothesis is then that such polymorphisms alter the impact of

stimulant

medication on brain systems as well as treatment efficacy (Stein and

McGough 2008). However, DAT1 is not co-localized with DRD4 as shown by

Madras, Miller et al. (2002) and methylphenidate is only an “indirect agonist”

of DA, via DA transporter blockade, so the hypothesis is stronger for DAT1

than DRD4.

A number of pharmacogenetic studies have examined relationship

between methylphenidate response and DA gene polymorphisms in ADHD.

The majority of studies have focused on DAT1. The results, so far, are

inconclusive for both genes (Levy 2007; Stein and McGough 2008). The first

study (Winsberg and Comings 1999) reported a better therapeutic response

to methylphenidate in ADHD children with the 9/10 genotype compared to

children with the 10/10 genotype. While (Roman, Szobot et al. 2002) and

(Cheon, Ryu et al. 2005) replicated this finding, others (Kirley, Lowe et al.

2003; Stein, Waldman et al. 2005), found better treatment response in

patients homozygous for the 10R. A further two studies demonstrated that

9/9 genotype was associated with a decreased response to methylphenidate

(Stein, Waldman et al. 2005; Joober, Grizenko et al. 2007). In addition,

several studies found no effect of DAT1 in relation to a medication response

(Langley, Turic et al. 2005; van der Meulen, Bakker et al. 2005; McGough,

McCracken et al. 2006; Zeni, Guimaraes et al. 2007; Tharoor, Lobos et al.

2008). For DRD4 Hamarman, Fossella et al. (2004) found that patients with

7R allele required higher doses for symptom improvement while Cheon, Kim

et al. (2007) reported that children homozygous for the 4R allele presented a

better response to MPH. Other studies did not report a significant association

between the DRD4 7R (van der Meulen, Bakker et al. 2005; Zeni, Guimaraes

et al. 2007; Tharoor, Lobos et al. 2008) . In trying to understand this

conflicting and inconsistent set of results it must be acknowledged that studies

to date have

been on very small samples and therefore papers may be reporting chance

findings.

6. SUMMARY OF KEY FINDINGS

ADHD is highly heritable (among the highest of all psychiatric disorders

and nearly as high as the physical traits such as height) and at the

advent of molecular genetic studies of ADHD it was assumed that the

discovery of specific genes would be relatively easy.

The initial discoveries of associations with candidate genes was

remarkably successful (in the context of general psychiatric genetics),

with significant association with first DAT1 and then DRD4 genetic

variants that were chosen as candidate genes because of their pattern

of distribution and neurofunctionality with regard DA activity and a

presumed role in the response to the common pharmacological

treatments for ADHD with stimulant drugs.

The subsequent genome wide scans (GWA) approaches have not

discovered additional genes and have not even detected the replicated

associations with ADHD from the candidate gene studies of DAT and

DRD4 (see Neale et al, 2008).

Association studies provide stronger evidence for DRD4 (i.e., 7R allele)

than DAT1 (i.e. 10/10 genotype) in the pathogenesis of ADHD

probably because of greater between-study heterogeneity in DAT1

findings. Absolute effect sizes for either gene individually are very

small but due to high allele proportions in the population, the relative

magnitude is much larger in term of percentage of the maximum effect.

Evidence relating DRD4 and DAT genotypes to endophenotypes of

ADHD is so far weak and inconsistent, but somewhat stronger for

DRD4, especially with regard to response time variability.

There are also inconsistencies in evidence implicating these genes in

gene-environment interactions, with the strongest findings for DAT1

especially with regard to the impact of maternal smoking during

pregnancy, although the role of gene-environment correlations cannot

be ruled out.

DRD4 and DAT1 polymorphisms are interesting candidates for

phamaco-genetic studies. DAT1 has the best evidence but the specific

genotype associated with greater efficacy is yet to be determined

definitively. This finding has to be treated cautiously given the

inconsistency of findings and the small samples.

7. FUTURE DIRECTIONS

Future studies relating to the role of DRD4 and DAT1 should:

Examine more fully the interactions between genetic factors.

Examining DRD4 x DAT1 interactions as well interactions between

these and variants in other genes perhaps in the context of genome

wide association studies. A few studies have examined gene x gene

interactions but initial results are encouraging (Gabriela, John et al.

2009; Carrasco, Rothhammer et al. 2006)

Explore a wider range of endophenotypes especially moving away from

the focus on executive functions and basic cognitive processes and

towards markers of motivational dysfunction which one might expect to

be more closely linked to DAT1 alterations within sub-corticol regions.

Furthermore, studies of neuro-biological endophenotypes in clinical

samples should be encouraged. Preliminary results are promising;

DAT1 genotype interacting with familial risk of ADHD in stiatum

(Durston, Fossell et al, 2008).

Test for GxE interaction with a wider range of environmental risk

factors especially where these are neuro-biological plausible. As far as

the social environment is concerned it might be especially valuable to

examine genetic moderation of outcomes in non-pharmacological

interventions such as parent training.

To combine GxE and endophenotype designs to explore the role of the

environment in moderating genetic effects at multiple levels of analysis

within the child (neuro-biology, neuro-chemistry and neuropsychology).

To include measues of the environment and endophenotypes in

pharmaco-genetic studies in an attempt to account for the current

heterogeneity in published studies.

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