|Additional related information may be found at:|
|Neuropsychopharmacology: The Fifth Generation of Progress|
The Interface of Genetics, Neuroimaging, and Neurochemistry in Attention-Deficit Hyperactivity Disorder
The Interface of Genetics, Neuroimaging, and Neurochemistry in Attention-Deficit Hyperactivity Disorder
Monique Ernst and Alan Zametkin
The application of new technological breakthroughs in basic sciences on problems of children and adolescents presents great challenges to neuroscientists. Despite increasing concerns of using children in research, new advances in family genetics and brain imaging have been applied to children and adolescents diagnosed with attention-deficit hyperactivity disorder (ADHD). The need for enrolling young subjects in neuroscience research is not restricted to the study of childhood disorders. The importance of understanding the developmental origins of such disorders as schizophrenia or bipolar disorder is becoming clearer to researchers studying adult disorders.
This chapter will review progress made in the investigation of ADHD over the past 5 years in three areas: genetics, neuroimaging, and neurochemistry. Our main emphasis is placed in the areas of genetics and neuroimaging because most progress has been done in these fields, in contrast to the lack of new findings in the neurochemistry of ADHD. Advances in genetics and brain imaging may have great impact on research in pharmacology, because they provide means to identify more homogeneous samples for drug trials and enable us to explore more directly drug effects on brain activity and neurotransmitter systems.
Although it is a large topic to be covered in a short chapter, it is our hope that the interface of these three scientific fields would highlight the direction of research not only in child and adolescent psychiatry, but also in adult psychiatry.
The term ADHD will refer to the disorder of attention-deficit hyperactivity disorder as defined by DSM-III (2) or DSM-III-R (3). It is important to keep in mind that these definitions may identify overlapping, and possibly different, syndromes. DSM-III-R is more inclusive because it allows subjects with only two domains of dysfunction to fulfill ADHD criteria in contrast to the impairment in three domains (impulsivity, inattention, and hyperactivity) required in the DSM-III definition (53). For the most part, we will restrict our review to Attention-Deficit Disorder with Hyperactivity, as there is some evidence that Attention-Deficit Disorder without Hyperactivity might be a different disorder (9, 36, 37). (See 2 Basic Concepts and Techniques of Molecular Genetics, Genetic Stategies in preclical Substance Abuse Research, Methodological Issues in the Neuropathology of Mental Illness, and Amyloidogenisis in Alzheimer's Disease and Animal Models, for related issues.)
GENETICS OF ADHD
There is compelling evidence for the presence of a genetic component to the etiology of ADHD. Familial aggregation of the disorder has been observed for a long time (for review see ref. 11). Recently, family studies attempted to tease out the contribution of familial versus environmental factors to the development of ADHD (for review see ref. 23).
Several models of genetic transmission have been proposed: single gene, polygenetic, or multifactorial models (13).
Deutsch et al. (14) performed a genetic latent structure analysis of dysmorphology in attention deficit disorder (ADD), and they found their data to fit an autosomal mode of transmission.
In keeping with this finding, results from a family genetic study of 140 ADHD child probands and their 454 first-degree relatives, compared to 120 normal child probands and their 368 first-degree relatives, were consistent with a model of highly penetrant autosomal dominant gene transmission (23, 24). In this study (24), female members of the family (mothers and sisters of male probands) seemed to be linked to an increased familial risk for the disorder. If a parent had ADHD, the risk was 6.6 times greater for sisters and 1.5 times greater for brothers. Also the risk to brothers was 4 times greater than the risk to sisters when no parents were ill. These authors rejected the hypothesis of a more severe genetic disorder in girls, a hypothesis based on the multiple threshold model of familial transmission. This model posits that the expression of the disorder requires more pathogenic genes in girls than in boys. Instead, the authors hypothesized that a proportion of male cases were caused by environmental rather than genetic factors.
In summary, the family studies mentioned above all found positive familial aggregation of ADHD. Although very suggestive of the genetic transmission of the disorder, familial aggregation can also reflect social learning, or other environmental factors transmitted from parent to child.
The determination of the relative influence of environmental and genetic factors in the transmission of a disorder is best carried out in adoption studies, where, in a simplistic way, differences are assumed to originate from the environment and similarities from shared genes.
Morrison and Stewart (51) conducted home interviews of the legal parents of 35 adopted hyperactive children who were compared to data previously reported in the groups of biologic parents of 59 hyperactive children and of 41 normal children. The percentage of parents who were retrospectively hyperactive as children were 7.5% in the biologic parents (N = 97), 2.1% in the adopting parents (N = 89), and 0.8% in the control parents (N = 41). The authors cautioned against an overinterpretation of the data because the information was not collected blindly, and the sample of the adopted children was not selected similarly to both other samples.
Deutsch and Swanson (15) compared ADHD symptomatology in first-degree relatives of three groups of probands (N = 24 in each group), ADHD non-adoptees, ADHD adoptees, and non-adopted controls. ADHD was found with higher frequency in the biological relatives of non-adopted ADHD probands than in the adoptive relatives of adopted ADHD probands. This finding suggests greater incidence of ADHD in biological than in adoptive parents of ADHD. However, a stronger case could be made if the comparison were between biological and adoptive parents of the same ADHD adoptees.
Studies of twins represent a third strategy besides family studies and adoptees studies for assessing the role of genetic factors.
Willerman (68) examined activity level in 54 pairs of monozygotic twins (28 males, 26 females) and 39 same-sexed dizygotic pairs (28 males, 11 females) by means of activity and zygosity questionnaires sent to mothers. Zygosity was determined on the basis of the twin zygosity questionnaire, which is less than optimal for assigning twin pairs to either mono- or dizygotic groups. In the pairs with "certain" type of zygosity, correlation between raw scores of activity level were .90 for the monozygotic pairs (N = 38) and .52 for the dizygotic pairs (N = 30). In pairs where at least one twin was rated "hyperactive" (scores in the upper 20% of the activity scale), the twin–twin intraclass correlation was .71 for the monozygotic pairs (N = 8) and 0 for the dizygotic pairs (N = 16).
Goodman and Stevenson (28) conducted home interviews in the families of monozygotic and same-sex dizygotic twin pairs. The intraclass correlation for distractibility was .60 for the monozygotic pairs (N = 186) and .44 for the dizygotic pairs (N = 214). For hyperactivity rated by the teachers, it was 0.62 for the monozygotic pairs (N = 192) and 0.26 for the dizygotic pairs (N = 190). The scores obtained from mothers were thought to be subjected to significant expectancy effects and were difficult to interpret. On the whole, using a broad definition of hyperactivity, 51% (20/39) of the identical twin and 33% (18/54) of the same-sexed dizygotic twin of the hyperactive probands were also hyperactive.
The higher concordance rate for ADHD in monozygotic than in dizygotic twins is a strong argument for a significant genetic component to ADHD, but does not exclude environmental influences. Unfortunately, data on non-twin siblings in these studies were not collected, and concordance rates for ADHD in monozygotic, dizygotic, and non-twin siblings could not be compared. Increased concordance rates for ADHD in twins compared to non-twin siblings would suggest a role for in utero and perinatal biological environmental factors in the transmission of ADHD. The higher risk for ADHD in the siblings (N = 117) of ADHD probands (N = 73) than in the siblings (N = 39) of normal probands (N = 26) (20.8% versus 5.6%) has already been reported (10).
In general, environmental factors have not been systematically addressed, although a wide variety of factors have been implicated, such as lead toxicity, early institutional care, psychosocial stress, pregnancy and delivery complications, and prenatal alcohol exposure.
Furthermore, studies of monozygotic twins, with careful assessment of environmental variables, are needed to clarify the nonshared environmental familial factors (59). Any differences between identical twins, who have identical genotype and live in the same household, are assumed to originate from environmental factors (psychosocial and biological), such as parental attitude, classrooms, peer relationships, or medical problems different for each twin.
Biederman's group, in their family studies of ADHD, recorded socioeconomic status and family integrity. They found the families with an ADHD parent to be less cohesive and to have more conflicts (Moos Family Environment Scale) than the families without an ADHD parent (24, 26). Parents of ADHD children were more likely to be separated than parents of children with other psychiatric problems or than parents of normal children (10, 25). There was no effect of socioeconomic status on pattern of familial transmission.
The recognition of protective factors adds to the complexity of the model of transmission of the disorder. Genetic characteristics can protect from pathogenic environment, and environment can protect individuals from pathogenic genes. Studies tend to focus on identifying adverse factors, and very little is known about protective factors.
Thyroid Receptor-b Gene on Chromosome 3 Linked to ADHD
At present, to our knowledge, there is no information regarding the molecular genetics of ADHD. However, the very interesting finding of an association between ADHD and a specific well-defined autosomal dominant genetic abnormality responsible for a "generalized resistance to thyroid hormone" may provide a model for the study of the biological underpinnings of ADHD (29). "Generalized resistance to thyroid hormone" has been linked to the human thyroid receptor-b gene on chromosome 3 (57) and is characterized by elevated serum thyroxine and triiodothyronine concentrations and decreased responsiveness of the pituitary gland and peripheral tissues to thyroid hormone. This study assessed ADHD in 18 families with a history of "generalized resistance to thyroid hormone," including 49 affected with the thyroid genetic disorder (27 children and 22 adults) and 55 unaffected (23 children and 30 adults). The prevalence rate for ADHD was significantly higher in the affected individuals than in the nonaffected ones (in adults: 50% versus 7%; in children: 70% versus 20%). The gender distribution of ADHD among this population (male/female: 3.2/1 in affected group and 2.7/1 in the unaffected group) was consistent with the distribution of ADHD in the general population reported in the literature (4, 12). Comorbidity with other psychiatric disorders also matched the findings in the literature of families of ADHD children. More studies are warranted to separate the possible primary effect of the gene mutation from the secondary effects of the hormonal dysfunction.
In conclusion, we learned from familial studies that both familial and environmental factors contribute to the development of ADHD. We also learned that there is at least one disorder with a well-defined genetic defect, associated with ADHD at an unusually high rate, which can be used to further the understanding of ADHD. Knowledge of the genetic and environmental influences are important not only to clarify etiologies, psychopathogenesis, psychopathology, treatment, and prognosis, but also to validate the syndrome as a separate psychopathological entity. In this regard, brain imaging has a special place. Promising findings have already been reported showing brain metabolism deviance in ADHD subjects (41, 42, 43, 70).
Deficits in attention and abnormal motor activity have been linked to specific brain regions, which constitute the basis for the hypotheses guiding brain imaging studies in ADHD. The symptoms of ADHD have often been compared to those of frontal lesions in humans and animals (7, 30, 47). Barkley et al. (5) reviewed 22 neuropsychological studies of frontal lobe functions in children with ADD. Tests of response inhibition more reliably distinguished ADHD from normals than did the other tests of frontal lobe function. To date, the regions implicated in attention, motor activation, and arousal include the dorsolateral and medial frontal lobes (including the cingulate gyrus), parietal lobe, striatum, and regions of the reticular formation, including thalamus and mesencephalon (for review, see refs. 30 and 50). It has been noticed that lesions in the right cerebral hemisphere were associated with more attentional problems than were lesions on the left side (30, 65). Because brain imaging is a relatively new technology, only relatively few studies of ADHD are available at present.
Brain imaging provides two sets of information, structural and functional, depending on the techniques. Computerized tomography (CT) and magnetic resonance imaging (MRI) are used to assess structures; single photon emission computerized tomography (SPECT) and Positron emission tomography (PET) are used for functional analyses. A new method, functional MRI, may provide simultaneously structural and functional information of cerebral blood flow. Data of brain imaging in ADHD are from structural CT and MRI studies and from functional SPECT and PET studies. Radiation exposure is critical, especially in studies of minors, and explains the absence of PET studies in individuals younger than 12–13 years of age to this date.
The few CT studies of ADHD (8, 52, 63) are difficult to compare with each other, because of the use of different diagnostic definitions, different designs (open or blind, with or without a control group), and different methods of analysis (qualitative or quantitative).
Bergström and Bille (8) studied 46 children with minimal brain dysfunction characterized by the presence of "incoordination" and "impairment in sensory–motor integration." Fifteen of these 46 children (32.6%) presented gross CT abnormalities, including cerebral atrophy, ventricular asymmetry, or ventriculomegaly. The detailed description of the clinical presentation of three of these children resembled that of cerebral palsy more than that of ADHD. Also, the analysis was qualitative and the design did not involve controls.
Using quantitative measurement, a control group, and blind analysis, Shaywitz et al. (63) studied 35 children and adolescents ADHD by DSM-III (29 boys and 6 girls; 4–18 years of age, mean 11.0 ± 4.2) and 27 controls (20 boys and 7 girls; 4–19 years of age, mean 11.0 ± 3.5). These control subjects had a normal IQ and had no history of seizures or of ADHD. The authors did not specify the clinical indications for the CT scan in this control group. There was no mention of comorbid psychiatric disorders in the ADHD group. The results showed no significant differences between groups in any of the measurements, which included biventricular width, widths of the left and right anterior horns of the lateral ventricles, width of the brain plus ventricle, widths of the right and left hemispheres, and two derived measures, the cerebroventricular index (Evans index: add: 0.237 ± 0.015, contrasts 0.263 ± 0.016) and the asymmetry index. There was no correlation between brain measurements and IQ, nor was there a correlation between brain measurements and handedness. The authors did not give data on age effect.
Nasrallah et al. (52) studied 24 hyperactive male adults, including 22 with a documented history of childhood ADHD treated with stimulant (mean age 23.2 ± 1.9 years) and 27 control males (mean age 28.7 ± 8.3 years). The hyperactive group was part of a cohort of boys who were diagnosed at the age of 8.7 ± 1.9 years with hyperkinesis/minimal brain dysfunction and who presented primary symptoms of hyperactivity, fidgetiness, inattention, and incoordination. No information was given regarding these symptoms at the time of the CT scan. Seven of the hyperactive group had a history of alcohol abuse. The control group consisted of consecutive victims of vehicle accidents whose neurological exam and CT scan, part of the medical work-up, were normal. Measurements included lateral ventricular size expressed as the ventricle-to-brain ratio, third ventricular size, sulcal widening visually rated by a neuroradiologist on a 4-point rating scale, and cerebellar atrophy. The hyperactive group showed increased sulcal widening and cerebellar atrophy relative to controls. Although never severe, these abnormalities suggested mild cerebral atrophy. Unfortunately, the inclusion of individuals with a history of alcohol abuse, representing 30% of the sample, confused the interpretation of the results, because the finding mirrored those reported in CT studies of alcoholic adults (19).
In conclusion, one of the three studies was negative. Of the two studies with positive findings of either gross abnormalities or mild cerebral atrophy, one used children with neurological deficits whereas the other used adults with a history of ADHD, comorbid for 30% of the sample with alcohol abuse, and no assessment of the current clinical presentation. There were no abnormalities of left/right ratios, or of the frontal cortex.
Magnetic Resonance Imaging
Most of the MRI studies in ADHD were conducted by Hynd's group in Georgia (31, 32!popup(ch14, 33, 62).
In their first report, Hynd et al. (32) compared three groups, including 10 children with ADHD by DSM-III and DSM-III-R (8 males; age 120.6 ± 40.4 months), 10 children with reading developmental disorder (8 males; age 118.90 ± 24.55 months), and 10 normal controls (8 males; age 141.20 ± 24.07 months). All children had a normal IQ. Comorbidity was present in seven children with ADHD (five conduct disorder/oppositional defiant disorder and two anxiety disorder). The ADHD group had bilaterally smaller anterior cortices, especially on the right, relative to normals. There was a loss of the normal asymmetry of the frontal lobes (L < R) in ADHD children. All other measures were similar to the normal group.
This finding prompted the authors to study the corpus callosum. This structure is composed of connective interhemispheric fibers (34, 55), which may reflect the degree of function and lateralization of homologous cerebral hemispheric regions. The anterior region of the corpus callosum contains fibers connecting the premotor, orbitofrontal, and prefrontal cortex (55, 56), whereas the posterior part of the corpus callosum is composed of fibers connecting the peri-striate, pro-peri-striate, and juxtastriate regions (1, 55). The hypothesis posited that the anterior part of the corpus callosum would be smaller in ADHD individuals than in normal subjects, because this region connects the frontal lobes. In their first study, the authors found that both the anterior (genu) and posterior (splenium) regions of the corpus callosum were significantly smaller in ADHD children (N = 7; 5 males; age 109.0 ± 61.07 months) than in normal children (N = 10; 8 males; age 141.50 ± 24.36 months) (33). The significant reduction in size of the splenium, but not of the anterior part of the corpus callosum, was replicated in a subsequent study which used a "pure" ADHD group, in contrast to the previous studies whose ADHD sample had comorbid diagnoses (mainly disruptive disorders). There was a trend for the children who did not respond to stimulant medication (N = 5) to have smaller corpus callosum than children who responded to medication (N = 10).
In a brief report, Hynd et al. (31) showed that the head of the caudate nucleus on the left side was significantly smaller in ADHD subjects (N = 11; 8 males) than in normals (N = 11; 6 males).
In summary, the right frontal cortex, the corpus callosum (splenium more consistently), and the left head of the caudate nucleus were found reduced in size in ADHD subjects relative to normals. The functional significance and the clinical relevance of these abnormalities remain to be determined.
Cerebral Blood Flow
Lou et al. (41, 42, 43) presented three studies of cerebral blood flow in ADHD children using xenon-133 inhalation and SPECT in children at rest, with open eyes. This technique gives a quantitative measure of cerebral blood flow in three dimensions, reflecting the metabolic and functional activity of the brain. Resolution of the images in these studies was 17 mm, and the brain slice examined was located 50 mm above the orbitomeatal line.
The first study (41) used a heterogeneous sample of 11 clinically diagnosed ADD children (1 female, 6.5–15 years of age) with various degrees of neonatal/congenital insults (4 of 11), dysphasia (6 of 11), mild mental retardation (2 of 11), and other neuropsychological deficits (7 of 11). Six of these children were also being treated with methylphenidate. The ADD group was compared to 9 normal children (3 females; 7–15 years of age) who were all siblings of the children of the study group.
The results showed hypoperfusion of the frontal lobes in all 11 ADD children, and of the region of the caudate nuclei in 7 of the 11 ADD subjects. In contrast, the occipital lobes were relatively hyperperfused. Six ADD children were scanned before and 30 min after oral administration of their treatment dose of methylphenidate (10–30 mg). They all showed increased perfusion in the frontal and caudate regions after treatment. Absolute or relative values of regional blood flow are not reported by the authors. Also, the findings are difficult to interpret in the face of the heterogeneity of the patient group, the lack of criteria for the diagnosis of ADD, the lack of information regarding comorbid psychiatric disorders, and the fact that the control group was not independent from the study group because they had genetic and environmental factors in common.
In their second study (43), Lou et al. expanded the patient group from 11 to 19 and divided it into pure ADHD (N = 6; 1 female) and ADHD with other neurologic or neuropsychiatric symptoms (N = 13; 1 female). The control group was the same as that in the previous study (N = 9; 7–15 years old; siblings of patients). Five of the six "pure" ADHD patients had a history of neonatal problems. The findings were consistent with those of the first study: (a) hypoperfusion of the right striatal region (10.6% decrease) and (b) hyperperfusion of the occipital lobe (13.7% increase) and the left sensorimotor and primary auditory region (9.6% increase). Thirty to 60 minutes after methylphenidate administration (10–30 mg) in four "pure" and nine neurologically impaired ADHD children, cerebral blood flow increased significantly: 7% in the left striatal region and in the left and right posterior periventricular regions.
In their third study, Lou et al. (42) used a new control group of 15 normal children (7 females; median age 11 years, range 6–17 years), which included 4 children siblings of patients in the study group. They expanded again the patient group to include children with dysphasia. The extent of overlap of patients between this study and the two preceding ones is unclear. Nine "pure" ADHD children (7 boys and 2 girls) were isolated from the patient group. The findings for this "pure" ADHD group, compared to the control group, were again (a) a decrease in blood flow in the striatal regions without mention of laterality (10.7%) and in the posterior periventricular region (6.8%) and (b) an increase in blood flow in occipital regions.
The consistency of the results within these three studies is not unexpected because there seems to be a significant overlap among samples, which, unfortunately, include patients with history of perinatal brain insults. No standardized instruments were used to make the diagnosis of ADHD. However, the results are in keeping with the theoretical framework of the pathogenesis of ADHD which implicates abnormalities in the frontal cortex and striatum, more so on the right side than on the left side.
Glucose Metabolic Rates
Study in Adults
Zametkin et al. (70) published a study showing, for the first time, definite and quantifiable central neurophysiological differences between ADHD adults and normal adults, using PET and [18F]fluorodeoxyglucose. They studied a very carefully screened sample of 25 adults (18 men, 7 women; 37.4 ± 6.9 years old), who currently met Utah criteria for ADHD, who had a childhood history of ADHD, and who were parents of children diagnosed with ADHD. This group of 25 patients was compared to 50 normal adults (28 men, 22 females; 36.3 ± 11.7 years old). None of the ADHD adults had ever been treated with stimulants. All studies were done under similar conditions, and the subjects performed an auditory continuous performance task with their eyes patched.
Global glucose metabolism (mean of glucose metabolic rates for all the gray matter-rich areas examined in this study) was 8.1% lower in adults with ADHD than in normals (p = 0.03). Half of the brain regions studied (30/60) had significantly reduced glucose metabolic rates in ADHD compared to normal subjects, including four subcortical regions, the right thalamus, right caudate, right hippocampus, and cingulate. The cortical regions were localized bilaterally and predominated in the upper brain. When normalized (divided by global metabolism values), the regional metabolic rates of four regions, in the left premotor and left somatosensory areas, were also significantly decreased. Interestingly, the reduction in brain metabolism was greater in women than in men, but not statistically so.
The decrease in frontal and striatal brain metabolism is consistent with Lou et al.'s finding (42). However, the decreased metabolic rates found in the somatosensory and occipital areas are in contrast to the increased blood flow in these regions reported by Lou et al. (42). It is important to keep in mind, in comparing Lou's and Zametkin's studies, the differences in sample characteristics (children versus adults) and in analysis of the results (single-plane versus five-plane analysis, 17-mm versus 6-mm image resolution, and normalized data versus absolute and normalized values) (see Brain Energy metabolism: An Integrated Cellular Perspective, for background).
Study in Adolescents
Because of the promising results in adults, Zametkin et al. (69) initiated a PET study in adolescents. The authors modified the PET procedure to significantly reduce the amount of radiation exposure to a fifth of the adult exposure. The study of younger subjects, especially in investigations of childhood disorders, is critical. For instance, the interpretation of data collected in adults suffering from a childhood disorder is difficult, because the primary effects of the disorder cannot be sorted out from its secondary effects or long-lasting environmental influences.
Twenty adolescents (14.7 ± 1.7 years old, 5 girls), fulfilling ADHD DSM-III-R criteria, were compared to 19 normal adolescents (14.4 ± 1.4 years old, 6 girls) (29, 30). The data originating from the first half of the ADHD and normal samples were analyzed in a preliminary study (69). In the final study (20, 21), no significant differences were found in global and absolute glucose metabolic rates between ADHD and normal adolescents. However, similarly to the findings in the adult study, female adolescents showed greater brain metabolism deviance than did male adolescents. In contrast to boys, ADHD girls (N = 5) showed a significant 15% global brain metabolism reduction when compared to normal girls (N = 6). Several reasons could have accounted for the overall lack of brain metabolism differences between ADHD and normal teenagers. First, the adolescent control group was not as pure as the control group used in the adult study, because 63% of the normal adolescents had a first-degree relative with ADHD (12/19), in contrast to the absence of ADHD pathology in families of normal adults. Second, 75% adolescents with ADHD had been previously exposed to treatment with stimulants, compared to no history of stimulant treatment in the ADHD adults. Third, an age effect in the development of brain abnormalities in ADHD individuals cannot be ruled out. The results of this study clearly emphasizes the need for studies in females and in children with ADHD.
Effects of Stimulants on Brain Imaging
Besides examining a younger population with ADHD, another question raised by the positive results obtained in ADHD adults (70) was to find out how the reduction in brain metabolism observed in adults with ADHD could be affected by the treatment of choice of this disorder—that is, stimulants (16). The authors expected to observe increased brain glucose metabolism after the administration of a stimulant, especially in the striatal and frontal regions. Matochik et al. (44, 45, 46) conducted two studies of acute and chronic stimulant treatment in ADHD adults using PET and [18F]flurorodeoxyglucose.
In the acute study (45), 27 adult outpatients with ADHD were scanned twice: (i) off medication and (ii) after receiving orally a single dose of either dextroamphetamine (0.25 mg/kg) (N = 13) or methylphenidate hydrochloride (0.35 mg/kg) (N = 14). On-drug and off-drug studies were 1–4 months apart, in counterbalanced order. The PET procedure was identical to the one used in the previous adult study (70), where subjects were studied during an auditory continuous performance task with their eyes patched. The acute administration of an oral dose of stimulant (dextroamphetamine or methylphenidate) had no effect on global glucose metabolic rates. With the data normalized (regional/global), the regional metabolic rates of 7 of 60 regions significantly changed after dextroamphetamine administration. These regions predominated on the right side (5 right, 2 left), and included 4 regions with increased metabolism and 3 with decreased metabolism. Of interest is the increased metabolism in the right caudate nucleus. After methylphenidate, the normalized regional metabolism of 5 regions, all on the left side, were significantly changed: 2 increased and 3 decreased.
The results of the study of the effects of chronic administration of stimulants on brain metabolism (44, 46) also showed minimal changes. In this study, a total of 37 adults with ADHD were studied twice, off drug and then on drug, at the end of 6–15 weeks of dextroamphetamine (N = 18; mean dose 19 ± 7 mg/day) or methylphenidate (N = 19; 28 ± 10 mg/day) treatment. Subjects were randomized to either stimulants, and dosage was individually titrated to optimal therapeutic efficacy. Global and absolute regional brain metabolic rates were unchanged after the administration of stimulants. Normalized metabolic rates were modified in only 2 of the 60 regions studied, and only after methylphenidate treatment (decreased metabolism in the right anterior putamen and increased metabolism in the right posterior orbital frontal region). The lack of effect of the stimulants on brain metabolism was in contrast to the 68% clinical response rate for both drugs combined (positive clinical response defined as an 8-point decrease on the modified self-rated Conners Scale).
Another reason to expect stimulants to increase brain metabolism stemmed from findings in animal studies (6, 17, 58, 67), all reporting an increase in brain activity after stimulant injection.
Zametkin's group undertook a third study to more closely approximate the animal experiments (22). Glucose brain metabolism was measured before and after dextroamphetamine intravenous injection at a dose of 0.15 mg/kg in ADHD adults. Preliminary results in 8 subjects failed to detect any significant changes in global or absolute regional glucose metabolic rates. Only 3 of 60 regional normalized metabolic rates differed between conditions. These 3 regions were on the right side of the brain. Glucose metabolism was decreased in 2 regions (right temporal cortex and right hippocampus), and increased in 1 (right parietal cortex). Here again, the minimal effects on brain metabolism were in contrast to the striking changes in affective (more energetic, increased concentration) and in physiological states (significant increases in diastolic and systolic blood pressure) induced by the intravenous injection of dextroamphetamine. The discrepant results between animal and human studies are not too surprising. For instance, similar findings were reported regarding the effect of cocaine on brain metabolism, where the animal study showed increased brain metabolism (40) and the human study showed a decrease in brain metabolism (39). Many variables may account for the different results in humans and animals, including most importantly the effects of species and of experimental conditions.
The results of the last 4 PET studies described above—assessing brain metabolism in adolescents with ADHD, and after stimulant treatment in ADHD adults—have been somewhat disappointing. However, they clearly illustrate the difficulty of using and interpreting data from functional brain imaging studies. To increase the yield of such studies, it is important to consider (a) the use of behavioral activation tasks tapping the specific areas of deficits of the disorder under study and (b) the use of neurotransmitter-dependent tracers to focus on a specific neurotransmitter system. In ADHD, the activation tasks should target attention and impulsivity. Hyperactivity is now thought to be part of the domain of impulsivity, conceptualized as a motor disinhibition paradigm (DSM-IV). The neurotransmitter system most relevant to ADHD pathology at this time is the dopaminergic system.
Finally, results from the brain imaging studies, along with those of the genetic studies, emphasize the importance of studying females with ADHD, as there is some evidence for greater deviance in brain metabolism and stronger familial risk in females compared to males with ADHD.
In 1987 Zametkin and Rapoport (71) published a review of the neurochemistry of ADHD entitled "Neurobiology of Attention Deficit Disorder with Hyperactivity: Where Have We Come in 50 Years?" The exact cause of ADHD remains elusive, as does the mechanism of action of its treatment of choice (stimulants). Since that review, no new findings have emerged. However, much interesting theoretical writing has appeared.
Our intent in this section is to refer the reader to six most recent reviews of the neurobiochemical basis of ADHD (48, 49, 54, 60, 64, 66). Each of these reviews offers a model for the understanding and means of studying ADHD. Pharmacological treatments, including stimulants (d-amphetamine, methylphenidate, and magnesium pemoline), antidepressants (tricyclic antidepressants and monoamine oxidase inhibitors), neuroleptics, and the alpha-2 adrenoceptor agonist clonidine, are also presented, and their mechanisms of action are discussed in light of the specific models proposed by the authors. We chose not to repeat the presentation of the various drugs used for the treatment of ADHD, but to highlight one or two points in each of the six reviews:
1. Rogeness et al. (60), in a review of the three neurotransmitter systems—dopaminergic, serotoninergic, and noradrenergic—make the point that no single neurotransmitter hypotheses could fully account for the findings of the large array of data and studies in ADHD. The authors underline the interaction of the norepinephrine with the dopamine systems, whereby dopamine-dependent behaviors are regulated by norepinephrine activity. They suggest that the balance between these systems may be more critical than the individual activity level for the regulation of behavior. For example, decreased activity in both systems, as opposed to the reduction in one system only, would not alter the balance and have no deleterious effect on behavior. The authors also underline the influence of neural maturation on the relative activity of these systems, reflecting the differential maturational rate among neurotransmitter systems. Accordingly, dopamine receptor density increases from birth to 2 years of age, and then decreases to reach adult levels by adolescence (61), whereas the index of norpinephrine activity (CSF 3-methoxy-4-hydroxyphenylglycol) remains unchanged after 8 or 9 months of age (38). Both issues of interdependence and differential maturational rates of neurotransmitter systems stress the need to assess neurotransmitter systems simultaneously and to use a sample of narrow age range to be able to interpret studies of the neurochemistry of behavior.
2. In a comprehensive review of the contribution of catecholaminergic activity to ADHD (54), Oades shows how the dysfunction in catecholaminergic systems can lead to various types of symptoms, including inattention, hyperactivity, tics, dyskinesia, and self-mutilation. This is suggested by catecholaminergic abnormalities found in various disorders, including phenylketonuria, Tourette's syndrome, and Lesch Nyhan disease. The type of dysfunction in the neurotransmitter systems, including changes in "balance" and time of impairment relative to the developmental stage, account for the variety of symptoms produced by the same neural systems. In addition to the role of neurotransmitters, Oades mentions the putative involvement of estrogen in the development of hyperactivity, because estrogen can act as a dopamine receptor antagonist (35). This finding is in keeping with gender-related differences in incidence of ADHD (4, 12) and in brain metabolism of ADHD versus normal subjects (20).
3. Mefford and Potter (49) speculated a dominant role of adrenaline and its inhibitory effect on the locus coeruleus activity in ADHD. This hypothesis stems from the ethological model of behavior stating that "the orienting response" (novel stimuli supplant present activity) and "the orienting reaction" (motor responses to the novel stimuli) have survival value. The orienting reaction and orienting response, identified as hypervigilance and hyperactivity respectively, have been shown to be regulated through the locus coeruleus activity (27).
4. Voeller (66) reviewed the anatomical substrates of attention and motor control as they apply to ADHD. She proposes the theory of lateralized dysfunction, whereby the right hemisphere of the brain plays a dominant role in the attentional/intentional and arousal/activation systems implicated in ADHD. As more data become available through functional imaging, these hypotheses will be more carefully tested.
5. McCracken (48) submits a neurobiochemical model of ADHD which posits that for the action of a drug to be effective in the treatment of ADHD, there must be simultaneous increases in both (a) dopamine release and (b) inhibited adrenergic tone on the locus coeruleus. The contention by Elia et al. (18) that up to 98% of ADHD children respond to stimulants, when at least two types of stimulants are tried, is not consistent with the requirement for both dopaminergic and noradrenergic effects to occur to achieve therapeutic efficacy, since stimulant actions are primarily mediated through dopamine release. This is further supported by the lack of specific effect of clonidine on ADHD symptoms as mentioned earlier.
6. Shenker (64), focusing on catecholamine receptor pharmacology, alludes to the function of autoreceptors likely to be implicated in the mechanism of action of stimulants in the treatment of ADHD. This review highlights the dramatic increase in complexity of our understanding about neuropharmacology, which renders earlier speculation about the biochemical basis of ADHD symptomatology woefully constrained.
It is likely that part of the slow progress made in the neurochemistry of ADHD stems from the difficulty in isolating homogeneous samples to study. Advances in genetics and brain imaging may help to refine the selection of uniform groups. It is clear that any significant gain in knowledge about one of the most prevalent disorder in childhood will come from the integrated findings in the three scientific fields of genetics, brain imaging, and neurochemistry (see Pharmacological treatment of Obesity).