- Email: [email protected]
Behavioural genomics: an integrated approach
BEHAVIOURAL GENOMICS
Behavioural genomics: an integrated approach
Twin studies of psychiatric disorders Schizophrenia Autism
Philip Asherson
Bipolar disorder Unipolar depression Attention deficit hyperactivity disorder Childhood fatigue 0.0
dizygote
Family, twin and adoption studies of common behavioural disorders have highlighted the importance of both genes and environments. For almost all human behaviours we find that genetic variation accounts for around 40% of phenotypic variation, with higher levels of heritability for a number of important psychiatric conditions including schizophrenia, bipolar disorder, major depression, autism and attention deficit hyperactivity disorder (ADHD; Figure 1). At the same time, the molecular genetic revolution heralded by the near-complete sequencing of the human genome in 2000, and rapidly advancing techniques to interrogate human genetic variation, has opened the way for investigators to identify the genes involved and the ways that genetic variation can influence human behaviour. This will be a complex task since human behaviours do not result from simple one-to-one relationships with aetiological factors, but rather a complex net of co-acting, correlated and interactional factors. Despite the inherent complexity that is expected, combining quantitative and molecular genetic strategies with social, developmental, environmental, neurobiological and psychological methods holds the promise of elucidating major components of ‘aetiological networks’. The challenge is to embrace this complexity while delineating key functions that can be used to further our knowledge of the development of human behaviours with consequent refinement of our conceptual ideas and practical outcomes in terms of prevention and treatment. This article provides an overview of some of the ways in which genetic strategies are being used to bring together diverse areas of investigation and make best use of emerging technologies in the investigation of behavioural traits and psychiatric disorders.
0.4
0.6
0.8
1.0
1.2
monozygote
a) Monozygote (identical) twin and dizygote (non-identical) twin correlations for major psychiatric disorders. The proportion of phenotypic variance attributable to genetic variance can be estimated by doubling the difference in the correlations between monozygote and dizygote twins.
Schizophrenia Autism Bipolar disorder Unipolar depression Attention deficit hyperactivity disorder 0.0
environment
0.2
0.4
0.6
shared environment
0.8
1.0
1.2
additive
b) Variance explained by additive, shared environment and residual environment components for the major psychiatric disorders. Variance in common environment does not have a significant role an any of these disorders, although environment may still play a key role through gene– environment interaction. The non-shared environmental component reflects influences that bring about differences between siblings. This component includes error variance.
1
by investigating so-called ‘candidate’ genes. Such an approach has, for example, been successful in the investigation of ADHD in children where several genetic variants within dopamine system genes have been associated with the disorder.1,2 Although such findings do not identify novel genes or gene systems, they shift the focus of research from gene identification to gene function and investigation of the neurobiological and neuropsychological mechanisms that mediate genetic effects on behaviour.3 The other major strategy is to use positional cloning methods to locate genetic variants that are linked or associated with human behaviours. An efficient method for screening the entire genome is to use linkage-mapping methods, usually by running genetic markers that span the entire genome in large samples of affected sibling pairs. For example, meta-analyses of 20 genome scans for schizophrenia identified a number chromosomal regions that consistently provide evidence for the localization of susceptibility genes. More importantly, replicated findings have identified individual genes within some of the linked regions, such as neuregulin-1 (NRG1) on chromosome 8p12 and dysbindin (DTNBP1) on chromosome 6p22.4 These are important findings in psychiatric genetics since they are some of the first genes associated with a
Gene mapping and ‘SNP sets’ Methods for mapping genes for complex disorders are described by Norton and colleagues (this issue). Since multiple genetic variants are expected, each conferring only a small risk to human behaviour, statistically powerful approaches are required. Two main strategies have been adopted. First, testing a priori hypotheses
Philip Asherson is Professor of Molecular Psychiatry at the MRC Social, Genetic and Developmental Psychiatry Research Centre at the Institute of Psychiatry, King’s College London, UK. He holds an Honorary Consultant post with the South London and Maudsley Health Trust where, in collaboration with senior colleagues, he runs a national specialist clinic for adults with attention deficit hyperactivity disorder (ADHD). His research interests include genetic mapping studies of ADHD.
PSYCHIATRY 4:12
0.2
1
© 2005 The Medicine Publishing Company Ltd
BEHAVIOURAL GENOMICS
complex behavioural disorder that have been identified following a positional cloning rather than candidate gene approach. Future studies will adopt whole genome association scanning methods – a positional cloning approach that searches for genetic associations using many thousands of markers spanning the entire genome. Work in this area has been pioneered using a DNA pooling method to scan around 10,000 single nucleotide polymorphisms (SNPs) for association with mild mental impairment (MMI).5 Four genetic variants were identified with an average effect size of only 0.2%. Despite the small size of the genetic effects of each individual SNP, the data can be combined together in an additive fashion to provide an informative ‘SNP set’. The principle of aggregating together associated SNPs to generate a composite genetic index is thought to be important in improving the reliability and predictive value for complex traits. Furthermore, as new associated SNPs are identified these can be added to the SNP set to increase the overall effect size of the molecular genetic data. For example Butcher et al.,5 predict that further screening of the latest 100,000 SNP arrays will increase the variance explained by the SNP set to around 8%.
Diagrammatic representation of gene–environment interactions MAOA SERT
Maltreatment Life events
Disruptive behaviour/aggression Depression 4.5
environment +
Symptom score
4.0 3.5 3.0 2.5 2.0
environment –
1.5 1.0 0.5 0
AA
AB
BB
The studies of Caspi and colleagues found no main effect of genotype. Genotype effects were seen only when individuals were exposed to known environmental risk factors. AA, AB and BB represent 3 genotypes with 0, 1 and 2 risk alleles, respectively. The environmental risk exposed group (+) and environmental risk non-exposed group (–) are represented by the blue and orange lines, respectively.
Gene–environment interactions
2
To date most genetic studies in neuropsychiatry have focused on the detection of genetic variants that have a main effect on the risk for behavioural disorders. However, it has been known for a long time that gene–environment interactions are likely to play an important role on risk for behavioural disorders and in some cases will be present in the absence of main effects. What is not widely understood is that the heritable component estimated from family, twin and adoption studies, indexes both the main effects of genes plus the effects of gene–environment interactions. For this reason environmental research remains critical to our understanding of psychiatric disorders, even for those that are highly heritable.6 An emerging literature on the effects of gene–environment interactions on behavioural disorders and an outline of the methodological issues has recently been reviewed.7 Using a longitudinal population sample from Dunedin in New Zealand, Caspi, Moffitt and colleagues reported three key findings (Figure 2). First they hypothesized that a functional polymorphism in the promoter region of the gene encoding the neurotransmitter metabolizing enzyme monoamine oxidase A (MAOA), would moderate the effect of child maltreatment in the cycle of violence. Their results showed that maltreated children with genotypes that conferred low levels of MAOA expression were more likely to develop conduct disorder, antisocial personality disorder and adult violent criminal behaviour than children possessing high activity variants of MAOA.8 In the second study they hypothesized that a functional variant in the promoter region of the serotonin transporter gene (HTT) would moderate the influence of stressful life events on depression. They found that individuals with 1 or 2 copies of the HTT short allele exhibited more depressive symptoms, diagnosable depression, and suicidality following stressful life events than individuals homozygous for the long allele.9 This finding has been replicated in several further studies and is now one of the most consistent findings in psychiatric genetics.10–12 In the third study, they reported that a functional variant of the catechol-O-methyltransferase gene (COMT Val158Met) moderates the risk of cannabis use by adolescents on the later development of psychosis in adult life.13
These three findings highlight the importance of considering the effects of environmental exposure in the search for genetic risk factors. Moffitt, Caspi and Rutter noted several important methodological points in their review.7 First, they noted that several of their initial reports were subsequently replicated, indicating the robust nature of some gene–environment interactions on human behaviour. Second, that in each case the environmental risk involved had shown an association with the disorder in previous epidemiological studies. In other words, they were known environmental pathogens. Third, in several of the reports it was noted that there was no main effect of gene alone. This has important implications since the search for genetic associations with behavioural disorders would have been unsuccessful in these examples if interaction with the environmental pathogen had not been taken into account. These findings have promoted a new wave of interest in gene–environment research, although identifying such interactions remains a major challenge. Unlike DNA variation, where we know that we will soon be able to scan the entire human genome for associated genetic variants, environmental research will depend on careful selection of appropriate and measurable environmental risks. This is necessarily a time-consuming and costly process and requires reasonable prior hypotheses to be generated. Once a specific gene–environment interaction has been identified the next set of questions is to clarify the precise mechanisms involved. This is not always immediately obvious since apparent interactions with an environmental variable may have several causes. As an example, we consider the recent report of an interaction between the mother’s use of alcohol during pregnancy and genetic variants of the dopamine transporter gene (DAT1) on the risk for development of childhood attention deficit hyperactivity disorder (ADHD).14 In this study, only those individuals carrying the DAT1 risk alleles whose mothers used alcohol during the pregnancy showed an increased risk for ADHD. There are, however, several plausible explanations for this observation. First, there may be a direct toxic effect of alcohol on the developing fetus. Further work to establish this causal link needs to focus on more
PSYCHIATRY 4:12
2
© 2005 The Medicine Publishing Company Ltd
BEHAVIOURAL GENOMICS
detailed analysis that considers the timing and amount of alcohol used by mothers during the pregnancy. However, other causal relationships need to be considered since maternal drinking may be correlated with parental behaviours that could act as more proximal risk factors, such as levels of maternal stress, quality of parenting and maternal psychopathology, including ADHD. Interactions with variables that reflect parental behaviour may also index genetic loading consistent with the increased co-transmission of interacting genes (gene–gene interaction also referred to as epistasis). For example, in this study we also found preliminary evidence for gene–environment correlation between the DAT1 risk alleles and maternal use of alcohol. Although we controlled for this in our analysis this highlights the complexity of interpreting gene–environment effects where genes cause change in parent as well as offspring behaviour. Well-designed epidemiological studies are one approach, but direct testing of environmental hypotheses may require the use of animal behavioural and genetic models and a focus on more direct neurobiological measures of brain function in addition to the analysis of behavioural phenotypes.
differences is not sufficient to confidently identify a measure as a candidate endophenotype. Another problems is sample size, since many of the current studies lack statistical power for small to moderate genetic effects and would reliably detect only major gene effects. The existence of major gene rather than minor polygene effects will have a very large bearing on the success of endophenotype studies where generating large and reliable datasets is costly and time-consuming, such as many current neuroimaging techniques. As in other areas of genetic research on human behaviour replication of initial findings and subsequent meta-analysis remain essential steps to identify true findings. It is also important to consider whether any single endophenotype measure provides the most effective method for the identification of behavioural genes, by parsing complex behavioural disorders into more genetically homogeneous components. The work of Robert Plomin and colleagues on the latent construct of general cognitive ability (‘g’) has been hugely influential in this field.16, 17 Genetic models of cognition began by proposing a single fundamental process. However, this model was modified, as the different components of cognitive ability were delineated (e.g. verbal, spatial, memory, maths, processing speed) and the major model became one of multiple independent cognitive pathways. The perception was that each cognitive function was causally linked to a specific set of genetic factors that mapped onto independent neurocognitive pathways. Genetic model fitting did not, however, support this model (Figure 3). Multivariate genetic analysis that quantifies the extent of the shared genetic influences between measured variables identified a common genetic factor termed ‘g’ that explains almost all the genetic variance for the various components of general cognitive ability. So, at least for general cognitive ability, investigation of a common factor derived from multiple correlated variables is the most effective way to identify the genetic variants associated with the various components of cognition. When considering other behavioural disorders this model should be born in mind and one-to-one relationships between genes and various neurobiological variables should not be assumed until they have been explicitly tested using genetic model fitting approaches. Further delineation of the links between different brain functions, cognitions and behaviours will come once specific genes and environmental factors have been identified. For example, once informative ‘SNP sets’ have been identified these can be used to identify the neurobiological processes that mediate the effects of the SNP set on behaviour.5
Endophenotypes The use of endophenotypes or intermediate phenotypes has been suggested as a potential panacea to unravelling the complexity of human behavioural disorders. Gottesman and Gould15 describe the concept of endophenotypes as ‘measurable components unseen by the unaided eye along the pathway between disease and distal genotype’. Endophenotypes for human behaviour therefore include a wide range of measures of brain function and processes including neurophsyiology, functional and anatomical neuroimaging, neuropsychology and biochemical and endocrinological assays. The overall aim is to identify the processes and mechanisms that mediate genetic effects on behaviour. Gottesman provides a set of criteria for endophenotypes.15 • The endophenotype should be associated with the clinical disorder/behaviour in the population. • The endophenotype should be heritable. • The endophenotype should be primarily state independent in the sense that it should manifest itself whether or not the illness is active or not. This criterion has greatest relevance to episodic disorders such as depression or bipolar disorder where behavioural manifestations show fluctuations over time. • The endophenotype is familial so that both the clinical disorder and endophenotype co-segregate within families. Using quantitative genetics (family, twin and adoption studies) we can use model-fitting approaches to identify whether there are shared genetic influences between putative endophenotypes and the behavioural disorder (e.g. Andreou and Kuntsi, pages 27–30, McGloughlin et al., pages 14–18). • Related to the previous criteria, endophenotypes should be found more frequently among close relatives of affected probands than in the general population. The complexity of human behaviour and recent advances in our ability to measure different facets of brain function, has led many current investigators to adopt an endophenotype approach. The relative ease of genotyping a few candidate gene markers has, however, meant that much of this research has gone forward with little prior information on the status of the measure as a true endophenotype. For example, the demonstration of case-control
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Quantitative trait locus approaches and animal behaviour Due to the complexity of human behavioural disorders and the difficulties in investigating human brain function and controlling for genetic and environmental variation, animal models are an important adjunct to human studies. Animal research within psychiatry has mainly focused on comparisons between one or a few animals that are thought to model particular disorders, and the investigation of genetic manipulations such as targeted gene knockouts and gene mutations. Such approaches have been instrumental in the development and testing of psychiatric medications. Furthermore, some experimental paradigms have been very sophisticated, such as the demonstration that polymorphisms of the serotonin transporter gene interact with the effects of early rearing on behaviour in rhesus monkey neonates; providing direct 3
© 2005 The Medicine Publishing Company Ltd
BEHAVIOURAL GENOMICS
Models of cognitive performance patterns throughout the population
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Multivariate quantitative genetic studies indicate that a model of multiple correlated cognitive processes provides the best explanation for the observed patterns of cognition performance throughout the population. Similar analyses have not been completed for processes thought to underlie common psychiatric disorders and it is therefore premature to conclude whether complex behavioural disorders result from multiple independent processes or multiple correlated processes.
1 P2 P3 g 1 P2 P3 g
Cognition
Genes
Psychometrics
Model 1: single fundamental cognitive process 1
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Model 2: multiple independent cognitive processes 1 2 3 4 5 6
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Model 3: multiple correlated cognitive processes 1 2 3 4 5
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experimental evidence for the gene–environment interaction identified by Caspi and colleagues in the Dunedin sample.9 Such approaches are, however, limited in their ability to model complex polygenetic traits. The ability to model complex behavioural traits using quantitative trait locus (QTL) approaches in mouse is possible using strategies outlined by Schalkwyk (pages 18–21). Behavioural research has focused mainly on the use of rodents and measures such as activity level, response to novel objects, ability to solve mazes, response to anxiety-provoking stimuli and accuracy and speed of reactions. Clearly one of the difficulties in using animal models is the identification of mouse behaviours that are the equivalent of human behaviours. This is particularly difficult for behavioural phenotypes such as schizophrenia where diagnosis depends on verbal accounts of mental states from affected individuals, although greater progress has been made in the analysis of traits such as anxiety, depression, alcohol use and general cognitive ability. The use of endophenotypes is an alternative approach since cognitive experimental and neurobiological measures may show greater cross-species similarities than more complex behavioural measures (Figure 4). One strategy that takes advantage of quantitative genetic approaches is to look for genetic correlations between cognitive and behavioural paradigms across inbred strains, recombinant inbred strain panels or outbred mouse strains. An example of this type of work is the demonstration of a general cognitive ability (g) factor in outbred heterogeneous stock (HS) mice.18 HS is a genetically outbred line of mice established more than 30 years ago from an 8-way cross of eight inbred mouse strains. Galsworthy and colleagues18 compared the performance of 40 HS mice across a battery of diverse cognitive tasks. All measures of ability loaded positively onto a principal component that accounted for 31% of the variance, suggesting the presence of a common factor of general cognitive ability. A general cognitive ability factor (g) therefore appears to underlie the performance of HS mice on a battery tapping diverse cognitive demands, paralleling the identification of the latent construct ‘g’ in the human literature. In a
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Phenotypic analysis of general cognitive ability Phenotypic ‘g’ accounts for 40% of the variance
Verbal
Spatial ‘g‘
Memory Genetic ‘g’ accounts for almost all of the genetic variance of cognitive abilities Verbal
Spatial Genetic ‘g‘
Memory Phenotypic analysis of general cognitive ability finds that a common factor (‘g’) explains around 40% of the phenotypic variance. Different domains of cognition show high genetic correlations indicating that a common genetic factor (‘genetic g’) accounts for almost all of the general cognitive ability are shared across the various domains of cognition.
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© 2005 The Medicine Publishing Company Ltd
BEHAVIOURAL GENOMICS
similar way we can investigate whether paradigms for a disorder such as ADHD (activity level, impulsivity, performance on tests of attention, response variability) show a similar pattern of genetic correlations in humans and mouse. Subsequent studies can use methods for complex trait analysis in mouse to map behavioural genes, map out gene expression patterns and study gene–gene and gene–environment interactions.19
the prediction of episodes of major depression: a replication. Arch Gen Psychiatry 2005; 62: 529–35. 11 Kaufman J, Yang B Z, Douglas-Palumberi H et al. Social supports and serotonin transporter gene moderate depression in maltreated children. Proc Natl Acad Sci USA 2004; 101: 17316–21. 12 Eley T C, Sugden K, Corsico A et al. Gene-environment interaction analysis of serotonin system markers with adolescent depression. Mol Psychiatry 2004; 9: 908–15. 13 Caspi A, Moffitt T E, Cannon M et al. Moderation of the effect of adolescent-onset cannabis use on adult psychosis by a functional polymorphism in the catechol-O-methyltransferase gene: longitudinal evidence of a gene X environment interaction. Biol Psychiatry 2005; 57: 1117–27. 14 Brookes K, Mill J, Guindalini C et al. A common haplotype of the dopamine transporter gene is associated with attention deficit hyperactivity disorder and interacts with prenataleExposure to alcohol. Arch Gen Psychiatry 2005; in press. 15 Gottesman I I, Gould T D. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 2003; 160: 636–45. 16 Plomin R. Genetics and general cognitive ability. Nature 1999; 402: C25–9. 17 Plomin R, Spinath F M. Genetics and general cognitive ability (g). Trends Cogn Sci 2002; 6: 169–76. 18 Galsworthy M J, Paya-Cano J L, Monleon S, Plomin R. Evidence for general cognitive ability (g) in heterogeneous stock mice and an analysis of potential confounds. Genes Brain Behav 2002; 1: 88–95. 19 Churchill G A, Airey D C, Allayee H et al. The collaborative cross, a community resource for the genetic analysis of complex traits. Nat Genet 2004; 36: 1133–7. 20 McGuffin P, Plomin R. A decade of the Social Genetic Development Centre at the Institute of Psychiatry. Br J Psychiatry 2004; 185: 280–2.
Conclusion The new genetics heralded by the near completion of the human genome sequence was rapidly followed by an exponential rise in the number of identified genetic variants. The goal of behavioural genomics is shifting from gene discovery towards gene functionality at the level of molecular mechanisms and brain processes and a focus on interaction with environmental pathogens.20 Quantitative genetic studies have led to a perceptual shift where psychiatric disorders are perceived as quantitative traits that share genetic influences with other developmental behavioural and cognitive traits. Molecular genetic studies have confirmed a priori hypotheses for some disorders and identified novel genes for others and identification of many additional behavioural genes is expected in the coming decade. Combining genetic, environmental and neurobiological research strategies has the potential to delineate the causal links between behavioural traits, psychiatric conditions and developmental course, including the persistence/desistance of psychiatric symptoms and comorbidity between psychiatric disorders and traits. As a result we can look forward to new insights and potential advances in our treatment of previously intractable problems.
REFERENCES 1 Asherson P. Attention-deficit hyperactivity disorder in the postgenomic era. Eur Child Adolesc Psychiatry 2004; 13(Suppl 1): 50–70. 2 Faraone S V, Perlis R H, Doyle A E et al. Molecular genetics of attention-deficit/hyperactivity disorder. Biol Psychiatry 2005; 57: 1313–23. 3 Asherson P, Kuntsi J, Taylor E. Unravelling the complexity of attentiondeficit hyperactivity disorder: a behavioural genomic approach. Br J Psychiatry 2005: in press. 4 Owen M J, Craddock N, O’Donovan M C. Schizophrenia: genes at last? Trends Genet 2005; 21: 518–25. 5 Butcher L M, Meaburn E, Knight J et al. SNPs, microarrays and pooled DNA: identification of four loci associated with mild mental impairment in a sample of 6000 children. Hum Mol Genet 2005; 14: 1315–25. 6 Rutter M. The interplay of nature, nurture, and developmental influences: the challenge ahead for mental health. Arch Gen Psychiatry 2002; 59: 996–1000. 7 Moffitt T E, Caspi A, Rutter M. Strategy for investigating interactions between measured genes and measured environments. Arch Gen Psychiatry 2005; 62: 473–81. 8 Caspi A, McClay J, Moffitt T E et al. Role of genotype in the cycle of violence in maltreated children. Science 2002; 297: 851–4. 9 Caspi A, Sugden K, Moffitt T E et al. Influence of life stress on depression: moderation by a polymorphism in the 5-HTT gene. Science 2003; 301: 386–9. 10 Kendler K S, Kuhn J W, Vittum J, Prescott C A, Riley B. The interaction of stressful life events and a serotonin transporter polymorphism in
PSYCHIATRY 4:12
5
© 2005 The Medicine Publishing Company Ltd
Behavioural genomics: an integrated approach
Twin studies of psychiatric disorders Schizophrenia Autism
Philip Asherson
Bipolar disorder Unipolar depression Attention deficit hyperactivity disorder Childhood fatigue 0.0
dizygote
Family, twin and adoption studies of common behavioural disorders have highlighted the importance of both genes and environments. For almost all human behaviours we find that genetic variation accounts for around 40% of phenotypic variation, with higher levels of heritability for a number of important psychiatric conditions including schizophrenia, bipolar disorder, major depression, autism and attention deficit hyperactivity disorder (ADHD; Figure 1). At the same time, the molecular genetic revolution heralded by the near-complete sequencing of the human genome in 2000, and rapidly advancing techniques to interrogate human genetic variation, has opened the way for investigators to identify the genes involved and the ways that genetic variation can influence human behaviour. This will be a complex task since human behaviours do not result from simple one-to-one relationships with aetiological factors, but rather a complex net of co-acting, correlated and interactional factors. Despite the inherent complexity that is expected, combining quantitative and molecular genetic strategies with social, developmental, environmental, neurobiological and psychological methods holds the promise of elucidating major components of ‘aetiological networks’. The challenge is to embrace this complexity while delineating key functions that can be used to further our knowledge of the development of human behaviours with consequent refinement of our conceptual ideas and practical outcomes in terms of prevention and treatment. This article provides an overview of some of the ways in which genetic strategies are being used to bring together diverse areas of investigation and make best use of emerging technologies in the investigation of behavioural traits and psychiatric disorders.
0.4
0.6
0.8
1.0
1.2
monozygote
a) Monozygote (identical) twin and dizygote (non-identical) twin correlations for major psychiatric disorders. The proportion of phenotypic variance attributable to genetic variance can be estimated by doubling the difference in the correlations between monozygote and dizygote twins.
Schizophrenia Autism Bipolar disorder Unipolar depression Attention deficit hyperactivity disorder 0.0
environment
0.2
0.4
0.6
shared environment
0.8
1.0
1.2
additive
b) Variance explained by additive, shared environment and residual environment components for the major psychiatric disorders. Variance in common environment does not have a significant role an any of these disorders, although environment may still play a key role through gene– environment interaction. The non-shared environmental component reflects influences that bring about differences between siblings. This component includes error variance.
1
by investigating so-called ‘candidate’ genes. Such an approach has, for example, been successful in the investigation of ADHD in children where several genetic variants within dopamine system genes have been associated with the disorder.1,2 Although such findings do not identify novel genes or gene systems, they shift the focus of research from gene identification to gene function and investigation of the neurobiological and neuropsychological mechanisms that mediate genetic effects on behaviour.3 The other major strategy is to use positional cloning methods to locate genetic variants that are linked or associated with human behaviours. An efficient method for screening the entire genome is to use linkage-mapping methods, usually by running genetic markers that span the entire genome in large samples of affected sibling pairs. For example, meta-analyses of 20 genome scans for schizophrenia identified a number chromosomal regions that consistently provide evidence for the localization of susceptibility genes. More importantly, replicated findings have identified individual genes within some of the linked regions, such as neuregulin-1 (NRG1) on chromosome 8p12 and dysbindin (DTNBP1) on chromosome 6p22.4 These are important findings in psychiatric genetics since they are some of the first genes associated with a
Gene mapping and ‘SNP sets’ Methods for mapping genes for complex disorders are described by Norton and colleagues (this issue). Since multiple genetic variants are expected, each conferring only a small risk to human behaviour, statistically powerful approaches are required. Two main strategies have been adopted. First, testing a priori hypotheses
Philip Asherson is Professor of Molecular Psychiatry at the MRC Social, Genetic and Developmental Psychiatry Research Centre at the Institute of Psychiatry, King’s College London, UK. He holds an Honorary Consultant post with the South London and Maudsley Health Trust where, in collaboration with senior colleagues, he runs a national specialist clinic for adults with attention deficit hyperactivity disorder (ADHD). His research interests include genetic mapping studies of ADHD.
PSYCHIATRY 4:12
0.2
1
© 2005 The Medicine Publishing Company Ltd
BEHAVIOURAL GENOMICS
complex behavioural disorder that have been identified following a positional cloning rather than candidate gene approach. Future studies will adopt whole genome association scanning methods – a positional cloning approach that searches for genetic associations using many thousands of markers spanning the entire genome. Work in this area has been pioneered using a DNA pooling method to scan around 10,000 single nucleotide polymorphisms (SNPs) for association with mild mental impairment (MMI).5 Four genetic variants were identified with an average effect size of only 0.2%. Despite the small size of the genetic effects of each individual SNP, the data can be combined together in an additive fashion to provide an informative ‘SNP set’. The principle of aggregating together associated SNPs to generate a composite genetic index is thought to be important in improving the reliability and predictive value for complex traits. Furthermore, as new associated SNPs are identified these can be added to the SNP set to increase the overall effect size of the molecular genetic data. For example Butcher et al.,5 predict that further screening of the latest 100,000 SNP arrays will increase the variance explained by the SNP set to around 8%.
Diagrammatic representation of gene–environment interactions MAOA SERT
Maltreatment Life events
Disruptive behaviour/aggression Depression 4.5
environment +
Symptom score
4.0 3.5 3.0 2.5 2.0
environment –
1.5 1.0 0.5 0
AA
AB
BB
The studies of Caspi and colleagues found no main effect of genotype. Genotype effects were seen only when individuals were exposed to known environmental risk factors. AA, AB and BB represent 3 genotypes with 0, 1 and 2 risk alleles, respectively. The environmental risk exposed group (+) and environmental risk non-exposed group (–) are represented by the blue and orange lines, respectively.
Gene–environment interactions
2
To date most genetic studies in neuropsychiatry have focused on the detection of genetic variants that have a main effect on the risk for behavioural disorders. However, it has been known for a long time that gene–environment interactions are likely to play an important role on risk for behavioural disorders and in some cases will be present in the absence of main effects. What is not widely understood is that the heritable component estimated from family, twin and adoption studies, indexes both the main effects of genes plus the effects of gene–environment interactions. For this reason environmental research remains critical to our understanding of psychiatric disorders, even for those that are highly heritable.6 An emerging literature on the effects of gene–environment interactions on behavioural disorders and an outline of the methodological issues has recently been reviewed.7 Using a longitudinal population sample from Dunedin in New Zealand, Caspi, Moffitt and colleagues reported three key findings (Figure 2). First they hypothesized that a functional polymorphism in the promoter region of the gene encoding the neurotransmitter metabolizing enzyme monoamine oxidase A (MAOA), would moderate the effect of child maltreatment in the cycle of violence. Their results showed that maltreated children with genotypes that conferred low levels of MAOA expression were more likely to develop conduct disorder, antisocial personality disorder and adult violent criminal behaviour than children possessing high activity variants of MAOA.8 In the second study they hypothesized that a functional variant in the promoter region of the serotonin transporter gene (HTT) would moderate the influence of stressful life events on depression. They found that individuals with 1 or 2 copies of the HTT short allele exhibited more depressive symptoms, diagnosable depression, and suicidality following stressful life events than individuals homozygous for the long allele.9 This finding has been replicated in several further studies and is now one of the most consistent findings in psychiatric genetics.10–12 In the third study, they reported that a functional variant of the catechol-O-methyltransferase gene (COMT Val158Met) moderates the risk of cannabis use by adolescents on the later development of psychosis in adult life.13
These three findings highlight the importance of considering the effects of environmental exposure in the search for genetic risk factors. Moffitt, Caspi and Rutter noted several important methodological points in their review.7 First, they noted that several of their initial reports were subsequently replicated, indicating the robust nature of some gene–environment interactions on human behaviour. Second, that in each case the environmental risk involved had shown an association with the disorder in previous epidemiological studies. In other words, they were known environmental pathogens. Third, in several of the reports it was noted that there was no main effect of gene alone. This has important implications since the search for genetic associations with behavioural disorders would have been unsuccessful in these examples if interaction with the environmental pathogen had not been taken into account. These findings have promoted a new wave of interest in gene–environment research, although identifying such interactions remains a major challenge. Unlike DNA variation, where we know that we will soon be able to scan the entire human genome for associated genetic variants, environmental research will depend on careful selection of appropriate and measurable environmental risks. This is necessarily a time-consuming and costly process and requires reasonable prior hypotheses to be generated. Once a specific gene–environment interaction has been identified the next set of questions is to clarify the precise mechanisms involved. This is not always immediately obvious since apparent interactions with an environmental variable may have several causes. As an example, we consider the recent report of an interaction between the mother’s use of alcohol during pregnancy and genetic variants of the dopamine transporter gene (DAT1) on the risk for development of childhood attention deficit hyperactivity disorder (ADHD).14 In this study, only those individuals carrying the DAT1 risk alleles whose mothers used alcohol during the pregnancy showed an increased risk for ADHD. There are, however, several plausible explanations for this observation. First, there may be a direct toxic effect of alcohol on the developing fetus. Further work to establish this causal link needs to focus on more
PSYCHIATRY 4:12
2
© 2005 The Medicine Publishing Company Ltd
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detailed analysis that considers the timing and amount of alcohol used by mothers during the pregnancy. However, other causal relationships need to be considered since maternal drinking may be correlated with parental behaviours that could act as more proximal risk factors, such as levels of maternal stress, quality of parenting and maternal psychopathology, including ADHD. Interactions with variables that reflect parental behaviour may also index genetic loading consistent with the increased co-transmission of interacting genes (gene–gene interaction also referred to as epistasis). For example, in this study we also found preliminary evidence for gene–environment correlation between the DAT1 risk alleles and maternal use of alcohol. Although we controlled for this in our analysis this highlights the complexity of interpreting gene–environment effects where genes cause change in parent as well as offspring behaviour. Well-designed epidemiological studies are one approach, but direct testing of environmental hypotheses may require the use of animal behavioural and genetic models and a focus on more direct neurobiological measures of brain function in addition to the analysis of behavioural phenotypes.
differences is not sufficient to confidently identify a measure as a candidate endophenotype. Another problems is sample size, since many of the current studies lack statistical power for small to moderate genetic effects and would reliably detect only major gene effects. The existence of major gene rather than minor polygene effects will have a very large bearing on the success of endophenotype studies where generating large and reliable datasets is costly and time-consuming, such as many current neuroimaging techniques. As in other areas of genetic research on human behaviour replication of initial findings and subsequent meta-analysis remain essential steps to identify true findings. It is also important to consider whether any single endophenotype measure provides the most effective method for the identification of behavioural genes, by parsing complex behavioural disorders into more genetically homogeneous components. The work of Robert Plomin and colleagues on the latent construct of general cognitive ability (‘g’) has been hugely influential in this field.16, 17 Genetic models of cognition began by proposing a single fundamental process. However, this model was modified, as the different components of cognitive ability were delineated (e.g. verbal, spatial, memory, maths, processing speed) and the major model became one of multiple independent cognitive pathways. The perception was that each cognitive function was causally linked to a specific set of genetic factors that mapped onto independent neurocognitive pathways. Genetic model fitting did not, however, support this model (Figure 3). Multivariate genetic analysis that quantifies the extent of the shared genetic influences between measured variables identified a common genetic factor termed ‘g’ that explains almost all the genetic variance for the various components of general cognitive ability. So, at least for general cognitive ability, investigation of a common factor derived from multiple correlated variables is the most effective way to identify the genetic variants associated with the various components of cognition. When considering other behavioural disorders this model should be born in mind and one-to-one relationships between genes and various neurobiological variables should not be assumed until they have been explicitly tested using genetic model fitting approaches. Further delineation of the links between different brain functions, cognitions and behaviours will come once specific genes and environmental factors have been identified. For example, once informative ‘SNP sets’ have been identified these can be used to identify the neurobiological processes that mediate the effects of the SNP set on behaviour.5
Endophenotypes The use of endophenotypes or intermediate phenotypes has been suggested as a potential panacea to unravelling the complexity of human behavioural disorders. Gottesman and Gould15 describe the concept of endophenotypes as ‘measurable components unseen by the unaided eye along the pathway between disease and distal genotype’. Endophenotypes for human behaviour therefore include a wide range of measures of brain function and processes including neurophsyiology, functional and anatomical neuroimaging, neuropsychology and biochemical and endocrinological assays. The overall aim is to identify the processes and mechanisms that mediate genetic effects on behaviour. Gottesman provides a set of criteria for endophenotypes.15 • The endophenotype should be associated with the clinical disorder/behaviour in the population. • The endophenotype should be heritable. • The endophenotype should be primarily state independent in the sense that it should manifest itself whether or not the illness is active or not. This criterion has greatest relevance to episodic disorders such as depression or bipolar disorder where behavioural manifestations show fluctuations over time. • The endophenotype is familial so that both the clinical disorder and endophenotype co-segregate within families. Using quantitative genetics (family, twin and adoption studies) we can use model-fitting approaches to identify whether there are shared genetic influences between putative endophenotypes and the behavioural disorder (e.g. Andreou and Kuntsi, pages 27–30, McGloughlin et al., pages 14–18). • Related to the previous criteria, endophenotypes should be found more frequently among close relatives of affected probands than in the general population. The complexity of human behaviour and recent advances in our ability to measure different facets of brain function, has led many current investigators to adopt an endophenotype approach. The relative ease of genotyping a few candidate gene markers has, however, meant that much of this research has gone forward with little prior information on the status of the measure as a true endophenotype. For example, the demonstration of case-control
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Quantitative trait locus approaches and animal behaviour Due to the complexity of human behavioural disorders and the difficulties in investigating human brain function and controlling for genetic and environmental variation, animal models are an important adjunct to human studies. Animal research within psychiatry has mainly focused on comparisons between one or a few animals that are thought to model particular disorders, and the investigation of genetic manipulations such as targeted gene knockouts and gene mutations. Such approaches have been instrumental in the development and testing of psychiatric medications. Furthermore, some experimental paradigms have been very sophisticated, such as the demonstration that polymorphisms of the serotonin transporter gene interact with the effects of early rearing on behaviour in rhesus monkey neonates; providing direct 3
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Models of cognitive performance patterns throughout the population
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Multivariate quantitative genetic studies indicate that a model of multiple correlated cognitive processes provides the best explanation for the observed patterns of cognition performance throughout the population. Similar analyses have not been completed for processes thought to underlie common psychiatric disorders and it is therefore premature to conclude whether complex behavioural disorders result from multiple independent processes or multiple correlated processes.
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experimental evidence for the gene–environment interaction identified by Caspi and colleagues in the Dunedin sample.9 Such approaches are, however, limited in their ability to model complex polygenetic traits. The ability to model complex behavioural traits using quantitative trait locus (QTL) approaches in mouse is possible using strategies outlined by Schalkwyk (pages 18–21). Behavioural research has focused mainly on the use of rodents and measures such as activity level, response to novel objects, ability to solve mazes, response to anxiety-provoking stimuli and accuracy and speed of reactions. Clearly one of the difficulties in using animal models is the identification of mouse behaviours that are the equivalent of human behaviours. This is particularly difficult for behavioural phenotypes such as schizophrenia where diagnosis depends on verbal accounts of mental states from affected individuals, although greater progress has been made in the analysis of traits such as anxiety, depression, alcohol use and general cognitive ability. The use of endophenotypes is an alternative approach since cognitive experimental and neurobiological measures may show greater cross-species similarities than more complex behavioural measures (Figure 4). One strategy that takes advantage of quantitative genetic approaches is to look for genetic correlations between cognitive and behavioural paradigms across inbred strains, recombinant inbred strain panels or outbred mouse strains. An example of this type of work is the demonstration of a general cognitive ability (g) factor in outbred heterogeneous stock (HS) mice.18 HS is a genetically outbred line of mice established more than 30 years ago from an 8-way cross of eight inbred mouse strains. Galsworthy and colleagues18 compared the performance of 40 HS mice across a battery of diverse cognitive tasks. All measures of ability loaded positively onto a principal component that accounted for 31% of the variance, suggesting the presence of a common factor of general cognitive ability. A general cognitive ability factor (g) therefore appears to underlie the performance of HS mice on a battery tapping diverse cognitive demands, paralleling the identification of the latent construct ‘g’ in the human literature. In a
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Phenotypic analysis of general cognitive ability Phenotypic ‘g’ accounts for 40% of the variance
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Memory Phenotypic analysis of general cognitive ability finds that a common factor (‘g’) explains around 40% of the phenotypic variance. Different domains of cognition show high genetic correlations indicating that a common genetic factor (‘genetic g’) accounts for almost all of the general cognitive ability are shared across the various domains of cognition.
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similar way we can investigate whether paradigms for a disorder such as ADHD (activity level, impulsivity, performance on tests of attention, response variability) show a similar pattern of genetic correlations in humans and mouse. Subsequent studies can use methods for complex trait analysis in mouse to map behavioural genes, map out gene expression patterns and study gene–gene and gene–environment interactions.19
the prediction of episodes of major depression: a replication. Arch Gen Psychiatry 2005; 62: 529–35. 11 Kaufman J, Yang B Z, Douglas-Palumberi H et al. Social supports and serotonin transporter gene moderate depression in maltreated children. Proc Natl Acad Sci USA 2004; 101: 17316–21. 12 Eley T C, Sugden K, Corsico A et al. Gene-environment interaction analysis of serotonin system markers with adolescent depression. Mol Psychiatry 2004; 9: 908–15. 13 Caspi A, Moffitt T E, Cannon M et al. Moderation of the effect of adolescent-onset cannabis use on adult psychosis by a functional polymorphism in the catechol-O-methyltransferase gene: longitudinal evidence of a gene X environment interaction. Biol Psychiatry 2005; 57: 1117–27. 14 Brookes K, Mill J, Guindalini C et al. A common haplotype of the dopamine transporter gene is associated with attention deficit hyperactivity disorder and interacts with prenataleExposure to alcohol. Arch Gen Psychiatry 2005; in press. 15 Gottesman I I, Gould T D. The endophenotype concept in psychiatry: etymology and strategic intentions. Am J Psychiatry 2003; 160: 636–45. 16 Plomin R. Genetics and general cognitive ability. Nature 1999; 402: C25–9. 17 Plomin R, Spinath F M. Genetics and general cognitive ability (g). Trends Cogn Sci 2002; 6: 169–76. 18 Galsworthy M J, Paya-Cano J L, Monleon S, Plomin R. Evidence for general cognitive ability (g) in heterogeneous stock mice and an analysis of potential confounds. Genes Brain Behav 2002; 1: 88–95. 19 Churchill G A, Airey D C, Allayee H et al. The collaborative cross, a community resource for the genetic analysis of complex traits. Nat Genet 2004; 36: 1133–7. 20 McGuffin P, Plomin R. A decade of the Social Genetic Development Centre at the Institute of Psychiatry. Br J Psychiatry 2004; 185: 280–2.
Conclusion The new genetics heralded by the near completion of the human genome sequence was rapidly followed by an exponential rise in the number of identified genetic variants. The goal of behavioural genomics is shifting from gene discovery towards gene functionality at the level of molecular mechanisms and brain processes and a focus on interaction with environmental pathogens.20 Quantitative genetic studies have led to a perceptual shift where psychiatric disorders are perceived as quantitative traits that share genetic influences with other developmental behavioural and cognitive traits. Molecular genetic studies have confirmed a priori hypotheses for some disorders and identified novel genes for others and identification of many additional behavioural genes is expected in the coming decade. Combining genetic, environmental and neurobiological research strategies has the potential to delineate the causal links between behavioural traits, psychiatric conditions and developmental course, including the persistence/desistance of psychiatric symptoms and comorbidity between psychiatric disorders and traits. As a result we can look forward to new insights and potential advances in our treatment of previously intractable problems.
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