Skip to main content Accessibility help
×
Home
Hostname: page-component-cf9d5c678-m9wwp Total loading time: 0.389 Render date: 2021-08-01T17:19:27.810Z Has data issue: true Feature Flags: { "shouldUseShareProductTool": true, "shouldUseHypothesis": true, "isUnsiloEnabled": true, "metricsAbstractViews": false, "figures": true, "newCiteModal": false, "newCitedByModal": true, "newEcommerce": true, "newUsageEvents": true }

Examining the comorbidity of ADHD-related behaviours and conduct problems using a twin study design

Published online by Cambridge University Press:  02 January 2018

Anita Thapar
Affiliation:
Child and Adolescent Psychiatry Section, Department of Psychological Medicine, University of Wales College of Medicine, Cardiff, UK
Richard Harrington
Affiliation:
University of Manchester Department of Child and Adolescent Psychiatry, Royal Manchester Children's Hospital, Manchester, UK
Peter McGuffin
Affiliation:
Social Genetic and Developmental Psychiatry Research Centre, Institute of Psychiatry, London, UK
Rights & Permissions[Opens in a new window]

Abstract

Background

Although attention-deficit hyperactivity disorder (ADHD) and conduct disorder (CD) frequently co-occur, the underlying mechanisms for this comorbidity are not well understood.

Aims

To examine whether ADHD and conduct problems share common risk factors and whether ADHD+CD is a more heritable variant of ADHD.

Method

Questionnaires were sent to 2846 families. Parent-rated data were obtained for 2082 twin pairs and analysed using bivariate genetic analysis and a liability threshold model approach.

Results

The overlap of ADHD and conduct problems was explained by common genetic and non-shared environmental factors influencing both categories. Nevertheless, the two categories appeared to be partly distinct in that additional environmental factors influenced conduct problems. It appeared that ADHD+CD was a genetically more severe variant of ADHD.

Conclusions

Conduct problems and ADHD share a common genetic aetiology; ADHD+CD appears to be a more severe subtype in terms of genetic loading as well as clinical severity.

Type
Developmental Psychopathology Papers, Part 2
Copyright
Copyright © Royal College of Psychiatrists, 2001 

It has consistently been observed that attention-deficit hyperactivity disorder (ADHD) and conduct disorder commonly co-occur, and family and twin study findings suggest that much of this overlap is due to a common genetic aetiology (Reference Silberg, Rutter and MeyerSilberg et al, 1996; Reference Faraone, Biederman and MenninFaraone et al, 1998). A separate question is whether the sub-group with both ADHD and conduct disorder (ADHD+CD) is distinct from those with pure ADHD. Children who fulfil ICD-10 diagnostic criteria for both hyperkinetic disorder and conduct disorder (World Health Organization, 1992) are separately categorised under hyperkinetic conduct disorder. There is some clinical support for this distinction in that most studies suggest that ADHD+CD is a more severe condition than either disorder alone (Reference Bark ley, Fischer and EdelbrockBarkley et al, 1990; Reference Jensen, Martin and CantwellJensen et al, 1997; Reference Kuhne, Schachar and TannockKuhne et al, 1997), although findings have not been entirely consistent (Reference Leung, Ho and LukLeung et al, 1996; Reference Taylor, Chadwick and HeptinstallTaylor et al, 1996). Family study findings also suggest that ADHD+CD represents a distinct familial subtype of ADHD (Reference Faraone, Biederman and MonuteauxFaraone et al, 2000) although twin data are needed to test whether ADHD+CD is genetically distinct or a more severe category of ADHD in terms of genetic loading.

METHOD

Our aims were first to replicate and extend previous twin work on hyperactivity and conduct symptom scores (Reference Silberg, Rutter and MeyerSilberg et al, 1996) by examining whether common genetic and environmental risk factors account for the comorbidity between categorically defined ADHD-related problems and conduct problems, and second to use a liability threshold model to examine whether a comorbid category of ‘ADHD +CD’ represents a genetically more severe variant of ADHD-related behaviours.

Participants

The sample consisted of school-aged twins (aged 5-17 years) included on the population-based Greater Manchester twin register. This is a register of 2846 live twin births who were identified from community child-health databases for nine health districts in Greater Manchester and Lancashire. The characteristics of the twin register and responding families have been described in detail elsewhere (Reference Thapar, Ross and HarringtonThapar et al, 2000). The final sample for whom data were available included 767 female twin pairs, 715 male twin pairs and 600 opposite-sex twin pairs. Of the 1920 pairs for whom zygosity could be assigned, 731 (38.1%) were monozygotic, 590 (30.7%) were same-gender dizygotic and 599 (31.2%) were opposite-gender dizygotic; 162 twin pairs could not be assigned zygosity because of incomplete or ambiguous responses.

Measures

Questionnaires were mailed to the families of the twins; non-responders were sent two postal reminders and given one telephone reminder. The overall response rate was 73% (2082/2846). A standard twin similarity questionnaire that has over 90% accuracy (Reference Cohen, Dibble and GraweCohen et al, 1975) was used to assign zygosity. Parent ratings of ADHD symptoms for each twin were obtained using a modified version of the DuPaul ADHD rating scale (Reference DuPaulDuPaul, 1981). The original scale included the 14 DSM—III—R symptoms of ADHD (American Psychiatric Association, 1987) and we added a further four items to cover additional ICD-10 symptoms of hyperkinetic disorder. Each symptom can be rated on a four-point scale of severity, and each item was summed to generate a total ADHD score. Hyperactivity was then defined categorically using the 80th centile as a cut-off point, chosen on the grounds of previously reported validating data (Reference Thapar, Ross and HarringtonThapar et al, 2000), and in accordance with the approach adopted by others when analysing extreme scores in twins.

Parents were also asked to complete the Rutter A scale (Reference Rutter, Tizard and WhitmoreRutter et al, 1970). This scale includes five conduct items, and the scores for these were summed to obtain a total conduct symptom score. A categorical measure of conduct problems was then generated by again using a cut-off above the 80th centile. Children who were assigned to both the ‘ADHD+CD’ and ‘CD’ categories were labelled as ‘ADHD+CD’ for the liability threshold model analyses.

Although diagnostic criteria were not used, for the purposes of simplicity the following discussion refers to the broadly defined study categories as ‘ADHD-related behaviours’ and ‘Conduct problems’, and for the subgroup analysis the terms ‘pure ADHD’, ‘pure CD’ and ‘ADHD+CD’ are given in quotation marks to emphasise that these are not diagnostic categories.

Genetic analysis

Univariate and bivariate genetic model fitting

Monozygotic (MZ) and dizygotic (DZ) probandwise concordance rates were calculated and the raw categorical twin data were then summarised in the form of polychoric and asymptotic covariance matrices which were generated using PRELIS (Reference Joreskog and SorbomJoreskog & Sorbom, 1988). Genetic models were then fitted to these matrices with the structural equation modelling package Mx (Reference NealeNeale, 1997), using the asymptotic weighted least squares method (Reference Neale and CardonNeale & Cardon, 1992).

The full univariate genetic model for a single phenotype includes additive genetic factors (A), shared environmental factors (C) and non-shared environmental factors (E). The overall goodness of fit of a model is given by a chi-squared value, with a smaller value indicating a better fit. Reduced models where additive genes, shared environment and both of these factors are dropped (CE, AE, E models) can then be tested and compared against the fit of the full model by examining the difference in the χ2 goodness-of-fit values.

This method can then be extended to examine to what extent shared genetic and/or environmental influences explain the covariation or correlation between two phenotypes. Bivariate model fitting using a Cholesky decomposition (see Reference Neale and CardonNeale & Cardon, 1992) was used to examine the overlap of categorically defined hyper-activity and conduct problems. The full bivariate model (see Fig. 2) includes a common genetic influence and common non-shared environmental influence on both ‘ADHD’ and ‘CD’ (shared environment was not included, given the results of the univariate analysis for ‘ADHD’; Reference Thapar, Ross and HarringtonThapar et al, 2000), and specific genetic, specific shared environmental and specific non-shared environmental factors for conduct problems. Reduced models where the common factors and specific factors were dropped in turn were tested. The model accepted as the most satisfactory explanation of the data was chosen on the basis of the goodness of fit and parsimony (simplicity of the model). In the results section we also present Akaike's Information Criteria (AIC; Reference Neale and CardonNeale & Cardon, 1992) for each model, which provides an indication of goodness of fit and parsimony. The model with the lowest AIC value is chosen as the most satisfactory (Reference Neale and CardonNeale & Cardon, 1992).

Using a liability threshold model to examine the relationship between ‘ADHD+CD’ and ‘pure ADHD’

Twins were assigned to a broad category if they were either ‘ADHD+CD’ or ‘pure ADHD’ and to a narrow category if they had been assigned to the ‘ADHD+CD’ group.

Probandwise concordance rates for the broad and narrow categories were first calculated. For categorical data, the correlation between twins (tetrachoric correlation) can be estimated from the twin concordance and prevalence rates of the disorder assuming an underlying continuously distributed liability. A two-threshold liability model (Fig. 1) (Reference Reich, Rice and CloningerReich et al, 1979) was fitted using the FORTRAN program TWIN2. This uses the GEMINI subroutine (Reference Lalouel, Morton, Rao and LalouelLalouel, 1983) to minimise a goodness-of-fit χ2. Applying the two-threshold model entails estimating four correlations (broad proband—broad co-twin, broad proband—narrow co-twin, narrow proband—broad co-twin and narrow proband—narrow co-twin). We assume no shared environmental effects, so that the MZ correlations are double the DZ correlations. First, a general model was tested in which all four correlations were estimated. A nested isocorrelational model (Reference Reich, Rice and CloningerReich et al, 1979), which tests whether ‘ADHD+CD’ is a more extreme genetic variant than ‘pure ADHD’ but lies on the same continuum of liability, was then fitted (Fig. 1). In this model, as the name implies, the four correlations are constrained to be equal. An independent model was also applied to test whether ‘pure ADHD’ and ‘ADHD+CD’ are genetically distinct. Here the narrow—broad and broad—narrow twin correlations are constrained to be zero. The models were compared using the difference in χ2 (see Reference Reich, Rice and CloningerReich et al, 1979, for detailed explanation).

Fig. 1 Liability threshold model: the two-threshold (isocorrelational) type.

Fig. 2 Full bivariate model for ADHD-related problems and conduct problems; ADHD, attention-deficit hyperactivity disorder; CD, conduct disorder; A, additive genetic factors; C, shared environmental factors; E, non-shared environmental factors.

RESULTS

Univariate genetic models

Previous analyses suggested no significant gender effects (Reference Thapar, Ross and HarringtonThapar et al, 2000). Given that this study focused on categorical data, opposite-gender DZ twin pairs were not included.

Table 1 shows the results of univariate genetic model fitting for ADHD-related behaviours and conduct problems (for more detailed results for ADHD-related behaviours such as teacher ratings and continuous data, see Reference Thapar, Ross and HarringtonThapar et al, 2000). For conduct problems, an AE model where shared environmental effects are dropped results in a significant deterioration in fit compared with the full model (χ2=8.3, d.f.=1). A CE model also provides a poorer fit (χ2=11.65) and a model of no familial transmission (E) results in a very much worse fit. We thus accept the ACE model as providing the most satisfactory explanation for conduct problems with a heritability estimate of 47%, a shared environment component of 36% and the non-shared environment component estimated as 17%. For ADHD-related behaviours the most acceptable model is an AE model with a heritability estimate of 80%.

Table 1 Univariate genetic model fitting for ADHD-related problems and conduct problems

Model h2 c2 e2 χ 2 d.f. P AIC
Conduct problems
ACE * 0.47 0.36 0.17 0 0 - 0
CI 0.20-0.75 0.11-0.60 0.08-0.26
AE 0.86 [0] 0.14 8.3 1 0.004 6.3
CE [0] 0.77 0.23 11.65 1 0.001 9.65
E [0] [0] 1 654 2 <0.001 650
ADHD-related problems
ACE 0.80 0.00 0.20 0.056 0 - 0.056
AE * 0.80 [0] 0.20 0.056 1 0.812 -1.94
CI 0.73-0.87 0.11-0.29
CE [0] 0.72 0.28 28.9 1 0 26.9
E [0] [0] 1 561 2 0 557

Bivariate genetic model fitting

The results of the bivariate model fitting (see Fig. 2 for full model) are shown in Table 2.

Table 2 Bivariate genetic model fitting for ADHD-related problems and conduct problems (see Fig. 2 for full model)

χ 2 d.f. P AIC
Full model 4.05 7 0.774 -9.95
Drop common factors
drop a2 322.25 8 0 306.25
drop e2 11.092 8 0.197 -4.908
Drop specific factors
drop a3* 4.08 8 0.850 -11.92
drop c3 11.459 8 0.177 -4.54
drop e3 13.21 8 0.105 -2.79

It can be seen that neither the common genetic (a2) nor the non-shared environmental component (e2) for conduct problems can be dropped without a significant deterioration in fit. However, the specific additive genetic factor (a3) for conduct problems can be removed. Given the results of the univariate model fitting for conduct problems, not surprisingly a reduced model without a shared environment component (c3) for conduct problems results in a deterioration of fit. Similarly, a specific non-shared environment component (e3) for conduct problems is also needed to explain the data. The accepted model on grounds of fit and parsimony (lowest AIC value) is shown in Fig. 3.

Fig. 3 Accepted bivariate model for ADHD-related problems and conduct-related problems; ADHD, attention-deficit hyperactivity disorder; CD, conduct disorder; A, additive genetic factors; C, shared environmental factors; E, non-shared environmental factors.

Examining ADHD+CD using a liability threshold model approach

In Table 3, the probandwise concordance rates for the broad and narrow categories are presented for MZ and DZ twins. The results of threshold analysis are shown in Table 4. For the isocorrelational model testing whether ADHD and ‘ADHD+CD’ lie on the same continuum of liability, a single correlation was estimated and this resulted in no significant deterioration in fit compared with the general model where four correlations were estimated (χ2=2.48, d.f.=3, P=0.48). However, the independent model, which tests whether the broad and narrow categories are transmitted independently, that is whether they are genetically distinct, provided a very poor fit (χ2=229, d.f.=2, P<0.001). On grounds of parsimony we thus accept the isocorrelational model, where ‘ADHD+CD’ (the narrow category) represents a genetically more extreme variant of ADHD, as providing the most satisfactory explanation of the data.

Table 3 Probandwise concordance rates for broad and narrow categories of ADHD-related problems

Proband Concordance rates (%)
Broad Narrow
MZ twins
Broad 79 53
Narrow 83 74
DZ twins
Broad 54 37
Narrow 60 47

Table 4 Results of liability threshold model fitting

r11 r12 r21 r22 χ 2 χ 2 difference P
General model 0.39 0.36 0.36 0.41 0.77
Independent model 0.39 0 0 0.41 229 228 (2 d.f.) < 0.001
Isocorrelational model 0.38 0.38 0.38 0.38 3.25 2.48 (3 d.f.) 0.48

DISCUSSION

Conduct problems and ADHD share a common genetic aetiology

We first considered ADHD-related behaviours and conduct problems as two separate phenotypes and examined the genetic and environmental contribution to the comorbidity of these two categories. Bivariate genetic analysis showed that the genetic contribution to conduct problems was entirely explained by the same genetic factor influencing ADHD-related behaviours. The comorbidity between the two categories was mostly explained by this common genetic risk factor although a common non-shared environmental factor also contributed to the phenotypic overlap. These findings are consistent with family studies based on clinical diagnoses of ADHD, where ADHD and conduct disorder have been shown to share a common familial risk (Faraone et al, Reference Faraone, Biederman and Keenan1991, Reference Faraone, Biederman and Mennin1998). The twin study findings suggest that this common familial risk is genetic in origin. Our findings are similar to those of Silberg et al (Reference Silberg, Rutter and Meyer1996), who found that a common genetic influence accounted for the covariation in symptoms of ADHD and conduct disorder. It is interesting that genetic findings on the comorbidity of ADHD-related behaviours and conduct problems from these three studies have been so consistent, despite phenotypic definition having ranged from questionnaire symptom counts and questionnaire-derived categories to interview-based clinical diagnosis.

Additional environmental influences on conduct problems

Despite the overlap of ADHD-related behaviours and conduct problems, inspection of our twin data strongly supported the distinction of these two categories, in that for both MZ and DZ twins ADHD-related behaviours in one twin rarely predicted conduct problems in the other, and vice versa. The bivariate genetic findings more formally support a degree of aetiological distinction of ADHD-related behaviours and conduct problems in that additional shared environmental and non-shared environmental factors were found for conduct problems. A considerable amount of clinical research has focused on examining the differences between ADHD and conduct disorder. Although there have been some inconsistencies in findings, most results suggest that ADHD and conduct disorder differ in terms of outcome (Reference Taylor, Chadwick and HeptinstallTaylor et al, 1996) and in their pattern of correlates, with ADHD being more commonly associated with neurodevelopmental problems while conduct disorder shows a greater association with social adversity (Reference Taylor, Sandberg and ThorleyTaylor et al, 1991; Reference Schachar and TannockSchachar & Tannock, 1995; Reference Leung, Ho and LukLeung et al, 1996). Our finding of a shared environmental component for conduct problems is in keeping with clinical and epidemiological research, which has consistently shown that conduct disorder is strongly associated with social and family adversity (Reference Rutter, Giller and HagellRutter et al, 1998).

Examining the subgroup of those with both ADHD and conduct problems

The second aim of this study was to examine how ‘ADHD+CD’ is genetically related to ADHD-related behaviours. Using a liability threshold model approach, our results suggest that ‘ADHD+CD’ is a quantitative variant of ADHD-related behaviours and represents a category associated with a higher genetic loading. Twin data have not been used previously to examine this issue, although there have been a series of family study-based papers on this topic (Faraone et al, Reference Faraone, Biederman and Keenan1991, Reference Faraone, Biederman and Mennin1998) and a number of studies have focused on the clinical severity, correlates and outcome of ‘ADHD+CD’ (Reference Jensen, Martin and CantwellJensen et al, 1997; Reference Kuhne, Schachar and TannockKuhne et al, 1997). Most of these studies have shown that ‘ADHD+CD’ is a more severe variant of ADHD (and conduct disorder alone) in so far as it is associated with more severe symptoms (Reference Jensen, Martin and CantwellJensen et al, 1997; Reference Kuhne, Schachar and TannockKuhne et al, 1997) and a worse outcome (Reference Bark ley, Fischer and EdelbrockBarkley et al, 1990; Reference Jensen, Martin and CantwellJensen et al, 1997). Family study findings have suggested that ‘ADHD+CD’ represents a more familial subtype (Reference Faraone, Biederman and MonuteauxFaraone et al, 2000) and our twin findings add a further dimension to this by suggesting that ‘ADHD+CD’ is also a more severe variant of ADHD in terms of genetic loading. One possibility that has to be considered is that our finding of a higher genetic loading for ‘ADHD+CD’ is an artefact of higher ADHD symptom scores in this subgroup. Although we found that ADHD symptom scores were significantly higher in the ‘ADHD+CD’ group compared with the ‘pure ADHD’ group, further analysing twin concordance rates for the ‘ADHD+CD’ group suggested that the genetic findings did not vary according to symptom severity. Moreover, there is now good evidence from twin studies that the genetic aetiology of high ADHD symptom scores is no different from that for scores across the normal range (Reference StevensonStevenson, 1992; Reference Levy, Hay and McStephenLevy et al, 1997). Thus, our results add genetic validational support for the ICD-10 classificatory system whereby ADHD+CD is considered as a category which is related to ADHD, in that hyperkinetic conduct disorder is classified under hyperkinetic disorders, but because it appears to be a more severe genetic (as well as clinical) variant it warrants a separate category.

Limitations

Finally, we have to consider the limitations of this study and how these might have influenced our findings. The results reported here are entirely based on categories defined using questionnaire data, which cannot be equated with clinical diagnoses. Our sample is also population-based, and for these two reasons caution is required in extrapolating the results to clinical populations. Nevertheless, it also has to be emphasised that twin studies based on systematically ascertained population samples are free from the referral and selection biases of clinically referred twin samples. Given that even the largest of population-based twin samples will not yield a sufficient number of twins who meet clinical diagnostic criteria for ADHD and ADHD+CD, at present we have to resort to this sort of phenotypic approximation. However, from an aetiological — and more specifically a genetic — perspective, this may not be such an important problem, given that for ADHD at least there is little evidence to suggest genetic discontinuities between extreme and more broad categories and scores (Reference Levy, Hay and McStephenLevy et al, 1997).

Clinical Implications and Limitations

CLINICAL IMPLICATIONS

  1. Attention-deficit hyperactivity disorder (ADHD)-related behaviours and conduct problems share a common genetic aetiology.

  2. Conduct problems are influenced by additional environmental factors.

  3. When combined with conduct problems, ADHD behaviour appears to represent a genetically more severe variant of ADHD, which supports the validity of the ICD—10 approach to classifying hyperkinetic disorder.

LIMITATIONS

  1. Questionnaire measures were used.

  2. Categories were defined using cut-offs on questionnaires.

  3. A general population sample was used, so the results may not apply to clinical populations.

Acknowledgements

Lydia White, Nicole Perrin Trent, Hilary Hood, Amanda Tew and Justine Porter assisted with establishing the twin register and data collection. Kenny Ross assisted with questionnaire design and data coding. We thank Eric Taylor of the Institute of Psychiatry for his comments on the potential confound of more severe symptoms in the ADHD+CD group.

Footnotes

See editorial, pp. 189–190, this issue.

Declaration of interest

This study was funded by the Medical Research Council (UK) G9608217.

References

American Psychiatric Association (1987) Diagnostic and Statistical Manual of Mental Disorders (4th edn) (DSM–IV). Washington: APA.Google Scholar
Bark ley, R. A., Fischer, M., Edelbrock, C. S., et al (1990) The adolescent outcome of hyperactive children diagnosed by research criteria. I: an 8 year prospective follow up study. Journal of the American Academy of Child and Adolescent Psychiatry, 29, 546557.CrossRefGoogle Scholar
Cohen, D. J., Dibble, E., Grawe, J. M., et al (1975) Reliably separating identical from fraternal twins. Archives of General Psychiatry, 32, 13711375.CrossRefGoogle ScholarPubMed
DuPaul, G. J. (1981) Parent and teacher ratings of ADHD symptoms: psychometric properties in a community-based sample. Journal of Clinical Child Psychology, 20, 245253.CrossRefGoogle Scholar
Faraone, S. V., Biederman, J., Keenan, K., et al (1991) Separation of DSM–III attention deficit disorder and conduct disorder: evidence from a family-genetic study of American child psychiatric patients. Psychological Medicine, 21, 109121.CrossRefGoogle ScholarPubMed
Faraone, S. V., Biederman, J., Mennin, D., et al (1998) Familial subtypes of Attention Deficit Hyperactivity Disorder: a 4 year follow up study of children from antisocial-ADHD families. Journal of Child Psychology and Psychiatry, 39, 10451053.CrossRefGoogle ScholarPubMed
Faraone, S. V., Biederman, J., & Monuteaux, M. C. (2000) Toward guidelines for pedigree selection in genetic studies of attention deficit hyperactivity disorder. Genetic Epidemiology, 18, 116.3.0.CO;2-X>CrossRefGoogle ScholarPubMed
Jensen, P. S., Martin, D. & Cantwell, D. P. (1997) Comorbidity in ADHD: implications for research, practice and DSM–V. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 10651079.CrossRefGoogle ScholarPubMed
Joreskog, K. G. & Sorbom, D. (1988) PRELIS – A Program for Multivariate Data Screening and Data Summarization. A Preprocessor for LISREL (2nd edn). Mooresville, NC: Scientific Software.Google Scholar
Kuhne, M., Schachar, R. & Tannock, R. (1997) Impact of comorbid oppositional or conduct problems on Attention Deficit Hyperactivity Disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 17151725.CrossRefGoogle ScholarPubMed
Lalouel, J. M. (1983) Optimisation of functions. In Methods of Genetic Epidemiology (eds Morton, N. E., Rao, C. C. & Lalouel, J. M.), pp. 235259. New York: Karger Google Scholar
Leung, P. W. L., Ho, T. P., Luk, S. L., et al (1996) Separation and comorbidity of hyperactivity and conduct disturbance in Chinese schoolboys. Journal of Child Psychology and Psychiatry, 37, 841853.CrossRefGoogle ScholarPubMed
Levy, F., Hay, D. A., McStephen, M., et al (1997) Attention-deficit hyperactivity disorder: a category or a continuum? Genetic analysis of a large-scale twin study. Journal of the American Academy of Child and Adolescent Psychiatry 36, 737744.CrossRefGoogle ScholarPubMed
Neale, M. C. (1997) Statistical Modeling. Richmond, VA: Department of Human Genetics, Medical College of Virginia.Google Scholar
Neale, M. C. & Cardon, L. R. (1992) Methodology for Genetic Studies of Twins and Families. Dordrecht: Kluwer.CrossRefGoogle Scholar
Reich, T., Rice, J., Cloninger, C. R., et al (1979) The use of multiple thresholds and segregation analysis in analyzing the phenotypic heterogeneity of multifactorial traits. Annals of Human Genetics, 42, 371390.CrossRefGoogle ScholarPubMed
Rutter, M., Tizard, J. & Whitmore, K. (1970) Education, Health and Behaviour. London: Longman.Google Scholar
Rutter, M., Giller, H. & Hagell, A. (1998) Antisocial Behaviour by Young People. Cambridge: Cambridge University Press.Google Scholar
Schachar, R. & Tannock, R. (1995) Test of four hypotheses for the comorbidity of Attention Deficit Hyperactivity Disorder and Conduct Disorder. Journal of the American Academy of Child and Adolescent Psychiatry, 34, 639648.CrossRefGoogle ScholarPubMed
Silberg, J., Rutter, M., Meyer, J., et al (1996) Genetic and environmental influences on the covariation between hyperactivity and conduct disturbance in juvenile twins. Journal of Child Psychology and Psychiatry, 37, 803816.CrossRefGoogle ScholarPubMed
Stevenson, J. (1992) Evidence for a genetic etiology in hyperactivity in children. Behavior Genetics, 22, 337344.CrossRefGoogle ScholarPubMed
Taylor, E., Sandberg, S., Thorley, G., et al (1991) The Epidemiology of Childhood Hyperactivity. Oxford: Oxford University Press.Google Scholar
Taylor, E., Chadwick, O., Heptinstall, E., et al (1996) Hyperactivity and conduct problems as risk factors for adolescent development. Journal of the American Academy of Child and Adolescent Psychiatry, 35, 12131226.CrossRefGoogle ScholarPubMed
Thapar, A., Ross, K., Harrington, R., et al (2000) Does the definition of ADHD affect heritability? Journal of the American Academy of Child and Adolescent Psychiatry, 39, 15281536.CrossRefGoogle ScholarPubMed
World Health Organization (1992) International Classification of Diseases and Related Disorders (ICD–10). Geneva: WHO.Google Scholar
Figure 0

Fig. 1 Liability threshold model: the two-threshold (isocorrelational) type.

Figure 1

Fig. 2 Full bivariate model for ADHD-related problems and conduct problems; ADHD, attention-deficit hyperactivity disorder; CD, conduct disorder; A, additive genetic factors; C, shared environmental factors; E, non-shared environmental factors.

Figure 2

Table 1 Univariate genetic model fitting for ADHD-related problems and conduct problems

Figure 3

Table 2 Bivariate genetic model fitting for ADHD-related problems and conduct problems (see Fig. 2 for full model)

Figure 4

Fig. 3 Accepted bivariate model for ADHD-related problems and conduct-related problems; ADHD, attention-deficit hyperactivity disorder; CD, conduct disorder; A, additive genetic factors; C, shared environmental factors; E, non-shared environmental factors.

Figure 5

Table 3 Probandwise concordance rates for broad and narrow categories of ADHD-related problems

Figure 6

Table 4 Results of liability threshold model fitting

Submit a response

eLetters

No eLetters have been published for this article.
You have Access
171
Cited by

Send article to Kindle

To send this article to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about sending to your Kindle. Find out more about sending to your Kindle.

Note you can select to send to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Examining the comorbidity of ADHD-related behaviours and conduct problems using a twin study design
Available formats
×

Send article to Dropbox

To send this article to your Dropbox account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Dropbox.

Examining the comorbidity of ADHD-related behaviours and conduct problems using a twin study design
Available formats
×

Send article to Google Drive

To send this article to your Google Drive account, please select one or more formats and confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your <service> account. Find out more about sending content to Google Drive.

Examining the comorbidity of ADHD-related behaviours and conduct problems using a twin study design
Available formats
×
×

Reply to: Submit a response

Please enter your response.

Your details

Please enter a valid email address.

Conflicting interests

Do you have any conflicting interests? *