A high co-occurrence of attention-deficit/hyperactivity disorder (ADHD) and autism spectrum disorders (ASDs) has been indicated by previous research (Rommelse et al.
2010; Simonoff et al.
2008). Despite this, previous diagnostic exclusionary criteria in the Diagnostic and Statistical Manual of Mental Disorders (DSM-IV-TR; American Psychiatric Association
2000) prohibited a dual diagnosis, although this has been amended in the most recent diagnostic revision (DSM-5; American Psychiatric Association
2013). Partly as a result of the diagnostic exclusionary criteria, little is known about the underlying causes of the covariation of these disorders (Ronald et al.
2008).
Both ADHD and autism symptoms can be viewed as continuously distributed traits (Chen et al.
2008; Dawson et al.
2002; Lubke et al.
2009; Robinson et al.
2011). Consequently, twin studies have explored shared and specific etiological influences of quantitative assessments of autistic-like traits (ALTs) and ADHD symptoms (reviewed by Posthuma and Polderman
2013; Ronald and Hoekstra
2011). Analysis of ratings on a UK population-based twin sample (Twins’ Early Development Study; TEDS) at age 8 yielded significant phenotypic correlations (
rPH around 0.50) between ADHD symptoms and ALTs (Ronald et al.
2008). Substantial common genetic influences (genetic correlations;
rG > 0.50) were found whether assessing co-variation throughout the population, at the quantitative extreme, or adopting a categorical approach (Ronald et al.
2008). These findings were consistent across genders and informants. A similarly high genetic correlation (
rG = 0.72) was obtained for self-report symptom ratings in adulthood (Reiersen et al.
2008), and moderate to high genetic overlap has been reported in a handful of other twin studies of children and adults (Constantino et al.
2003; Lundstrom et al.
2011; Taylor et al.
2013). Taken together, these findings suggest that ALTs and ADHD symptoms are modestly correlated and share, in part, a common genetic etiology.
Yet the substantial genetic heterogeneity observed within the symptom subscales of ASD (Dworzynski et al.
2009; Robinson et al.
2012; Ronald et al.
2005,
2006a,
b,
2011) and modest genetic overlap of ADHD symptom domains (Greven et al.
2011; McLoughlin et al.
2007) requires further detailed analysis. This issue was partly addressed in a sample of 2-year-old twins that separated ALTs into social and non-social symptom subscales (Ronald et al.
2010b). Despite the young age of the sample, the phenotypic and genetic covariation of ADHD symptoms and ALTs was evident, although slightly lower than observed in the aforementioned studies, suggestive of a possible developmental increase. Moreover, both ALT subscales contributed equally to the phenotypic covariation and etiological influences shared with ADHD symptoms (Ronald et al.
2010b). More recently, two large population-based Swedish studies of child (Ronald et al.
2014) and adult (Polderman et al.
2014) twins, focusing on parent- and self-ratings, respectively, both found that repetitive and restricted behavior and interests (versus social-communication difficulties) were driving the genetic overlap equally with both inattention and hyperactivity-impulsivity. A recent report from the UK TEDS sample based on parental ratings at age 12 reported greatest phenotypic and genetic overlap between autistic-like communication difficulties with both ADHD symptom scales, but also significant overlap between both ADHD symptom subscales and repetitive and restricted behavior (Taylor et al.
2015).
Aspects of executive functioning (EF) are compromised in both disorders, and have been identified as potential shared endophenotypes (Rommelse et al.
2011). In ADHD, response inhibition (as measured, for example, with commission errors (CE) on go/no-go tasks) is commonly impaired (Kuntsi et al.
2010; Willcutt et al.
2005). Although response inhibition deficits have also been reported in ASD, the evidence is more mixed (Happe et al.
2006; Nyden et al.
1999; Raymaekers et al.
2007). In two studies comparing across ADHD, ASD, and combined (ADHD + ASD) groups, the combined group was significantly more impaired on response inhibition, compared to the ASD-only group (Buhler et al.
2011; Sinzig et al.
2008).
Another candidate for a shared cognitive impairment between ADHD and ASD is reaction time variability (RTV), thought to reflect attentional lapses. In ADHD research RTV has emerged as one of the strongest cognitive endophenotypes, indexing a substantial proportion of the genetic influences on the disorder (Kuntsi and Klein
2012). Comparisons between ADHD and ASD on RTV have to date produced a mixed set of findings, however, with reports of increased RTV in ADHD only (Johnson et al.
2007), in ASD only (Geurts et al.
2008), in both (Nyden et al.
2010) or neither disorder (Geurts et al.
2004; Raymaekers et al.
2007). More recently, when comparing children from single and comorbid diagnosis groups, increased RTV was exhibited in groups with ADHD symptoms (ADHD-only and ADHD + ASD group) versus groups with no ADHD symptoms (ASD-only and controls) (Tye et al.
2014).
In previous research on ADHD we have shown the etiological separation of RTV and CE (Kuntsi et al.
2010,
2014) and further showed in a population twin sample that these two cognitive impairments display partially distinct phenotypic and genetic relationships to the two ADHD symptom domains (Kuntsi et al.
2014). We found a strong genetic overlap between RTV and particularly inattention. CE showed less differentiation between the ADHD symptom domains, although the genetic correlations were overall low. Given these findings and the genetic heterogeneity of ALTs (Dworzynski et al.
2009; Robinson et al.
2012; Ronald et al.
2005,
2006a,
b,
2011), we extended the previous model with an aim to investigate if the phenotypic and genetic covariation between ADHD symptoms and ALTS are driven by specific symptom subscales, and if cognitive impairments (CE and RTV) represent unique etiological pathways for ADHD symptoms or are shared with ALTs, and similarly show different patterns of co-occurrence across ALT subscales. Using a population-based twin sample our study aimed, specifically, to investigate: (1) to what extent are social-communication and non-social ALTs phenotypically and genetically associated with the two ADHD symptom domains of inattention and hyperactivity-impulsivity in childhood; (2) to what extent are social-communication and non-social ALTs phenotypically and genetically associated with RTV and CE; and (3) for any significant genetic correlations that emerge in (2), to estimate the extent to which this shared cognitive impairment underlies the genetic risk shared between ADHD symptoms and ALTs.
Methods
Sample and Procedure
Participants were from the Study of Activity and Impulsivity Levels in children (SAIL). Sampling methods and data collection procedures are described in detail elsewhere (Kuntsi et al.
2006). The parents of all participating children provided informed consent, with ethical approval obtained from the Research Ethics Committee of the Institute of Psychiatry, King’s College London, UK. The final sample consisted of 1312 children: 255 identical (monozygotic; MZ) twin pairs, 184 same-sex non-identical (dizygotic; DZ) twin pairs, and 206 opposite-sex DZ twin pairs, and 22 singletons coming from pairs with one of the twins excluded.
Twin zygosity was determined using a parental-report questionnaire with 95 % accuracy, later verified using DNA (Price et al.
2000). The mean age of participating children was 8.83 years (SD = 0.67), with a similar proportion of boys (49.5 %) and girls. Children’s IQs ranged from 70 to 158 (mean = 109.34, SD = 14.72).
Results
Given the variance differences between the genders, means and standard deviations are presented separately for males and females (Table
2).
Table 2
Means and standard deviations for behavioral ratings and cognitive measures
MZM |
11.06 (8.61) |
12.70 (8.95) |
6.01 (3.57) |
5.86 (3.15) |
619.06 (350.81) |
116.52 (34.29) |
MZF |
6.74 (5.89) |
7.79 (6.51) |
4.53 (2.99) |
5.58 (2.44) |
629.94 (364.15) |
96.42 (31.47) |
DZM |
11.53 (9.64) |
14.25 (11.14) |
6.20 (3.79) |
6.57 (3.30) |
631.01 (376.52) |
115.59 (32.90) |
DZF |
7.31 (6.49) |
9.06 (7.88) |
5.08 (3.29) |
5.80 (2.80) |
628.04 (359.12) |
95.61 (33.14) |
The focus of this paper is on the covariance of social-communication and non-social ALTs each with ADHD symptom subscales and cognitive variables. Accordingly, in Table
3 we present maximum likelihood cross-twin cross-trait correlations for the ALT subscales separately with each of the remaining variables. Similarly in Table
4, we present parameter estimates for the specific relationships of social-communication and non-social ALTs with behavioural ADHD and cognitive variables (for all parameter estimates between all the variables, see Fig.
1).
Table 3
Maximum-likelihood cross-twin cross-trait correlations (constrained correlated model) for social-communication and non-social ALTs between ADHD symptoms and cognitive measures
Hyperactivity-impulsivity with: |
Social-communication ALTs |
0.31 (0.23/0.37) |
0.14 (0.06/0.22) |
Non-social ALTs |
0.13 (0.05/0.19) | 0.08 (−0.002/0.15) |
Inattention with: |
Social-communication ALTs |
0.31 (0.23/0.35) |
0.13 (0.04/0.21) |
Non-social ALTs | −0.01 (−0.09/0.03) | 0.06 (−0.02/0.10) |
RTV with: |
Social-communication ALTs |
0.16 (0.08/0.24) | 0.03 (−0.05/0.10) |
Non-social ALTs | 0.01 (−0.10/0.05) | 0.01 (−0.07/0.06) |
CE with: |
Social-communication ALTs | 0.01 (−0.07/0.09) | −0.01 (−0.08/0.07) |
Non-social ALTs | −0.05 (−0.13/−0.01) | 0.02 (−0.06/0.08) |
Table 4
Etiological and phenotypic correlations (standardised correlated factors solution genetic model) for social-communication and non-social ALTs between ADHD symptoms and cognitive measures
Hyperactivity-impulsivity with: |
Social-communication ALTs |
0.44 (0.33/0.55) | −0.03 (−0.17/0.11) |
0.31 (0.24/0.37) | 0.32* | −0.01* |
Non-social ALTs |
0.20 (0.08/0.32) | −0.08 (−0.21/0.07) |
0.11 (0.04/0.18) | 0.14* | −0.03* |
Inattention with: |
Social-communication ALTs |
0.52 (0.39/0.65) | 0.03 (−0.12/0.18) |
0.33 (0.26/0.39) | 0.31 (96 %) | 0.01 (4 %) |
Non-social ALTs | 0.05 (−0.11/0.21) | −0.20 (−0.34/−0.05) | −0.06 (−0.13/0.01) | 0.03* | −0.08* |
RTV with: |
Social-communication ALTs |
0.32 (0.15/0.66) | 0.06 (−0.07/0.19) |
0.18 (0.11/0.25) | 0.16 (87 %) | 0.02 (13 %) |
Non-social ALTs | −0.01 (−0.20/0.21) | −0.07 (−0.20/0.06) | −0.04 (−0.11/0.04) | −0.01 (13 %) | −0.03 (87 %) |
CE with: |
Social-communication ALTs | 0.12 (−0.35/0.37) | 0.04 (−0.09/0.16) | 0.03 (−0.05/0.09) | 0.04 (71 %) | 0.01 (29 %) |
Non-social ALTs | −0.10 (−0.68/0.15) | −0.10 (−0.22/0.03) | −0.09 (−0.15/−0.02) | −0.04 (42 %) | −0.05 (58 %) |
Social-Communication and Non-Social ALTs With the two ADHD Symptom Domains of Inattention and Hyperactivity-Impulsivity
Social-communications ALTs correlated moderately and equally with both inattention (
rPH = 0.33; 95 % confidence intervals (CI) 0.26–0.39) and hyperactivity-impulsivity (
rPH = 0.31; 0.24–0.37). In contrast, the correlation between non-social ALTs and hyperactivity-impulsivity was significantly (non-overlapping CI) lower (
rPH = 0.11; 0.04–0.18) and did not reach significance with inattention. The phenotypic covariance between social-communication ALTs and inattention was predominantly accounted for by shared broad-sense genetic effects (96 %). Although the proportion of the phenotypic covariance between social-communication ALTs and hyperactivity-impulsivity, and non-social ALTs and either ADHD behavioral dimension, could not be quantified (etiological correlations had both positive and negative values), visual inspection of raw estimates (Table
4) suggested that the majority of the phenotypic correlations were due to shared genetic influences.
The broad-sense genetic correlations for social-communication ALTs were substantial (Table
4) and showed little differentiation (overlapping CI) with either ADHD symptom domain (inattention (
rG = 0.52) and hyperactivity-impulsivity (
rG = 0.44)). The genetic correlation between non-social ALTs and hyperactivity-impulsivity was significantly lower (
rG = 0.20). The broad-sense genetic correlation between non-social ALTs and inattention was low and non-significant.
Social-Communication and Non-Social ALTs With RTV and CE
Social-communications ALTs were significantly correlated with RTV (
rPH = 0.18), with broad-sense genetic effects accounting for the vast majority (87 %) of the phenotypic covariation (Table
4). The broad-sense genetic correlation between RTV and social-communication ALTs was moderate (
rG = 0.32). Non-social ALTs showed a small but significant negative correlation with CE (
rPH = −0.09). There were no significant correlations seen between RTV and non-social ALTs, or between CE and social-communications ALTs (Table
4).
Cholesky Decomposition: Social-communication ALTs, Inattention and RTV
In the full correlated factors solution (Fig.
1), inattention and social-communication ALTs showed strong overlapping broad-sense genetic effects (
rG = 0.52) and RTV displayed substantial shared broad-sense genetic influences with both inattention (
rG = 0.40) and social-communication ALTs (
rG = 0.32). Based on these multivariate findings, we selected social communication ALTs, inattention and RTV for further investigation of their interrelationships. Therefore we selected to test in the Cholesky decomposition (Fig.
2), how much of the broad-sense genetic effects shared between inattention and social-communication ALTs were also shared with RTV. This was tested using a reduced three-factor Cholesky decomposition, with RTV assigned as the first variable, and estimated by summing the product of Cholesky genetic paths that are shared with RTV and taking them as a percentage of the total genetic covariance between inattention and social-communication ALTs. We also estimated how much of the covariance between social-communication ALTs and inattention was shared with individual-specific environmental risk factors shared with RTV. (Common environment (C) did not contribute to the covariation between RTV and either inattention or social-communication ALTs and so is not included in the model.)
Using the parameter estimates from the Cholesky decomposition, we estimated that 24 % of the broad-sense genetic covariance between inattention and social-communication ALTs was shared with genetic effects underlying RTV: ((0.77*0.77) / (0.77*0.77) + (1.82*1.03) = 0.59 / (0.59 + 1.87) = 0.59/2.47 = 0.24). In a similar vein, 57 % of the individual-specific environmental covariance between social-communication ALTs and inattention was shared with RTV.
Discussion
An investigation of the individual ADHD and ALT symptom domains indicated, first, that the phenotypic and genetic overlap between ADHD symptoms and ALTs in this study is largely driven by social-communication ALTs, equally with both inattention and hyperactivity-impulsivity. Second, social-communication ALTs were phenotypically and genetically correlated with RTV, consistent with the view that increased RTV is not specific to ADHD symptoms (or, specifically, inattention symptoms). Third, RTV captured a significant proportion (24 %) of the genetic influences shared between inattention and social-communication ALTs.
Our study suggests that the previously observed phenotypic and genetic association between ADHD and ASD is predominantly driven by social-communication ALTs. Furthermore, inattention and hyperactivity-impulsivity are similarly associated with social-communication ALTs. The findings indicate that the phenotypic and genetic covariation between the symptoms of these two disorders is partially symptom-specific, driven by social-communication ALTs equally with both ADHD symptom subscales. This pattern of findings is partially in line with the Generalist Genes hypothesis, that the same set of genetic risk factors will influence symptom subscales across disorders: in our study, a set of generalist genes were influencing inattention, hyperactivity-impulsivity and social-communication ALTs. In addition, this pattern of findings is consistent with the greater genetic heterogeneity across ALTs (Dworzynski et al.
2009; Robinson et al.
2012; Ronald et al.
2005,
2006a,
b,
2011), than across ADHD symptom dimensions (Greven et al.
2011; McLoughlin et al.
2007).
Of the previous twin studies on subscales of ADHD and ALT, two reported strongest overlap between repetitive and restricted behavior and interests and ADHD traits (Polderman et al.
2014; Ronald et al.
2014), in contrast to our results which showed strongest associations with social-communication ALTs. It is unclear why these larger studies, one on children and one on adults, reported a different pattern of results to those seen here. A third recent study of the TEDS sample reported that communication ALTs were most strongly linked with both ADHD traits, which is more similar to our findings (Taylor et al.
2015), although their social ALT scale showed low overlap with ADHD traits). It is important to note that our sample is a subset of TEDS, and so these findings are not fully independent, although Taylor’s study used assessments obtained at age 12 from the Childhood Autism Spectrum Test (Scott et al.
2002). An important direction of future research is to clarify the source of the discrepant findings.
Our findings on cognitive markers are in line with the previous studies that have found that increased RTV is not specific to ADHD, but is also observed in ASD (Nyden et al.
2010). Our findings now extend these observations by indicating that the association between RTV and ASD is driven by social-communication ALTs, and by showing that genetic influences explain the majority (87 %) of this association. Moreover, a notable proportion (24 %) of the genetic effects shared between inattention and social-communication ALTs could be accounted for by RTV. This suggests that a modest set of shared genetic risk factors contribute to RTV, inattention and social-communication ALTs. The second cognitive marker that we investigated – response inhibition (CE) – did not emerge as meaningfully associated to ALTs, as the only phenotypic or etiological correlation that emerged as significant was a low, negative phenotypic correlation with non-social ALTs (
rPH = −0.09). The previous findings on response inhibition in ASD groups have been mixed (Buhler et al.
2011; Happe et al.
2006; Nyden et al.
1999; Raymaekers et al.
2007; Sinzig et al.
2008). The present study adds to this evidence by showing that response inhibition does not account for the overlap between ADHD and ALT symptoms.
The genetic overlap of RTV with symptom subscales across both ADHD and ALTs (specifically inattention and social-communication ALTs) suggest that RTV can be considered a trans-diagnostic cognitive endophenotypes. The highly heterogeneous clinical presentation, genetically complex nature, and non-optimal phenotypic definition of ADHD and ASD, likely contribute to the challenges involved in identifying genetic risk markers. One way to overcome these obstacles may be to use endophenotypes as targets for molecular genetic studies or as a means of subdividing samples into more homogenous subgroups (Losh et al.
2008; Viding and Blakemore
2007), potentially across current diagnostic categories (Levy and Ebstein
2009). However, the main appeal of endophenotypes is in bridging the gap between etiological factors and clinical phenotypes by elucidating underlying pathophysiological processes (Meyer-Lindenberg
2010). Our previous findings indicated specific neurocognitive pathways, with RTV particularly underlying inattentive symptoms (Kuntsi et al.
2014). The findings in this study suggest that this gene-behavioral pathway may not be unique, but is a partly common pathway underlying social-communication ALTs.
Our findings underline that investigating the individual symptom domains of ADHD and ALTs may clarify the etiological link between these two commonly occurring disorders. Quantitative genetic studies that identify genetically-related behavioral traits, even across diagnostic boundaries, can inform the selection of additional genetic markers for candidate gene association studies. In this respect, our findings suggest that molecular genetic investigations may benefit from examining putative genetic risk markers for inattention or hyperactivity-impulsivity for social-communication ALTs, and vice-versa. The clustering of cross-diagnostic symptom profiles (see also Ronald et al.
2014) further supports the change in diagnostic criteria to allow a dual diagnosis of ADHD and ASD. However, our findings also highlight that the etiology of disorders does not necessarily follow diagnostic boundaries, and accordingly may give rise to different ways of conceptualizing disorders.
The findings presented here indicate shared genetic effects between RTV, inattention and social-communication ALTs, but cannot clarify whether a causal relationship is involved. A further limitation of our study was that the behavioral ratings on ADHD and ALT symptoms were not collected simultaneously, which will have the effect of dampening the observed phenotypic correlations. Future studies should aim to replicate our findings. In addition, RTV only partially accounts for the covariation of social-communication ALTs and inattention; therefore future studies should extend investigations to include additional cognitive markers. Finally, although there is good evidence that both ADHD and ASD represent extremes of traits that are continuously distributed throughout the population, studies of clinical samples are required before these findings can be generalised to clinical populations.
Overall, our findings on the distinction between social-communication and non-social ALTs in their association with ADHD symptoms emphasise the importance of analysing symptom sub-domains in the investigation of neurodevelopmental disorders. The genetic overlap we observed across some of the behavioral symptoms, as well as with the cognitive marker of RTV, is consistent with the many reports in psychiatric genetics of partly shared genetic influences across psychiatric phenotypes (Cross-Disorder Group of the Psychiatric Genomics Consortium
2013); yet we also observed a degree of specificity. Future research that incorporates additional levels of analysis, such as neurophysiological or other neuroimaging approaches, will likely help to clarify further the similarities and differences between the overlapping neurodevelopmental disorders of ADHD and ASD. The changes in diagnostic practice will allow more research into the co-occurrence of these disorders and contribute to a greater understanding of their individual and shared etiology.
Acknowledgments
We gratefully acknowledge the ongoing contribution of the participants in the Twins Early Development Study (TEDS) and their families. We thank the TEDS-SAIL families, who give their time and support so unstintingly. We also thank research team members Keeley Brookes, Rebecca Gibbs, Hannah Rogers, Eda Salih, Greer Swinard, Kate Lievesley, Kayley O’Flynn, Suzi Marquis, Rebecca Whittemore, Xiaohui Xu, and everyone on the TEDS team.
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