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Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion
SCHRES-05162; No of Pages 5 Schizophrenia Research xxx (2012) xxx–xxx
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Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion Jacob A.S. Vorstman a,⁎, Elemi J. Breetvelt a, Kirstin I. Thode b, Eva W.C. Chow c, d, Anne S. Bassett c, d a
Rudolf Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands Department of Psychiatry, Malcolm Grow Medical Center, Joint Base Andrews, Andrews AFB, MD, USA c Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada d Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada b
a r t i c l e
i n f o
Article history: Received 31 May 2012 Received in revised form 4 September 2012 Accepted 7 October 2012 Available online xxxx Keywords: Pleiotropy Copy number variant (CNV) Autism Schizophrenia 22q11.2 deletion syndrome
a b s t r a c t Background: Copy number variants (CNVs) associated with neuropsychiatric disorders are increasingly being identified. While the initial reports were relatively specific, i.e. implicating vulnerability for a particular neuropsychiatric disorder, subsequent studies suggested that most of these CNVs can increase the risk for more than one neuropsychiatric disorder. Possibly, the different neuropsychiatric phenotypes associated with a single genetic variant are really distinct phenomena, indicating pleiotropy. Alternatively, seemingly different disorders could represent the same phenotype observed at different developmental stages or the same underlying pathogenesis with different phenotypic expressions. Aims: To examine the relation between autism and schizophrenia in patients sharing the same CNV. Method: We interviewed parents of 78 adult patients with the 22q11.2 deletion (22q11.2DS) to examine if autistic symptoms during childhood were associated with psychosis in adulthood. We used Chi-square, T-tests and logistic regression while entering cognitive level, gender and age as covariates. Results: The subgroup of 22q11.2DS patients with probable ASD during childhood did not show an increased risk for psychosis in adulthood. The average SRS scores were highly similar between those with and those without schizophrenia. Conclusions: ASD and schizophrenia associated with 22q11.2DS should be regarded as two unrelated, distinct phenotypic manifestations, consistent with true neuropsychiatric pleiotropy. 22q11.2DS can serve as a model to examine the mechanisms associated with neuropsychiatric pleiotropy associated with other CNVs. © 2012 Published by Elsevier B.V.
1. Introduction In recent years, increasing numbers of structural genomic variants, in particular rare, recurrent copy number variants (CNVs), have been identified as risk factors of large effect for neuropsychiatric disorders (Sebat et al., 2007; International Schizophrenia Consortium, 2008; Stefansson et al., 2008; Walsh et al., 2008; Bassett et al., 2010). Initial studies suggested that certain CNVs appeared to be associated with specific disorders. Cumulative reports, however, indicate that the same variant may be a risk factor for several neuropsychiatric and developmental disorders (Girirajan and Eichler, 2010). Examples include the 15q13.3 deletion associated with schizophrenia (Stefansson et al., 2008), autism (Pagnamenta et al., 2009), intellectual disability (Sharp et al., 2008) and generalized epilepsy (Helbig et al., 2009) and 16p11.2 deletions and duplications with schizophrenia (McCarthy et al., 2009), autism (Weiss et al., 2008), and intellectual disability (Girirajan et al., 2010). When one genetic variant can lead to two or more distinct, unrelated or seemingly unrelated, phenotypes, the variant can be considered pleiotropic. Pleiotropy is a common biological ⁎ Corresponding author. Tel.: +31 88 755 8141. E-mail address: [email protected] (J.A.S. Vorstman).
phenomenon in which one genetic variant has the potential to result in two or more distinct phenotypic manifestations. Can we better understand the pleiotropy of genetic variants, in particular in CNVs? The first question to address is whether the observed expression truly represents pleiotropy. For example, the most common recurrent CNV, the 22q11.2 deletions associated with 22q11.2 deletion syndrome (22q11.2DS), are associated with congenital cardiac defects (Cohen et al., 1999) and schizophrenia (Murphy et al., 1999). These two phenotypes occur independently, i.e. in 22q11.2DS the presence or absence of cardiac defects is not associated with an altered risk for schizophrenia (Bassett and Chow, 2008), consistent with true pleiotropy. Pseudopleiotropy, by contrast, would refer to phenotypes that are observed as discrete manifestations while in reality, they are expressions of the same pathological process, for instance at different developmental stages. This distinction may be particularly relevant with regard to the association of both autism spectrum disorders (ASDs) and schizophrenia with several pathogenic CNVs. In this regard, it has been suggested that the high prevalence of autistic behaviors in children with 22q11.2 deletions should not be viewed as autism spectrum disorders (ASDs), but rather as prodromal symptoms preceding the onset of schizophrenia (Vorstman et al., 2006; Eliez, 2007; Crespi and Badcock, 2008; Karayiorgou et al., 2010). If a marker such as childhood autistic
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Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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behaviors could be shown to predict the development of schizophrenia, a later onset condition occurring in approximately 20–25% of individuals with 22q11.2DS, this would be important in guiding anticipatory clinical care for this vulnerable group. Alternatively, if schizophrenia and autistic features appear as independent expressions in 22q11.2DS, this could be exploited in studies of the underlying brain changes and pathogenesis. Using an adult cohort with 22q11.2DS where reports of the presence of childhood ASD symptoms were available, we tested the hypothesis that ASD during childhood would be associated with higher rates of psychotic disorders in adulthood. We proposed the following possible scenarios: A. In 22q11.2DS, the ASD phenotype in childhood is associated with schizophrenia in adulthood because either 1) the ASD features observed in children with 22q11.2DS are in fact prodromal to the onset of schizophrenia (consistent with developmental pseudopleiotropy), or 2) the ASD features in 22q11.2DS during childhood are related to expression of autism and the close association with schizophrenia is the result of shared pathogenesis between these two conditions; or B. The ASD phenotype in 22q11.2DS is not associated with the expression of schizophrenia in 22q11.2DS, consistent with true pleiotropy, and supporting the null hypothesis. 2. Methods 2.1. Participants and procedure Parents of adults with 22q11.2DS followed at the Clinical Genetics Research Program, Centre for Addiction and Mental Health at the University of Toronto, were asked to participate in this study. In all subjects with 22q11.2DS the hemizygous 22q11.2 deletion was clinically confirmed by fluorescence in situ hybridization (FISH) using a standard probe (e.g., TUPLE1) (Bassett et al., 2008). As expected, in the majority of cases (>90%) the 22q11.2 deletion was a de novo event (Bassett et al., 2008). Participants provided written informed consent, and the study was approved by the local Research Ethics Boards. Patients were assessed by experienced psychiatrists for lifetime DSM-IV psychiatric diagnoses using standard methods, and tested for intellectual level, as previously described (Chow et al., 1999; Bassett et al., 2007). Data for 77 patients were available: 36 (17, 47.2% male) with a psychotic disorder (n= 34 schizophrenia; n = 2 psychotic disorder, not otherwise specified) formed the schizophrenia subgroup (22q11.2DS-SZ) and 41 (22, 53.7% male) with no history of a psychotic illness formed the comparison group (22q11.2DS-Co). In all but 11 patients detailed information regarding intellectual level was available (Chow et al., 2006) (n=30 22q11.2DS-SZ; n = 36 22q11.2DS-Co). Schizophrenia is not only characterized by the manifestation of psychotic symptoms (i.e. hallucinations and/or delusions). However, other hallmarks of schizophrenia (e.g. social deficits) are less readily distinguishable from features of ASD (Solomon et al., 2008). In order to study a possible relationship between ASD in early childhood and the later onset of schizophrenia, we therefore focused on the psychotic (positive) symptoms of schizophrenia. Parents were asked to complete two questionnaires, the Social Responsiveness Scale (SRS) (Constantino and Gruber, 2005) and the Social Communication Questionnaire lifetime (SCQ) (Rutter et al., 2003) for the assessment of autistic behavior. Both questionnaires have been well validated with good sensitivity and specificity values greater than 0.75 (Norris and Lecavalier, 2010). Parents were instructed to answer the questions by reflecting on the patient's behavior as a child. To prevent possible inflation of scores as a result of developmental delay in children with 22q11.2DS, we instructed parents to estimate the chronological age at which they considered their child to
be functioning at the global cognitive level of a typically developing child at kindergarten and to use that age as a reference for the behavioral questions. This further served as a means of obtaining retrospective information on possible autistic behaviors long before the onset of schizophrenia. Social deficits are to be expected in schizophrenia (Bassett et al., 2003) and may not be readily distinguishable from autistic symptomatology. Parents were therefore explicitly instructed not to refer to any current autistic behaviors in their offspring. Both the SRS and the SCQ were selected for this study because of their slightly different psychometric properties. The SCQ has been reported to perform somewhat better than SRS with respect to the identification of ASD, in particular in children with IQs in the lower range (Charman et al., 2007). In contrast, the SRS has the advantage over the SCQ in generating a single continuously distributed score to quantify the severity of autistic symptomatology (Constantino et al., 2003), allowing for more powerful statistical comparisons. 2.2. Measures The SRS consists of 65 questions answerable on a four point Likert scale (Not true, Sometimes, Often, Almost always). For each individual a gender-based T-score can be calculated from the SRS raw total scores (Constantino and Gruber, 2005) as well as T-scores on five subdomains; social awareness (e.g., …was aware what others are thinking or feeling), social cognition (e.g. …took things too literally and did not get the real meaning of a conversation), social communication (e.g., …was emotionally distant, did not show his or her feelings), social motivation (e.g., …would rather be alone than with others) and autistic mannerisms (e.g., …had repetitive, odd behaviors such as hand flapping or rocking). According to the SRS manual, total T-scores equal or higher to 60 indicate a probable ASD (Constantino and Gruber, 2005). The SCQ consists of 40 yes-or-no items (e.g. did he or she have any particular friends or a best friend?). A probable ASD diagnosis is suggested when the total SCQ score is 15 or more (Rutter et al., 2003). Thus, based on the responses on the SCQ, the subjects were divided into those who had and did not have a probable diagnosis of ASD during childhood. Since the use of a lower cut-off (score of 12 or more) has been suggested as more sensitive, in particular when applying the SCQ in children younger than 8 years of age (Eaves et al., 2006), we also analyzed the data using this score to generate groups with and without probable ASD. 2.3. Statistical analyses To test the primary hypothesis that ASD during childhood would be associated with subsequent schizophrenia, we compared mean SRS T-scores in both subgroups and generated 95% confidence intervals (CIs) through a bootstrapping procedure (n =1,000). Given that SRS T-scores deviated from a normal distribution in one of the subgroups (Kolmogorov–Smirnov test, p b 0.05) we used a Mann–Whitney– Wilcoxon test to examine differences between the two groups. For the categorical outcomes we used Chi-square analyses to test whether subjects with a probable ASD, according to the SRS and SCQ criteria noted above, were more likely to have schizophrenia. Logistic regression allows for adequate correction of potential confounders in the analysis of the categorical outcomes. In addition, this statistic provides easily interpretable probability predictions. Therefore we applied a binary logistic model using the stated cut-off scores as predictors. We calculated odds ratios (ORs) and their 95% CIs, entering age, IQ and sex as covariates for the SCQ, and age and IQ as covariates for the SRS. In post-hoc analyses we evaluated the association of SRS subdomain scores with schizophrenia and a possible correlation between SRS T-scores and IQ. Given the non-normal distribution of the SRS T-score, the SRS T-score was dichotomized by a median split, and a t-test was used to compare mean IQ scores between those with low and those with high SRS T-scores.
Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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Given our sample size of 77, we calculated a priori that we would have good (~ 80%) power to detect a moderate effect size (Cohen's d = 0.4) of ASD on the development of schizophrenia in 22q11.2DS with α = 0.05 (one-sided). 3. Results The mean “reference age” used by the parents for the two autism scales was similar in the 22q11.2DS-SZ group and the 22q11.2DS-Co; 5.9 ± 2.0 and 6.4 ± 2.0 years respectively, p = 0.217 (Mann–Whitney– Wilcoxon). In comparison to the 22q11.2DS-Co group, the subgroup with schizophrenia was older (36.6 (95% CI 33.1 to 40.2) vs. 28.5 (26.2 to 31.1) years, p = 0.001 (Mann–Whitney–Wilcoxon)) and on average had lower IQ (69.7 (66.5–73.2) vs. 75.7 (72.4–79.2), t = − 2.40, p = 0.02). There were no significant sex differences between the subgroups (Chi-Square = 0.32, p = 0.57). Table 1 shows the results for the autism scales. Using the SCQ thresholds of 12 points and 15 points, respectively, 13 (100%) and 26/27 (96.3%) subjects with 22q11.2DS categorized as probable ASD were also amongst those categorized as probable ASD using the more liberal SRS criteria. In other words, the SCQ identified a subset (comprising 22.0% and 44.0%, respectively, using the 12 and 15 points cut-off scores) of the 59 (76.6%) subjects identified as probable ASD by the SRS. The results for comparisons between the schizophrenia and nonpsychotic subgroups supported the null hypothesis. The mean SRS T-scores and 95% CIs were highly similar in 22q11.2DS patients with and those without schizophrenia (Table 1). Results from the logistic regressions (Table 1) also demonstrated no significant predictive effect for schizophrenia using any of the three dichotomous groupings of probable ASD. In post hoc analyses, we considered the subdomains generated by the SRS. These revealed no significant difference in any of the subdomains between those with and those without schizophrenia as adults (all p values > 0.45, data not shown). To examine the relationship between SRS-T score and IQ we calculated a Spearmans' Rho which showed a significant correlation of −0.28 (p= 0.02). Dividing the sample in two, using the median SRS T-score of 74, the subgroup with higher SRS scores for autistic features had a non-significantly lower mean IQ (n= 33, 70.7 ± 8.2) than that with lower SRS scores (n= 33, 75.2± 12.0, p = 0.08). 4. Discussion The results of this study support the possibility that ASD and schizophrenia should be considered as distinct, pleiotropic neuropsychiatric consequences of a 22q11.2 deletion. Although we found high levels of probable ASD, autistic or autistic-like symptoms during childhood, in line with previous findings of elevated prevalence of ASDs in children with 22q11.2DS (Niklasson et al., 2001, 2009; Antshel et al., 2007; Vorstman et al., 2006), the results did not support the
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hypothesis of an increased vulnerability for schizophrenia in the subgroup of 22q11.2DS patients with such symptoms. Indeed, using the most stringent SCQ criteria suggested, if anything, that childhood ASD features were inclined towards association with the non-psychotic group, despite the fact that IQ was higher in this sub-group. Average SRS scores were highly similar between those with and those without schizophrenia, suggesting that even small effect sizes are unlikely. Post-hoc analyses excluded any effects of ASD subdomains as defined by the SRS. Importantly, these findings indicate that autistic features in childhood cannot be used as a marker that can predict the development of schizophrenia in 22q11.2DS. The results of our study suggest that the genetic and/or epigenetic consequences of 22q11.2DS affect brain development in such a way that certain pathways in the brain become prone to dysfunction. One or several of these pathway(s) may lead to ASD while others may lead to schizophrenia. Whether and what pathways are compromised may depend on additional deleterious or protective factors, including chance and genetic, epigenetic and environmental factors. This would be consistent with the observation that although the prevalences are substantially increased in comparison to the general population, the majority of 22q11.2DS patients do not develop schizophrenia or ASD. The changes in brain development caused by the 22q11.2 deletion may drive the vulnerability of the individual with this CNV towards one or more of several possible neuropsychiatric phenotypes, although this should not be interpreted as a non-specific effect. Which developmental processes are rendered vulnerable to additional factors is likely to dependent on the specific genetic pathway(s) affected by the individual rare CNV involved. In line with this possibility, it was recently shown that the clinical heterogeneity of autistic symptomatology may be reduced when etiologic subgroups of ASD patients based on specific genotypes are extracted from the idiopathic ASD population (Bruining et al., 2010). Bassett et al. (2001, 2010) and more recently Owen et al. (2011) have posited that finding CNVs associated with variable neuropsychiatric phenotypes challenges the view that these are unrelated diagnostic entities. Our findings suggest that CNV-related neuropsychiatric phenotypes, such as ASD and schizophrenia in 22q11.2DS, can share the same major genetic etiology. This is also consistent with the model outlined by Craddock and Owen (2010). In the words used to describe this model (see Fig. 1 in the cited manuscript): 22q11.2DS could affect one or more basic biological systems with relevance to autism and schizophrenia. In combination with additional stochastic environmental and genetic variation specific “neural modules” are affected, ultimately leading to domains of psychopathology defining the clinical syndromes. The predicted outcome in 22q11.2DS would be that schizophrenia does not emerge via ASD, but can occur co-morbidly, which is consistent with the findings of this study. This proposition fits equally well to the model recently proposed by Bassett et al. (2010) which emphasizes the observed pleiotropy of CNVs. The current results add to this model that combined with the effect of major CNVs, additional
Table 1 Autistic symptoms and probable ASD during childhood, assessed in 77 adults with 22q11.2DS, comparing those with and without schizophrenia. Total (n = 77)
22q11.2DS-SZ (n = 36)
22q11.2DS-Co (n=41)
p
Mean SRS T-score (95% CI)
73.1 (69.7–76.6)
72.4 (67.3–78.0)
73.7 (68.9–78.6)
0.36a
Subjects categorized as probable ASD
n (%)
n (%)
n (%)
p
Uncorrected OR (95% CI)
p
Corrected OR (95% CI)
p
SRS T score cut-off 60 SCQ cut-off 15 SCQ cut-off 12
59 (76.6%) 13 (16.9%) 27 (35.1%)
27 (75.0%) 3 (8.3%) 13 (36.1%)
32 (78.0%) 10 (24.4%) 14 (34.1%)
0.75b 0.06b 0.86b
0.84 (0.29–2.43) 0.28 (0.07–1.12) 1.10 (0.44–2.78)
0.75 0.07 0.86
0.36 (0.085–1.52) 0.20 (0.03–1.46) 1.53 (0.49–5.27)
0.17c 0.11d 0.49d
CI = confidence interval. a Mann–Whitney–Wilcoxon. b Chi-square. c Corrected for age and IQ. d Corrected for gender, age, IQ.
Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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factors may shape the various phenotypic expressions that emerge. The combination of these factors may result in one or more pathways to a specific neuropsychiatric disorder. Thus, the consequence of the major genetic variant-related disruption may be a priming of one or several specific biological pathways in the brain, rendering the carrier more vulnerable to specific neuropsychiatric disorders, conforming to the model of Bassett et al. (2010). In comparison to non-carriers in the general population, relatively little more is needed to cause a neuropsychiatric disorder. The required additional factors do not have to be limited to genetic variants, and the genetic variation may or may not be limited to genetic variation directly related to the major CNV. Possible genetic causes for phenotypic variability in carriers of CNVs include variation in the remaining allele in the case of a deletion (Vorstman et al., 2009, 2011), expression-altering SNPs in close proximity to the CNV, different genomic extents of the main CNV, parent-of-origin and imprinting effects and modifying effects of other functionally relevant genes (Bassett et al., 2001, 2008; Girirajan and Eichler, 2010). To date, however, there is no evidence for parent-of-origin effects in 22q11.2DS (Bassett et al., 2008). 4.1. Strengths and limitations While a prospective design would be optimal, the current study provided data for a relatively large sample of adults with 22q11.2DS with relevant expression, including approximately equal numbers of those with and without schizophrenia, and parents available to provide information about childhood behaviors. An important limitation is that the retrospective design may have introduced biases. A recall bias, for example, could imply that the parents of those with schizophrenia may be inclined to over-report psychopathology during childhood in comparison to parents of 22q11.2DS patients without schizophrenia. If a positive correlation had been found in this study, the possibility of recall bias would have affected our ability to interpret this result. Such a finding could have been the result of a true correlation (ASD predicts psychosis) or alternatively, the result of recall bias (current psychosis biased the parents into reporting more childhood ASD). However, in the absence of a significant association between childhood ASD and later schizophrenia, the possibility of a recall bias is less relevant. The current study was only powered to detect a moderate effect size with respect to the hypothesized association between these two conditions. The a priori power to detect smaller effect sizes (Cohen's d b 0.4) was limited. However, the high similarity of the degree of autistic features in childhood between 22q11DS individuals with and those without schizophrenia suggests, post-hoc, that such smaller effects are unlikely. In fact, if anything we detected, a trend in the opposite direction (Table 1). The 22q11.2DS subgroups differed with respect to average age, however the average age in the 22q11.2DS-Co subgroup was well beyond the period of highest risk for the onset of psychosis. Parents of older patients may be less able to remember childhood behaviors and therefore may tend to underreport ASD symptoms compared to parents of younger patients. We included age as a covariate to correct for such bias and the analyses revealed no substantial impact on the results. The SRS and SCQ are meant as screening methods, not as stand-alone diagnostic instruments. Therefore, although comparable to results for children with 22q11.2DS (Niklasson et al., 2001, 2009; Antshel et al., 2007; Vorstman et al., 2006) the results of this study should not be interpreted as providing insight into the prevalence of true ASD in this sample of adults with 22q11.2DS. 5. Conclusion The current study provides evidence that in 22q11.2DS patients, ASD or autistic symptoms during childhood are not correlated with schizophrenia in adulthood. Therefore, ASDs and/or autistic symptoms cannot be considered as indicating premorbid symptoms of schizophrenia and would therefore not be useful as markers for increased vulnerability
for schizophrenia in 22q11.2DS. Although the results may or may not apply to the variability of neuropsychiatric disorders observed in other pathogenic CNVs, the 22q11.2 deletion may be useful as a model to examine the mechanisms underlying neuropsychiatric pleiotropy. Our observations indicate that ASD and schizophrenia associated with 22q11.2DS should be regarded as distinct phenotypic manifestations, consistent with true neuropsychiatric pleiotropy of the 22q11.2 deletion. Role of funding source This work was supported by grants from the Canadian Institutes of Health Research (MOP-79518, MOP-97800) and W. Garfield Weston Foundation (ASB, EWC). Dr. Bassett holds the Canada Research Chair in Schizophrenia Genetics and Genomic Disorders. J.A.S. Vorstman M.D., Ph.D. was supported by a 2006 NARSAD Young Investigator Award, funded by Stephen and Constance Lieber. Contributors Authors JV and AB took part in designing the study. Authors JV, AB, KT and EC collected the data. Author EB carried out the statistical analyses. Author JV wrote the first draft of the manuscript. Author AB contributed significantly to the writing of subsequent versions. All authors contributed to and have approved of the manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgements None.
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Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion Jacob A.S. Vorstman a,⁎, Elemi J. Breetvelt a, Kirstin I. Thode b, Eva W.C. Chow c, d, Anne S. Bassett c, d a
Rudolf Magnus Institute of Neuroscience, Department of Psychiatry, University Medical Center Utrecht, Utrecht, The Netherlands Department of Psychiatry, Malcolm Grow Medical Center, Joint Base Andrews, Andrews AFB, MD, USA c Clinical Genetics Research Program, Centre for Addiction and Mental Health, Toronto, Ontario, Canada d Department of Psychiatry, University of Toronto, Toronto, Ontario, Canada b
a r t i c l e
i n f o
Article history: Received 31 May 2012 Received in revised form 4 September 2012 Accepted 7 October 2012 Available online xxxx Keywords: Pleiotropy Copy number variant (CNV) Autism Schizophrenia 22q11.2 deletion syndrome
a b s t r a c t Background: Copy number variants (CNVs) associated with neuropsychiatric disorders are increasingly being identified. While the initial reports were relatively specific, i.e. implicating vulnerability for a particular neuropsychiatric disorder, subsequent studies suggested that most of these CNVs can increase the risk for more than one neuropsychiatric disorder. Possibly, the different neuropsychiatric phenotypes associated with a single genetic variant are really distinct phenomena, indicating pleiotropy. Alternatively, seemingly different disorders could represent the same phenotype observed at different developmental stages or the same underlying pathogenesis with different phenotypic expressions. Aims: To examine the relation between autism and schizophrenia in patients sharing the same CNV. Method: We interviewed parents of 78 adult patients with the 22q11.2 deletion (22q11.2DS) to examine if autistic symptoms during childhood were associated with psychosis in adulthood. We used Chi-square, T-tests and logistic regression while entering cognitive level, gender and age as covariates. Results: The subgroup of 22q11.2DS patients with probable ASD during childhood did not show an increased risk for psychosis in adulthood. The average SRS scores were highly similar between those with and those without schizophrenia. Conclusions: ASD and schizophrenia associated with 22q11.2DS should be regarded as two unrelated, distinct phenotypic manifestations, consistent with true neuropsychiatric pleiotropy. 22q11.2DS can serve as a model to examine the mechanisms associated with neuropsychiatric pleiotropy associated with other CNVs. © 2012 Published by Elsevier B.V.
1. Introduction In recent years, increasing numbers of structural genomic variants, in particular rare, recurrent copy number variants (CNVs), have been identified as risk factors of large effect for neuropsychiatric disorders (Sebat et al., 2007; International Schizophrenia Consortium, 2008; Stefansson et al., 2008; Walsh et al., 2008; Bassett et al., 2010). Initial studies suggested that certain CNVs appeared to be associated with specific disorders. Cumulative reports, however, indicate that the same variant may be a risk factor for several neuropsychiatric and developmental disorders (Girirajan and Eichler, 2010). Examples include the 15q13.3 deletion associated with schizophrenia (Stefansson et al., 2008), autism (Pagnamenta et al., 2009), intellectual disability (Sharp et al., 2008) and generalized epilepsy (Helbig et al., 2009) and 16p11.2 deletions and duplications with schizophrenia (McCarthy et al., 2009), autism (Weiss et al., 2008), and intellectual disability (Girirajan et al., 2010). When one genetic variant can lead to two or more distinct, unrelated or seemingly unrelated, phenotypes, the variant can be considered pleiotropic. Pleiotropy is a common biological ⁎ Corresponding author. Tel.: +31 88 755 8141. E-mail address: [email protected] (J.A.S. Vorstman).
phenomenon in which one genetic variant has the potential to result in two or more distinct phenotypic manifestations. Can we better understand the pleiotropy of genetic variants, in particular in CNVs? The first question to address is whether the observed expression truly represents pleiotropy. For example, the most common recurrent CNV, the 22q11.2 deletions associated with 22q11.2 deletion syndrome (22q11.2DS), are associated with congenital cardiac defects (Cohen et al., 1999) and schizophrenia (Murphy et al., 1999). These two phenotypes occur independently, i.e. in 22q11.2DS the presence or absence of cardiac defects is not associated with an altered risk for schizophrenia (Bassett and Chow, 2008), consistent with true pleiotropy. Pseudopleiotropy, by contrast, would refer to phenotypes that are observed as discrete manifestations while in reality, they are expressions of the same pathological process, for instance at different developmental stages. This distinction may be particularly relevant with regard to the association of both autism spectrum disorders (ASDs) and schizophrenia with several pathogenic CNVs. In this regard, it has been suggested that the high prevalence of autistic behaviors in children with 22q11.2 deletions should not be viewed as autism spectrum disorders (ASDs), but rather as prodromal symptoms preceding the onset of schizophrenia (Vorstman et al., 2006; Eliez, 2007; Crespi and Badcock, 2008; Karayiorgou et al., 2010). If a marker such as childhood autistic
0920-9964/$ – see front matter © 2012 Published by Elsevier B.V. http://dx.doi.org/10.1016/j.schres.2012.10.010
Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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behaviors could be shown to predict the development of schizophrenia, a later onset condition occurring in approximately 20–25% of individuals with 22q11.2DS, this would be important in guiding anticipatory clinical care for this vulnerable group. Alternatively, if schizophrenia and autistic features appear as independent expressions in 22q11.2DS, this could be exploited in studies of the underlying brain changes and pathogenesis. Using an adult cohort with 22q11.2DS where reports of the presence of childhood ASD symptoms were available, we tested the hypothesis that ASD during childhood would be associated with higher rates of psychotic disorders in adulthood. We proposed the following possible scenarios: A. In 22q11.2DS, the ASD phenotype in childhood is associated with schizophrenia in adulthood because either 1) the ASD features observed in children with 22q11.2DS are in fact prodromal to the onset of schizophrenia (consistent with developmental pseudopleiotropy), or 2) the ASD features in 22q11.2DS during childhood are related to expression of autism and the close association with schizophrenia is the result of shared pathogenesis between these two conditions; or B. The ASD phenotype in 22q11.2DS is not associated with the expression of schizophrenia in 22q11.2DS, consistent with true pleiotropy, and supporting the null hypothesis. 2. Methods 2.1. Participants and procedure Parents of adults with 22q11.2DS followed at the Clinical Genetics Research Program, Centre for Addiction and Mental Health at the University of Toronto, were asked to participate in this study. In all subjects with 22q11.2DS the hemizygous 22q11.2 deletion was clinically confirmed by fluorescence in situ hybridization (FISH) using a standard probe (e.g., TUPLE1) (Bassett et al., 2008). As expected, in the majority of cases (>90%) the 22q11.2 deletion was a de novo event (Bassett et al., 2008). Participants provided written informed consent, and the study was approved by the local Research Ethics Boards. Patients were assessed by experienced psychiatrists for lifetime DSM-IV psychiatric diagnoses using standard methods, and tested for intellectual level, as previously described (Chow et al., 1999; Bassett et al., 2007). Data for 77 patients were available: 36 (17, 47.2% male) with a psychotic disorder (n= 34 schizophrenia; n = 2 psychotic disorder, not otherwise specified) formed the schizophrenia subgroup (22q11.2DS-SZ) and 41 (22, 53.7% male) with no history of a psychotic illness formed the comparison group (22q11.2DS-Co). In all but 11 patients detailed information regarding intellectual level was available (Chow et al., 2006) (n=30 22q11.2DS-SZ; n = 36 22q11.2DS-Co). Schizophrenia is not only characterized by the manifestation of psychotic symptoms (i.e. hallucinations and/or delusions). However, other hallmarks of schizophrenia (e.g. social deficits) are less readily distinguishable from features of ASD (Solomon et al., 2008). In order to study a possible relationship between ASD in early childhood and the later onset of schizophrenia, we therefore focused on the psychotic (positive) symptoms of schizophrenia. Parents were asked to complete two questionnaires, the Social Responsiveness Scale (SRS) (Constantino and Gruber, 2005) and the Social Communication Questionnaire lifetime (SCQ) (Rutter et al., 2003) for the assessment of autistic behavior. Both questionnaires have been well validated with good sensitivity and specificity values greater than 0.75 (Norris and Lecavalier, 2010). Parents were instructed to answer the questions by reflecting on the patient's behavior as a child. To prevent possible inflation of scores as a result of developmental delay in children with 22q11.2DS, we instructed parents to estimate the chronological age at which they considered their child to
be functioning at the global cognitive level of a typically developing child at kindergarten and to use that age as a reference for the behavioral questions. This further served as a means of obtaining retrospective information on possible autistic behaviors long before the onset of schizophrenia. Social deficits are to be expected in schizophrenia (Bassett et al., 2003) and may not be readily distinguishable from autistic symptomatology. Parents were therefore explicitly instructed not to refer to any current autistic behaviors in their offspring. Both the SRS and the SCQ were selected for this study because of their slightly different psychometric properties. The SCQ has been reported to perform somewhat better than SRS with respect to the identification of ASD, in particular in children with IQs in the lower range (Charman et al., 2007). In contrast, the SRS has the advantage over the SCQ in generating a single continuously distributed score to quantify the severity of autistic symptomatology (Constantino et al., 2003), allowing for more powerful statistical comparisons. 2.2. Measures The SRS consists of 65 questions answerable on a four point Likert scale (Not true, Sometimes, Often, Almost always). For each individual a gender-based T-score can be calculated from the SRS raw total scores (Constantino and Gruber, 2005) as well as T-scores on five subdomains; social awareness (e.g., …was aware what others are thinking or feeling), social cognition (e.g. …took things too literally and did not get the real meaning of a conversation), social communication (e.g., …was emotionally distant, did not show his or her feelings), social motivation (e.g., …would rather be alone than with others) and autistic mannerisms (e.g., …had repetitive, odd behaviors such as hand flapping or rocking). According to the SRS manual, total T-scores equal or higher to 60 indicate a probable ASD (Constantino and Gruber, 2005). The SCQ consists of 40 yes-or-no items (e.g. did he or she have any particular friends or a best friend?). A probable ASD diagnosis is suggested when the total SCQ score is 15 or more (Rutter et al., 2003). Thus, based on the responses on the SCQ, the subjects were divided into those who had and did not have a probable diagnosis of ASD during childhood. Since the use of a lower cut-off (score of 12 or more) has been suggested as more sensitive, in particular when applying the SCQ in children younger than 8 years of age (Eaves et al., 2006), we also analyzed the data using this score to generate groups with and without probable ASD. 2.3. Statistical analyses To test the primary hypothesis that ASD during childhood would be associated with subsequent schizophrenia, we compared mean SRS T-scores in both subgroups and generated 95% confidence intervals (CIs) through a bootstrapping procedure (n =1,000). Given that SRS T-scores deviated from a normal distribution in one of the subgroups (Kolmogorov–Smirnov test, p b 0.05) we used a Mann–Whitney– Wilcoxon test to examine differences between the two groups. For the categorical outcomes we used Chi-square analyses to test whether subjects with a probable ASD, according to the SRS and SCQ criteria noted above, were more likely to have schizophrenia. Logistic regression allows for adequate correction of potential confounders in the analysis of the categorical outcomes. In addition, this statistic provides easily interpretable probability predictions. Therefore we applied a binary logistic model using the stated cut-off scores as predictors. We calculated odds ratios (ORs) and their 95% CIs, entering age, IQ and sex as covariates for the SCQ, and age and IQ as covariates for the SRS. In post-hoc analyses we evaluated the association of SRS subdomain scores with schizophrenia and a possible correlation between SRS T-scores and IQ. Given the non-normal distribution of the SRS T-score, the SRS T-score was dichotomized by a median split, and a t-test was used to compare mean IQ scores between those with low and those with high SRS T-scores.
Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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Given our sample size of 77, we calculated a priori that we would have good (~ 80%) power to detect a moderate effect size (Cohen's d = 0.4) of ASD on the development of schizophrenia in 22q11.2DS with α = 0.05 (one-sided). 3. Results The mean “reference age” used by the parents for the two autism scales was similar in the 22q11.2DS-SZ group and the 22q11.2DS-Co; 5.9 ± 2.0 and 6.4 ± 2.0 years respectively, p = 0.217 (Mann–Whitney– Wilcoxon). In comparison to the 22q11.2DS-Co group, the subgroup with schizophrenia was older (36.6 (95% CI 33.1 to 40.2) vs. 28.5 (26.2 to 31.1) years, p = 0.001 (Mann–Whitney–Wilcoxon)) and on average had lower IQ (69.7 (66.5–73.2) vs. 75.7 (72.4–79.2), t = − 2.40, p = 0.02). There were no significant sex differences between the subgroups (Chi-Square = 0.32, p = 0.57). Table 1 shows the results for the autism scales. Using the SCQ thresholds of 12 points and 15 points, respectively, 13 (100%) and 26/27 (96.3%) subjects with 22q11.2DS categorized as probable ASD were also amongst those categorized as probable ASD using the more liberal SRS criteria. In other words, the SCQ identified a subset (comprising 22.0% and 44.0%, respectively, using the 12 and 15 points cut-off scores) of the 59 (76.6%) subjects identified as probable ASD by the SRS. The results for comparisons between the schizophrenia and nonpsychotic subgroups supported the null hypothesis. The mean SRS T-scores and 95% CIs were highly similar in 22q11.2DS patients with and those without schizophrenia (Table 1). Results from the logistic regressions (Table 1) also demonstrated no significant predictive effect for schizophrenia using any of the three dichotomous groupings of probable ASD. In post hoc analyses, we considered the subdomains generated by the SRS. These revealed no significant difference in any of the subdomains between those with and those without schizophrenia as adults (all p values > 0.45, data not shown). To examine the relationship between SRS-T score and IQ we calculated a Spearmans' Rho which showed a significant correlation of −0.28 (p= 0.02). Dividing the sample in two, using the median SRS T-score of 74, the subgroup with higher SRS scores for autistic features had a non-significantly lower mean IQ (n= 33, 70.7 ± 8.2) than that with lower SRS scores (n= 33, 75.2± 12.0, p = 0.08). 4. Discussion The results of this study support the possibility that ASD and schizophrenia should be considered as distinct, pleiotropic neuropsychiatric consequences of a 22q11.2 deletion. Although we found high levels of probable ASD, autistic or autistic-like symptoms during childhood, in line with previous findings of elevated prevalence of ASDs in children with 22q11.2DS (Niklasson et al., 2001, 2009; Antshel et al., 2007; Vorstman et al., 2006), the results did not support the
3
hypothesis of an increased vulnerability for schizophrenia in the subgroup of 22q11.2DS patients with such symptoms. Indeed, using the most stringent SCQ criteria suggested, if anything, that childhood ASD features were inclined towards association with the non-psychotic group, despite the fact that IQ was higher in this sub-group. Average SRS scores were highly similar between those with and those without schizophrenia, suggesting that even small effect sizes are unlikely. Post-hoc analyses excluded any effects of ASD subdomains as defined by the SRS. Importantly, these findings indicate that autistic features in childhood cannot be used as a marker that can predict the development of schizophrenia in 22q11.2DS. The results of our study suggest that the genetic and/or epigenetic consequences of 22q11.2DS affect brain development in such a way that certain pathways in the brain become prone to dysfunction. One or several of these pathway(s) may lead to ASD while others may lead to schizophrenia. Whether and what pathways are compromised may depend on additional deleterious or protective factors, including chance and genetic, epigenetic and environmental factors. This would be consistent with the observation that although the prevalences are substantially increased in comparison to the general population, the majority of 22q11.2DS patients do not develop schizophrenia or ASD. The changes in brain development caused by the 22q11.2 deletion may drive the vulnerability of the individual with this CNV towards one or more of several possible neuropsychiatric phenotypes, although this should not be interpreted as a non-specific effect. Which developmental processes are rendered vulnerable to additional factors is likely to dependent on the specific genetic pathway(s) affected by the individual rare CNV involved. In line with this possibility, it was recently shown that the clinical heterogeneity of autistic symptomatology may be reduced when etiologic subgroups of ASD patients based on specific genotypes are extracted from the idiopathic ASD population (Bruining et al., 2010). Bassett et al. (2001, 2010) and more recently Owen et al. (2011) have posited that finding CNVs associated with variable neuropsychiatric phenotypes challenges the view that these are unrelated diagnostic entities. Our findings suggest that CNV-related neuropsychiatric phenotypes, such as ASD and schizophrenia in 22q11.2DS, can share the same major genetic etiology. This is also consistent with the model outlined by Craddock and Owen (2010). In the words used to describe this model (see Fig. 1 in the cited manuscript): 22q11.2DS could affect one or more basic biological systems with relevance to autism and schizophrenia. In combination with additional stochastic environmental and genetic variation specific “neural modules” are affected, ultimately leading to domains of psychopathology defining the clinical syndromes. The predicted outcome in 22q11.2DS would be that schizophrenia does not emerge via ASD, but can occur co-morbidly, which is consistent with the findings of this study. This proposition fits equally well to the model recently proposed by Bassett et al. (2010) which emphasizes the observed pleiotropy of CNVs. The current results add to this model that combined with the effect of major CNVs, additional
Table 1 Autistic symptoms and probable ASD during childhood, assessed in 77 adults with 22q11.2DS, comparing those with and without schizophrenia. Total (n = 77)
22q11.2DS-SZ (n = 36)
22q11.2DS-Co (n=41)
p
Mean SRS T-score (95% CI)
73.1 (69.7–76.6)
72.4 (67.3–78.0)
73.7 (68.9–78.6)
0.36a
Subjects categorized as probable ASD
n (%)
n (%)
n (%)
p
Uncorrected OR (95% CI)
p
Corrected OR (95% CI)
p
SRS T score cut-off 60 SCQ cut-off 15 SCQ cut-off 12
59 (76.6%) 13 (16.9%) 27 (35.1%)
27 (75.0%) 3 (8.3%) 13 (36.1%)
32 (78.0%) 10 (24.4%) 14 (34.1%)
0.75b 0.06b 0.86b
0.84 (0.29–2.43) 0.28 (0.07–1.12) 1.10 (0.44–2.78)
0.75 0.07 0.86
0.36 (0.085–1.52) 0.20 (0.03–1.46) 1.53 (0.49–5.27)
0.17c 0.11d 0.49d
CI = confidence interval. a Mann–Whitney–Wilcoxon. b Chi-square. c Corrected for age and IQ. d Corrected for gender, age, IQ.
Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010
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J.A.S. Vorstman et al. / Schizophrenia Research xxx (2012) xxx–xxx
factors may shape the various phenotypic expressions that emerge. The combination of these factors may result in one or more pathways to a specific neuropsychiatric disorder. Thus, the consequence of the major genetic variant-related disruption may be a priming of one or several specific biological pathways in the brain, rendering the carrier more vulnerable to specific neuropsychiatric disorders, conforming to the model of Bassett et al. (2010). In comparison to non-carriers in the general population, relatively little more is needed to cause a neuropsychiatric disorder. The required additional factors do not have to be limited to genetic variants, and the genetic variation may or may not be limited to genetic variation directly related to the major CNV. Possible genetic causes for phenotypic variability in carriers of CNVs include variation in the remaining allele in the case of a deletion (Vorstman et al., 2009, 2011), expression-altering SNPs in close proximity to the CNV, different genomic extents of the main CNV, parent-of-origin and imprinting effects and modifying effects of other functionally relevant genes (Bassett et al., 2001, 2008; Girirajan and Eichler, 2010). To date, however, there is no evidence for parent-of-origin effects in 22q11.2DS (Bassett et al., 2008). 4.1. Strengths and limitations While a prospective design would be optimal, the current study provided data for a relatively large sample of adults with 22q11.2DS with relevant expression, including approximately equal numbers of those with and without schizophrenia, and parents available to provide information about childhood behaviors. An important limitation is that the retrospective design may have introduced biases. A recall bias, for example, could imply that the parents of those with schizophrenia may be inclined to over-report psychopathology during childhood in comparison to parents of 22q11.2DS patients without schizophrenia. If a positive correlation had been found in this study, the possibility of recall bias would have affected our ability to interpret this result. Such a finding could have been the result of a true correlation (ASD predicts psychosis) or alternatively, the result of recall bias (current psychosis biased the parents into reporting more childhood ASD). However, in the absence of a significant association between childhood ASD and later schizophrenia, the possibility of a recall bias is less relevant. The current study was only powered to detect a moderate effect size with respect to the hypothesized association between these two conditions. The a priori power to detect smaller effect sizes (Cohen's d b 0.4) was limited. However, the high similarity of the degree of autistic features in childhood between 22q11DS individuals with and those without schizophrenia suggests, post-hoc, that such smaller effects are unlikely. In fact, if anything we detected, a trend in the opposite direction (Table 1). The 22q11.2DS subgroups differed with respect to average age, however the average age in the 22q11.2DS-Co subgroup was well beyond the period of highest risk for the onset of psychosis. Parents of older patients may be less able to remember childhood behaviors and therefore may tend to underreport ASD symptoms compared to parents of younger patients. We included age as a covariate to correct for such bias and the analyses revealed no substantial impact on the results. The SRS and SCQ are meant as screening methods, not as stand-alone diagnostic instruments. Therefore, although comparable to results for children with 22q11.2DS (Niklasson et al., 2001, 2009; Antshel et al., 2007; Vorstman et al., 2006) the results of this study should not be interpreted as providing insight into the prevalence of true ASD in this sample of adults with 22q11.2DS. 5. Conclusion The current study provides evidence that in 22q11.2DS patients, ASD or autistic symptoms during childhood are not correlated with schizophrenia in adulthood. Therefore, ASDs and/or autistic symptoms cannot be considered as indicating premorbid symptoms of schizophrenia and would therefore not be useful as markers for increased vulnerability
for schizophrenia in 22q11.2DS. Although the results may or may not apply to the variability of neuropsychiatric disorders observed in other pathogenic CNVs, the 22q11.2 deletion may be useful as a model to examine the mechanisms underlying neuropsychiatric pleiotropy. Our observations indicate that ASD and schizophrenia associated with 22q11.2DS should be regarded as distinct phenotypic manifestations, consistent with true neuropsychiatric pleiotropy of the 22q11.2 deletion. Role of funding source This work was supported by grants from the Canadian Institutes of Health Research (MOP-79518, MOP-97800) and W. Garfield Weston Foundation (ASB, EWC). Dr. Bassett holds the Canada Research Chair in Schizophrenia Genetics and Genomic Disorders. J.A.S. Vorstman M.D., Ph.D. was supported by a 2006 NARSAD Young Investigator Award, funded by Stephen and Constance Lieber. Contributors Authors JV and AB took part in designing the study. Authors JV, AB, KT and EC collected the data. Author EB carried out the statistical analyses. Author JV wrote the first draft of the manuscript. Author AB contributed significantly to the writing of subsequent versions. All authors contributed to and have approved of the manuscript. Conflict of interest All authors declare that they have no conflicts of interest. Acknowledgements None.
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Please cite this article as: Vorstman, J.A.S., et al., Expression of autism spectrum and schizophrenia in patients with a 22q11.2 deletion, Schizophr. Res. (2012), http://dx.doi.org/10.1016/j.schres.2012.10.010