Hostname: page-component-78c5997874-g7gxr Total loading time: 0 Render date: 2024-11-05T21:07:44.443Z Has data issue: false hasContentIssue false

Autistic traits in psychotic disorders: prevalence, familial risk, and impact on social functioning

Published online by Cambridge University Press:  10 March 2020

Tim B. Ziermans*
Affiliation:
Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
Frederike Schirmbeck
Affiliation:
Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands Arkin Institute for Mental Health, Amsterdam, The Netherlands
Floor Oosterwijk
Affiliation:
Parnassia, Zaandam, The Netherlands
Hilde M. Geurts
Affiliation:
Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands Dr. Leo Kannerhuis, Amsterdam, The Netherlands
Lieuwe de Haan
Affiliation:
Department of Psychiatry, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands Arkin Institute for Mental Health, Amsterdam, The Netherlands
*
Author for correspondence: Tim B. Ziermans, E-mail: [email protected]
Rights & Permissions [Opens in a new window]

Abstract

Background

Prevalence estimates of autistic traits in individuals with psychotic disorders (PD) vary greatly and it is unclear whether individuals with a familial risk (FR) for psychosis have an increased propensity to display autistic traits. Furthermore, it is unknown whether the presence of comorbid autism traits disproportionally affects the cognitive and behavioral aspects of social functioning in PD.

Methods

In total, 504 individuals with PD, 587 unaffected siblings with FR, and 337 typical comparison (TC) individuals (16–50 years) were included. Autistic and psychotic traits were measured with the Autism Spectrum Quotient (AQ) and the Community Assessment of Psychic Experiences (CAPE). Social cognition was assessed with the Picture Sequencing Task (PST) and social behavior with the Social Functioning Scale (SFS).

Results

For PD 6.5% scored above AQ clinical cut-off (⩾32), 1.0% for FR, and 1.2% for TC. After accounting for age, sex, and IQ, the PD group showed significantly more autistic traits and alterations in social behavior and cognition, while FR and TC only displayed marginal differences. Within the PD group autistic traits were a robust predictor of social behavior and there were no interactions with positive psychotic symptoms.

Conclusions

Levels of autistic traits are substantially elevated in PD and have a profoundly negative association with social functioning. In contrast, autistic traits above the clinical cut-off are not elevated in those with FR, and only marginally on a dimensional level. These findings warrant specific clinical guidelines for psychotic patients who present themselves with autistic comorbidity to help address their social needs.

Type
Original Article
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
Copyright © The Author(s), 2020. Published by Cambridge University Press

Introduction

Since the concept of ‘autism’ was conceived by Bleuler in 1911 (Bleuler, Reference Bleuler1950), it has been intertwined with the diagnosis of schizophrenia and evolved from a central feature of severe psychotic disorders (PD) to a separate spectrum of clinical disorders. The literature suggests that autism spectrum disorders (ASD) and PD still co-occur more frequently than one would expect based on the prevalence rates in the general population, which gravitate around 1% for both (Chisholm, Lin, Abu-Akel, & Wood, Reference Chisholm, Lin, Abu-Akel and Wood2015). In addition, findings from longitudinal, registry-based studies convincingly suggest that individuals diagnosed with ASD are not only at an increased risk for non-affective PD such as schizophrenia, but also for affective PD, as observed in diagnosed mood disorders (Schalbroeck, Termorshuizen, Visser, Van Amelsvoort, & Selten, Reference Sasson, Pinkham, Weittenhiller, Faso and Simpson2018; Selten, Lundberg, Rai, & Magnusson, Reference Schneider, Reininghaus, van Nierop, Janssens and Myin-Germeys2015). Vice versa, the prevalence of ASD diagnoses in individuals with an established PD has been investigated less systematically and is mostly restricted to the observations in adult populations of modest sample size (Chisholm et al., Reference Chisholm, Lin, Abu-Akel and Wood2015; Kincaid, Doris, Shannon, & Mulholland, Reference Kästner, Begemann, Michel, Everts, Stepniak, Bach and Ehrenreich2017; Padgett, Miltsiou, & Tiffin, Reference Ohmuro, Katsura, Obara, Kikuchi, Sakuma, Iizuka and Matsmoto2010). Findings from the largest patient sample to date indicate a substantially elevated prevalence (3.6%, N = 197) (Davidson, Greenwood, Stansfield, & Wright, Reference Davidson, Greenwood, Stansfield and Wright2014) of ASD diagnoses among PD individuals, but this analysis did not include the prevalence estimates of sub-clinical autism traits.

Recent efforts have therefore focused more on dimensional rather than categorical approaches, under the assumption that both conditions represent extremes on a continuum of symptomatic severity, and that even isolated or low-intensity traits may affect clinical outcomes. Such studies have provided further evidence that autistic and psychotic traits co-occur at an elevated behavioral level in clinical samples (Barneveld et al., Reference Barneveld, Pieterse, de Sonneville, van Rijn, Lahuis, van Engeland and Swaab2011; De Crescenzo et al., Reference De Crescenzo, Postorino, Siracusano, Riccioni, Armando, Curatolo and Mazzone2019; Esterberg, Trotman, Brasfield, Compton, & Walker, Reference Eack, Bahorik, McKnight, Hogarty, Greenwald, Newhill and Minshew2008; Fagel et al., Reference Esterberg, Trotman, Brasfield, Compton and Walker2013; Kincaid et al., Reference Kästner, Begemann, Michel, Everts, Stepniak, Bach and Ehrenreich2017; Ziermans, Swaab, Stockmann, de Bruin, & van Rijn, Reference Zarrei, Burton, Engchuan, Young, Higginbotham, MacDonald and Scherer2017). From a cognitive and functional perspective, it is also well established that both ASD and PD are characterized by (partially) overlapping impairments compared to typical healthy comparisons, particularly in the social domain (Martinez et al., Reference Malla and Payne2017; Pinkham et al., Reference Pepper, Demetriou, Park, Song, Hickie, Cacciotti-Saija and Guastella2019; Sasson et al., Reference Sasamoto, Miyata, Hirao, Fujiwara, Kawada, Fujimoto and Murai2007, Reference Sasson, Tsuchiya, Hurley, Couture, Penn, Adolphs and Piven2011, Reference Sasson, Pinkham, Carpenter and Belger2016; Velthorst et al., Reference Vaskinn and Abu-Akel2018). However, it is currently unclear whether the presence of comorbid autistic and psychotic traits has a detrimental effect on the outcome. A recent study in schizophrenia patients with a positive screening for ASD (28 out of 75) showed an increased duration of illness, more general psychopathology, and worse cognitive functioning (working memory and processing speed) compared to patients without ASD traits, yet similar levels of IQ, social cognition, and functioning (Barlati, Deste, Gregorelli, & Vita, Reference Barlati, Deste, Gregorelli and Vita2019). In contrast, Vaskinn and Abu-Akel (Reference van Rooijen, Isvoranu, Kruijt, van Borkulo, Meijer, Wigman and Bartels-Velthuis2019) used a dimensional approach and concluded that the presence of more psychotic and autistic traits in schizophrenia patients (N = 81) was associated with relatively better functioning and mentalizing. The latter finding also provided clinical support for the (counterintuitive) diametrical model of autism and psychosis (Crespi & Badcock, Reference Crespi and Badcock2008), which posits that both disorders have opposite genetic relations and that co-occurrence would diametrically modulate behavior toward normality.

Whether genetic markers associated with autism and psychosis are diametrical opposites remains open to debate. There is ample evidence, however, that etiological overlap between both conditions does exist, as further supported by recent studies focusing on polygenic risk for both autism and schizophrenia (Fromer et al., Reference Fagel, Swaab, De Sonneville, Van Rijn, Pieterse, Scheepers and Van Engeland2016; Pourcain et al., Reference Pinkham, Morrison, Penn, Harvey, Kelsven, Ludwig and Sasson2018; Velthorst et al., Reference Vaskinn and Abu-Akel2018), as well as the presence of rare copy-number variations in both populations (Kushima et al., Reference Korver, Quee, Boos, Simons, De Haan, Kahn and Linszen2018; Zarrei et al., Reference Wüsten, Schlier, Jaya, Fonseca-Pedrero, Peters, Verdoux and Lincoln2019). In addition, given the highly heritable nature of both ASD and PD, it is reasonable to expect a higher co-occurrence of subclinical traits of both dimensions in unaffected relatives of either patient population. Indeed, twin data have suggested that psychiatric disorders in general are associated with continuously distributed genetic risks throughout the general population (Taylor et al., Reference Sullivan, Magnusson, Reichenberg, Boman, Dalman, Davidson and Lichtenstein2019). An important next step is to establish whether concurrent traits of autism and psychosis are also associated with social impairments in at-risk samples.

The primary aim of the current study was to establish the prevalence of autistic traits in a substantial group of PD individuals compared to their unaffected siblings with a familial risk for PD (FR) and a typical comparison (TC) group. It was expected that the PD group would show more autistic traits than the TC group, with a large effect size, and the FR group in an intermediate position. The second aim was to establish to what extent the levels of autism or psychotic traits were associated with social cognition and social functioning, using both categorical and dimensional approaches. It was expected that both psychotic and autism traits would show independent negative associations with social cognition and functioning across groups, but most profoundly within the PD group as we assumed they would display more variability in trait scores and therefore stronger associations. A third and final aim was to explore whether our data could provide any further support for the diametric hypothesis, which postulates that negative main effects of both autistic and positive psychotic traits on social functioning are modulated toward positivity if both are present.

Methods

The current cross-sectional study is part of a longitudinal cohort study, Genetic Risk and Outcome of Psychosis (GROUP). The main objective of GROUP is to elucidate etiological and pathogenetic factors influencing the onset and course of PD in patients, their unaffected family members, and non-related controls. For a full description of recruitment and assessment procedures, the reader is referred to a previous publication on this topic (Korver et al., Reference Kincaid, Doris, Shannon and Mulholland2012).

Participants

Participant groups for this study consisted of patients diagnosed with schizophrenia or related PD, unaffected siblings with FR and TC individuals from the general population. Participants were recruited in 36 mental health care institutes in the Netherlands and Belgium. PD were identified through clinicians in the participating institutes by applying the following inclusion criteria: (1) age between 16 and 50 years, (2) meet DSM-IV-TR (American Psychiatric Association, 2000) criteria for a non-affective PD, (3) good command of the Dutch language, and (4) able and willing to provide informed consent. Siblings were not allowed to meet the criteria for a lifetime diagnosis of any PD at baseline. Healthy control participants had no lifetime diagnosis of a PD at baseline and no first-degree relative with a lifetime PD. For the purpose of the present study, we only included participants from the database (Data release 6.0) with available data on the Autism Spectrum Quotient (AQ) (Baron-Cohen, Wheelwright, Skinner, Martin, & Clubley, Reference Baron-Cohen, Wheelwright, Skinner, Martin and Clubley2001) measured at the 6-year follow-up assessment (T3). The study was approved by the Medical Ethics Committee of the University Medical Center Utrecht and subsequently by local review boards of each participating institute. All subjects gave written informed consent in accordance with the committee's guidelines.

Instruments

Global cognitive functioning

All participants were assessed with a cognitive task battery that included four tasks (Arithmetic, Block Design, Digit Symbol-Coding, and Information) of the Dutch version of the Wechsler Adult Intelligence Scale – Third Edition (WAIS-III; Wechsler, Reference Velthorst, Froudist-Walsh, Stahl, Ruderfer, Ivanov, Buxbaum and Martin1997), resulting in a total IQ estimate.

Psychotic traits

Psychotic traits were assessed with the Community Assessment of Psychic Experiences (CAPE; Stefanis et al., Reference Selten, Lundberg, Rai and Magnusson2002). This self-report scale typically measures the lifetime prevalence of positive, negative, and depressive traits on both a frequency scale and a distress scale. Because the instrument was assessed as part of a follow-up study, individuals were instructed to answer the questions with regard to the last 3 years (since the previous assessment). Only the more commonly used frequency scores were included in this study.

Autistic traits

The AQ is a well-validated, 50-item self-report questionnaire that measures autism traits and is commonly used to screen for ASD diagnosis (Woodbury-Smith, Robinson, Wheelwright, & Baron-Cohen, Reference Wing, Babor, Brugha, Burke, Cooper, Giel and Sartorius2005). AQ scores fall within the range of 0–50 and higher scores indicate a higher level of autism traits. In addition, AQ scores of ⩾32 indicate that an ASD diagnosis may be appropriate, and individuals with ASD are unlikely to score below a threshold of 26 (Baron-Cohen et al., Reference Baron-Cohen, Wheelwright, Skinner, Martin and Clubley2001; Woodbury-Smith et al., Reference Wing, Babor, Brugha, Burke, Cooper, Giel and Sartorius2005). The AQ consists of five subscales measuring the following domains: social skills, communication, imagination, attention switching, and attention to detail. The Dutch translation of the AQ was used for this study (Hoekstra, Bartels, Cath, & Boomsma, Reference Harvey, Deckler, Jones, Jarskog, Penn and Pinkham2008).

Social functioning

Cognition. The Picture Sequencing Task (PST; Langdon and Coltheart, Reference Kushima, Aleksic, Nakatochi, Shimamura, Okada, Uno and Arioka1999) was assessed to measure mentalizing ability in participants. The PST consists of stories depicted in four illustrated (black and white) card picture sequences. Subjects are asked to turn over the cards placed in front of them and to place them in the correct order to show a logical sequence of events. The false-belief (PST-FB) stories depict a story character who, unaware of an event that occurred in a story, acted on his or her misinformation. These stories have previously been associated with underperformance in individuals with schizophrenia (Langdon, Coltheart, & Ward, Reference Langdon and Coltheart2006) and autism (Baron-Cohen, Leslie, & Frith, Reference Baron-Cohen, Leslie and Frith1986). Total score ranges between 0 and 24.

Behavior. On a daily behavioral level, social functioning was assessed with the Social Functioning Scale (SFS; Birchwood, Smith, Cochrane, Wetton, and Copestake, Reference Birchwood, Smith, Cochrane, Wetton and Copestake1990), a widely used self-report instrument to measure the areas of functioning essential for successful community maintenance. The total scaled score on the SFS was used as a measure of overall social functioning in the past 3 months. Higher scores on the SFS indicate higher levels of social functioning. It has a mean standardized score of 100, with a standard deviation of 15. It is commonly assessed in PD, and adults with ASD have an equally reduced score on this instrument compared to TC (Chan et al., Reference Chan, Kong, Park, Song, Demetriou, Pepper and Guastella2019).

Statistical analysis

The χ2 and ANOVA tests were used for the comparisons of group characteristics, with Cramer's V and partial η 2 as respective effect sizes, followed by Games–Howell or Hochberg's G2 post hoc tests, where applicable. To compare the prevalence of autism and psychotic traits (AQ and CAPE) across groups, a missing value analysis was conducted and missing items were imputed with the predicted mean matching method (Markov chain Monte Carlo; 50 iterations) to generate subscale and total scores for all individuals. Proportions above cut-off scores were compared with χ2 tests. Next, (M)ANCOVA was implemented by using general linear models with age, sex, and IQ entered as covariates and Bonferroni-corrected post hoc comparisons.

Next, we assessed the relative impact of autism traits on social functioning across groups by conducting two separate series of multilevel mixed linear models for both dependent variables. A two-level model with random intercepts was applied, i.e. measurements within families and within study sites. Age, IQ, and trait scores were centered around their respective means. In the initial models, group was entered as a factor. Significant analyses were continued for PD only, as this was the primary group of interest. The relative goodness of fit of the competing models was evaluated with the Akaike information criterion (AIC) and the Bayesian information criterion (BIC), where smaller values indicate a better fit. Finally, to test for a possible diametric effect between positive symptoms and autistic symptoms, the analyses were repeated with AQ Total, CAPE positive, and their interaction term included. Multilevel models were computed with the unstructured covariance setting and maximum likelihood estimation.

To improve reproducibility and reduce the chance of Type I error, a critical p value of <0.005 was applied for all ad hoc analyses (Benjamin et al., Reference Benjamin, Berger, Johannesson, Nosek, Wagenmakers, Berk and Johnson2018) and p < 0.05 for post hoc and explorative analyses. Cohen's d, based on pooled variances and estimated marginal means, was calculated for the effect sizes of group differences and the standardized β coefficient was reported as an effect size for individual predictors in multilevel analyses.

Results

Demographics and clinical characteristics

Data were available for 504 PD, 572 FR, and 337 TC individuals (N = 1413). Demographic data and clinical characteristics are provided in Table 1. Groups differed significantly on sex, age, education, and IQ estimate (all p < 0.001). Post hoc testing showed that there were significantly more males in the PD group than in the FR (χ2 = 161.16, p < 0.001, V = 0.28) or TC group (χ2 = 129.89, p < 0.001, V = 0.30). Both the PD and FR groups had a lower mean age than the TC group (both p < 0.001, η2 partial = 0.08 and 0.06) and education (post hoc, all p < 0.001, V range = 0.14–0.44) and IQ estimates differed for all group comparisons (post hoc, all p < 0.01, η2 partial, range = 0.01–0.14) with PD showing the lowest average IQ score and TC the highest.

Table 1. Demographic and clinical characteristics of patients, siblings, and healthy controls in the GROUP study, mean scores (standard deviations) and absolute numbers (%)

PD, psychotic disorder group; FR, familial risk group; TC, typical comparison group; ES, effect size.

a Games–Howell, p < 0.05.

b Missing data: Age of onset – 1 PD, IQ – 1 FR, CAPE – 2 PD & 3 FR, PANSS – max. 20 PD.

c Based on the Comprehensive Assessment of Symptoms and History (CASH; Andreasen, Flaum, and Arndt, Reference Andreasen, Flaum and Arndt1992) and the Schedules for Clinical Assessment for Neuropsychiatry (SCAN 2.1; Wing et al., Reference Wigman, Van Os, Borsboom, Wardenaar, Epskamp, Klippel and Wichers1990) at baseline, reported for schizophrenia spectrum only.

d Based on PANSS remission tool (Andreasen et al., Reference Andreasen, Carpenter, Kane, Lasser, Marder and Weinberger2005).

In the PD group, schizophrenia diagnoses were the most common primary DSM-IV diagnosis (61.5%), followed by psychotic (15.7%) and schizoaffective (13.7%) diagnoses. Psychotic traits on all three CAPE dimensions (Positive, Negative, and Depressive) were significantly more frequent in PD compared to FR and TC (all p < 0.001, η2 partial, range = 0.12–0.23). In addition, FR reported significantly more negative traits than TC on average (p = 0.018, η2 partial = 0.01), but no difference in positive (p = 0.561, η2 partial = 0.00) or depressive traits (p = 0.542, η2 partial = 0.00).

Autistic traits

Missing value analysis indicated that for 54 individuals (3.8%; 31 PD, 17 FR, 6 TC) AQ data were incomplete, with a total of 0.1% of items missing. Due to the small proportion of missing values, a single imputed data set was generated. Total AQ score distributions are illustrated in Fig. 1 and reported by group and gender for all subscales in Table 2. Based on recommended and most stringent clinical cut-offs for Total AQ scores (Table 2), 6.5% of PD scored ⩾32 and 21.4% ⩾26, while lower proportions scored above these thresholds in the FR (1.0% and 2.8%) and TC (1.2% and 2.3%) groups, respectively. Proportions differed significantly across all groups for AQ ⩾ 32 (χ2 = 32.62, p < 0.001, V = 0.15) and AQ ⩾ 26 (χ2 = 135.19, p < 0.001, V = 0.31). Post hoc comparisons showed that PD differed from the other groups on both cut-offs (all p < 0.001, V range = 0.13–0.27), but FR did not differ from TC (p = 0.85, V = 0.01 and p = 0.70, V = 0.01, respectively).

Fig. 1. Left: Histogram plot with the normal curve of Total AQ scores stacked across groups. Right: Normal curves per group: PD (top), FR (middle), and TC (bottom).

Table 2. AQ data per group, mean scores (standard deviations) and number of participants exceeding standard AQ cut-off scores (%)

Next, mean comparisons showed that groups differed significantly on the overall level of autistic traits, covaried for age, sex, and IQ (F 2,1406 = 129.28, p < 0.001, η2 partial = 0.16). Covariates were significant as well, with positive effects for age (p = 0.004, η2 partial = 0.01) and male sex (p < 0.001, η2 partial = 0.01), and a negative effect for IQ (p < 0.001, η2 partial = 0.01). Bonferroni-corrected post hoc comparisons indicated that PD reported significantly more autistic traits than FR (p < 0.001, d = 0.80) and TC (p < 0.001, d = 0.92). FR also reported more autistic traits than TC, albeit with a small effect size (p = 0.028, d = 0.18). On a subscale level MANCOVA analysis showed similar group differences on all subscales (all p < 0.001), except post hoc tests were not significant for mean differences between FR and TC.

Impact of autistic traits on social functioning in PD

Group, Total AQ, and CAPE Positive were entered by default in the initial models. Linearity assumptions (p < 0.05; correlations in online Supplementary Tables) were checked next to determine which additional variables were entered into the models. In the initial models only main effects were included. Additional two-way interactions were also examined for potential model optimization.

Cognition. PST-FB data were missing for 55 individuals (17 PD, 18 FR, 20 TC). Standardized group means are displayed in Fig. 2. In addition to Group, Total AQ, and CAPE Positive, the covariates age and IQ were also included. There was no significant group effect on PST-FB (p = 0.124), hence model comparison was continued for the total sample without Group as a factor. The best fit (see Table 3a) included: Total AQ (β = −0.09, p = 0.001), age (β = −0.20, p < 0.001), IQ (β = 0.28, p < 0.001), and Total AQ × age (β = −0.07, p = 0.002). CAPE Positive was not significant and no longer included in the final model.

Fig. 2. Z-transformed group means for Picture Sequencing Test – False Belief (PST-FB; left) and the Social Functioning Scale (SFS; right). Error bars represent ±1 standard error.

Table 3. Best-fitting multilevel models for social functioning

Centered around the means: Total AQ = 20.04, age = 33.38, IQ = 100.72, CAPE Negative = 26.25.

Behavior. SFS data were missing for 10 individuals (four PD, four FR, two TC). See Fig. 2 for standardized group means. All candidate predictors were included. There was a significant group effect on SFS (F = 45.70, p < 0.001). Bonferroni-corrected post hoc comparisons indicated that PD differed significantly from the other groups (p < 0.001), but FR did not differ from TC. Model comparison was then continued for the PD group only. The best model fit (see Table 3b) included fixed effects for age (β = −0.09, p = 0.019), sex (β = 0.21, p < 0.001), IQ (β = 0.19, p < 0.001), Total AQ (β = −0.37, p < 0.001), and CAPE Negative (β = −0.24, p < 0.001). Neither CAPE Positive and CAPE Depressive, nor any two-way interactions improved both AIC and BIC values.

Interaction autistic and positive symptoms. Adding the interaction term Total AQ × CAPE Positive did not yield significant predictors or model improvements for PST-FB or SFS. To allow for better statistical comparison with previous results from Vaskinn and Abu-Akel (Reference van Rooijen, Isvoranu, Kruijt, van Borkulo, Meijer, Wigman and Bartels-Velthuis2019), the analyses were repeated in generalized linear models for PD only, without region and family ID included in the models. Again, no significant interactions supporting a diametrical model were detected (see online Supplementary Tables).

Discussion

The current study provides robust evidence for a substantially increased presence of autistic traits in individuals diagnosed with PD compared to their unaffected siblings and TC individuals. This concerns both categorical and dimensional levels of autistic traits, which may arguably reflect separate etiologies (Abu-Akel, Allison, Baron-Cohen, & Heinke, Reference Abu-Akel, Allison, Baron-Cohen and Heinke2019; Linscott & van Os, Reference Langdon, Coltheart and Ward2010). Concerning categorical classifications, an AQ cut-off of 32 is known to discriminate satisfactorily between ASD and TC individuals, and a cut-off of 26 shows reasonable sensitivity (Baron-Cohen et al., Reference Baron-Cohen, Wheelwright, Skinner, Martin and Clubley2001; Woodbury-Smith et al., Reference Wing, Babor, Brugha, Burke, Cooper, Giel and Sartorius2005). Therefore, our findings suggest that one in 15 individuals with PD falls above the clinical cut-off, and one in five above the sub-clinical threshold. For FR, the odds are, respectively, 6 and 7 times smaller than for PD, and comparable with TC. However, the predictive diagnostic accuracy of AQ thresholds in suspected ASD appears modest (Ashwood et al., Reference Ashwood, Gillan, Horder, Hayward, Woodhouse, McEwen and Murphy2016), and in our sample, only six (1.2%) PD individuals had a suspected diagnosis of ASD at intake. This raises the question whether elevated autistic traits in PD may reflect symptomatic overlap, in particular with negative psychotic traits. Based on the assessments used in this study, there is evident overlap between the social skill subscale of AQ (10 items; e.g. ‘I enjoy meeting new people’) and social withdrawal items of the CAPE (four items; e.g. ‘Do you ever feel you have no interest to be with other people’). Nevertheless, most items do not resemble each other as closely and correlations of AQ and CAPE in PD individuals were modest and comparable for all dimensions (0.32–0.36; online Supplementary Table). Therefore, symptom overlap can only provide a limited explanation for the increased presence of autistic traits in PD. Regardless, the absence of diagnoses in our sample further emphasizes that comorbid ASD is potentially overlooked or wrongfully dismissed by clinicians presented with PD cases.

On a dimensional level, group differences in autism traits are equally striking for PD and in line with previous findings in smaller samples (Lugnegard, Hallerbäck, & Gillberg, Reference Linscott and van Os2015; Sasamoto et al., Reference Pourcain, Robinson, Anttila, Sullivan, Maller, Golding and Davey Smith2011). Additionally, individuals with FR reported marginally more autism traits than TC when the potential effects of age, sex, and IQ were accounted for. However, this group difference dissipated on a subscale level. Importantly, our sibling group was unaffected in terms of schizophrenia spectrum diagnoses, but not completely devoid of other comorbid conditions, in particular mood disorders (n = 111, including 74 remissions). Explorative post hoc analyses indicated that those who met the criteria for any DSM-IV disorder (n = 126; M = 15.48) scored significantly higher on AQ than those not meeting any criteria (n = 446, M = 12.91, p < 0.001). In addition, the few siblings who did acquire a PD after baseline were reassigned to the patient group. This likely led to a slight underestimation of psychotic and autistic traits in the sibling group than would be expected based on family history alone (Sullivan et al., Reference Stouten, Veling, Laan, van der Helm and van der Gaag2012). As such, we can ascertain that only unaffected siblings of individuals with PD are relatively resistant to developing autistic traits.

As expected, the results provide strong evidence for a profoundly negative relation of autism traits with social functioning in PD. Comparable data are surprisingly scarce or only available for modest and mostly pediatric samples, with three notable exceptions that all used the PANSS Autism Severity Score (PAUSS; Kästner et al., Reference Hoekstra, Bartels, Cath and Boomsma2015) to measure autism symptoms in adult PD. Barlati et al. (Reference Barlati, Deste, Gregorelli and Vita2019) showed that psychosocial functioning did not differ between schizophrenia patients (N = 75) with and without autism, after patients were thoroughly screened for ASD. However, global measures of functioning were used (Honos, GAF) and the prediction of autism severity scales was dichotomized, making it difficult to establish any potential linear dosage effects on a dimensional scale. Vaskinn and Abu-Akel (Reference van Rooijen, Isvoranu, Kruijt, van Borkulo, Meijer, Wigman and Bartels-Velthuis2019) did report a negative linear relation between autistic symptoms and functioning in PD (N = 81) by using both GAF and SFS as outcome measures, but also found positive two-way interaction effects with positive symptoms that were suggestive of diametric effects on functioning (discussed further below). Finally, Harvey et al. also found a small but significant effect of autistic symptoms on real-world functioning in PD (N = 171) (Harvey et al., Reference Fromer, Roussos, Sieberts, Johnson, Kavanagh, Perumal and Sklar2019). Our results add to these findings a more robust outcome and direct comparisons with a related and unrelated group of individuals without PD.

Although it is known that cognitive and negative symptoms are better predictors of functional outcome (Malla & Payne, Reference Lundqvist and Lindner2005; Stouten, Veling, Laan, van der Helm, & van der Gaag, Reference Stefanis, Hanssen, Smirnis, Avramopoulos, Evdokimidis, Stefanis and Van Os2017), it was still somewhat unexpected that there were no significant relations between positive psychotic traits and social functioning. The positive traits were also relatively low in our PD sample, perhaps due to treatment effects, which may help explain the absence of associations with functioning measures. To improve our understanding of the dynamics between co-occurring autistic traits, psychotic traits, and functioning in PD, it would therefore be of great interest to study the strength of relations on a subdomain level and determine centrality measures within a network approach (van Rooijen et al., Reference Taylor, Martin, Lu, Brikell, Lundström, Larsson and Lichtenstein2018; Wigman et al., Reference Wechsler2015; Wüsten et al., Reference Woodbury-Smith, Robinson, Wheelwright and Baron-Cohen2018).

Social cognitive functioning was also negatively associated with autistic traits in line with previous findings (Harvey et al., Reference Fromer, Roussos, Sieberts, Johnson, Kavanagh, Perumal and Sklar2019; Vaskinn & Abu-Akel, Reference van Rooijen, Isvoranu, Kruijt, van Borkulo, Meijer, Wigman and Bartels-Velthuis2019) but, contrary to expectations, the effect was small and comparable across groups. Likewise, the correlation between social cognition and social functioning was surprisingly small. We used a classic mentalizing (false belief) paradigm, which is typically performed less accurately by individuals with PD (Langdon et al., Reference Langdon and Coltheart2006), though not always (Pepper et al., Reference Padgett, Miltsiou and Tiffin2018). Group differences in mentalizing were obscured by relatively strong effects of IQ and age in our study. However, these differences may be meaningful in their own right and covarying for them may not always be necessary or preferable in some instances (Miller & Chapman, Reference Martinez, Alexandre, Mam-Lam-Fook, Bendjemaa, Gaillard, Garel and Krebs2001). The influence of other factors affecting outcome may also help explain why mentalizing performance may not be sensitive enough to reveal strong relations with the functional outcome (Ohmuro et al., Reference Miller and Chapman2016). Notwithstanding, it is safe to conclude from our results that autistic traits are negatively associated with mentalizing abilities in general, hence also for PD. Possibly, the effect would have been stronger if other, lower-order social cognition tasks (i.e. emotion recognition) were used, as these appear to be more clearly impaired in both PD and ASD (Eack et al., Reference Davidson, Greenwood, Stansfield and Wright2013; Pepper et al., Reference Padgett, Miltsiou and Tiffin2018; Sasson, Pinkham, Weittenhiller, Faso, & Simpson, Reference Sasson, Pinkham, Carpenter and Belger2016). Future studies may benefit in general from broader and more ecologically valid assessments of social cognition.

A final aim of this study was to explore the presence of diametric effects of autistic and positive psychotic traits on social functioning. Contrary to recent exciting findings in non-clinical (Abu-Akel, Wood, Hansen, & Apperly, Reference Abu-Akel, Wood, Hansen and Apperly2015, Reference Abu-Akel, Apperly, Wood and Hansen2017b, Reference Abu-Akel, Apperly, Wood, Hansen and Mevorach2017a, Reference Abu-Akel, Apperly, Spaniol, Geng and Mevorach2018a) and clinical (Abu-Akel et al., Reference Abu-Akel, Testa, Jones, Ross, Skafidas, Tonge and Pantelis2018b; Vaskinn & Abu-Akel, Reference van Rooijen, Isvoranu, Kruijt, van Borkulo, Meijer, Wigman and Bartels-Velthuis2019) samples in the literature, our results do not provide further support for the diametric hypothesis. Although there are some differences in samples and methods across studies, the type, quality, and amount of data available to address this question in the GROUP cohort would have been sufficient to detect even small interaction effects if a diametric relation had been present. It is unclear how to interpret these opposing findings and we propose future studies address the diametric hypothesis by cross-validation in different samples with identical methods.

Several limitations should be considered when interpreting our findings. First, despite their psychometric strengths and common use, self-report questionnaires such as AQ-50 and SFS have notable shortcomings. For example, the AQ-50 is not equivalent to an objective assessment of autistic traits, potentially affected by subgroup bias (Agelink van Rentergem, Lever, & Geurts, Reference Agelink van Rentergem, Lever and Geurts2019) and has a debatable factor structure (Lundqvist & Lindner, Reference Lugnegard, Hallerbäck and Gillberg2017). Additional observations, interviews, or informant reports are required to confirm the presence of traits and/or a clinical diagnosis of ASD in PD. Concurrently, it would help establish convergent validity of ASD assessments in PD and reduce potential bias introduced by mono-method associations (i.e. based on self-report). The SFS was constructed specifically to tap those areas of functioning that are crucial to individuals with schizophrenia and related disorders and generally has good psychometric properties, but its use may be suboptimal for assessing social functioning in individuals with ASD (Chan et al., Reference Chan, Kong, Park, Song, Demetriou, Pepper and Guastella2019) and some domains may have low ecological validity (Schneider et al., Reference Schalbroeck, Termorshuizen, Visser, Van Amelsvoort and Selten2017). Second, data were assessed approximately 6 years after baseline. Consequently, a relatively large portion of PD individuals (approximately 40%) fulfilled PANSS remission criteria. It is up to speculation if and how this affected the prevalence rates and relations with social functioning. Interestingly, when assessed post hoc, PD individuals in remission had significantly lower AQ scores than those not in remission, which could indicate that the impact of autistic traits extends beyond social functioning. Third, the data were cross-sectional and can therefore only establish concurrent relations and not whether autism traits are an actual determinant of poor outcome. Only follow-up data can and should address this in the future.

In conclusion, this report set out to establish the prevalence of (self-reported) autistic traits in an unprecedented sample size of individuals with PD and their unaffected siblings compared to typical comparisons. Our results confirm that the prevalence is overwhelmingly higher in PD, both categorically and dimensionally, an only marginally higher in FR on a dimensional level. The higher prevalence in PD is accompanied by a strong negative relation with social functioning on a behavioral level and to a lesser extent on a cognitive level. This indicates a need for better transdiagnostic clinical guidelines. For example, it is generally accepted that psychotic decompensation can occur due to a maladaptive stress response. For individuals on the autism spectrum, there are often clear indicators which situations trigger a severe stress response, e.g. sensory overload or unexpected, life-changing events. Therefore, when they present themselves with prodromal symptoms, these individuals can benefit from supervised daily schedules and access to a stimulus-free room to help prevent the onset/relapse of psychosis and potentially marginalize the need for antipsychotic treatment. These and other alternative treatment hypotheses need to be substantiated with additional scientific evidence (e.g. from clinical trials), but are worthy of consideration. Taken together, our findings suggest that autistic comorbidity in PD represents a very relevant clinical issue that needs to be addressed in order to improve treatment outcome.

Supplementary material

The supplementary material for this article can be found at https://doi.org/10.1017/S0033291720000458

Acknowledgements

We are grateful for the generosity of time and effort by the patients, their families, and healthy subjects. Furthermore, thanks to all research personnel involved in the GROUP project, in particular: Joyce van Baaren, Erwin Veermans, Ger Driessen, Truda Driesen, Erna van ‘t Hag.

Financial support

This work was supported by the Brain & Behaviour Research Foundation (T.Z., NARSAD Young Investigator grant, number 25500). The infrastructure for the GROUP study is funded through the Geestkracht program of the Dutch Health Research Council (Zon-Mw, grant number 10-000-1001), and matching funds from participating pharmaceutical companies (Lundbeck, AstraZeneca, Eli Lilly, Janssen Cilag) and universities and mental health care organizations.

Conflict of interest

None.

Footnotes

*

(Therese van Amelsvoortf, Agna A. Bartels-Velthuisg, Richard Bruggemang,h, Wiepke Cahni,j, Claudia J.P. Simonsf,k, Jim van Osi,l) fMaastricht University Medical Center, Department of Psychiatry and Neuropsychology, School for Mental Health and Neuroscience, Maastricht, The Netherlands; gUniversity of Groningen, University Medical Center Groningen, University Center for Psychiatry, Rob Giel Research center, Groningen, The Netherlands; hUniversity of Groningen, Department of Clinical and Developmental Neuropsychology, Groningen, The Netherlands; iUniversity Medical Center Utrecht, Department of Psychiatry, Brain Centre Rudolf Magnus, Utrecht University, Utrecht, The Netherlands; jAltrecht, General Menthal Health Care, Utrecht, The Netherlands; kGGzE Institute for Mental Health Care, Eindhoven, the Netherlands; lKing's College London, King's Health Partners, Department of Psychosis Studies, Institute of Psychiatry, London, United Kingdom.

References

Abu-Akel, A., Allison, C., Baron-Cohen, S., & Heinke, D. (2019). The distribution of autistic traits across the autism spectrum: Evidence for discontinuous dimensional subpopulations underlying the autism continuum. Molecular Autism, 10, 17521764.CrossRefGoogle ScholarPubMed
Abu-Akel, A., Apperly, I., Spaniol, M. M., Geng, J. J., & Mevorach, C. (2018a). Diametric effects of autism tendencies and psychosis proneness on attention control irrespective of task demands. Scientific Reports, 8, 8478.CrossRefGoogle Scholar
Abu-Akel, A. M., Apperly, I. A., Wood, S. J., & Hansen, P. C. (2017b). Autism and psychosis expressions diametrically modulate the right temporoparietal junction. Social Neuroscience, 12, 506518.CrossRefGoogle Scholar
Abu-Akel, A., Apperly, I. A., Wood, S. J., Hansen, P. C., & Mevorach, C. (2017a). Autism tendencies and psychosis proneness interactively modulate saliency cost. Schizophrenia Bulletin, 43, 142151.CrossRefGoogle Scholar
Abu-Akel, A., Testa, R. R., Jones, H. P., Ross, N., Skafidas, E., Tonge, B., & Pantelis, C. (2018b). Attentional set-shifting and social abilities in children with schizotypal and comorbid autism spectrum disorders. Australian and New Zealand Journal of Psychiatry, 52, 6877.CrossRefGoogle Scholar
Abu-Akel, A. M., Wood, S. J., Hansen, P. C., & Apperly, I. A. (2015). Perspective-taking abilities in the balance between autism tendencies and psychosis proneness. Proceedings of the Royal Society B: Biological Sciences, 282, 20150563.CrossRefGoogle ScholarPubMed
Agelink van Rentergem, J. A., Lever, A. G., & Geurts, H. M. (2019). Negatively phrased items of the Autism Spectrum Quotient function differently for groups with and without autism. Autism, 23, 17521764.CrossRefGoogle ScholarPubMed
American Psychiatric Association (2000). Diagnostic and statistical manual of mental Disorders (4th ed). Washington, DC: DSM-IV-TR.Google Scholar
Andreasen, N. C., Carpenter, W. T., Kane, J. M., Lasser, R. A., Marder, S. R., & Weinberger, D. R. (2005). Remission in schizophrenia: Proposed criteria and rationale for consensus. American Journal of Psychiatry, 162, 441449.CrossRefGoogle ScholarPubMed
Andreasen, N. C., Flaum, M., & Arndt, S. (1992). The Comprehensive Assessment of Symptoms and History (CASH): An instrument for assessing diagnosis and psychopathology. Archives of General Psychiatry, 49, 615623.CrossRefGoogle ScholarPubMed
Ashwood, K. L., Gillan, N., Horder, J., Hayward, H., Woodhouse, E., McEwen, F. S., … Murphy, D. G. (2016). Predicting the diagnosis of autism in adults using the Autism-Spectrum Quotient (AQ) questionnaire. Psychological Medicine, 46, 25952604.CrossRefGoogle Scholar
Barlati, S., Deste, G., Gregorelli, M., & Vita, A. (2019). Autistic traits in a sample of adult patients with schizophrenia: Prevalence and correlates. Psychological Medicine, 49, 140148.CrossRefGoogle Scholar
Barneveld, P. S., Pieterse, J., de Sonneville, L., van Rijn, S., Lahuis, B., van Engeland, H., & Swaab, H. (2011). Overlap of autistic and schizotypal traits in adolescents with autism spectrum disorders. Schizophrenia Research, 126, 231236.CrossRefGoogle ScholarPubMed
Baron-Cohen, S., Leslie, A. M., & Frith, U. (1986). Mechanical, behavioural and intentional understanding of picture stories in autistic children. British Journal of Developmental Psychology, 4, 113125.CrossRefGoogle Scholar
Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The Autism-Spectrum Quotient (AQ): Evidence from Asperger syndrome/high-functioning autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31, 517.CrossRefGoogle ScholarPubMed
Benjamin, D. J., Berger, J. O., Johannesson, M., Nosek, B. A., Wagenmakers, E. J., Berk, R., … Johnson, V. E. (2018). Redefine statistical significance. Nature Human Behaviour, 2, 610.CrossRefGoogle ScholarPubMed
Birchwood, M., Smith, J., Cochrane, R., Wetton, S., & Copestake, S. (1990). The Social Functioning Scale. The development and validation of a new scale of social adjustment for use in family intervention programmes with schizophrenic patients. British Journal of Psychiatry, 157, 853859.CrossRefGoogle ScholarPubMed
Bleuler, E. (1950). Dementia praecox or the group of schizophrenias. Oxford, England: International Universities Press.Google Scholar
Chan, E. H. C., Kong, S. D. X., Park, S. H., Song, Y. J. C., Demetriou, E. A., Pepper, K. L., … Guastella, A. J. (2019). Validation of the social functioning scale: Comparison and evaluation in early psychosis, autism spectrum disorder and social anxiety disorder. Psychiatry Research, 276, 4555.CrossRefGoogle ScholarPubMed
Chisholm, K., Lin, A., Abu-Akel, A., & Wood, S. J. (2015). The association between autism and schizophrenia spectrum disorders: A review of eight alternate models of co-occurrence. Neuroscience and Biobehavioral Reviews, 55, 173183.CrossRefGoogle ScholarPubMed
Crespi, B., & Badcock, C. (2008). Psychosis and autism as diametrical disorders of the social brain. Behavioral and Brain Sciences, 31, 241261.CrossRefGoogle ScholarPubMed
Davidson, C., Greenwood, N., Stansfield, A., & Wright, S. (2014). Prevalence of Asperger syndrome among patients of an early intervention in psychosis team. Early Intervention in Psychiatry, 8, 138146.CrossRefGoogle ScholarPubMed
De Crescenzo, F., Postorino, V., Siracusano, M., Riccioni, A., Armando, M., Curatolo, P., & Mazzone, L. (2019). Autistic symptoms in schizophrenia spectrum disorders: A systematic review and meta-analysis. Frontiers in Psychiatry, 10, 111.CrossRefGoogle ScholarPubMed
Eack, S. M., Bahorik, A. L., McKnight, S. A. F., Hogarty, S. S., Greenwald, D. P., Newhill, C. E., … Minshew, N. J. (2013). Commonalities in social and non-social cognitive impairments in adults with autism spectrum disorder and schizophrenia. Schizophrenia Research, 148, 2428.CrossRefGoogle Scholar
Esterberg, M. L., Trotman, H. D., Brasfield, J. L., Compton, M. T., & Walker, E. F. (2008). Childhood and current autistic features in adolescents with schizotypal personality disorder. Schizophrenia Research, 104, 265273.CrossRefGoogle ScholarPubMed
Fagel, S. S. A. A., Swaab, H., De Sonneville, L. M. J., Van Rijn, S., Pieterse, J. K., Scheepers, F., & Van Engeland, H. (2013). Development of schizotypal symptoms following psychiatric disorders in childhood or adolescence. European Child and Adolescent Psychiatry, 22, 683692.CrossRefGoogle ScholarPubMed
Fromer, M., Roussos, P., Sieberts, S. K., Johnson, J. S., Kavanagh, D. H., Perumal, T. M., … Sklar, P. (2016). Gene expression elucidates functional impact of polygenic risk for schizophrenia. Nature Neuroscience, 11, 14421453.CrossRefGoogle Scholar
Harvey, P. D., Deckler, E., Jones, M. T., Jarskog, L. F., Penn, D. L., & Pinkham, A. E. (2019). Autism symptoms, depression, and active social avoidance in schizophrenia: Association with self-reports and informant assessments of everyday functioning. Journal of Psychiatric Research, 115, 3642.CrossRefGoogle ScholarPubMed
Hoekstra, R. A., Bartels, M., Cath, D. C., & Boomsma, D. I. (2008). Factor structure, reliability and criterion validity of the autism-spectrum quotient (AQ): A study in Dutch population and patient groups. Journal of Autism and Developmental Disorders, 38, 15551566.CrossRefGoogle ScholarPubMed
Kästner, A., Begemann, M., Michel, T. M., Everts, S., Stepniak, B., Bach, C., … Ehrenreich, H. (2015). Autism beyond diagnostic categories: Characterization of autistic phenotypes in schizophrenia. BMC Psychiatry, 15, 115.CrossRefGoogle Scholar
Kincaid, D. L., Doris, M., Shannon, C., & Mulholland, C. (2017). What is the prevalence of autism spectrum disorder and ASD traits in psychosis? A systematic review. Psychiatry Research, 250, 99105.CrossRefGoogle ScholarPubMed
Korver, N., Quee, P. J., Boos, H. B. M., Simons, C. J. P., De Haan, L., Kahn, R. S., & Linszen, D. H. (2012). Genetic Risk and Outcome of Psychosis (GROUP), a multi site longitudinal cohort study focused on gene-environment interaction: Objectives, sample characteristics, recruitment and assessment methods. International Journal of Methods in Psychiatric Research, 21, 205221.CrossRefGoogle ScholarPubMed
Kushima, I., Aleksic, B., Nakatochi, M., Shimamura, T., Okada, T., Uno, Y., … Arioka, Y. (2018). Comparative analyses of copy-number variation in autism spectrum disorder and schizophrenia reveal etiological overlap and biological insights. Cell Reports, 24, 28382856.CrossRefGoogle ScholarPubMed
Langdon, R., & Coltheart, M. (1999). Mentalising, schizotypy, and schizophrenia. Cognition, 71, 4371.CrossRefGoogle Scholar
Langdon, R., Coltheart, M., & Ward, P. B. (2006). Empathetic perspective-taking is impaired in schizophrenia: Evidence from a study of emotion attribution and theory of mind. Cognitive Neuropsychiatry, 11, 133155.CrossRefGoogle ScholarPubMed
Linscott, R. J., & van Os, J. (2010). Systematic reviews of categorical versus continuum models in psychosis: Evidence for discontinuous subpopulations underlying a psychometric continuum. Implications for DSM-V, DSM-VI, and DSM-VII. Annual Review of Clinical Psychology, 6, 391419.CrossRefGoogle ScholarPubMed
Lugnegard, T., Hallerbäck, M. U., & Gillberg, C. (2015). Asperger syndrome and schizophrenia: Overlap of self-reported autistic traits using the Autism-spectrum Quotient (AQ). Nordic Journal of Psychiatry, 69, 268274.CrossRefGoogle Scholar
Lundqvist, L. O., & Lindner, H. (2017). Is the Autism-Spectrum Quotient a valid measure of traits associated with the autism spectrum? A Rasch validation in adults with and without autism spectrum disorders. Journal of Autism and Developmental Disorders, 47, 20802091.CrossRefGoogle ScholarPubMed
Malla, A., & Payne, J. (2005). First-episode psychosis: Psychopathology, quality of life, and functional outcome. Schizophrenia Bulletin, 31, 650671.CrossRefGoogle ScholarPubMed
Martinez, G., Alexandre, C., Mam-Lam-Fook, C., Bendjemaa, N., Gaillard, R., Garel, P., … Krebs, M. O. (2017). Phenotypic continuum between autism and schizophrenia: Evidence from the Movie for the Assessment of Social Cognition (MASC). Schizophrenia Research, 185, 161166.CrossRefGoogle Scholar
Miller, G. A., & Chapman, J. P. (2001). Misunderstanding analysis of covariance. Journal of Abnormal Psychology, 110, 4048.CrossRefGoogle ScholarPubMed
Ohmuro, N., Katsura, M., Obara, C., Kikuchi, T., Sakuma, A., Iizuka, K., … Matsmoto, K. (2016). Deficits of cognitive theory of mind and its relationship with functioning in individuals with an at-risk mental state and first-episode psychosis. Psychiatry Research, 243, 318325.CrossRefGoogle ScholarPubMed
Padgett, F. E., Miltsiou, E., & Tiffin, P. A. (2010). The co-occurrence of nonaffective psychosis and the pervasive developmental disorders: A systematic review. Journal of Intellectual and Developmental Disability, 35, 187198.CrossRefGoogle ScholarPubMed
Pepper, K. L., Demetriou, E. A., Park, S. H., Song, Y. C., Hickie, I. B., Cacciotti-Saija, C., … Guastella, A. J. (2018). Autism, early psychosis, and social anxiety disorder: Understanding the role of social cognition and its relationship to disability in young adults with disorders characterized by social impairments. Translational Psychiatry, 8, 233.CrossRefGoogle ScholarPubMed
Pinkham, A. E., Morrison, K. E., Penn, D. L., Harvey, P. D., Kelsven, S., Ludwig, K., & Sasson, N. J. (2019). Comprehensive comparison of social cognitive performance in autism spectrum disorder and schizophrenia. Psychological Medicine, 19.Google Scholar
Pourcain, B. S., Robinson, E. B., Anttila, V., Sullivan, B. B., Maller, J., Golding, J., … Davey Smith, G. (2018). ASD and schizophrenia show distinct developmental profiles in common genetic overlap with population-based social communication difficulties. Molecular Psychiatry, 23, 263270.CrossRefGoogle Scholar
Sasamoto, A., Miyata, J., Hirao, K., Fujiwara, H., Kawada, R., Fujimoto, S., … Murai, T. (2011). Social impairment in schizophrenia revealed by Autism-Spectrum Quotient correlated with gray matter reduction. Social Neuroscience, 6, 548558.CrossRefGoogle ScholarPubMed
Sasson, N. J., Pinkham, A. E., Carpenter, K. L. H., & Belger, A. (2011). The benefit of directly comparing autism and schizophrenia for revealing mechanisms of social cognitive impairment. Journal of Neurodevelopmental Disorders, 3, 87100.CrossRefGoogle ScholarPubMed
Sasson, N. J., Pinkham, A. E., Weittenhiller, L. P., Faso, D. J., & Simpson, C. (2016). Context effects on facial affect recognition in schizophrenia and autism: Behavioral and eye-tracking evidence. Schizophrenia Bulletin, 42, 675683.CrossRefGoogle ScholarPubMed
Sasson, N., Tsuchiya, N., Hurley, R., Couture, S. M., Penn, D. L., Adolphs, R., & Piven, J. (2007). Orienting to social stimuli differentiates social cognitive impairment in autism and schizophrenia. Neuropsychologia, 45, 25802588.CrossRefGoogle Scholar
Schalbroeck, R., Termorshuizen, F., Visser, E., Van Amelsvoort, T., & Selten, J. P. (2018). Risk of non-affective psychotic disorder or bipolar disorder in autism spectrum disorder: A longitudinal register-based study in the Netherlands. Psychological Medicine, 49, 25432550.CrossRefGoogle ScholarPubMed
Schneider, M., Reininghaus, U., van Nierop, M., Janssens, M., Myin-Germeys, I., & Investigators GROUP (2017). Does the Social Functioning Scale reflect real-life social functioning? An experience sampling study in patients with a non-affective psychotic disorder and healthy control individuals. Psychological Medicine, 47, 27772786.CrossRefGoogle ScholarPubMed
Selten, J. P., Lundberg, M., Rai, D., & Magnusson, C. (2015). Risks for nonaffective psychotic disorder and bipolar disorder in young people with autism spectrum disorder: A population-based study. JAMA Psychiatry, 72, 483489.CrossRefGoogle ScholarPubMed
Stefanis, N. C., Hanssen, M., Smirnis, N. K., Avramopoulos, D. A., Evdokimidis, I. K., Stefanis, C. N., … Van Os, J. (2002). Evidence that three dimensions of psychosis have a distribution in the general population. Psychological Medicine, 32, 347358.CrossRefGoogle ScholarPubMed
Stouten, L. H., Veling, W., Laan, W., van der Helm, M., & van der Gaag, M. (2017). Psychosocial functioning in first-episode psychosis and associations with neurocognition, social cognition, psychotic and affective symptoms. Early Intervention in Psychiatry, 11, 2336.CrossRefGoogle ScholarPubMed
Sullivan, P. F., Magnusson, C., Reichenberg, A., Boman, M., Dalman, C., Davidson, M., … Lichtenstein, P. (2012). Family history of schizophrenia and bipolar disorder as risk factors for autism. Archives of General Psychiatry, 69, 10991103.CrossRefGoogle ScholarPubMed
Taylor, M. J., Martin, J., Lu, Y., Brikell, I., Lundström, S., Larsson, H., & Lichtenstein, P. (2019). Association of genetic risk factors for psychiatric disorders and traits of these disorders in a Swedish population twin sample. JAMA Psychiatry, 76, 280289.CrossRefGoogle Scholar
van Rooijen, G., Isvoranu, A. M., Kruijt, O. H., van Borkulo, C. D., Meijer, C. J., Wigman, J. T. W., … Bartels-Velthuis, A. A. (2018). A state-independent network of depressive, negative and positive symptoms in male patients with schizophrenia spectrum disorders. Schizophrenia Research, 193, 232239.CrossRefGoogle ScholarPubMed
Vaskinn, A., & Abu-Akel, A. (2019). The interactive effect of autism and psychosis severity on theory of mind and functioning in schizophrenia. Neuropsychology, 33, 195202.CrossRefGoogle Scholar
Velthorst, E., Froudist-Walsh, S., Stahl, E., Ruderfer, D., Ivanov, I., Buxbaum, J., … Martin, J. (2018). Genetic risk for schizophrenia and autism, social impairment and developmental pathways to psychosis. Translational Psychiatry, 8, 204.CrossRefGoogle ScholarPubMed
Wechsler, D. (1997). Wechsler adult intelligence scale – third edition (WAIS-III). San Antonio, TX: Psychological Corporation.Google Scholar
Wigman, J. T. W., Van Os, J., Borsboom, D., Wardenaar, K. J., Epskamp, S., Klippel, A., … Wichers, M. (2015). Exploring the underlying structure of mental disorders: Cross-diagnostic differences and similarities from a network perspective using both a top-down and a bottom-up approach. Psychological Medicine, 45, 23752387.CrossRefGoogle Scholar
Wing, J. K., Babor, T., Brugha, T., Burke, J., Cooper, J. E., Giel, R., … Sartorius, N. (1990). Schedules for clinical assessment in neuropsychiatry. Archives of General Psychiatry, 47, 589593.CrossRefGoogle ScholarPubMed
Woodbury-Smith, M. R., Robinson, J., Wheelwright, S., & Baron-Cohen, S. (2005). Screening adults for Asperger Syndrome using the AQ: A preliminary study of its diagnostic validity in clinical practice. Journal of Autism and Developmental Disorders, 35, 331335.CrossRefGoogle ScholarPubMed
Wüsten, C., Schlier, B., Jaya, E. S., Fonseca-Pedrero, E., Peters, E., Verdoux, H., … Lincoln, T. M. (2018). Psychotic experiences and related distress: A cross-national comparison and network analysis based on 7141 participants from 13 countries. Schizophrenia Bulletin, 44, 11851194.CrossRefGoogle ScholarPubMed
Zarrei, M., Burton, C. L., Engchuan, W., Young, E. J., Higginbotham, E. J., MacDonald, J. R., … Scherer, S. W. (2019). A large data resource of genomic copy number variation across neurodevelopmental disorders. NPJ Genomic Medicine, 4, 26.CrossRefGoogle ScholarPubMed
Ziermans, T., Swaab, H., Stockmann, A., de Bruin, E., & van Rijn, S. (2017). Formal thought disorder and executive functioning in children and adolescents with autism spectrum disorder: Old leads and new avenues. Journal of Autism and Developmental Disorders, 47, 17561768.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Demographic and clinical characteristics of patients, siblings, and healthy controls in the GROUP study, mean scores (standard deviations) and absolute numbers (%)

Figure 1

Fig. 1. Left: Histogram plot with the normal curve of Total AQ scores stacked across groups. Right: Normal curves per group: PD (top), FR (middle), and TC (bottom).

Figure 2

Table 2. AQ data per group, mean scores (standard deviations) and number of participants exceeding standard AQ cut-off scores (%)

Figure 3

Fig. 2. Z-transformed group means for Picture Sequencing Test – False Belief (PST-FB; left) and the Social Functioning Scale (SFS; right). Error bars represent ±1 standard error.

Figure 4

Table 3. Best-fitting multilevel models for social functioning

Supplementary material: File

Ziermans et al. supplementary material

Tables S1 and S2

Download Ziermans et al. supplementary material(File)
File 19.6 KB