Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-05T04:20:48.401Z Has data issue: false hasContentIssue false

Autistic symptoms in unaffected first-degree relatives of people with schizophrenia: results from the Italian Network for Research on Psychoses multicenter study

Published online by Cambridge University Press:  23 October 2023

Antonio Vita
Affiliation:
Psychiatric Unit, School of Medicine, University of Brescia, Brescia, Italy Department of Mental Health, Spedali Civili Hospital, Brescia, Italy
Stefano Barlati*
Affiliation:
Psychiatric Unit, School of Medicine, University of Brescia, Brescia, Italy Department of Mental Health, Spedali Civili Hospital, Brescia, Italy
Giacomo Deste
Affiliation:
Psychiatric Unit, School of Medicine, University of Brescia, Brescia, Italy Department of Mental Health, Spedali Civili Hospital, Brescia, Italy
Alessandro Rossi
Affiliation:
Section of Psychiatry, Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila, Italy
Paola Rocca
Affiliation:
Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy
Alessandro Bertolino
Affiliation:
Department of Neurological and Psychiatric Sciences, University of Bari, Bari, Italy
Eugenio Aguglia
Affiliation:
Department of Clinical and Molecular Biomedicine, Psychiatry Unit, University of Catania, Catania, Italy
Carlo A. Altamura
Affiliation:
Department of Psychiatry, University of Milan, Milan, Italy
Mario Amore
Affiliation:
Section of Psychiatry, Department of Neurosciences, Rehabilitation, Ophthalmology, Genetics and Maternal and Child Health, University of Genoa, Genoa, Italy
Antonello Bellomo
Affiliation:
Psychiatry Unit, Department of Medical Sciences, University of Foggia, Foggia, Italy
Paola Bucci
Affiliation:
Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
Bernardo Carpiniello
Affiliation:
Section of Psychiatry, Department of Public Health, Clinical and Molecular Medicine, University of Cagliari, Cagliari, Italy
Alessandro Cuomo
Affiliation:
Department of Molecular Medicine and Clinical Department of Mental Health, University of Siena, Siena, Italy
Liliana Dell’Osso
Affiliation:
Section of Psychiatry, Department of Clinical and Experimental Medicine, University of Pisa, Pisa, Italy
Luigi Giuliani
Affiliation:
Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
Carlo Marchesi
Affiliation:
Department of Neuroscience, Psychiatry Unit, University of Parma, Parma, Italy
Giovanni Martinotti
Affiliation:
Department of Neuroscience and Imaging, G. d’Annunzio University, Chieti, Italy
Palmiero Monteleone
Affiliation:
Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, Salerno, Italy
Cristiana Montemagni
Affiliation:
Department of Neuroscience, Section of Psychiatry, University of Turin, Turin, Italy
Gabriele Nibbio
Affiliation:
Psychiatric Unit, School of Medicine, University of Brescia, Brescia, Italy
Massimo Pasquini
Affiliation:
Department of Neurology and Psychiatry, Sapienza University of Rome, Rome, Italy
Maurizio Pompili
Affiliation:
Department of Neurosciences, Mental Health and Sensory Organs, S. Andrea Hospital, Sapienza University of Rome, Rome, Italy
Antonio Rampino
Affiliation:
Department of Neurological and Psychiatric Sciences, University of Bari, Bari, Italy
Rita Roncone
Affiliation:
Unit of Psychiatry, Department of Life, Health and Environmental Sciences, University of L’Aquila, L’Aquila, Italy
Rodolfo Rossi
Affiliation:
Section of Psychiatry, Department of Biotechnological and Applied Clinical Sciences, University of L’Aquila, L’Aquila, Italy
Alberto Siracusano
Affiliation:
Department of Systems Medicine, Psychiatry and Clinical Psychology Unit, Tor Vergata University of Rome, Rome, Italy
Elena Tenconi
Affiliation:
Psychiatric Clinic, Department of Neurosciences, University of Padua, Padua, Italy
Patrizia Zeppegno
Affiliation:
Department of Translational Medicine, Psychiatric Unit, University of Eastern Piedmont, Novara, Italy
Silvana Galderisi
Affiliation:
Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
Mario Maj
Affiliation:
Department of Psychiatry, University of Campania “Luigi Vanvitelli”, Naples, Italy
*
Corresponding author: Stefano Barlati; Email: [email protected]

Abstract

Background

Autistic symptoms represent a frequent feature in schizophrenia spectrum disorders (SSD). However, the prevalence and the cognitive and functional correlates of autistic symptoms in unaffected first-degree relatives of people with SSD remain to be assessed.

Methods

A total of 342 unaffected first-degree relatives related to 247 outpatients with schizophrenia were recruited as part of the multicenter study of the Italian Network for Research on Psychoses (NIRP). Autistic features were measured with the PANSS Autism Severity Scale. Three groups of participants, defined on the presence and severity of autistic symptoms, were compared on a wide array of cognitive and functional measures.

Results

Of the total sample, 44.9% presented autistic symptoms; 22.8% showed moderate levels of autistic symptoms, which can be observed in the majority of people with SSD. Participants with higher levels of autistic symptoms showed worse performance on Working Memory (p = 0.014) and Social Cognition (p = 0.025) domains and in the Global Cognition composite score (p = 0.008), as well as worse on functional capacity (p = 0.001), global psychosocial functioning (p < 0.001), real-world interpersonal relationships (p < 0.001), participation in community activities (p = 0.017), and work skills (p = 0.006).

Conclusions

A high prevalence of autistic symptoms was observed in first-degree relatives of people with SSD. Autistic symptoms severity showed a negative correlation with cognitive performance and functional outcomes also in this population and may represent a diagnostic and treatment target of considerable scientific and clinical interest in both patients and their first-degree relatives.

Type
Research 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, provided the original article is properly cited.
Copyright
© The Author(s), 2023. Published by Cambridge University Press on behalf of the European Psychiatric Association

Introduction

Background

Schizophrenia spectrum disorders (SSD) and autism spectrum disorders (ASD) are two distinct nosological entities, characterized by different age of onset, course of the disorder, and treatment response [1, 2]. Psychotic symptoms do not represent an essential feature of ASD, and symptoms can generally be observed at a much earlier age: these distinctions as well as differences on a neurobiological level have led some researchers to hypothesize that SSD and ASD represent opposite neurodevelopmental models [Reference Crespi and Badcock3].

Notwithstanding these differences, SSD and ASD share several remarkable overlaps: impairment in social cognition abilities represents a core feature of both spectra, with very similar levels of limitation across the disorders [Reference Barlati, Deste, Ariu and Vita4Reference Pinkham and Sasson7]. Neurocognitive performance, particularly in the domains of processing speed, verbal comprehension, and working memory, appears to be similar in people diagnosed with SSD or ASD [Reference Kuo, Wojtalik, Mesholam-Gately, Keshavan and Eack8, Reference Kuo and Eack9].

Important similarities can be also observed at a genetic level and in neuroanatomical and neurofunctional imaging [Reference Barlati, Minelli, Ceraso, Nibbio, Carvalho Silva and Deste10Reference Voineskos, Lett, Lerch, Tiwari, Ameis and Rajji15].

ASD symptoms are more frequent in people diagnosed with SSD than in healthy individuals [Reference Barlati, Deste, Gregorelli and Vita16Reference Kincaid, Doris, Shannon and Mulholland18]. Subjects with a childhood diagnosis of ASD are frequently diagnosed with SSD during adolescence and early adulthood [Reference King and Lord19Reference Mouridsen, Rich and Isager22], and 30% of young people receiving a diagnosis of very early-onset schizophrenia also present a concomitant diagnosis of ASD [Reference Rapoport, Chavez, Greenstein, Addington and Gogtay23].

Autistic features also appear to have a significant impact on several cognitive, clinical, and functional outcomes in people living with SSD and have, therefore, recently become a topic of increasing scientific interest: autistic symptoms in people with SSD are related to worse social cognition performance and worse real-world functioning [Reference Bechi, Agostoni, Buonocore, Bosinelli, Spangaro and Bianchi24Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28] and could represent a negative moderator of response to pharmacological treatment [Reference Downs, Lechler, Dean, Sears, Patel and Shetty29, Reference Nakata, Kanahara, Kimura, Niitsu, Komatsu and Oda30] and psychosocial interventions such as social cognition-oriented cognitive remediation [Reference Bechi, Agostoni, Buonocore, Gritti, Mascia and Spangaro31].

However, autistic symptoms may also have some protective effects: some studies report that autistic symptoms could mitigate the negative impact on functioning produced by high levels of psychotic symptoms [Reference Abu-Akel, Wood, Upthegrove, Chisholm, Lin and Hansen32Reference Vaskinn and Abu-Akel34]. Some studies also report that autistic symptoms appear to be related to other positive outcomes: one study has found a positive correlation between the severity of autistic symptoms and better stigma resistance, as measured by the Stigma Resistance factor of the Internalized Stigma of Mental Illness [Reference Barlati, Nibbio, Morena, Cacciani, Corsini and Mosca35]; another study has reported that individuals diagnosed with SSD showing more prominent autistic features present better real-world social acceptability, as measured by the dedicated subscale of the Specific Level of Functioning Scale (SLOF), compared to other participants with same diagnosis with less severe autistic symptoms [Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28]. These effects may be partly explained by differences in relational and coping styles observed in individuals with prominent autistic features [Reference Dell’Osso, Carpita, Cremone, Gesi, D’Ermo and De Iorio36].

Despite this recent scientific and clinical interest in the role of autistic symptoms and the characteristics related to an autistic phenotype in SSD, their impacts on the lives of first-degree relatives of people diagnosed with SSD are currently scarcely explored.

SSD presents a considerable genetic component and a high degree of heritability [Reference Hilker, Helenius, Fagerlund, Skytthe, Christensen and Werge37, Reference Seidman, Hellemann, Nuechterlein, Greenwood, Braff and Cadenhead38], and first-degree relatives of people living with SSD present a profile of neurocognitive and social cognition performance that is intermediate between unaffected controls and individuals diagnosed with SSD [Reference Bora and Pantelis39Reference Mucci, Galderisi, Green, Nuechterlein, Rucci and Gibertoni42] and are usually considered an intermediate phenotype of SSD [Reference Tamminga, Ivleva, Keshavan, Pearlson, Clementz and Witte43]. Pathways of real-world functional impairment are also similar in people living with SSD and their first-degree relatives [Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci44].

The role of features related to an autistic phenotype in people living with SSD was investigated in a large sample of patients with schizophrenia included in the baseline multicenter study of the Italian Network for Research on Psychoses (NIRP) [Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci45]. The study showed worse cognitive performance and worse real-world outcomes in several domains, but better real-world social acceptability in subjects with higher levels of autistic symptoms [Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28]. The NIRP study also included a large cohort of first-degree relatives of people with SSD [Reference Mucci, Galderisi, Green, Nuechterlein, Rucci and Gibertoni42], in which the prevalence of autistic symptoms and their role on real-world outcomes were not previously investigated. As people with a family history of SSD in general also present a consistently increased risk of ASD diagnosis [Reference Liu, Li, Fan, Zhang and Chen46, Reference Sullivan, Magnusson, Reichenberg, Boman, Dalman and Davidson47], exploring the prevalence and impact of autistic symptoms in first-degree relatives of people with SSD could provide valuable insight both in a scientific and in a clinical perspective.

Aims

The aims of the present study were to assess the prevalence of autistic symptoms in first-degree relatives of people diagnosed with schizophrenia and to investigate their cognitive and functional correlates. In particular, the study compared participants without autistic symptoms, with minimal autistic symptoms, and with moderate autistic symptoms on demographic, neurocognitive, sociocognitive, and real-world functional measures. The main hypothesis of the study is that subjects with more severe levels of autistic symptoms and a more pronounced autistic phenotype would show worse cognitive performances and worse real-world outcomes compared to other participants.

Methods

Sample

For the present study, the database of first-degree relatives of people living with schizophrenia recruited in the NIRP was used.

The NIRP is a large research network involving 26 Italian university psychiatric clinics and mental health departments. Its database includes a sample of 921 people diagnosed with schizophrenia living in the community [Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci44, Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci45].

For each recruited patient who agreed to involve relatives, two first-degree relatives were recruited, when available. They had to be, in order of preference, the two parents, or one parent and one sibling, or two siblings. Relatives were included in the study if they did not meet criteria for a current or lifetime psychiatric diagnosis as assessed by the Structured Clinical Interview for DSM-IV–Non-Patient version (SCID-I/NP) and the Structured Clinical Interview for DSM-IV axis II Disorders (SCID-II).

Further exclusion criteria were: (1) a history of head trauma with loss of consciousness, (2) neurological disease, (3) a history of alcoholism or substance abuse in the last 6 months, and (4) inability to provide informed consent.

Three hundred forty-two first-degree relatives (M:F = 145:197, age 53.9 ± 13.5 years, education 11.5 ± 3.9 years) related to 247 participants diagnosed with schizophrenia were recruited and completed the assessment and were included in the present analyses [Reference Mucci, Galderisi, Green, Nuechterlein, Rucci and Gibertoni42].

Participants were recruited from March 1, 2012, to September 30, 2013.

All included subjects provided written informed consent after receiving a comprehensive explanation of study procedures and goals. The study protocol was approved by the ethical committee of the coordinating center and of all other participating centers (approval number 73/2012).

Assessment

The assessment was conducted within 2 weeks after subjects’ recruitment. According to the same procedure in all centers, enrolled participants completed the assessment for the study in 2 days: sociodemographic and clinical assessment on day 1 in the morning and assessments of neurocognitive functions, social cognition, and functional capacity on day 2 in the morning.

A complete description of study recruitment and assessment procedures, including inter-rater reliability and comparability of data collection procedures, has been reported elsewhere [Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28, Reference Mucci, Galderisi, Green, Nuechterlein, Rucci and Gibertoni42, Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci44, Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci45].

Autistic symptoms assessment

Autistic symptoms severity was assessed in all included participants using the PANSS Autism Severity Scale (PAUSS) [Reference Kästner, Begemann, Michel, Everts and Stepniak48]. The PAUSS is a scale composed of eight items ranging one to seven derived from the Positive and Negative Syndrome Scale [Reference Kay, Fiszbein and Opler49] and has been designed specifically to assess the expression of an autistic phenotype in people with SSD. Included items feature N1 (“blunted affect”), N3 (“poor rapport”), N4 (“social withdrawal”), N5 (“difficulties in abstract thinking”), N6 (“lack of spontaneity and flow of conversation”), N7 (“stereotyped thinking”), G5 (“mannerism”), and G15 (“preoccupation”): these features, rather than assessing the presence and diagnosis of ASD as a distinct neurodevelopmental disorder, explore the severity of difficulties in social interactions and in communication and the limited, repetitive, and stereotypic patterns of behavior that characterize the autistic phenotype in people with SSD [Reference Kästner, Begemann, Michel, Everts and Stepniak48, Reference Nibbio, Barlati, Calzavara-Pinton, Necchini, Invernizzi and Dell’Ovo50, Reference Palumbo, Stanghellini, Mucci, Ballerini, Giordano and Lysaker51].

Its validity and precision have been already demonstrated and found to be satisfying, with the PAUSS strongly correlating with other more established diagnostic tools for the assessment of autistic features and showing even better sensitivity than such scales in measuring autistic symptoms severity in people with SSD [Reference Nibbio, Barlati, Calzavara-Pinton, Necchini, Invernizzi and Dell’Ovo50, Reference Deste, Barlati, Gregorelli, Lisoni, Turrina and Valsecchi52]. It has also been used to assess genetic and neurobiological correlates of autistic features in people with SSD [Reference Ehrenreich, Mitjans, Van der Auwera, Centeno, Begemann and Grabe53Reference Stepniak, Kästner, Poggi, Mitjans, Begemann and Hartmann55] and in first-episode psychosis [Reference Abu-Akel, Wood, Upthegrove, Chisholm, Lin and Hansen32, Reference Parellada, Pina-Camacho, Moreno, Aleman, Krebs and Desco56, Reference Davut, Onur and Hüseyin57] as well as healthy subjects [Reference Mitjans, Begemann, Ju, Dere, Wüstefeld and Hofer58].

According to the original validation study cut-offs [Reference Kästner, Begemann, Michel, Everts and Stepniak48], the sample was divided into participants with no ASD symptoms (PAUSS = 8), minimal ASD symptoms (8 < PAUSS ≤ 10), and moderate ASD symptoms (PAUSS ≥ 11). This partitioning was structured considering that the investigated sample was composed of subjects without a diagnosis of SSD or ASD, so a high number of subjects without ASD symptoms and no subject with severe ASD symptoms (PAUSS ≥ 30) was expected.

Cognitive assessment

Cognitive performance was assessed using the MATRICS Consensus Cognitive Battery (MCCB) [Reference Nuechterlein, Green, Kern, Baade, Barch and Cohen59]. The MCCB is a cognitive assessment battery with the highest level of recommendation for use in both clinical and research settings according to recent international guidance [Reference Vita, Gaebel, Mucci, Sachs, Erfurth and Barlati60] and is composed of specific tasks assessing the following cognitive domains: speed of processing (Trail Making Test Part A; Brief Assessment of Cognition in Schizophrenia: Symbol Coding; Category Fluency Test: Animal Naming), verbal and spatial learning (Hopkins Verbal Learning Test–Revised, immediate recall; Brief Visuospatial Memory Test–Revised), reasoning and problem-solving (Neuropsychological Assessment Battery, Mazes subtest), attention (Continuous Performance Test: Identical Pairs), working memory (Wechsler Memory Scale, Spatial Span subset; Letter Number Span Test), and social cognition (Mayer-Salovey-Caruso Emotional Intelligence Test: Managing Emotion task). A t-score was computed for each cognitive domain, corrected for gender, age, and education, and a global cognitive composite score was finally calculated following the recommendation of the battery developers [Reference Nuechterlein and Green61].

Functional outcomes measures

Functional capacity was assessed with the UCSD Performance-Based Skills Assessment, Brief (UPSA-B) [Reference Mausbach, Harvey, Goldman, Jeste and Patterson62]. The UPSA-B is a brief and widely used performance-based instrument that assesses skills involved in community tasks: “financial skills” (e.g., counting money and paying bills) and “communication skills” (e.g., to dial a telephone number for emergency or reschedule an appointment by telephone), with a total score ranging from 0 to 100.

Global personal and social functioning was assessed with the Personal and Social Performance (PSP) scale [Reference Morosini, Magliano, Brambilla, Ugolini and Pioli63]. The PSP in a single-item, interview-based scale assessing functioning in the last month in four areas: personal and social relationships, socially useful activities, self-care, and disturbing and aggressive behavior, each one with six degrees of severity characterized by specific anchor points. The total score ranges from 0 to 100, with higher scores representing better functioning.

Real-world functioning was assessed by the Specific Level of Functioning Scale (SLOF), an informant-rated measure that explores many aspects of functioning and is based on the key caregiver’s judgment on behavior and functioning of patients [Reference Schneider and Struening64]. It consists of 43 items, divided into six different scales, and includes the following domains: physical efficiency, skills in self-care, interpersonal relationships, social acceptability, participation in community activities (e.g., shopping, using public transportation), and working abilities. Each item is rated from 1 to 5, with higher scores indicating better functioning. The SLOF has been found to be a reliable and valid instrument to assess real-world functioning with good construct validity and internal consistency: for the present study, the validated Italian version [Reference Mucci, Rucci, Rocca, Bucci, Gibertoni and Merlotti65] was used.

Statistical analyses

The three groups of subjects identified using the PAUSS cut-off scores were compared on demographic, cognitive, and functional measures. The distribution of scores of each considered variable was inspected for normality and homogeneity of variance in order to allow the use of parametric statistics.

Categorical variables were analyzed using Pearson’s χ2 tests, with results reported as percentages. Continuous variables were analyzed with general linear model analyses of variance (ANOVA).

Sociodemographic variables showing significant between-group differences were used as covariates in functional outcome comparisons; t-scores of cognitive domains, already corrected for gender, age, and education, were used. Post-hoc, between-groups analyses were performed accounting for multiple comparisons using Bonferroni correction.

Statistical analyses were performed using SPSS 15.0; p-values <0.05 (two tailed) were considered significant.

Results

Prevalence of autistic symptoms and sociodemographic characteristics

The mean PAUSS total score was 9.56 (SD ± 2.70, range 8–26). One hundred and ninety-two participants (56.1% of the sample) had a PAUSS score of 8 and thus were included in the “No autistic symptoms” group; 72 participants (22.1%) had a PAUSS score between 8 and 10 and were included in the “Minimal autistic symptoms” group; 78 participants (22.8%) had a PAUSS ≥ 11 and thus were included into the “Moderate autistic symptoms” group.

Comparing these three groups, no significant difference emerged regarding gender distribution, age, and education (see Table 1), so no additional covariate was introduced in between-group comparisons regarding functional outcomes.

Table 1. Group comparison for demographic and clinical variables

Abbreviation: AS, autistic symptoms.

Note: Post-hoc comparisons include Bonferroni correction.

Between-group comparisons on cognitive performance

Significant between-group differences were observed in the Working Memory (p = 0.014) and Social Cognition (p = 0.025) domains, as well as in the global cognition composite score (p = 0.008). In particular, the “Moderate autistic symptoms group” showed a worse performance compared to the “No autistic symptoms” group on Working Memory (p = 0.012), Social Cognition (p = 0.020), and Global Cognition (p = 0.006) scores.

No difference was observed in the other investigated cognitive domains (see Table 2).

Table 2. Group comparison for cognitive measures

Abbreviation: AS, autistic symptoms.

Note: All cognitive measures are corrected for gender, age, education. Post-hoc comparisons include Bonferroni correction.

* p < 0.05;

** p < 0.01.

Between-group comparisons on functional measures

Significant between-group differences were observed for functional capacity, as measured by the UPSA-B (p = 0.001); for global psychosocial functioning, as measured by the PSP (p < 0.001); and for real-world interpersonal relationships (p < 0.001), participation in community activities (p = 0.017), and work skills (p = 0.006), as measured by the SLOF scale.

In particular, the “Moderate autistic symptoms group” showed a worse functional profile, with lower UPSA-B (p = 0.002), PSP (p < 0.001), SLOF Interpersonal Relationships (p < 0.001), SLOF Activities (p = 0.013), and SLOF Work (p = 0.019) scores as compared to the “No autistic symptoms group,” and lower PSP (p = 0.004), SLOF Interpersonal Relationships (p < 0.005), and SLOF Work (p = 0.010) scores as compared to the “Minimal autistic symptoms group.” The “Minimal autistic symptoms group,” compared to the “No autistic symptoms group,” showed worse global psychosocial functioning, with lower PSP scores (p = 0.003) (Table 3).

Table 3. Group comparison for functional measures

Abbreviations: AS, autistic symptoms; PSP, personal and social performance scale; SLOF, specific level of functioning scale; UPSA-B, UCSD performance-based skills assessment–brief version.

Note: Post-hoc comparisons include Bonferroni correction.

* p < 0.05;

** p < 0.01.

Discussion

Several interesting results concerning both the prevalence and the correlates of autistic symptoms emerged from the analyses.

Autistic characteristics can be considered a continuum of features in the general population, and therefore subthreshold levels of autistic symptoms can be observed in nonclinical samples [Reference Dell’Osso, Gesi, Massimetti, Cremone, Barbuti and Maccariello66Reference Vannucchi, Masi, Toni, Dell’Osso, Marazziti and Perugi69]. In fact, while the global prevalence of ASD diagnosis can be attested between 1.6% and 2.6% [Reference Abu-Akel, Allison, Baron-Cohen and Heinke70Reference Lundström, Reichenberg, Anckarsäter, Lichtenstein and Gillberg73], a recent study [Reference Dell’Osso, Carpita, Nardi, Benedetti, Dell’Oste and Massimetti74] has highlighted that 17.6% of healthy controls show significant subthreshold autistic features measured with a dedicated assessment tool [Reference Dell’Osso, Gesi, Massimetti, Cremone, Barbuti and Maccariello66, Reference Donati, Berrocal, Primi, Petracchi, Carpita and Cosci75, Reference Dell’Osso, Luche, Gesi, Moroni, Carmassi and Maj76].

However, 44.9% of the present sample showed autistic symptoms, that is, 22.8% were of moderate severity, which is a level commonly observed in the majority of people living with SSD [Reference De Crescenzo, Postorino, Siracusano, Riccioni, Armando and Curatolo17, Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28, Reference Kästner, Begemann, Michel, Everts and Stepniak48].

The prevalence of autistic symptoms in this sample is however consistently lower than that observed using the same instrument in large samples of people with SSD: in the NIRP sample, 73.8% of participants showed moderate autistic symptoms and 20.1% severe autistic symptoms [Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28]. Another recent study conducted in China using the PAUSS did not include data regarding moderate autistic symptoms, but reported that 18.6% had severe autistic features [Reference Peng, Wang, Zhou, Hao, Chen and Wu77].

This finding suggests that autistic features could be more frequent in first-degree relatives of individuals diagnosed with SSD than in the general population, but less frequent and less severe than those observed in people living with SSD.

In participants with more severe autistic symptoms, a worse cognitive performance was observed, both in the Global Cognition composite index and in Working Memory and Social Cognition domains. This finding is line with those observed in people with SSD and confirms the relationship between autistic symptoms and worse cognitive performance, which is particularly important regarding social cognition abilities [Reference Kuo, Wojtalik, Mesholam-Gately, Keshavan and Eack8, Reference Kuo and Eack9, Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28, Reference Deste, Vita, Penn, Pinkham, Nibbio and Harvey78, Reference Hajdúk, Pinkham, Penn, Harvey and Sasson79].

Participants with more severe levels of ASD symptoms also showed worse functional capacity and worse psychosocial functioning, particularly in areas where social abilities are more relevant, such as real-world interpersonal relationships, community activities, and work outcomes.

This is another expected finding, which is again in line with those observed in people living with SSD [Reference Harvey, Deckler, Jones, Jarskog, Penn and Pinkham26, Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28, Reference Abu-Akel, Wood, Upthegrove, Chisholm, Lin and Hansen32, Reference Deste, Vita, Nibbio, Barlati, Penn and Pinkham80]. Participants with minimal autistic symptoms did not show worse real-world functional outcomes compared to those without autistic symptoms; however, they showed significantly reduced personal and social functioning as measured by the PSP. In this regard, minimal autistic symptoms might not be as clinically relevant as moderate or more severe autistic features, but could still deserve scientific attention and observation.

Taken together, all these findings suggest that autistic features have a similar role in people living with SSD and in their first-degree relatives and confirm the similarities in cognitive and functional impairment patterns observed in these two populations [Reference Mucci, Galderisi, Green, Nuechterlein, Rucci and Gibertoni42, Reference Galderisi, Rossi, Rocca, Bertolino, Mucci and Bucci44]. However, while autistic symptoms may also have a protective effect in people with SSD, limiting negative impact of high levels of positive symptoms on functional outcomes [Reference Abu-Akel, Wood, Upthegrove, Chisholm, Lin and Hansen32Reference Vaskinn and Abu-Akel34], first-degree relatives of people living with SSD typically do not present positive symptoms, so autistic symptoms may be even more detrimental in this population.

Detecting autistic features in first-degree relatives, therefore, could also represent a useful feature in clinical practice. According to the results of this study, the presence of autistic symptoms could represent a marker of functional impairment in first-degree relatives of people living with SSD. This could be of clinical interest both because first-degree relatives of patients with SSD often have a contact with mental health services either for their diagnosed relative or for conditions of their own and because assessing autistic symptoms, particularly with the PAUSS, represents a much faster assessment than a complete evaluation of functional capacity and functional outcomes. In fact, this may allow to easily identify individuals who, even without a clear diagnosis of SSD, might show relevant levels of functional impairment and may particularly benefit, alongside their diagnosed relatives, from evidence-based psychosocial interventions targeting cognitive and functional outcomes [Reference Deste, Corbo, Nibbio, Italia, Dell’Ovo and Calzavara-Pinton81Reference Vita, Barlati, Ceraso, Deste, Nibbio and Wykes86].

The present study shows some remarkable strengths.

To the best of our knowledge, it represents the first comprehensive assessment of the impact of autistic symptoms in first-degree relatives of people living with SSD on both cognitive and functional outcomes.

The inclusion of a large sample of participants, combined with the use of a wide panel of well-validated assessment tools, contributes to the validity and reproducibility of the observed results.

However, the present study has also some limitations.

The PAUSS was designed specifically to investigate the severity of autistic symptoms and the correlates of the autistic phenotype in SSD: the present study included first-degree relatives of people living with schizophrenia, which can be considered an intermediate phenotype.

In this perspective, other instruments, designed to assess ASD features in the general population, such as the Autism Diagnostic Observation Schedule [Reference Lord, Risi, Lambrecht, Cook, Leventhal and DiLavore87] or the Adult Autism Subthreshold Spectrum [Reference Dell’Osso, Gesi, Massimetti, Cremone, Barbuti and Maccariello66], may be more adequate to assess and differentiate subjects with minimal levels of autistic features. However, specific instruments aimed to assess autistic characteristics usually require dedicated training and longer administration times compared to the PAUSS [Reference Deste, Barlati, Gregorelli, Lisoni, Turrina and Valsecchi52]. The present study did not include a sample of participants with high levels of autistic symptoms (PAUSS > 30). Again, this might be due to the included sample, composed exclusively of unaffected relatives without psychiatric comorbidities, but it might have limited the potentiality of the PAUSS scale, which reliably allows to identify people living with SSD showing a clear autistic phenotype [Reference Deste, Barlati, Gregorelli, Lisoni, Turrina and Valsecchi52]. Moreover, the present study did not include a sample of participants drawn from the general population: for this reason, it was not possible to directly compare the prevalence, severity, and the correlates of autistic symptoms measured with the PAUSS in our sample with those of healthy controls without a diagnosis of any mental disorder who were not first-degree relatives of people living with SSD. Finally, while the PAUSS has been extensively validated [Reference Pina-Camacho, Boada, Díaz-Caneja, García-Alcón, Burdeus and Serrano-Drozdowskyj27, Reference Kästner, Begemann, Michel, Everts and Stepniak48, Reference Deste, Barlati, Gregorelli, Lisoni, Turrina and Valsecchi52] and employed in several different international studies with large samples of people with SSD [Reference Harvey, Deckler, Jones, Jarskog, Penn and Pinkham26, Reference Vita, Barlati, Deste, Rocca, Rossi and Bertolino28, Reference Abu-Akel, Wood, Upthegrove, Chisholm, Lin and Hansen32, Reference Peng, Wang, Zhou, Hao, Chen and Wu77], more data regarding its clinical specificity, in particular its long-term stability, is currently required [Reference Nibbio, Barlati, Calzavara-Pinton, Necchini, Invernizzi and Dell’Ovo50].

However, by using the PAUSS we were able to highlight significant cognitive and functional correlates in the present sample, particularly in subjects with relatively higher levels of autistic symptoms.

In conclusion, the results of the present study show that autistic symptoms in first-degree relatives of people with SSD are correlated with lower levels of cognitive performance and real-life functioning also in this population and may represent a diagnostic and treatment target of considerable scientific and clinical interest in both populations.

Future studies should focus on further assessing the role of autistic symptoms as a predictor and modulator of treatment response for both psychosocial interventions and pharmacological therapies in order to better devise personalized treatment programs that are more effective and useful for both people living with SSD and their families.

Appendix

Members of the Italian Network for Research on Psychoses involved in this study include Alessandro Galluzzo, Anna Ceraso, Jacopo Lisoni (University of Brescia); Enrico D’Ambrosio, Ileana Andriola, Pierluigi Selvaggi (University of Bari); Federica Pinna, Luca Marras, Michele Muscas (University of Cagliari); Giuseppe Piegari, Francesco Brando, Giulia Maria Giordano, Pasquale Pezzella (University of Campania “Luigi Vanvitelli”, Naples); Carmen Concerto, Alessandro Rodolico, Maria Salvina Signorelli (University of Catania); Mauro Pettorruso, Stefania Chiappini, Giacomo d’Andrea (University of Chieti); Stefano Pallanti (University of Firenze); Mario Altamura, Laura De Masi, Ivana Leccisotti (University of Foggia); Pietro Calcagno, Anna Bovio, Juxhin Bode (University of Genoa); Lorena Campoli, Luca Bonanni, Arianna Di Berardo, Laura Giusti, Silvia Mammarella, Anna Salza (University of L’Aquila); Matteo Marcatili, Oscar Fusi (University of Milan); Carla Gramaglia, Eleonora Gambaro, Valentina Zanoli (University of Eastern Piedmont, Novara); Angela Favaro, Paolo Meneguzzo, Enrico Collantoni (University of Padua); Matteo Tonna, Davide Fausto Borelli, Francesca Magnani (University of Parma); Barbara Carpita, Ivan Mirko Cremone, Giulia Amatori (University of Pisa); Giammarco Cascino, Giulio Corrivetti, Gianfranco Del Buono (Department of Mental Health, Salerno); Claudio Brasso, Gianluca Colli, Rodolfo Sgro (University of Turin); Antonino Buzzanca, Tommaso Accinni, Fabio di Fabio, Anna Comparelli, Isabella Berardelli, Denise Erbuto (Sapienza University of Rome); Andrea Fagiolini, Arianna Goracci, Simone Bolognesi (University of Siena); Cinzia Niolu, Giorgio Di Lorenzo, Emanuela Bianciardi (Tor Vergata University of Rome).

Financial support

This research received no specific grant from any funding agency, commercial or not-for-profit sectors.

Competing interest

The authors declare none.

Footnotes

The members of the Italian Network for Research on Psychoses involved in this study are listed in the Appendix.

References

American Psychiatric Association. Diagnostic and statistical manual of mental disorders (DSM-5). 5th ed. Washington, DC: American Psychiatric Association; 2013.Google Scholar
World Health Organization. ICD-11 CDDR – Global Clinical Practice Network 2022, https://gcp.network/icd-11-cddr [accessed 15 February 2023].Google Scholar
Crespi, B, Badcock, C. Psychosis and autism as diametrical disorders of the social brain. Behav Brain Sci. 2008;31:241–61. https://doi.org/10.1017/S0140525X08004214.CrossRefGoogle ScholarPubMed
Barlati, S, Deste, G, Ariu, C, Vita, A. Autism spectrum disorder and schizophrenia: do they overlap. Int J Emerg Ment Health Hum Resil. 2016;18:760–3.Google Scholar
Fernandes, JM, Cajão, R, Lopes, R, Jerónimo, R, Barahona-Corrêa, JB. Social cognition in schizophrenia and autism spectrum disorders: a systematic review and meta-analysis of direct comparisons. Front Psychiatry. 2018;9:504. https://doi.org/10.3389/fpsyt.2018.00504.CrossRefGoogle ScholarPubMed
Oliver, LD, Moxon-Emre, I, Lai, M-C, Grennan, L, Voineskos, AN, Ameis, SH. Social cognitive performance in schizophrenia spectrum disorders compared with autism spectrum disorder: a systematic review, meta-analysis, and meta-regression. JAMA Psychiatry. 2021;78:281–92. https://doi.org/10.1001/jamapsychiatry.2020.3908.CrossRefGoogle ScholarPubMed
Pinkham, AE, Sasson, NJ. The benefit of directly comparing autism and schizophrenia, revisited. Psychol Med. 2020;50:526–8. https://doi.org/10.1017/S0033291719003635.CrossRefGoogle ScholarPubMed
Kuo, SS, Wojtalik, JA, Mesholam-Gately, RI, Keshavan, MS, Eack, SM. Transdiagnostic validity of the MATRICS consensus cognitive battery across the autism-schizophrenia spectrum. Psychol Med. 2020;50:1623–32. https://doi.org/10.1017/S0033291719001582.CrossRefGoogle ScholarPubMed
Kuo, SS, Eack, SM. Meta-analysis of cognitive performance in neurodevelopmental disorders during adulthood: comparisons between autism spectrum disorder and schizophrenia on the Wechsler Adult Intelligence Scales. Front Psychiatry. 2020;11:187. https://doi.org/10.3389/fpsyt.2020.00187.CrossRefGoogle ScholarPubMed
Barlati, S, Minelli, A, Ceraso, A, Nibbio, G, Carvalho Silva, R, Deste, G, et al. Social cognition in a research domain criteria perspective: a bridge between schizophrenia and autism spectra disorders. Front Psychiatry. 2020;11.Google Scholar
Carroll, LS, Owen, MJ. Genetic overlap between autism, schizophrenia and bipolar disorder. Genome Med. 2009;1:102. https://doi.org/10.1186/gm102.CrossRefGoogle ScholarPubMed
de Lacy, N, King, BH. Revisiting the relationship between autism and schizophrenia: toward an integrated neurobiology. Annu Rev Clin Psychol. 2013;9:555–87. https://doi.org/10.1146/annurev-clinpsy-050212-185627.CrossRefGoogle ScholarPubMed
Eack, SM, Bahorik, AL, McKnight, SAF, Hogarty, SS, Greenwald, DP, Newhill, CE, et al. Commonalities in social and non-social cognitive impairments in adults with autism spectrum disorder and schizophrenia. Schizophr Res. 2013;148:24–8. https://doi.org/10.1016/j.schres.2013.05.013.CrossRefGoogle ScholarPubMed
Kushima, I, Aleksic, B, Nakatochi, M, Shimamura, T, Okada, T, Uno, Y, et al. Comparative analyses of copy-number variation in autism spectrum disorder and schizophrenia reveal etiological overlap and biological insights. Cell Rep. 2018;24:2838–56. https://doi.org/10.1016/j.celrep.2018.08.022.CrossRefGoogle ScholarPubMed
Voineskos, AN, Lett, TAP, Lerch, JP, Tiwari, AK, Ameis, SH, Rajji, TK. et al. Neurexin-1 and frontal lobe white matter: an overlapping intermediate phenotype for schizophrenia and autism spectrum disorders. PLoS One. 2011;6:e20982. https://doi.org/10.1371/journal.pone.0020982.CrossRefGoogle ScholarPubMed
Barlati, S, Deste, G, Gregorelli, M, Vita, A. Autistic traits in a sample of adult patients with schizophrenia: prevalence and correlates. Psychol Med. 2019;49:140–8.CrossRefGoogle Scholar
De Crescenzo, F, Postorino, V, Siracusano, M, Riccioni, A, Armando, M, Curatolo, P, et al. Autistic symptoms in schizophrenia spectrum disorders: a systematic review and meta-analysis. Front Psychiatry. 2019;10:78.CrossRefGoogle ScholarPubMed
Kincaid, DL, Doris, M, Shannon, C, Mulholland, C. What is the prevalence of autism spectrum disorder and ASD traits in psychosis? A systematic review. Psychiatry Res. 2017;250:99105. https://doi.org/10.1016/j.psychres.2017.01.017.CrossRefGoogle ScholarPubMed
King, BH, Lord, C. Is schizophrenia on the autism spectrum? Brain Res. 2011;1380:3441. https://doi.org/10.1016/j.brainres.2010.11.031.CrossRefGoogle ScholarPubMed
Konstantareas, MM, Hewitt, T. Autistic disorder and schizophrenia: diagnostic overlaps. J Autism Dev Disord. 2001;31:1928. https://doi.org/10.1023/a:1005605528309.CrossRefGoogle ScholarPubMed
Larson, FV, Wagner, AP, Jones, PB, Tantam, D, Lai, M-C, Baron-Cohen, S, et al. Psychosis in autism: comparison of the features of both conditions in a dually affected cohort. Br J Psychiatry. 2017;210:269–75. https://doi.org/10.1192/bjp.bp.116.187682.CrossRefGoogle Scholar
Mouridsen, SE, Rich, B, Isager, T. Psychiatric disorders in adults diagnosed as children with atypical autism. A case control study. J Neural Transm (Vienna). 2008;115:135–8. https://doi.org/10.1007/s00702-007-0798-1.CrossRefGoogle ScholarPubMed
Rapoport, J, Chavez, A, Greenstein, D, Addington, A, Gogtay, N. Autism spectrum disorders and childhood-onset schizophrenia: clinical and biological contributions to a relation revisited. J Am Acad Child Adolesc Psychiatry. 2009;48:1018. https://doi.org/10.1097/CHI.0b013e31818b1c63.CrossRefGoogle ScholarPubMed
Bechi, M, Agostoni, G, Buonocore, M, Bosinelli, F, Spangaro, M, Bianchi, L, et al. The influence of premorbid adjustment and autistic traits on social cognitive dysfunction in schizophrenia. J Int Neuropsychol Soc. 2020;26:276–85. https://doi.org/10.1017/S1355617719000961.CrossRefGoogle ScholarPubMed
Deste, G, Vita, A, Nibbio, G, Penn, DL, Pinkham, AE, Harvey, PD. Autistic symptoms and social cognition predict real-world outcomes in patients with schizophrenia. Front Psychiatry. 2020;11:524. https://doi.org/10.3389/fpsyt.2020.00524.CrossRefGoogle ScholarPubMed
Harvey, PD, Deckler, E, Jones, MT, Jarskog, LF, Penn, DL, Pinkham, AE. Autism symptoms, depression, and active social avoidance in schizophrenia: association with self-reports and informant assessments of everyday functioning. J Psychiatr Res. 2019;115:3642. https://doi.org/10.1016/j.jpsychires.2019.05.010.CrossRefGoogle ScholarPubMed
Pina-Camacho, L, Boada, L, Díaz-Caneja, CM, García-Alcón, A, Burdeus, M, Serrano-Drozdowskyj, E, et al. The positive and negative syndrome scale for schizophrenia autism severity scale (PAUSS) in young people with autism and schizophrenia. Rev Psiquiatr Salud Ment (Engl Ed). 2020;13:118–30. https://doi.org/10.1016/j.rpsm.2020.05.006.CrossRefGoogle ScholarPubMed
Vita, A, Barlati, S, Deste, G, Rocca, P, Rossi, A, Bertolino, A, et al. The influence of autistic symptoms on social and non-social cognition and on real-life functioning in people with schizophrenia: evidence from the Italian Network for Research on Psychoses multicenter study. Eur Psychiatry. 2020;63:e98. https://doi.org/10.1192/j.eurpsy.2020.99.CrossRefGoogle Scholar
Downs, JM, Lechler, S, Dean, H, Sears, N, Patel, R, Shetty, H, et al. The association between comorbid autism spectrum disorders and antipsychotic treatment failure in early-onset psychosis: a historical cohort study using electronic health records. J Clin Psychiatry. 2017;78:e1233–41. https://doi.org/10.4088/JCP.16m11422.CrossRefGoogle ScholarPubMed
Nakata, Y, Kanahara, N, Kimura, A, Niitsu, T, Komatsu, H, Oda, Y, et al. Autistic traits and cognitive profiles of treatment-resistant schizophrenia. Schizophr Res Cogn. 2020;22:100186. https://doi.org/10.1016/j.scog.2020.100186.CrossRefGoogle ScholarPubMed
Bechi, M, Agostoni, G, Buonocore, M, Gritti, D, Mascia, M, Spangaro, M, et al. The association of autistic traits with theory of mind and its training efficacy in patients with schizophrenia. Schizophr Res Cogn. 2020;19:100164. https://doi.org/10.1016/j.scog.2019.100164.CrossRefGoogle ScholarPubMed
Abu-Akel, A, Wood, SJ, Upthegrove, R, Chisholm, K, Lin, A, Hansen, PC, et al. Psychosocial functioning in the balance between autism and psychosis: evidence from three populations. Mol Psychiatry. 2022;27:2976–84. https://doi.org/10.1038/s41380-022-01543-5.CrossRefGoogle ScholarPubMed
Bechi, M, Abu-Akel, A, Agostoni, G, Bosia, M, Cocchi, F, Spangaro, M, et al. Functional benefits of co-occurring autistic symptoms in schizophrenia is delimited by symptom severity. J Psychiatr Res. 2021;137:4854. https://doi.org/10.1016/j.jpsychires.2021.02.044.CrossRefGoogle ScholarPubMed
Vaskinn, A, Abu-Akel, A. The interactive effect of autism and psychosis severity on theory of mind and functioning in schizophrenia. Neuropsychology. 2019;33:195202. https://doi.org/10.1037/neu0000499.CrossRefGoogle ScholarPubMed
Barlati, S, Nibbio, G, Morena, D, Cacciani, P, Corsini, P, Mosca, A, et al. Autistic symptoms in schizophrenia: impact on internalized stigma, well-being, clinical and functional characteristics. Front Psychiatry. 2022;13:801651. https://doi.org/10.3389/fpsyt.2022.801651.CrossRefGoogle ScholarPubMed
Dell’Osso, L, Carpita, B, Cremone, IM, Gesi, C, D’Ermo, A, De Iorio, G, et al. Autism spectrum in patients with schizophrenia: correlations with real-life functioning, resilience, and coping styles. CNS Spectr. 2022; 27(4):457467. https://doi.org/10.1017/S1092852921000353.Google Scholar
Hilker, R, Helenius, D, Fagerlund, B, Skytthe, A, Christensen, K, Werge, TM, et al. Heritability of schizophrenia and schizophrenia spectrum based on the nationwide Danish twin register. Biol Psychiatry. 2018;83:492–8. https://doi.org/10.1016/j.biopsych.2017.08.017.CrossRefGoogle ScholarPubMed
Seidman, LJ, Hellemann, G, Nuechterlein, KH, Greenwood, TA, Braff, DL, Cadenhead, KS, et al. Factor structure and heritability of endophenotypes in schizophrenia: findings from the Consortium on the Genetics of Schizophrenia (COGS-1). Schizophrenia Res. 2015;163:73–9. https://doi.org/10.1016/j.schres.2015.01.027.CrossRefGoogle Scholar
Bora, E, Pantelis, C. Theory of mind impairments in first-episode psychosis, individuals at ultra-high risk for psychosis and in first-degree relatives of schizophrenia: systematic review and meta-analysis. Schizophrenia Res. 2013;144:31–6. https://doi.org/10.1016/j.schres.2012.12.013.CrossRefGoogle ScholarPubMed
Fett, A-KJ, Viechtbauer, W, Dominguez, M-G, Penn, DL, van Os, J, Krabbendam, L. The relationship between neurocognition and social cognition with functional outcomes in schizophrenia: a meta-analysis. Neurosci Biobehav Rev. 2011;35:573–88. https://doi.org/10.1016/j.neubiorev.2010.07.001.CrossRefGoogle ScholarPubMed
Lavoie, M-A, Plana, I, Bédard Lacroix, J, Godmaire-Duhaime, F, Jackson, PL, Achim, AM. Social cognition in first-degree relatives of people with schizophrenia: a meta-analysis. Psychiatry Res. 2013;209:129–35. https://doi.org/10.1016/j.psychres.2012.11.037.CrossRefGoogle ScholarPubMed
Mucci, A, Galderisi, S, Green, MF, Nuechterlein, K, Rucci, P, Gibertoni, D, et al. Familial aggregation of MATRICS consensus cognitive battery scores in a large sample of outpatients with schizophrenia and their unaffected relatives. Psychol Med. 2018;48:1359–66. https://doi.org/10.1017/S0033291717002902.CrossRefGoogle Scholar
Tamminga, CA, Ivleva, EI, Keshavan, MS, Pearlson, GD, Clementz, BA, Witte, B, et al. Clinical phenotypes of psychosis in the Bipolar-Schizophrenia Network on Intermediate Phenotypes (B-SNIP). Am J Psychiatry. 2013;170:1263–74. https://doi.org/10.1176/appi.ajp.2013.12101339.CrossRefGoogle ScholarPubMed
Galderisi, S, Rossi, A, Rocca, P, Bertolino, A, Mucci, A, Bucci, P, et al. Pathways to functional outcome in subjects with schizophrenia living in the community and their unaffected first-degree relatives. Schizophrenia Res. 2016;175:154–60. https://doi.org/10.1016/j.schres.2016.04.043.CrossRefGoogle ScholarPubMed
Galderisi, S, Rossi, A, Rocca, P, Bertolino, A, Mucci, A, Bucci, P, et al. The influence of illness-related variables, personal resources and context-related factors on real-life functioning of people with schizophrenia. World J Psychiatry 2014;13:275–87. https://doi.org/10.1002/wps.20167.CrossRefGoogle ScholarPubMed
Liu, X, Li, Z, Fan, C, Zhang, D, Chen, J. Genetics implicate common mechanisms in autism and schizophrenia: synaptic activity and immunity. J Med Genet. 2017;54:511–20. https://doi.org/10.1136/jmedgenet-2016-104487.CrossRefGoogle ScholarPubMed
Sullivan, PF, Magnusson, C, Reichenberg, A, Boman, M, Dalman, C, Davidson, M, et al. Family history of schizophrenia and bipolar disorder as risk factors for autism. Arch Gen Psychiatry. 2012;69:1099–103. https://doi.org/10.1001/archgenpsychiatry.2012.730.CrossRefGoogle ScholarPubMed
Kästner, A, Begemann, M, Michel, TM, Everts, S, Stepniak, B, Bach C, et al. Autism beyond diagnostic categories: characterization of autistic phenotypes in schizophrenia. BMC Psychiatry. 2015;15:115. https://doi.org/10.1186/s12888-015-0494-x.CrossRefGoogle ScholarPubMed
Kay, SR, Fiszbein, A, Opler, LA. The Positive and Negative Syndrome Scale (PANSS) for schizophrenia. Schizophr Bull. 1987;13:261–76. https://doi.org/10.1093/schbul/13.2.261.CrossRefGoogle ScholarPubMed
Nibbio, G, Barlati, S, Calzavara-Pinton, I, Necchini, N, Invernizzi, E, Dell’Ovo, D, et al. Assessment and correlates of autistic symptoms in schizophrenia spectrum disorders measured with the PANSS Autism Severity Score: a systematic review. Front Psychiatry. 2022;13:934005. https://doi.org/10.3389/fpsyt.2022.934005.CrossRefGoogle ScholarPubMed
Palumbo, D, Stanghellini, G, Mucci, A, Ballerini, M, Giordano, GM, Lysaker, PH, et al. Autism rating scale: a new tool for characterizing the schizophrenia phenotype. Front Psychiatry. 2021;12:622359. https://doi.org/10.3389/fpsyt.2021.622359.CrossRefGoogle Scholar
Deste, G, Barlati, S, Gregorelli, M, Lisoni, J, Turrina, C, Valsecchi, P, et al. Looking through autistic features in schizophrenia using the PANSS Autism Severity Score (PAUSS). Psychiatry Res. 2018;270:764–8. https://doi.org/10.1016/j.psychres.2018.10.074.CrossRefGoogle ScholarPubMed
Ehrenreich, H, Mitjans, M, Van der Auwera, S, Centeno, TP, Begemann, M, Grabe, HJ, et al. OTTO: a new strategy to extract mental disease-relevant combinations of GWAS hits from individuals. Mol Psychiatry. 2018;23:476–86. https://doi.org/10.1038/mp.2016.208.CrossRefGoogle Scholar
Oliveira, B, Mitjans, M, Nitsche, MA, Kuo, M-F, Ehrenreich, H. Excitation-inhibition dysbalance as predictor of autistic phenotypes. J Psychiatr Res. 2018;104:96–9. https://doi.org/10.1016/j.jpsychires.2018.06.004.CrossRefGoogle ScholarPubMed
Stepniak, B, Kästner, A, Poggi, G, Mitjans, M, Begemann, M, Hartmann, A, et al. Accumulated common variants in the broader fragile X gene family modulate autistic phenotypes. EMBO Mol Med. 2015;7:1565–79. https://doi.org/10.15252/emmm.201505696.CrossRefGoogle ScholarPubMed
Parellada, M, Pina-Camacho, L, Moreno, C, Aleman, Y, Krebs, M-O, Desco, M, et al. Insular pathology in young people with high-functioning autism and first-episode psychosis. Psychol Med. 2017;47:2472–82. https://doi.org/10.1017/S0033291717000988.CrossRefGoogle ScholarPubMed
Davut, G, Onur, D, Hüseyin, G. Autistic features and executive functions in first episode psychosis: associations with functionality and quality of life. Early Interv Psychiatry. 2023; 17(8):814823. https://doi.org/10.1111/eip.13372.CrossRefGoogle ScholarPubMed
Mitjans, M, Begemann, M, Ju, A, Dere, E, Wüstefeld, L, Hofer, S, et al. Sexual dimorphism of AMBRA1-related autistic features in human and mouse. Transl Psychiatry. 2017;7:e1247. https://doi.org/10.1038/tp.2017.213.CrossRefGoogle ScholarPubMed
Nuechterlein, KH, Green, MF, Kern, RS, Baade, LE, Barch, DM, Cohen, JD, et al. The MATRICS consensus cognitive battery, part 1: test selection, reliability, and validity. Am J Psychiatry. 2008;165:203–13. https://doi.org/10.1176/appi.ajp.2007.07010042.CrossRefGoogle ScholarPubMed
Vita, A, Gaebel, W, Mucci, A, Sachs, G, Erfurth, A, Barlati, S, et al. European Psychiatric Association guidance on assessment of cognitive impairment in schizophrenia. Eur Psychiatry. 2022;65:e58. https://doi.org/10.1192/j.eurpsy.2022.2316.CrossRefGoogle ScholarPubMed
Nuechterlein, KH, Green, M. MATRICS consensus cognitive battery. Los Angeles, CA: Manual MATRICS Assessment Inc; 2006.Google Scholar
Mausbach, BT, Harvey, PD, Goldman, SR, Jeste, DV, Patterson, TL Development of a brief scale of everyday functioning in persons with serious mental illness. Schizophr Bull. 2007;33:1364–72. https://doi.org/10.1093/schbul/sbm014.CrossRefGoogle ScholarPubMed
Morosini, PL, Magliano, L, Brambilla, L, Ugolini, S, Pioli, R. Development, reliability and acceptability of a new version of the DSM-IV Social and Occupational Functioning Assessment Scale (SOFAS) to assess routine social functioning. Acta Psychiatr Scand. 2000;101:323–9.Google ScholarPubMed
Schneider, LC, Struening, EL. SLOF: a behavioral rating scale for assessing the mentally ill. Soc Work Res Abstr. 1983;19:921. https://doi.org/10.1093/swra/19.3.9.CrossRefGoogle ScholarPubMed
Mucci, A, Rucci, P, Rocca, P, Bucci, P, Gibertoni, D, Merlotti, E, et al. The specific level of functioning scale: construct validity, internal consistency and factor structure in a large Italian sample of people with schizophrenia living in the community. Schizophrenia Res. 2014;159:144–50. https://doi.org/10.1016/j.schres.2014.07.044.CrossRefGoogle Scholar
Dell’Osso, L, Gesi, C, Massimetti, E, Cremone, IM, Barbuti, M, Maccariello, G, et al. Adult Autism Subthreshold Spectrum (AdAS Spectrum): validation of a questionnaire investigating subthreshold autism spectrum. Compr Psychiatry. 2017;73:6183. https://doi.org/10.1016/j.comppsych.2016.11.001.CrossRefGoogle ScholarPubMed
Lord, C, Brugha, TS, Charman, T, Cusack, J, Dumas, G, Frazier, T, et al. Autism spectrum disorder. Nat Rev Dis Prim. 2020;6:5. https://doi.org/10.1038/s41572-019-0138-4.CrossRefGoogle ScholarPubMed
Ruzich, E, Allison, C, Smith, P, Watson, P, Auyeung, B, Ring, H, et al. Measuring autistic traits in the general population: a systematic review of the Autism-Spectrum Quotient (AQ) in a nonclinical population sample of 6,900 typical adult males and females. Mol Autism. 2015;6:2. https://doi.org/10.1186/2040-2392-6-2.CrossRefGoogle Scholar
Vannucchi, G, Masi, G, Toni, C, Dell’Osso, L, Marazziti, D, Perugi, G. Clinical features, developmental course, and psychiatric comorbidity of adult autism spectrum disorders. CNS Spectr. 2014;19:157–64. https://doi.org/10.1017/S1092852913000941.CrossRefGoogle ScholarPubMed
Abu-Akel, A, Allison, C, Baron-Cohen, S, Heinke, D. The distribution of autistic traits across the autism spectrum: evidence for discontinuous dimensional subpopulations underlying the autism continuum. Mol Autism. 2019;10:24. https://doi.org/10.1186/s13229-019-0275-3.CrossRefGoogle ScholarPubMed
Minnis, H, Messow, C-M, McConnachie, A, Bradshaw, P, Briggs, A, Wilson, P, et al. Autism and attachment disorder symptoms in the general population: prevalence, overlap, and burden. Dev Child Welf. 2020;2:3751. https://doi.org/10.1177/2516103220902778.CrossRefGoogle Scholar
Kim, YS, Leventhal, BL, Koh, Y-J, Fombonne, E, Laska, E, Lim, E-C, et al. Prevalence of autism spectrum disorders in a total population sample. Am J Psychiatry. 2011;168:904–12. https://doi.org/10.1176/appi.ajp.2011.10101532.CrossRefGoogle Scholar
Lundström, S, Reichenberg, A, Anckarsäter, H, Lichtenstein, P, Gillberg, C. Autism phenotype versus registered diagnosis in Swedish children: prevalence trends over 10 years in general population samples. Br Med J. 2015;350:h1961. https://doi.org/10.1136/bmj.h1961.CrossRefGoogle ScholarPubMed
Dell’Osso, L, Carpita, B, Nardi, B, Benedetti, F, Dell’Oste, V, Massimetti, G, et al. Autistic traits distribution in different psychiatric conditions: a cluster analysis on the basis of the Adult Autism Subthreshold Spectrum (AdAS Spectrum) questionnaire. Psychiatry Res. 2023;326:115270. https://doi.org/10.1016/j.psychres.2023.115270.CrossRefGoogle ScholarPubMed
Donati, MA, Berrocal, C, Primi, C, Petracchi, G, Carpita, B, Cosci, F, et al. Measuring subthreshold autistic traits in the general population: psychometric properties of the Adult Autism Subthreshold Spectrum (AdAS Spectrum) scale. Psychiatry Res. 2019;281:112576. https://doi.org/10.1016/j.psychres.2019.112576.CrossRefGoogle ScholarPubMed
Dell’Osso, L, Luche, RD, Gesi, C, Moroni, I, Carmassi, C, Maj, M. From Asperger’s Autistischen Psychopathen to DSM-5 autism spectrum disorder and beyond: a subthreshold autism spectrum model. Clin Pract Epidemiol Ment Health. 2016;12:120–31. https://doi.org/10.2174/1745017901612010120.CrossRefGoogle ScholarPubMed
Peng, P, Wang, Q, Zhou, Y, Hao, Y, Chen, S, Wu, Q, et al. Autistic features in Chinese patients with chronic schizophrenia: prevalence, clinical characteristics, and relationship with cognitive impairment. Asian J Psychiatr. 2023;87:103697. https://doi.org/10.1016/j.ajp.2023.103697.CrossRefGoogle ScholarPubMed
Deste, G, Vita, A, Penn, DL, Pinkham, AE, Nibbio, G, Harvey, PD. Autistic symptoms predict social cognitive performance in patients with schizophrenia. Schizophr Res. 2020;215:113–9. https://doi.org/10.1016/j.schres.2019.11.008.CrossRefGoogle ScholarPubMed
Hajdúk, M, Pinkham, AE, Penn, DL, Harvey, PD, Sasson, NJ. Heterogeneity of social cognitive performance in autism and schizophrenia. Autism Res. 2022;15:1522–34. https://doi.org/10.1002/aur.2730.CrossRefGoogle ScholarPubMed
Deste, G, Vita, A, Nibbio, G, Barlati, S, Penn, DL, Pinkham, AE, et al. Autistic symptoms in people with schizophrenia: neurocognitive, socio-cognitive, clinical and real-world functional characteristics of individuals without autistic features. Schizophrenia Res. 2021;236:12–8. https://doi.org/10.1016/j.schres.2021.07.037.CrossRefGoogle ScholarPubMed
Deste, G, Corbo, D, Nibbio, G, Italia, M, Dell’Ovo, D, Calzavara-Pinton, I, et al. Impact of physical exercise alone or in combination with cognitive remediation on cognitive functions in people with schizophrenia: a qualitative critical review. Br Sci. 2023;13:320. https://doi.org/10.3390/brainsci13020320.CrossRefGoogle ScholarPubMed
Firth, J, Stubbs, B, Rosenbaum, S, Vancampfort, D, Malchow, B, Schuch, F, et al. Aerobic exercise improves cognitive functioning in people with schizophrenia: a systematic review and meta-analysis. Schizophr Bull. 2017;43:546–56. https://doi.org/10.1093/schbul/sbw115.Google ScholarPubMed
Mueser, KT, Deavers, F, Penn, DL, Cassisi, JE. Psychosocial treatments for schizophrenia. Annu Rev Clin Psychol. 2013;9:465–97. https://doi.org/10.1146/annurev-clinpsy-050212-185620.CrossRefGoogle ScholarPubMed
Penney, D, Sauvé, G, Mendelson, D, Thibaudeau, É, Moritz, S, Lepage, M. Immediate and sustained outcomes and moderators associated with metacognitive training for psychosis: a systematic review and meta-analysis. JAMA Psychiatry. 2022;79:417–29. https://doi.org/10.1001/jamapsychiatry.2022.0277.CrossRefGoogle ScholarPubMed
Vita, A, Gaebel, W, Mucci, A, Sachs, G, Barlati, S, Giordano, GM, et al. European Psychiatric Association guidance on treatment of cognitive impairment in schizophrenia. Eur Psychiatry. 2022;65:e57. https://doi.org/10.1192/j.eurpsy.2022.2315.CrossRefGoogle ScholarPubMed
Vita, A, Barlati, S, Ceraso, A, Deste, G, Nibbio, G, Wykes, T. Acceptability of cognitive remediation for schizophrenia: a systematic review and meta-analysis of randomized controlled trials. Psychol Med. 2023; 53(8):36613671. https://doi.org/10.1017/S0033291722000319.CrossRefGoogle ScholarPubMed
Lord, C, Risi, S, Lambrecht, L, Cook, EH, Leventhal, BL, DiLavore, PC, et al. The autism diagnostic observation schedule-generic: a standard measure of social and communication deficits associated with the spectrum of autism. J Autism Dev Disord. 2000;30:205–23.CrossRefGoogle ScholarPubMed
Figure 0

Table 1. Group comparison for demographic and clinical variables

Figure 1

Table 2. Group comparison for cognitive measures

Figure 2

Table 3. Group comparison for functional measures

Submit a response

Comments

No Comments have been published for this article.