Associations of schizophrenia risk genes ZNF804A and CACNA1C with schizotypy and modulation of attention in healthy subjects

Factor analysis of lifetime psychopathology and its brain morphometric and genetic correlates in a transdiagnostic sample

There is a lack of knowledge regarding the relationship between proneness to dimensional psychopathological syndromes and the underlying pathogenesis across major psychiatric disorders, i.e., Major Depressive Disorder (MDD), Bipolar Disorder (BD), Schizoaffective Disorder (SZA), and Schizophrenia (SZ). Lifetime psychopathology was assessed using the OPerational CRITeria (OPCRIT) system in 1,038 patients meeting DSM-IV-TR criteria for MDD, BD, SZ, or SZA. The cohort was split into two samples for exploratory and confirmatory factor analyses. All patients were scanned with 3-T MRI, and data was analyzed with the CAT-12 toolbox in SPM12. Psychopathological factor scores were correlated with gray matter volume (GMV) and cortical thickness (CT). Finally, factor scores were used for exploratory genetic analyses including genome-wide association studies (GWAS) and polygenic risk score (PRS) association analyses. Three factors (paranoid-hallucinatory syndrome, PHS; mania, MA; depression, DEP) were identified and cross-validated. PHS was negatively correlated with four GMV clusters comprising parts of the hippocampus, amygdala, angular, middle occipital, and middle frontal gyri. PHS was also negatively associated with the bilateral superior temporal, left parietal operculum, and right angular gyrus CT. No significant brain correlates were observed for the two other psychopathological factors. We identified genome-wide significant associations for MA and DEP. PRS for MDD and SZ showed a positive effect on PHS, while PRS for BD showed a positive effect on all three factors. This study investigated the relationship of lifetime psychopathological factors and brain morphometric and genetic markers. Results highlight the need for dimensional approaches, overcoming the limitations of the current psychiatric nosology.

The interplay between polygenic score for tumor necrosis factor-α, brain structural connectivity, and processing speed in major depression

Reduced processing speed is a core deficit in major depressive disorder (MDD) and has been linked to altered structural brain network connectivity. Ample evidence highlights the involvement of genetic-immunological processes in MDD and specific depressive symptoms. Here, we extended these findings by examining associations between polygenic scores for tumor necrosis factor-α blood levels (TNF-α PGS), structural brain connectivity, and processing speed in a large sample of MDD patients. Processing speed performance of n = 284 acutely depressed, n = 177 partially and n = 198 fully remitted patients, and n = 743 healthy controls (HC) was estimated based on five neuropsychological tests. Network-based statistic was used to identify a brain network associated with processing speed. We employed general linear models to examine the association between TNF-α PGS and processing speed. We investigated whether network connectivity mediates the association between TNF-α PGS and processing speed. We identified a structural network positively associated with processing speed in the whole sample. We observed a significant negative association between TNF-α PGS and processing speed in acutely depressed patients, whereas no association was found in remitted patients and HC. The mediation analysis revealed that brain connectivity partially mediated the association between TNF-α PGS and processing speed in acute MDD. The present study provides evidence that TNF-α PGS is associated with decreased processing speed exclusively in patients with acute depression. This association was partially mediated by structural brain connectivity. Using multimodal data, the current findings advance our understanding of cognitive dysfunction in MDD and highlight the involvement of genetic-immunological processes in its pathomechanisms.

Schizophrenia polygenic risk score in psychosis proneness

Schizophrenia (SZ) is a complex disorder with a highly polygenic inheritance. It can be conceived as the extreme expression of a continuum of traits that are present in the general population often broadly referred to as schizotypy. However, it is still poorly understood how these traits overlap genetically with the disorder. We investigated whether polygenic risk for SZ is associated with these disorder-related phenotypes (schizotypy, psychotic-like experiences, and subclinical psychopathology) in a sample of 253 non-clinically identified participants. Polygenic risk scores (PRSs) were constructed based on the latest SZ genome-wide association study using the PRS-CS method. Their association with self-report and interview measures of SZ-related traits was tested. No association with either schizotypy or psychotic-like experiences was found. However, we identified a significant association with the Motor Change subscale of the Comprehensive Assessment of At-Risk Mental States (CAARMS) interview. Our results indicate that the genetic overlap of SZ with schizotypy and psychotic-like experiences is less robust than previously hypothesized. The relationship between high PRS for SZ and motor abnormalities could reflect neurodevelopmental processes associated with psychosis proneness and SZ.

Pleiotropic Association of CACNA1C Variants With Neuropsychiatric Disorders

BACKGROUND

Neuropsychiatric disorders are highly heritable and have overlapping genetic underpinnings. Single nucleotide polymorphisms (SNPs) in the gene CACNA1C have been associated with several neuropsychiatric disorders, across multiple genome-wide association studies.

METHOD

A total of 70,711 subjects from 37 independent cohorts with 13 different neuropsychiatric disorders were meta-analyzed to identify overlap of disorder-associated SNPs within CACNA1C. The differential expression of CACNA1C mRNA in five independent postmortem brain cohorts was examined. Finally, the associations of disease-sharing risk alleles with total intracranial volume (ICV), gray matter volumes (GMVs) of subcortical structures, cortical surface area (SA), and average cortical thickness (TH) were tested.

RESULTS

Eighteen SNPs within CACNA1C were nominally associated with more than one neuropsychiatric disorder (P < .05); the associations shared among schizophrenia, bipolar disorder, and alcohol use disorder survived false discovery rate correction (five SNPs with P < 7.3 × 10-4 and q < 0.05). CACNA1C mRNA was differentially expressed in brains from individuals with schizophrenia, bipolar disorder, and Parkinson's disease, relative to controls (three SNPs with P < .01). Risk alleles shared by schizophrenia, bipolar disorder, substance dependence, and Parkinson's disease were significantly associated with ICV, GMVs, SA, or TH (one SNP with P ≤ 7.1 × 10-3 and q < 0.05).

CONCLUSION

Integrating multiple levels of analyses, we identified CACNA1C variants associated with multiple psychiatric disorders, and schizophrenia and bipolar disorder were most strongly implicated. CACNA1C variants may contribute to shared risk and pathophysiology in these conditions.

Trait schizotypy and the psychosis prodrome: Current standard assessment of extended psychosis spectrum phenotypes

Schizotypy has become an increasingly important construct for elaborating psychotic disorders that vary along the schizophrenic spectrum. However, different schizotypy inventories vary in conceptual approach and measurement. In addition, commonly used schizotypy scales have been seen as qualitatively different from screening instruments for prodromal schizophrenia like the Prodromal Questionnaire-16 (PQ-16). Our study investigated the psychometric properties of three schizotypy questionnaires (the Schizotypal Personality Questionnaire-Brief, Oxford-Liverpool Inventory of Feelings and Experiences, and the Multidimensional Schizotypy Scale) as well as the PQ-16 in a cohort of 383 non-clinical subjects. We initially evaluated their factor structure using Principal Component Analysis (PCA) and used Confirmatory Factor Analysis (CFA) to test a newly proposed composition of factors. PCA results support a three-factor structure of schizotypy that accounts for 71 % of the total variance, but also shows cross-loadings of some schizotypy subscales. CFA of the newly composed schizotypy factors (together with an added neuroticism factor) shows good fit. Analyses including the PQ-16 indicate considerable overlap with measures of trait schizotypy, suggesting that the PQ-16 might not be quantitatively or qualitatively different from schizotypy measurements. Taken together, results indicate that there is good support for a three-factor structure of schizotypy but also that different schizotypy measurements grasp facets of schizotypy differently. This points towards the need for an integrative approach for assessing the construct of schizotypy.

Genetic, individual, and familial risk correlates of brain network controllability in major depressive disorder

Many therapeutic interventions in psychiatry can be viewed as attempts to influence the brain's large-scale, dynamic network state transitions. Building on connectome-based graph analysis and control theory, Network Control Theory is emerging as a powerful tool to quantify network controllability-i.e., the influence of one brain region over others regarding dynamic network state transitions. If and how network controllability is related to mental health remains elusive. Here, from Diffusion Tensor Imaging data, we inferred structural connectivity and inferred calculated network controllability parameters to investigate their association with genetic and familial risk in patients diagnosed with major depressive disorder (MDD, n = 692) and healthy controls (n = 820). First, we establish that controllability measures differ between healthy controls and MDD patients while not varying with current symptom severity or remission status. Second, we show that controllability in MDD patients is associated with polygenic scores for MDD and psychiatric cross-disorder risk. Finally, we provide evidence that controllability varies with familial risk of MDD and bipolar disorder as well as with body mass index. In summary, we show that network controllability is related to genetic, individual, and familial risk in MDD patients. We discuss how these insights into individual variation of network controllability may inform mechanistic models of treatment response prediction and personalized intervention-design in mental health.

Genetic contributions to transdiagnostic symptom dimensions in patients with major depressive disorder, bipolar disorder, and schizophrenia spectrum disorders

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia spectrum disorders (SZ) exhibit considerable phenotypic and genetic overlap. However, the contribution of genetic factors to their shared psychopathological symptom dimensions remains unclear. The present exploratory study investigated genetic contributions to the symptom dimensions "Depression", "Negative syndrome", "Positive formal thought disorder", "Paranoid-hallucinatory syndrome", and "Increased appetite" in a transdiagnostic subset of the German FOR2107 cohort (n = 1042 patients with MDD, BD, or SZ). As replication cohort, a subset of the German/Austrian PsyCourse study (n = 816 patients with MDD, BD, or SZ) was employed. First, the relationship between symptom dimensions and common variants associated with MDD, BD, and SZ was investigated via polygenic risk score (PRS) association analyses, with disorder-specific PRS as predictors and symptom dimensions as outcomes. In the FOR2107 study sample, PRS for BD and SZ were positively associated with "Positive formal thought disorder", the PRS for SZ was positively associated with "Paranoid-hallucinatory syndrome", and the PRS for BD was negatively associated with "Depression". The effects of PRS for SZ were replicated in PsyCourse. No significant associations were observed for the MDD PRS. Second, genome-wide association studies (GWAS) were performed for the five symptom dimensions. No genome-wide significant associations and no replicable suggestive associations (p < 1e-6 in the GWAS) were identified. In summary, our results suggest that, similar to diagnostic categories, transdiagnostic psychiatric symptom dimensions are attributable to polygenic contributions with small effect sizes. Further studies in larger thoroughly phenotyped psychiatric cohorts are required to elucidate the genetic factors that shape psychopathological symptom dimensions.

Comparison of executive functions in individuals with high and low levels of schizotypal trait

The dimensional approach to Schizotypal Personality Disorder (SPD) indicates that SPD includes a constellation of maladaptive personality traits on a continuum with general personality functioning. This study aimed to compare executive functions (EFs) in low and high-level schizotypal individuals. Using a convenient sampling method, we recruited 120 individuals, from which 30 individuals with high schizotypal trait levels (fourth quartile) and 30 participants with lower schizotypal trait levels (first quartile) were selected based on their scores on the schizotypal personality disorder questionnaire. Then, participants from the two groups were administered the Corsi Block-Tapping Test (CBTT), Wisconsin Card Sorting Test (WCST), and Continuance Performance Test (CPT). The results indicated individuals with higher schizotypy trait levels performed significantly poorer in tasks measuring working-visual-spatial memory, cognitive flexibility, sustained attention, and response inhibition. This pattern of results indicated that EF dysfunctions in individuals with higher schizotypy trait levels would cause significant disturbances in multiple areas of life. The practical implications of the findings are further discussed.

Relationship between polygenic risk scores and symptom dimensions of schizophrenia and schizotypy in multiplex families with schizophrenia

BACKGROUND

Psychotic disorders and schizotypal traits aggregate in the relatives of probands with schizophrenia. It is currently unclear how variability in symptom dimensions in schizophrenia probands and their relatives is associated with polygenic liability to psychiatric disorders.

AIMS

To investigate whether polygenic risk scores (PRSs) can predict symptom dimensions in members of multiplex families with schizophrenia.

METHOD

The largest genome-wide data-sets for schizophrenia, bipolar disorder and major depressive disorder were used to construct PRSs in 861 participants from the Irish Study of High-Density Multiplex Schizophrenia Families. Symptom dimensions were derived using the Operational Criteria Checklist for Psychotic Disorders in participants with a history of a psychotic episode, and the Structured Interview for Schizotypy in participants without a history of a psychotic episode. Mixed-effects linear regression models were used to assess the relationship between PRS and symptom dimensions across the psychosis spectrum.

RESULTS

Schizophrenia PRS is significantly associated with the negative/disorganised symptom dimension in participants with a history of a psychotic episode (P = 2.31 × 10^-4) and negative dimension in participants without a history of a psychotic episode (P = 1.42 × 10^-3). Bipolar disorder PRS is significantly associated with the manic symptom dimension in participants with a history of a psychotic episode (P = 3.70 × 10^-4). No association with major depressive disorder PRS was observed.

CONCLUSIONS

Polygenic liability to schizophrenia is associated with higher negative/disorganised symptoms in participants with a history of a psychotic episode and negative symptoms in participants without a history of a psychotic episode in multiplex families with schizophrenia. These results provide genetic evidence in support of the spectrum model of schizophrenia, and support the view that negative and disorganised symptoms may have greater genetic basis than positive symptoms, making them better indices of familial liability to schizophrenia.

A functional neuroimaging association study on the interplay between two schizophrenia genome-wide associated genes (CACNA1C and ZNF804A)

The CACNA1C and the ZNF804A genes are among the most relevant schizophrenia GWAS findings. Recent evidence shows that the interaction of these genes with the schizophrenia diagnosis modulates brain functional response to a verbal fluency task. To better understand how these genes might influence the risk for schizophrenia, we aimed to study the interplay between CACNA1C and ZNF804A on working memory brain functional correlates. The analyses included functional and behavioural N-back task data (obtained from an fMRI protocol) and CACNA1C-rs1006737 and ZNF804A-rs1344706 genotypes for 78 healthy subjects and 78 patients with schizophrenia (matched for age, sex and premorbid IQ). We tested the effects of the epistasis between these genes as well as of the three-way interaction (CACNA1C × ZNAF804A × diagnosis) on working memory-associated activity (N-back: 2-back vs 1-back). We detected a significant CACNA1C × ZNAF804A interaction on working memory functional response in regions comprising the ventral caudate medially and within the left hemisphere, the superior and inferior orbitofrontal gyrus, the superior temporal pole and the ventral-anterior insula. The individuals with the GWAS-identified risk genotypes (CACNA1C-AA/AG and ZNF804A-AA) displayed a reduced working memory modulation response. This genotypic combination was also associated with opposite brain activity patterns between patients and controls. While further research will help to comprehend the neurobiological mechanisms of this interaction, our data highlight the role of the epistasis between CACNA1C and ZNF804A in the functional mechanisms underlying the pathophysiology of schizophrenia.

Polygenic risk for schizophrenia and schizotypal traits in non-clinical subjects

BACKGROUND

Schizotypy is a putative risk phenotype for psychosis liability, but the overlap of its genetic architecture with schizophrenia is poorly understood.

METHODS

We tested the hypothesis that dimensions of schizotypy (assessed with the SPQ-B) are associated with a polygenic risk score (PRS) for schizophrenia in a sample of 623 psychiatrically healthy, non-clinical subjects from the FOR2107 multi-centre study and a second sample of 1133 blood donors.

RESULTS

We did not find correlations of schizophrenia PRS with either overall SPQ or specific dimension scores, nor with adjusted schizotypy scores derived from the SPQ (addressing inter-scale variance). Also, PRS for affective disorders (bipolar disorder and major depression) were not significantly associated with schizotypy.

CONCLUSIONS

This important negative finding demonstrates that despite the hypothesised continuum of schizotypy and schizophrenia, schizotypy might share less genetic risk with schizophrenia than previously assumed (and possibly less compared to psychotic-like experiences).

CACNA1C Gene rs1006737 Polymorphism Affects Cognitive Performance in Chinese Han Schizophrenia

OBJECTIVE

To investigate the relationship between L-type calcium channel α1C subunit (CACNA1C) gene polymorphism and schizophrenia (SCZ) and cognitive function in the Han nationality, the main nationality in China.

METHODS

Genotyping of CACNA1C SNP (rs1006737, rs1024582, rs2007044) in SCZ patients (n = 312) and healthy controls (n = 305) was performed. Cognitive function was assessed in the SCZ patients using Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Then, the correlation between SNP and SCZ, as well as cognition, was calculated.

RESULTS

There was no significant difference in allele frequency and genotype distribution frequency of the three polymorphic loci of CACNA1C gene between the two groups. In cognitive tests, delayed memory scores in RBANS were significantly lower in rs1006737 "A" risk allele carriers than in non-carriers.

CONCLUSION

There is no significant difference in allele and genotype frequency of CANCA1C Gene rs1006737, rs1024582 and rs2007044 between the schizophrenia patients and healthy controls. The cognitive function of schizophrenia patients is correlated with the rs1006737, and the delayed memory of "A" allele carriers is significantly reduced.

Polygenic risk scores across the extended psychosis spectrum

As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.

Identification of transdiagnostic psychiatric disorder subtypes using unsupervised learning

Psychiatric disorders show heterogeneous symptoms and trajectories, with current nosology not accurately reflecting their molecular etiology and the variability and symptomatic overlap within and between diagnostic classes. This heterogeneity impedes timely and targeted treatment. Our study aimed to identify psychiatric patient clusters that share clinical and genetic features and may profit from similar therapies. We used high-dimensional data clustering on deep clinical data to identify transdiagnostic groups in a discovery sample (N = 1250) of healthy controls and patients diagnosed with depression, bipolar disorder, schizophrenia, schizoaffective disorder, and other psychiatric disorders. We observed five diagnostically mixed clusters and ordered them based on severity. The least impaired cluster 0, containing most healthy controls, showed general well-being. Clusters 1-3 differed predominantly regarding levels of maltreatment, depression, daily functioning, and parental bonding. Cluster 4 contained most patients diagnosed with psychotic disorders and exhibited the highest severity in many dimensions, including medication load. Depressed patients were present in all clusters, indicating that we captured different disease stages or subtypes. We replicated all but the smallest cluster 1 in an independent sample (N = 622). Next, we analyzed genetic differences between clusters using polygenic scores (PGS) and the psychiatric family history. These genetic variables differed mainly between clusters 0 and 4 (prediction area under the receiver operating characteristic curve (AUC) = 81%; significant PGS: cross-disorder psychiatric risk, schizophrenia, and educational attainment). Our results confirm that psychiatric disorders consist of heterogeneous subtypes sharing molecular factors and symptoms. The identification of transdiagnostic clusters advances our understanding of the heterogeneity of psychiatric disorders and may support the development of personalized treatments.

Nonclinical psychotic-like experiences and schizotypy dimensions: Associations with hippocampal subfield and amygdala volumes

Schizotypy and psychotic‐like experiences (PLE) form part of the wider psychosis continuum and may have brain structural correlates in nonclinical cohorts. This study aimed to compare the effects of differential schizotypy dimensions, PLE, and their interaction on hippocampal subfields and amygdala volumes in the absence of clinical psychopathology. In a cohort of 367 psychiatrically healthy individuals, we assessed schizotypal traits using the Oxford‐Liverpool Inventory of Life Experiences (O‐LIFE) and PLE using the short form of the Prodromal Questionnaire (PQ‐16). Based on high‐resolution structural MRI scans, we used automated segmentation to estimate volumes of limbic structures. Sex and total intracranial volume (Step 1), PLE and schizotypy dimensions (Step 2), and their interaction terms (Step 3) were entered as regressors for bilateral amygdala and hippocampal subfield volumes in hierarchical multiple linear regression models. Positive schizotypy, but not PLE, was negatively associated with left amygdala and subiculum volumes. O‐LIFE Impulsive Nonconformity, as well as the two‐way interaction between positive schizotypy and PLE, were associated with larger left subiculum volumes. None of the estimators for right hemispheric hippocampal subfield volumes survived correction for multiple comparisons. Our findings support differential associations of hippocampus subfield volumes with trait dimensions rather than PLE, and support overlap and interactions between psychometric positive schizotypy and PLE. In a healthy cohort without current psychosis risk syndromes, the positive association between PLE and hippocampal subfield volume occurred at a high expression of positive schizotypy. Further studies combining stable, transient, and genetic parameters are required.

rs1344706 polymorphism of zinc finger protein 804a (ZNF804a) gene related to the integrity of white matter fiber bundle in schizophrenics

Genetic factors play an important role in the pathogenesis of schizophrenia (SZ), and the zinc finger protein 804a (ZNF804a) gene has been considered to be a risk gene for schizophrenia. In the present study, the correlation between rs1344706 polymorphism of ZNF804a gene and the integrity of white matter in schizophrenic cases was explored. A total of 60 SZ patients and 100 healthy controls (HC) were included to undergo head MRI. According to the genotyping of rs1344706 in ZNF804a, the subjects in each group were divided into a normal allele and risk allele-carrying group. The imaging data were preprocessed by PANDA software, and thefractional anisotropy (FA) of each subject was calculated. With SPM8 software, age and years of education were considered as covariates, and diagnosis as well as genotype (AA, GG/AG) were considered as intergroup factors. Four groups of FA images were analyzed by two-factor analysis of variance. The FA value of the right posterior radiocrown in the patient group was lower than that in the control group, and the difference was statistically significant. The FA value of the right lower frontal occipital tract and the right upper radiocrown in the G allele carrier group was lower than that in the A allele homozygous group. There was detection of an interaction between the FA value of the splenium of corpus callosum, the body part of the corpus callosum and the right cingulate tract. In the present study, it was demonstrated that the rs1344706 GG/AG genotype of the ZNF804a gene locus in SZ patients suffered from abnormal structure in a specific region of the brain. This finding indicated that the rs1344706 single nucleotide polymorphism of the ZNF804a gene may affect the integrity of the white matter of the brain in SZ patients and may be involved in the pathophysiological mechanism of SZ.

The Schizotypal Personality Questionnaire for Children (SPQ-C): Factor Structure, Child Abuse, and Family History of Schizotypy

There is a relative dearth of research on features of schizotypal personality in children, in part due to lack of instrumentation. This study tests 5 competing models of the factor structure of the self-report Schizotypal Personality Questionnaire for Children (SPQ-C) and examines its relationship with a family history of schizotypal personality disorder (SPD), child abuse, and stability over time. Hypotheses were tested on 454 11- to 12-year-old schoolchildren and their caregivers. Confirmatory factor analyses supported a 3-factor structure of the SPQ-C (cognitive-perceptual, interpersonal, and disorganized). Test-retest stability was relatively robust over 3 months (r = .67), 6 months (r = .64), and 12 months (r = .55), with acceptable internal reliabilities (r = .84 to .91). Regarding construct validity, children with a biological family history of SPD had higher scores on all 3 factors (d =.51). Abused children had higher schizotypy scores (d = .55). A genetic × environment interaction was observed, with schizotypy highest in those with both a family history of schizotypy and also child abuse. Findings are the first in the child schizotypy field to document a gene × environment interaction and the independence of child abuse from confounding genetic influences. Results support the utility of the SPQ-C in future family and clinical studies of schizotypal personality and provide an avenue for much-needed and neglected research into the early antecedents of child schizotypal personality.