Wendy Alfonso Torrens

Introduction
Autism spectrum disorder (ASD) and schizophrenia spectrum disorder (SSD) share some symptoms. We conducted machine learning classification to determine if common screeners used for research in non-clinical and subclinical populations, the Autism-Spectrum Quotient (AQ) and Schizotypal Personality Questionnaire – Brief Revised (SPQ-BR), could identify non-overlapping symptoms.
Methods
1,397 undergraduates completed the SPQ-BR and AQ. Random forest classification modelled whether SPQ-BR item scores predicted AQ scores and factors, and vice versa. The models first used all item scores and then the least/most important features.
Results
Robust trait overlap allows for the prediction of AQ from SPQ-BR and vice versa. Results showed that AQ item scores predicted 2 of 3 SPQ-BR factors (disorganised, interpersonal), and SPQ-BR item scores successfully predicted 2 of 5 AQ factors (communication, social skills). Importantly, classification model failures showed that AQ item scores could not predict the SPQ-BR cognitive-perceptual factor, and the SPQ-BR item scores could not predict 3 AQ factors (imagination, attention to detail, attention switching).
Conclusions
Overall, the SPQ-BR and AQ measure overlapping symptoms that can be isolated to some factors. Importantly, where we observe model failures, we capture distinctive factors. We provide guidance for leveraging existing screeners to avert misdiagnosis and advancing specific/selective biomarker identification.

Introduction: Schizophrenia and autism spectrum disorder are distinct neurodevelopmental disorders sharing clinically relevant behaviours. However, early sensory responses show divergent responses. Individuals with schizophrenia typically exhibit cortical hypo-excitability whereas individuals with autism show cortical hyperexcitability. Identifying reliable neurobiological differences between the disorders can diminish misdiagnosis and optimise treatments.
Methods: The pattern glare test (PGT) is a simple measure of behavioural hyperexcitability. It measures the number of illusions seen in a static horizontal grating. We collected PGT data from non-clinical adults varying in traits of autism and schizophrenia (schizotypy). 576 undergraduate students completed an online survey consisting of the Schizotypal Personality Questionnaire –Brief Revised, the Autism Spectrum Quotient, and the PGT.
Results: Subclinical autism and schizotypy traits were highly positively correlated. However, only schizotypy scores were significantly predictive of reporting more pattern glare (PG) illusions. When assessing the subcomponents of the schizotypy and autism scores, positive and disorganised schizotypy traits were predictive of reporting more PG illusions. Whereas, subclinical autism factors were not predictive of PG illusions.
Conclusions: High schizotypy performed the PGT in a manner consistent with behavioural hyperexcitability. The PGT distinguished subclinical autistic traits from schizotypy, suggesting potential clinical application.

Poster presentation for Society for Biological Psychiatry:

Sensory responses in schizophrenia are generally characterized as hypo-excitable, particularly to auditory stimuli. However, individuals with subclinical schizophrenia-like traits (schizotypy) tend to experience high numbers of illusions in the Pattern Glare Test (PGT), suggesting behavioral hyperexcitability. In the current study, we sought to examine the interaction between behavioral hyperexcitability and sensory neural responses in schizotypy.

Poster presentation for Society for Biological Psychiatry:

Mismatch negativity (MMN) is a proposed biomarker of schizophrenia and is thought to worsen with symptom severity. MMN is a negative event-related potential (ERP) that is generated in response to deviant stimuli and is robustly attenuated in schizophrenia. For MMN to be a biomarker of symptom severity, it must be evident, to a lesser extent, in those with subclinical high schizotypy. Schizotypy refers to the subclinical population exhibiting a cluster of schizophrenia-like characteristics. Advantages of using schizotypy include the lack of medication-related confounds and their similar sensory profile to schizophrenia.

Individuals diagnosed with schizophrenia spectrum disorders (SSD) exhibit a constellation of sensory and perceptual impairments, including hyporeactivity to external input. However, individuals with SSD also report subjective experiences of sensory flooding, suggesting sensory hyperexcitability. To identify the extent to which behavioural indices of hyperexcitability are related to non-psychotic symptoms of schizophrenia, we tested a non-clinical population measured for schizophrenia-like traits (schizotypy), and a behavioural measure of sensory hyperexcitability, specifically the number of illusions seen in the Pattern Glare Test. Two samples totaling 913 individuals completed an online version of the Schizotypal Personality Questionnaire – Brief Revised (SPQ-BR) and the Pattern Glare Test. Individuals with higher schizotypy traits reported more illusions in the Pattern Glare Test. Additionally, one of the three SPQ-BR factors, the disorganized factor, significantly predicted the number of illusions reported. These data illustrate the potential for research in non-clinical samples to inform clinically relevant research.

Abstract for Poster Presentation:

Individuals with schizophrenia spectrum disorders (SSD) exhibit working memory (WM) impairments. These impairments may be associated with symptom severity rather than the onset of psychosis. We searched for a biomarker of WM deficits in individuals high in schizotypy traits (non-clinical population). We predicted that individuals high in schizotypy would perform worse and have lower event-related potential (ERP) amplitudes than controls in a WM task.

Previous research suggests there is a relationship between individuals’ insecure attachment and level of psychopathy. However, there is little evidence indicating whether anxious or avoidant attachment is more predictive of psychopathy generally, or the two factors of psychopathy (meanness and impulsivity) specifically. A convenience sample of 137 participants was gathered to test four hypotheses. We first hypothesized that avoidant attachment in adulthood (i.e., attachments to all domains) would predict meanness, the primary factor of psychopathy; secondly, we hypothesized avoidant attachment would also predict impulsivity. Similarly, we hypothesized that anxious attachment in adulthood would predict meanness in psychopathy as well as impulsivity in psychopathy. We used a simple linear regression to test all four hypotheses. All but one hypothesis was supported. Anxious attachment served as a better predictor for both dimensions of psychopathy. Limitations and implications are discussed.