Introduction
Schizophrenia and schizophrenia spectrum disorders (SSD) remain a prominent public health risk. There are persistent gaps in knowledge surrounding the biological mechanisms of symptoms affecting cognition, behavior, and emotion. To track the emergence and progression of symptoms, there is a need for reliable biomarkers of schizophrenia and SSD. These biomarkers can reveal underlying mechanisms as well as complementing existing clinical interviewing methods. Biomarkers may also be used to predict conversion from high-risk to diagnosis (Näätänen et al., 2016). Currently there is no gold standard biomarker that reliably tracks symptom severity (Lieberman et al., 2019), although there is convergence regarding risk factors and cognitive deficits (Mohn-Haugen et al., 2022). This has led to many calls for multivariate biomarker metrics to more comprehensively assess an individual’s risk level (e.g., (Cannon et al., 2016; Price et al., 2006; Seidman, Shapiro, et al., 2016). Although this opinion is not controversial, there remains a tendency to focus on single biomarkers and their predictive power. This may be due to the simplicity of understanding how a single biomarker reflects underlying processing schizophrenia and SSD, and to the added technical difficulties and financial challenges involved when measuring multiple biomarkers. Here, we support the call for a multivariate biomarker, and we extend this view by suggesting that to accelerate our understanding of the neural mechanisms associated with symptoms, it would be valuable to test across the entire SSD, including neurotypical individuals with high subclinical schizotypy symptomatology in the general population . This suggestion has the added benefit of increasing the pool of researchers available to investigate questions of clinical relevance, but who do not have access to clinical populations.
Here, we define schizotypy as the subclinicalcharacteristics associated with schizophrenia that are prevalent within the general population. Schizotypy in this context is not a diagnosis as the schizophrenia-related traits are not severe enough to warrant intervention. It is unknown if participants with high schizotypy traits will develop schizophrenia and/or psychosis in the future, as many of these studies are cross-sectional in design and recruit from the general population . However, one value of focusing on schizotypy is that participants with psychiatric or neurological diagnosis can be removed. This reduces the likelihood of comorbid conditions and medications that may confound the findings. Therefore, it would be expeditious to include a larger swath of the spectrum to include the larger subclinical population, and to combine discrete biomarkers that track symptom severity.
Existing biomarkers include: genetic polymorphisms (Ettinger et al., 2014), oculomotor abnormalities (reviewed in: (Levy et al., 2010)), and atypical neural responses detected using EEG and fMRI. Unfortunately, many of these biomarkers were identified in isolation rather than in tandem with other biomarkers associated with a particular sensory or cognitive domain. This is despite success when taking a multifactorial approach to monitoring multiple neural (Kent et al., 2004; Price et al., 2006; Ranlund et al., 2018; Taylor et al., 2017) and behavioral (Seidman, Shapiro, et al., 2016) measures to help distinguish between schizophrenia and other psychosis-related conditions such as bipolar disorder. Due to the success seen in those diagnosed with schizophrenia, we recommend the same multifactorial approach for the subclinical schizotypy population. For the current review, we revisit EEG biomarkers from several related literatures: abnormal sensorymemory (SM) and working memory (WM), in both auditory and visual modalities. These topics have well-developed literatures with a substantial foundation in the clinical schizophrenia and SSD populations. We focused on sensory and working memory specifically, to explore how these biomarkers may interact due to downstream deficits impacting later processing. We discuss the use of sensory and working memory measures as biomarkers of symptom severity from a cross-sectional perspective - how do these markers reflect on their internal processes at this moment? We conclude by discussing how some of the biomarkers we discuss may be promising as predictive biomarkers of the onset of psychosis and schizophrenia, and briefly summarize some of the literature up to this point.