Neurobiological approaches to the study of clinical and genetic high risk for developing psychosis

Resting-state functional connectivity correlates of brain structural aging in schizophrenia

A large body of research has shown that schizophrenia patients demonstrate increased brain structural aging. Although this process may be coupled with aberrant changes in intrinsic functional architecture of the brain, they remain understudied. We hypothesized that there are brain regions whose whole-brain functional connectivity at rest is differently associated with brain structural aging in schizophrenia patients compared to healthy controls. Eighty-four male schizophrenia patients and eighty-six male healthy controls underwent structural MRI and resting-state fMRI. The brain-predicted age difference (b-PAD) was a measure of brain structural aging. Resting-state fMRI was applied to obtain global correlation (GCOR) maps comprising voxelwise values of the strength and sign of functional connectivity of a given voxel with the rest of the brain. Schizophrenia patients had higher b-PAD compared to controls (mean between-group difference + 2.9 years). Greater b-PAD in schizophrenia patients, compared to controls, was associated with lower whole-brain functional connectivity of a region in frontal orbital cortex, inferior frontal gyrus, Heschl's Gyrus, plana temporale and polare, insula, and opercular cortices of the right hemisphere (rFTI). According to post hoc seed-based correlation analysis, decrease of functional connectivity with the posterior cingulate gyrus, left superior temporal cortices, as well as right angular gyrus/superior lateral occipital cortex has mainly driven the results. Lower functional connectivity of the rFTI was related to worse verbal working memory and language production. Our findings demonstrate that well-established frontotemporal functional abnormalities in schizophrenia are related to increased brain structural aging.

New portable device for an examination of visual cognitive evoked potentials might extend their diagnostic applications in psychiatry

Despite positive prior results obtained by using event-related potentials (ERPs) in psychiatric patients, they are not routinely used in the clinical setting. This may in part be due to problems regarding a lack of transportable equipment availability. It can be difficult for these patients to repeatedly visit electrophysiological laboratories. To address this issue, we propose using a new, fully portable device for visually evoked potentials (VEP) and cognitive function assessment, that can be used for quick examinations (https://www.veppeak.com). Our device, called "VEPpeak", is built into a headset with a color LED visual stimulator. It weighs 390 g and is connected to a notebook (PC) with evaluation software via USB. In this pilot study, we verified the device's usability in 31 patients with schizophrenia. We used the oddball paradigm with the recognition of colors for the P300 wave and choice reaction time evaluation. The examination lasted only about ten minutes. The results indicated good reproducibility of large cognitive potentials (P300) with prolonged P300 latencies and reduced amplitudes in patients compared to 15 control subjects. The P300 latency and reaction time prolongation in patients correlated with their age and the sedative effect of the pharmacotherapy.

Executive control of language in schizophrenia patients with history of auditory verbal hallucinations: A neuropsychological and resting-state fMRI study

BACKGROUND

As demonstrated by a plethora of studies, compromised executive functions (EF) and language are implicated in mechanisms of auditory verbal hallucinations (AVH), but the contribution of their interaction to AVH remains unclear. We hypothesized that schizophrenia patients with history of AVH (AVHh+) vs. without history of AVH (AVHh-) have a specific deficit of executive control of language and alterations in functional connectivity (FC) between the brain regions involved in EF and language, and these neuropsychological and neurophysiological traits are associated with each other.

METHODS

To explore the executive control of language and its contribution to AVH, we used an integrative approach involving analysis of neuropsychological and resting-state fMRI data of 34 AVHh+, 16 AVHh-, and 40 healthy controls. We identified the neuropsychological and FC measures that differentiated between AVHh+, AVHh-, and HC, and tested the associations between them.

RESULTS

AVHh+ were characterized by decreased category and phonological verbal fluency, utterance length, productivity in the planning tasks, and poorer retelling. AVHh+ had decreased FC between the left inferior frontal gyrus and the anterior cingulate cortex. Productivity in category verbal fluency was associated with the FC between these regions.

CONCLUSIONS

Poor executive control of word retrieval and deficient programming of sentence and narrative related to more general deficits of planning may be the neuropsychological traits specific for AVHh+. A neurophysiological trait specific for AVHh+ may be a decreased FC between regions involved in language production and differentiation between alien- vs. self-generated speech and between language production vs. comprehension.

Value of P300 amplitude in the diagnosis of untreated first-episode schizophrenia and psychosis risk syndrome in children and adolescents

BACKGROUND

Identifying the characteristic neurobiological changes of early psychosis is helpful for early clinical diagnosis. However, previous studies on the brain electrophysiology of children and adolescents with psychosis are rare.

METHODS

This study compared P300 amplitude at multiple electrodes between children and adolescents with first-episode schizophrenia (FES, n = 48), children and adolescents with psychosis risk syndrome (PRS, n = 24), and healthy controls (HC, n = 30). Receiver operating characteristic (ROC) analysis was used to test the ability of P300 amplitude to distinguish FES, PRS and HC individuals.

RESULTS

The P300 amplitude in the FES group were significantly lower than those in the HC at the Cz, Pz, and Oz electrodes. The P300 amplitude was also significantly lower in the prodromal group than in the HC at the Pz and Oz electrodes. ROC curve analysis showed that at the Pz electrode, the P300 amplitude evoked by the target and standard stimulus showed high sensitivity, specificity, accuracy, and area under the curve value for distinguishing FES from HC individuals.

CONCLUSIONS

This study found early visual P300 deficits in children and adolescents with FES and PRS, with the exclusion of possible influence of medication and chronic medical conditions, suggesting the value of P300 amplitude for the identification of early psychosis.

Magnetic resonance advanced imaging analysis in adolescents: cortical thickness study to identify attenuated psychosis syndrome

PURPOSE

Psychosis is a symptom common to several mental illnesses and a defining feature of schizophrenia spectrum disorders, whose onset typically occurs in adolescence. Neuroradiological studies have reported evidence of brain structural abnormalities in patients with overt psychosis. However, early identification of brain structural changes in young subjects at risk for developing psychosis (such as those with Attenuated Psychosis Syndrome -APS) is currently lacking.

METHODS

Brain 3D T1-weighted and 64 directions diffusion-weighted images were acquired on 55 help-seeking adolescents (12-17 years old) with psychiatric disorders who referred to our Institute. Patients were divided into three groups: non-APS (n = 20), APS (n = 20), and Early-Onset Psychosis (n = 15). Cortical thickness was calculated from T1w images, and Tract-Based Spatial Statistics analysis was performed to study the distribution of white matter fractional anisotropy and all diffusivity metrics. A thorough neuropsychological test battery was adopted to investigate cognitive performance in several domains.

RESULTS

In patients with Attenuated Psychotic Syndrome, the left superior frontal gyrus was significantly thinner compared to patients with non-APS (p = 0.048), and their right medial orbitofrontal cortex thickness was associated with lower working memory scores (p = 0.0025, r = -0.668 for the working memory index and p = 0.001, r = -0.738 for the digit span). Early-Onset Psychosis patients showed thinner left pars triangularis compared to non-APS individuals (p = 0.024), and their left pars orbitalis was associated with impaired performance at the symbol search test (p = 0.005, r = -0.726). No differences in diffusivity along main tracts were found between sub-groups (p > 0.05).

CONCLUSION

This study showed specific associations between structural imaging features and cognitive performance in patients with APS. Characterizing this disorder using neuroimaging could reveal useful information that may aid in the development and evaluation of preventive strategies in these individuals.

Development and validation of a scale of self-alienation-related attributes for the early diagnosis of schizophrenia

BACKGROUND

The onset of schizophrenia is often preceded by a prodromal phase. However, it is difficult to predict the future transition to schizophrenia from the prodromal symptoms. Based on the diagnostic significance of Schneider's first rank symptoms (FRS), especially those representing "ego disorders (Ichstörungen)", we developed a scale of self-alienation-related attributes (Self-A) to assess the psychological characteristics associated with ego disorders for the early diagnosis of schizophrenia.

METHODS

In total, 153 schizophrenia (Sz) patients, 83 at-risk mental state (ARMS) subjects, and 154 healthy control (HC) subjects participated in this study. The Self-A scale was constructed by items from the Minnesota Multiphasic Personality Inventory (MMPI) based on the differences between schizophrenia patients with and without FRS representing ego-disorders designated as "self-alienation symptoms". The Self-A scale was tested for its reliability and validity in a different sample of schizophrenia patients, and was then applied to different cohorts including first-episode schizophrenia (FES) patients, ARMS individuals, and HC subjects.

RESULTS

The Self-A consisting of 27 items exhibited good internal consistency reliability. The validity was well demonstrated by the high correlation of the Self-A scores with the self-alienation symptom scores. The ARMS and FES groups had higher Self-A scores than the HC group. The Self-A score in the ARMS individuals who later developed schizophrenia was higher than that in the ARMS subjects who did not, and was comparable with that in the FES group.

CONCLUSIONS

This study suggests that the newly developed Self-A scale assessing the self-alienation-related attributes can improve the early diagnosis of schizophrenia.

White matter microstructure in youth at risk for serious mental illness: A comparative analysis

Identifying biomarkers of serious mental illness, such as altered white matter microstructure, can aid in early diagnosis and treatment. White matter microstructure was assessed using constrained spherical deconvolution of diffusion imaging data in a sample of 219 youth (age 12-25 years, 64.84% female) across 8 sites. Participants were classified as healthy controls (HC; n = 47), familial risk for serious mental illness (n = 31), mild-symptoms (n = 37), attenuated syndromes (n = 66), or discrete disorder (n = 38) based on clinical assessments. Fractional anisotropy (FA) and mean diffusivity (MD) values were derived for the whole brain white matter, forceps minor, anterior cingulate, anterior thalamic radiations (ATR), inferior fronto-occipital fasciculus, superior longitudinal fasciculus (SLF), and uncinate fasciculus (UF). Linear mixed effects models showed a significant effect of age on MD of the left ATR, left SLF, and left UF, and a significant effect of group on FA for all tracts examined. For most tracts, the discrete disorder group had significantly lower FA than other groups, and the attenuated syndromes group had higher FA compared to HC, with few differences between the remaining groups. White matter differences in MDD are most evident in individuals following illness onset, as few significant differences were observed in the risk phase.

Prolonged P300 Latency in Antipsychotic-Free Subjects with At-Risk Mental States Who Later Developed Schizophrenia

We measured P300, an event-related potential, in subjects with at-risk mental states (ARMS) and aimed to determine whether P300 parameter can predict progression to overt schizophrenia. Thirty-three subjects with ARMS, 39 with schizophrenia, and 28 healthy controls participated in the study. All subjects were antipsychotic-free. Subjects with ARMS were followed-up for more than two years. Cognitive function was measured by the Brief assessment of Cognition in Schizophrenia (BACS) and Schizophrenia Cognition Rating Scale (SCoRS), while the modified Global Assessment of Functioning (mGAF) was used to assess global function. Patients with schizophrenia showed smaller P300 amplitudes and prolonged latency at Pz compared to those of healthy controls and subjects with ARMS. During the follow-up period, eight out of 33 subjects with ARMS developed overt psychosis (ARMS-P) while 25 did not (ARMS-NP). P300 latency of ARMS-P was significantly longer than that of ARMS-NP. At baseline, ARMS-P elicited worse cognitive functions, as measured by the BACS and SCoRS compared to ARMS-NP. We also detected a significant relationship between P300 amplitudes and mGAF scores in ARMS subjects. Our results suggest the usefulness of prolonged P300 latency and cognitive impairment as a predictive marker of later development of schizophrenia in vulnerable individuals.

Neuroimaging Markers of Resiliency in Youth at Clinical High Risk for Psychosis: A Qualitative Review

Psychotic disorders are highly debilitating and constitute a major public health burden. Identifying markers of psychosis risk and resilience is a necessary step toward understanding etiology and informing prevention and treatment efforts in individuals at clinical high risk (CHR) for psychosis. In this context, it is important to consider that neural risk markers have been particularly useful in identifying mechanistic determinants along with predicting clinical outcomes. Notably, despite a growing body of supportive literature and the promise of recent findings identifying potential neural markers, the current work on CHR resilience markers has received little attention. The present review provides a brief overview of brain-based risk markers with a focus on predicting symptom course. Next, the review turns to protective markers, examining research from nonpsychiatric and schizophrenia fields to build an understanding of framing, priorities, and potential, applying these ideas to contextualizing a small but informative body of resiliency-relevant CHR research. Four domains (neurocognition, emotion regulation, allostatic load, and sensory and sensorimotor function) were identified and are discussed in terms of behavioral and neural markers. Taken together, the literature suggests significant predictive value for brain-based markers for individuals at CHR for psychosis, and the limited but compelling resiliency work highlights the critical importance of expanding this promising area of inquiry.

Forecasting Remission From the Psychosis Risk Syndrome With Mismatch Negativity and P300: Potentials and Pitfalls

Clinical outcomes vary for individuals at clinical high risk (CHR) for psychosis, ranging from conversion to a psychotic disorder to full remission from the risk syndrome. Given that most CHR individuals do not convert to psychosis, recent research efforts have turned toward identifying specific predictors of CHR remission, a task that is conceptually and empirically dissociable from the identification of predictors of conversion to psychosis, and one that may reveal specific biological characteristics that confer resilience to psychosis and provide further insights into the mechanisms associated with the pathogenesis of schizophrenia and those underlying a transient CHR syndrome. Such biomarkers may ultimately facilitate the development of novel early interventions and support the optimization of individualized care. In this review, we focus on two event-related brain potential measures, mismatch negativity and P300, that have attracted interest as predictors of future psychosis among CHR individuals. We describe several recent studies examining whether mismatch negativity and P300 predict subsequent CHR remission and suggest that intact mismatch negativity and P300 may reflect the integrity of specific neurocognitive processes that confer resilience against the persistence of the CHR syndrome and its associated risk for future transition to psychosis. We also highlight several major methodological concerns associated with these studies that apply to the broader literature examining predictors of CHR remission. Among them is the concern that studies that predict dichotomous remission versus nonremission and/or dichotomous conversion versus nonconversion outcomes potentially confound remission and conversion effects, a phenomenon we demonstrate with a data simulation.

Identification of Children at Risk of Schizophrenia via Deep Learning and EEG Responses

The prospective identification of children likely to develop schizophrenia is a vital tool to support early interventions that can mitigate the risk of progression to clinical psychosis. Electroencephalographic (EEG) patterns from brain activity and deep learning techniques are valuable resources in achieving this identification. We propose automated techniques that can process raw EEG waveforms to identify children who may have an increased risk of schizophrenia compared to typically developing children. We also analyse abnormal features that remain during developmental follow-up over a period of   ∼ 4 years in children with a vulnerability to schizophrenia initially assessed when aged 9 to 12 years. EEG data from participants were captured during the recording of a passive auditory oddball paradigm. We undertake a holistic study to identify brain abnormalities, first by exploring traditional machine learning algorithms using classification methods applied to hand-engineered features (event-related potential components). Then, we compare the performance of these methods with end-to-end deep learning techniques applied to raw data. We demonstrate via average cross-validation performance measures that recurrent deep convolutional neural networks can outperform traditional machine learning methods for sequence modeling. We illustrate the intuitive salient information of the model with the location of the most relevant attributes of a post-stimulus window. This baseline identification system in the area of mental illness supports the evidence of developmental and disease effects in a pre-prodromal phase of psychosis. These results reinforce the benefits of deep learning to support psychiatric classification and neuroscientific research more broadly.

White Matter Connectivity in Youth at Risk for Serious Mental Illness: A Longitudinal Analysis

Longitudinal changes in white matter connectivity were assessed in a sample of youth at-risk for serious mental illness (n=183; age 12-25). Diffusion tensor imaging (DTI) was acquired at baseline and 12 months from youth recruited across two sites and classified as healthy controls (n=36), familial risk (n=30), mild-symptoms (n=41), attenuated syndromes (n=70), or transition (n=9) based on clinical assessments. Fractional anisotropy (FA) and mean diffusivity (MD) values were derived for the whole brain white matter, forceps minor, anterior cingulate, anterior thalamic radiations, inferior fronto-occipital fasciculus, superior longitudinal fasciculus, and uncinate fasciculus. MANCOVA analysis controlling for site, sex, and age showed no significant group differences in FA and MD at baseline or at 12 months. Linear mixed effects analysis showed a significant effect for time for most white matter tracts, but no effect for group, or group by time interaction. Transdiagnostic risk groups have similar profiles of WM connectivity and similar rates of change over time.

Defining Individual-Specific Functional Neuroanatomy for Precision Psychiatry

Studies comparing diverse groups have shown that many psychiatric diseases involve disruptions across distributed large-scale networks of the brain. There is hope that functional magnetic resonance imaging (fMRI) functional connectivity techniques will shed light on these disruptions, providing prognostic and diagnostic biomarkers as well as targets for therapeutic interventions. However, to date, progress on clinical translation of fMRI methods has been limited. Here, we argue that this limited translation is driven by a combination of intersubject heterogeneity and the relatively low reliability of standard fMRI techniques at the individual level. We review a potential solution to these limitations: the use of new "precision" fMRI approaches that shift the focus of analysis from groups to single individuals through the use of extended data acquisition strategies. We begin by discussing the potential advantages of fMRI functional connectivity methods for improving our understanding of functional neuroanatomy and disruptions in psychiatric disorders. We then discuss the budding field of precision fMRI and findings garnered from this work. We demonstrate that precision fMRI can improve the reliability of functional connectivity measures, while showing high stability and sensitivity to individual differences. We close by discussing the application of these approaches to clinical settings.

Meta-analysis of auditory P50 sensory gating in schizophrenia and bipolar disorder

The ability of the brain to reduce the amount of trivial or redundant sensory inputs is called gating function. Dysfunction of sensory gating may lead to cognitive fragmentation and poor real-world functioning. The auditory dual-click paradigm is a pertinent neurophysiological measure of sensory gating function. This meta-analysis aimed to examine the subcomponents of abnormal P50 waveforms in bipolar disorder and schizophrenia to assess P50 sensory gating deficits and examine effects of diagnoses, illness states (first-episode psychosis vs. schizophrenia, remission vs. episodes in bipolar disorder), and treatment status (medication-free vs. medicated). Literature search of PubMed between Jan 1st 1980 and March 31st 2019 identified 2091 records for schizophrenia, 362 for bipolar disorder. 115 studies in schizophrenia (4932 patients), 16 in bipolar disorder (975 patients) and 10 in first-degree relatives (848 subjects) met the inclusion criteria. P50 sensory gating ratio (S2/S1) and S1-S2 difference were significantly altered in schizophrenia, bipolar disorder and their first-degree relatives. First-episode psychosis did not differ from schizophrenia, however episodes altered P50 sensory gating in bipolar disorder. Medications improve P50 sensory gating alterations in schizophrenia significantly and at trend level in bipolar disorder. Future studies should examine longitudinal course of P50 sensory gating in schizophrenia and bipolar disorder.