Cortical and Subcortical Brain Alterations in Specific Phobia and Its Animal and Blood-Injection-Injury Subtypes: A Mega-Analysis From the ENIGMA Anxiety Working Group.

OBJECTIVE: Specific phobia is a common anxiety disorder, but the literature on associated brain structure alterations exhibits substantial gaps. The ENIGMA Anxiety Working Group examined brain structure differences between individuals with specific phobias and healthy control subjects as well as between the animal and blood-injection-injury (BII) subtypes of specific phobia. Additionally, the authors investigated associations of brain structure with symptom severity and age (youths vs. adults). METHODS: Data sets from 31 original studies were combined to create a final sample with 1,452 participants with phobia and 2,991 healthy participants (62.7% female; ages 5-90). Imaging processing and quality control were performed using established ENIGMA protocols. Subcortical volumes as well as cortical surface area and thickness were examined in a preregistered analysis. RESULTS: Compared with the healthy control group, the phobia group showed mostly smaller subcortical volumes, mixed surface differences, and larger cortical thickness across a substantial number of regions. The phobia subgroups also showed differences, including, as hypothesized, larger medial orbitofrontal cortex thickness in BII phobia (N=182) compared with animal phobia (N=739). All findings were driven by adult participants; no significant results were observed in children and adolescents. CONCLUSIONS: Brain alterations associated with specific phobia exceeded those of other anxiety disorders in comparable analyses in extent and effect size and were not limited to reductions in brain structure. Moreover, phenomenological differences between phobia subgroups were reflected in diverging neural underpinnings, including brain areas related to fear processing and higher cognitive processes. The findings implicate brain structure alterations in specific phobia, although subcortical alterations in particular may also relate to broader internalizing psychopathology.

Current and Future Approaches to Pediatric Anxiety Disorder Treatment.

This overview critically appraises the literature on the treatment of pediatric anxiety disorders. The two established treatments for these conditions comprise cognitive-behavioral therapy (CBT) and antidepressant medications. Many youths receiving these treatments fail to achieve remission, which creates a need for new treatments. After summarizing the literature on CBT and currently available medications, the authors describe research that lays a foundation for improvements in the treatment of pediatric anxiety disorders. This foundation leverages neuroscientific investigations, also described in the overview, which provide insights on mechanisms of successful treatment.

Brain Functional Connectivity and Anatomical Features as Predictors of Cognitive Behavioral Therapy Outcome for Anxiety in Youths.

Background: Because pediatric anxiety disorders precede the onset of many other problems, successful prediction of response to the first-line treatment, cognitive-behavioral therapy (CBT), could have major impact. However, existing clinical models are weakly predictive. The current study evaluates whether structural and resting-state functional magnetic resonance imaging can predict post-CBT anxiety symptoms. Methods: Two datasets were studied: (A) one consisted of n=54 subjects with an anxiety diagnosis, who received 12 weeks of CBT, and (B) one consisted of n=15 subjects treated for 8 weeks. Connectome Predictive Modeling (CPM) was used to predict treatment response, as assessed with the PARS; additionally we investigated models using anatomical features, instead of functional connectivity. The main analysis included network edges positively correlated with treatment outcome, and age, sex, and baseline anxiety severity as predictors. Results from alternative models and analyses also are presented. Model assessments utilized 1000 bootstraps, resulting in a 95% CI for R2, r and mean absolute error (MAE). Outcomes: The main model showed a mean absolute error of approximately 3.5 (95%CI: [3.1-3.8]) points a R2 of 0.08 [-0.14 - 0.26] and r of 0.38 [0.24 - 0.511]. When testing this model in the left-out sample (B) the results were similar, with a MAE of 3.4 [2.8 - 4.7], R2-0.65 [-2.29 - 0.16] and r of 0.4 [0.24 - 0.54]. The anatomical metrics showed a similar pattern, where models rendered overall low R2. Interpretation: The analysis showed that models based on earlier promising results failed to predict clinical outcomes. Despite the small sample size, the current study does not support extensive use of CPM to predict outcome in pediatric anxiety.

A systematic review and meta-analysis of resting-state fMRI in anxiety disorders: Need for data sharing to move the field forward.

Anxiety disorders are among the most prevalent psychiatric disorders. Neuroimaging findings remain uncertain, and resting state functional magnetic resonance (rs-fMRI) connectivity is of particular interest since it is a scalable functional imaging modality. Given heterogeneous past findings for rs-fMRI in anxious individuals, we characterize patterns across anxiety disorders by conducting a systematic review and meta-analysis. Studies were included if they contained at the time of scanning both a healthy group and a patient group. Due to insufficient study numbers, the quantitative meta-analysis only included seed-based studies. We performed an activation likelihood estimation (ALE) analysis that compared patients and healthy volunteers. All analyses were corrected for family-wise error with a cluster-level threshold of p < .05. Patients exhibited hypo-connectivity between the amygdala and the medial frontal gyrus, anterior cingulate cortex, and cingulate gyrus. This finding, however, was not robust to potential file-drawer effects. Though limited by strict inclusion criteria, our results highlight the heterogeneous nature of reported findings. This underscores the need for data sharing when attempting to detect reliable patterns of disruption in brain activity across anxiety disorders.

The association between duration of breastfeeding and the trajectory of brain development from childhood to young adulthood: an 8-year longitudinal study.

Breastfeeding has been associated with several short- and long-term health benefits, including positive cognitive and behavioral outcomes. However, the impact of breastfeeding on structural brain development over time remains unclear. We aimed to assess the association between breastfeeding duration in childhood and the developmental trajectory of overall cortical thickness, cortical area, and total intracranial volume during the transition from childhood to early adulthood. Participants included 670 children and adolescents with 1326 MRI scans acquired over 8 years from the Brazilian High-Risk Cohort for Mental Conditions (BHRCS). Breastfeeding was assessed using a questionnaire answered by the parents. Brain measures were estimated using MRI T1-weighted images at three time points, with 3-year intervals. Data were evaluated using generalized additive models adjusted for multiple confounders. We found that a longer breastfeeding duration was directly associated with higher global cortical thickness in the left (edf = 1.0, F = 6.07, p = 0.01) and right (edf = 1.0, F = 4.70, p = 0.03) hemispheres. For the total intracranial volume, we found an interaction between duration of breastfeeding and developmental stage (edf = 1.0, F = 6.81, p = 0.009). No association was found between breastfeeding duration and brain area. Our study suggests that the duration of breastfeeding impacts overall cortical thickness and the development of total brain volume, but not area. This study adds to the evidence on the potential impact of breastfeeding on brain development and provides relevant insights into the mechanisms by which breastfeeding might confer cognitive and mental health benefits.

Country-level gender inequality is associated with structural differences in the brains of women and men.

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.

Deviations from a typical development of the cerebellum in youth are associated with psychopathology, executive functions and educational outcomes.

BACKGROUND: Understanding deviations from typical brain development is a promising approach to comprehend pathophysiology in childhood and adolescence. We investigated if cerebellar volumes different than expected for age and sex could predict psychopathology, executive functions and academic achievement. METHODS: Children and adolescents aged 6-17 years from the Brazilian High-Risk Cohort Study for Mental Conditions had their cerebellar volume estimated using Multiple Automatically Generated Templates from T1-weighted images at baseline (n = 677) and at 3-year follow-up (n = 447). Outcomes were assessed using the Child Behavior Checklist and standardized measures of executive functions and school achievement. Models of typically developing cerebellum were based on a subsample not exposed to risk factors and without mental-health conditions (n = 216). Deviations from this model were constructed for the remaining individuals (n = 461) and standardized variation from age and sex trajectory model was used to predict outcomes in cross-sectional, longitudinal and mediation analyses. RESULTS: Cerebellar volumes higher than expected for age and sex were associated with lower externalizing specific factor and higher executive functions. In a longitudinal analysis, deviations from typical development at baseline predicted inhibitory control at follow-up, and cerebellar deviation changes from baseline to follow-up predicted changes in reading and writing abilities. The association between deviations in cerebellar volume and academic achievement was mediated by inhibitory control. CONCLUSIONS: Deviations in the cerebellar typical development are associated with outcomes in youth that have long-lasting consequences. This study highlights both the potential of typical developing models and the important role of the cerebellum in mental health, cognition and education.

Translating Big Data to Clinical Outcomes in Anxiety: Potential for Multimodal Integration.

PURPOSE OF THE REVIEW: This review describes approaches to research on anxiety that attempt to link neural correlates to treatment response and novel therapies. The review emphasizes pediatric anxiety disorders since most anxiety disorders begin before adulthood. RECENT FINDINGS: Recent literature illustrates how current treatments for anxiety manifest diverse relations with a range of neural markers. While some studies demonstrate post-treatment normalization of markers in anxious individuals, others find persistence of group differences. For other markers, which show no pretreatment association with anxiety, the markers nevertheless distinguish treatment-responders from non-responders. Heightened error related negativity represents the risk marker discussed in the most depth; however, limitations in measures related to error responding necessitate multimodal and big-data approaches. Single risk markers show limits as correlates of treatment response. Large-scale, multimodal data analyzed with predictive models may illuminate additional risk markers related to anxiety disorder treatment outcomes. Such work may identify novel targets and eventually guide improvements in treatment response/outcomes.

Structural Brain Correlates of Childhood Inhibited Temperament: An ENIGMA-Anxiety Mega-analysis.

Temperament involves stable behavioral and emotional tendencies that differ between individuals, which can be first observed in infancy or early childhood and relate to behavior in many contexts and over many years.1 One of the most rigorously characterized temperament classifications relates to the tendency of individuals to avoid the unfamiliar and to withdraw from unfamiliar people, objects, and unexpected events. This temperament is referred to as behavioral inhibition or inhibited temperament (IT).2 IT is a moderately heritable trait1 that can be measured in multiple species.3 In humans, levels of IT can be quantified from the first year of life through direct behavioral observations or reports by caregivers or teachers. Similar approaches as well as self-report questionnaires on current and/or retrospective levels of IT1 can be used later in life.

Mega-analysis methods in ENIGMA: The experience of the generalized anxiety disorder working group.

The ENIGMA group on Generalized Anxiety Disorder (ENIGMA-Anxiety/GAD) is part of a broader effort to investigate anxiety disorders using imaging and genetic data across multiple sites worldwide. The group is actively conducting a mega-analysis of a large number of brain structural scans. In this process, the group was confronted with many methodological challenges related to study planning and implementation, between-country transfer of subject-level data, quality control of a considerable amount of imaging data, and choices related to statistical methods and efficient use of resources. This report summarizes the background information and rationale for the various methodological decisions, as well as the approach taken to implement them. The goal is to document the approach and help guide other research groups working with large brain imaging data sets as they develop their own analytic pipelines for mega-analyses.

Recent advances in understanding neural correlates of anxiety disorders in children and adolescents.

PURPOSE OF REVIEW: Anxiety disorders are some of the most common psychiatric diagnoses in children and adolescents, but attempts to improve outcome prediction and treatment have stalled. This review highlights recent findings on neural indices related to fear and anxiety that provide novel directions for attempts to create such improvements. RECENT FINDINGS: Stimuli capable of provoking fear engage many brain regions, including the amygdala, medial prefrontal cortex, hippocampus, and bed nucleus of the stria terminalis. Studies in rodents suggest that sustained, low-level threats are particularly likely to engage the bed nucleus of the stria terminalis, which appears to malfunction in anxiety disorders. However, anxiety disorders, like most mental illnesses, appear less likely to arise from alterations in isolated brain regions than in distributed brain circuitry. Findings from large-scale studies of brain connectivity may reveal signs of such broadly distributed dysfunction, though available studies report small effect sizes. Finally, we review novel approaches with promise for using such large-scale data to detect clinically relevant, broadly distributed circuitry dysfunction. SUMMARY: Recent work maps neural circuitry related to fear and anxiety. This circuitry may malfunction in anxiety disorders. Integrating findings from animal studies, big datasets, and novel analytical approaches may generate clinically relevant insights based on this recent work.

Cortical surface abnormalities are different depending on the stage of schizophrenia: A cross-sectional vertexwise mega-analysis of thickness, area and gyrification.

BACKGROUND: Brain magnetic resonance imaging studies have not investigated the cortical surface comprehensively in schizophrenia subjects by assessing thickness, surface area and gyrification separately during the first-episode of psychosis (FEP) or chronic schizophrenia (ChSch). METHODS: We investigated cortical surface abnormalities in 137 FEP patients and 240 ChSch subjects compared to 297 Healthy Controls (HC) contributed by five cohorts. Maps showing results of vertexwise between-group comparisons of cortical thickness, area, and gyrification were produced using T1-weighted datasets processed using FreeSurfer 5.3, followed by validated quality control protocols. RESULTS: FEP subjects showed large clusters of increased area and gyrification relative to HC in prefrontal and insuli cortices (Cohen's d: 0.049 to 0.28). These between-group differences occurred partially beyond the effect of sample. ChSch subjects displayed reduced cortical thickness relative to HC in smaller fronto-temporal foci (d: -0.73 to -0.35), but not beyond the effect of sample. Differences between FEP and HC subjects were associated with male gender, younger age, and earlier illness onset, while differences between ChSch and HC were associated with treatment-resistance and first-generation antipsychotic (FGA) intake independently of sample effect. CONCLUSIONS: Separate assessments of FEP and ChSch revealed abnormalities that differed in regional distribution, phenotypes affected and effect size. In FEP, associations of greater cortical area and gyrification abnormalities with earlier age of onset suggest an origin on anomalous neurodevelopment, while thickness reductions in ChSch are at least partially explained by treatment-resistance and FGA intake. Associations of between-group differences with clinical variables retained statistical significance beyond the effect of sample.

Long-term stability of the cortical volumetric profile and the functional human connectome throughout childhood and adolescence.

There is compelling evidence showing that between-subject variability in several functional and structural brain features is sufficient for unique identification in adults. However, individuation of brain functional connectomes depends on the stabilization of neurodevelopmental processes during childhood and adolescence. Here, we aimed to (1) evaluate the intra-subject functional connectome stability over time for the whole brain and for large scale functional networks and (2) determine the long-term identification accuracy or 'fingerprinting' for the cortical volumetric profile and the functional connectome. For these purposes, we analysed a longitudinal cohort of 239 children and adolescents scanned in two sessions with an interval of approximately 3 years (age range 6-15 years at baseline and 9-18 years at follow-up). Corroborating previous results using short between-scan intervals in children and adolescents, we observed a moderate identification accuracy (38%) for the whole functional profile. In contrast, identification accuracy using cortical volumetric profile was 95%. Among the large-scale networks, the default-mode (26.8%), the frontoparietal (23.4%) and the dorsal-attention (27.6%) networks were the most discriminative. Our results provide further evidence for a protracted development of specific individual structural and functional connectivity profiles.

Obsessive-Compulsive Symptoms, Polygenic Risk Score, and Thalamic Development in Children From the Brazilian High-Risk Cohort for Mental Conditions (BHRCS).

Background: Thalamic volume measures have been linked to obsessive-compulsive disorder (OCD) in children and adolescents. However, it is unclear if alterations in thalamic volumes occur before or after symptom onset and if there is a relation to the presence of sub-clinical obsessive-compulsive symptoms (OCS). Here, we explore the relationship between OCS and the rate of thalamic volume change in a cohort of children and youth at high risk to develop a mental disorder. A secondary aim was to determine if there is a relationship between OCS and the individual's OCD polygenic risk score (OCD-PRS) and between the rate of thalamic volume change and the OCD-PRS. Methods: The sample included 378 children enrolled in the longitudinal Brazilian High-Risk Cohort for Mental Conditions. Participants were assessed for OCS and the symmetrized percent change (SPC) of thalamic volume across two time-points separated by 3 years, along with the OCD-PRS. Zero-altered negative binomial models were used to analyze the relationship between OCS and thalamic SPC. Multiple linear regressions were used to examine the relationship between thalamic SPC and OCD-PRS. Results: A significant relationship between OCS and the right thalamus SPC (p = 0.042) was found. There was no significant relationship between changes in thalamic volume SPC and OCD-PRS. Conclusions: The findings suggest that changes in the right thalamic volume over the course of 3 years in children may be associated to OCS. Future studies are needed to confirm these results and further characterize the specific nature of OCS symptoms associated with thalamic volumes.

Is treatment-resistant schizophrenia associated with distinct neurobiological callosal connectivity abnormalities?

BACKGROUND: Resistance to antipsychotic treatment affects up to 30% of patients with schizophrenia. Although the time course of development of treatment-resistant schizophrenia (TRS) varies from patient to patient, the reasons for these variations remain unknown. Growing evidence suggests brain dysconnectivity as a significant feature of schizophrenia. In this study, we compared fractional anisotropy (FA) of brain white matter between TRS and non-treatment-resistant schizophrenia (non-TRS) patients. Our central hypothesis was that TRS is associated with reduced FA values. METHODS: TRS was defined as the persistence of moderate to severe symptoms after adequate treatment with at least two antipsychotics from different classes. Diffusion-tensor brain MRI obtained images from 34 TRS participants and 51 non-TRS. Whole-brain analysis of FA and axial, radial, and mean diffusivity were performed using Tract-Based Spatial Statistics (TBSS) and FMRIB's Software Library (FSL), yielding a contrast between TRS and non-TRS patients, corrected for multiple comparisons using family-wise error (FWE) < 0.05. RESULTS: We found a significant reduction in FA in the splenium of corpus callosum (CC) in TRS when compared to non-TRS. The antipsychotic dose did not relate to the splenium CC. CONCLUSION: Our results suggest that the focal abnormality of CC may be a potential biomarker of TRS.

Structural brain abnormalities in schizophrenia in adverse environments: examining the effect of poverty and violence in six Latin American cities.

BACKGROUND: Social and environmental factors such as poverty or violence modulate the risk and course of schizophrenia. However, how they affect the brain in patients with psychosis remains unclear. AIMS: We studied how environmental factors are related to brain structure in patients with schizophrenia and controls in Latin America, where these factors are large and unequally distributed. METHOD: This is a multicentre study of magnetic resonance imaging in patients with schizophrenia and controls from six Latin American cities. Total and voxel-level grey matter volumes, and their relationship with neighbourhood characteristics such as average income and homicide rates, were analysed with a general linear model. RESULTS: A total of 334 patients with schizophrenia and 262 controls were included. Income was differentially related to total grey matter volume in both groups (P = 0.006). Controls showed a positive correlation between total grey matter volume and income (R = 0.14, P = 0.02). Surprisingly, this relationship was not present in patients with schizophrenia (R = -0.076, P = 0.17). Voxel-level analysis confirmed that this interaction was widespread across the cortex. After adjusting for global brain changes, income was positively related to prefrontal cortex volumes only in controls. Conversely, the hippocampus in patients with schizophrenia, but not in controls, was relatively larger in affluent environments. There was no significant correlation between environmental violence and brain structure. CONCLUSIONS: Our results highlight the interplay between environment, particularly poverty, and individual characteristics in psychosis. This is particularly important for harsh environments such as low- and middle-income countries, where potentially less brain vulnerability (less grey matter loss) is sufficient to become unwell in adverse (poor) environments.

Testing the Stability and Validity of an Executive Dysfunction Classification Using Task-Based Assessment in Children and Adolescents.

OBJECTIVE: It is unclear if pediatric executive dysfunction assessed only with cognitive tasks predicts clinically relevant outcomes independently of psychiatric diagnoses. This study tested the stability and validity of a task-based classification of executive function. METHOD: A total of 2,207 individuals (6-17 years old) from the Brazilian High-Risk Cohort Study participated in this study (1,930 at baseline, 1,532 at follow-up). Executive function was measured using tests of working memory and inhibitory control. Dichotomized age- and sex-standardized performances were used as input in latent class analysis and receiver operating curves to create an executive dysfunction classification (EDC). The study tested EDC's stability over time, association with symptoms, functional impairment, a polymorphism in the CADM2 gene, polygenic risk scores (PRS), and brain structure. Analyses covaried for age, sex, social class, IQ, and psychiatric diagnoses. RESULTS: EDC at baseline predicted itself at follow-up (odds ratio [OR] = 5.11; 95% CI 3.41-7.64). Participants in the EDC reported symptoms spanning several domains of psychopathology and exhibited impairment in multiple settings, including more adverse school events (OR = 2.530; 95% CI 1.838-3.483). Children in the EDC presented higher attention-deficit/hyperactivity disorder and lower educational attainment PRS at baseline; higher schizophrenia PRS at follow-up; and lower chances of presenting a polymorphism in a gene previously linked to high performance in executive function (CADM2 gene). They also exhibited smaller intracranial volumes and smaller bilateral cortical surface areas in several brain regions. CONCLUSION: Task-based executive dysfunction is associated with several validators, independently of psychiatric diagnoses and intelligence. Further refinement of task-based assessments might generate clinically useful tools.

Neuroimaging Association Scores: reliability and validity of aggregate measures of brain structural features linked to mental disorders in youth.

In genetics, aggregation of many loci with small effect sizes into a single score improved prediction. Nevertheless, studies applying easily replicable weighted scores to neuroimaging data are lacking. Our aim was to assess the reliability and validity of the Neuroimaging Association Score (NAS), which combines information from structural brain features previously linked to mental disorders. Participants were 726 youth (aged 6-14) from two cities in Brazil who underwent MRI and psychopathology assessment at baseline and 387 at 3-year follow-up. Results were replicated in two samples: IMAGEN (n = 1627) and the Healthy Brain Network (n = 843). NAS were derived by summing the product of each standardized brain feature by the effect size of the association of that brain feature with seven psychiatric disorders documented by previous meta-analyses. NAS were calculated for surface area, cortical thickness and subcortical volumes using T1-weighted scans. NAS reliability, temporal stability and psychopathology and cognition prediction were analyzed. NAS for surface area showed high internal consistency and 3-year stability and predicted general psychopathology and cognition with higher replicability than specific symptomatic domains for all samples. They also predicted general psychopathology with higher replicability than single structures alone, accounting for 1-3% of the variance, but without directionality. The NAS for cortical thickness and subcortical volumes showed lower internal consistency and less replicable associations with behavioural phenotypes. These findings indicate the NAS based on surface area might be replicable markers of general psychopathology, but these links are unlikely to be causal or clinically useful yet.

Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation

Objective: Obstacles for computational tools in psychiatry include gathering robust evidence and keeping implementation costs reasonable. We report a systematic review of automated speech evaluation for the psychosis spectrum and analyze the value of information for a screening program in a healthcare system with a limited number of psychiatrists (Maputo, Mozambique). Methods: Original studies on speech analysis for forecasting of conversion in individuals at clinical high risk (CHR) for psychosis, diagnosis of manifested psychotic disorder, and first-episode psychosis (FEP) were included in this review. Studies addressing non-verbal components of speech (e.g., pitch, tone) were excluded. Results: Of 168 works identified, 28 original studies were included. Valuable speech features included direct measures (e.g., relative word counting) and mathematical embeddings (e.g.: word-to-vector, graphs). Accuracy estimates reported for schizophrenia diagnosis and CHR conversion ranged from 71 to 100% across studies. Studies used structured interviews, directed tasks, or prompted free speech. Directed-task protocols were faster while seemingly maintaining performance. The expected value of perfect information is USD 9.34 million. Imperfect tests would nevertheless yield high value. Conclusion: Accuracy for screening and diagnosis was high. Larger studies are needed to enhance precision of classificatory estimates. Automated analysis presents itself as a feasible, low-cost method which should be especially useful for regions in which the physician pool is insufficient to meet demand.

Lowering costs for large-scale screening in psychosis: a systematic review and meta-analysis of performance and value of information for speech-based psychiatric evaluation.

OBJECTIVE: Obstacles for computational tools in psychiatry include gathering robust evidence and keeping implementation costs reasonable. We report a systematic review of automated speech evaluation for the psychosis spectrum and analyze the value of information for a screening program in a healthcare system with a limited number of psychiatrists (Maputo, Mozambique). METHODS: Original studies on speech analysis for forecasting of conversion in individuals at clinical high risk (CHR) for psychosis, diagnosis of manifested psychotic disorder, and first-episode psychosis (FEP) were included in this review. Studies addressing non-verbal components of speech (e.g., pitch, tone) were excluded. RESULTS: Of 168 works identified, 28 original studies were included. Valuable speech features included direct measures (e.g., relative word counting) and mathematical embeddings (e.g.: word-to-vector, graphs). Accuracy estimates reported for schizophrenia diagnosis and CHR conversion ranged from 71 to 100% across studies. Studies used structured interviews, directed tasks, or prompted free speech. Directed-task protocols were faster while seemingly maintaining performance. The expected value of perfect information is USD 9.34 million. Imperfect tests would nevertheless yield high value. CONCLUSION: Accuracy for screening and diagnosis was high. Larger studies are needed to enhance precision of classificatory estimates. Automated analysis presents itself as a feasible, low-cost method which should be especially useful for regions in which the physician pool is insufficient to meet demand.