Lost in translation? Deciphering the role of language differences in the excess risk of psychosis among migrant groups.

BACKGROUND: Migration is a well-established risk factor for psychotic disorders, and migrant language has been proposed as a novel factor that may improve our understanding of this relationship. Our objective was to explore the association between indicators of linguistic distance and the risk of psychotic disorders among first-generation migrant groups. METHODS: Using linked health administrative data, we constructed a retrospective cohort of first-generation migrants to Ontario over a 20-year period (1992-2011). Linguistic distance of the first language was categorized using several approaches, including language family classifications, estimated acquisition time, syntax-based distance scores, and lexical-based distance scores. Incident cases of non-affective psychotic disorder were identified over a 5- to 25-year period. We used Poisson regression to estimate incidence rate ratios (IRR) for each language variable, after adjustment for knowledge of English at arrival and other factors. RESULTS: Our cohort included 1 863 803 first-generation migrants. Migrants whose first language was in a different language family than English had higher rates of psychotic disorders (IRR = 1.08, 95% CI 1.01-1.16), relative to those whose first language was English. Similarly, migrants in the highest quintile of linguistic distance based on lexical similarity had an elevated risk of psychotic disorder (IRR = 1.15, 95% CI 1.06-1.24). Adjustment for knowledge of English at arrival had minimal effect on observed estimates. CONCLUSION: We found some evidence that linguistic factors that impair comprehension may play a role in the excess risk of psychosis among migrant groups; however, the magnitude of effect is small and unlikely to fully explain the elevated rates of psychotic disorder across migrant groups.

Neuromelanin levels in individuals with substance use disorders: A systematic review and meta-analysis.

Dopamine's role in addiction has been extensively studied, revealing disruptions in its functioning throughout all addiction stages. Neuromelanin in the substantia nigra (SN) may reflect dopamine auto-oxidation, and can be quantified using neuromelaninsensitive magnetic resonance imaging (neuromelanin-MRI) in a non-invasive manner.In this pre-registered systematic review, we assess the current body of evidence related to neuromelanin levels in substance use disorders, using both post-mortem and MRI examinations. The systematic search identified 10 relevant articles, primarily focusing on the substantia nigra. An early-stage meta-analysis (n = 6) revealed varied observations ranging from standardized mean differences of -3.55 to +0.62, with a pooled estimate of -0.44 (95 % CI = -1.52, 0.65), but there was insufficient power to detect differences in neuromelanin content among individuals with substance use disorders. Our gap analysis highlights the lack of sufficient replication studies, with existing studies lacking the power to detect a true difference, and a complete lack of neuromelanin studies on certain substances of clinical interest. We provide recommendations for future studies of dopaminergic neurobiology in addictions and related psychiatric comorbidities.

Speech based natural language profile before, during and after the onset of psychosis: A cluster analysis.

BACKGROUND AND HYPOTHESIS: Speech markers are digitally acquired, computationally derived, quantifiable set of measures that reflect the state of neurocognitive processes relevant for social functioning. "Oddities" in language and communication have historically been seen as a core feature of schizophrenia. The application of natural language processing (NLP) to speech samples can elucidate even the most subtle deviations in language. We aim to determine if NLP based profiles that are distinctive of schizophrenia can be observed across the various clinical phases of psychosis. DESIGN: Our sample consisted of 147 participants and included 39 healthy controls (HC), 72 with first-episode psychosis (FEP), 18 in a clinical high-risk state (CHR), 18 with schizophrenia (SZ). A structured task elicited 3 minutes of speech, which was then transformed into quantitative measures on 12 linguistic variables (lexical, syntactic, and semantic). Cluster analysis that leveraged healthy variations was then applied to determine language-based subgroups. RESULTS: We observed a three-cluster solution. The largest cluster included most HC and the majority of patients, indicating a 'typical linguistic profile (TLP)'. One of the atypical clusters had notably high semantic similarity in word choices with less perceptual words, lower cohesion and analytical structure; this cluster was almost entirely composed of patients in early stages of psychosis (EPP - early phase profile). The second atypical cluster had more patients with established schizophrenia (SPP - stable phase profile), with more perceptual but less cognitive/emotional word classes, simpler syntactic structure, and a lack of sufficient reference to prior information (reduced givenness). CONCLUSION: The patterns of speech deviations in early and established stages of schizophrenia are distinguishable from each other and detectable when lexical, semantic and syntactic aspects are assessed in the pursuit of 'formal thought disorder'.

Multimodal workflows optimally predict response to repetitive transcranial magnetic stimulation in patients with schizophrenia: a multisite machine learning analysis.

The response variability to repetitive transcranial magnetic stimulation (rTMS) challenges the effective use of this treatment option in patients with schizophrenia. This variability may be deciphered by leveraging predictive information in structural MRI, clinical, sociodemographic, and genetic data using artificial intelligence. We developed and cross-validated rTMS response prediction models in patients with schizophrenia drawn from the multisite RESIS trial. The models incorporated pre-treatment sMRI, clinical, sociodemographic, and polygenic risk score (PRS) data. Patients were randomly assigned to receive active (N = 45) or sham (N = 47) rTMS treatment. The prediction target was individual response, defined as ≥20% reduction in pre-treatment negative symptom sum scores of the Positive and Negative Syndrome Scale. Our multimodal sequential prediction workflow achieved a balanced accuracy (BAC) of 94% (non-responders: 92%, responders: 95%) in the active-treated group and 50% in the sham-treated group. The clinical, clinical + PRS, and sMRI-based classifiers yielded BACs of 65%, 76%, and 80%, respectively. Apparent sadness, inability to feel, educational attainment PRS, and unemployment were most predictive of non-response in the clinical + PRS model, while grey matter density reductions in the default mode, limbic networks, and the cerebellum were most predictive in the sMRI model. Our sequential modelling approach provided superior predictive performance while minimising the diagnostic burden in the clinical setting. Predictive patterns suggest that rTMS responders may have higher levels of brain grey matter in the default mode and salience networks which increases their likelihood of profiting from plasticity-inducing brain stimulation methods, such as rTMS. The future clinical implementation of our models requires findings to be replicated at the international scale using stratified clinical trial designs.

Antecedents of major depressive, bipolar, and psychotic disorders: A systematic review and meta-analysis of prospective studies.

Major depressive, bipolar, or psychotic disorders are preceded by earlier manifestations in behaviours and experiences. We present a synthesis of evidence on associations between person-level antecedents (behaviour, performance, psychopathology) in childhood, adolescence, or early adulthood and later onsets of major depressive disorder, bipolar disorder, or psychotic disorder based on prospective studies published up to September 16, 2022. We screened 11,342 records, identified 460 eligible publications, and extracted 570 risk ratios quantifying the relationships between 52 antecedents and onsets in 198 unique samples with prospective follow-up of 122,766 individuals from a mean age of 12.4 to a mean age of 24.8 for 1522,426 person years of follow-up. We completed meta-analyses of 12 antecedents with adequate data. Psychotic symptoms, depressive symptoms, anxiety, disruptive behaviors, affective lability, and sleep problems were transdiagnostic antecedents associated with onsets of depressive, bipolar, and psychotic disorders. Attention-deficit/hyperactivity and hypomanic symptoms specifically predicted bipolar disorder. While transdiagnostic and diagnosis-specific antecedents inform targeted prevention and help understand pathogenic mechanisms, extensive gaps in evidence indicate potential for improving early risk identification.

Speech markers to predict and prevent recurrent episodes of psychosis: A narrative overview and emerging opportunities.

Preventing relapse in schizophrenia improves long-term health outcomes. Repeated episodes of psychotic symptoms shape the trajectory of this illness and can be a detriment to functional recovery. Despite early intervention programs, high relapse rates persist, calling for alternative approaches in relapse prevention. Predicting imminent relapse at an individual level is critical for effective intervention. While clinical profiles are often used to foresee relapse, they lack the specificity and sensitivity needed for timely prediction. Here, we review the use of speech through Natural Language Processing (NLP) to predict a recurrent psychotic episode. Recent advancements in NLP of speech have shown the ability to detect linguistic markers related to thought disorder and other language disruptions within 2-4 weeks preceding a relapse. This approach has shown to be able to capture individual speech patterns, showing promise in its use as a prediction tool. We outline current developments in remote monitoring for psychotic relapses, discuss the challenges and limitations and present the speech-NLP based approach as an alternative to detect relapses with sufficient accuracy, construct validity and lead time to generate clinical actions towards prevention.

Epigenetic profile of the immune system associated with symptom severity and treatment response in schizophrenia.

BACKGROUND: Environmental modification of genetic information (epigenetics) is often invoked to explain interindividual differences in the phenotype of schizophrenia. In clinical practice, such variability is most prominent in the symptom profile and the treatment response. Epigenetic regulation of immune function is of particular interest, given the therapeutic relevance of this mechanism in schizophrenia. METHODS: We analyzed the DNA methylation data of immune-relevant genes in patients with schizophrenia whose disease duration was less than 3 years, with previous lifetime antipsychotic treatment of no more than 2 weeks total. RESULTS: A total of 441 patients met the inclusion criteria. Core symptoms were consistently associated with 206 methylation positions, many of which had previously been implicated in inflammatory responses. Of these, 24 methylation positions were located either in regulatory regions or near the CpG islands of 20 genes, including the SRC gene, which is a key player in glutamatergic signalling. These symptom-associated immune genes were enriched in neuronal development functions, such as neuronal migration and glutamatergic synapse. Compared with using only clinical information (including scores on the Positive and Negative Syndrome Scale), integrating methylation data into the model significantly improved the predictive ability (as indicated by area under the curve) for response to 8 weeks of antipsychotic treatment. LIMITATIONS: We focused on a small number of methylation probes (immune-centred search) and lacked nutritional data and direct brain-based measures. CONCLUSION: Epigenetic modifications of the immune system are associated with symptom severity at onset and subsequent treatment response in schizophrenia.

Navigating the semantic space: Unraveling the structure of meaning in psychosis using different computational language models.

Speech in psychosis has long been ascribed as involving 'loosening of associations'. We pursued the aim to elucidate its underlying cognitive mechanisms by analysing picture descriptions from 94 subjects (29 healthy controls, 18 participants at clinical high risk, 29 with first-episode psychosis, and 18 with chronic schizophrenia), using five language models with different computational architectures: FastText, which represents meaning non-contextually/statically; BERT, which represents contextual meaning sensitive to grammar and context; Infersent and SBERT, which provide sentential representations; and CLIP, which evaluates speech relative to a visual stimulus. These models were used to quantify semantic distances crossed between successive tokens/sentences, and semantic perplexity indicating unexpectedness in continuations. Results showed that, among patients, semantic similarity increased when measured with FastText, Infersent, and SBERT, while it decreased with CLIP and BERT. Higher perplexity was observed in first-episode psychosis. Static semantic measures were associated with clinically measured impoverishment of thought and referential semantic measures with disorganization. These patterns indicate a shrinking conceptual semantic space as represented by static language models, which co-occurs with a widening in the referential semantic space as represented by contextual models. This duality underlines the need to separate these two forms of meaning for understanding mechanisms involved in semantic change in psychosis.

Using a longitudinal network structure to subgroup depressive symptoms among adolescents.

BACKGROUND: Network modeling has been proposed as an effective approach to examine complex associations among antecedents, mediators and symptoms. This study aimed to investigate whether the severity of depressive symptoms affects the multivariate relationships among symptoms and mediating factors over a 2-year longitudinal follow-up. METHODS: We recruited a school-based cohort of 1480 primary and secondary school students over four semesters from January 2020 to December 2021. The participants (n = 1145) were assessed at four time points (ages 10-13 years old at baseline). Based on a cut-off score of 5 on the 9-item Patient Health Questionnaire at each time point, the participants were categorized into the non-depressive symptom (NDS) and depressive symptom (DS) groups. We conducted network analysis to investigate the symptom-to-symptom influences in these two groups over time. RESULTS: The global network metrics did not differ statistically between the NDS and DS groups at four time points. However, network connection strength varied with symptom severity. The edge weights between learning anxiety and social anxiety were prominently in the NDS group over time. The central factors for NDS and DS were oversensitivity and impulsivity (3 out of 4 time points), respectively. Moreover, both node strength and closeness were stable over time in both groups. CONCLUSIONS: Our study suggests that interrelationships among symptoms and contributing factors are generally stable in adolescents, but a higher severity of depressive symptoms may lead to increased stability in these relationships.

The 'L-factor': Language as a transdiagnostic dimension in psychopathology.

Thoughts and moods constituting our mental life incessantly change. When the steady flow of this dynamics diverges in clinical directions, the possible pathways involved are captured through discrete diagnostic labels. Yet a single vulnerable neurocognitive system may be causally involved in psychopathological deviations transdiagnostically. We argue that language viewed as integrating cortical functions is the best current candidate, whose forms of breakdown along its different dimensions are then manifest as symptoms - from prosodic abnormalities and rumination in depression to distortions of speech perception in verbal hallucinations, distortions of meaning and content in delusions, or disorganized speech in formal thought disorder. Spontaneous connected speech provides continuous objective readouts generating a highly accessible bio-behavioral marker with the potential of revolutionizing neuropsychological measurement. This argument turns language into a transdiagnostic 'L-factor' providing an analytical and mechanistic substrate for previously proposed latent general factors of psychopathology ('p-factor') and cognitive functioning ('c-factor'). Together with immense practical opportunities afforded by rapidly advancing natural language processing (NLP) technologies and abundantly available data, this suggests a new era of translational clinical psychiatry, in which both psychopathology and language may be rethought together.

Aberrant Brain Dynamics in Schizophrenia During Working Memory Task: Evidence From a Replication Functional MRI Study.

BACKGROUND AND HYPOTHESIS: The integration of information that typifies working memory (WM) operation requires a flexible, dynamic functional relationship among brain regions. In schizophrenia, though WM capacity is prominently impaired at higher loads, the mechanistic underpinnings are unclear. As a result, we lack convincing cognitive remediation of load-dependent deficits. We hypothesize that reduced WM capacity arises from a disruption in dynamic functional connectivity when patients face cognitive demands. STUDY DESIGN: We calculate the dynamic voxel-wise degree centrality (dDC) across the functional connectome in 142 patients with schizophrenia and 88 healthy controls (HCs) facing different WM loads during an n-back task. We tested associations of the altered variability in dDC and clinical symptoms and identified intermediate connectivity configurations (clustered states) across time during WM operation. These analyses were repeated in another independent dataset of 169 subjects (102 with schizophrenia). STUDY RESULTS: Compared with HCs, patients showed an increased dDC variability of supplementary motor area (SMA) for the "2back vs. 0back" contrast. This instability at the SMA seen in patients correlated with increased positive symptoms and followed a limited "U-shape" pattern at rest-condition and 2 loads. In the clustering analysis, patients showed reduced centrality in the SMA, superior temporal gyrus, and putamen. These results were replicated in a constrained search in the second independent dataset. CONCLUSIONS: Schizophrenia is characterized by a load-dependent reduction of stable centrality in SMA; this relates to the severity of positive symptoms, especially disorganized behaviour. Restoring SMA stability in the presence of cognitive demands may have a therapeutic effect in schizophrenia.

Impact of non-medical cannabis legalization with market restrictions on health service use and incident cases of psychotic disorder in Ontario, Canada.

BACKGROUND: Cannabis is a risk factor in the onset and persistence of psychotic disorders. There is concern that non-medical cannabis legalization in Canada may have population-level impacts on psychotic disorders. We sought to examine changes in health service use and incident cases of psychotic disorder following cannabis legalization, during a period of tight restrictions on retail stores and product types. METHODS: We conducted a cross-sectional interrupted time-series analysis using linked population-based health administrative data from Ontario (Canada) from January 2014 to March 2020. We identified psychosis-related outpatient visits, emergency department visits, hospitalizations, and inpatient length of stay, as well as incident cases of psychotic disorders, among people aged 14 to 60 years. RESULTS: We did not find evidence of increases in health service use or incident cases of psychotic disorders over the short-term (17 month) period following cannabis legalization. However, we found clear increasing trends in health service use and incident cases of substance-induced psychotic disorders over the entire observation window (2014-2020). CONCLUSION: Our findings suggest that the initial period of tight market restriction following legalization of non-medical cannabis was not associated with an increase in health service use or frequency of psychotic disorders. A longer post-legalization observation period, which includes expansion of the commercial cannabis market, is needed to fully understand the population-level impacts of non-medical cannabis legalization; thus, it would be premature to conclude that the legalization of non-medical cannabis did not lead to increases in health service use and incident cases of psychotic disorder.

Glutamatergic basis of antipsychotic response in first-episode psychosis: a dual voxel study of the anterior cingulate cortex.

A subgroup of patients with schizophrenia is believed to have aberrant excess of glutamate in the frontal cortex; this subgroup is thought to show poor response to first-line antipsychotic treatments that focus on dopamine blockade. If we can identify this subgroup early in the course of illness, we can reduce the repeated use of first-line antipsychotics and potentially stratify first-episode patients to intervene early with second-line treatments such as clozapine. The use of proton magnetic resonance spectroscopy (1H-MRS) to measure glutamate and Glx (glutamate plus glutamine) may provide a means for such a stratification. We must first establish if there is robust evidence linking elevations in anterior cingulate cortex (ACC) glutamate metabolites to poor response, and determine if the use of antipsychotics worsens the glutamatergic excess in eventual nonresponders. In this study, we estimated glutamate levels at baseline in 42 drug-naive patients with schizophrenia. We then treated them all with risperidone at a standard dose range of 2-6 mg/day and followed them up for 3 months to categorize their response status. We expected to see baseline "hyperglutamatergia" in nonresponders, and expected this to worsen over time at the follow-up. In line with our predictions, nonresponders had higher glutamate than responders, but patients as a group did not differ in glutamate and Glx from the healthy control (HC) group before treatment-onset (F1,79 = 3.20, p = 0.046, partial η2 = 0.075). Glutamatergic metabolites did not change significantly over time in both nonresponders and responders over the 3 months of antipsychotic exposure (F1,31 = 1.26, p = 0.270, partial η2 = 0.039). We conclude that the use of antipsychotics without prior knowledge of later response delays symptom relief in a subgroup of first-episode patients, but does not worsen the glutamatergic excess seen at the baseline. Given the current practice of nonstratified use of antipsychotics, longer-time follow-up MRS studies are required to see if improvement in symptoms accompanies a dynamic shift in glutamate profile.

Frontostriatal circuitry and the tryptophan kynurenine pathway in major psychiatric disorders.

RATIONALE: An imbalance of the tryptophan kynurenine pathway (KP) commonly occurs in psychiatric disorders, though the neurocognitive and network-level effects of this aberration are unclear. OBJECTIVES: In this study, we examined the connection between dysfunction in the frontostriatal brain circuits, imbalances in the tryptophan kynurenine pathway (KP), and neurocognition in major psychiatric disorders. METHODS: Forty first-episode medication-naive patients with schizophrenia (SCZ), fifty patients with bipolar disorder (BD), fifty patients with major depressive disorder (MDD), and forty-two healthy controls underwent resting-state functional magnetic resonance imaging. Plasma levels of KP metabolites were measured, and neurocognitive function was evaluated. Frontostriatal connectivity and KP metabolites were compared between groups while controlling for demographic and clinical characteristics. Canonical correlation analyses were conducted to explore multidimensional relationships between frontostriatal circuits-KP and KP-cognitive features. RESULTS: Patient groups shared hypoconnectivity between bilateral ventrolateral prefrontal cortex (vlPFC) and left insula, with disorder-specific dysconnectivity in SCZ related to PFC, left dorsal striatum hypoconnectivity. The BD group had higher anthranilic acid and lower xanthurenic acid levels than the other groups. KP metabolites and ratios related to disrupted frontostriatal dysconnectivity in a transdiagnostic manner. The SCZ group and MDD group separately had high-dimensional associations between KP metabolites and cognitive measures. CONCLUSIONS: The findings suggest that KP may influence cognitive performance across psychiatric conditions via frontostriatal dysfunction.

The effect of non-medical cannabis retailer proximity on use of mental health services for psychotic disorders in Ontario, Canada.

BACKGROUND: Cannabis is associated with the onset and persistence of psychotic disorders. Evidence suggests that accessibility of substances is associated with an increased risk of use-related harms. We sought to examine the effect of residing in proximity to non-medical cannabis retailers on the prevalence of health service use for psychosis. METHODS: We conducted a cross-sectional study using linked health administrative data, and used geospatial analyses to determine whether people in Ontario, Canada (aged 14-60 years) resided within walking (1.6 km) or driving (5.0 km) distance of non-medical cannabis retailers (open as of February-2020). We identified outpatient visits, emergency department (ED) visits, and hospitalizations for psychotic disorders between 01-April-2019 and 17-March-2020. We used zero-inflated Poisson regression models and gamma generalized linear models to estimate the association between cannabis retailer proximity and indicators of health service use. RESULTS: Non-medical cannabis retailers were differentially located in areas with high levels of marginalization and pre-existing health service use for psychosis. People residing within walking or driving distance of a cannabis retailer had a higher rate of psychosis-related outpatient visits, ED visits, and hospitalizations, compared to people living outside these areas. This effect was stronger among those with no prior service use for psychosis. CONCLUSIONS: Proximity to a non-medical cannabis retailer was associated with higher health service use for psychosis, even after adjustment for prior health service use. These findings suggest that opening of non-medical cannabis retailers could worsen the burden of psychosis on mental health services in areas with high-risk populations.

Precision of metabolite-selective MRS measurements of glutamate, GABA and glutathione: A review of human brain studies.

Single-voxel proton magnetic resonance spectroscopy (SV 1 H-MRS) is an in vivo noninvasive imaging technique used to detect neurotransmitters and metabolites. It enables repeated measurements in living participants to build explanatory neurochemical models of psychiatric symptoms and testing of therapeutic approaches. Given the tight link among glutamate, gamma-amino butyric acid (GABA), glutathione and glutamine within the cellular machinery, MRS investigations of neurocognitive and psychiatric disorders must quantify a network of metabolites simultaneously to capture the pathophysiological states of interest. Metabolite-selective sequences typically provide improved metabolite isolation and spectral modelling simplification for a single metabolite at a time. Non-metabolite-selective sequences provide information on all detectable human brain metabolites, but feature many signal overlaps and require complicated spectral modelling. Although there are short-echo time (TE) MRS sequences that do not use spectral editing and are optimised to target either glutamate, GABA or glutathione, these approaches usually imply a precision tradeoff for the remaining two metabolites. Given the interest in assessing psychiatric and neurocognitive diseases that involve excitation-inhibition imbalances along with oxidative stress, there is a need to survey the literature on the quantification precision of current metabolite-selective MRS techniques. In this review, we locate and describe 17 studies that report on the quality of simultaneously acquired MRS metabolite data in the human brain. We note several factors that influence the data quality for single-shot acquisition of multiple metabolites of interest using metabolite-selective MRS: (1) internal in vivo references; (2) brain regions of interests; (3) field strength of scanner; and/or (4) optimised acquisition parameters. We also highlight the strengths and weaknesses of various SV spectroscopy techniques that were able to quantify in vivo glutamate, GABA and glutathione simultaneously. The insights from this review will assist in the development of new MRS pulse sequences for simultaneous, selective measurements of these metabolites and simplified spectral modelling.

Access to a regular primary care physician among young people with early psychosis in Ontario, Canada.

AIM: Access to a primary care physician in early psychosis facilitates help-seeking and engagement with psychiatric treatment. We examined access to a regular primary care physician in people with early psychosis, compared to the general population, and explored factors associated with access. METHODS: Using linked health administrative data from Ontario (Canada), we identified people aged 14-35 years with a first diagnosis of nonaffective psychotic disorder (n = 39 449; 2005-2015). We matched cases to four randomly selected general population controls based on age, sex, neighbourhood, and index date (n = 157 796). We used modified Poisson regression to estimate prevalence ratios (PR) for access to a regular primary care physician in the year prior to first diagnosis of psychotic disorder, and the sociodemographic and clinical factors associated with access. RESULTS: A larger proportion of people with early psychosis had a regular primary care physician, relative to the general population (89% vs. 68%; PR = 1.30, 95%CI = 1.30-1.31). However, this was accounted for by a higher prevalence of comorbidities among people with psychosis, and this association was no longer present after adjustment (PR = 0.97, 95%CI = 0.97, 0.98). People with early psychosis who were older, male, refugees and those residing in lower income or high residential instability neighbourhoods were less likely to have a regular primary care physician. CONCLUSION: Approximately one in ten young people with early psychosis in Ontario lack access to a regular primary care physician. Strategies to improve primary care physician access are needed for management of physical comorbidities and to ensure continuity of care.

Association of cortical gyrification, white matter microstructure, and phenotypic profile in medication-naïve obsessive-compulsive disorder.

BACKGROUND: Obsessive-compulsive disorder (OCD) is thought to arise from dysconnectivity among interlinked brain regions resulting in a wide spectrum of clinical manifestations. Cortical gyrification, a key morphological feature of human cerebral cortex, has been considered associated with developmental connectivity in early life. Monitoring cortical gyrification alterations may provide new insights into the developmental pathogenesis of OCD. METHODS: Sixty-two medication-naive patients with OCD and 59 healthy controls (HCs) were included in this study. Local gyrification index (LGI) was extracted from T1-weighted MRI data to identify the gyrification changes in OCD. Total distortion (splay, bend, or twist of fibers) was calculated using diffusion-weighted MRI data to examine the changes in white matter microstructure in patients with OCD. RESULTS: Compared with HCs, patients with OCD showed significantly increased LGI in bilateral medial frontal gyrus and the right precuneus, where the mean LGI was positively correlated with anxiety score. Patients with OCD also showed significantly decreased total distortion in the body, genu, and splenium of the corpus callosum (CC), where the average distortion was negatively correlated with anxiety scores. Intriguingly, the mean LGI of the affected cortical regions was significantly correlated with the mean distortion of the affected white matter tracts in patients with OCD. CONCLUSIONS: We demonstrated associations among increased LGI, aberrant white matter geometry, and higher anxiety in patients with OCD. Our findings indicate that developmental dysconnectivity-driven alterations in cortical folding are one of the neural substrates underlying the clinical manifestations of OCD.

Risk stratification for treating people at ultra-high risk for psychosis: A cost-effectiveness analysis.

People who are at ultra-high risk (UHR) for psychosis receive clinical care with the aim to prevent first-episode psychosis (FEP), regardless of the risk of conversion to psychosis. An economic model from the Canadian health system perspective was developed to evaluate the cost-effectiveness of treating all with UHR compared to risk stratification over a 15-year time horizon, based on conversion probability, expected quality-of-life and costs. The analysis used a decision tree followed by a Markov model. Health states included: Not UHR, UHR with <20 % risk of conversion to FEP (based on the North American Prodrome Longitudinal Study risk calculator), UHR with ≥20 % risk, FEP, Remission, Post-FEP, and Death. The analysis found that: risk stratification (i.e., only treating those with ≥20 % risk) had lower costs ($1398) and quality-adjusted life-years (0.055 QALYs) per person compared to treating all. The incremental cost-effectiveness ratio for 'treat all' was $25,448/QALY, and suggests treating all may be cost-effective. The model was sensitive to changes to the probability of conversion.