Dissecting Heterogeneity in Functional Network Connectivity Aberrations in Antipsychotic Medication-Naïve First Episode Psychosis Patients - A Normative Modeling Study.

Importance: While there is a general consensus that functional connectome pathology is a key mechanism underlying psychosis spectrum disorders, the literature is plagued with inconsistencies and translation into clinical practice is non-existent. This is perhaps because group-level findings may not be accurate reflections of pathology at the individual patient level. Objective: To characterize inter-individual heterogeneity in functional networks and investigate if normative values can be leveraged to identify biologically less heterogeneous subgroups of patients. Design Setting and Participants: We used data collected in a case-control study conducted at the University of Alabama at Birmingham (UAB). We recruited antipsychotic medication-naïve first-episode psychosis patients from UAB outpatient, inpatient, and emergency room settings. Main Outcomes and Measures: Individual-level patterns of deviations from a normative reference range in resting-state functional networks using the Yeo-17 atlas for parcellations. Results: Statistical analyses included 108 medication-naïve first-episode psychosis patients. We found that there is a high level of inter-individual heterogeneity in resting-state network connectivity deviations from the normative reference range. Interestingly 48% of patients did not have any functional connectivity deviations, and no more than 11.1% of patients shared functional deviations between the same regions of interest. In a post hoc analysis, we grouped patients based on deviations into four theoretically possible groups. We discovered that all four groups do exist in our experimental data and showed that subgroups based on deviation profiles were significantly less heterogeneous compared to the overall group (positive deviation group: z= -2.88, p = 0.002; negative deviation group: z= -3.36, p<0.001). Conclusions and Relevance: Our findings experimentally demonstrate that there is a high level of inter-individual heterogeneity in resting-state network pathology in first-episode psychosis patients which support the idea that group-level findings are not accurate reflections of pathology at the individual level. We also demonstrated that normative functional connectivity deviations may have utility for identifying biologically less heterogeneous subgroups of patients, even though they are not distinguishable clinically. Our findings constitute a significant step towards making precision psychiatry a reality, where patients are selected for treatments based on their individual biological characteristics. KEY POINTS: Question: How heterogeneous is individual-level resting-state functional network pathology in patients suffering from a first psychotic episode? Can normative reference values in functional network connectivity be leveraged to identify biologically more homogenous subgroups of patients?Findings: We report that functional network pathology is highly heterogeneous, with no more than 11% of patients sharing functional deviations between the same regions of interest.Meaning: Normative modeling is a tool that can map individual neurobiological differences and enables the classification of a clinically heterogenous patient group into subgroups that are neurobiologically less heterogenous.

Post-Roe v Wade psychiatry: legal, clinical, and ethical challenges in psychiatry under abortion bans.

In recent history, the world has witnessed a trend towards liberalization of abortion laws driven by an increasing understanding of the negative personal and public health consequences of criminalizing abortion. By contrast, several countries have recently implemented restrictive reproductive laws, joining the 112 countries where access to abortion care is banned completely or with narrow exceptions. On June 24, 2022, the US Supreme Court ruling in Dobbs v Jackson Women's Health Organization overturned its landmark decisions in Roe v Wade that established abortion until the point of viability of the fetus as a constitutional right. After Roe v Wade having been overturned, it is projected that many women in the USA will be prevented from accessing safe abortion care. Importantly, abortion bans not only impose constraints on patient autonomy, they also restrict physicians' ability to practice evidence-based medicine, which will negatively impact psychiatric care. It is therefore crucial for the practicing psychiatrist to be familiar with this new legal landscape. In this Personal View, we aim to provide a topical overview to help clinicians gain a clear understanding of legal, clinical, and ethical responsibilities, focusing on the USA. We also discuss the reality that psychiatrists might be called upon to determine medical necessity for an abortion on psychiatric grounds, which is new for most US psychiatrists. We predict that psychiatrists will be confronted with very difficult situations in which lawful and ethical conduct might be incongruent, and that abortion bans will result in greater numbers of patients needing psychiatric care from a system that is ill-prepared for additional demands.

Topological Perturbations in the Functional Connectome Support the Deficit/Non-deficit Distinction in Antipsychotic Medication-Naïve First Episode Psychosis Patients.

BACKGROUND: Heterogeneity in the etiology, pathophysiology, and clinical features of schizophrenia challenges clinicians and researchers. A helpful approach could be stratifying patients according to the presence or absence of clinical features of the deficit syndrome (DS). DS is characterized by enduring and primary negative symptoms, a clinically less heterogeneous subtype of the illness, and patients with features of DS are thought to present abnormal brain network characteristics, however, this idea has received limited attention. We investigated functional brain network topology in patients displaying deficit features and those who do not. DESIGN: We applied graph theory analytics to resting-state functional magnetic resonance imaging data of 61 antipsychotic medication-naïve first episode psychosis patients, 18 DS and 43 non-deficit schizophrenia (NDS), and 72 healthy controls (HC). We quantified small-worldness, global and nodal efficiency measures, shortest path length, nodal local efficiency, and synchronization and contrasted them among the 3 groups. RESULTS: DS presented decreased network integration and segregation compared to HC and NDS. DS showed lower global efficiency, longer global path lengths, and lower global local efficiency. Nodal efficiency was lower and the shortest path length was longer in DS in default mode, ventral attention, dorsal attention, frontoparietal, limbic, somatomotor, and visual networks compared to HC. Compared to NDS, DS showed lower efficiency and longer shortest path length in default mode, limbic, somatomotor, and visual networks. CONCLUSIONS: Our data supports increasing evidence, based on topological perturbations of the functional connectome, that deficit syndrome may be a distinct form of the illness.

Higher-order functional brain networks and anterior cingulate glutamate + glutamine (Glx) in antipsychotic-naïve first episode psychosis patients.

Human connectome studies have provided abundant data consistent with the hypothesis that functional dysconnectivity is predominant in psychosis spectrum disorders. Converging lines of evidence also suggest an interaction between dorsal anterior cingulate cortex (dACC) cortical glutamate with higher-order functional brain networks (FC) such as the default mode (DMN), dorsal attention (DAN), and executive control networks (ECN) in healthy controls (HC) and this mechanism may be impaired in psychosis. Data from 70 antipsychotic-medication naïve first-episode psychosis (FEP) and 52 HC were analyzed. 3T Proton magnetic resonance spectroscopy (1H-MRS) data were acquired from a voxel in the dACC and assessed correlations (positive FC) and anticorrelations (negative FC) of the DMN, DAN, and ECN. We then performed regressions to assess associations between glutamate + glutamine (Glx) with positive and negative FC of these same networks and compared them between groups. We found alterations in positive and negative FC in all networks (HC > FEP). A relationship between dACC Glx and positive and negative FC was found in both groups, but when comparing these relationships between groups, we found contrasting associations between these variables in FEP patients compared to HC. We demonstrated that both positive and negative FC in three higher-order resting state networks are already altered in antipsychotic-naïve FEP, underscoring the importance of also considering anticorrelations for optimal characterization of large-scale functional brain networks as these represent biological processes as well. Our data also adds to the growing body of evidence supporting the role of dACC cortical Glx as a mechanism underlying alterations in functional brain network connectivity. Overall, the implications for these findings are imperative as this particular mechanism may differ in untreated or chronic psychotic patients; therefore, understanding this mechanism prior to treatment could better inform clinicians.Clinical trial registration: Trajectories of Treatment Response as Window into the Heterogeneity of Psychosis: A Longitudinal Multimodal Imaging Study, NCT03442101 . Glutamate, Brain Connectivity and Duration of Untreated Psychosis (DUP), NCT02034253 .

Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n = 101) from healthy controls (n = 51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n = 97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC = 75.4%, 95% CI = 67.0-83.3%; in non-affective psychosis AUC = 80.5%, 95% CI = 72.1-88.0%, and in affective psychosis AUC = 58.7%, 95% CI = 44.2-72.0%). Test-retest reliability ranged between ICC = 0.48 (95% CI = 0.35-0.59) and ICC = 0.22 (95% CI = 0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC = 0.51 (95% CI = 0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 min, diagnostic classification of the FSA increased from AUC = 71.7% (95% CI = 63.1-80.3%) to 75.4% (95% CI = 67.0-83.3%) and phase encoding direction reliability from ICC = 0.29 (95% CI = 0.14-0.43) to ICC = 0.51 (95% CI = 0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Higher-Order Intrinsic Brain Network Trajectories After Antipsychotic Treatment in Medication-Naïve Patients With First-Episode Psychosis.

BACKGROUND: Intrinsic brain network connectivity is already altered in first-episode psychosis (FEP), but the longitudinal trajectories of network connectivity, especially in response to antipsychotic treatment, remain poorly understood. The goal of this study was to investigate how antipsychotic medications affect higher-order intrinsic brain network connectivity in FEP. METHODS: Data from 87 antipsychotic medication-naïve patients with FEP and 87 healthy control participants were used. Medication-naïve patients received antipsychotic treatment for 16 weeks. Resting-state functional connectivity (FC) of the default mode, salience, dorsal attention, and executive control networks were assessed prior to treatment and at 6 and 16 weeks after treatment. We evaluated baseline and FC changes using linear mixed models to test group × time interactions within each network. Associations between FC changes after 16 weeks and response to treatment were also evaluated. RESULTS: Prior to treatment, significant group differences in all networks were found. However, significant trajectory changes in FC were found only in the default mode and executive control networks. Changes in FC in these networks were associated with treatment response. Several sensitivity analyses showed a consistent normalization of executive control network FC in response to antipsychotic treatment. CONCLUSIONS: Here, we found that alterations in intrinsic brain network FC were not only alleviated with antipsychotic treatment, but the extent of this normalization was also associated with the degree of reduction in symptom severity. Taken together, our data suggest modulation of intrinsic brain network connectivity (mainly frontoparietal connectivity) as a mechanism underlying antipsychotic treatment response in FEP.

Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Replication of a neuroimaging biomarker for striatal dysfunction in psychosis.

To bring biomarkers closer to clinical application, they should be generalizable, reliable, and maintain performance within the constraints of routine clinical conditions. The functional striatal abnormalities (FSA), is among the most advanced neuroimaging biomarkers in schizophrenia, trained to discriminate diagnosis, with post-hoc analyses indicating prognostic properties. Here, we attempt to replicate its diagnostic capabilities measured by the area under the curve (AUC) in receiver operator characteristic curves discriminating individuals with psychosis (n=101) from healthy controls (n=51) in the Human Connectome Project for Early Psychosis. We also measured the test-retest (run 1 vs 2) and phase encoding direction (i.e., AP vs PA) reliability with intraclass correlation coefficients (ICC). Additionally, we measured effects of scan length on classification accuracy (i.e., AUCs) and reliability (i.e., ICCs). Finally, we tested the prognostic capability of the FSA by the correlation between baseline scores and symptom improvement over 12 weeks of antipsychotic treatment in a separate cohort (n=97). Similar analyses were conducted for the Yeo networks intrinsic connectivity as a reference. The FSA had good/excellent diagnostic discrimination (AUC=75.4%, 95%CI=67.0%-83.3%; in non-affective psychosis AUC=80.5%, 95%CI=72.1-88.0%, and in affective psychosis AUC=58.7%, 95%CI=44.2-72.0%). Test-retest reliability ranged between ICC=0.48 (95%CI=0.35-0.59) and ICC=0.22 (95%CI=0.06-0.36), which was comparable to that of networks intrinsic connectivity. Phase encoding direction reliability for the FSA was ICC=0.51 (95%CI=0.42-0.59), generally lower than for networks intrinsic connectivity. By increasing scan length from 2 to 10 minutes, diagnostic classification of the FSA increased from AUC=71.7% (95%CI=63.1%-80.3%) to 75.4% (95%CI=67.0%-83.3%) and phase encoding direction reliability from ICC=0.29 (95%CI=0.14-0.43) to ICC=0.51 (95%CI=0.42-0.59). FSA scores did not correlate with symptom improvement. These results reassure that the FSA is a generalizable diagnostic - but not prognostic - biomarker. Given the replicable results of the FSA as a diagnostic biomarker trained on case-control datasets, next the development of prognostic biomarkers should be on treatment-response data.

Structural Racism in Psychiatric Research Careers: Eradicating Barriers to a More Diverse Workforce.

Investigators from minoritized backgrounds are underrepresented in psychiatric research. That underrepresentation contributes to disparities in outcomes of access to mental health care. Drawing on lived experience, scholarly qualitative reports, and empirical data, the authors review how the underrepresentation of minoritized researchers arises from interlocking, self-reinforcing effects of structural biases in our research training and funding institutions. Minoritized researchers experience diminished early access to advanced training and opportunities, stereotype threats and microaggressions, isolation due to lack of peers and senior mentors, decreased access to early funding, and unique community and personal financial pressures. These represent structural racism-a system of institutional assumptions and practices that perpetuates race-based disparities, in spite of those institutions' efforts to increase diversity and in contradiction to the values that academic leaders outwardly espouse. The authors further review potential approaches to reversing these structural biases, including undergraduate-focused research experiences, financial support for faculty who lead training/mentoring programs, targeted mentoring through scholarly societies, better use of federal diversity supplement funding, support for scientific reentry, cohort building, diversity efforts targeting senior leadership, and rigorous examination of hiring, compensation, and promotion practices. Several of these approaches have empirically proven best practices and models for dissemination. If implemented alongside outcome measurement, they have the potential to reverse decades of structural bias in psychiatry and psychiatric research.

Hippocampal Hyperconnectivity to the Visual Cortex Predicts Treatment Response.

BACKGROUND: Converging lines of evidence point to hippocampal dysfunction in psychosis spectrum disorders, including altered functional connectivity. Evidence also suggests that antipsychotic medications can modulate hippocampal dysfunction. The goal of this project was to identify patterns of hippocampal connectivity predictive of response to antipsychotic treatment in 2 cohorts of patients with a psychosis spectrum disorder, one medication-naïve and the other one unmedicated. HYPOTHESIS: We hypothesized that we would identify reliable patterns of hippocampal connectivity in the 2 cohorts that were predictive of treatment response and that medications would modulate abnormal hippocampal connectivity after 6 weeks of treatment. STUDY DESIGN: We used a prospective design to collect resting-state fMRI scans prior to antipsychotic treatment and after 6 weeks of treatment with risperidone, a commonly used antipsychotic medication, in both cohorts. We enrolled 44 medication-naïve first-episode psychosis patients (FEP) and 39 unmedicated patients with schizophrenia (SZ). STUDY RESULTS: In both patient cohorts, we observed a similar pattern where greater hippocampal connectivity to regions of the occipital cortex was predictive of treatment response. Lower hippocampal connectivity of the frontal pole, orbitofrontal cortex, subcallosal area, and medial prefrontal cortex was predictive of treatment response in unmedicated SZ, but not in the medication-naïve cohort. Furthermore, greater reduction in hippocampal connectivity to the visual cortex with treatment was associated with better clinical response. CONCLUSIONS: Our results suggest that greater connectivity between the hippocampus and occipital cortex is not only predictive of better treatment response, but that antipsychotic medications have a modulatory effect by reducing hyperconnectivity.

Co-occurring opioid use disorder and serious mental illness: A selective literature review.

OBJECTIVE: The overarching goal of this review is to provide a clinical overview of epidemiology, diagnosis, and treatment, and to discuss the public health impact, social determinants including access to care, and implications for health care delivery and research. It is estimated that approximately 1 in 4 individuals suffering from a serious mental illness (SMI) may have a co-occurring opioid use disorder (OUD). In these individuals, the overall disease burden is higher and clinical outcomes are worse compared to those without a co-occurring illness, making an integrated approach to diagnosis and treatment an urgent priority. METHODS: We conducted a selective review of the literature to investigate prevalence, etiology for co-occurring OUD and SMI, and diagnostic and clinical guidelines in the United States, and consideration special populations. FINDINGS: Our findings suggest that, despite the high prevalence of co-occurring OUD and SMI, contemporary diagnostics and treatment approaches are underutilized in this patient population. The literature also suggests that both pharmacological and psychosocial treatment approaches need to be tailored to optimize clinical management, and that integrated treatment is pivotal for improving overall outcomes, yet comprehensive clinical guidelines for co-occurring OUD and SMI are lacking at this time.

Neurite Orientation Dispersion and Density Imaging in Psychiatric Disorders: A Systematic Literature Review and a Technical Note.

While major psychiatric disorders lack signature diagnostic neuropathologies akin to dementias, classic postmortem studies have established microstructural involvement, i.e., cellular changes in neurons and glia, as a key pathophysiological finding. Advanced magnetic resonance imaging techniques allow mapping of cellular tissue architecture and microstructural abnormalities in vivo, which holds promise for advancing our understanding of the pathophysiology underlying psychiatric disorders. Here, we performed a systematic review of case-control studies using neurite orientation dispersion and density imaging (NODDI) to assess brain microstructure in psychiatric disorders and a selective review of technical considerations in NODDI. Of the 584 potentially relevant articles, 18 studies met the criteria to be included in this systematic review. We found a general theme of abnormal gray and white matter microstructure across the diagnostic spectrum. We also noted significant variability in patterns of neurite density and fiber orientation within and across diagnostic groups, as well as associations between brain microstructure and phenotypical variables. NODDI has been successfully used to detect subtle microstructure abnormalities in patients with psychiatric disorders. Given that NODDI indices may provide a more direct link to pathophysiological processes, this method may not only contribute to advancing our mechanistic understanding of disease processes, it may also be well positioned for next-generation biomarker development studies.

In Search of Biomarkers to Guide Interventions in Autism Spectrum Disorder: A Systematic Review.

OBJECTIVE: The aim of this study was to catalog and evaluate response biomarkers correlated with autism spectrum disorder (ASD) symptoms to improve clinical trials. METHODS: A systematic review of MEDLINE, Embase, and Scopus was conducted in April 2020. Seven criteria were applied to focus on original research that includes quantifiable response biomarkers measured alongside ASD symptoms. Interventional studies or human studies that assessed the correlation between biomarkers and ASD-related behavioral measures were included. RESULTS: A total of 5,799 independent records yielded 280 articles for review that reported on 940 biomarkers, 755 of which were unique to a single publication. Molecular biomarkers were the most frequently assayed, including cytokines, growth factors, measures of oxidative stress, neurotransmitters, and hormones, followed by neurophysiology (e.g., EEG and eye tracking), neuroimaging (e.g., functional MRI), and other physiological measures. Studies were highly heterogeneous, including in phenotypes, demographic characteristics, tissues assayed, and methods for biomarker detection. With a median total sample size of 64, almost all of the reviewed studies were only powered to identify biomarkers with large effect sizes. Reporting of individual-level values and summary statistics was inconsistent, hampering mega- and meta-analysis. Biomarkers assayed in multiple studies yielded mostly inconsistent results, revealing a "replication crisis." CONCLUSIONS: There is currently no response biomarker with sufficient evidence to inform ASD clinical trials. This review highlights methodological imperatives for ASD biomarker research necessary to make definitive progress: consistent experimental design, correction for multiple comparisons, formal replication, sharing of sample-level data, and preregistration of study designs. Systematic "big data" analyses of multiple potential biomarkers could accelerate discovery.

Dorsal striatial hypoconnectivity predicts antipsychotic medication treatment response in first-episode psychosis and unmedicated patients with schizophrenia.

INTRODUCTION: The dorsal striatum, comprised of the caudate and putamen, is implicated in the pathophysiology of psychosis spectrum disorders. Given the high concentration of dopamine receptors in the striatum, striatal dopamine imbalance is a likely cause in cortico-striatal dysconnectivity. There is great interest in understanding the relationship between striatal abnormalities in psychosis and antipsychotic treatment response, but few studies have considered differential involvement of the caudate and putamen. This study's goals were twofold. First, identify patterns of dorsal striatal dysconnectivity for the caudate and putamen separately in patients with a psychosis spectrum disorder; second, determine if these dysconnectivity patterns were predictive of treatment response. METHODS: Using resting state functional connectivity, we evaluated dorsal striatal connectivity using separate bilateral caudate and putamen seed regions in two cohorts of subjects: a cohort of 71 medication-naïve first episode psychosis patients and a cohort of 42 unmedicated patients with schizophrenia (along with matched controls). Patient and control connectivity maps were contrasted for each cohort. After receiving 6 weeks of risperidone treatment, patients' clinical response was calculated. We used regression analyses to determine the relationship between baseline dysconnectivity and treatment response. RESULTS: This dysconnectivity was also predictive of treatment response in both cohorts. DISCUSSION: These findings suggest that the caudate may be more of a driving factor than the putamen in early cortico-striatal dysconnectivity.

Contrasting Case-Control and Normative Reference Approaches to Capture Clinically Relevant Structural Brain Abnormalities in Patients With First-Episode Psychosis Who Are Antipsychotic Naive.

Importance: To make progress toward precision psychiatry, it is crucial to move beyond case-control studies and instead capture individual variations and interpret them in the context of a normal range of biological systems. Objective: To evaluate whether baseline deviations from a normative reference range in subcortical volumes are better predictors of antipsychotic treatment response than raw volumes in patients with first-episode psychosis (FEP) who were naive to antipsychotic medication. Design, Setting, and Participants: In this prospective longitudinal study, patients with first-episode psychosis who were referred from different clinical settings (emergency department, inpatient units, and outpatient clinics) at the University of Alabama at Birmingham were included. A total of 286 patients were screened, 114 consented, 104 enrolled in the treatment trial, and 85 completed the trial. Patients were observed for 16 weeks. Controls were matched by age and sex. Data were collected between June 2016 and July 2021, and data were analyzed from August 2021 to June 2022. Interventions: Risperidone on a flexible dosing scheme for 16 weeks. There was an option to switch to aripiprazole for excessive adverse effects. Main Outcomes and Measures: The main outcome of this study was to evaluate, in patients with FEP who were naive to antipsychotic medication, the association of baseline raw volumes and volume deviations in subcortical brain regions with response to antipsychotic medication. Raw brain volumes or volume deviation changes after treatment were not examined. Results: Of 190 included participants, 111 (58.4%) were male, and the mean (SD) age was 23.7 (5.5) years. Volumes and deviations were quantified in 98 patients with FEP, and data from 92 controls were used as comparison for case-control contrasts and reference curve calibration. In case-control contrasts, patients with FEP had lower raw thalamus (P = .002; F = 9.63; df = 1), hippocampus (P = .009; F = 17.23; df = 1), amygdala (P = .01; F = 6.55; df = 1), ventral diencephalon (P = .03; F = 4.84; df = 1), and brainstem volumes (P = .004; F = 8.39; df = 1). Of 98 patients, 36 patients with FEP (36%) displayed extreme deviations. Associations with treatment response significantly differed between raw volume and deviation measures in the caudate (z = -2.17; P = .03) and putamen (z = -2.15; P = .03). Conclusions and Relevance: These data suggest that normative modeling allows capture of interindividual heterogeneity of regional brain volumes in patients with FEP and characterize structural pathology in a clinically relevant fashion. This holds promise for progress in precision medicine in psychiatry, where group-level studies have failed to derive reliable maps of structural pathology.

The neural substrates of neurological soft signs in schizophrenia: a systematic review.

Neurological soft signs (NSS) are common in patients with schizophrenia. However, the neural substrates of NSS remain poorly understood. Using legacy PubMed, we performed a systematic review and included studies that assessed NSS and obtained neuroimaging data in patients with a schizophrenia spectrum disorder published up to June 2020. We systematically reviewed 35 relevant articles. Studies consistently implicate the basal ganglia and cerebellum as structural substrates of NSS and suggest that somatomotor and somatosensory regions as well as areas involved in visual processing and spatial orientation may underlie NSS in psychosis spectrum disorders. Additionally, dysfunction of frontoparietal and cerebellar networks has been implicated in the pathophysiology of NSS. The current literature outlines several structural and functional brain signatures that are relevant for NSS in schizophrenia spectrum disorder. The majority of studies assessed gray matter structure, but only a few studies leveraged other imaging methods such as diffusion weighted imaging, or molecular imaging. Due to this, it remains unclear if white matter integrity deficits or neurometabolic alterations contribute to NSS in the illness. While a substantial portion of the literature has been conducted in patients in the early illness stages, mitigating confounds of illness chronicity, few studies have been conducted in antipsychotic medication-naïve patients, which is a clear limitation. Furthermore, only little is known about the temporal evolution of NSS and associated brain signatures. Future studies addressing these pivotal gaps in our mechanistic understanding of NSS will be important.

Contrasting Frontoparietal Network Connectivity in Antipsychotic Medication-Naive First-Episode Psychosis Patients Who Do and Do Not Display Features of the Deficit Syndrome.

BACKGROUND: The deficit syndrome is a clinical subtype of schizophrenia that is characterized by enduring negative symptoms. Several lines of evidence point to frontoparietal involvement, but the frontoparietal control network (FPCN) and its subsystems (FPCNA and FPCNB) proposed by Yeo et al. have not been systematically characterized at rest in patients with the deficit syndrome. METHODS: We used resting-state fMRI to investigate the FPCN and its subnetworks in 72 healthy controls and 65 antipsychotic medication-naive, first-episode psychosis patients (22 displayed deficit syndrome features, 43 did not). To assess whole-brain FPCN connectivity, we used the right posterior parietal cortex as the seed region. We then performed region of interest analyses in FPCN subsystems. RESULTS: We found that patterns of FPCN dysconnectivity to the whole brain differed in patients who displayed deficit syndrome features compared with those who did not. Examining the FPCN on a more granular level revealed reduced within-FPCN(A) connectivity only in patients displaying deficit features. FPCNB connectivity did not differ between patient groups. DISCUSSION: Here, we describe a neurobiological signature of aberrant FPCN connectivity in antipsychotic-naive, first-episode patients who display clinical features of the deficit syndrome. Importantly, frontoparietal subnetwork connectivity differentiated subgroups, where the FPCNA is selectively involved in patients with deficit features. Our findings add to the growing body of literature supporting a neurobiological distinction between two clinical subtypes of schizophrenia, which has the potential to be leveraged for patient stratification in clinical trials and the development of novel treatments.

The role of glutamate and GABA in cognitive dysfunction in schizophrenia and mood disorders - A systematic review of magnetic resonance spectroscopy studies.

Epidemiologic, genetic, and neurobiological studies suggest considerable overlap between schizophrenia and mood disorders. Importantly, both disorders are associated with a broad range of cognitive deficits as well as altered glutamatergic and GABAergic neurometabolism. We conducted a systematic review of magnetic resonance spectroscopy (MRS) studies investigating the relationship between glutamatergic and GABAergic neurometabolites and cognition in schizophrenia spectrum disorders and mood disorders. A literature search in Pubmed of studies published before April 15, 2019 was conducted and 37 studies were deemed eligible for systematic review. We found that alterations in glutamatergic and GABAergic neurotransmission have been identified relatively consistently in both schizophrenia and mood disorders. However, because of the vast heterogeneity of published studies in terms of illness stage, medication exposure, MRS acquisition parameters and data post-processing strategies, we still do not understand the relationship between those neurotransmitters and cognitive dysfunction in mental illness, which is a critical initial step for rational drug development. Our findings emphasize the need for coordinated multi-center studies that characterize cognitive function and its biological substrates in large and well-defined clinical populations, using harmonized imaging sequences and analytical methods with the goal to elucidate the underlying pathophysiological mechanisms and to inform future clinical trials.

Hippocampal Dysconnectivity and Altered Glutamatergic Modulation of the Default Mode Network: A Combined Resting-State Connectivity and Magnetic Resonance Spectroscopy Study in Schizophrenia.

BACKGROUND: Converging lines of evidence point to hippocampal dysfunction in schizophrenia. It is thought that hippocampal dysfunction spreads across hippocampal subfields and to cortical regions by way of long-range efferent projections. Importantly, abnormalities in the excitation/inhibition balance could impair the long-range modulation of neural networks. The goal of this project was twofold. First, we sought to identify replicable patterns of hippocampal dysconnectivity in patients with a psychosis spectrum disorder. Second, we aimed to investigate a putative link between glutamatergic metabolism and hippocampal connectivity alterations. METHODS: We evaluated resting-state hippocampal functional connectivity alterations in two cohorts of patients with a psychosis spectrum disorder. The first cohort consisted of 55 medication-naïve patients with first-episode psychosis and 41 matched healthy control subjects, and the second cohort consisted of 42 unmedicated patients with schizophrenia and 41 matched control subjects. We also acquired measurements of glutamate + glutamine in the left hippocampus using magnetic resonance spectroscopy for 42 patients with first-episode psychosis and 37 healthy control subjects from our first cohort. RESULTS: We observed a pattern of hippocampal functional hypoconnectivity to regions of the default mode network and hyperconnectivity to the lateral occipital cortex in both cohorts. We also show that in healthy control subjects, greater hippocampal glutamate + glutamine levels predicted greater hippocampal functional connectivity to the anterior default mode network. Furthermore, this relationship was reversed in medication-naïve subjects with first-episode psychosis. CONCLUSIONS: These results suggest that an alteration in the relationship between glutamate and functional connectivity may disrupt the dynamic of major neural networks.

Risks and Benefits of Cannabis and Cannabinoids in Psychiatry.

OBJECTIVE: The United States is in the midst of rapidly changing laws regarding cannabis. The increasing availability of cannabis for recreational and medical use requires that mental health clinicians be knowledgeable about evidence to be considered when counseling both patients and colleagues. In this review, the authors outline the evidence from randomized double-blind placebo-controlled trials for therapeutic use of cannabinoids for specific medical conditions and the potential side effects associated with acute and chronic cannabis use. METHODS: Searches of PubMed and PsycInfo were conducted for articles published through July 2021 reporting on "cannabis" or "cannabinoids" or "medicinal cannabis." Additional articles were identified from the reference lists of published reviews. Articles that did not contain the terms "clinical trial" or "therapy" in the title or abstract were not reviewed. A total of 4,431 articles were screened, and 841 articles that met criteria for inclusion were reviewed by two or more authors. RESULTS: There are currently no psychiatric indications approved by the U.S. Food and Drug Administration (FDA) for cannabinoids, and there is limited evidence supporting the therapeutic use of cannabinoids for treatment of psychiatric disorders. To date, evidence supporting cannabinoid prescription beyond the FDA indications is strongest for the management of pain and spasticity. CONCLUSIONS: As cannabinoids become more available, the need for an evidence base adequately evaluating their safety and efficacy is increasingly important. There is considerable evidence that cannabinoids have a potential for harm in vulnerable populations such as adolescents and those with psychotic disorders. The current evidence base is insufficient to support the prescription of cannabinoids for the treatment of psychiatric disorders.