Dysfunctional Alpha Modulation as a Mechanism of Working Memory Impairment in Serious Mental Illness.

BACKGROUND: People with psychosis and mood disorders experience disruptions in working memory; however, the underlying mechanism remains unknown. We focused on two potential mechanisms: first, poor attentional engagement should be associated with elevated levels of pre-stimulus alpha-band activity within the EEG, whereas impaired working memory encoding should be associated with reduced post-stimulus alpha suppression. METHODS: We collected EEG data from 68 people with schizophrenia, 43 people with bipolar disorder with a history of psychosis, and 53 people with major depressive disorder, as well as 90 healthy comparison subjects (HCS), while they completed a spatial working memory task. We quantified attention lapsing, memory precision, and memory capacity from the behavioral responses, and we quantified alpha using both traditional wavelet analysis as well as a novel approach for isolating oscillatory alpha power from aperiodic elements of the EEG signal. RESULTS: We found that (1) greater pre-stimulus alpha power estimated using traditional wavelet analysis predicted behavioral errors; (2) post-stimulus alpha suppression was reduced in the patient groups; and (3) reduced suppression was associated with lower likelihood of memory storage. However, we also observed that pre-stimulus alpha was larger among HCS compared to patients, and single-trial analyses showed that it was the aperiodic elements of the pre-stimulus EEG-not oscillatory alpha-that predicted behavioral errors. DISCUSSION: These results suggest that working memory impairments in serious mental illness primarily reflect an impairment in the post-stimulus encoding processes rather than reduced attentional engagement prior to stimulus onset.

Using Task-fMRI to Explore the Relationship Between Lifetime Cannabis Use and Cognitive Control in Individuals With First-Episode Schizophrenia.

While continued cannabis use and misuse in individuals with schizophrenia is associated with a variety of negative outcomes, individuals with a history of use tend to show higher cognitive performance compared to non-users. While this is replicated in the literature, few studies have used task-based functional magnetic resonance imaging (fMRI) to evaluate whether the brain networks underpinning these cognitive features are similarly impacted. Forty-eight first-episode individuals with schizophrenia (FES) with a history of cannabis use (FES + CAN), 28 FES individuals with no history of cannabis use (FES-CAN), and 59 controls (CON) performed the AX-Continuous Performance Task during fMRI. FES+CAN showed higher cognitive control performance (d'-context) compared to FES-CAN (P < .05, ηp 2 = 0.053), and both FES+CAN (P < .05, ηp 2 = 0.049) and FES-CAN (P < .001, ηp 2 = 0.216) showed lower performance compared to CON. FES+CAN (P < .05, ηp 2 = 0.055) and CON (P < 0.05, ηp 2 = 0.058) showed higher dorsolateral prefrontal cortex (DLPFC) activation during the task compared to FES-CAN, while FES+CAN and CON were not significantly different. Within the FES+CAN group, the younger age of initiation of cannabis use was associated with lower IQ and lower global functioning. More frequent use was also associated with higher reality distortion symptoms at the time of the scan. These data are consistent with previous literature suggesting that individuals with schizophrenia and a history of cannabis use have higher cognitive control performance. For the first time, we also reveal that FES+CAN have higher DLPFC brain activity during cognitive control compared to FES-CAN. Several possible explanations for these findings are discussed.

Exploring the acceptability, barriers, and facilitators to psychosis screening in the integrated behavioral health primary care setting: a qualitative study.

BACKGROUND: A longer duration of untreated psychosis (DUP) is associated with poorer treatment outcomes. Screening for psychosis spectrum disorders in the primary care setting could help support the earlier detection and treatment of individuals in need. However, the acceptability of screening for psychosis in this setting as part of routine care is currently unknown. METHODS: We conducted a qualitative interview study with providers and service users who participated in an early psychosis screening program conducted in an integrated behavioral health primary care (IBH-PC) setting. Interviews were recruited from one of eight WellSpace Federally Qualified Health Center IBH-PC clinics in the Sacramento, CA area. Transcripts of the recorded interviews were analyzed using thematic analysis. RESULTS: In total, 12 providers and eight service users participated in the interviews. Most service user and provider participants were supportive of psychosis screening in an IBH-PC setting, but not as part of the general practitioner consultation due to the brief, non-behavioral health nature of many of the appointments, and the expected low prevalence of psychosis in this population. The support of leadership, adequate training and support, staff turnover, and organizational changes were all seen to impact the successful implementation of the program. Different barriers and facilitators were considered important at each stage of the process from introducing the screening procedures to service users; to determining when, where, and how to screen; and how to effectively manage the referral and post-referral stages. CONCLUSIONS: Despite the additional challenges of screening in an IBH-PC setting relative to secondary mental health services, the process was considered acceptable and feasible to providers and service users. Services that plan to conduct psychosis screening in their clinics need to consider the challenges and their potential solutions to implementation at each stage of the screening process.

Altered brain metabolites in male nonhuman primate offspring exposed to maternal immune activation.

Converging data show that exposure to maternal immune activation (MIA) in utero alters brain development in animals and increases the risk of neurodevelopmental disorders in humans. A recently developed non-human primate MIA model affords opportunities for studies with uniquely strong translational relevance to human neurodevelopment. The current longitudinal study used 1H-MRS to investigate the developmental trajectory of prefrontal cortex metabolites in male rhesus monkey offspring of dams (n = 14) exposed to a modified form of the inflammatory viral mimic, polyinosinic:polycytidylic acid (Poly IC), in the late first trimester. Brain metabolites in these animals were compared to offspring of dams that received saline (n = 10) or no injection (n = 4). N-acetylaspartate (NAA), glutamate, creatine, choline, myo-inositol, taurine, and glutathione were estimated from PRESS and MEGA-PRESS acquisitions obtained at 6, 12, 24, 36, and 45 months of age. Prior investigations of this cohort reported reduced frontal cortical gray and white matter and subtle cognitive impairments in MIA offspring. We hypothesized that the MIA-induced neurodevelopmental changes would extend to abnormal brain metabolite levels, which would be associated with the observed cognitive impairments. Prefrontal NAA was significantly higher in the MIA offspring across all ages (p < 0.001) and was associated with better performance on the two cognitive measures most sensitive to impairment in the MIA animals (both p < 0.05). Myo-inositol was significantly lower across all ages in MIA offspring but was not associated with cognitive performance. Taurine was elevated in MIA offspring at 36 and 45 months. Glutathione did not differ between groups. MIA exposure in male non-human primates is associated with altered prefrontal cortex metabolites during childhood and adolescence. A positive association between elevated NAA and cognitive performance suggests the hypothesis that elevated NAA throughout these developmental stages reflects a protective or resilience-related process in MIA-exposed offspring. The potential relevance of these findings to human neurodevelopmental disorders is discussed.

Predicting Clinical Improvement in Early Psychosis Using Circuit-Based Resting-State Functional Magnetic Resonance Imaging.

BACKGROUND AND HYPOTHESIS: Identifying biomarkers that predict treatment response in early psychosis (EP) is a priority for psychiatry research. Previous work suggests that resting-state connectivity biomarkers may have promise as predictive measures, although prior results vary considerably in direction and magnitude. Here, we evaluated the relationship between intrinsic functional connectivity of the attention, default mode, and salience resting-state networks and 12-month clinical improvement in EP. STUDY DESIGN: Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as "Improvers." STUDY RESULTS: The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke's R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant. CONCLUSIONS: Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.

Whole-brain intrinsic functional connectivity predicts symptoms and functioning in early psychosis.

Theories of psychotic illness suggest that abnormal intrinsic functional connectivity may explain its characteristic positive and disorganization symptoms as well as lead to impaired general functioning. Here we used resting state functional magnetic resonance imaging (fMRI) to evaluate associations between these symptoms and the degree to which global connectivity is abnormal in early psychosis (EP). Eighty-six healthy controls (HCs) and 108 individuals with EP with resting state fMRI data were included in primary analyses. The EP group included 83 participants with schizophrenia-spectrum disorders and 25 with bipolar disorder type I with psychotic features. A global intrinsic connectivity "similarity index" for each EP individual was determined by calculating its correlation with the average HC connectivity matrix extracted using Schaefer atlases of multiple parcellations (100, 200, 300, and 400 region parcellations). As hypothesized, connectivity similarity with the average HC matrix was negatively associated with Brief Psychiatric Rating Scale total score, Scale for the Assessment of Positive Symptoms total score, and disorganization symptoms. Similarity was also positively associated with Global Assessment of Functioning score. Results were not driven by sex or diagnosis effects and were consistent across parcellation schemes. These results support the hypothesis that changes in whole-brain connectivity patterns are associated with psychosis symptoms and support the use of functional connectivity as a biomarker for these symptoms in EP.

Assessing Trial-by-Trial Electrophysiological and Behavioral Markers of Attentional Control and Sensory Precision in Psychotic and Mood Disorders.

BACKGROUND AND HYPOTHESIS: The current study investigated the extent to which changes in attentional control contribute to performance on a visual perceptual discrimination task, on a trial-by-trial basis in a transdiagnostic clinical sample. STUDY DESIGN: Participants with schizophrenia (SZ; N = 58), bipolar disorder (N = 42), major depression disorder (N = 51), and psychiatrically healthy controls (N = 92) completed a visual perception task in which stimuli appeared briefly. The design allowed us to estimate the lapse rate and the precision of perceptual representations of the stimuli. Electroencephalograms (EEG) were recorded to examine pre-stimulus activity in the alpha band (8-13 Hz), overall and in relation to behavior performance on the task. STUDY RESULTS: We found that the attention lapse rate was elevated in the SZ group compared with all other groups. We also observed group differences in pre-stimulus alpha activity, with control participants showing the highest levels of pre-stimulus alpha when averaging across trials. However, trial-by-trial analyses showed within-participant fluctuations in pre-stimulus alpha activity significantly predicted the likelihood of making an error, in all groups. Interestingly, our analysis demonstrated that aperiodic contributions to the EEG signal (which affect power estimates across frequency bands) serve as a significant predictor of behavior as well. CONCLUSIONS: These results confirm the elevated attention lapse rate that has been observed in SZ, validate pre-stimulus EEG markers of attentional control and their use as a predictor of behavior on a trial-by-trial basis, and suggest that aperiodic contributions to the EEG signal are an important target for further research in this area, in addition to alpha-band activity.

Over 30 years of STEP: The Pittsburgh experience with first-episode psychosis.

AIMS: For over 30 years, combined research and treatment settings in the US have been critical to conceptualizing care for first-episode psychosis (FEP). Here we describe an early example of such a context, the Services for the Treatment of Early Psychosis (STEP) clinic, which is affiliated with the University of Pittsburgh. METHODS: We describe STEP's historical roots and establishment in the early 1990s; STEP's research and treatment contributions, alongside its growth and ongoing leadership. RESULTS: Research-based clinics, like STEP, preceded and helped pave the way for the Recovery After an Initial Schizophrenia Episode project in the US and the ensuing Coordinated Specialty Care (CSC) approach, now widely adopted in the US. Early clinic-based research at STEP helped establish protocols for psychopharmacology, the relevance of effective early treatment, including psychosocial approaches, and highlighted disparities in treatment outcomes across race/ethnicity. Multidisciplinary collaboration and dialogue with consumers contributed to early treatment, combining psychosocial and pharmacological approaches. STEP adopted CSC and is situated within a bi-state Learning Health System. STEP has retained a relatively unique 5-year treatment model and exists within continuum of care ideally suited to studying psychotic illness and treatment outcomes. CONCLUSIONS: STEP remains the largest academic FEP clinic in Pennsylvania. Academic FEP clinics like STEP will have a critical role within Learning Health Systems nationally to model participatory approaches, sustain early intervention treatment quality and ongoing treatment developments.

Association of neurotransmitter pathway polygenic risk with specific symptom profiles in psychosis.

A primary goal of psychiatry is to better understand the pathways that link genetic risk to psychiatric symptoms. Here, we tested association of diagnosis and endophenotypes with overall and neurotransmitter pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 205 demographically diverse cases with a psychotic disorder who underwent comprehensive psychiatric and neurological phenotyping and 115 matched controls. Following genotyping, we calculated polygenic scores (PGSs) for schizophrenia (SZ) and bipolar disorder (BP) using Psychiatric Genomics Consortium GWAS summary statistics. To test if overall genetic risk can be partitioned into affected neurotransmitter pathways, we calculated pathway PGSs (pPGSs) for SZ risk affecting each of four major neurotransmitter systems: glutamate, GABA, dopamine, and serotonin. Psychosis subjects had elevated SZ PGS versus controls; cases with SZ or BP diagnoses had stronger SZ or BP risk, respectively. There was no significant association within psychosis cases between individual symptom measures and overall PGS. However, neurotransmitter-specific pPGSs were moderately associated with specific endophenotypes; notably, glutamate was associated with SZ diagnosis and with deficits in cognitive control during task-based fMRI, while dopamine was associated with global functioning. Finally, unbiased endophenotype-driven clustering identified three diagnostically mixed case groups that separated on primary deficits of positive symptoms, negative symptoms, global functioning, and cognitive control. All clusters showed strong genome-wide risk. Cluster 2, characterized by deficits in cognitive control and negative symptoms, additionally showed specific risk concentrated in glutamatergic and GABAergic pathways. Due to the intensive characterization of our subjects, the present study was limited to a relatively small cohort. As such, results should be followed up with additional research at the population and mechanism level. Our study suggests pathway-based PGS analysis may be a powerful path forward to study genetic mechanisms driving psychiatric endophenotypes.

Identification of distinct clinical profiles and trajectories in individuals at high risk of developing psychosis: A latent profile analysis of the north American prodrome longitudinal study consortium-3 dataset.

AIM: People at clinical high risk (CHR) for psychosis are a heterogeneous population in regard to clinical presentation and outcome. It is unclear, however, if their baseline clinical characteristics can be used to construct orthogonal subgroups that differ in their clinical trajectory to provide early identification of individuals in need of tailored interventions. METHODS: We used latent profile analysis (LPA) to determine the number of distinct clinical profiles within the CHR population using the NAPLS-3 dataset, focusing on the clinical features incorporated in the NAPLS psychosis risk calculator (including age, unusual thought content and suspiciousness, processing speed, verbal learning and memory function, social functioning decline, life events, childhood trauma, and family history of psychosis). We then conducted a between-profile comparisons of clinical trajectories based on psychotic and depressive symptoms as well as substance use disorder (SUD) related features over time. RESULTS: Two distinct profiles emerged. One profile, comprising approximately 25% of the sample, was significantly older, displayed better cognitive performance, experienced more types of traumatic and undesirable life events, exhibited a greater decline in functioning in the past year, and was more likely to have relatives with psychosis. This group showed worse positive symptoms and SUD-related features over time, although groups did not differ in the proportion of individuals who developed psychosis. CONCLUSIONS: LPA results suggest CHRs can be segregated into two profiles with different clinical trajectories. Characterizing individuals within these clinical profiles may help understand the divergent outcomes of this population and ultimately facilitate the development of specialized interventions.

The diagnostic accuracy of screening for psychosis spectrum disorders in behavioral health clinics integrated into primary care.

Screening for psychosis spectrum disorders in primary care could improve early identification and reduce the duration of untreated psychosis. However, the accuracy of psychosis screening in this setting is unknown. To address this, we conducted a diagnostic accuracy study of screening for psychosis spectrum disorders in eight behavioral health services integrated into primary care clinics. Patients attending an integrated behavioral health appointment at their primary care clinic completed the Prodromal Questionnaire - Brief (PQ-B) immediately prior to their intake assessment. This was compared to a diagnostic phone interview based on the Structured Interview for Psychosis Risk Syndromes (SIPS). In total, 145 participants completed all study procedures, of which 100 screened positive and 45 negative at a provisional PQ-B threshold of ≥20. The PQ-B was moderately accurate at differentiating psychosis spectrum from no psychosis spectrum disorders; a PQ-B distress score of ≥27 had a sensitivity and specificity of 71.2 % and 57.0 % respectively. In total, 66 individuals (45.5 %) met criteria for a psychosis spectrum disorder and 24 (16.7 %) were diagnosed with full psychosis, indicating a high prevalence of psychosis in the sample. Overall, screening for psychosis spectrum disorders in an IBH primary care setting identified a relatively high number of individuals and may identify people that would otherwise be missed. The PQ-B performed slightly less well than in population-based screening in community mental health settings. However, the findings suggest this may represent an effective way to streamline the pathway between specialty early psychosis programs and primary care clinics for those in need.

A Transdiagnostic Study of Effort-Cost Decision-Making in Psychotic and Mood Disorders.

BACKGROUND: Research suggests that effort-cost decision-making (ECDM), the estimation of work required to obtain reward, may be a relevant framework for understanding motivational impairment in psychotic and mood pathology. Specifically, research has suggested that people with psychotic and mood pathology experience effort as more costly than controls, and thus pursue effortful goals less frequently. This study examined ECDM across psychotic and mood pathology. HYPOTHESIS: We hypothesized that patient groups would show reduced willingness to expend effort compared to controls. STUDY DESIGN: People with schizophrenia (N = 33), schizoaffective disorder (N = 28), bipolar disorder (N = 39), major depressive disorder (N = 40), and controls (N = 70) completed a physical ECDM task. Participants decided between completing a low-effort or high-effort option for small or larger rewards, respectively. Reward magnitude, reward probability, and effort magnitude varied trial-by-trial. Data were analyzed using standard and hierarchical logistic regression analyses to assess the subject-specific contribution of various factors to choice. Negative symptoms were measured with a clinician-rated interview. STUDY RESULTS: There was a significant effect of group, driven by reduced choice of high-effort options in schizophrenia. Hierarchical logistic regression revealed that reduced choice of high-effort options in schizophrenia was driven by weaker contributions of probability information. Use of reward information was inversely associated with motivational impairment in schizophrenia. Surprisingly, individuals with major depressive disorder and bipolar disorder did not differ from controls. CONCLUSIONS: Our results provide support for ECDM deficits in schizophrenia. Additionally, differences between groups in ECDM suggest a seemingly similar behavioral phenotype, reduced motivation, could arise from disparate mechanisms.

Greater Choline-Containing Compounds and Myo-inositol in Treatment-Resistant Versus Responsive Schizophrenia: A 1H-Magnetic Resonance Spectroscopy Meta-analysis.

BACKGROUND: The neurobiology of treatment-resistant schizophrenia (TRS) is poorly understood, and meta-analytic consensus regarding magnetic resonance spectroscopic profiles of glutamate, choline-containing compounds, myo-inositol, and other metabolites in the condition is lacking. METHODS: In this meta-analysis, we examined published findings for N-acetylaspartate, choline-containing compounds (phosphocholine+glycerophosphocholine), myo-inositol, creatine+phosphocreatine, glutamate, and glutamate+glutamine in the anterior cingulate cortex and dorsal striatum in people with TRS versus non-TRS as well as TRS versus healthy control participants (HCs) and TRS versus ultra TRS (i.e., TRS with clozapine resistance). A MEDLINE search revealed 9 articles including 239 people with pooled TRS and ultra TRS, 59 with ultra TRS, 175 with non-TRS, and 153 (HCs) that met meta-analytic criteria. RESULTS: Significant effects included higher anterior cingulate cortex phosphocholine+glycerophosphocholine and myo-inositol in the pooled TRS and ultra TRS group than in both the non-TRS group and HCs as well as higher dorsal striatal phosphocholine+glycerophosphocholine in ultra TRS versus HCs, but no differences in other regional metabolites. CONCLUSIONS: The observed metabolite profile in TRS (higher phosphocholine+glycerophosphocholine and myo-inositol signal) is consistent with the hypothesis that TRS has a neuroinflammatory component, although this meta-analysis is not a critical test of that hypothesis. A similar profile is seen in healthy aging, which is known to involve increased neuroinflammation and glial activation. Because the overall number of datasets was low, however, results should be considered preliminary and highlight the need for additional studies of brain metabolites in TRS and their possible association with inflammatory processes.

Recreational cannabis use over time in individuals at clinical high risk for psychosis: Lack of associations with symptom, neurocognitive, functioning, and treatment patterns.

Recreational cannabis use has recently gained considerable interest as an environmental risk factor that triggers the onset of psychosis. To date, however, the evidence that cannabis is associated with negative outcomes in individuals at clinical high risk (CHR) for psychosis is inconsistent. The present study tracked cannabis usage over a 2-year period and examined its associations with clinical and neurocognitive outcomes, along with medication rates. CHR youth who continuously used cannabis had higher neurocognition and social functioning over time, and decreased medication usage, relative to non-users. Surprisingly, clinical symptoms improved over time despite the medication decreases.

Extracellular free water elevations are associated with brain volume and maternal cytokine response in a longitudinal nonhuman primate maternal immune activation model.

Maternal infection has emerged as an important environmental risk factor for neurodevelopmental disorders, including schizophrenia and autism spectrum disorders. Animal model systems of maternal immune activation (MIA) suggest that the maternal immune response plays a significant role in the offspring's neurodevelopment and behavioral outcomes. Extracellular free water is a measure of freely diffusing water in the brain that may be associated with neuroinflammation and impacted by MIA. The present study evaluates the brain diffusion characteristics of male rhesus monkeys (Macaca mulatta) born to MIA-exposed dams (n = 14) treated with a modified form of the viral mimic polyinosinic:polycytidylic acid at the end of the first trimester. Control dams received saline injections at the end of the first trimester (n = 10) or were untreated (n = 4). Offspring underwent diffusion MRI scans at 6, 12, 24, 36, and 45 months. Offspring born to MIA-exposed dams showed significantly increased extracellular free water in cingulate cortex gray matter starting as early as 6 months of age and persisting through 45 months. In addition, offspring gray matter free water in this region was significantly correlated with the magnitude of the maternal IL-6 response in the MIA-exposed dams. Significant correlations between brain volume and extracellular free water in the MIA-exposed offspring also indicate converging, multimodal evidence of the impact of MIA on brain development. These findings provide strong evidence for the construct validity of the nonhuman primate MIA model as a system of relevance for investigating the pathophysiology of human neurodevelopmental psychiatric disorders. Elevated free water in individuals exposed to immune activation in utero could represent an early marker of a perturbed or vulnerable neurodevelopmental trajectory.

Transdiagnostic Predictors of Everyday Functioning: Examining the Relationships of Depression and Reinforcement Learning.

BACKGROUND AND HYPOTHESIS: Impairments in function (ie, the ability to independently accomplish daily tasks) have been established in psychotic disorders. Identifying factors that contribute to these deficits is essential to developing effective interventions. The current study had several goals: examine potential differential relationships across domains of neurocognition, assess whether reinforcement learning is related to function, identify if predictors of function are transdiagnostic, determine whether depression and positive symptoms contribute to function, and to explore whether the modality of assessment impacts observed relationships. STUDY DESIGN: Data from 274 participants were examined with schizophrenia/schizoaffective disorder (SZ; n = 195) and bipolar disorder (BD; n = 79). To reduce dimensionality, a PCA was completed on neurocognitive tasks which resulted in 3 components. These components and clinical interview data were used to investigate predictors of functional domains across measures of function (self- and informant-report SLOF and UPSA). RESULTS: Two components, working memory/processing speed/episodic memory (ßs = 0.18-0.42), and negative/positive reinforcement learning (ß = -0.04), predicted different functional domains. Predictors of function were largely transdiagnostic with two exceptions: reinforcement learning had a positive association with self-reported interpersonal relationships for SZ and a negative association for BD (ß = 0.34), and the negative association between positive symptoms and self-reported social acceptability was stronger for BD than for SZ (ß = 0.93). Depression robustly predicted self-reported but not informant-reported function, and anhedonia predicted all domains of informant-reported function. CONCLUSIONS: These findings imply that reinforcement learning may differentially relate to function across disorders, traditional domains of neurocognition can be effective transdiagnostic targets for interventions, and positive symptoms and depression play a critical role in self-perceived functional impairments.

Association of neurotransmitter pathway polygenic risk with specific symptom profiles in psychosis.

A primary goal of psychiatry is to better understand the pathways that link genetic risk to psychiatric symptoms. Here, we tested association of diagnosis and endophenotypes with overall and neurotransmitter pathway-specific polygenic risk in patients with early-stage psychosis. Subjects included 206 demographically diverse cases with a psychotic disorder who underwent comprehensive psychiatric and neurological phenotyping and 115 matched controls. Following genotyping, we calculated polygenic scores (PGSs) for schizophrenia (SZ) and bipolar disorder (BP) using Psychiatric Genomics Consortium GWAS summary statistics. To test if overall genetic risk can be partitioned into affected neurotransmitter pathways, we calculated pathway PGSs (pPGSs) for SZ risk affecting each of four major neurotransmitter systems: glutamate, GABA, dopamine, and serotonin. Psychosis subjects had elevated SZ PGS versus controls; cases with SZ or BP diagnoses had stronger SZ or BP risk, respectively. There was no significant association within psychosis cases between individual symptom measures and overall PGS. However, neurotransmitter-specific pPGSs were moderately associated with specific endophenotypes; notably, glutamate was associated with SZ diagnosis and with deficits in cognitive control during task-based fMRI, while dopamine was associated with global functioning. Finally, unbiased endophenotype-driven clustering identified three diagnostically mixed case groups that separated on primary deficits of positive symptoms, negative symptoms, global functioning, and cognitive control. All clusters showed strong genome-wide risk. Cluster 2, characterized by deficits in cognitive control and negative symptoms, additionally showed specific risk concentrated in glutamatergic and GABAergic pathways. Due to the intensive characterization of our subjects, the present study was limited to a relatively small cohort. As such, results should be followed up with additional research at the population and mechanism level. Our study suggests pathway-based PGS analysis may be a powerful path forward to study genetic mechanisms driving psychiatric endophenotypes.

Managing EEG studies: How to prepare and what to do once data collection has begun.

In this paper, we provide guidance for the organization and implementation of EEG studies. This work was inspired by our experience conducting a large-scale, multi-site study, but many elements could be applied to any EEG project. Section 1 focuses on study activities that take place before data collection begins. Topics covered include: establishing and training study teams, considerations for task design and piloting, setting up equipment and software, development of formal protocol documents, and planning communication strategy with all study team members. Section 2 focuses on what to do once data collection has already begun. Topics covered include: (1) how to effectively monitor and maintain EEG data quality, (2) how to ensure consistent implementation of experimental protocols, and (3) how to develop rigorous preprocessing procedures that are feasible for use in a large-scale study. Links to resources are also provided, including sample protocols, sample equipment and software tracking forms, sample code, and tutorial videos (to access resources, please visit: https://osf.io/wdrj3/).