Patients with posttraumatic stress disorder (PTSD) exhibit smaller regional brain volumes in commonly reported regions including the amygdala and hippocampus, regions associated with fear and memory processing. In the current study, we have conducted a voxel-based morphometry (VBM) meta-analysis using whole-brain statistical maps with neuroimaging data from the ENIGMA-PGC PTSD working group.

T1-weighted structural neuroimaging scans from 36 cohorts (PTSD n = 1309; controls n = 2198) were processed using a standardized VBM pipeline (ENIGMA-VBM tool). We meta-analyzed the resulting statistical maps for voxel-wise differences in gray matter (GM) and white matter (WM) volumes between PTSD patients and controls, performed subgroup analyses considering the trauma exposure of the controls, and examined associations between regional brain volumes and clinical variables including PTSD (CAPS-4/5, PCL-5) and depression severity (BDI-II, PHQ-9).

PTSD patients exhibited smaller GM volumes across the frontal and temporal lobes, and cerebellum, with the most significant effect in the left cerebellum (Hedges’ g = 0.22, pcorrected = .001), and smaller cerebellar WM volume (peak Hedges’ g = 0.14, pcorrected = .008). We observed similar regional differences when comparing patients to trauma-exposed controls, suggesting these structural abnormalities may be specific to PTSD. Regression analyses revealed PTSD severity was negatively associated with GM volumes within the cerebellum (pcorrected = .003), while depression severity was negatively associated with GM volumes within the cerebellum and superior frontal gyrus in patients (pcorrected = .001).

PTSD patients exhibited widespread, regional differences in brain volumes where greater regional deficits appeared to reflect more severe symptoms. Our findings add to the growing literature implicating the cerebellum in PTSD psychopathology.

Duchenne muscular dystrophy is a devastating neuromuscular disorder characterized by the loss of dystrophin, inevitably leading to cardiomyopathy. Despite publications on prophylaxis and treatment with cardiac medications to mitigate cardiomyopathy progression, gaps remain in the specifics of medication initiation and optimization.

This document is an expert opinion statement, addressing a critical gap in cardiac care for Duchenne muscular dystrophy. It provides thorough recommendations for the initiation and titration of cardiac medications based on disease progression and patient response. Recommendations are derived from the expertise of the Advance Cardiac Therapies Improving Outcomes Network and are informed by established guidelines from the American Heart Association, American College of Cardiology, and Duchenne Muscular Dystrophy Care Considerations. These expert-derived recommendations aim to navigate the complexities of Duchenne muscular dystrophy-related cardiac care.

Comprehensive recommendations for initiation, titration, and optimization of critical cardiac medications are provided to address Duchenne muscular dystrophy-associated cardiomyopathy.

The management of Duchenne muscular dystrophy requires a multidisciplinary approach. However, the diversity of healthcare providers involved in Duchenne muscular dystrophy can result in variations in cardiac care, complicating treatment standardization and patient outcomes. The aim of this report is to provide a roadmap for managing Duchenne muscular dystrophy-associated cardiomyopathy, by elucidating timing and dosage nuances crucial for optimal therapeutic efficacy, ultimately improving cardiac outcomes, and improving the quality of life for individuals with Duchenne muscular dystrophy.

This document seeks to establish a standardized framework for cardiac care in Duchenne muscular dystrophy, aiming to improve cardiac prognosis.

Cohort studies demonstrate that people who later develop schizophrenia, on average, present with mild cognitive deficits in childhood and endure a decline in adolescence and adulthood. Yet, tremendous heterogeneity exists during the course of psychotic disorders, including the prodromal period. Individuals identified to be in this period (known as CHR-P) are at heightened risk for developing psychosis (~35%) and begin to exhibit cognitive deficits. Cognitive impairments in CHR-P (as a singular group) appear to be relatively stable or ameliorate over time. A sizeable proportion has been described to decline on measures related to processing speed or verbal learning. The purpose of this analysis is to use data-driven approaches to identify latent subgroups among CHR-P based on cognitive trajectories. This will yield a clearer understanding of the timing and presentation of both general and domain-specific deficits.

Participants included 684 young people at CHR-P (ages 12–35) from the second cohort of the North American Prodromal Longitudinal Study. Performance on the MATRICS Consensus Cognitive Battery (MCCB) and the Wechsler Abbreviated Scale of Intelligence (WASI-I) was assessed at baseline, 12-, and 24-months. Tested MCCB domains include verbal learning, speed of processing, working memory, and reasoning & problem-solving. Sex- and age-based norms were utilized. The Oral Reading subtest on the Wide Range Achievement Test (WRAT4) indexed pre-morbid IQ at baseline. Latent class mixture models were used to identify distinct trajectories of cognitive performance across two years. One- to 5-class solutions were compared to decide the best solution. This determination depended on goodness-of-fit metrics, interpretability of latent trajectories, and proportion of subgroup membership (>5%).

A one-class solution was found for WASI-I Full-Scale IQ, as people at CHR-P predominantly demonstrated an average IQ that increased gradually over time. For individual domains, one-class solutions also best fit the trajectories for speed of processing, verbal learning, and working memory domains. Two distinct subgroups were identified on one of the executive functioning domains, reasoning and problem-solving (NAB Mazes). The sample divided into unimpaired performance with mild improvement over time (Class I, 74%) and persistent performance two standard deviations below average (Class II, 26%). Between these classes, no significant differences were found for biological sex, age, years of education, or likelihood of conversion to psychosis (OR = 1.68, 95% CI 0.86 to 3.14). Individuals assigned to Class II did demonstrate a lower WASI-I IQ at baseline (96.3 vs. 106.3) and a lower premorbid IQ (100.8 vs. 106.2).

Youth at CHR-P demonstrate relatively homogeneous trajectories across time in terms of general cognition and most individual domains. In contrast, two distinct subgroups were observed with higher cognitive skills involving planning and foresight, and they notably exist independent of conversion outcome. Overall, these findings replicate and extend results from a recently published latent class analysis that examined 12-month trajectories among CHR-P using a different cognitive battery (Allott et al., 2022). Findings inform which individuals at CHR-P may be most likely to benefit from cognitive remediation and can inform about the substrates of deficits by establishing meaningful subtypes.

Clinical implementation of risk calculator models in the clinical high-risk for psychosis (CHR-P) population has been hindered by heterogeneous risk distributions across study cohorts which could be attributed to pre-ascertainment illness progression. To examine this, we tested whether the duration of attenuated psychotic symptom (APS) worsening prior to baseline moderated performance of the North American prodrome longitudinal study 2 (NAPLS2) risk calculator. We also examined whether rates of cortical thinning, another marker of illness progression, bolstered clinical prediction models.

Participants from both the NAPLS2 and NAPLS3 samples were classified as either ‘long’ or ‘short’ symptom duration based on time since APS increase prior to baseline. The NAPLS2 risk calculator model was applied to each of these groups. In a subset of NAPLS3 participants who completed follow-up magnetic resonance imaging scans, change in cortical thickness was combined with the individual risk score to predict conversion to psychosis.

The risk calculator models achieved similar performance across the combined NAPLS2/NAPLS3 sample [area under the curve (AUC) = 0.69], the long duration group (AUC = 0.71), and the short duration group (AUC = 0.71). The shorter duration group was younger and had higher baseline APS than the longer duration group. The addition of cortical thinning improved the prediction of conversion significantly for the short duration group (AUC = 0.84), with a moderate improvement in prediction for the longer duration group (AUC = 0.78).

These results suggest that early illness progression differs among CHR-P patients, is detectable with both clinical and neuroimaging measures, and could play an essential role in the prediction of clinical outcomes.

Several hypotheses may explain the association between substance use, posttraumatic stress disorder (PTSD), and depression. However, few studies have utilized a large multisite dataset to understand this complex relationship. Our study assessed the relationship between alcohol and cannabis use trajectories and PTSD and depression symptoms across 3 months in recently trauma-exposed civilians.

In total, 1618 (1037 female) participants provided self-report data on past 30-day alcohol and cannabis use and PTSD and depression symptoms during their emergency department (baseline) visit. We reassessed participant's substance use and clinical symptoms 2, 8, and 12 weeks posttrauma. Latent class mixture modeling determined alcohol and cannabis use trajectories in the sample. Changes in PTSD and depression symptoms were assessed across alcohol and cannabis use trajectories via a mixed-model repeated-measures analysis of variance.

Three trajectory classes (low, high, increasing use) provided the best model fit for alcohol and cannabis use. The low alcohol use class exhibited lower PTSD symptoms at baseline than the high use class; the low cannabis use class exhibited lower PTSD and depression symptoms at baseline than the high and increasing use classes; these symptoms greatly increased at week 8 and declined at week 12. Participants who already use alcohol and cannabis exhibited greater PTSD and depression symptoms at baseline that increased at week 8 with a decrease in symptoms at week 12.

Our findings suggest that alcohol and cannabis use trajectories are associated with the intensity of posttrauma psychopathology. These findings could potentially inform the timing of therapeutic strategies.

Data from neurocognitive assessments may not be accurate in the context of factors impacting validity, such as disengagement, unmotivated responding, or intentional underperformance. Performance validity tests (PVTs) were developed to address these phenomena and assess underperformance on neurocognitive tests. However, PVTs can be burdensome, rely on cutoff scores that reduce information, do not examine potential variations in task engagement across a battery, and are typically not well-suited to acquisition of large cognitive datasets. Here we describe the development of novel performance validity measures that could address some of these limitations by leveraging psychometric concepts using data embedded within the Penn Computerized Neurocognitive Battery (PennCNB).

We first developed these validity measures using simulations of invalid response patterns with parameters drawn from real data. Next, we examined their application in two large, independent samples: 1) children and adolescents from the Philadelphia Neurodevelopmental Cohort (n = 9498); and 2) adult servicemembers from the Marine Resiliency Study-II (n = 1444).

Our performance validity metrics detected patterns of invalid responding in simulated data, even at subtle levels. Furthermore, a combination of these metrics significantly predicted previously established validity rules for these tests in both developmental and adult datasets. Moreover, most clinical diagnostic groups did not show reduced validity estimates.

These results provide proof-of-concept evidence for multivariate, data-driven performance validity metrics. These metrics offer a novel method for determining the performance validity for individual neurocognitive tests that is scalable, applicable across different tests, less burdensome, and dimensional. However, more research is needed into their application.

The transition from residency to paediatric cardiology fellowship is challenging due to the new knowledge and technical skills required. Online learning can be an effective didactic modality that can be widely accessed by trainees. We sought to evaluate the effectiveness of a paediatric cardiology Fellowship Online Preparatory Course prior to the start of fellowship.

The Online Preparatory Course contained 18 online learning modules covering basic concepts in anatomy, auscultation, echocardiography, catheterisation, cardiovascular intensive care, electrophysiology, pulmonary hypertension, heart failure, and cardiac surgery. Each online learning module included an instructional video with pre-and post-video tests. Participants completed pre- and post-Online Preparatory Course knowledge-based exams and surveys. Pre- and post-Online Preparatory Course survey and knowledge-based examination results were compared via Wilcoxon sign and paired t-tests.

151 incoming paediatric cardiology fellows from programmes across the USA participated in the 3 months prior to starting fellowship training between 2017 and 2019. There was significant improvement between pre- and post-video test scores for all 18 online learning modules. There was also significant improvement between pre- and post-Online Preparatory Course exam scores (PRE 43.6 ± 11% versus POST 60.3 ± 10%, p < 0.001). Comparing pre- and post-Online Preparatory Course surveys, there was a statistically significant improvement in the participants’ comfort level in 35 of 36 (97%) assessment areas. Nearly all participants (98%) agreed or strongly agreed that the Online Preparatory Course was a valuable learning experience and helped alleviate some anxieties (77% agreed or strongly agreed) related to starting fellowship.

An Online Preparatory Course prior to starting fellowship can provide a foundation of knowledge, decrease anxiety, and serve as an effective educational springboard for paediatric cardiology fellows.

Response to lithium in patients with bipolar disorder is associated with clinical and transdiagnostic genetic factors. The predictive combination of these variables might help clinicians better predict which patients will respond to lithium treatment.

To use a combination of transdiagnostic genetic and clinical factors to predict lithium response in patients with bipolar disorder.

This study utilised genetic and clinical data (n = 1034) collected as part of the International Consortium on Lithium Genetics (ConLi+Gen) project. Polygenic risk scores (PRS) were computed for schizophrenia and major depressive disorder, and then combined with clinical variables using a cross-validated machine-learning regression approach. Unimodal, multimodal and genetically stratified models were trained and validated using ridge, elastic net and random forest regression on 692 patients with bipolar disorder from ten study sites using leave-site-out cross-validation. All models were then tested on an independent test set of 342 patients. The best performing models were then tested in a classification framework.

The best performing linear model explained 5.1% (P = 0.0001) of variance in lithium response and was composed of clinical variables, PRS variables and interaction terms between them. The best performing non-linear model used only clinical variables and explained 8.1% (P = 0.0001) of variance in lithium response. A priori genomic stratification improved non-linear model performance to 13.7% (P = 0.0001) and improved the binary classification of lithium response. This model stratified patients based on their meta-polygenic loadings for major depressive disorder and schizophrenia and was then trained using clinical data.

Using PRS to first stratify patients genetically and then train machine-learning models with clinical predictors led to large improvements in lithium response prediction. When used with other PRS and biological markers in the future this approach may help inform which patients are most likely to respond to lithium treatment.

While comorbidity of clinical high-risk for psychosis (CHR-P) status and social anxiety is well-established, it remains unclear how social anxiety and positive symptoms covary over time in this population. The present study aimed to determine whether there are more than one covariant trajectory of social anxiety and positive symptoms in the North American Prodrome Longitudinal Study cohort (NAPLS 2) and, if so, to test whether the different trajectory subgroups differ in terms of genetic and environmental risk factors for psychotic disorders and general functional outcome.

In total, 764 CHR individuals were evaluated at baseline for social anxiety and psychosis risk symptom severity and followed up every 6 months for 2 years. Application of group-based multi-trajectory modeling discerned three subgroups based on the covariant trajectories of social anxiety and positive symptoms over 2 years.

One of the subgroups showed sustained social anxiety over time despite moderate recovery in positive symptoms, while the other two showed recovery of social anxiety below clinically significant thresholds, along with modest to moderate recovery in positive symptom severity. The trajectory group with sustained social anxiety had poorer long-term global functional outcomes than the other trajectory groups. In addition, compared with the other two trajectory groups, membership in the group with sustained social anxiety was predicted by higher levels of polygenic risk for schizophrenia and environmental stress exposures.

Together, these analyses indicate differential relevance of sustained v. remitting social anxiety symptoms in the CHR-P population, which in turn may carry implications for differential intervention strategies.