White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Polygenic architecture of brain structure and function, behaviors, and psychopathologies in children.

The human brain undergoes structural and functional changes during childhood, a critical period in cognitive and behavioral development. Understanding the genetic architecture of the brain development in children can offer valuable insights into the development of the brain, cognition, and behaviors. Here, we integrated brain imaging-genetic-phenotype data from over 8,600 preadolescent children of diverse ethnic backgrounds using multivariate statistical techniques. We found a low-to-moderate level of SNP-based heritability in most IDPs, which is lower compared to the adult brain. Using sparse generalized canonical correlation analysis (SGCCA), we identified several covariation patterns among genome-wide polygenic scores (GPSs) of 29 traits, 7 different modalities of brain imaging-derived phenotypes (IDPs), and 266 cognitive and psychological phenotype data. In structural MRI, significant positive associations were observed between total grey matter volume, left ventral diencephalon volume, surface area of right accumbens and the GPSs of cognition-related traits. Conversely, negative associations were found with the GPSs of ADHD, depression and neuroticism. Additionally, we identified a significant positive association between educational attainment GPS and regional brain activation during the N-back task. The BMI GPS showed a positive association with fractional anisotropy (FA) of connectivity between the cerebellum cortex and amygdala in diffusion MRI, while the GPSs for educational attainment and cannabis use were negatively associated with the same IDPs. Our GPS-based prediction models revealed substantial genetic contributions to cognitive variability, while the genetic basis for many mental and behavioral phenotypes remained elusive. This study delivers a comprehensive map of the relationships between genetic profiles, neuroanatomical diversity, and the spectrum of cognitive and behavioral traits in preadolescence.

Gene-environment pathways to cognitive intelligence and psychotic-like experiences in children.

In children, psychotic-like experiences (PLEs) are related to risk of psychosis, schizophrenia, and other mental disorders. Maladaptive cognitive functioning, influenced by genetic and environmental factors, is hypothesized to mediate the relationship between these factors and childhood PLEs. Using large-scale longitudinal data, we tested the relationships of genetic and environmental factors (such as familial and neighborhood environment) with cognitive intelligence and their relationships with current and future PLEs in children. We leveraged large-scale multimodal data of 6,602 children from the Adolescent Brain and Cognitive Development Study. Linear mixed model and a novel structural equation modeling (SEM) method that allows estimation of both components and factors were used to estimate the joint effects of cognitive phenotypes polygenic scores (PGSs), familial and neighborhood socioeconomic status (SES), and supportive environment on NIH Toolbox cognitive intelligence and PLEs. We adjusted for ethnicity (genetically defined), schizophrenia PGS, and additionally unobserved confounders (using computational confound modeling). Our findings indicate that lower cognitive intelligence and higher PLEs are significantly associated with lower PGSs for cognitive phenotypes, lower familial SES, lower neighborhood SES, and less supportive environments. Specifically, cognitive intelligence mediates the effects of these factors on PLEs, with supportive parenting and positive school environments showing the strongest impact on reducing PLEs. This study underscores the influence of genetic and environmental factors on PLEs through their effects on cognitive intelligence. Our findings have policy implications in that improving school and family environments and promoting local economic development may enhance cognitive and mental health in children.

Childhood is a critical period for brain development. Difficult experiences during this developmental phase may contribute to reduced intelligence and poorer mental health later in life. Genetics and environmental factors also play roles. For example, having family support or a higher family income has been linked to better brain health outcomes for children. Delusions or hallucinations, or other psychotic-like experiences during childhood, are linked with poor mental health later in life. Children who experience psychotic-like episodes between the ages of nine and eleven have a higher risk of developing schizophrenia or related conditions. Environmental circumstances during childhood also appear to play a crucial role in shaping the risk of schizophrenia or related conditions. Park, Lee et al. show that positive parenting and supportive school and neighborhood environments boost child intelligence and mental health. In the experiments, Park, Lee et al. analyzed data on 6,602 children to determine how genetics and environmental factors shaped their intelligence and mental health. The models show that children with higher intelligence have a lower risk of psychosis. Both genetics and supportive environments contribute to higher intelligence. Complex interactions between biology and social factors shape children's intelligence and mental health. Beneficial genetics and coming from a family with more financial resources are helpful. Yet, social environments, such as having parents who use positive child-rearing practices, or having supportive schools or neighborhoods, have protective effects that can offset other disadvantages. Policies that help parents, encourage supportive school environments, and strengthen neighborhoods may boost children's intelligence and mental health later in life.

Relative bioavailability of generic and branded 250-mg and 500-mg oral chlorphenesin carbamate tablets in healthy Korean volunteers: a single-dose, randomized-sequence, open-label, two-period crossover trial.

BACKGROUND: Chlorphenesin carbamate is a skeletal muscle relaxant approved in Korea for use in the treatment of pain and discomfort related to skeletal muscle trauma and inflammation. OBJECTIVE: The aim of this study was to assess the bioequivalence of a generic formulation of chlorphenesin carbamate at doses of 250 and 500 mg and 2 branded formulations of the same doses in healthy Korean adults. METHODS: This single-dose, randomized-sequence, open-label, 2-period crossover study was conducted in healthy Korean male and female volunteers. Subjects were assigned to receive, in a randomized sequence, a single dose of the generic (test) and branded (reference) formulations of chlorphenesin carbamate at a dose of 250 or 500 mg. Blood samples were drawn at 0, 0.33, 0.67, 1, 1.5, 2, 3, 4, 6, 9, 12, and 15 hours after administration. Pharmacokinetic properties (C(max), T(max), AUC(0-t) AUC(0-infinity), t(1/2), and ke) were determined using HPLC. The formulations were to be considered bioequivalent if the 90% CIs of the treatment ratios of the geometric means of C(max) and AUC(0-t) were within a predetermined range of log 0.80 to log 1.25 based on regulatory criteria. Tolerability was assessed by monitoring for adverse events (AEs) on physical examination and/or e-mail and personal interview at the beginning and end of each study period. RESULTS: Twenty-eight subjects (22 men, 6 women) received chlorphenesin carbamate at the 250-mg dose, and 24 male subjects received the 500-mg dose. The mean (SD) ages of the subjects were 24.0 (2.6) and 24.0 (1.9) years in the 250- and 500-mg groups, respectively. No significant differences were found between the test and reference formulations (90% CIs: C(max), 1.0048-1.1153 with the 250-mg dose and 0.9630-1.1189 with the 500-mg dose; AUC(0-t), 0.9882-1.0546 and 0.9842-1.0578, respectively). No clinically significant AEs (upper gastric pain, abdominal bloating, pyrexia, edema, nausea, heartburn, constipation, headache, dizziness, drowsiness, or fatigue) were reported throughout the study. CONCLUSION: In this single-dose study in these healthy Korean subjects, the generic and branded formulations of chlorphenesin carbamate 250 and 500 mg met the regulatory criteria for bioequivalence. All formulations were well tolerated.