Differences in schizophrenia treatments by race and ethnicity-analysis of electronic health records.

Racial disparities in prescriptions of anti-psychotics have been highlighted before. However, (i) the evidence on other medications, including anti-depressant or mood stabilizing medications is lacking, and (ii) the role of potentially confounding factors and (iii) specificity of such disparities to schizophrenia (SCZ), are still unknown. We used electronic health records (EHRs) from 224,212 adults to estimate the odds ratios of receiving a prescription for different nervous system medications among patients with SCZ of different race/ethnicity, and analogous linear models to investigate differences in prescribed medication doses.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates.

Genome-wide analysis of a model-derived binge eating disorder phenotype identifies risk loci and implicates iron metabolism.

Binge eating disorder (BED) is the most common eating disorder, yet its genetic architecture remains largely unknown. Studying BED is challenging because it is often comorbid with obesity, a common and highly polygenic trait, and it is underdiagnosed in biobank data sets. To address this limitation, we apply a supervised machine-learning approach (using 822 cases of individuals diagnosed with BED) to estimate the probability of each individual having BED based on electronic medical records from the Million Veteran Program.

Systematic evaluation of machine learning algorithms for neuroanatomically-based age prediction in youth.

Application of machine learning (ML) algorithms to structural magnetic resonance imaging (sMRI) data has yielded behaviorally meaningful estimates of the biological age of the brain (brain-age). The choice of the ML approach in estimating brain-age in youth is important because age-related brain changes in this age-group are dynamic. However, the comparative performance of the available ML algorithms has not been systematically appraised.

Accelerated Global and Local Brain Aging Differentiate Cognitively Impaired From Cognitively Spared Patients With Schizophrenia.

Background: Accelerated aging has been proposed as a mechanism underlying the clinical and cognitive presentation of schizophrenia. The current study extends the field by examining both global and regional patterns of brain aging in schizophrenia, as inferred from brain structural data, and their association with cognitive and psychotic symptoms.

Methods: Global and local brain-age-gap-estimates (G-brainAGE and L-brainAGE) were computed using a U-Net Model from T-weighted structural neuroimaging data from 84 patients (aged 16-35 years) with early-stage schizophrenia (illness duration <5 years) and 1,169 healthy individuals (aged 16-37 years).

Sex differences in predictors and regional patterns of brain age gap estimates.

The brain-age-gap estimate (brainAGE) quantifies the difference between chronological age and age predicted by applying machine-learning models to neuroimaging data and is considered a biomarker of brain health. Understanding sex differences in brainAGE is a significant step toward precision medicine. Global and local brainAGE (G-brainAGE and L-brainAGE, respectively) were computed by applying machine learning algorithms to brain structural magnetic resonance imaging data from 1113 healthy young adults (54.

Evidence of discontinuity between psychosis-risk and non-clinical samples in the neuroanatomical correlates of social function.

Objective: Social dysfunction is a major feature of clinical-high-risk states for psychosis (CHR-P). Prior research has identified a neuroanatomical pattern associated with impaired social function outcome in CHR-P. The aim of the current study was to test whether social dysfunction in CHR-P is neurobiologically distinct or in a continuum with the lower end of the normal distribution of individual differences in social functioning.

Neural signatures of data-driven psychopathology dimensions at the transition to adolescence.

Background: One of the challenges in human neuroscience is to uncover associations between brain organization and psychopathology in order to better understand the biological underpinnings of mental disorders. Here, we aimed to characterize the neural correlates of psychopathology dimensions obtained using two conceptually different data-driven approaches.

Methods: Dimensions of psychopathology that were either maximally dissociable or correlated were respectively extracted by independent component analysis (ICA) and exploratory factor analysis (EFA) applied to the Childhood Behavior Checklist items from 9- to 10-year-olds (n = 9983; 47.

Hippocampal volume reduction is associated with direct measure of insulin resistance in adults.

Hippocampal integrity is highly susceptible to metabolic dysfunction, yet its mechanisms are not well defined. We studied 126 healthy individuals aged 23-61 years. Insulin resistance (IR) was quantified by measuring steady-state plasma glucose (SSPG) concentration during the insulin suppression test.

Impact of opioid agonist treatment on mental health in patients with opioid use disorder: a systematic review and network meta-analysis of randomized clinical trials.

: There is a knowledge gap in systematic reviews on the impact of opioid agonist treatments on mental health.: We compared mental health outcomes between different opioid agonist treatments and placebo/waitlist, and between the different opioids themselves.: This meta-analysis of randomized clinical trials (RCTs) was pre-registered at PROSPERO (CRD42018109375).

Cortical thickness across the lifespan: Data from 17,075 healthy individuals aged 3-90 years.

Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3-90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness.

Subcortical volumes across the lifespan: Data from 18,605 healthy individuals aged 3-90 years.

Age has a major effect on brain volume. However, the normative studies available are constrained by small sample sizes, restricted age coverage and significant methodological variability. These limitations introduce inconsistencies and may obscure or distort the lifespan trajectories of brain morphometry.

Personalized Estimates of Brain Structural Variability in Individuals With Early Psychosis.

Background: Early psychosis in first-episode psychosis (FEP) and clinical high-risk (CHR) individuals has been associated with alterations in mean regional measures of brain morphology. Examination of variability in brain morphology could assist in quantifying the degree of brain structural heterogeneity in clinical relative to healthy control (HC) samples.

Methods: Structural magnetic resonance imaging data were obtained from CHR (n = 71), FEP (n = 72), and HC individuals (n = 55).

Multivariate Patterns of Brain-Behavior-Environment Associations in the Adolescent Brain and Cognitive Development Study.

Background: Adolescence is a critical developmental stage. A key challenge is to characterize how variation in adolescent brain organization relates to psychosocial and environmental influences.

Methods: We used canonical correlation analysis to discover distinct patterns of covariation between measures of brain organization (brain morphometry, intracortical myelination, white matter integrity, and resting-state functional connectivity) and individual, psychosocial, and environmental factors in a nationally representative U.

Linked patterns of biological and environmental covariation with brain structure in adolescence: a population-based longitudinal study.

Adolescence is a period of major brain reorganization shaped by biologically timed and by environmental factors. We sought to discover linked patterns of covariation between brain structural development and a wide array of these factors by leveraging data from the IMAGEN study, a longitudinal population-based cohort of adolescents. Brain structural measures and a comprehensive array of non-imaging features (relating to demographic, anthropometric, and psychosocial characteristics) were available on 1476 IMAGEN participants aged 14 years and from a subsample reassessed at age 19 years (n = 714).

Parsing out the role of dopamine D4 receptor gene (DRD4) on alcohol-related phenotypes: A meta-analysis and systematic review.

Genetics account for moderate variation of individual differences in developing alcohol use disorder (AUD), but it is unclear which genetic variations contribute to AUD risk. One candidate gene investigated due to its association with AUD is the dopamine D4 receptor gene (DRD4), which contains a 48-base pair variable number tandem repeat (VNTR) in exon 3 of its coding region. To date, no quantitative synthesis of the published literature on the effects of DRD4 VNTR variation on alcohol-related phenotypes has been conducted.

Hemorrhage, Seizures, and Dynamic Changes of Familial versus Nonfamilial Cavernous Malformation: Systematic Review and Meta-analysis.

Background: Cerebral cavernous malformations (CCMs) may be familial or nonfamilial. This systematic review compared the natural history of CCMs in familial compared with nonfamilial cases.

Methods: We searched MEDLINE, Web of Science, and EMBASE for natural history studies on CCMs up to September 2018.

Parental Age and Differential Estimates of Risk for Neuropsychiatric Disorders: Findings From the Danish Birth Cohort.

Objective: Parental age at birth has been shown to affect the rates of a range of neurodevelopmental disorders, but the understanding of the mechanisms through which it mediates different outcomes is still lacking. A population-based cohort was used to assess differential effects of parental age on estimates of risk across pediatric-onset neuropsychiatric disorders: autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), and Tourette's disorder/chronic tic disorder (TD/CT).

Method: The study cohort included all singleton births in Denmark from 1980 through 2007 with full information on parental ages (N = 1,490,745) and was followed through December 31, 2013.

Apgar score and risk of autism.

Low Apgar score has been associated with higher risk for several neurological and psychiatric disorders, including cerebral palsy and intellectual disability. Studies of the association between Apgar score and autism spectrum disorder (ASD) have been inconsistent. We aimed to investigate (1) the association between low Apgar score at 5 min and risk for ASD, and (2) the modifying effects of gestational age and sex on this association in the largest multinational database of ASD.

Environmental risk factors for autism: an evidence-based review of systematic reviews and meta-analyses.

Background: According to recent evidence, up to 40-50% of variance in autism spectrum disorder (ASD) liability might be determined by environmental factors. In the present paper, we conducted a review of systematic reviews and meta-analyses of environmental risk factors for ASD. We assessed each review for quality of evidence and provided a brief overview of putative mechanisms of environmental risk factors for ASD.

Prenatal Maternal Smoking and Increased Risk for Tourette Syndrome and Chronic Tic Disorders.

Objective: We assessed the role of prenatal maternal smoking in risk for Tourette syndrome and chronic tic disorder (TS/CT) and pediatric-onset obsessive-compulsive disorder (OCD).

Method: In an analysis of 73,073 singleton pregnancies from the Danish National Birth Cohort, we calculated incidence rates (IR) per 1,000 person-year for TS/CT and OCD. We then determined crude and adjusted hazard ratios and 95% CIs associated with prenatal maternal smoking, considering smoking as a dichotomous (yes/no) variable or a stratified variable (no smoking, light smoking, and heavy smoking [≥10 cigarettes/day]).

Attentional bias towards and away from fearful faces is modulated by developmental amygdala damage.

The amygdala is believed to play a major role in orienting attention towards threat-related stimuli. However, behavioral studies on amygdala-damaged patients have given inconsistent results-variously reporting decreased, persisted, and increased attention towards threat. Here we aimed to characterize the impact of developmental amygdala damage on emotion perception and the nature and time-course of spatial attentional bias towards fearful faces.

Natural history of cavernous malformation: Systematic review and meta-analysis of 25 studies.

Objective: We pooled the results of studies on natural history of cavernous malformations (CM) to calculate point estimates and investigate main sources of heterogeneity.

Methods: We searched MEDLINE, EMBASE, and ISI Web of Science for relevant studies published before May 2015. We used fixed or random effects models and meta-regression to pool the data.

Environmental exposure to metals, neurodevelopment, and psychosis.

Purpose Of Review: This article presents a new hypothesis about the possible relation between early life exposure to metals and psychosis. We review limitations of available research, and discuss novel approaches to overcome previous methodological barriers.

Recent Findings: Mechanistic studies suggest a possible association between excess lead, manganese, cadmium, arsenic, or copper, and zinc deficiency, and several biochemical disturbances related to psychosis, such as altered neurotransmitters levels, excitotoxicity, and inflammation.

Impaired Gas Exchange at Birth and Risk of Intellectual Disability and Autism: A Meta-analysis.

We conducted meta-analyses of 67 studies on the association between neonatal proxies of impaired gas exchange and intellectual disability (ID) or autism spectrum disorders (ASD). Neonatal acidosis was associated with an odds ratio (OR) of 3.55 [95 % confidence interval (95 % CI) 2.