Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.

Macroscopic cortical networks are important for cognitive function, but it remains challenging to construct anatomically plausible individual structural connectomes from human neuroimaging. We introduce a new technique for cortical network mapping based on inter-regional similarity of multiple morphometric parameters measured using multimodal MRI. In three cohorts (two human, one macaque), we find that the resulting morphometric similarity networks (MSNs) have a complex topological organization comprising modules and high-degree hubs. Human MSN modules recapitulate known cortical cytoarchitectonic divisions, and greater inter-regional morphometric similarity was associated with stronger inter-regional co-expression of genes enriched for neuronal terms. Comparing macaque MSNs with tract-tracing data confirmed that morphometric similarity was related to axonal connectivity. Finally, variation in the degree of human MSN nodes accounted for about 40% of between-subject variability in IQ. Morphometric similarity mapping provides a novel, robust, and biologically plausible approach to understanding how human cortical networks underpin individual differences in psychological functions.

Background Cannabis use is associated with increased risk of later psychotic disorder but whether it affects incidence of the disorder remains unclear. We aimed to identify patterns of cannabis use with the strongest effect on odds of psychotic disorder across Europe and explore whether differences in such patterns contribute to variations in the incidence rates of psychotic disorder. Methods We included patients aged 18-64 years who presented to psychiatric services in 11 sites across Europe and Brazil with first-episode psychosis and recruited controls representative of the local populations. We applied adjusted logistic regression models to the data to estimate which patterns of cannabis use carried the highest odds for psychotic disorder. Using Europe-wide and national data on the expected concentration of Δ⁹-tetrahydrocannabinol (THC) in the different types of cannabis available across the sites, we divided the types of cannabis used by participants into two categories: low potency (THC <10%) and high potency (THC ≥10%). Assuming causality, we calculated the population attributable fractions (PAFs) for the patterns of cannabis use associated with the highest odds of psychosis and the correlation between such patterns and the incidence rates for psychotic disorder across the study sites. Findings Between May 1, 2010, and April 1, 2015, we obtained data from 901 patients with first-episode psychosis across 11 sites and 1237 population controls from those same sites. Daily cannabis use was associated with increased odds of psychotic disorder compared with never users (adjusted odds ratio [OR] 3•2, 95% CI 2•2-4•1), increasing to nearly five-times increased odds for daily use of high-potency types of cannabis (4•8, 2•5-6•3). The PAFs calculated indicated that if high-potency cannabis were no longer available, 12•2% (95% CI 3•0-16•1) of cases of first-episode psychosis could be prevented across the 11 sites, rising to 30•3% (15•2-40•0) in London and 50•3% (27•4-66•0) in Amsterdam. The adjusted incident rates for psychotic disorder were positively correlated with the prevalence in controls across the 11 sites of use of high-potency cannabis (r = 0•7; p=0•0286) and daily use (r = 0•8; p=0•0109). Interpretation Differences in frequency of daily cannabis use and in use of high-potency cannabis contributed to the striking variation in the incidence of psychotic disorder across the 11 studied sites. Given the increasing availability of high-potency cannabis, this has important implications for public health.

Objective:  To describe the development and validation of the Clinical Global Impression–Schizophrenia (CGI‐SCH) scale, designed to assess positive, negative, depressive and cognitive symptoms in schizophrenia. Method:  The CGI‐SCH scale was adapted from the CGI scale. Concurrent validity and sensitivity to change were assessed by comparison with the Positive and Negative Symptom Severity (PANSS) and Global Assessment of Functioning (GAF) scales. To evaluate inter‐rater reliability, all patients were assessed by two clinicians. Results:  Symptoms were assessed in 114 patients. Correlation coefficients between the CGI‐SCH and the GAF and PANSS scores were high (most above 0.75), and were highest for positive and negative symptoms. Reliability was substantial (intraclass correlation coefficient, ICC > 0.70) in all but one dimension (depressive dimension, ICC = 0.64). Conclusion:  The CGI‐SCH scale is a valid, reliable instrument to evaluate severity and treatment response in schizophrenia. Given its simplicity, brevity and clinical face validity, the scale is appropriate for use in observational studies and routine clinical practice.

Background. The incidence of schizophrenia in the African-Caribbean population in England is reported to be raised. We sought to clarify whether (a) the rates of other psychotic disorders are increased, (b) whether psychosis is increased in other ethnic minority groups, and (c) whether particular age or gender groups are especially at risk.

Assessing and analysing individual differences in change over time is of central scientific importance to developmental neuroscience. However, the literature is based largely on cross-sectional comparisons, which reflect a variety of influences and cannot directly represent change. We advocate using latent change score (LCS) models in longitudinal samples as a statistical framework to tease apart the complex processes underlying lifespan development in brain and behaviour using longitudinal data. LCS models provide a flexible framework that naturally accommodates key developmental questions as model parameters and can even be used, with some limitations, in cases with only two measurement occasions. We illustrate the use of LCS models with two empirical examples. In a lifespan cognitive training study (COGITO, N = 204 (N = 32 imaging) on two waves) we observe correlated change in brain and behaviour in the context of a high-intensity training intervention. In an adolescent development cohort (NSPN, N = 176, two waves) we find greater variability in cortical thinning in males than in females. To facilitate the adoption of LCS by the developmental community, we provide analysis code that can be adapted by other researchers and basic primers in two freely available SEM software packages (lavaan and Ωnyx).

BackgroundPeripheral low-grade inflammation in depression is increasingly seen as a therapeutic target. We aimed to establish the prevalence of low-grade inflammation in depression, using different C-reactive protein (CRP) levels, through a systematic literature review and meta-analysis.MethodsWe searched the PubMed database from its inception to July 2018, and selected studies that assessed depression using a validated tool/scale, and allowed the calculation of the proportion of patients with low-grade inflammation (CRP >3 mg/L) or elevated CRP (>1 mg/L).ResultsAfter quality assessment, 37 studies comprising 13 541 depressed patients and 155 728 controls were included. Based on the meta-analysis of 30 studies, the prevalence of low-grade inflammation (CRP >3 mg/L) in depression was 27% (95% CI 21–34%); this prevalence was not associated with sample source (inpatient, outpatient or population-based), antidepressant treatment, participant age, BMI or ethnicity. Based on the meta-analysis of 17 studies of depression and matched healthy controls, the odds ratio for low-grade inflammation in depression was 1.46 (95% CI 1.22–1.75). The prevalence of elevated CRP (>1 mg/L) in depression was 58% (95% CI 47–69%), and the meta-analytic odds ratio for elevated CRP in depression compared with controls was 1.47 (95% CI 1.18–1.82).ConclusionsAbout a quarter of patients with depression show evidence of low-grade inflammation, and over half of patients show mildly elevated CRP levels. There are significant differences in the prevalence of low-grade inflammation between patients and matched healthy controls. These findings suggest that inflammation could be relevant to a large number of patients with depression.

SummaryBackgroundThe rising number of young people going to university has led to concerns about an increasing demand for student mental health services. We aimed to assess whether provision of mindfulness courses to university students would improve their resilience to stress.MethodsWe did this pragmatic randomised controlled trial at the University of Cambridge, UK. Students aged 18 years or older with no severe mental illness or crisis (self-assessed) were randomly assigned (1:1), via remote survey software using computer-generated random numbers, to receive either an 8 week mindfulness course adapted for university students (Mindfulness Skills for Students [MSS]) plus mental health support as usual, or mental health support as usual alone. Participants and the study management team were aware of group allocation, but allocation was concealed from the researchers, outcome assessors, and study statistician. The primary outcome was self-reported psychological distress during the examination period, as measured with the Clinical Outcomes in Routine Evaluation Outcome Measure (CORE–OM), with higher scores indicating more distress. The primary analysis was by intention to treat. This trial is registered with the Australia and New Zealand Clinical Trials Registry, number ACTRN12615001160527.FindingsBetween Sept 28, 2015, and Jan 15, 2016, we randomly assigned 616 students to the MSS group (n=309) or the support as usual group (n=307). 453 (74%) participants completed the CORE–OM during the examination period and 182 (59%) MSS participants completed at least half of the course. MSS reduced distress scores during the examination period compared with support as usual, with mean CORE–OM scores of 0·87 (SD 0·50) in 237 MSS participants versus 1·11 (0·57) in 216 support as usual participants (adjusted mean difference –0·14, 95% CI –0·22 to –0·06; p=0·001), showing a moderate effect size (β –0·44, 95% CI –0·60 to –0·29; p<0·0001). 123 (57%) of 214 participants in the support as usual group had distress scores above an accepted clinical threshold compared with 88 (37%) of 235 participants in the MSS group. On average, six students (95% CI four to ten) needed to be offered the MSS course to prevent one from experiencing clinical levels of distress. No participants had adverse reactions related to self-harm, suicidality, or harm to others.InterpretationOur findings show that provision of mindfulness training could be an effective component of a wider student mental health strategy. Further comparative effectiveness research with inclusion of controls for non-specific effects is needed to define a range of additional, effective interventions to increase resilience to stress in university students.FundingUniversity of Cambridge and National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care East of England.