Studying phenotypic and genetic characteristics of age at onset (AAO) and polarity at onset (PAO) in bipolar disorder can provide new insights into disease pathology and facilitate the development of screening tools.

To examine the genetic architecture of AAO and PAO and their association with bipolar disorder disease characteristics.

Genome-wide association studies (GWASs) and polygenic score (PGS) analyses of AAO (n = 12 977) and PAO (n = 6773) were conducted in patients with bipolar disorder from 34 cohorts and a replication sample (n = 2237). The association of onset with disease characteristics was investigated in two of these cohorts.

Earlier AAO was associated with a higher probability of psychotic symptoms, suicidality, lower educational attainment, not living together and fewer episodes. Depressive onset correlated with suicidality and manic onset correlated with delusions and manic episodes. Systematic differences in AAO between cohorts and continents of origin were observed. This was also reflected in single-nucleotide variant-based heritability estimates, with higher heritabilities for stricter onset definitions. Increased PGS for autism spectrum disorder (β = −0.34 years, s.e. = 0.08), major depression (β = −0.34 years, s.e. = 0.08), schizophrenia (β = −0.39 years, s.e. = 0.08), and educational attainment (β = −0.31 years, s.e. = 0.08) were associated with an earlier AAO. The AAO GWAS identified one significant locus, but this finding did not replicate. Neither GWAS nor PGS analyses yielded significant associations with PAO.

AAO and PAO are associated with indicators of bipolar disorder severity. Individuals with an earlier onset show an increased polygenic liability for a broad spectrum of psychiatric traits. Systematic differences in AAO across cohorts, continents and phenotype definitions introduce significant heterogeneity, affecting analyses.

As Ireland confronts the many challenges of broadening the introduction of early intervention services (EIS) for first episode psychosis (FEP) as national policy, this article describes Carepath for Overcoming Psychosis Early (COPE), the EIS of Cavan–Monaghan Mental Health Service, and presents prospective research findings during its first 5 years of operation.

COPE was launched as a rural EIS with an embedded research protocol in early 2012, following an education programme for general practitioners (GPs). Here, operational activities are documented and research findings presented through to late 2016.

During this period, 115 instances of FEP were incepted into COPE, 70.4% via their GP and 29.6% via the Emergency Department. The annual rate of inception was 24.8/100,000 of population aged > 15 years and was 2.1-fold more common among men than women. Mean duration of untreated psychosis was 5.7 months and median time from first psychotic presentation to initiation of antipsychotic treatment was zero days. Assessments of psychopathology, neuropsychology, neurology, premorbid functioning, quality of life, insight, and functionality compared across 10 DSM-IV psychotic diagnoses made at six months following presentation indicated minimal differences between them, other than more prominent negative symptoms in schizophrenia and more prominent mania in bipolar disorder.

COPE illustrates the actuality of introducing and the challenges of operating a rural EIS for FEP. Prospective follow-up studies of the 5-year COPE cohort should inform on the effectiveness of this EIS model in relation to long-term outcome in psychotic illness across what appear to be arbitrary diagnostic boundaries at FEP.

In clinical and translational research, data science is often and fortuitously integrated with data collection. This contrasts to the typical position of data scientists in other settings, where they are isolated from data collectors. Because of this, effective use of data science techniques to resolve translational questions requires innovation in the organization and management of these data.

We propose an operational framework that respects this important difference in how research teams are organized. To maximize the accuracy and speed of the clinical and translational data science enterprise under this framework, we define a set of eight best practices for data management.

In our own work at the University of Rochester, we have strived to utilize these practices in a customized version of the open source LabKey platform for integrated data management and collaboration. We have applied this platform to cohorts that longitudinally track multidomain data from over 3000 subjects.

We argue that this has made analytical datasets more readily available and lowered the bar to interdisciplinary collaboration, enabling a team-based data science that is unique to the clinical and translational setting.

Background Attention-deficit/hyperactivity disorder (ADHD) is among the most common psychiatric disorders of childhood that often persists into adulthood and old age. Yet ADHD is currently underdiagnosed and undertreated in many European countries, leading to chronicity of symptoms and impairment, due to lack of, or ineffective treatment, and higher costs of illness.

Methods The European Network Adult ADHD and the Section for Neurodevelopmental Disorders Across the Lifespan (NDAL) of the European Psychiatric Association (EPA), aim to increase awareness and knowledge of adult ADHD in and outside Europe. This Updated European Consensus Statement aims to support clinicians with research evidence and clinical experience from 63 experts of European and other countries in which ADHD in adults is recognized and treated.

Results Besides reviewing the latest research on prevalence, persistence, genetics and neurobiology of ADHD, three major questions are addressed: (1) What is the clinical picture of ADHD in adults? (2) How should ADHD be properly diagnosed in adults? (3) How should adult ADHDbe effectively treated?

Conclusions ADHD often presents as a lifelong impairing condition. The stigma surrounding ADHD, mainly due to lack of knowledge, increases the suffering of patients. Education on the lifespan perspective, diagnostic assessment, and treatment of ADHD must increase for students of general and mental health, and for psychiatry professionals. Instruments for screening and diagnosis of ADHD in adults are available, as are effective evidence-based treatments for ADHD and its negative outcomes. More research is needed on gender differences, and in older adults with ADHD.

Our understanding of the complex relationship between schizophrenia symptomatology and etiological factors can be improved by studying brain-based correlates of schizophrenia. Research showed that impairments in value processing and executive functioning, which have been associated with prefrontal brain areas [particularly the medial orbitofrontal cortex (MOFC)], are linked to negative symptoms. Here we tested the hypothesis that MOFC thickness is associated with negative symptom severity.

This study included 1985 individuals with schizophrenia from 17 research groups around the world contributing to the ENIGMA Schizophrenia Working Group. Cortical thickness values were obtained from T1-weighted structural brain scans using FreeSurfer. A meta-analysis across sites was conducted over effect sizes from a model predicting cortical thickness by negative symptom score (harmonized Scale for the Assessment of Negative Symptoms or Positive and Negative Syndrome Scale scores).

Meta-analytical results showed that left, but not right, MOFC thickness was significantly associated with negative symptom severity (βstd = −0.075; p = 0.019) after accounting for age, gender, and site. This effect remained significant (p = 0.036) in a model including overall illness severity. Covarying for duration of illness, age of onset, antipsychotic medication or handedness weakened the association of negative symptoms with left MOFC thickness. As part of a secondary analysis including 10 other prefrontal regions further associations in the left lateral orbitofrontal gyrus and pars opercularis emerged.

Using an unusually large cohort and a meta-analytical approach, our findings point towards a link between prefrontal thinning and negative symptom severity in schizophrenia. This finding provides further insight into the relationship between structural brain abnormalities and negative symptoms in schizophrenia.

DSM-5 proposes an Attenuated Psychosis Syndrome (APS) for further investigation, based upon the Attenuated Positive Symptom Syndrome (APSS) in the Structured Interview for Psychosis-Risk Syndromes (SIPS). SIPS Unusual Thought Content, Disorganized Communication and Total Disorganization scores predicted progression to psychosis in a 2015 NAPLS-2 Consortium report. We sought to independently replicate this in a large single-site high-risk cohort, and identify baseline demographic and clinical predictors beyond current APS/APSS criteria.

We prospectively studied 200 participants meeting criteria for both the SIPS APSS and DSM-5 APS. SIPS scores, demographics, family history of psychosis, DSM Axis-I diagnoses, schizotypy, and social and role functioning were assessed at baseline, with follow-up every 3 months for 2 years.

The conversion rate was 30% (n = 60), or 37.7% excluding participants who were followed under 2 years. This rate was stable across time. Conversion time averaged 7.97 months for 60% who developed schizophrenia and 15.68 for other psychoses. Mean conversion age was 20.3 for males and 23.5 for females. Attenuated odd ideas and thought disorder appear to be the positive symptoms which best predict psychosis in a logistic regression. Total negative symptom score, Asian/Pacific Islander and Black/African-American race were also predictive. As no Axis-I diagnosis or schizotypy predicted conversion, the APS is supported as a distinct syndrome. In addition, cannabis use disorder did not increase risk of conversion to psychosis.

NAPLS SIPS findings were replicated while controlling for clinical and demographic factors, strongly supporting the validity of the SIPS APSS and DSM-5 APS diagnosis.

Identifying youth who may engage in future substance use could facilitate early identification of substance use disorder vulnerability. We aimed to identify biomarkers that predicted future substance use in psychiatrically un-well youth.

LASSO regression for variable selection was used to predict substance use 24.3 months after neuroimaging assessment in 73 behaviorally and emotionally dysregulated youth aged 13.9 (s.d. = 2.0) years, 30 female, from three clinical sites in the Longitudinal Assessment of Manic Symptoms (LAMS) study. Predictor variables included neural activity during a reward task, cortical thickness, and clinical and demographic variables.

Future substance use was associated with higher left middle prefrontal cortex activity, lower left ventral anterior insula activity, thicker caudal anterior cingulate cortex, higher depression and lower mania scores, not using antipsychotic medication, more parental stress, older age. This combination of variables explained 60.4% of the variance in future substance use, and accurately classified 83.6%.

These variables explained a large proportion of the variance, were useful classifiers of future substance use, and showed the value of combining multiple domains to provide a comprehensive understanding of substance use development. This may be a step toward identifying neural measures that can identify future substance use disorder risk, and act as targets for therapeutic interventions.

Social functioning (SF) difficulties are ubiquitous among individuals at clinical high risk for psychosis (CHR), but it is not yet clear why. One possibility is suggested by the observation that effective SF requires adaptive emotion awareness and regulation. Previous reports have documented deficits in emotion awareness and regulation in individuals with schizophrenia, and have shown that such deficits predicted SF. However, it is unknown whether these deficits are present prior to the onset of psychosis or whether they are linked to SF in CHR individuals.

We conducted a cross-sectional comparison of emotion awareness and regulation in 54 individuals at CHR, 87 with schizophrenia and 50 healthy controls (HC). Then, within the CHR group, we examined links between emotion awareness, emotion regulation and SF as indexed by the Global Functioning Scale: Social (Cornblatt et al. 2007).

Group comparisons indicated significant differences between HC and the two clinical groups in their ability to identify and describe feelings, as well as the use of suppression and reappraisal emotion-regulation strategies. Specifically, the CHR and schizophrenia groups displayed comparable deficits in all domains of emotion awareness and emotion regulation. A hierarchical multiple regression analysis indicated that difficulties describing feelings accounted for 23.2% of the SF variance.

The results indicate that CHR individuals display substantial emotion awareness and emotion-regulation deficits, at severity comparable with those observed in individuals with schizophrenia. Such deficits, in particular difficulties describing feelings, predate the onset of psychosis and contribute significantly to poor SF in this population.

Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).

For investigating familiality, we used 691 families with 2–5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.

Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.

AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.