Despite a wide range of proposed risk factors and theoretical models, prediction of eating disorder (ED) onset remains poor. This study undertook the first comparison of two machine learning (ML) approaches [penalised logistic regression (LASSO), and prediction rule ensembles (PREs)] to conventional logistic regression (LR) models to enhance prediction of ED onset and differential ED diagnoses from a range of putative risk factors.

Data were part of a European Project and comprised 1402 participants, 642 ED patients [52% with anorexia nervosa (AN) and 40% with bulimia nervosa (BN)] and 760 controls. The Cross-Cultural Risk Factor Questionnaire, which assesses retrospectively a range of sociocultural and psychological ED risk factors occurring before the age of 12 years (46 predictors in total), was used.

All three statistical approaches had satisfactory model accuracy, with an average area under the curve (AUC) of 86% for predicting ED onset and 70% for predicting AN v. BN. Predictive performance was greatest for the two regression methods (LR and LASSO), although the PRE technique relied on fewer predictors with comparable accuracy. The individual risk factors differed depending on the outcome classification (EDs v. non-EDs and AN v. BN).

Even though the conventional LR performed comparably to the ML approaches in terms of predictive accuracy, the ML methods produced more parsimonious predictive models. ML approaches offer a viable way to modify screening practices for ED risk that balance accuracy against participant burden.

To stop transmission of hepatitis B virus (HBV) and hepatitis C virus (HCV) infections in association with myocardial perfusion imaging (MPI) at a cardiology clinic.

Outbreak investigation and quasispecies analysis of HCV hypervariable region 1 genome.

Outpatient cardiology clinic.

Patients undergoing MPI.

Case patients met definitions for HBV or HCV infection. Cases were identified through surveillance registry cross-matching against clinic records and serological screening. Observations of clinic practices were performed.

During 2012–2014, 7 cases of HCV and 4 cases of HBV occurred in 4 distinct clusters among patients at a cardiology clinic. Among 3 case patients with HCV infection who had MPI on June 25, 2014, 2 had 98.48% genetic identity of HCV RNA. Among 4 case patients with HCV infection who had MPI on March 13, 2014, 3 had 96.96%–99.24% molecular identity of HCV RNA. Also, 2 clusters of 2 patients each with HBV infection had MPI on March 7, 2012, and December 4, 2014. Clinic staff reused saline vials for >1 patient. No infection control breaches were identified at the compounding pharmacy that supplied the clinic. Patients seen in clinic through March 27, 2015, were encouraged to seek testing for HBV, HCV, and human immunodeficiency virus. The clinic switched to all single-dose medications and single-use intravenous flushes on March 27, 2015, and no further cases were identified.

This prolonged healthcare-associated outbreak of HBV and HCV was most likely related to breaches in injection safety. Providers should follow injection safety guidelines in all practice settings.

Gene × environment (G × E) interactions in eating pathology have been increasingly investigated, however studies have been limited by sample size due to the difficulty of obtaining genetic data.

To synthesize existing G × E research in the eating disorders (ED) field and provide a clear picture of the current state of knowledge with analyses of larger samples.

Complete data from seven studies investigating community (n = 1750, 64.5% female) and clinical (n = 426, 100% female) populations, identified via systematic review, were included. Data were combined to perform five analyses: 5-HTTLPR × Traumatic Life Events (0–17 events) to predict ED status (n = 909), 5-HTTLPR × Sexual and Physical Abuse (n = 1097) to predict bulimic symptoms, 5-HTLPR × Depression to predict bulimic symptoms (n = 1256), and 5-HTTLPR × Impulsivity to predict disordered eating (n = 1149).

The low function (s) allele of 5-HTTLPR interacted with number of traumatic life events (P < .01) and sexual and physical abuse (P < .05) to predict increased likelihood of an ED in females but not males (Fig. 1). No other G × E interactions were significant, possibly due to the medium to low compatibility between datasets (Fig. 1).

Early promising results suggest that increased knowledge of G × E interactions could be achieved if studies increased uniformity of measuring ED and environmental variables, allowing for continued collaboration to overcome the restrictions of obtaining genetic samples.

The authors have not supplied their declaration of competing interest.

Cognitive deficits in schizophrenia have major functional impacts. Modafinil is a cognitive enhancer whose effect in healthy volunteers is well-described, but whose effects on the cognitive deficits of schizophrenia appear to be inconsistent. Two possible reasons for this are that cognitive test batteries vary in their sensitivity, or that the phase of illness may be important, with patients early in their illness responding better.

A double-blind, randomised, placebo-controlled single-dose crossover study of modafinil 200 mg examined this with two cognitive batteries [MATRICS Consensus Cognitive Battery (MCCB) and Cambridge Neuropsychological Test Automated Battery (CANTAB)] in 46 participants with under 3 years’ duration of DSM-IV schizophrenia, on stable antipsychotic medication. In parallel, the same design was used in 28 age-, sex-, and education-matched healthy volunteers. Uncorrected p values were calculated using mixed effects models.

In patients, modafinil significantly improved CANTAB Paired Associate Learning, non-significantly improved efficiency and significantly slowed performance of the CANTAB Stockings of Cambridge spatial planning task. There was no significant effect on any MCCB domain. In healthy volunteers, modafinil significantly increased CANTAB Rapid Visual Processing, Intra-Extra Dimensional Set Shifting and verbal recall accuracy, and MCCB social cognition performance. The only significant differences between groups were in MCCB visual learning.

As in earlier chronic schizophrenia studies, modafinil failed to produce changes in cognition in early psychosis as measured by MCCB. CANTAB proved more sensitive to the effects of modafinil in participants with early schizophrenia and in healthy volunteers. This confirms the importance of selecting the appropriate test battery in treatment studies of cognition in schizophrenia.

Alterations in gray matter (GM) are commonly observed in schizophrenia. Accumulating studies suggest that the brain changes associated with schizophrenia are distributed rather than focal, involving interconnected networks of areas as opposed to single regions. In the current study we aimed to explore GM volume (GMV) changes in a relatively large sample of treatment-naive first-episode schizophrenia (FES) patients using optimized voxel-based morphometry (VBM) and covariation analysis.

High-resolution T1-weighted images were obtained using 3.0-T magnetic resonance imaging (MRI) from 86 first-episode drug-naive patients with schizophrenia and 86 age- and gender-matched healthy volunteers. Symptom severity was evaluated using the Positive and Negative Syndrome Scale (PANSS). GMV was assessed using optimized VBM and in 16 regions of interest (ROIs), selected on the basis of a previous meta-analysis. The relationships between GMVs in the ROIs were examined using an analysis of covariance (ANCOVA).

The VBM analysis revealed that first-episode patients showed reduced GMV in the hippocampus bilaterally. The ROI analysis identified reductions in GMV in the left inferior frontal gyrus, bilateral hippocampus and right thalamus. The ANCOVA revealed different patterns of regional GMV correlations in patients and controls, including of inter- and intra-insula, inter-amygdala and insula–postcentral gyrus connections.

Schizophrenia involves regional reductions in GMV and changes in GMV covariance in the insula, amygdala and postcentral gyrus. These findings were evident at the onset of the disorder, before treatment, and therefore cannot be attributable to the effects of chronic illness progression or medication.

It is not clear whether the progressive changes in brain microstructural deficits documented in previous longitudinal magnetic resonance imaging (MRI) studies might be due to the disease process or to other factors such as medication. It is important to explore the longitudinal alterations in white-matter (WM) microstructure in antipsychotic-naive patients with first-episode schizophrenia during the very early phase of treatment when relatively ‘free’ from chronicity.

Thirty-five patients with first-episode schizophrenia and 22 healthy volunteers were recruited. High-resolution diffusion tensor imaging (DTI) was obtained from participants at baseline and after 6 weeks of treatment. A ‘difference map’ for each individual was calculated from the 6-week follow-up fractional anisotropy (FA) of DTI minus the baseline FA. Differences in Positive and Negative Syndrome Scale (PANSS) scores and Global Assessment of Functioning (GAF) scores between baseline and 6 weeks were also evaluated and expressed as a 6-week/baseline ratio.

Compared to healthy controls, there was a significant decrease in absolute FA of WM around the bilateral anterior cingulate gyrus and the right anterior corona radiata of the frontal lobe in first-episode drug-naive patients with schizophrenia following 6 weeks of treatment. Clinical symptoms improved during this period but the change in FA did not correlate with the changes in clinical symptoms or the dose of antipsychotic medication.

During the early phase of treatment, there is an acute reduction in WM FA that may be due to the effects of antipsychotic medications. However, it is not possible to entirely exclude the effects of underlying progression of illness.

Evidence shows that cognitive deficits and white matter (WM) dysconnectivity can independently be associated with clinical manifestations in schizophrenia. It is important to explore this triadic relationship in order to investigate whether the triplet could serve as potential extended endophenotypes of schizophrenia.

Diffusion tensor images and clinical performances were evaluated in 122 individuals with first-episode schizophrenia and 122 age- and gender-matched controls. In addition, 65 of 122 of the patient group and 40 of 122 controls were measured using intelligence quotient (IQ) testing.

The schizophrenia group showed lower fractional anisotropy (FA) values than controls in the right cerebral frontal lobar sub-gyral (RFSG) WM. The schizophrenia group also showed a significant positive correlation between FA in the RFSG and performance IQ (PIQ); in turn, their PIQ score showed a significant negative correlation with negative syndromes.

Overall, these findings support the hypothesis that WM deficits may be a core deficit that contributes to cognitive deficits as well as to negative symptoms.

Brain structure appears to alter after antipsychotic administration, but it is unknown whether these alterations are associated with improvement of psychopathology in patients with schizophrenia. In this study, the authors explore this relationship.

Altogether, 66 first-episode, drug-naive patients with schizophrenia and 23 well-matched healthy controls underwent brain magnetic resonance imaging scans at baseline. All 23 healthy controls and 42 of the patients were rescanned after 6 weeks follow-up. The patients received regular antipsychotic treatment during the 6-week period and their psychopathology was assessed using the Positive and Negative Syndrome Scale (PANSS) at baseline and 6 weeks. The difference in PANSS scores between baseline and 6 weeks was expressed as a ratio of the scores at baseline – ‘PANSS reduction ratio’. A modified tensor-based morphometry procedure was applied to analyse longitudinal images. Correlations between regional volume changes, PANSS reduction ratio and antipsychotic drug dosages were explored.

Compared with healthy controls, there was a significant increase in grey-matter volume of the right putamen in patients after 6 weeks treatment. This volume change was positively correlated with a positive PANSS reduction score but not related to drug dosages.

Putaminal volume increased after 6 weeks antipsychotic treatment in first-episode schizophrenia. The increased volume was closely correlated with improved psychopathology, suggesting the putamen might be a biomarker to predict the treatment response in schizophrenia.

Abnormalities in the connectivity of white-matter (WM) tracts in schizophrenia are supported by evidence from post-mortem investigations, functional and structural magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI). The aims of this study were to explore the microstructural changes in first-episode schizophrenia in a Han Chinese population and to investigate whether a family history of psychiatric disorder is related to the severity of WM tract integrity abnormalities in these patients.

T1-weighted MR and DT images were collected in 68 patients with first-episode schizophrenia [22 with a positive family history (PFH) and 46 with a negative family history (NFH)] and 100 healthy controls. Voxel-based analysis was performed and WM integrity was quantified by fractional anisotropy (FA). Cluster- and voxel-level analyses were performed by using two-sample t tests between patients and controls and/or using a full factorial model with one factor and three levels among the three sample groups (patients with PFH or NFH, and controls), as appropriate.

FA deficits were observed in the patient group, especially in the left temporal lobe and right corpus callosum. This effect was more severe in the non-familial schizophrenia than in the familial schizophrenia subgroup.

Overall, these findings support the hypothesis that loss of WM integrity may be an important pathophysiological feature of schizophrenia, with particular implications for brain dysmaturation in non-familial and familial schizophrenia.

Psychiatric phenotypes are currently defined according to sets of descriptive criteria. Although many of these phenotypes are heritable, it would be useful to know whether any of the various diagnostic categories in current use identify cases that are particularly helpful for biological–genetic research.

To use genome-wide genetic association data to explore the relative genetic utility of seven different descriptive operational diagnostic categories relevant to bipolar illness within a large UK case–control bipolar disorder sample.

We analysed our previously published Wellcome Trust Case Control Consortium (WTCCC) bipolar disorder genome-wide association data-set, comprising 1868 individuals with bipolar disorder and 2938 controls genotyped for 276 122 single nucleotide polymorphisms (SNPs) that met stringent criteria for genotype quality. For each SNP we performed a test of association (bipolar disorder group v. control group) and used the number of associated independent SNPs statistically significant atP<0.00001 as a metric for the overall genetic signal in the sample. We next compared this metric with that obtained using each of seven diagnostic subsets of the group with bipolar disorder: Research Diagnostic Criteria (RDC): bipolar I disorder; manic disorder; bipolar II disorder; schizoaffective disorder, bipolar type; DSM–IV: bipolar I disorder; bipolar II disorder; schizoaffective disorder, bipolar type.

The RDC schizoaffective disorder, bipolar type (v. controls) stood out from the other diagnostic subsets as having a significant excess of independent association signals (P<0.003) compared with that expected in samples of the same size selected randomly from the total bipolar disorder group data-set. The strongest association in this subset of participants with bipolar disorder was at rs4818065 (P = 2.42 ×10–7). Biological systems implicated included gamma amniobutyric acid (GABA)A receptors. Genes having at least one associated polymorphism at P<10–4 includedB3GALTS, A2BP1, GABRB1, AUTS2, BSN, PTPRG, GIRK2 andCDH12.

Our findings show that individuals with broadly defined bipolar schizoaffective features have either a particularly strong genetic contribution or that, as a group, are genetically more homogeneous than the other phenotypes tested. The results point to the importance of using diagnostic approaches that recognise this group of individuals. Our approach can be applied to similar data-sets for other psychiatric and non-psychiatric phenotypes.