Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.

We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.

We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).

Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.

Freezing of gait (FoG) in Parkinson’s disease (PD) has been associated with response inhibition. However, the relationship between response inhibition, neural dysfunction, and PD remains unclear. We assessed response inhibition and microstructural integrity of brain regions involved in response inhibition [right hemisphere inferior frontal cortex (IFC), bilateral pre-supplementary motor areas (preSMA), and subthalamic nuclei (STN)] in PD subjects with and without FoG and elderly controls.

Twenty-one people with PD and FoG (PD-FoG), 18 without FoG (PD-noFoG), and 19 age-matched controls (HC) completed a Stop-Signal Task (SST) and MRI scan. Probabilistic fiber tractography assessed structural integrity (fractional anisotropy, FA) among IFC, preSMA, and STN regions.

Stop-signal performance did not differ between PD and HC, nor between PD-FoG and PD-noFoG. Differences in white matter integrity were observed across groups (.001 < p < .064), but were restricted to PD versus HC groups; no differences in FA were observed between PD-FoG and PD-noFoG (p > .096). Interestingly, worse FoG was associated with higher (better) mean FA in the r-preSMA, (β = .547, p = .015). Microstructural integrity of the r-IFC, r-preSMA, and r-STN tracts correlated with stop-signal performance in HC (p ≤ .019), but not people with PD.

These results do not support inefficient response inhibition in PD-FoG. Those with PD exhibited white matter loss in the response inhibition network, but this was not associated with FoG, nor with response inhibition deficits, suggesting FoG-specific neural changes may occur outside the response inhibition network. As shown previously, white matter loss was associated with response inhibition in elderly controls, suggesting PD may disturb this relationship.

Family-based treatment (FBT) is an efficacious intervention for adolescents with an eating disorder. Evaluated to a lesser degree among adolescents, enhanced cognitive-behavior therapy (CBT-E) has shown promising results. This study compared the relative effectiveness of FBT and CBT-E, and as per manualized CBT-E, the sample was divided into a lower weight [<90% median body mass index (mBMI)], and higher weight cohort (⩾90%mBMI).

Participants (N = 97) aged 12–18 years, with a DSM-5 eating disorder diagnosis (largely restrictive, excluding Avoidant Restrictive Food Intake Disorder), and their parents, chose between FBT and CBT-E. Assessments were administered at baseline, end-of-treatment (EOT), and follow-up (6 and 12 months). Treatment comprised of 20 sessions over 6 months, except for the lower weight cohort where CBT-E comprised 40 sessions over 9–12 months. Primary outcomes were slope of weight gain and change in Eating Disorder Examination (EDE) Global Score at EOT.

Slope of weight gain at EOT was significantly higher for FBT than for CBT-E (lower weight, est. = 0.597, s.e. = 0.096, p < 0.001; higher weight, est. = 0.495, s.e. = 0.83, p < 0.001), but not at follow-up. There were no differences in the EDE Global Score or most secondary outcome measures at any time-point. Several baseline variables emerged as potential treatment effect moderators at EOT. Choosing between FBT and CBT-E resulted in older and less well participants opting for CBT-E.

Results underscore the efficiency of FBT to facilitate weight gain among underweight adolescents. FBT and CBT-E achieved similar outcomes in other domains assessed, making CBT-E a viable treatment for adolescents with an eating disorder.

Treatment Outcome in Eating Disorders; https://clinicaltrials.gov/; NCT03599921.

Previous studies showed that replacing conventional flattened beams (FF) with flattening filter-free (FFF) beams improves the therapeutic ratio in lung stereotactic body radiation therapy (SBRT), but these findings could have been impacted by dose calculation uncertainties caused by the heterogeneity of the thoracic anatomy and by respiratory motion, which were particularly high for target coverage. In this study, we minimised such uncertainties by calculating doses using high-spatial-resolution Monte Carlo and four-dimensional computed tomography (4DCT) images. We aimed to evaluate more reliably the benefits of using FFF beams for lung SBRT.

For a cohort of 15 patients with early-stage lung cancer that we investigated in a previous treatment planning study, we recalculated dose distributions with Monte Carlo using 4DCT images. This included 15 FF and 15 FFF treatment plans.

Compared to Monte Carlo, the treatment planning system (TPS) over-predicted doses in low-dose regions of the planning target volume (PTV). For most patients, replacing FF beams with FFF beams improved target coverage, tumour control, and uncomplicated tumour control probabilities.

Monte Carlo tends to reveal deficiencies in target coverage compared to coverage predicted by the TPS. Our data support previously reported benefits of using FFF beams for lung SBRT.

The aim of this study was to investigate the extent to which lung stereotactic body radiotherapy (SBRT) treatment plans can be improved by replacing conventional flattening filter (FF) beams with flattening filter-free (FFF) beams.

We selected 15 patients who had received SBRT with conventional 6-MV photon beams for early-stage lung cancer. We imported the patients’ treatment plans into the Eclipse 13·6 treatment planning system, in which we configured the AAA dose calculation model using representative beam data for a TrueBeam accelerator operated in 6-MV FFF mode. We then created new treatment plans by replacing the conventional FF beams in the original plans with FFF beams.

The FFF plans had better target coverage than the original FF plans did. For the planning target volume, FFF plans significantly improved the D98, D95, D90, homogeneity index and uncomplicated tumour control probability. In most cases, the doses to organs at risk were lower in FFF plans. FFF plans significantly reduced the mean lung dose, V10, V20, V30, and normal tissue complication probability for the total lung and improved the dosimetric indices for the ipsilateral lung. For most patients, FFF beams achieved lower maximum doses to the oesophagus, heart and the spinal cord, and a lower chest wall V30.

Compared with FF beams, FFF beams achieved lower doses to organs at risk, especially the lung, without compromising tumour coverage; in fact, FFF beams improved coverage in most cases. Thus, replacing FF beams with FFF beams can achieve a better therapeutic ratio.

While negative affect reliably predicts binge eating, it is unknown how this association may decrease or ‘de-couple’ during treatment for binge eating disorder (BED), whether such change is greater in treatments targeting emotion regulation, or how such change predicts outcome. This study utilized multi-wave ecological momentary assessment (EMA) to assess changes in the momentary association between negative affect and subsequent binge-eating symptoms during Integrative Cognitive Affective Therapy (ICAT-BED) and Cognitive Behavior Therapy Guided Self-Help (CBTgsh). It was predicted that there would be stronger de-coupling effects in ICAT-BED compared to CBTgsh given the focus on emotion regulation skills in ICAT-BED and that greater de-coupling would predict outcomes.

Adults with BED were randomized to ICAT-BED or CBTgsh and completed 1-week EMA protocols and the Eating Disorder Examination (EDE) at pre-treatment, end-of-treatment, and 6-month follow-up (final N = 78). De-coupling was operationalized as a change in momentary associations between negative affect and binge-eating symptoms from pre-treatment to end-of-treatment.

There was a significant de-coupling effect at follow-up but not end-of-treatment, and de-coupling did not differ between ICAT-BED and CBTgsh. Less de-coupling was associated with higher end-of-treatment EDE global scores at end-of-treatment and higher binge frequency at follow-up.

Both ICAT-BED and CBTgsh were associated with de-coupling of momentary negative affect and binge-eating symptoms, which in turn relate to cognitive and behavioral treatment outcomes. Future research is warranted to identify differential mechanisms of change across ICAT-BED and CBTgsh. Results also highlight the importance of developing momentary interventions to more effectively de-couple negative affect and binge eating.

Developing empirically sound measures for social cognition is a key step in improving the factors that contribute to deficits in social functioning in schizophrenia. Investigating the psychometric properties and acceptability of social cognitive instruments may contribute to identification of a reliable and valid instrument for schizophrenia patients.

To investigate the psychometric properties and acceptability of a dynamic social cognition scale (DSCB) compared to three common social cognition instruments in schizophrenia.

41 patients with schizophrenia were evaluated to assess acceptability, internal consistency and validity of five social cognition measures: DSCB, Emotion Recognition-40 (ER-40), Facial Emotion Identification Task (FEIT), Tone Matching Task and MSCEIT. Multiple linear regressions were conducted to identify variables which perform well as social cognition determinants.

The DSCB and FEIT showed good acceptability, evidenced by shorter administration time, completion and patient preference for the DSCB. Good levels of internal consistency were found for the DSCB (α = 0.851), ER-40 (α = 0.803), and FEIT (α = 0.782). Confirmatory Factor Analysis indicated sufficient to good model fit. The DSCB and the ER-40 demonstrated a good model fit. The correlations for the DSCB were significant for the ER-40 (r = 0.512) and FEIT (r = 0.500).

Findings suggest that DSCB is the preferred instrument to evaluate social cognition, due to its dynamic nature and short administration time. Further research is needed to develop and improve these measurements. Additionally, the DSCB, FEIT and ER-40 show adequate to good reliability and validity.

Psychiatric disorders, including eating disorders (EDs), have clinical outcomes that range widely in severity and chronicity. The ability to predict such outcomes is extremely limited. Machine-learning (ML) approaches that model complexity may optimize the prediction of multifaceted psychiatric behaviors. However, the investigations of many psychiatric concerns have not capitalized on ML to improve prognosis. This study conducted the first comparison of an ML approach (elastic net regularized logistic regression) to traditional regression to longitudinally predict ED outcomes.

Females with heterogeneous ED diagnoses completed demographic and psychiatric assessments at baseline (n = 415) and Year 1 (n = 320) and 2 (n = 277) follow-ups. Elastic net and traditional logistic regression models comprising the same baseline variables were compared in ability to longitudinally predict ED diagnosis, binge eating, compensatory behavior, and underweight BMI at Years 1 and 2.

Elastic net models had higher accuracy for all outcomes at Years 1 and 2 [average Area Under the Receiving Operating Characteristics Curve (AUC) = 0.78] compared to logistic regression (average AUC = 0.67). Model performance did not deteriorate when the most important predictor was removed or an alternative ML algorithm (random forests) was applied. Baseline ED (e.g. diagnosis), psychiatric (e.g. hospitalization), and demographic (e.g. ethnicity) characteristics emerged as important predictors in exploratory predictor importance analyses.

ML algorithms can enhance the prediction of ED symptoms for 2 years and may identify important risk markers. The superior accuracy of ML for predicting complex outcomes suggests that these approaches may ultimately aid in advancing precision medicine for serious psychiatric disorders.

The Psychiatric Genomics Consortium (PGC) has made major advances in the molecular etiology of MDD, confirming that MDD is highly polygenic. Pathway enrichment results from PGC meta-analyses can also be used to help inform molecular drug targets. Prior to any knowledge of molecular biomarkers for MDD, drugs targeting molecular pathways (MPs) proved successful in treating MDD. It is possible that examining polygenicity within specific MPs implicated in MDD can further refine molecular drug targets.

Using a large case–control GWAS based on low-coverage whole genome sequencing (N = 10 640) in Han Chinese women, we derived polygenic risk scores (PRS) for MDD and for MDD specific to each of over 300 MPs previously shown to be relevant to psychiatric diagnoses. We then identified sets of PRSs, accounting for critical covariates, significantly predictive of case status.

Over and above global MDD polygenic risk, polygenic risk within the GO: 0017144 drug metabolism pathway significantly predicted recurrent depression after multiple testing correction. Secondary transcriptomic analysis suggests that among genes in this pathway, CYP2C19 (family of Cytochrome P450) and CBR1 (Carbonyl Reductase 1) might be most relevant to MDD. Within the cases, pathway-based risk was additionally associated with age at onset of MDD.

Results indicate that pathway-based risk might inform etiology of recurrent major depression. Future research should examine whether polygenicity of the drug metabolism gene pathway has any association with clinical presentation or treatment response. We discuss limitations to the generalizability of these preliminary findings, and urge replication in future research.

Few studies have investigated the patterns of posttraumatic stress disorder (PTSD) symptom change in prolonged exposure (PE) therapy. In this study, we aimed to understand the patterns of PTSD symptom change in both PE and present-centered therapy (PCT).

Participants were active duty military personnel (N = 326, 89.3% male, 61.2% white, 32.5 years old) randomized to spaced-PE (S-PE; 10 sessions over 8 weeks), PCT (10 sessions over 8 weeks), or massed-PE (M-PE; 10 sessions over 2 weeks). Using latent profile analysis, we determined the optimal number of PTSD symptom change classes over time and analyzed whether baseline and follow-up variables were associated with class membership.

Five classes, namely rapid responder (7–17%), steep linear responder (14–22%), gradual responder (30–34%), non-responder (27–33%), and symptom exacerbation (7–13%) classes, characterized each treatment. No baseline clinical characteristics predicted class membership for S-PE and M-PE; in PCT, more negative baseline trauma cognitions predicted membership in the non-responder v. gradual responder class. Class membership was robustly associated with PTSD, trauma cognitions, and depression up to 6 months after treatment for both S-PE and M-PE but not for PCT.

Distinct profiles of treatment response emerged that were similar across interventions. By and large, no baseline variables predicted responder class. Responder status was a strong predictor of future symptom severity for PE, whereas response to PCT was not as strongly associated with future symptoms.